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Civil and Environmental Engineering

Graduate Student Research Opportunities

Dr. Florence Sanchez, Vanderbilt University Civil Engineering

Both M.S. (thesis option) and Ph.D. students require undertaking research work under the direction of one or more advisors.   All Ph.D. students will have some type of financial support, normally covering tuition, stipend and other fees. Students will be working on research projects which are mostly sponsored by government or private agencies. 

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The research projects can exclusively belong to a particular area of specialization or can be interdisciplinary. Necessary laboratory, library, and computational resources, including the university's massively parallel computer system, ACCRE ,  are available within Vanderbilt University for successful execution of research work.  Occasionally, a student may have to access some special facilities at another organization, like Oak Ridge National Laboratory, or U.S. Army - Engineering Research and Development Center.

Research Areas of Specialization

Multi-modal Transportation Engineering

This area of specialization employs the use of information technology tools to address issues facing freight transportation. Geographic Information Systems (GIS), database management systems (DBMS) and custom software solutions are among the tools most commonly used in the conduct of research. There are currently exciting research assistant opportunities in travel information system development, intermodal freight transportation risk assessment, and enterprise operational risk management.
Travel information systems convey real-time information to motorists about real-time traffic conditions (congestion, incidents) as well as current and planned construction activities. VECTOR has developed tools that enable field personnel to report information about real-time conditions on Tennessee highways and interstates as well as relay this information to motorists. Recently, VECTOR has performed research applying tools and capabilities developed for travel information systems to freight transportation. Current projects include analyzing freight corridors for safety, security, and capacity, looking at network vulnerability and resiliency and enterprise operational risk management. Please refer to the VECTOR website for more information about these projects and opportunities.

Multi-scale Structural Mechanics and Advanced Materials

In this area of specialization, a wide range of problems addressing current and future needs of industry, civil infrastructure, and national defense are considered.  The emphasis is on the development of new high-performance advanced materials and understanding the deterioration and failure processes of structures and components exposed to acute environmental actions (like temperature, moisture, wind and earthquake), chemical effects (like gases in the air, salt, acids, and other corrosive agents), and accidental or man-made events (like blast and projectile impact). The research methodology involves experimental investigation, analytical treatment, and numerical modeling and simulation. Experimental investigation may be undertaken in the laboratory and/or in the field under real conditions. Analytical treatment is often the precursor to numerical modeling and simulation which may involve multi-scale representation over micro-, meso- and macro-scales to accurately identify initiation and propagation of damage and deterioration processe Link to Civil and Environmental Engineering Video Playlist s. 

The Multi-Scale Computational Mechanics Laboratory (MCML) research focus is on computational characterization of the failure response of systems that involve multiple temporal and spatial scales, development of computational methodologies for failure and fragmentation of composite systems subjected to extreme loading conditions including impact, blast and crushing loads, characterization of complex and hybrid composite systems, and analysis of multiphysics problems.

In addition to deterministic treatment of the problems, modern stochastic methodologies are also applied to specify the reliability of the predicted behavior, both at component and system levels. The stochastic analysis scheme also allows for optimal performance at service load conditions. In addition, it accounts for the temporal effect of the deterioration process affecting scheduling of maintenance.

Another important research area is concerned with monitoring the health of civil infrastructure like bridges, pavements, critical buildings, dams, etc., and transportation hardware like aircrafts, ships, rapid transit vehicles, etc. In addition, developing effective but economic ways to rapid extension of the life of these is another area of research.

Risk, Reliability and Optimization

The current sponsored research projects fall into four categories:

  • Structures and materials degradation

  • Structural health monitoring

  • Optimization under uncertainty

  • Uncertainty analysis methods

In research efforts related to structures and materials degradation, physical, mechanical and chemical degradation mechanisms in materials like metals, composites, and cement/concrete are considered. Ongoing projects include: a Federal Aviation Administration project focused on modeling fatigue and fracture in aerospace mechanical components under multi-axial variable amplitude loading; project funded by the railroad industry (Transportation Technology Center) models different fracture mechanisms in railroad wheels; and research on durability of cementitious materials under various types of physical and chemical degradation such as chloride ingress, sulfate attack, carbonation, and freeze-thaw is funded by the U.S. Department of Energy.

Research related to structural health monitoring focuses on several questions related to both diagnosis and prognosis:(a) optimization of measurement system, such as sensor placement, (b) rapid diagnosis for online applications, using bond graph representations; (c) uncertainty assessment in diagnosis and prognosis; and (d) integration of diagnosis and prognosis. Applications include civil structures (bridges), mechanical and aerospace components (actuators, aircraft and space shuttle components). Materials include metals, composites and concrete. Sensor types include piezoelectric, acoustic emission, and fiber gratings. Current projects on these topics are funded by NASA, U. S. Air Force, and NSF.

Research on optimization under uncertainty focuses on a wide range of inverse problems related to design, testing, model development, inspection, and operations of civil infrastructure, automotive, and aerospace systems. Specific projects are funded by NASA Langley Research Center (multidisciplinary optimization of aerospace vehicles), NASA Jet Propulsion Laboratory (test resource allocation for sperformance prediction), U. S. Department of Transportation (transportation network operations, airline network allocation and design, pavement design, bridge inspection), General Motors (automotive structures optimization), Sandia National Labs (critical facilities optimization), U. S. Department of Homeland Security and Los Alamos National Labs (bird flu emergency response, food safety), U. S. Department of Defense (flexible systems design), and the National Science Foundation (business enterprise optimization).

Research on uncertainty analysis methods addresses different sources of uncertainty that contribute to risk prediction, especially data uncertainty and model uncertainty. Current projects funded by Sandia National Labs, NASA, FAA, AFOSR, and U. S. DOE are developing quantitative methods for model verification, validation, calibration, extrapolation, and error quantification. Both aleatory and epistemic sources of uncertainty are included. Problems of interest are multi-scale, multi-disciplinary, and time-variant. Applications include aerospace structural components (helicopter mast, aircraft wing, space telescope truss, energy dissipation systems), micro-electro-mechanical (MEMS) devices, and civil infrastructure (bridges, nuclear waste storage). System-level uncertainty analysis includes research on human reliability modeling, funded by Nuclear Regulatory Commission, NASA, and the Idaho National Laboratory.