Carnegie Mellon University

CEE Graduate Seminar Series

Fall 2021

Seminars will be held remotely between 11:50am to 1:10pm. 

Our seminars are open to the public, please contact Randi Senchur for information. Students registered for seminars will receive details via email.

Path Integrals in Stochastic Engineering Dynamics

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Ioannis A. Kougioumtzoglou
Associate Professor
Civil Engineering & Engineering Mechanics
Columbia

Abstract

Ever-increasing computational capabilities, development of potent signal processing tools, as well as advanced experimental setups have contributed to a highly sophisticated modeling of engineering systems and related excitations. As a result, the form of the governing equations has become highly complex from a mathematics perspective. Examples include high dimensionality, complex nonlinearities, joint time-frequency representations, as well as generalized/fractional calculus modeling. In many cases even the deterministic solution of such equations is an open issue and an active research topic. Clearly, solving the stochastic counterparts of these equations becomes orders of magnitude more challenging.

To address this issue, the speaker and co-workers have developed recently a solution framework, based on the concept of Wiener path integral, for stochastic response analysis and reliability assessment of diverse dynamical systems of engineering interest. Significant novelties and advantages that will be highlighted in this talk include:

i) The methodology can readily account for complex nonlinear/hysteretic behaviors, for fractional calculus modeling, as well as for non-white and non-Gaussian stochastic process representations. 

ii) High-dimensional systems can be readily addressed by relying on a variational formulation with mixed fixed/free boundary conditions, which renders the computational cost independent of the total number of degrees-of-freedom (DOFs) or stochastic dimensions; and thus, the ‘curse of dimensionality’ in stochastic dynamics is circumvented.

iii) The computational cost can be further drastically reduced by employing sparse representations for the system response probability density function (PDF) in conjunction with compressive sampling schemes and group sparsity concepts. 

Moreover, the methodology is capable of uncertainty quantification associated with the system response PDF estimate by relying on a Bayesian formulation.   

Various examples are presented and discussed pertaining to a wide range of engineering systems including, indicatively, a class of nonlinear electromechanical energy harvesters and a 100-DOF stochastically excited nonlinear dynamical system modeling the behavior of large arrays of coupled nano-mechanical oscillators.


Professor Ioannis A. Kougioumtzoglou received his five-year Diploma in Civil Engineering from the National Technical University of Athens (NTUA) in Greece (2007), and his M.Sc. (2009) and Ph.D. (2011) degrees in Civil Engineering from Rice University, TX, USA. He joined Columbia University in 2014, where he is currently an Associate Professor in the Department of Civil Engineering & Engineering Mechanics.

He is the author of approximately 150 publications, including more than 75 technical papers in archival International Journals. Prof. Kougioumtzoglou was chosen in 2018 by the National Science Foundation (NSF) to receive the CAREER Award, which recognizes early stage scholars with high levels of promise and excellence. He is also the 2014 European Association of Structural Dynamics (EASD) Junior Research Prize recipient “for his innovative influence on the field of nonlinear stochastic dynamics”.

Kougioumtzoglou is an Associate Editor for the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems and an Editorial Board Member of the following Journals: Mechanical Systems and Signal Processing, Probabilistic Engineering Mechanics, and International Journal of Non-Linear Mechanics. He is also a co-Editor of the Encyclopedia of Earthquake Engineering (Springer), and has served as a Guest Editor for several Special Issues in International Journals.

Kougioumtzoglou has co-chaired the ASCE Engineering Mechanics Institute Conference 2021 and Probabilistic Mechanics & Reliability Conference 2021 (EMI 2021 / PMC 2021), and has served in the scientific and/or organizing committees of many international technical conferences. Prof. Kougioumtzoglou is a member both of the American Society of Civil Engineers (M.ASCE) and the American Society of Mechanical Engineers (M.ASME), while he currently serves as a member of the ASCE EMI committees on Dynamics and on Probabilistic Methods. He is a Licensed Professional Civil Engineer in Greece, and a Fellow of the Higher Education Academy (FHEA) in the UK.


9-industry-600-min.jpgThis story demonstrates CMU's work toward attaining Sustainable Development Goal 9 of the 17 Global Goals to create a more equitable and viable planet by 2030.

A Unified Framework for Sequential Decisions Under Uncertainty

warren-powell

Warren B. Powell
Professor Emeritus
Princeton University
Chief Analytics Officer
Optimal Dynamics

Abstract

Sequential decisions are an almost universal problem class, spanning dynamic resource allocation problems, control problems, stopping/buy/sell problems, active learning problems, as well as two-agent games and multiagent problems.  Application settings span engineering, the sciences, transportation, health services, medical decision making, energy, e-commerce and finance.  A rich problem class involves systems that must actively learn about the environment.  We also consider hybrid resource allocation and learning problems such as those that arise in disease mitigation, as well as complex multiagent supply chains.

These problems have been addressed in the academic literature using a variety of modeling and algorithmic frameworks, including (but not limited to) dynamic programming, stochastic programming, stochastic control, simulation optimization, stochastic search, approximate dynamic programming, reinforcement learning, model predictive control, and even multiarmed bandit problems. Particularly frustrating is that these communities do not use a common modeling framework.

We are going to introduce a universal modeling framework that can be used for any sequential decision problem in the presence of different sources of uncertainty.  Our approach is to define the problem first, which consists of sequential decision problems (decision, information, decision, information, …) where the challenge is to find policies for making decisions.  We claim that there are four (meta)classes of policies that are the foundation of any solution approach that has ever been proposed for a sequential problem.  Using a simple energy storage problem, we show that any of the four classes of policies might work best depending on the data, and hybrids can be created that combine two or more classes.  All of these ideas will be illustrated with applications drawn from different application settings.


Warren B. Powell is Professor Emeritus at Princeton University, where he taught for 39 years, and is currently the Chief Analytics Officer at Optimal Dynamics.   He is the founder and director of CASTLE Labs, which spans contributions to models and algorithms in stochastic optimization, with applications to energy systems, transportation, health, e-commerce, and the laboratory sciences (see www.castlelab.princeton.edu). 

He has pioneered the use of approximate dynamic programming for high-dimensional applications, and the knowledge gradient for active learning problems.  His recent work has focused on developing a unified framework for sequential decision problems under uncertainty, spanning active learning to a wide range of dynamic resource allocation problems.  He has authored books on Approximate Dynamic Programming and (with Ilya Ryzhov) Optimal Learning, and is nearing completion of a book Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions.


9-industry-600-min.jpgThis story demonstrates CMU's work toward attaining Sustainable Development Goal 9 of the 17 Global Goals to create a more equitable and viable planet by 2030.

Embracing the Full Complexity of the Urban Atmosphere: Sources, Chemistry, Exposure, and Environmental Justice

 Albert Presto

Albert Presto
Research Professor
Mechanical Engineering
Carnegie Mellon Univeristy

Abstract

Exposure to ambient air pollution is a leading cause of death both in the US and worldwide. Air pollutant concentrations and source impacts change rapidly in space and time. These variations are especially large in urban areas, where the majority of the population lives and works.

This seminar describes our recent efforts to quantify these spatiotemporal gradients and to build exposure models that allow us to estimate population impacts of air pollution. We deployed both low-cost monitors and a mobile laboratory equipped with research-grade equipment to characterize intra-urban variations in air pollutant composition and concentrations. Sharp spatial gradients of particulate matter (PM), organic aerosol (OA), and black carbon (BC) concentrations exist at intra-city scales (<1 km) due to intense emissions from sources like traffic and cooking activities. 

By deploying an Aerodyne Aerosol Mass Spectrometer (AMS) and other high temporal resolution measurements on a mobile sampling platform, we are able to investigate the spatial variation of PM mass concentration, PM composition, and particle number concentrations within cities. Source apportionment with Positive Matrix Factorization (PMF) enables identification of the contributions of traffic and other sources to the observed PM mass. Cooking and traffic sources dominate PM spatial variability. For example, in Pittsburgh, 27.7% and 8.9% of the total population are exposed to >1 micrograms per cubic meter of traffic- and cooking-related primary emissions, with some populations exposed to high concentrations from both sources. Exposures at both the city and national level reveal patterns of environmental injustice. People of color are exposed to higher air pollution levels from multiple sources, independent of income.


Albert Presto is a Research Professor in the Department of Mechanical Engineering and Center for Atmospheric Particle Studies (CAPS) at Carnegie Mellon University. His group examines atmospheric emissions from energy production and use, the physical and chemical transformations those emissions undergo in the atmosphere, and subsequent human exposures.


11-sustain-cities-600-min.jpgThis story demonstrates CMU's work toward attaining Sustainable Development Goal 11 of the 17 Global Goals to create a more equitable and viable planet by 2030.

Exploring the Intersection Between Cities and Nature

 Erica Spiritos

Erica Spiritos (BS '11)
Preconstruction Manager
Timberlab

Abstract

I have dedicated my career to exploring our relationship with, and consumption of natural resources.  Of course, this narrative is easy (or easier) to craft in hindsight! Before getting started, I felt at a loss in my senior year as I contemplated a career ahead. I was graduating with an engineering degree but was motivated more by societal challenges than by technical ones. And I was afraid that my next step would set me on a permanent path in a direction I was not yet ready to name.  I’ve since learned that there is exciting and meaningful work to be done for engineers who may not want to crunch numbers all day, and that the next step is, thankfully, just one step.

In the ten years since completing my undergraduate degree in the CEE Department, I have worked for an international non-profit researching seawater desalination, then for the NYC Department of Environmental Protection on the construction of NYC’s drinking water treatment facility. And, in the in-between summers, I have grounded myself leading service-learning and wilderness trips for high school students in Ecuador, Costa Rica, Colorado and India.  Inspired by a talk given at a conference I attended in 2015, I pivoted into the mass timber industry. I’ve worked for my father’s real estate development company, for a mass timber manufacturer, helped launched a nationwide general contractor’s mass timber division, and now transformed that division into a separate business entity – Timberlab – focused on designing and building mass timber structures across the United States.

In this seminar, I will share some of the details and highlights of my career’s journey, and things to consider as you contemplate your own journey and next steps. 


Erica Spiritos graduated from the CEE department with a bachelor’s degree in 2011. She was raised in New York City, and decided to study engineering when she read a WIRED magazine interview with Google’s Larry Brilliant, who said engineers were going to solve the world’s problems. At Carnegie Mellon, she was a founding member of the Engineers Without Borders chapter and got her ya-yas out running laps around the track and in Schenley Park.

In her work, Spiritos is curious about how we can build ‘ecologically friendly’ cities that honor our dependence on natural resources. In her current role as Vice President and Preconstruction Manager of Timberlab,Spiritos brings mass timber dreams to life, nurturing projects to meet sustainability, architectural, and budgetary goals. An expert in mass timber project delivery with deep supply chain knowledge and a passion for sustainable wood sourcing and social justice, Spiritos was recently named by ThinkWood as one of six women innovating in AEC and Beyond.  She currently lives in Portland, Oregon with her partner and one-year-old twin sons.

 

Humanizing Engineering and Resilience

 Christine Kirchoff

Christine Kirchhoff
Assistant Professor
Civil and Environmental Engineering
Univeristy of 
Connecticut

Abstract

A range of stressors (extreme events, aging infrastructure, insufficient funding, in and out migration, lack of investment, and climate change) contribute to the persistent disruption of essential services and underperformance of critical infrastructure upon which our societies depend. My research aims at understanding how human and engineering systems interact to countermand these stressors and advance the sustainability and resilience of critical infrastructure.

In this talk, I will discuss my research in this area, and in particular, how the generation and use of science/scientific information, organizational and individual behavior, and governance approaches drive (or impede) resilient infrastructure systems.

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Dr. Christine J. Kirchhoff is an Associate Professor in the Department of Civil & Environmental Engineering at the University of Connecticut and holds the honorary title of Castleman Professor in Engineering Innovation. She is also a faculty affiliate of the Connecticut Institute for Resilience and Climate Adaptation and of the Department of Natural Resources and Environment.

Kirchhoff holds a B.S. in Civil Engineering, a M.S. in Environmental and Water Resource Engineering from the University of Texas, Austin and a Ph.D. in Resource Policy and Behavior from the University of Michigan and is a licensed professional engineer (TX). She received an NSF CAREER award in 2020.

Kirchhoff’s research focuses on the social studies of science, technology and public policy; the science of actionable knowledge; water governance, management, and regulatory compliance; and, the human dimensions of resilience, especially of water and wastewater infrastructure. Her work is supported by the National Science Foundation, U.S. Department of Agriculture, and the Connecticut Department of Public Health among others. In addition to 32 peer-reviewed publications to date, she is a co-author on the Connecticut climate assessment report, and the drinking water vulnerability and resilience assessment report for Connecticut and is a contributing author to the IPCC WGII Sixth Assessment Report, Chapter on Cities, Settlements and Key Infrastructure.

She serves as an Associate Editor for the Journal of the American Water Resources Association and the Bulletin of the American Meteorological Society and is a Science Advisor for Eos. She teaches undergraduate and graduate courses in civil and environmental engineering including Environmental Sustainability, Probability and Statistics, Water Resources Policy & Management, and research methods. In her free time, she enjoys baking, hiking, and spending time outdoors with family and friends.

Load Paths: One Structural Engineer's Career Advice on What To Do and What Not To Do

jeffie-chang

Jeffie Chang (BS '13, MS '14)

 

Abstract

In structural engineering, there are multiple solutions to a single problem. The most important consideration is the load path, how the loads imposed on the structure are transferred to the ground. There are often several load paths in a single structure. Similarly, there are many avenues to reach a career in structural engineering. This talk is but one engineer's experience. I will cover my own career path, two projects, and career advice for those who want to pursue structural engineering in the building industry. 


 Jeffie Chang is a building structural engineer who focuses on renovation work and adaptive reuse. Since graduating the Civil and Environemtnal Engineering department with a B.S. and M.S. from Carnegie Mellon University in 2014, she has been practicing in Chicago. After leaving a large international engineering company, Chang currently works at Silman's new Chicago office. Some of her past projects include Essex on the Park in Chicago, SC Johnson Headquarters renovation in Racine, and the Lincoln Park Zoo Lion House renovation in Chicago. Chang also actively volunteers with ACE Mentoring, where young professionals introduce the building industry to high school students. Outside of work, she really enjoys baking French pastries, cycling, knitting, and photography.