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Research Projects - UNR

Fighting Wildfires: A Data-Informed, Physics-Based Computational Framework for Probabilistic Risk Assessment and Mitigation and Emergency Response Management

September 2020 - September 2025

Through a cross-disciplinary multi-institution collaboration, we are awarded a prestigious project from NSF LEAP-HI program to create an overarching computational platform for wildfire risk management at multiple spatial and temporal scales. This vision will be accomplished by creating and integrating transdisciplinary scientific knowledge and techniques in the fields of data harnessing (viz., collection, processing, fusion, and uncertainty quantification), computational modeling (viz., wildfire, urban-fire, and social quality-of-life models), stochastic simulation, and model-based inference. I serve as the Principal Investigator (PI) on this project.

Funding amount: $2,000,000

Learning from Real-World Data to Inform High-Fidelity Modeling: Bayesian Model Updating for Identification of Soil-Structure-Interaction Dynamics Considering Material Nonlinearity

September 2020 - September 2021

In this project, we propose the development a model inversion framework that can be used to back-calculate the soil-structure-interaction (SSI) model parameters from the seismic response of real-world buildings. The proposed model inversion framework is based on a Bayesian Finite Element (FE) model updating techniques to integrate the measurement data with mechanics-based models for parameter estimation and uncertainty quantification. The framework has been previously applied to estimate the SSI parameters considering low-amplitude earthquake records and linear models. This project takes the next step in extending this framework into the nonlinear realm. Extending to nonlinear realm enables us to consider various levels of earthquake excitation to devise proper modeling guidance considering the nonlinearity in the behavior of structural and soil domain. I serve as the Principal Investigator (PI) on this project, which is funded by USGS.

 

Funding amount: $81,130

Optimal Sensor Placement for Physics-Based Digital Twins

To be started in 2021

Funded by the Department of Energy (DOE) National Offshore Wind Research and Development Consortium, the project is focused on developing a novel digital twining technique for operational monitoring and diagnosis of fixed-pole offshore wind turbines. This is a collaborative project led by Tufts University. I serve as a team member and UNR lead on this project.

Funding amount (UNR portion): $180,021

Digital Twins for Bridge Management through the Integrating of Computer Vision Techniques and Finite Element Models

September 2018 - March 2023

Through SC Solutions, we have received a Small Business Innovative Research (SBIR) award (Phase I & II) from the U.S. Department of Transportation (U.S. DOT) to develop a novel technology solution for operational monitoring and damage diagnosis of bridges. I served as the Principal Investigator (PI) on both phases of this project, and upon joining UNR, my position changed to Co-PI and UNR lead on the second phase, due to the requirements of the SBIR program. Along with our team at SC Solutions and UCLA, we will execute this exciting research and technology development project. 

 

Phase I funding amount: $149,180 (September 2018 – March 2019)

Phase II funding amount: $999,303 – UNR portion: $125,162 (October 2019 – March 2023)

Improving the Safety of Rebar Cages by using Innovative Connectors

January 2020 - January 2023

The proposed study will improve the safety of pile shaft and slurry wall rebar cages that are commonly used for foundations of high-rise buildings and bridges. Innovative mechanical connectors, such as U-bolts, wire rope connectors, and similar, will be used at strategic locations (template hoops) along the rebar cage in lieu of tie-wire. These reliable connections will increase the stiffness and strength of the rebar cage, and thus, increase construction productivity, improve safety, and reduce construction cost. Mitigating failure in rebar cages will provide immediate benefit to construction team and project owner. This project is funded through ASCE Construction Institute and Charles Pankow Foundation with contributions received from several industry partners.

Funding amount (cash and in-kind): $310,240

Applications of Elastomeric Polymers for Accelerated Bridge Construction and Retrofit

April 2020 - April 2021

This project takes the first step of a long-term research vision to examine and investigate the innovative applications of elastomeric polymers and specifically polyurea coating in accelerated bridge construction. The focus of this project is on the application of elastomeric polymer coatings for design and retrofit of side bridge girders. We plan for an experimental-analytical research effort, to develop simple phenomenological material models for the polyurea coating system and to investigate the potential cost-benefit of the coating in design and retrofit of side girders. The project is funded by the Accelerated Bridge Construction University Research Center (ABC-UTC).

Funding amount: $60,000

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