Announcements

Thesis Defense: Marietta Squire, “Mathematical Modeling and the Prevention of Healthcare-Associated Infections”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR TAKERU IGUSA, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Marietta Squire

Monday, July 27, 2020

11 AM

Contact Elena Shichkova for access to this presentation.

“Mathematical Modeling and the Prevention of Healthcare-Associated Infections”

Hospital construction, renewal, and sustainment involve complex processes as a result of rapid change in healthcare technology and information systems technology, changing practices of care, and the ongoing presence of varied bacterial and viral threats. Quality of care is in many ways predicated upon the quality and safety of the environment upon which the patient receives care. Hospitals operate twenty-four hours a day at staff levels that are often not adequate for the number of patients being seen. This further emphasizes the importance of ensuring that a hospital is designed and operated in the safest manner possible, for both patients and staff.

This thesis develops novel methods and toolsets that can be implemented during the hospital design phase as well as during hospital operations, to help ensure patient and staff safety are paramount. These methods quantify the clinical impacts of infection control as well as associated costs and savings, prior to intervention implementation. The Hospital Energy model addresses the management and sustainment of critical care when operating within a distressed power grid environment. These quantitative tools provide an objective assessment of how to best allocate resources and energy within fiscal constraints. Both the Infection De-escalation model and Hospital Energy model are then adapted and expanded to address SARS-CoV-2 transmission in hospitals. The excess energy and economic cost of implementing both ultraviolet light decontamination and negative pressure treatment rooms in hospitals are evaluated through the integration of these two models.

Thesis Defense: Xiaohui Tu, “Developing Image-based Crystal Plasticity Models for Deformation and Crack Propagation in Polycrystalline 7000-series Aluminum Alloys”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR SOMNATH GHOSH, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Xiaohui Tu

Thursday, July 23, 2020

11 AM

Contact Elena Shichkova for access to this presentation.

Developing Image-based Crystal Plasticity Models for Deformation and Crack Propagation in Polycrystalline 7000-series Aluminum Alloys

This dissertation develops various models for image-based crystal plasticity FEM modeling of deformation and fracture mechanisms of 7000 series Aluminum alloys. The work begins with the development of preprocessors for micromechanical analysis of polycrystalline-polyphase microstructures of Al alloys, such as Al7075-T651. Starting from input data in the form of electron backscatter diffraction (EBSD) and scanning electron microscopy (SEM) maps of orthogonal surfaces of experimental specimens, a robust methodology is created for generating 3D statistically equivalent virtual microstructures (3D-SEVMs) by a 3D stereological projection of 2D statistical distribution and correlation functions using a genetic algorithm (GA)-based numerical algorithm. Validation of the SEVM reconstruction process is conducted by comparing the SEVM statistics with morphological and crystallographic distributions of grains and precipitates from the experiments. Microstructure-based statistically equivalent representative volume element (M-SERVE) that corresponds to the minimum sized SERVE for convergence of morphological or crystallographic distributions are established using the Kolmogorov–Smirnov (KS) tests. Property-based statistically equivalent RVE (P-SERVE), defined as the smallest SERVE for predicting response functions (both effective and local), is estimated by conducting crystal plasticity finite-element simulations. Convergence plots of material response functions are used to assess the P-SERVE. These convergence analyses reveal that the controlling factor for the SERVE size is local extreme values of stress and strain, as well as the two-point correlation function of precipitates and precipitate-grain correlations.

A coupled crystal plasticity-phase field (CP-PF) model is next used for analyzing crack nucleation and propagation in polycrystalline-polyphase microstructures of metallic alloys. The model explicitly represents elastic and plastic anisotropies, tension-compression asymmetry, and the crack surface topology in the material. The phase-field model incorporates a regularization length-scale 𝑙𝑙𝑐𝑐 that controls the sharpness of the phase-field approximation to the discrete crack. Recently, to incorporate fracture energy anisotropy, the scalar fracture toughness 𝐺𝐺𝑐𝑐 is extended to an orientation-dependent tensor form and is represented in terms of crystallographic planes and their corresponding fracture energies. The development enables favorable crack growth on intrinsically weak planes in crystals. The coupled crystal plasticity-crack phase-field variational formulation is solved by a novel, wavelet-enriched adaptive FE framework. It has the unique capability of optimally resolving high gradients in the phase-field order parameter near the crack surface, and creating adaptive, multi-resolution wavelet-based hierarchical enrichment of the FE model.

Coupled deformation and crack nucleation-propagation simulations in polyphase-polycrystalline microstructures of Aluminum 7000 alloys are performed under monotonic (mode I, II) and cyclic loading conditions. As shown in these micromechanical analyses, the crack evolution in Aluminum 7000 alloys occurs in three stages, viz. crack initiation and propagation inside precipitates, the coalescence of precipitate cracks and crack propagation in the matrix. Surface precipitates play a dominant role in both the precipitate cracking and matrix cracking stages. Surface precipitates generally fail earlier compared to interior precipitates. Dominant cracks are formed by coalescence of precipitate pairs that include surface precipitates.

Thesis Defense: Fardad Haghpanah, “Multi-Scale Evacuation Models To Support Emergency And Disaster Response”

THE DEPARTMENT OF CIVIL AND SYSTEMS ENGINEERING

AND

ADVISOR BENJAMIN W. SCHAFER, PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Fardad Haghpanah

Tuesday, June 23, 2020

3:30PM

“Multi-Scale Evacuation Models To Support Emergency And Disaster Response”

Evacuation is a short-term measure to mitigate human injuries and losses by temporarily relocation of exposed population before, during, or after disasters. With the increasing growth of population and cities, buildings and urban areas are over-populated which brings about safety issues when there is a need for emergency evacuation. In disaster studies, simulation is widely used to explore how natural hazards might evolve in the future, and how societies might respond to these events. Accordingly, evacuation simulation is a potentially helpful tool for emergency responders and policy makers to evaluate the required time for evacuation and the estimated number and distribution of casualties under a disaster scenario.

The healthcare system is an essential subsystem of communities which ensures the health and well-being of their residents. Hence, the resilience of the healthcare system plays an essential role in the resilience of the whole community. In disasters, patient mobility is a major challenge for healthcare systems to overcome. This is where the scientific society enters with modeling and simulation techniques to help decision-makers. Hospital evacuation simulation considering patients with different mobility characteristics, needs, and interactions, demands a microscopic modeling approach, like Agent-Based Modeling (ABM). However, as the system increases in size, the models become highly complex and intractable. Large-scale complex ABMs can be reduced by reformulating the micro-scale model of agents by a meso-scale model of population densities and partial differential equations, or a macro-scale model of population stocks and ordinary differential equations. However, reducing microscopic models to meso- or macro-scale models implies certain drawbacks.

This dissertation contributes to the improvement of large-scale agent-based evacuation simulation and multi-scale hospital evacuation models.  For large-scale agent-based models, application of bug navigation algorithms, popular in the field of robotics, is evaluated to improve the efficiency of such models. A candidate bug algorithm is proposed based on a performance evaluation framework, and its applicability and practicability are demonstrated by a real-world example. For hospital evacuation simulation, crowd evacuation considering people with different physical and mobility characteristics is modeled on three different scales: microscopic (ABM), mesoscopic (fluid dynamics model), and macroscopic (system dynamics model). Similar to the well-known Predator-Prey model, the results of this study show the extent to which macroscopic and mesoscopic models can produce global behaviors emerging from agents’ interactions in ABMs. To evaluate the performance of these multi-scale models, the evacuation of the emergency department at Johns Hopkins University is simulated, and the outputs and performance of the models are compared in terms of implementation complexity, required input data, provided output data, and computation time.

Cancellation of Richard J. Carroll Memorial Lectureship

The Whiting School and Johns Hopkins University’s approach to the COVID-19 epidemic is guided by our commitment to the safety and security of our community, our constituents, and our visitors.  With that, we have determined it is prudent to cancel or postpone any Whiting-sponsored events or activities, on or off campus, that involve 25 people or more until at least the end of April.

Unfortunately, that means that tonight’s Richard J. Carroll Memorial Lectureship will be cancelled.

We sincerely apologize for any inconvenience this might cause.

Announcing the Spring 2020 Graduate Seminar Speakers

Below is a listing for the speakers being showcased during the Spring 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.

For directions and information on parking please see Maps & Directions link at www.jhu.edu and select information on Homewood Campus.

Post-Doctoral Fellowship: Network Modeling of Infectious Diseases

Post-Doctoral Fellowship: Network Modeling of Infectious Diseases

Applications are invited for a full-time postdoctoral position at the Department of Civil Engineering and the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University under the supervision of Associate Professor Lauren Gardner. The applicant will be expected to undertake and develop research on the topic of spatial epidemiology, with a focus on the development of models to infer outbreak risk factors, predict outbreaks, and optimize resource allocation for outbreak mitigation. Candidates should have expertise in one or more of the following areas: network modelling, optimization, machine learning, statistical modelling, and data visualization, with previous experience working on epidemiological applications.

The postdoc will work closely with an international multidisciplinary team of faculty and Ph.D. students across Engineering and Public Health. In addition, the PI will make every effort to mentor the postdoc for transition into a faculty position. This includes guidance on grant-writing, teaching opportunities, and translation of research. Women and Underrepresented Minorities are highly encouraged to apply. This is a year-long postdoc that can potentially be extended up to two years upon satisfactory performance and availability of funding.

SELECTION CRITERIA

The candidate will be expected to:

  • Possess a PhD degree in computer science, engineering, applied or computational mathematics, or a closely related field.
  • Have expertise in one or more of the following areas: network modelling, machine learning, statistical modelling, data visualization.
  • Previous experience working on epidemiological applications.
  • Strong programming and data visualization skills.
  • Demonstrated experience in analyzing large scale data sets.
  • Demonstrated experience in working on large-scale multi-disciplinary projects
  • The ability to work effectively as part of a multi-disciplinary research team
  • Illustrate the motivation and discipline to carry out autonomous research.
  • High level interpersonal, written and oral communication skills in English.
  • A record of research accomplishment as reflected in publications in peer-reviewed journals and conferences and presentations at scientific meetings.

Start date is flexible. Review of applications will begin immediately and continue until the position is filled. Complete applications should include the following (in a single pdf file) to l.gardner@jhu.edu:

(1) A cover letter

(2) A full curriculum vitae

(3) Up to two research publications and/or preprints

(4) The names and contact information for three references

(5) (Optional) A one-page original research proposal on the topic of your choosing, with the following headings: Motivation, Research Questions, Research Approach, Methods, Data Sources, Timeline.

Thesis Defense: Mikhail Osanov, “Topology Optimization for Additive Manufacturing: from Mechanical Components to Orthopaedic Implants”

THE DEPARTMENT OF CIVIL ENGINEERING

AND

ADVISOR JAMES GUEST, ASSOCIATE PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Mikhail Osanov

Thursday, September 26, 2019

1:30PM

Shriver Board Room

“Topology Optimization for Additive Manufacturing: from Mechanical Components to Orthopaedic Implants”

Abstract:

Additive Manufacturing (AM) is a free-form fabrication technique that creates structures in a layer-by-layer fashion. Topology Optimization is a free-form, systematic approach to designing structures. These technologies are therefore well-suited for each other, but must be integrated to fully leverage their capabilities. This dissertation seeks to more tightly couple Topology Optimization by proposing several novel algorithms that improve manufacturability of the optimized parts and components. These include cylindrical projection method, which mimics the layer-by-layer nature of Additive Manufacturing processes, and several extensions to overhang projection methods for eliminating support structures, including providing access points for easy removal of support structures, eliminating internal voids, accounting for build plate post-processing costs, and utilizing the overhang constraint within the design of support structures. These algorithms are demonstrated on several design examples and solutions are shown to be directly manufacturable, thereby requiring less post-processing operations that can be time and cost intensive.

The final Chapter of this dissertation is dedicated to the design of femoral implants used in Total Hip Arthroplasty (THA). With the growing number of yearly total joint replacements and the demand for improved mobility and quality of life, the need for high-performance implants is apparent. In this work we seek to alleviate the existing clinical issue of stress shielding, pertinent to current state-of-the-art implants, through new designs using Topology Optimization. We propose a novel Topology Optimization formulation that is capable of addressing regional stress levels in bone by manipulating the topology of the implant, and demonstrate solutions that are predicted to reduce stress shielding effects compared to implants that are currently used in practice.

Thesis Defense: Anindya Bhaduri, “Adaptive Construction of Surrogate Functions for Various Computational Mechanics Models”

THE DEPARTMENT OF CIVIL ENGINEERING

AND

ADVISOR LORI GRAHAM-BRADY, PROFESSOR AND CHAIR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

Anindya Bhaduri

Friday, September 20, 2019

2:00PM

Latrobe 106

“Adaptive Construction of Surrogate Functions for Various Computational Mechanics Models”

Abstract:

In most science and engineering fields, numerical simulation models are often used to replicate physical systems. An attempt to imitate the true behavior of complex systems results in computationally expensive simulation models. The models are more often than not associated with a number of parameters that may be uncertain or variable. Propagation of variability from the input parameters in a simulation model to the output quantities is important for better understanding the system behavior. Variability propagation of complex systems requires repeated runs of costly simulation models with different inputs, which can be prohibitively expensive. Thus for efficient propagation, the total number of model evaluations needs to be as few as possible. An efficient way to account for the variations in the output of interest with respect to these parameters in such situations is to develop black-box surrogates. It involves replacing the expensive high-fidelity simulation model by a much cheaper model (surrogate) using a limited number of the high-fidelity simulations on a set of points called the design of experiments (DoE).

In this talk, a couple of examples related to newly developed adaptive black-box surrogate constructions are presented first to demonstrate the usefulness of surrogate construction in general. Then we consider an LS-DYNA simulation model of a continuum level plain weave S-2 glass/SC-15 epoxy composite plate under ballistic impact by a cylinder projectile. The goal is to develop an efficient computational framework for generation of probabilistic penetration response of the plate using surrogates. More specifically, this study involves construction of adaptive classification surrogates in order to generate two important quantities of interest, the probabilistic velocity response (PVR) curve as a function of the projectile impact velocity, and the ballistic limit velocity prediction as a function of the strength parameters of the plate model.

Announcing the Fall 2019 Graduate Seminar Speakers

Below is a listing for the speakers being showcased during the Fall 2019 Civil Engineering Graduate Seminar Series. All civil engineering graduate seminars are FREE and open to the public. Attendance is required for all enrolled Civil Engineering graduate students. For information on individual seminars, please refer to the Events Calendar.

For directions and information on parking please see Maps & Directions link at www.jhu.edu and select information on Homewood Campus.

 

Thesis Defense: May Thu Nwe Nwe, “Topology Optimization of Truss Structures Considering Stress and Stability Constraints”

THE DEPARTMENT OF CIVIL ENGINEERING

AND

ADVISOR JAMIE GUEST, ASSOCIATE PROFESSOR

ANNOUNCE THE THESIS DEFENSE OF

Doctoral Candidate

May Thu Nwe Nwe 

Thursday, August 1, 2019

8:30AM

Latrobe 106

“Topology Optimization of Truss Structures Considering Stress and Stability Constraints”

Abstract:

Topology optimization is a free-form approach to designing efficient structural layouts. Although highlighted repeatedly in literature for its ability to identify creative, high performance designs, it is also well known that oversimplification of the underlying optimization formulation can lead to impractical structural solutions. A common truss optimization problem formulation is to minimize linear elastic strain energy for a given structural mass (or minimize mass subject to a linear elastic deformation constraint). The optimal solutions obtained from such a formulation are independent of the direction of the applied load and often include members that may readily fail due to yielding or buckling, and/or colinear members with unbraced hinges that are unstable. Such solutions are, of course, impractical from structural engineering perspective. Incorporating stress and stability metrics into the topology optimization formulation, however, involves significant mathematical challenges primarily due to the possibility of vanishing members, which ultimately leads to singularities and disjointed regions in the design space that gradient-based optimization struggles to navigate. This thesis reviews and discusses these challenges and explores a disaggregated formulation where design and state variables are treated as free optimization variables to enable consideration of stress, (member) buckling, and global (system) stability metrics in a mathematically consistent manner. The impact of various constraints and objectives on the optimized solutions is demonstrated for simple truss design problems. The presented results clearly show that the incorporation of stress, member buckling, and global stability metrics results in more realistic design solutions. Future directions of research are also discussed.

 

 

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