Research

Earthquake Engineering

Our objective in earthquake engineering research is to improve the state of knowledge, through fundamental and applied research, to help decision-makers reduce seismic hazards.

Decision-makers are defined as all the individuals and agencies affecting the planning and design/construct process, such as planning or regulatory agencies, owners, investors and insurers — and the engineers who protect against seismic hazards through earthquake-resistant design.

Earthquake engineering is a multi-phased process that ranges from the description of earthquake sources, to characterization of site effects and structural response, and to description of measures of seismic protection. Our current research includes occurrence modeling, geophysical modeling, ground-motion modeling, stochastic and nonlinear dynamic analysis, and design and experimentation. Components of these studies pertain to the individual phases but also, and perhaps more importantly, to aspects that incorporate some or all of the phases of earthquake engineering.

Seismic hazard and risk analysis

For over 30 years, research at the John A. Blume Earthquake Engineering Center has focused on seismic hazard and risk analysis. Early work focused mainly on modeling sources, occurrence and attenuation, and developing probabilistic hazard analysis methodologies, using Poisson models and Bayesian models. In recent years, considerable efforts have been placed on introducing mechanistic models to occurrence and attenuation phenomena. Time- and space-dependent models have been introduced to represent the fault rupture mechanics and the stress accumulation and release cycles of large earthquakes. Most recently, advanced computational tools, such as geographic information systems (GIS) and database management systems (DBMS), have been used to capture, analyze, integrate and display the tectonic, seismological, geological and engineering information needed in seismic hazard assessment.

Working with various countries in Central America, North Africa, Asia and Europe, our researchers have developed seismic hazard maps and structural design criteria, while our faculty and graduate students have significantly contributed to the development of models and methods for earthquake vulnerability and risk assessment. Current research uses analytical models for damage and structural vulnerability assessment that are based on nonlinear structural response simulation. A key question currently being addressed is the assessment of losses resulting from structural damage. Damage and vulnerability models are developed for individual structures within the context of performance-based engineering and more generic vulnerability models are formulated for application over large regions to many different types of structures. These risk assessment tools have been implemented and utilized by the practicing engineering community as well as by government agencies, insurance/reinsurance companies and financial institutions.

Researchers in our department are also working on seismic risk assessment models for transportation systems. These models use GIS and transportation network analysis tools to estimate the losses from damage to components of the system as well as those due to traffic time delays or inaccessibility of particular locations. Tools for emergency response and resource allocation following disasters are key features currently under development. Significant components of this research are supported through the Pacific Earthquake Engineering Research Center (PEER).

Ground motion modeling

Prediction of strong ground motion continues to be a major research area in earthquake engineering, using simulation of ground motion models for seismic hazard analysis, stochastic-physical rupture process models for ground motion prediction, prediction of ground motion for engineering applications, and study of the nonstationary characteristics of simulated and recorded ground motions for nonlinear analysis of structures. Various geophysical models are being considered for simulating strong ground motion, and recorded motions from recent earthquakes are being studied for their characteristics and damage potential. Recent seismological studies have focused on the understanding and characterization of strong ground motion in the near field. The effect of near-field motions on structures has been observed from past earthquakes to be particularly important; however, systematic studies of these effects had not been conducted so they now are a focus of current research.

 

Damage potential of ground motion

Experience in past earthquakes has shown that the engineering profession has not yet succeeded in defining ground-motion parameters that correlate well with observed damage. From an engineering perspective, we are seeking representations of the seismic “demand” that can be used, through convolution with the structural “capacity,” to assess structural reliability. Thus, both demand and capacity need to be evaluated, the latter with due regard to structural characteristics and cumulative damage effects that depend on strong motion duration. If this can be achieved, seismic risk analysis can be based on reliability concepts, and design parameters can be derived that are consistent with the damage potential of the ground motions.

Research studies on seismic hazard analysis, input and response characterization, structural reliability, and design are treated as interrelated subjects through a consistent and coordinated approach. The major components of this research are development of damage models for structural response; characterization of ground motions based on damage potential; reliability evaluation; seismic risk analysis; and development of design parameters.

Design and experimentation

Considerable effort is being devoted to design research that can be implemented directly in engineering practice. This research, concerned with methods to evaluate and improve the behavior of new and existing structures in severe earthquakes, includes:

• Development of a deformation-based seismic design methodology.
• Dynamic stability considerations and P-delta effects.
• Evaluation of the effects of stiffness and strength irregularities in plan and elevation.
• Cumulative damage modeling.
• Retrofit measures for existing structures.
• Exploration of new materials and new structural systems for earthquake resistance.

Our research facilities include a laboratory with equipment for static and dynamic testing of structural materials, components and system models. Current structural testing is focusing on research to validate computational models to predict dynamic nonlinear response of structures and for developing health-monitoring technologies. This includes shaking table tests to examine structural collapse phenomena as affected by the complex interactions of degrading structural response and random earthquake input motions. Shake table testing is also an important component of the research to develop more robust wireless strong motion sensors. Other projects involve quasi-static testing of structural components and materials to evaluate fiber-optic sensors and to investigate the effect of localized failure mechanisms on structural performance.

Design-Construction Integration

Unique Processes

Civil engineering structures provide few, if any, opportunities for mass production because of the unique production environment. This creates a special need for innovations in design and construction processes that are peculiar to this profession.

In most cases, planning, design, construction operation and maintenance are separated by disciplines and executed in phases, in an adversary environment and with little interaction between phases and disciplines. The vertical and horizontal fragmentation of the design/construction industry reduces quality and increases the life-cycle costs of the final product. Our research in this area, conducted in the Center for Integrated Facility Engineering (CIFE), the John A. Blume Earthquake Engineering Center and the Project-Based Learning Laboratory, is concerned with the structural engineering aspects of facility engineering, but from the viewpoint of integration with all other disciplines involved in the process.

Current areas of research

• Development of knowledge-based systems to incorporate construction knowledge into the design process to improve constructibility.
• Design, construction and performance of nonstructural components.
• Development of probabilistic functions to simulate their performance based on structural response parameters.
• Application of new sensing technologies based on micro electro-mechanical systems (MEMS) together with wireless communications and smaller and more powerful microprocessors to monitor construction operations in real time.
• Development of new efficient structural systems that result in structures that have better performance and are easier to build, operate and maintain.
• Advanced simulation and visualization of erection construction processes for the development of computer-assisted erection systems.
• Development, testing, deployment and assessment of new workspaces and information technologies, processes, learning and work cultures and approaches to foster cross-disciplinary, multi-cultural, collaborative, geographically distributed teamwork and eLearning.

PBL (problem-, project-, product-, process-, people-based learning)

The master builder’s atelier in the information age is the vision behind the integrated research and curriculum in architecture/engineering/construction (A/E/C) global teamwork program, which engages students from the Structural Engineering and Geomechanics, Construction Engineering Management and Design-Construction Integration Programs, in the Civil and Environmental Engineering Department at Stanford. This program was established in 1993 and has evolved from an experimental Stanford course into a global learning network. The goal is to be a world leader in A/E/C global teamwork together with its university and industry affiliates. Its mission is to educate the next generation of professionals who know how to team up with professionals from other disciplines, and leverage collaboration and information technologies to produce higher-quality products more quickly, economically and environmentally friendly.

The PBL Lab and the A/E/C global teamwork program are based on a PBL pedagogical approach, where PBL stands for problem, project-, product-, process- and people-based learning. The objectives are to develop, test, deploy and assess radically new work spaces, information and collaboration technologies, processes, learning and work culture, and approaches for cross-disciplinary, collaborative, geographically distributed teamwork.

The core atom in the A/E/C Global Teamwork program (CEE222 A & B) is the A/E/C team. One of the innovative features of this program is the role each of the participants play: undergraduate students are apprentices to master's students who play the role of journeyman while faculty and industry practitioners play the role of mentors, owners and sponsors. Over the years, global affiliates have joined the program from Europe, Asia and the United States (for an updated list of members in the A/E/C Global Teamwork learning network, visit http://pbl.stanford.edu). All the A/E/C teams are geographically distributed over time, space and culture. This authentic learning experience exposes students to four challenges: cross-disciplinary project-based teamwork; use of information and collaboration technologies; team coordination; and collaboration over time, space and culture (please visit http://pbl.stanford.edu/AEC%20projects/projpage.htm to view the A/C/C project gallery).

The PBL Lab integrates cutting-edge information technology and mature research software prototypes developed at CIFE. It offers a wide range of information and collaboration technologies, such as video conferencing, video streaming, project Web portals, team discussion forums, building modeling, knowledge management, integrated project delivery, visualization and direct interactive manipulation workspaces and devices that support the activities, processes and product development of mobile knowledge workers and learners.

Performance-Based Engineering and Construction

Performance-based engineering is the design, evaluation and construction of engineered facilities that meet — as economically as possible — the uncertain future demands of owner-users and nature.

The premise is that performance levels and objectives can be quantified, that performance can be predicted analytically, and that the cost of improved performance can be evaluated to allow rational trade-offs based on life-cycle considerations rather than construction costs alone.

Performance-based engineering offers great professional opportunities for producing better facilities faster and more cost effectively. It forms the foundation for strategies to revitalize of our decaying infrastructure and presents challenges for the utilization of emerging technologies to monitor the health of existing facilities through sensor technology and to control performance with active control systems and smart materials.

In the academic environment, performance-based engineering offers great opportunities for research and teaching of the processes involved in the design and construction of engineered systems whose performance can be quantified, monitored and controlled in a manner that responds to the diverse needs and objectives of owners and society. Adoption of performance-based engineering concepts requires major changes in the thinking, practice and education of structural engineers. Perhaps most important is a shift away from the dependence on empirical and experience-based conventions, and toward a design and assessment process more firmly rooted in a scientifically oriented approach that emphasizes accurate characterization and prediction of structural behavior.

Performance-based engineering is the central theme of many of the research activities of Stanford’s Structural Engineering and Geomechanics Program. Our students and faculty are researching performance-based design methodologies and fundamental issues of stochastic modeling of loads and resistance. They do pioneering work in probabilistic loss modeling of structural and nonstructural building systems and transportation networks, explore emerging technologies for health monitoring and active control, and remain at the forefront of developing the computational approaches needed to predict performance. The newly established Design/Construction Integration Program provides extensive lateral support on constructability issues and the performance of nonstructural systems.

Much of our specific research on performance-based engineering focuses on earthquakes, but we are also researching wind and ocean wave hazards and performance-based fire engineering. Our global objective is to develop knowledge and tools for the assessment, management and mitigation of the risks associated with these hazards.

Computational Mechanics

Computational mechanics emphasizes the development of mathematical models representing physical phenomena and applies modern computing methods to analyze these phenomena.

It draws on the disciplines of physics, mechanics, mathematics and computer science, and encompasses applying numerical methods to various problems in science and engineering. The general scope of work in computational mechanics includes fundamental studies of multiscale phenomena and processes in civil engineering, from kilometer-scale problems to a much finer scale up to and including the nano-scale.

Current research in computational mechanics dealing with kilometer-scale problems includes numerical simulation of folding and fracturing of sedimentary rock strata using combined elastoplastic-damage continuum theory along with enhanced finite element (FE) methods for shear localization analysis, as well as simulation of regional-scale earthquake fault nucleation and propagation using a finite deformation stick-slip law with a variable coefficient of friction. 

Research dealing with meter-scale problems includes development of constitutive models for new high-performance materials such as ductile fiber-reinforced concrete and modeling of nonlinear response of structural systems that use high-performance composite materials. Research on problems dealing with a much finer scale includes theoretical and numerical investigation into the micromechanics of porous media using coupled Lattice-Boltzmann (LB)/FE simulations of fluid flow hydrodynamics through micron-scale pores in rocks.

Measurement and calibration are key to a successful development of computational algorithms and numerical models at different scales. Light Detection and Ranging (LiDAR) technology, including laser scanning, GPS and digital imagery, provides high-resolution topographic data to constrain kilometer-scale fold models and decameter-long, centimeter-thickness fractures. At the other end of the spectrum lie the advances of 3D digital imaging of lab specimens using X-ray computed tomography with micron-scale resolution.

Combined with traditional testing of centimeter- and meter-scale lab specimens, numerical models can now reach a level of mathematical sophistication commensurate with our ability to measure relevant response variables. A great challenge in computational mechanics research is bridging the different scales without sacrificing resolution. For example, effort is underway to bridge the gap between continuum-scale and atomistic molecular dynamics through combining the particle-based LB approach with the continuum-based FE method to model the fluid flow hydrodynamics through porous rocks.

For a computational technique to be competitive, it is essential to consider not only the spatial and temporal discretization procedures but also how the equations will be solved. While it is generally acknowledged that parallel supercomputing offers considerable promise for solving large problems of practical interest, it is important to recognize that new algorithms and data structures have to be developed to exploit the new discretization methods and attack the intrinsic difficulties of the problem being addressed. Adaptive and stabilized solution schemes based on error estimation also provide unique challenges for solver technology. Current work in our group involves the development of new solution algorithms for multiscale statics and dynamics problems related to parallel and distributed computing.

Engineering and Design of Sustainable Built Systems

The tremendous growth of green building design and construction, sparked by the U.S. Green Building Council’s Leadership in Energy and Environmental Design (LEED) program, has brought sustainability to the forefront of many design and construction projects.

At Stanford, research on design and construction practices for a more sustainable built environment centers on the creation and widespread application of quantitative tools for measuring the comprehensive economic, social and environmental impacts of building and infrastructure systems.

The design and construction of sustainable building systems begins with modeling the entire life cycle of a building to measure the impacts from material mining and fabrication, construction, building use and placement in a landfill or recycling at end of life. The development of new datasets, modeling techniques and software tools for accurately measuring a full cadre of sustainability metrics is a major research effort. These metrics can range from global warming potential (CO2 equivalents), acidification potential (H mol equivalents), ecotoxicity (2,4-D equivalents), human health criteria pollutants (PM2.5 equivalents), energy use (MJ of nonrenewable and renewable energy), public health impacts, land use and social equity to long-term economic costs.

Building on these analysis and assessment tools, further research focuses on the use of quantitative sustainability metrics to guide design and operation of built systems. These efforts infuse sustainability-focused decision-making throughout the design process, from material design and selection to structural design to building-, neighborhood- and system-level planning, accounting for the fact that design choices at each scale affect overall sustainability performance. Our research includes the creation of design tools that incorporate numerous models for advanced material performance, durability and corrosion phenomena, building construction and operation, structural performance and system behavior with nonlinear optimization models to achieve maximum sustainability performance.

Innovative Materials

The built environment currently consumes 51 percent of total U.S. energy, of which 39 percent is consumed by the operation of buildings (primarily in heating and cooling) and 12 percent is consumed by construction material fabrication and demolition.

The built environment also contributes to 55 percent of total U.S. CO2 output, of which 43 pecent is the result of energy production for building operation and 12 percent is again in material fabrication and demolition. At Stanford, research on innovative, sustainable building materials is one of the ways we are seeking to lessen the negative impact of the built environment on our natural environment.

We are developing new construction materials, and re-engineering current materials, that are cement-based, polymer-based and bio-based. Our research is cross-disciplinary with collaborations among civil, environmental, chemical and material science engineers. Current materials research in our department includes the development and evaluation of fiber-reinforced polymeric materials that are made from renewable resources such as biobased polymers and natural plant fibers. Advantages of such materials include a reduced dependence on nonrenewable energy sources for materials production and a reduction of recalcitrant, non-degrading construction and demolition debris in landfills.

The ability of these materials to replace various non-structural and structural materials in buildings, to avoid deterioration while in service and to biodegrade after their useful service life is currently being investigated. Computational models and theoretical developments are underway to predict the performance of these highly nonlinear materials. In the area of improved building energy-efficiency in building operations, we are investigating new green insulating materials in structural panels.

Additional research is exploring re-engineering existing materials for improved performance and sustainability, including the application of fiber-reinforced polymer composites and high-performance fiber-reinforced cement-based composites, such as Engineered Cementitious Composites (ECC) that exhibit very fine, multiple cracking and tensile strain hardening up to strains of 3 percent. These materials, commonly called “bendable concrete” in the mainstream media, are highly damage-tolerant in both tension and compression and have potential for improved durability against corrosion as well as resistance to overloads such as earthquakes with minimal damage.

The application of these materials to new, sustainable building and infrastructure designs, as well as to structures needing seismic retrofit, is being investigated through physical experiments and computer modeling, including performance-based assessments.

Engineering Informatics and Simulation

Traditionally, the design and construction industry has faced many barriers to developing and implementing new technologies, including the threat of litigation, government regulations, code restrictions and the high cost of insurance.

Furthermore, because each civil structure tends to be unique, there is, in contrast to other manufacturing sectors, a lack of opportunity for mass production imposed by the “one-off’’ production environment. This in turn creates a special need for innovation in design procedures and construction techniques that are peculiar to this profession. Computers can play a significant role as an enabling technology to support future innovation in the design and construction industry.

Computers have been used in structural engineering primarily as a computational tool improving the accuracy of structural response prediction and assisting in many routine design tasks. Much has been accomplished in the past three decades and much more can be accomplished through advanced research in computational mechanics and computer-aided engineering. Computers provide a significant advantage as communicators of information through proper information management tools.

In a multidisciplinary project of facility engineering, the computer can serve as a medium for storage, management, visualization and communication in which the information is generated only once and is augmented and retrieved in the various phases of the facility engineering process. Furthermore, computers can simulate the fabrication, design, erection and operation processes of a constructed facility. Our research concerns the design and construction of facility engineering, from the viewpoint of integration with all disciplines involved in the process, focusing on the following areas:

• Development of tools to facilitate collaboration between disciplines.
• Use of Internet and mobile technologies to improve communication among project team members.
• Better documentation of design and information transfer.
• Management of engineering and regulatory information.
• Use of high-performance parallel and distributed computers for large-scale simulation of structural behavior as well as design and construction processes.

Risk and Reliability Analysis for Hazard Mitigation

The Structural Engineering and Geomechanics group at Stanford University has had a long tradition of research in the area of risk and reliability analysis for hazard mitigation.

Structural reliability concepts were conceived at Stanford and over the past three decades the field has matured and broadened to include problems ranging from the modeling of hazardous natural phenomena, such as earthquakes and hurricanes, to the evaluation of the performance of structures including buildings, dams, bridges and offshore platforms, to the assessment of the socio-economic consequences of such catastrophic events.

The need for safe operation of industrial facilities, such as nuclear power plants and manufacturing facilities that use hazardous materials, has led to the development of analytical methods for safety and reliability assessment of the structures and equipment at such facilities. Furthermore, uncertainties inherent in load processes, structural material properties and design, as well as a lack of complete control of the construction process, have necessitated the development of design codes that quantify the various sources of uncertainty and randomness. Current research thrusts include the development of efficient methods of systems reliability for large systems, reliability analysis of components under time-varying loads, and the treatment of the nonlinear behavior of structural components under extreme loading conditions.

Many current trends present challenges and opportunities to the field of risk and reliability analysis. At the narrowest level, structural engineering practice is beginning to adopt explicit probabilistic bases for the design of conventional facilities (e.g., new performance-based design seismic criteria that consider a range of damage levels and their likelihoods), and to demand improvements to them (e.g., better calibration to historic damage experience). Industries and regulatory bodies that are engaged in large special projects have moved steadily toward probabilistic structural analysis. The insurance industry has recently recognized that only formal probabilistic analysis of hazards, structural response, damage and losses provides the potential for accurate forecasts of the likelihoods of rare catastrophic losses. Finally, the political arena is replete with activities that involve risk assessments of structures. These movements demand that structural reliability and risk analysis be made more accurate, broader and more responsive to a wider set of interested parties.

Sensing, Monitoring, Control and Intelligent Systems

As advances in sensing, networking and new materials have made continuous monitoring and control of structural functions a realizable goal, the idea of the intelligent or smart system, originally applied to electrical, mechanical and aerospace systems, has now extended to include civil structures.

By definition, an intelligent structure has the ability to identify its status and optimally adapt its function to stimuli. Research focuses on mainly two areas: Identification of structural behavior or properties (e.g., deformation, energy usage and damage evaluation); and control of structural response to external (e.g., wind, earthquake) or internal (e.g., acoustics, temperature variation) stimuli. Some recent catastrophic structural failures due to natural events (such as the California earthquakes, hurricanes in the Southeast and blizzards in the Northeast and Midwest) have amply demonstrated the need for rapid assessment of structural integrity after such events, and a need to control and minimize damage.

Much of the research in the United States and abroad has gone toward the development of active control systems for structures subjected to extreme external excitations with the primary objective of maintaining structural and occupant safety. With recent advances in micromachined sensors, wireless communications devices and improved imbedded computation tools, considerable attention has also been focused on the development of near-real-time damage monitoring systems. Furthermore, the development of distributed actuation systems and better sensors and microprocessors is providing the tools for achieving optimal levels of controlled structural functionality. Advancements include smart materials fabricated to incorporate embedded computing tools such as sensors and microprocessors, and new classes of structural materials that offer the opportunity to revolutionize many aspects of civil engineering construction.

High-performance materials include applications of high-performance steels, concrete or fiber-reinforced plastics for structural frames, cement-based soil-mixing for site modification, etc., as well as special protective devices such as seismic isolators and dampers, geosynthetic membranes, etc. These new materials provide important opportunities for the design of new structures and the rehabilitation of aging or damaged structures with easier, less costly and more durable construction than conventional materials.

This area of research crosses over several fields of expertise and requires that the research from these fields be integrated in a coherent manner. For example, the design of an imbedded damage monitoring or actively controlled system requires expertise in sensor technology, radio transmission and communication, advanced computational methods, nonlinear structural dynamic behavior, smart materials, and the design of modern software and hardware systems. There is a strong focus on collaborative research with Departments of Mechanical Engineering, Electrical Engineering, Computer Science, Material Science and Engineering, and Aeronautics and Astronautics.