Announcements

Thesis Defense: Amartya Bhattacharjee, “Fragmentation, Granular Transition & Impact Performance of Ceramics”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR LORI GRAHAM-BRADY, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Amartya Bhattacharjee

Friday, April 23, 2021

2 PM

Contact Elena Shichkova for access to this presentation.

Fragmentation, Granular Transition & Impact Performance of Ceramics

Brittle materials under impact loading exhibit a transition from a cracked solid to a granular medium. Appropriate representation of this transition to granular mechanics and the resulting initial fragment size and shape distribution in computational models is not well understood. The current work provides a numerical model to analyze competitive crack coalescence in the transition regime and provides insight into the onset of comminution and the initial conditions for subsequent granular flow. A simple phenomenological model has also been proposed that suggests a transition criterion resembling the one obtained from the numerical model.

A micromechanical multi-physics model for ceramics, that integrates key physical mechanisms, has been recalibrated using the new granular transition criterion and used to simulate impact experiments with boron carbide in ABAQUS. The integrative model is able to accurately reproduce some of the key cracking patterns of Sphere Indentation experiments and Edge On Impact experiments.

Based on this integrative model, linear regression has been used to study the sensitivity of Sphere Indentation model predictions to the input parameters. The sensitivities are connected to physical mechanisms, and trends in model outputs have been intuitively explored. These results help suggest material modifications that might improve material performance, prioritize calibration experiments for materials-by-design iterations, and identify model parameters that require more in-depth understanding.

Finally, the dependence of microstructure on fragment morphology has been examined via a modified version of the fragmentation and crack coalescence model. Fragment statistics predicted via the model are used to infer fragment morphology for different initial microstructures. Existing geomechanics literature then helps to link the trends to bulk granular friction.  The observations suggest that an optimal defect size and spacing in the initial intact ceramic will enhance impact performance as compared to fine dispersed defects in the ceramic matrix.

Thesis Defense: Hamid Foroughi, “Enhancing Seismic Resiliency of Steel Buildings through Three-Dimensional Modeling of Diaphragm System Interaction with Braced Frame”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR BENJAMIN SCHAFER, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Hamid Foroughi

Friday, February 19th

9 AM

Contact Elena Shichkova for access to this presentation.

Enhancing Seismic Resiliency of Steel Buildings through Three-Dimensional Modeling of Diaphragm System Interaction with Braced Frame

Steel deck diaphragms have a number of benefits such as low weight, competitive cost and a wide range of stiffness (from bare deck to composite floor systems). However, steel diaphragm design lacks a design paradigm consistent with seismic performance-based design. To consider the diaphragm system as an integral part of the building, and not just as a distribution element, the seismic performance of steel braced frame buildings can be assessed through material and geometric nonlinear dynamic analysis. Extensive efforts have been conducted in the past, employing 2D building models, and dynamic analysis to predict the collapse probability of steel building and justify seismic response modification coefficients (e.g., R) employed in equivalent lateral force-based design procedures. Little work has been performed on 3D building models where the vertical lateral force resisting system (LFRS) may interact with the floor diaphragm. This work aims to develop fundamental understanding of steel deck diaphragms as structural systems integrated within the overall building performance and improve strategies for accurate modeling of floor systems to enhance the overall structural resilience of the building. To achieve the research objectives, different diaphragm design scenarios based on ASCE 7-16, are investigated for a series of 1, 4, 8, and 12-story archetype buildings with special concentrically braced frame (SCBF) as vertical lateral force resisting system. FEMA P-695 methodology is used to assess the seismic performance of SCBF archetype buildings with different diaphragm response modification factor, Rs, that accounts for diaphragm ductility and propose a reasonable Rs values for the steel braced frame buildings.

 

Announcing the Spring 2021 CaSE Seminar Speakers

Below is a listing for the speakers being showcased during the Spring 2021 Civil and Systems Engineering Graduate Seminar Series. All civil engineering graduate seminars are FREE and open to the public. Attendance is required for all enrolled Civil and Systems Engineering graduate students.

All seminars will be held Thursdays from 12-1:25 PM EDT and hosted online until further notice.
For information on individual seminars, please refer to the Events Calendar.

January 21 – Prof. Ramteen Sioshansi, Department of Integrated Systems Engineering, Ohio State University

January 28 – Jay Wilson, Resilience Coordinator, Clackamas County Emergency Management

February 4 – Prof. Prashant Purohit, Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania

February 11 – Prof. Daria Terekhov, Department of Mechanical, Industrial and Aerospace Engineering, Concordia University

February 15 – Prof. Paris Perdikaris, Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania

February 25 – Jamie Padgett, Stanley C. Moore Professor in Engineering, Department of Civil and Environmental Engineering, Rice University

March 4 – Prof. Chia-Ming Uang, Department of Structural Engineering, University of California San Diego

March 10: Richard J. Carroll Memorial Lecture – Kara Kockelman, Dewitt Greer Centennial Professor of Transportation Engineering, Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin

March 11– Carri Chan, Associate Professor of Business, Division of Decision, Risk, and Operations, Columbia Business School

March 18 – Curt Bronkhurst, Professor and Associate Chair for Undergraduate Studies, Department of Engineering Physics, University of Wisconsin-Madison

April 1 – Roger Ghanem, Gordon S. Marshall Professor of Engineering Technology and Professor of Civil and Environmental Engineering, University of Southern California

April 8 – John van de Lindt, George T. Abell Professor in Infrastructure, Department of Civil and Environmental Engineering, Colorado State University

April 15 – Prof. Bruno Sudret, Department of Civil, Environmental, and Geomatic Engineering, ETH Zurich

April 29 – Rema Padman, Trustees Professor of Management Science And Healthcare Informatics, Carnegie Mellon University

Thesis Defense: Qi Wang, “System Dynamics and Machine Learning Techniques for Studying Resilience in Public Health”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR TAKERU IGUSA, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

QI WANG

Tuesday, December 22

11:00 AM

Contact Elena Shichkova for access to this presentation.

“System Dynamics and Machine Learning Techniques for Studying Resilience in Public Health”

Systems Dynamics (SD) and Machine Learning (ML) are analytical methods that are becoming more broadly applied to studies in public health. This dissertation focuses on public health aspects of resilience, with an emphasis on distressed populations. We analyze a broad array of topics, including community resilience to natural disasters, suicide prevention interventions, cognitive resilience to aging effects, and interventions to mitigate the impacts of community violence on children.  We also include SD and ML studies in early childhood educational investment and a Bayesian analysis of wiki-surveys.

We begin with the development and calibration of a system dynamics model of community resilience, COPEWELL. We propose a stepwise approach to developing a measure set that combines domain expertise with statistical analyses. For our second study, we use SD to analyze processes of suicide prevention for refugees living in migration camps in Thailand to understand their causes, consequences, and mechanisms. An SD model is used to show the different impacts of proposed interventions on rates of suicide ideation and attempts. In our third study, we explore a novel application of supervised ML to study time-varying processes of cognitive reserve and resilience in an aging population in Baltimore City. For our fourth study, we worked with researchers at the United Stated Agency for International Development (USAID) and World Vision International to build an SD model of community violence in gang-controlled urban neighborhoods in Honduras and El Salvador. The long-term goal in this collaborative effort is to design interventions that would promote child protection against violence. An interactive webpage was developed for stakeholders to visualize the model and explore influential factors. In our fifth study, we use reinforcement learning to model parental investment in early childhood development. We integrate this model with an economics-based model of children human capital formation. We use Bayesian updating to assess the future state of the stock of human capital. In our sixth study, we construct and calibrate an SD model to examine the influence of community factors on suicide risk. This study lays the foundation for a larger project to examine the impact on community-based support programs such as home visitation programs on the rates of suicidal behaviors. In the final application of this thesis, we demonstrate a scoring and ranking approach for analyzing the results of wiki-survey voting using a maximum a posteriori probability (MAP) estimate. Two case studies are examined to test the accuracy of the estimating procedure.

This thesis demonstrates the broad applicability of system dynamics and machine learning methods on high-priority public health research topics. Mathematical details and software code are provided in the appendix for researchers interested in this growing direction of research.

 

Thesis Defense: Shravan Kumar Reddy Kotha, “Parametrically Homogenized Constitutive Models for Titanium Alloys ”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR SOMNATH GHOSH, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

SHRAVAN KUMAR REDDY KOTHA

Monday, December 14, 2020

3 PM

Contact Elena Shichkova for access to this presentation.

“Parametrically Homogenized Constitutive Models for Titanium Alloys”

            Structural analysis of heterogeneous materials using phenomenological constitutive models, is often faced with inaccuracies stemming from the lack of connection with the material microstructure and underlying physics. Pure micromechanical analysis, on the other hand, is computationally prohibitive on account of the large degrees of freedom needed to represent the entire structure. Hierarchical multiscale models based on computational homogenization, have been proposed to determine the homogenized material response for heterogeneous materials that can be used in component-scale analysis. However, for nonlinear problems involving history-dependent constitutive relations, many multiscale methods incur prohibitive computational costs from solving the micromechanical problem for every macroscopic point in the computational domain.

To overcome these shortcomings, this thesis develops a computationally efficient, Parametrically Homogenized Constitutive Model (PHCM) for dual-phase α/β Titanium alloys such as Ti6242S. PHCMs incorporate characteristic microstructural features as well as underlying physical mechanisms of deformation in macro-scale constitutive models. A size, rate and temperature dependent Crystal Plasticity Finite Element Model (CPFE) has been used to characterize the micro-mechanisms of deformation in dual-phase Titanium alloys. Statistically Equivalent Representative Volume Elements (SERVEs) are constructed to study the influence of different microstructural morphological and crystallographic distributions such as crystallographic orientation distribution, misorientation distribution, grain size distribution etc. on homogenized response. A detailed sensitivity analysis is performed to identify important microstructural distributions that govern the macroscopic material response and Representative Aggregated Microstructural Parameters (RAMPs) that quantify these distributions are defined. The constitutive equations in PHCM are then chosen to represent different homogenized mechanical behaviors observed from CPFE analysis such as elasto-plastic anisotropy, tension-compression asymmetry, grain size, strain rate and temperature dependency etc.. A database of SERVEs with different morphology and crystallographic distributions is created and CPFE simulations are performed under a variety of loading cases. The constitutive parameters of PHCM equations are calibrated to match its response with that obtained from CPFE analysis. These constitutive parameters are related to corresponding RAMPs using functional forms obtained from machine learning. A finite deformation formulation of PHCM constitutive equations is implemented in Abaqus as a user material subroutine. Using PHCM, microstructure-sensitive structural simulations of a representative ortho-grid panel are performed to demonstrate the microstructural dependency of structural response and the computational efficiency of PHCM. Moreover, the PHCM based predictions are compared with those obtained from isotropic elasticity and J2 plasticity models to demonstrate their deficiency.

Finally, the PHCM model for dual-phase Titanium alloys is extended to include the effects of damage. An anisotropic, coupled plasticity-damage model is formulated in which plasticity and damage are coupled via a Helmholtz free energy density function. Based on homogenized stress-strain response and crack propagation behaviors observed from coupled crystal plasticity-phase field simulations, an anisotropic damage surface and damage evolution equations are proposed. The proposed plasticity-damage model accounts for tension-compression asymmetry and strain rate dependency of damage and its thermodynamic consistency is established. Numerical results that demonstrate different aspects of the coupled plasticity-damage model are discussed at the end.

JOB OPPORTUNITY: Full-time Lecturer in the Area of Systems Engineering

The Whiting School of Engineering at Johns Hopkins University seeks applicants for a full-time teaching position (Lecturer) in the area of systems engineering to be part of the teaching faculty in the department of Civil and Systems Engineering (CaSE). This position will serve a key role in the department’s new program in Systems Engineering and the growing Center for Systems Science and Engineering (CSSE). More experienced candidates may be considered for a Senior Lecturer position.

This is a career-oriented, renewable appointment that is responsible for the development and delivery of undergraduate and graduate courses to those majoring in Civil and/or Systems Engineering. Some potential areas for instruction could include: data sciences, mathematical modeling, risk analysis, network modeling, optimization, or any course at the intersection of systems engineering and civil infrastructure. The Whiting School of Engineering has a well-established non-tenure track career path for full-time teaching faculty culminating in the rank of Teaching Professor.

The successful candidate will be expected to help articulate the role of systems engineering in undergraduate and graduate education, particularly in the context of a department that broadly covers the areas of systems, structures, and mechanics of materials. See the department website for more information (case.wse.jhu.edu). Teaching faculty members are encouraged to engage in departmental and university service and may have advising responsibilities. In particular, this position is likely to include some administrative responsibilities related to oversight of our full-time M.S. degree program in Systems Engineering and to coordination of the ABET accreditation process for Systems Engineering. Such activities will offset some of the teaching responsibilities of the position.

Qualifications:

Applicants for the position must have a Ph.D. degree in Systems Engineering or a closely related field. Related professional experience is considered a plus. Successful applicants must also have demonstrated excellence in, and commitment to, teaching, and have excellent communication skills.

Application Instructions

Applicants should apply online at https://apply.interfolio.com/81347. Please include a cover letter and a CV and, optionally, a brief teaching portfolio including (sample) course evaluations from any classes taught by the applicant. While candidates who complete their applications by January 15, 2021 will receive full consideration, the Department will consider exceptional applicants at any time.

The Johns Hopkins University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration without regard to any characteristic protected by law.

Center for Systems Science and Engineering (CSSE) Seeks PhD Candidates on Grand Societal Challenges Using Systems Thinking and Methods

The Department of Civil and Systems Engineering (CaSE) has recently launched a PhD Program in Systems Engineering. The Center for Systems Science and Engineering  (CSSE), housed in CaSE, has already had major impact with the COVID tracking dashboard used around the world. We are seeking highly motivated applicants (either master’s or exceptional undergraduate students) interested in pursuing doctoral research on grand societal challenges using systems thinking and methods.

Our faculty’s cutting-edge research addresses a range of domains including healthcare, public health, transportation, space, and energy. We are also closely tied to other major centers at Johns Hopkins including the Malone Center for Engineering in Healthcare, the Institute for Assured Autonomy, the Applied Physics Laboratory, and the Bloomberg School of Public Health. Our multidisciplinary program allows the students to explore topics from different fields including applied math, computer science, operations research, operations management, environmental sciences, and data sciences.

Prospective students should review our website, consult the academic requirements and the application process. Contact either Professors Lauren Gardner ([email protected]), Kimia Ghobadi ([email protected]), Gregory Falco ([email protected]), or Tak Igusa ([email protected]) for more information.

 

Autonomy OWL Lab Seeks PhD Candidates with Interests in Space Systems, Smart Cities, Space Habitation, Critical Infrastructure, or Space Systems Cybersecurity

Interested in doing a PhD on Space SystemsSmart Cities, Space Habitation, Critical Infrastructure, or Space Systems Cybersecurity? Consider applying for a PhD in the Department of Civil and Systems Engineering and joining the Autonomy OWL lab!

All OWL PhD students will have an office at our new lab space at the Institute for Assured Autonomy and benefit from exposure to both the Whiting School of Engineering and the Applied Physics Laboratory. They will also be fully funded for the duration of their PhD studies.

Our lab is highly interactive and has close ties to industry, the startup ecosystem and government sponsors making for a vibrant environment to conduct field-defining research.

We encourage applicants that have two or more of the following:

  • Prior industry experience;
  • Some research background, exposure/interest;
  • Interest in using AI or investigating questions of AI assurance/trust/security/safety;
  • Ambitions of starting companies or entrepreneurial tendencies;
  • A really hard systems problem that needs solving.

A technical educational background is strongly encouraged.

Contact [email protected] for more information.

Announcing the Fall 2020 CaSE Seminar Series Speakers

Below is a listing for the speakers being showcased during the Fall 2020 Civil and Systems Engineering Graduate Seminar Series. All civil engineering graduate seminars are FREE and open to the public. Attendance is required for all enrolled Civil and Systems Engineering graduate students. For information on individual seminars, please refer to the Events Calendar.

All seminars will be held Thursdays from 12-1:25 PM EDT and hosted online until further notice. Please contact Carla Diaz for connection details.

October 1 – Marcelo Giguale, Director World Bank

October 8 – Jean -Francois Molinari, Director, Computational Solid Mechanics Laboratory, EPFL

October 15 – Robert Bachus, Senior Principal, Geosyntec Consultants

October 29 – Steve WaiChing Sun, Associate Professor, Dept. of Civil Engineering and Engineering Mechanics, Columbia University

November 5 – Amy M. Cohn, Arthur F. Thurnau Professor, Dept. of Industrial & Operations Engineering, University of Michigan

November 12 – Lesley Sneed, Professor and Stirrat Faculty Scholar, Dept. of Civil, Architectural and Environmental Engineering, Missouri S&T University

November 19 – Karen Smilowitz, James N. and Margie M. Krebs Professor in Industrial Engineering and Management Sciences, Northwestern University

December 3 – Luke Bisby, Chair of Fire and Structures, Dept. of Civil and Environmental Engineering, University of Edinburgh

Thesis Defense: Aakash Bangalore Satish, “Multimodel Bayesian estimation of total uncertainty and its application to modeling the yield strength of structural aluminum at elevated temperature”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR MICHAEL SHIELDS, ASSOCIATE PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

AAKASH BANGALORE SATISH

Monday, August 24, 2020

1 PM

Contact Elena Shichkova for access to this presentation.

“Multimodel Bayesian estimation of total uncertainty and its application to modeling the yield strength of structural aluminum at elevated temperature”

In the multimodel approach, inference is based on an ensemble of model classes.  Uncertainties in the model  probabilities and parameter values are estimated from data using Bayesian inference. While the epistemic uncertainty in the estimates of parameter values and model form are accounted for in literature on Bayesian multimodel inference, the epistemic uncertainty in the estimates of model probabilities is often ignored. When working with small data sets, however, there might be large epistemic uncertainty in the model probabilities.

This thesis presents a Bayesian multimodel approach to quantify the total uncertainty in random variables quantified from limited data, which often serve as inputs to computational models of engineering systems. The novelty of this approach is that it builds on existing Bayesian multimodel methods by integrating into them the treatment of epistemic uncertainty in model probabilities. In this approach, model probabilities are treated as random variables and their posterior distribution is obtained by Bayesian inference. The mode of this posterior distribution quantifies the epistemic uncertainty in the model form, and the marginals quantify the epistemic uncertainty in the model probabilities.

The quantified uncertainty is propagated through computational models of engineering systems using samples drawn from the posterior predictive distribution, which incorporates the aleatory uncertainty as well as the epistemic uncertainty in the model probabilities, model form, and parameters of the set of input model classes. Then, importance sampling is employed to explicitly quantify the uncertainty in the outputs due to each kind of input uncertainty, by post-processing the outputs.

The proposed approach was applied to the estimation of total uncertainty in the yield strength of aluminum 6061-T6 at elevated temperatures, using data derived from an extensive testing program. A total of 100 steady-state uniaxial tension tests were conducted at six temperatures using material sourced off-the-shelf from nine different batches to study the variability in the stress-strain response of aluminum 6061-T6. Multimodel inference is employed using this data to estimate the design value and reduction factor for tensile yield strength incorporating epistemic uncertainty in the model probability, model form, and parameters used to model the variability in the yield strength.

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