CEE 29, Managing Natural Disaster Risk (offered Winter 2014)

Natural disasters arise from the interaction of natural processes, such as earthquakes or floods, with human development that suffers safety-related and economic losses. We cannot predict exactly when those disasters will occur, or prevent them entirely, but we have a number of engineering and policy options that can reduce the impacts of such events. In this course we study natural disasters, and how we have improved our ability to withstand disasters at the same time as we increasingly put ourselves in harm’s way. We survey topics in engineering, science and policy that help us understand and minimize our risk. We study historical disasters notable for their consequences or the role they played in advancing our ability to manage risk. Basic tools of probability are introduced to help quantify uncertainties in the future occurrence and consequences of disasters. The role of professional engineering societies, building codes and the insurance industry is investigated. Students have the opportunity to apply the course concepts to a region of the world of their choosing, and prepare an analysis and presentation of key problems, current risk management activities and opportunities for further reducing risk. 


CEE 101A, Mechanics of Materials (last taught 2013)

This course introduces undergraduate students to the theory behind fundamental topics of mechanics of materials and demonstrates how this theory is put into practice to analyze and design structural elements. The only prerequisite is a course in Statics (E14). Topics covered include: the principles of stress and strain, axial forces, shear forces and bending moments in statically determinate beams, normal and compound stresses in beams, analysis of composite beams, plastic bending, deflections of statically determinate beams, method of superposition, deflections and internal stresses in statically indeterminate beams, elastic column buckling and shear stress, shear flow and shear center.



CEE 203, Probabilistic Models in Civil Engineering (offered Fall quarter every year)

This course introduces graduate students to concepts and applications of probability and statistics in civil engineering. The focus will be on applications and concepts, with less emphasis on proofs and theory. By the end of this class, you will be able to: communicate using the language of probability and statistics, choose appropriate probabilistic models for a given problem using information from observed data and knowledge of the physical system being studied, use probability tools to perform civil engineering calculations, identify topics where probability and statistics have been or should be applied in civil engineering, and critically examine the work of others for valid use of probability and statistics.


CEE 204, Structural Reliability (offered Spring quarter in alternating years)

This course introduces graduate students to concepts and applications of structural reliability. Upon completion of this course, students will be able to compute first- and second-order estimates of failure probabilities of engineered systems, compute sensitivities of failure probabilities to assumed parameter values, measure the relative importance of the random variables associated with a system, update reliability estimates based on new observational data, identify the relative advantages and disadvantages of various analytical reliability methods (as well as Monte Carlo simulation), use reliability tools to calibrate simplified building codes, and perform reliability calculations related to performance-based engineering


CEE 289, Random Vibrations (offered Spring quarter in alternating years)

This course introduces graduate students to concepts of random vibrations for dynamic analysis of structural and mechanical systems subjected to stochastic loading. Students taking this course will learn to apply tools from probabilistic modeling to analyze dynamic systems while accounting for variability and uncertainties that are inevitably present in real engineered systems. By the end of this class, you will be able to: classify random excitations as stationary or non-stationary, discuss important properties of random processes, define and compute power spectral density functions, compute auto-and cross-correlation functions and relate them to power spectral density functions, describe the dynamic response of a multi-degree-of-freedom system to a stochastic excitation, quantify the distributions of peak loads and peak responses from a system subject to stochastic excitation, and understand the assumptions and techniques used to derive the SRSS and CQC combination rules for modal analysis.


Jack Baker