Research Projects

The following projects are representative of the types of research projects assigned to CEE research assistants (RAs). Not all of the projects on this list will require an RA for the next term, and not all of the research projects in the department are listed, but the list does provide a good indication of the types of research RAs perform.

If you are a prospective or recently admitted student and you are interested in a project, please contact the faculty member directly to get more information about his/her available research projects or visit that faculty member's website to learn more.

Environmental Chemistry
Environmental Fluid Mechanics and Coastal Engineering
Environmental Microbiology
Geotechnical Engineering, Geomechanics and Geotechnology
Hydrology and Hydroclimatology
Infrastructure Systems
Mechanics of Materials and Structures
Transportation Systems

Environmental Chemistry

Professor Philip Gschwend
Demonstrating LDPE Passive Samplers for Assessing Contaminated Sediments

The overall objective is to demonstrate that the polyethylene (PE) passive sampling methodology is a commercially viable technology for determining horizontal and vertical distributions of chemicals like PCBs and PAHs in sediments. To this end, our specific objectives include: (a) demonstrating the accuracy of the PE passive sampling method used in the field (i.e., in situ), (b) demonstrating the advantages of using PE passive sampling for defining the horizontal and vertical extent of contamination, (c) showing the PE passive sampling is well suited to long term monitoring programs (LTM), and (d) establishing not only the performance capabilities (limits of detection, accuracy, precision), but also the cost benefits of this passive sampling approach as compared to traditional sampling and analysis methods.

Professor Philip Gschwend
Estimating Black Carbon-Water Sorption Coefficients of Organic Contaminants in Sediments

In order to improve our fundamental understandings of chemical sorption to real world sediments, we need to elucidate the role of black carbon(s) (e.g., soots, chars, coal dust) in these deposits. Such BC sorption greatly reduces the bioavailability of a wide range of organic contaminants. This improved understanding will have a several important impacts including: (a) improved understanding and modeling of bioavailability when site managers are using sediment concentration data, (b) enhanced means to use and interpret passive samplers when assessing wide arrays of target compounds using only a few performance reference compounds, (c) insights to kinetic limitations associated with phenomena like contaminant desorption from resuspended sediments, (d) an ability to pre-judge the sorption of a far more diverse array of organic contaminants and (e) more accurate expectations for risk reduction associated with remedial efforts since BC sorption exhibits nonlinear behavior.

Professor Philip Gschwend
Application of Passive Sampler Technology to Assess DDTs and Dieldrin Release From Superfund Site Sediments Before, During and After Remediation Activities

Our objectives are (a) to utilize and compare two passive sampler technologies, polyethylene devices (PEDs) and solid phase micro-extraction fibers (SPME), for monitoring the presence of DDTs and dieldrin emanating from contaminated soils and sediments into the waters of the Lauritzen Channel-Richmond Harbor-San Francisco Bay before, during, and after environmental remediation of the United Heckathorn site, and (b) to compare DDTs and dieldrin uptake by the passive samplers to bioaccumulation seen (by us) in field deployments using a bivalve and in laboratory tests using a bivalve and an amphipod and to fish collected in the area (as reported by others).

Professor Philip Gschwend
Remediation Using Novel Magnetic Sorbents and Magnetically-Enhanced Separation Methods

We seek to develop novel nano-materials and devices which will facilitate accurate and cost-effective delineation of the spatial extent of contamination in sediments of concern. In this project we will focus on the in situ accurate determination of the local activity of the contaminants and then of the development of strategies to remove these contaminant in the most non-invasive way possible.

Professor Philip Gschwend
Healthy Coastal Ecosystems: Are Sewage-Derived Steroidal Estrogens a Problem in Massachusetts Bay?

Our goals are first to identify and quantify the full suite of natural and synthetic estrogens and their conjugated and chlorinated derivatives in (a) Deer Island WWTP effluent and (b) the receiving waters and sediments of Massachusetts Bay. We hypothesize that past observations have greatly underestimated the environmental dosing with estrogens because conjugated and chlorinated derivatives were not assessed. Second, we seek to develop quantitative tools, ranging from a spatially well-mixed mass budget (box model) to a 3D numerical transport and fate model for steroidal estrogens in Massachusetts Bay. This modeling effort will enable us to ascertain whether natural background estrogens and/or sources beyond the Deer Island outfall are important contributors, as well at to understand how different estrogen species (free vs conjugated vs chlorinated) respond to transport and transformation processes controlling their environmental distributions. 

Professor Philip Gschwend
A General Methodology for Evaluating Bed Sediments for Narcosis Toxicity
The objective of this project is to develop an accurate means with which to analyze the narcosis toxicity due to mixtures of hydrophobic organic compounds in sediments. Mixtures of toxic organic compounds can be accumulated from sediments in passive samplers such as those made of polyethylene. We are using two-dimensional gas chromatography with flame ionization detection analyses to, not only quantifying the components of these mixes, but also to provide the necessary weighting information needed to calculate phospholipid-normalized body burdens for organisms equilibrated within the original sediments.

Associate Professor Colette L. Heald
Satellite-based Investigations of Atmospheric Composition

Space-based observations provide large-scale and continuous insight into the emissions and transport of atmospherically relevant trace gases and particles. These observations are key to investigating the evolution of the atmosphere, particularly over poorly observed regions (e.g. the remote oceans). Research in our group addresses two primary topics: (1) the Intercontinental Transport of Pollution and (2) Using Remote Observations to Improve Emission Estimates. Graduate student research can be designed to address aspects of these topics.  

Associate Professor Colette L. Heald
Investigating Atmospheric Aerosol Sources, Composition and Chemistry

Aerosols are particles suspended in the atmosphere. They have both natural (e.g. dust and volcanic) and anthropogenic (e.g. vehicle emissions, industrial) sources and through their interaction with radiation can affect climate. Aerosols can also be a component of urban smog and contribute to visibility degradation. Understanding the sources, formation and transformation of aerosols in the troposphere is key to characterizing their role in climate and air pollution. Work in our group focuses on understanding the global budgets of aerosols in the atmosphere: What are their sources? How are they processed in the atmosphere? And what impact do they have? We make use of modeling and observational analysis (including the interpretation of satellite observations) to answer these questions.  

 Upcoming projects in the group will explore the following topics:

  • Investigating how the chemical transformations and mixing of black carbon (i.e. soot) in the atmosphere affect global radiative forcing.
  • Development of a new global model scheme to treat the chemical and physical transformations of organic aerosol in the atmosphere
  • Using new satellite observations and aircraft measurements to investigate the role of ammonia in particle formation in the United States.
  • Investigating composition and trends in tropical aerosols. 

Professor Harry Hemond
Real-Time In-situ AUV-Based Underwater Chemical Sensing

Capabilities for in-situ chemical sensing are increasingly necessary to obtain the improved spatiotemporal resolution essential to make advances in  the understanding and improvement of water quality. In-situ measurement also makes chemical information available quickly, allowing quick responses as necessary while obviating the need for costly sample preservation and transport. Deployment aboard AUVs (autonomous underwater vehicles), particularly in concert with underwater data networks, further multiplies the potential benefits of in-situ chemical measurement. This work builds on our invention of the cycloidal underwater mass spectrometer (such as used to monitor the recent Gulf oil spill) and now also includes research into optical sensors for nonvolatile compounds and electrochemical sensors for ionic measurement. Current collaborators include Dr. K. Ng at SMART and Prof. J. Sinfield at Purdue.

Professor Harry Hemond
Methane Geochemistry of Stratified Lakes

Freshwater lakes are believed to be significant, but poorly quantified, sources of the greenhouse gas methane to the atmosphere. Methane is also important to the ecology of lakes, influencing both the food web and the oxidation-reduction chemistry of the waters. Current work focuses on the process of ebullition, or bubbling, which is very poorly understood and is difficult to quantify on account of its patchy and intermittent nature. An improved understanding of the interactions of microbiological methane production and consumption with the physics of organic-rich lake sediments will also lead to better models of global methane cycling and potentially to possibilities for energy harvesting.  Current collaborators include Prof. R. Juanes and Dr. C. Ruppel.

Professor Harry Hemond
The Anthrobiogeochemical Cycle of Indium

Indium is an important metal whose production is increasing dramatically due to new uses in the rapidly growing electronics, photovoltaic, and LED industries. Increases of  its usage by one or more orders of magnitude within the next few years are very possible. Yet little is known about the natural or industrial cycling of indium, and toxicological data are incomplete.  The investigation of the environmental behavior of indium focuses on current and possible future releases of indium to both the air and water environment, with a focus on the magnitudes and the chemical forms of these fluxes. Improved understanding of the anthrobiogeochemical cycle of indium will allow informed decisions about its future use, handling, and disposal.

Professor Harry Hemond
Kilowatt-Scale Solar Thermal Power Plants

Small-scale solar thermal power systems are potentially advantageous in remote power generation applications, particularly where both thermal and electric power are required.  To date these systems have only been commercialized as large scale power plants where power cycle infrastructure is borrowed from existing conventional thermal plants.  Small scale power cycles for solar thermal plants are currently not commercially available.  The organic Rankine cycle (ORC) offers significant promise for small-scale solar power generation, as heat engines based on an ORC are appropriate for converting relatively low temperature (<300 degrees C) thermal energy to electric power.  This facilitates operating at modest temperatures using relatively low cost solar collectors such as the parabolic trough mirror. Costs are also addressed by using cycle designs based on the use of modifications of  low-cost mass-produced fluid components such as are available from the HVAC industry.  This project also involves collaboration with the student-led STG (Solar Turbine Group).

Associate Professor Jesse Kroll
Atmospheric Chemistry of Organic Compounds

Organic species are emitted into the earth’s atmosphere by both natural processes (e.g., biogenic emissions) and anthropogenic ones (e.g. fossil fuel combustion).  Once in the atmosphere, organics are subject to continuous oxidation, until they are either converted to inorganic carbon (CO or CO2) or removed from the atmosphere via deposition.  These oxidative chemical transformations are of great importance in that they determine the lifetime and environmental distributions of individual pollutants, and govern the formation of secondary pollutants such as ozone and secondary organic aerosol, which in turn have major implications for human health and climate.  Work in our lab focuses on the experimental study of the oxidation reactions of atmospheric organics, using a number of complementary approaches:

  • Laboratory study of atmospheric oxidation reactions, with a particular focus on the formation and evolution of organic aerosol, and changes to organics over their entire atmospheric lifetimes;
  • Development of simple mechanistic descriptions of reactivity of generic organics, for use in atmospheric models;
  • Development of new mass spectrometric techniques for the measurement and chemical characterization of organics in the atmosphere; and
  • Participation in field studies aimed at improving our understanding of the amounts and properties of ambient atmospheric organic species.

Projects within the group involve some combination of these four approaches, with substantial flexibility in terms of specific research topic.

Environmental Fluid Mechanics and Coastal Engineering back to top back to top

Professor Ole Madsen
Surf Zone Hydrodynamics and Sediment Transport

Understanding processes in the surf zone, where waves are breaking or broken, is critically important to coastal engineering. The dissipation of wave energy through breaking results in a reduction of wave momentum (so-called "radiation stresses") and thereby in wave-induced currents (longshore and cross-shore currents). Breaking waves also give rise to turbulence in the water column and in the thin bottom boundary layer. The latter dislodges bottom sediments and make these available for transport by the wave-induced currents. In this project, we are working with a numerical model that is capable of predicting the characteristics of breaking and broken waves, the resulting wave-induced currents and the associated sediment transport. Research centers on the improvement and generalization of this surf zone model, all components of which are in need of improvement. For example, (1) waves are treated as simple periodic disturbances with a simple correction accounting for the effects of narrow-banded spectral waves; (2) the model predicts both longshore currents and sediment transport quite accurately, but only for alongshore uniform beaches; and (3) cross-shore currents are reasonably well-predicted but the associated cross-shore transport of sediment is not. This project falls within the purview of the Singapore-MIT Alliance for Research and Technology, so research assistants may have the chance to spend time working in Singapore.

Professor Ole Madsen
Development of a Large-Scale Sediment Transport Model

Large-scale numerical coastal and ocean circulation models do not resolve motion of the scale of wind-waves. Nevertheless, slowly varying currents experience an enhanced bottom frictional resistance due to interaction with short period wind-waves. This enhanced (so-called "apparent") roughness is the appropriate one to use in large-scale circulation models, and the development of an efficient way to incorporate the apparent roughness in circulation models is one goal of this research. Another is to explore the effect of short period wind-waves in the mechanics of sediment transport in coastal waters. The bottom shear stress associated with short period wind-waves dislodges bottom sediment and makes it available for transport by slowly varying currents, which in the absence of the wind-waves would have been incapable of dislodging a single sediment grain. Thus, the effect of wind-waves needs to be formulated, parameterized and incorporated in large-scale numerical ocean and coastal circulation models. This project falls within the purview of the Singapore-MIT Alliance for Research and Technology, so research assistants may have the chance to spend time working in Singapore.

Professor Ole Madsen
Fundamental Experimental Research on Wave-Current-Sediment Interaction

As part of the Singapore-MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling, a unique experimental facility for wave-current-sediment interaction will be designed, constructed and operated in the Hydraulics Laboratory at the National University of Singapore. This facility will be able to reproduce field scale wave motions (velocities >1.5 m/s, periods >10 s) and should be available for use by fall 2009. The new facility will be similar to the large oscillating wave tunnel facility in Delft, Netherlands, and researchers will be able to use it to investigate a variety of fundamental aspects of sediment-fluid interaction in wave-dominated coastal waters. Initial experiments (1) on the influence of bottom slope on sediment transport rates by waves alone; (2) on the movable roughness of wave-rippled beds; and (3) on sediment transport rates by asymmetric and/or skewed waves, representative of waves in the surf zone, may be conducted by a research assistant whose home department is Civil and Environmental Engineering at MIT.

Professor Heidi Nepf
Sediment Transport in Vegetated Channels
The most obvious impact of vegetation in river channels is an increase in flow resistance and a reduction in conveyance capacity, so that for many years vegetation has been removed from channels to accelerate the passage of peak flows. However, vegetation has a positive influence on water quality, e.g. by removing nutrients and producing oxygen in stagnant regions. By baffling the flow and reducing bed-stress, vegetation creates regions of sediment retention and enhances channel stability. Because of these positive impacts, researchers now advocate the restoration of channel vegetation. However, the design of sustainable restoration schemes requires an understanding of how the distribution and density of vegetation determines sediment transport and the tendency toward deposition or erosion. These two projects will use laboratory studies to describe the interaction between vegetation, water motion, and sediment transport.   

  1. In the co-evolution of vegetation and channel morphology, we need to understand how individual patches of vegetation grow spatially and eventually merge with other regions of vegetation. The goal would be to understand how the patch size, shape and spacing to other patches impacts the flow around and in between the patches, and in turn impacts the potential for the patches to grow or diminish.
  2. Vegetation changes the scale and intensity of near bed turbulence.  The change in turbulence structure is believed to change the potential for sediment transport, but the role of turbulence in sediment transport is still not well understood. Most previous models link sediment transport to the mean bed stress. In this study, you will observe how the presence of vegetation changes the mean bed stress, as well as the nature of near bed turbulence. The goal is to derive a new parameterization for sediment motion within regions of vegetation, and to determine the relative role of mean bed stress and near bed turbulence. 

Professor Heidi Nepf
Nutrient Uptake by Aquatic Vegetation
Seagrass and freshwater macrophytes enhance water quality by filtering nutrients from the water, reducing re-suspension, and producing oxygen in stagnant regions. The global impact of these ecosystem services has been valued at over one trillion dollars per year. Unlike terrestrial plants, which acquire nutrients through their roots, aquatic plants acquire nutrients through their leaves and blades from the surrounding water. The nutrient uptake controls the growth of the vegetation, as well as its potential impact on water quality. This project will use laboratory experiments to examine how the interaction of individual blades with current and waves impacts the uptake potential at the blade surface, with the goal of providing better predictions of the potential maximum uptake rate for different hydrodynamic conditions. These studies feed into the larger question of how the hydrodynamic conditions at a site impact the growth of plants, the potential for restoration success, and their potential impact on carbon sequestration and primary production. 

Environmental Microbiology back to top back to top

Professor Sallie W. Chisholm
Integrative Systems Biology
The marine cyanobacterium Prochlorococcus is the smallest and most abundant photosynthetic cell on the planet. The goal of our lab is to understand this single microbe from the genome to the global scale, thereby developing the field of integrative systems biology. Work centers on the following topics:

  • The origins, nature and ecological impacts of genomic diversity among Prochlorococcus
  • The metabolic machinery of Prochlorococcus as a model for solar energy conversion
  • The role of viruses in Prochlorococcus ecology
  • The role of ecotypic variation in the dynamics and stability of the global Prochlorococcus population
  • The role of Prochlorococcus in ocean food webs and biogeochemistry

Research assistants have latitude to design their own projects under this general umbrella. We use the tools of genomics, metagenomics, transcriptomics and proteomics, and we have a vast culture collection of Prochlorococcus and phage as well as the complete genome sequences of 12 Prochlorococcus strains. Regular sampling programs take place off Bermuda and Hawaii, and we participate in research cruises throughout the global oceans.

Professor Martin Polz
The Ecology and Evolution of Bacterial Populations in the Wild

Our principal model system is bacteria of the genus Vibrio co-occurring in the coastal ocean. These afford the opportunity to study a wide range of environmental adaptations since their lifestyles range from free-living to symbiotic and pathogenic. Current research addresses:

  • The genomic diversity within and between ecologically differentiated populations
  • The temporal and spatial dynamics of populations
  • The diversity and role of extrachromosomal elements (plasmids, viruses) in horizontal gene transfer
  • The selection for pathogenicity (genes) in the environment
  • The diversity and range of antagonistic interactions

Researchers use a combination of ecological, genomic and molecular genetic tools. For example, we are in the process of sequencing ~100 genomes and many more plasmids and viruses in collaboration with Professor Eric Alm's lab and the Broad Institute. Graduate students are generally free to choose their own projects as long as they fit in with the overall focus of the lab.

Associate Professor Roman Stocker
Quantifying the Role of Bacteria in Ocean's Carbon Cycle
This project focuses on obtaining quantitative information on the swimming and foraging strategies of marine microbes. Motility of microbes in the ocean has a huge influence on their ability to take up limiting elements and can affect trophic dynamics. Yet, we know very little about how microbes in the ocean swim. In this project, researchers will apply a combination of state-of-the-art experimental techniques, including microfluidics and videomicroscopy, to explore how microbes move. Microfluidics will allow us to establish carefully controlled environmental conditions, such as flow and chemical gradients. The project will be a combination of fluid mechanics and microbial ecology. It will be primarily experimental, with a strong image analysis component, and the opportunity for mathematical modeling to interpret experimental data. 

Associate Professor Roman Stocker
The Biophysics of Bacterial Oil Degradation
Bacteria are one the primary drivers of oil degradation following an oil spill in the ocean. Yet, we know very little about the biophysical mechanisms underpinning degradation and how this process unfolds at the level of the single bacterium and the single oil droplet. How and how frequently do bacteria encounter droplets? Can bacteria sense the soluble components of the oil mixture and use these chemical signals in their search for droplets? How does the size of the droplet and its rising speed affect these processes? What, ultimately, is the best size of droplet to maximize oil degradation by marine bacteria? The Stocker lab has a unique set of tools, from microfluidic systems to high-speed videomicroscopy, and expertise spanning form fluid mechanics to microbial ecology, to study the microscale interactions of marine bacteria and oil droplets, and aims in this project to (i) improve our understanding of the environmental drivers of oil spill recovery; and (ii) guide improved engineering of remediation strategies (e.g. prediction of the optimal oil droplet size). 

Associate Professor Roman Stocker
The Fluid Mechanics and Microbial Ecology of Coral Reefs
Coral reefs are one of the most diverse ecosystems on the planet. In recent decades, they have been experiencing significant decline due both to anthropogenic effects and changes in environmental stressors (e.g. temperature). One of the causative agents of coral disease are pathogenic bacteria, yet we largely ignore how bacteria find and interact with corals. Chemical signals, coming for example from the mucus lining a coral, could represent an important cue for invading bacteria, and in fact many bacterial pathogens of corals are highly motile. At the same time, corals stir the fluid layer that immediately surrounds them through a dense canopy of cilia, which affects both bacteria as well as mass transport at the coral surface. In the Stocker lab, we strive to understand the coupling of flow, ciliary action, bacterial swimming, and chemical signaling through high-resolution direct observations, achieved through a combination of microfluidic experiments, imaging and image analysis, and microsensor measurements. Our goal is to understand the fundamental mechanisms driving coral disease, with the ultimate aim of improving predictions of the state of coral reefs and management of anthropogenic influences on these precious ecosystems. 

Assistant Professor Janelle Thompson
Experimental Microbial Ecology of Marine Anthozoa

Coral tissues harbor diverse communities of microbes, and increasing evidence suggests these communities provide beneficial functions-including nutrient cycling and pathogen protection. How these microbial communities are assembled and maintained remains a central question for understanding the role of microbes in health and disease. The starlet sea anemone Nematostella vectensis is emerging as a model for animal development and evolution because the phylum Cnidaria is one of the earliest branches on the animal tree of life. In addition, N. vectensis is closely related to corals and thus is a tractable laboratory model for probing the mechanisms of disease and disease resistance in this class of globally significant organisms (i.e. the Anthozoa). We have hypothesized that N. vectensis lives in association with a microbial community that supports host health. We are currently using a combination of isolation-based and cultivation-independent methods to explore the relationship between microbial community composition and the physiology of the N. vectensis host.

Assistant Professor Janelle Thompson
Ecology of Virulence

Reports of mass mortality in natural and cultivated marine populations are increasing worldwide, and many marine diseases have suspected microbial etiologies. We are currently using a combination of genetic tools to investigate the mechanisms by which Vibrios, closely related to V. harveyi and V. parahaemolyticus, cause disease and mortality in marine invertebrates. In addition, we are exploring the alternate roles of virulence mechanisms in environmental contexts outside of the animal host.

Assistant Professor Janelle Thompson
Microbiology of Carbon Sequestration

Carbon dioxide capture and storage (CCS) is currently being implemented as a strategy to mitigate atmospheric emissions of CO2 and help stabilize atmospheric greenhouse gas concentrations. In CCS, carbon dioxide is separated and captured from an industrial process stream before being compressed and injected deep underground into geological formations (e.g. hydrocarbon or saltwater-filled (saline) reservoirs) for storage on time scales of 1,000 years or more. Natural saline formations are biologically active environments that will be profoundly changed by the injection of CO2, potentially affecting both short-term injection operations and long-term storage of CO2. Little is known about how the subsurface microbial ecosystems will affect trapping mechanisms or the operational efficiency of CO2 injection into natural saline formations. We are investigating how geological carbon sequestration affects the subsurface microbiota and the biological processes that mediate potential biogeochemical transformations of subsurface carbon dioxide.

Geotechnical Engineering, Geomechanics and Geotechnology back to top back to top

Professor Herbert H. Einstein
Rock Fracture Processes for Enhanced Geothermal Systems (EGS) with Emphasis on Induced Seismicity. 
EGS involves the stimulation of a rock mass by creating new or extending existing fractures through hydraulic fracturing.  It appears that hydraulic fracturing related to EGS involves events of greater magnitude than hydraulic fracturing for hydrocarbons.  Such events have for instance led to the stoppage of the EGS effort in Basel.  The research at MIT, funded by MITEI Seed Funds intends to investigate experimentally and theoretically what might cause such higher reported events.  This is done through:  1.  Laboratory experiments in which cracks/fractures are subjected to water pressure; 2. Analytical models representing these processes and 3. The use of moment tensor analysis to interpret events that occur in EGS projects. 

Professor Herbert H. Einstein
Rock Fracture Characterization and Fracture Mechanics

Rock mass behavior, such as slope and tunnel stability and flow through rock is strongly affected by fractures (joints). Fractured rock flow is particularly important in sustainable energy production—for example, engineered geothermal systems. This is a focal area for the MIT rock mechanics group. The major emphasis of this project is to examine how fractures propagate and coalesce through lab experiments using high-speed observation, scanning electron microscope observations and nano-identation. The experimental information will then be used to develop analytical models. This research is sponsored by the National Science Foundation and the U.S. Department of Energy. For more information, visit the Video page for a short video showing some of this work. 

Professor Herbert H. Einstein
Tunnel Design and Construction

Tunneling is one of the most expensive and uncertain civil engineering endeavors. It is, therefore, essential to quantify and explicitly consider all factors that contribute to uncertainty in cost, time and resources. Several major computer-based tools (Decision Aids for Tunneling, Decision Aids for Tunnel Exploration) have already been developed and put to use to address uncertainty. Ongoing research seeks to extend the usefulness of these tools. This project, partially supported by the MIT Portugal Program, seeks to develop a procedure that will make it possible to use experience gained from past projects, together with observations of a particular project, to update predictions about geologic/geotechnical conditions as the tunnel is constructed. The updating is done with Bayesian networks. The objective of the project is (1) to reduce the number of accidents, which can cause injury, cost money and waste time, and (2) to more accurately gauge life-cycle costs when designing a tunnel-particularly considering construction and lifetime (operational, maintenance, etc.) uncertainties. 

Professor Herbert H. Einstein
Behavior of Shales
Shales, in the widest sense, are the most common near-surface rocks.  Within the last decade, they have become of great interest in conjunction with gas and oil extraction.  Shales are also of great interest in civil engineering because of their often problematic properties (low strength – high deformability – tendency to swell).  Professor Einstein’s research in this area has been going on for 40 years, first related to civil engineering problems and then resulted recently in models representing anisotropic behavior.  The present research is related to “tight shales” in conjunction with oil and gas extraction.  In the context of the project “Low Environmental Impact Fracture Processes”, sponsored by ENI-MITEI, propagation and coalescence in shales are being investigated.  This involves both experiments and modeling, which can be based on previous research with other types of rocks.  This work will show how fractures in shales can be produced with small impact on the environment. 

Professor Herbert H. Einstein
Risk Assessment for Landslides and Other Natural Threats

Landslides, which occur when earthquakes or heavy rains loosen layers of surface soil, can cause considerable damage and are difficult to predict. This research uses a combination of hydrologic and mechanical models to form the basis for probabilistic modeling of landslides-which in turn is used in risk analysis. In parallel, a methodology based on decision making under uncertainty was and is being developed. The goal of this project is to assess the risks associated with natural threats and, in particular, the effect of countermeasures. The methodology makes use of classic Bayesian updating and Bayesian networks. 

Professor Herbert H. Einstein
Decision Analysis for EGS (Enhanced Geothermal Systems)
EGS rely on circulating water through rock fractures to extract heat and then through heat exchangers to eventually produce electricity in addition to directly useable heat. In this context, holes need to be drilled, artificial fractures created and the water circulation maintained through the lifetime of the system. Many uncertainties affect this system, and this research addresses the uncertainties related to the subsurface components.  Specifically, stochastic fracture pattern models and fracture flow models are combined to produce probabilistic flow models. In parallel, cost-time models for wells (drill holes) are developed. Finally, on the basis of the fracture flow and drill cost/time models, models will be created to predict the optimal location of the wells. The research is funded by the U.S. Department of Energy under the ARRA (American Recovery and Reinvestment Act) Program. 

Professor John R. Williams
Pore Scale Simulation For Enhanced Oil Recovery

In an oil reservoir, 20-40% of the oil can be recovered by primary development techniques. The rest remains trapped in the rock pores. Enhanced Oil Recovery (EOR) techniques, such as water flooding, gas injection, chemical injection and thermal stimulation, optimistically recover an additional 10-20% of the oil. This still leaves almost half of the oil trapped in the rock pores. The Department of Energy (DOE) has estimated that if “next generation” EOR is applied, the United States could generate an additional 240 billion barrels of recoverable oil resources - over 30 years supply at the present US consumption rate of 20 million barrels per day. For comparison, the Middle East holds an estimated 685 billion barrels that are recoverable and the tar sands of Alberta 300 billion recoverable barrels of “heavy” oil, with over a trillion barrels potentially recoverable using enhanced methods. We are researching new EOR technologies by providing understanding of the fundamental physical processes within a reservoir, particularly at the pore scale. We are developing the computational algorithms for pore scale simulation of oil reservoirs based on multi-scale, multi-physics models. The work leverages “particle” models based on a partition of unity class of techniques, including SPH and DEM.

Professor John R. Williams
Mutiscale, Multiphysics Simulation on Multicore Computers

A typical multiphysics simulation takes direct input from a microCT scan, at a resolution of some 8 billion voxels of data. Each grain of rock has a different shape and may be cemented to other grains. Furthermore, the surface properties of the grains influence the wetability of the rock/fluid system. The gas, water and oil in the pores, and the rock matrix are then subject to driving forces, mainly mechanical but also seismic, chemical and electrical. We have developed new algorithms to take advantage of shared memory multicore computers. The challenge is to be fast but also to be “thread safe”. We have shown that by tuning the task size to the hardware we can solve problems that were impossible even a few years ago.

Hydrology and Hydroclimatology back to top back to top

Professor Elfatih Eltahir
Connections of Hydrology and Malaria in Africa

The objective of this project is to develop credible numerical models that simulate the interactions of hydrologic processes and biological processes, involving mosquito populations, that lead to malaria transmission in African villages. The long-term goal is to use this new class of models to (1) predict the impact of climate change on the transmission of malaria, and (2) perform a priori testing of any environmental management intervention. The work will involve the development and application of numerical models, field campaigns for monitoring environmental conditions, as well as the use of high-resolution satellite data to characterize the water environment near African villages. A field site has been established covering two villages in Niger.
For more information:

Professor Dara Entekhabi
Satellite Estimation and Retrieval Algorithms

The objective of this project is to develop satellite multi-pass estimation and retrieval models for surface soil moisture to support the forthcoming Soil Moisture Active and Passive (SMAP) satellite mission. The goal of the mission is to make global soil moisture and freeze/thaw measurements, data essential to the accuracy of weather forecasts and predictions of global carbon cycle and climate. SMAP will use low-frequency microwave sensors to map global fields of high-resolution radar backscatter and coarse-resolution but highly accurate radiobrightness simultaneously. The anticipated performance of the algorithm will be tested using a numerical algorithm test-bed. The multi-pass estimation and retrieval is anticipated to reduce the dependence of algorithms on auxiliary information on vegetation characteristics and other parameters. We propose to develop a combined estimation-retrieval algorithm that separates the time-scales of the various contributions to the signal and to the error. The new algorithm will use the separation of time scales together with multi-pass measurements in order to estimate values for the parameters and for the errors.
For more information:

Professor Dara Entekhabi
Smart Sensing for Land Surface Applications

The proposed project addresses the topic of "smart sensing." It is motivated by a sensor-web measurement scenario including spaceborne and in-situ assets. The objective of the technology proposed is to enable a guided/adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of the spaceborne sensors with respect to resolution and accuracy. The sensor nodes are guided to perform as macro-instrument measuring processes at the scale of the satellite footprint, hence meeting the requirements for the difficult problem of validation of satellite measurements. The science measurement considered is the surface-to-depth profiles of soil moisture estimated from satellite radars and radiometers, with calibration/validation using in-situ sensors.

Professor Dara Entekhabi
Effect of Climate Change on Precipitation Extremes

This project seeks to estimate the possible changes (modeled and observationally based) in the characteristics of weather/climate extremes for a number of variables over a range of scales. However, the fidelity and spatial detail of precipitation events, and particularly the extremes, as simulated by climate models remain in question. Precipitation in climate models results from the effects of both prognostic variables and parameterized processes. The prognostic fields among different climate models are more similar than parameterized fields because they represent the solution of the same basic equations, albeit with different numerical schemes. We will use historical precipitation and atmospheric data to develop analogues for the dependence of extreme precipitation on the climate regime. The analogues will then be used to process large-scale fields as simulated by climate models with global change forcing. The anticipated result is a robust and defensible estimate of shifts in the risk of extreme precipitation and flood events. Our tested hypothesis is that large-scale atmospheric patterns as simulated by climate models can provide a more robust assessment of potential trends in precipitation-event extremes than simulated precipitation outputs alone.

Professor Dara Entekhabi
Energy Flows Between Natural and Built Environments

This project will involve measuring and modeling the interconnected flows of energy (convective and radiative) between the built and natural environments. Research will be carried out in two main areas: (1) large eddy simulation of the urban canyon environment, including physical and thermodynamic interactions involving buildings and urban land use, and (2) radiometric and photometric measurements. The project will include modeling of urban heat island effects, accounting for conduction, convective and radiative heat fluxes from buildings, urban airflows and evapotranspiration from plants.

Professor Charles Harvey
Carbon Fluxes in Peat-land Rain Forests

Peat-land rain forests in Malaysia and Indonesia store tremendous amounts of carbon in their soils. These forests are now being cut and replaced by palm-oil plantations to provide biofuel. In this project, we will quantify the rates of carbon dioxide and methane uptake and release from these tropical soils under natural conditions, and after the destruction of the forest. We will develop and deploy sensors in the soils to measure the characteristics that control carbon transformations (such as moisture content), and on towers above the forest to measure carbon exchanges with the atmosphere. We will then develop predictive models of the relevant biogeochemical processes so that these models can be employed to reduce carbon release.

Associate Professor Ruben Juanes
Multiscale Modeling and Simulation

This project focuses on modeling of coupled multiphase fluid flow and geomechanics in naturally fractured oil and gas reservoirs. It involves developing variational multiscale techniques that bypass traditional upscaling procedures. Applications include simulation of enhanced oil recovery and prediction of surface subsidence.

Associate Professor Ruben Juanes
Energy Production From Methane Hydrates

This project focuses on energy production from methane hydrates in both ocean sediments and permafrost environments. It involves modeling, at the grain scale, the mechanisms of gas migration, fracture initiation and propagation, and hydrate formation and dissociation. Emphasis is on identifying the dominant mechanism for regional (and global) assessment of the hydrate energy resource, and its role in methane fluxes into the ocean and the atmosphere, as well as the implications for viable production strategies.

Associate Professor Ruben Juanes
Continuum Models of Unstable Multiphase Flow in Porous Media
This research will develop new multiphase flow equations to capture well-known instabilities (viscous fingering, gravity fingering) that current equations are unable to reproduce. Applications include water infiltration into dry soils and enhanced oil recovery by gas injection. (This project is heavy on mathematics and numerics.)

Professor Dennis McLaughlin
Data Assimilation for Chaotic Systems

In this project, we will consider methods for combining model predictions and measurements for chaotic systems such as the atmosphere and ocean. Chaotic systems are characterized by rapid growth of small changes in system variables. This makes the system's behavior difficult to predict unless the diverging variables are frequently updated with measurements. The procedures used to perform measurement updates for environmental applications are generally based on linear assumptions that are not compatible with the nonlinear dynamics of chaotic systems. This project examines some new estimation methods that may be able to provide better characterization and forecasting capabilities for chaotic environmental systems.

Professor Dennis McLaughlin
Real-Time Control for Petroleum Applications

This project considers the problem of designing control strategies for increasing oil and gas recovery in petroleum reservoirs. The reservoir control problem is complicated by the large uncertainty in subsurface geological properties that control the flow of water, oil and gas in the subsurface. This project will focus on the development of robust control strategies that recognize the role of geological uncertainty and explicitly consider connections between control decisions and property estimation.

Professor Dennis McLaughlin
Implications of Climate Change for Food Production in China

China currently depends almost entirely on domestically grown food. This project uses an integrated agricultural-hydrologic model to examine the connections between natural resources (land and water) and food production in China. Previous work has quantified these connections for present climate conditions. The new project will examine the implications of climate change, including both long-term regional trends and inter-annual variability in precipitation and temperature. This project has significant public policy implications but is primarily focused on better understanding relevant hydrologic factors.
For more information:

Professor Dennis McLaughlin
Feature-Based Data Assimilation for Environmental Systems

Many environmental systems are characterized by distinctive spatial features such as rainstorms, ocean currents, algae blooms, wildfires and chemical plumes, among others. Traditional data assimilation methods are not always able to preserve the structure of these features when they combine model forecasts with measurements. One way to address this problem is to reformulate the data assimilation process to more explicitly recognize the role of spatial structure. The resulting feature-based approach works with geometrical objects of uncertain size and shape. Many of the methods required to estimate these shapes from data rely on image-processing methods. However, it is also important to include physical constraints not always considered in image processing applications. This project will focus on developing new feature-based data assimilation methods that are applicable to a range of applications.

Professor Daniele Veneziano
Fractal Methods in Hydrology

Virtually all areas of hydrology have been deeply influenced by the concepts of fractality and scale invariance. The roots of scale invariance in hydrology can be traced to the early work of Robert E. Horton, R. L. Shreve and J. T. Hack on the topology and metric properties of river networks and of Henry Hurst on river flow. These early developments uncovered symmetries and laws that only later were recognized as manifestations of scale invariance. Lucien Le Cam, who in the early 1960s pioneered the use of multiscale pulse models of rainfall, provided renewed impetus to the scale-based models. Fractal approaches in hydrology have become more rigorous and widespread since Beno”t Mandelbrot systematized fractal geometry and discovered multifractal measures. Professor Veneziano and collaborators have a longstanding interest in the area of scale-invariant methods, including the construction of scale-invariant processes, their properties and the inference of scale invariance from data. They have applied these methods to several areas of hydrology, including rainfall and rainfall extremes, fluvial erosion topography and flow through random porous media.

Professor Daniele Veneziano
Risk of Extreme Rainfall from Tropical Cyclones

Tropical cyclones (TCs) are atmospheric disturbances capable of producing extreme rainfall with devastating social and economic impact. Consequently, there is much interest in assessing TC rainfall hazards in advance. This research examines the exceedance rate of different rainfall intensity levels over the long run. For this purpose, one needs to parameterize the storms and for each set of parameters evaluate the rainfall effects at the site of interest in probabilistic terms. In principle, the stochastic rainfall model could be fitted to data from historical events, but the large number of potentially influential parameters and the relative lack of historical data make an empirical model identification and fitting approach essentially unfeasible. For that reason, we have developed simple, physically based models and have statistically characterized the difference between actual rainfall intensities and model predictions. We are now coupling these two model components with a TC recurrence model to estimate the frequency with which rainfall intensity at a site exceeds different threshold levels. This risk-assessment tool should be useful to map the risk of rainfall-induced flooding in areas threatened by tropical cyclones.

Infrastructure Systems back to top

 Assistant Professor Saurabh Amin
Robust Infrastructure Diagnostics and Control
Networked control systems (NCS) can be viewed as a set of networked agents consisting of sensors, actuators, computational units, and communication devices. NCS are increasingly deployed to facilitate real-time monitoring and control of large-scale critical infrastructures. We are specifically interested in NCS for energy, transportation, and water distribution infrastructures. Our goal is to develop (i) model-based tools for incident detection and fault/attack diagnosis; (ii) network control algorithms for closed-loop stability and robustness; (iii) adaptive mechanisms for NCS reconfiguration in the presence of extreme disturbances. We believe that these control specific detection and response mechanisms will increase the infrastructures’ survivability, and reduce risks of cascading failures.  

Assistant Professor Saurabh Amin
Incentive Mechanisms for Network Security and Reliability
Our goal is to study the incentives for reliability and security of networked infrastructure systems. These systems are predominantly managed by profit-driven, private entities. The presence incomplete and asymmetric information results in a gap between the individually and socially optimal incentives. We use game theoretic models to characterize the optimal incentives for both individual and social settings. This provides new tools to evaluate the mechanisms aimed at improving network reliability and security. Of particular interest are mechanisms for (i) congestion management (and demand shaping) in smart infrastructures, and (ii) reduction of interdependent network risks.

Assistant Professor Saurabh Amin
Testbed for Networked Control Systems
We are developing a testbed to study the effect of correlated hardware malfunctions and software flaws on the survivability of networked control systems. The testbed capabilities will include: (i) reconfigurable and computationally efficient implementations of diagnostic tools and control methods; (ii) emulations and simulations of control system components; and (iii) experiments for humans and hardware in the loop. We will use a multi-scale approach to integrate strategic decision making with operational execution of robust control strategies. This flexible and powerful cyber-physical experimental facility will be made available to the larger research community.  

Professor Cynthia Barnhart*  
Optimization-Based Data Mining

The goal of this project is to develop new optimization-based methods of data mining that can be applied to a wide range of problems of interest to us and to society. To evaluate our new techniques, we will apply them to optimizing drug combinations in the treatment of cancer. Our objective is to build models that utilize all available information related to all types of cancer, since many drugs are commonly used against multiple cancers. We intend to identify drug combinations that seem very promising and propose new clinical trials to test their effectiveness. In addition, we aspire to build a system that takes information about existing clinical trials and, together with historical information, decides adaptively how to combine trials, stop them early and start new ones. Early action is particularly important, as cancer patients do not have the luxury of time. Other potential application areas for this work include sensor management; intelligence, surveillance, and reconnaissance/strike operations; logistics; and traffic management.
*With Professor Dimitris Bertsimas of the MIT Sloan School of Management

Assistant Professor  Marta González 
Dynamics of Land Use in Urban Spaces

The proliferation of mobile computing devices, principally cellular phones, have become an invaluable tool, helping us understand how cities function as a complex system so that we can we can increase the effectiveness and efficiency of urban planning and design. Behaviors can be decomposed into just a few fundamental patterns that can then be used to differentiate between groups of individuals or types of spaces. The properties of these patterns have been explored, laying the groundwork to discover how people move across space and interact with each other. We propose to expand upon previous work in two important ways: scaling methods from the college campus to entire cities, and exploring not just how far people are traveling, but how they are using these locations dynamically in time. To do this, we will leverage data generated from millions of mobile phone users in a major metropolitan area as they access location-based services on their phones. A phone’s ability to accurately locate itself to WiFi access points within 25m allows us to measure dynamic population density for roughly every intersection of a city at every hour of the day. Additionally, we will compare the results with survey data using data mining techniques, which have not been applied in this context before. Since the survey collected over the metropolitan area is conducted by the metropolitan planning organization for the regional transportation planning purposes, it is a representative sample of the total population of the region, these data will be used to sample and compare the land use and trips captured from the mobile phone. Impact: This is a significant improvement over the static and often outdated classifications dictated by traditional zoning and urban planning regulations. Moreover, a deeper understanding of population flow is critical to planning police service, or public health attempts to better prepare a city to resist disease outbreaks.

Assistant Professor  Marta González 
Analytical Model and Measurements of Aggregated Mobility Networks

The origin-destination matrix (OD), is a network of aggregated trips that allows one to test some ideas about the structure of human movement, there are many factors that control it — land use, location of industries and residential areas, accessibility, etc. — and it seems difficult to provide a general and simple enough model. Most of the studies are descriptive or empirical, i.e. they either present case studies or use regression analysis to quantify the influence on mobility characteristics of factors like neighborhood density, distance from the city center, measures of land use mix, street connectivity and socioeconomic factors. Fewer studies are theoretical, deriving mobility descriptors from assumed spatial distributions of trip origins and potential destinations and models for trip initiation and the choice of destination and transportation mode. Impact: We will validate and calibrate multiplicative models by analyzing the spatial distribution of population (a surrogate for demand) inside metropolitan areas in different countries. We plan to make extensive analyses of population and supply data to support the models of supply and demand and its effect in trips. Using mobile phones we will compare trip length distributions and construct mobility networks and try to provide a unified framework to test OD models.

Professor Richard de Neufville
Development of Flexibility in Design

This research focuses on developing flexibility in design, which frequently adds about 25 percent to the expected value of projects compared to traditional designs optimized around specific forecasts and requirements. Our team works on a broad range of applications: transportation and the development of infrastructure; real estate and building design; the design of oil platforms in the traditional civil engineering context; plus work with the mining industry, health care, defense systems, sustainable energy and other fields. Student researchers should combine excellent engineering skills with an interest in economics and project valuation. Practical industrial experience and the ability to write well are a plus. Students interested in this work are encouraged to visit Professor de Neufville's website and read some of his papers prior to contacting him at
For more information:

Senior Lecturer Peter Shanahan
Non-point-Source Studies for in Singapore Catchments
This project seeks to understand the sources of human fecal contamination and other pollutants to Singapore’s reservoirs, to identify appropriate environmental tracers for such contamination, to understand the association between land use and contamination sources, and to evaluate best management practices for control of non-point source pollution in Singapore. 

Professor Joseph Sussman
Cities as Complex Systems

Much has been written over the years about how cities develop. This research considers cities as complex systems, with characteristics of other complex systems-such as nonlinearity, uncertainty, emergent properties, adaptation, counterintuitive and policy-resistant behaviors, difference between short- and long-term effects, effects at a distance (geographically), high sensitivity to initial conditions and so forth. In this project we endeavor to better understand the behavior of urban areas and to develop strategies for improving city "performance."

Professor John R. Williams
Green Computing – Optimization of Data Centers Across the Globe

Data centers around the globe contain terabytes of data necessary for large enterprises to function efficiently. The data resides in both Enterprise Resource Planning (ERP) systems and Product Lifecycle Management (PLM) systems. The conflicting goal is to have data available locally (in the nearest data center) while at the same time making sure this data is the most up-to-date available. We are building a simulator to test out the feasibility of reducing the number of data centers a company needs by locating synchronization information at a single data center. The simulator is based on MIT technology developed for simulating supply chains with billions of events occurring every day.

Professor John R. Williams
Smart Grid - Next Generation Utility Systems

Reducing the demand side of our energy needs can be achieved by reducing and optimizing our use of energy in transportation and in the heating and cooling of buildings. The US Green Building Coalition estimates that US buildings account for 39 percent of all energy use, and 38% of all CO2 emissions. Transportation consumes 29% of all energy.  This project targets some of the key implementation challenges of the smart grid: The Smart grid will consist of the electricity distribution network including the supplier and consumers and of a parallel monitor and control network (Grid Control Network). The Grid Control Network will be an IP based network. There will be other players in the eco systems building the Grid Control Network and connecting it to the electricity grid. This work focuses on building applications for increasing energy efficiency and peak shaving and on securing the Grid Control Network.  MIT and SAP are collaborating to build a real time meter data unification system capable of handling ten million customers.

Mechanics of Materials and Structures back to top back to top

Professor Markus J. Buehler
Materials Science of Amyloid Protein Nanomaterials

As part of a larger effort to explain the structural hierarchy and strength of high-performance biological materials, this project will investigate the mechanical properties of individual proteins and protein materials at the nanoscale. The focus will be the assembly, deformation and fracture properties of beta-sheet protein structures found in amyloid fibrils (highly ordered beta-sheet based fibril structures found in tissue) and silk nanocrystals using molecular dynamics simulations. Beta-sheet structures are abundant in many strong materials such as spider silk and muscle tissue, and are linked to diseases such as Alzheimer's and Parkinson's. Common to these materials is their ability to self-assemble into highly ordered, robust and sturdy fibrillar protein deposits. This project will investigate the mechanical behavior of the fibril and crystal forming structures using molecular dynamics simulations to explain how the specific structural and chemical properties of simple protein building blocks lead to such material growth phenomena. The insight gained from this study could be beneficial for developing new biomimetic nano-structured materials and novel noninvasive drug delivery systems.

Professor Markus J. Buehler
Mechanics of Chemically Complex, Hierarchical Nanostructured Protein-Based Materials Under Extreme Conditions

Evolution in nature has yielded a vast array of biological materials that are involved in critical life functions. Bone, providing structure to our body, or spider silk, used for prey procurement, are examples of fascinating materials that have incredible elasticity and strength. To date, scientists have been unable to create a number of these materials with similar properties, primarily due to the lack of understanding of how particular arrangements of atoms and molecules give rise to their unique material properties. This project will use large-scale atomistic modeling to elucidate how building blocks at the nanoscale define material properties at the macroscale. Combining knowledge from nanotechnology and biological sciences will enable the development of new materials, designed with molecular precision, that can help us understand, and perhaps cure, diseases that currently ail humanity.

Professor Markus J. Buehler
Protein-Inspiried Hierarchical Biomimetic Materials

Hierarchical biological protein materials are intriguing examples of multifunctional materials that combine disparate properties such as robustness, high strength, high elasticity, controllability and the ability to self-assemble and self-heal. In this project, fundamental concepts will be investigated via the analysis of two classes of protein materials: the beta-sheet rich spider silk and amyloid protein structure, and the alpha-helical intermediate filament motif found in the cell's cytoskeleton, also forming the basis of wool and hair. While the spider silk motif leads to highly elastic, strong fibrils, the intermediate filament protein represents a multifunctional self-organizing protein network. We will employ an innovative approach that combines theoretical analyses based on continuum-statistical theories with large-scale atomistic-based multi-scale simulation implemented on massively parallelized supercomputers. Our goal is to develop an atomistically informed, hierarchical continuum theory of protein materials that combines structural mechanics, statistical mechanics and chemistry, providing quantitative predictions of the elastic and strength properties of protein materials throughout a vast range of time scales.

Professor Oral Buyukozturk
Moisture-Affected Debonding in FRP-Retrofitted Concrete Systems-An Interface Fracture Approach

Fiber reinforced polymer (FRP) retrofit systems for concrete structures have been widely used in the past 10 years, and their short-term debonding behavior has been studied extensively. Nevertheless, the long-term performance and durability of these systems remain largely uncertain. In this project, comprehensive experimental and analytical investigations of debonding in FRP-bonded concrete systems are performed under long-term environmental exposure to develop mechanics-based predictive failure models and related design tools for these systems. Our experimental approach involves an investigation of debonding under moisture ingress, moisture reversal and cyclic moisture conditioning using the concept of fracture mechanics. Synergistic analysis and correlation studies are conducted to incorporate this quantification method and experimental data into the design of retrofitted concrete structures strengthened with FRP to prevent premature failure due to long-term environmental exposure.

Professor Oral Buyukozturk
Atomistic Simulation of Interface Fracture in Bilayer Material Systems

Structural innovations often use multilayer material systems consisting of substrates and interfaces. Interface performance and related failures in such layered systems can play a critical role in overall safety-especially when initial defects are present at the interfaces or in the substrates. Fracture of the substrate materials or interfaces under various mechanical and environmental effects essentially involves atomistic deformation and breaking of chemical bonds between molecules. Molecular dynamics (MD) simulation allows researchers and engineers to study the fracture process in multilayered material systems at the microscopic level. The objective of this research is to use MD simulation to understand interface fracture behavior in bilayer material systems (i.e. crack initiation and propagation direction) and the effects of material and interface properties. Motivated by the safety assessment of complex structural systems involving layers of different polymeric and concrete material properties, this study is conducted in collaboration with Assistant Professor Markus J. Buehler of the Laboratory of Atomistic and Molecular Mechanics, Department of Civil and Environmental Engineering.

Professor Oral Buyukozturk
Material Property Characterization of Concrete/Epoxy System

Understanding the durability of concrete/epoxy interfaces is becoming essential as the use of these systems in applications such as fiber reinforced polymer (FRP) strengthening and retrofitting of concrete structures is becoming increasingly popular. Prior research in this area has indicated that moisture-affected debonding in an FRP-bonded concrete system is a complex phenomenon that may often involve a distinctive dry-to-wet debonding mode shift from material decohesion (concrete delamination) to interface separation (concrete/epoxy interface) in which the concrete/epoxy interface becomes the critical region of failure. Such premature failures may occur regardless of the durability of individual constituent materials. Thus, the durability of FRP-bonded concrete is governed by the microstructure of the concrete/epoxy interface as affected by moisture ingress. In this project, fracture toughness of concrete/epoxy interfaces as affected by combinations of various degrees of moisture ingress and temperature levels is quantified. For this purpose, sandwich beam specimens containing concrete/epoxy interfaces are tested and analyzed using the concepts of fracture mechanics.

Professor Oral Buyukozturk
Development of the Concept of Defect Criticality

Extensive research has been conducted on the behavior of reinforced concrete columns with perfectly bonded fiber reinforced polymer (FRP), but little attention has been paid to the effect of possible initial defects on the structural performance of FRP-confined (or wrapped) concrete columns. This project explores the effect of defect size on the integrity of FRP-confined concrete, which governs the strength and deformability of the structural element. The effect of initial defects on FRP-retrofitted concrete columns appears more complicated than that on FRP-retrofitted concrete beams. In the FRP-retrofitted concrete beam, propagation of a crack from an initial defect (pre-crack) at the interface may start as a local failure and be followed by a rapid global failure. In a FRP-confined concrete column, the propagation of the initial defect may not lead to global failure. In general, such a phenomenon alters the confining pressure provided by the FRP, leading to stress redistribution and weakening of the structure. Deformation behavior and final failure may greatly depend on defect criticality. The objective of this research is to develop an in-depth mechanistic understanding of initial defect-induced fracture-through proper quantification-and to establish a link between local fracture and global failure in FRP-confined concrete. This work will inform future design guideline development and life-cycle predictive capability.

Professor Franz-Josef Ulm
Atomistic Simulation of Nanocomposites

Atomistic simulation of nanocomposites can provide deep insight into the smallest building block of materials. The aim of our research is to examine material behavior systematically, at the nano level, and correlate properties to higher scales. We focus on calcium silicate hydrate (C-S-H), a hydrated nanocomposite known to be the structure of cement paste materials. The molecular dynamics method and ab initio calculations are used to simulate and predict the mechanical properties of C-S-H.

Professor Franz-Josef Ulm
Microporomechanical Modeling of Shale-the GeoGenome Approach

Shales are made of highly compacted clay particles of sub-micrometer size, nanometric porosity and different mineral compositions. Understanding the mechanical properties of shale is key to success in many fields of petroleum engineering and geophysics, ranging from seismic exploration to well drilling and production. Adequate knowledge of shale poromechanics is also important for the development of sustainable nuclear waste storage solutions. The challenge lies in how to translate the highly heterogenous nature of shale into new predictive models of its mechanical properties. In this project, the micromechanical modeling of shale is framed within the GeoGenomeTM approach, which is: break down materials to a scale where the mechanical behavior is governed by invariant properties, then upscale this behavior to the macroscale. Using this approach, we have been able to identify the building blocks that delineate the nanoscale behavior of the load-bearing clay phase in shale materials. The microporomechanics model is being validated at multiple-length scales using novel experimental results from nanoindentation, as well as data from conventional macroscopic techniques for elasticity and strength assessments.

Transportation Systems back to top back to top

Professor Cynthia Barnhart*
The National Air Transportation System as a Reconfigurable Engineered System

The smooth and reliable functioning of the National Air Transportation System (NATS) is vital to the nation's economy. NATS generates about $150 billion in revenue and transports more than 700 million people annually. Yet, disturbance-induced delays-typically problems caused by weather-cost the industry and consumers more than $10 billion each year. The goal of this research is to work toward the autonomous reconfigurability of NATS, so that the system can respond to any disturbance. Researchers will model NATS as a distributed multiagent control problem, and consider the autonomous reconfigurability of NATS through the development of theory and algorithms for dynamic and distributed robust optimization models on multiple scales and granularities. Our goal is to investigate, (1) how local interventions can be made to work autonomously, robustly and synergistically; (2) what operating environments, pricing and other incentives might bring about such a paradigm shift in NATS; and (3) what the potential national benefits from such an integrated approach might be in terms of reduced delays to flights and passengers, more schedule reliability, and lower operating costs.
*With Professor Amedeo Odoni and Professors Dimitris Bertsimas and Georgia Perakis of the MIT Sloan School of Management

Professor Moshe Ben-Akiva
Capturing the Relationship between Motility, Mobility and Well-Being Using Smart Phones
Understanding and incorporating measures of travel well-being in transportation research is critical for the design and evaluation of policies aimed at enhancing well-being. In recent years several efforts have been made to quantify travelers’ subjective well-being using travelers’ self-reported state of happiness while participating in various activities or travel patterns. But, in line with Amartya Sen’s capability approach, we argue that the well-being of a person is derived not only from what a person actually does or is (i.e. a person’s achieved functionings) but also from his/her capabilities i.e. the feasible alternative forms of functionings that he/she could have achieved or could have been. So far, a very limited number of studies have been conducted specifically in the field of transportation to measure well-being of travelers derived from their potential of mobility (can be related to accessibility in  a broader sense) i.e. from motility. The limitations of conventional survey methods to collect uninterrupted and comprehensive information about the activities and travel spaces of people have primarily restricted the number of such studies. In this research, we propose to conduct surveys and measure mobility patterns using smart phone technology (enabled with GPS, GSM, Wi-Fi and accelerometer) which will overcome the limitations of conventional surveys and will assist in developing novel measures of well-being based on a traveler’s mobility potentials i.e. from motility. We anticipate that by providing travelers with feedback about their own travel choices and the travel choices of their peer group, we will be able to influence travelers to make conscious decisions which will ultimately contribute to enhancing their travel well-being and encourage them to shift towards more sustainable transport behavior. 

This research project builds upon an innovative smart phone application for activity travel survey and will develop an enhanced method for the measurement of travel well-being. The novel measures of well-being that we will develop using smart phone technology will provide innovative guidelines for transportation policy design and evaluation based on travel well-being. The techniques and findings will further be useful to researchers in several other fields due to the multi-disciplinary nature of the topic of well-being measurement and survey data collection using smart phone technology.

Professor Moshe Ben-Akiva
Collaborative Research on Travel Behavior Modeling and Traffic Simulation
This research project focuses on multimodal route choice models and the development of models for the joint choice of mode and route. A critical element of this model is the generation of the choice set, ie., the set of alternatives that a traveler is choosing from. The choice set generation process and eventual choice from a choice set need to take into account the daily activity schedule, attributes of the various modes and the multimodal routing options and characteristics of the traveler. Data for such models may be collected by logging the movements of individuals using smartphones equipped with GPS and other sensors.

Professor Moshe Ben-Akiva
Key Decision Factors for Toll Road Usage by Trucks
This research attempts to better understand truck routing behavior in terms of the decision-making process and the factors that affect routing choices. In order to collect data on the decision-making process, a computerized survey was employed to collect exploratory background information and Stated Preferences (SP). During the first year, road-intercept interviews of truck drivers were conducted at three major corridors in North America, with 1121 valid SP observations. An experimental design will be conducted in the second year in which an experiment to collect routing data from truckers using in-vehicle GPS units will be developed. In this experiment, in addition to the GPS data, drivers will be asked to provide information about the trips they have made (e.g. schedule, contract terms etc.) and to respond to a stated preferences (SP) questionnaire, in which they will be presented with various scenarios of alternative routes that will be characterized by different attributes of travel times and distances, tolls and other factors.

Professor Moshe Ben-Akiva*
Intelligent Analysis of Ubiquitous Data (Singapore Alliance for Research and Technology – SMART)
The ubiquity of technologies related to Networked Computing and Control (NCC) provides a range of new close-to-real-time data for urban mobility planning and management, as in the case of GPS/Wi-Fi/cell-id traces and smartcard usage. The challenge lies in capturing the relevant information to enable it for real-time control, improved user service, and long-term strategic planning.  The objective here is to apply pattern recognition tools to obtain information relevant to mobility and transportation, namely activity, path and mode taken. 
*With Chris Zegras of MIT's Department of Urban Studies and Planning

Professor Moshe Ben-Akiva* 
Smartphone based prompted recall surveys (Singapore Alliance for Research and Technology – SMART)
The ubiquity of technologies related to Networked Computing and Control (NCC) provides a range of new close-to-real-time data for urban mobility planning and management, as in the case of any data obtainable from Smartphone usage. We are implementing a broad data collection effort using smartphones matched with web-based surveying tools to infer household and firm activities, including mobility and location choices.
*With Chris Zegras of MIT's Department of Urban Studies and Planning

Professor Moshe Ben-Akiva
Web information retrieval to support transportation network prediction and planning (Singapore Alliance for Research and Technology – SMART)
This project utilizes the web as a predictor of mobility phenomena. The base approach involves planned special events (e.g. concerts, festivals, sports, etc.), since these events are clearly identifiable both in online resources and in terms of their impact. We apply information retrieval and extraction techniques to mine for relevant information from the web and analyze available mobility data. The main outcome is a prediction model that receives extracted features from the web and generates expected impacts given future events. 

Professor Moshe Ben-Akiva* 
Behavioral Models for Land Use, Mobility, Energy and Resource Uses (Singapore Alliance for Research and Technology – SMART)
To plan sustainable future urban mobility systems, we need a set of forecasting tools to help make well-informed, consistent assessments of future conditions under various scenarios. Behavioral models are at the heart of the approach. The objective is to develop state-of-the-art models to understand and forecast different behavioral rationales of households and firms. These models cover different time frames, including long-term models such as residential location and auto ownership, medium-term models of activity and travel choices, and short-term driving and pedestrian behavior models. 
* With Chris Zegras of MIT's Department of Urban Studies and Planning, Joseph Ferreira of the Department of Urban Studies and Planning, and Maya Abou-Zeid of CEE's ITS Lab.

Professor Moshe Ben-Akiva
Advanced computation and modeling for real-time traffic prediction applications (Singapore Alliance for Research and Technology – SMART)
We are designing a new traffic prediction tool for highly complex transport networks such as Singapore. Such software needs innovative architectural design and implementation with state-of-the-art parallel and distributed computing functionalities. These requirements raise computer science research challenges that have implications in the modeling of complex systems beyond the traffic prediction case (e.g. weather, environment, market modeling, etc.). The project is also developing an Integrated suite of behavior models for simulation-based real-time traffic prediction systems. Given the real-time constraint, such models need to be simple, efficient and accurate. The challenges implied include advanced transport modeling, mathematical optimization and computer science. 

Professor Moshe Ben-Akiva
Real-Time Model System for Network Management and Emergency Response (Singapore Alliance for Research and Technology – SMART)
Develop an Integrated suite of models to estimate the impact of alternative interventions and support the real-time deployment of such interventions to mitigate urban mobility problems as they occur on a daily basis.

Professor Moshe Ben-Akiva
Integrated Simulation Platform: SimMobility (Singapore Alliance for Research and Technology – SMART)
Integrate and link together various mobility-sensitive behavioral models with state-of-the-art simulators to predict impacts of mobility demands on transportation networks, services and vehicular emissions.  Integration will make it possible to simulate the effects of a portfolio of technology, policy and investment options under alternative future scenarios. The platform will integrate different types of modeling into a coherent agent-based micro-simulation. The decision process of the agents will be modeled by an activity-based approach. This simulation will be linked with a range of networked computing and control technology-enabled mobility innovations. The project's research plan is to develop an agent based and activity-based, multimodal simulator with the ability to simulate Long-Term timeframe at a Macroscopic level, Medium-term timeframe at Mesoscopic level and Short-term timeframe at Microscopic level. The challenge on the software side is to develop a parallel & distributed simulation engine to integrate short, medium and long-term modeling capability of urban mobility. The simulation engine will be the heart of the overall framework which will handle the events generated in various parts of the software, responsible for message passing between the processes and distributing the load among various processes. 

Professor Moshe Ben-Akiva
Activity based travel demand models (Singapore Alliance for Research and Technology – SMART)
Develop an Integrated suite of activity-based behavior models for SimMobility, our integrated simulation platform. Such models will consider aspects like transport multi-modality, activities, needs and other typical mobility related choices (route choice, departure time, etc.). The focus will be at the medium-term level, i.e. mesoscopic simulation. The topic areas include transport modeling and behavioral econometrics.

Assistant Professor Marta González
Characterizing Transit Disruptions through Buses
Historically, studies of bus networks are confined to a single bus route. In contrast, we will approach bus performance with a computational architecture that enables us to compare routes and systems across multiple cities seamlessly, bringing a new perspective to bus performance as a system. We will exploit transit agencies publicly available General Transit Feed Specification (GTFS) data and their live XML feeds of bus GPS coordinates. The GTFS files define every aspect of each transit agency’s service. It provides the latitude/longitude coordinate definitions of the routes and the routes stops through to the daily transit vehicle trip schedules. Impact: Altering service is a huge commitment; this analysis will help transit providers eliminate some of the risk and uncertainty. Ultimately, we hope that in building this robust, extensible analysis tool, we will shed light onto the fundamental dynamics of buses dynamics on the city scale. We will compare bus systems across cities and hopefully deduce statistical laws to improve the system.

Assistant Professor  Marta González 
Road Usage Patterns

Global communication through mobile phones and online activity is a massive phenomenon in urban centers around the entire planet. This generates petabytes of information that contains fingerprints of individual human activity from remote locations. To date, however, it is still missing the link to quantify the individual interaction with streets infrastructures at a city scale. The underlying mechanisms driving the observed traffic flows in modern cities are still less known due to the lack of reliable data and proper methodologies. In this project, we use mobile phone data and road network data to estimate the road usage patterns in the San Francisco Bay area. This finding enables us to locate the home neighborhoods of road users and find how drivers from a particular neighborhood use each road in the city. Impact: We expect to learn more properties of the road networks determined by properties based on their usage and to extend the analysis to several cities. This finding will provide an alternative to the expensive travel diaries that only few cities in the world can afford. Our aim is to capture the relation of roads the population of each small zone within a city uses in daily trips. The information is of paramount importance to plan alternative transportation solutions based on group sharing, such as car sharing alternatives (see or ride sharing options (see

 Assistant Professor Carolina Osorio
Simulation-based Optimization Methods for Urban Traffic Management
Microscopic traffic simulators are popular tools used in practice to evaluate the performance of a set of pre-determined traffic management strategies. For a given strategy, they can provide accurate and detailed performance estimates. This project develops computationally efficient simulation-based optimization frameworks that enable the use of microscopic traffic simulation models to go beyond scenario-based analysis, and to devise suitable traffic management strategies. It enables the traffic simulation community to expand the use and purpose of these, costly to develop and evaluate, simulation models.

Professor Joseph Sussman
High-Speed Rail in Portugal
Professor Sussman and his research group are working on high-speed rail issues with universities in Portugal and RAVE (The Portuguese HSR agency). This research, aimed to assist the Portuguese in strategic questions regarding this major infrastructure investment. Research includes development of new methods of analysis (Multi-Attribute Tradespace Exploration or MATE), financing considerations, megaregion potential and the associated economic development opportunities, air/high-speed rail competition and and cooperation, and the possibility of using the high-speed rail network for international freight transportation.

Professor Joseph Sussman
Regional Transportation Strategy Development

This research aims to develop innovative methods for regional transportation strategy development using the nation of Portugal as a focal point through the MIT-Portugal Program. Researchers will consider both a multimodal transportation perspective and intermodal opportunities; the interface of urban with intercity transportation; and new technologies that can provide unconventional data for use in the regional transportation strategy process. Promising ways of innovating in strategy development include such procedures as scenario analysis, life-cycle costing and the CLIOS Process, a method for studying complex, large-scale, interconnected, open, sociotechnical (CLIOS) systems.
We will also link this research with other aspects of broad-based engineering systems, including consideration of real options, flexibility and stakeholder analysis.

Professor Nigel Wilson
Public Transportation Planning and Operations in London

London's century-old public transport system is undergoing more than $40 billion worth of renovation and expansion while facing major financial and capacity pressures. Our collaborative research program with Transport for London (TfL) focuses on the use of automatically collected data systems in strategic decision-making. Origin-destination matrices estimated based on data collected from the Oyster smart card ticketing system, as well as path choice models estimated from onboard surveys, will yield drastically improved, cheaper and more timely estimates of volumes and crowding on the London Underground and bus networks. Estimation of interchange behavior and multimodal journey patterns will aid in integrated network design. Methods are being developed to use end-to-end journey times, also measured by the Oyster system, to quantify the delays and unreliability experienced by passengers on London's rail networks. Rail signaling information will be used to evaluate and improve day-to-day service control decisions. A parallel focus of our work with TfL is to examine the technology and policy requirements for using commercial contactless credit cards for ticketing, as well as the effects of such a system on fare policy. Finally, we are investigating the use of innovative strategies and structures for the finance and delivery of large rail infrastructure projects, including Crossrail. 

Professor Nigel Wilson
Planning for Boston’s Green Line (Light Rail) Extension to Somerville and Medford

Final planning and engineering is currently underway to extend the MBTA’s Green Line from its current terminus at Lechmere Station in East Cambridge to the north through the City of Somerville to Medford. Seven new stations are being designed that should substantially improve resident and visitor access to the regional transit network and to Somerville’s commercial and business centers. This research is sponsored by Mass DOT, the state agency responsible for the final engineering and construction of the project and focuses on future development around the planned new stations, including access planning for pedestrians, cyclists, bus passengers, and auto users. This transit project is viewed as a unique opportunity for the economic and urban revitalization of Somerville. The current research scope includes:

  • bus improvement alternatives for the period leading up to the opening of the extension as well as after the overall Green extension is operational, to improve overall transit accessibility
  • new evaluation approaches to incorporate the Livability objective into FTA’s New Starts Process
  • analysis of the impact of other infrastructure and land use developments using innovative dynamic network modeling approaches
  • retrospective analyses of land use and ridership behavioral impacts of a similar extension of the Red Line into Somerville in 1983