Login: My Utah.edu

First time logging on?
Go HERE First.

LAB Announcements

SLC lawn watering recommendation
EFD Lab awarded new NSF grant to study cold fog forming in mountain valleys May 2021
Sustainability growing at the U with the GCSC

Spotlight

Bhagirath Addepalli

Hometown: Hyderabad, India

Program: PhD (Graduated May 2012)

Current Position: Microsoft Program Manager

Research Interests: Fundamental and applied research in fluid dynamics, inverse and optimization techniques, and statistical modeling and analysis of data. Specifically, interests include: laboratory experiments, computational fluid dynamics, Lagrangian random-walk modeling, development of novel case-specific objective functionals (metrics) for inverse problems, development of efficient and robust optimization and inversion techniques spanning deterministic, stochastic (frequentist), and Bayesian methods, multiple criteria decision making (MCDM - Pareto optimality), linear and nonlinear regression techniques for stochastic modeling, statistical modeling of time series data, model selection in inverse problems.

Publications:
A) Journal Publications / Pre-prints:
a) Addepalli, B., K. Sikorski, E.R. Pardyjak and M.S. Zhdanov. Source characterization of atmospheric releases using stochastic search and regularized gradient optimization. Inverse Problems in Science and Engineering, 2011. 19(8): p. 1097-1124.
b) Addepalli, B. and E.R. Pardyjak. A pseudo-metric to handle zero measurements and predictions in atmospheric inverse-source problems. Under review. Submitted to Inverse Problems in Science and Engineering.
c) Addepalli, B. and E.R. Pardyjak. Investigation of flow structure in step-up street canyons. Ready to be submitted to Boundary Layer Meteorology. Pre-print available upon request.
d) Addepalli, B. and E.R. Pardyjak. Study of flow fields in asymmetric step-down street canyons. Ready to be submitted to Boundary Layer Meteorology. Pre-print available upon request.
e) Addepalli, B., E.R. Pardyjak, P. Willemsen and D.E. Johnson. Urban form optimization for air quality applications using simulated annealing and genetic algorithms. Ready to be submitted to Atmospheric Environment. Pre-print available upon request.
f) Addepalli, B. Markov Chain Monte Carlo annealing for atmospheric inverse-source problems. To be submitted to Inverse Problems in Science and Engineering. Pre-print available upon request.

B) Peer-reviewed Conference Publications:
a) Addepalli, B., K. Sikorski, E.R. Pardyjak and M.S. Zhdanov. Quasi-Monte Carlo, Monte Carlo, and regularized gradient optimization methods for source characterization of atmospheric releases. in Dagstuhl Seminar Proceedings 09391, Algorithms and Complexity for Continuous Problems. 2009. Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany.
b) Addepalli, B. and E.R. Pardyjak. Study of flow fields in asymmetric step-down street canyons. in The International Workshop on Physical Modelling of Flow and Dispersion Phenomena (PHYSMOD). 2007. University of Orleans, France.

C) Conference Publications:
a) Pardyjak, E.R., Addepalli, B., et al., Impact of green infrastructure on urban microclimate and air quality, in the 8^th International Conference on Urban Climate - ICUC 8. 2012: Dublin, Ireland.
b) Addepalli, B. and C. Sikorski, A note on objective functions for atmospheric inverse-source problems, in second National Conference in Advancing Tools and Solutions for Nuclear Material Detection. 2011: Salt Lake City, UT.
c) Addepalli, B. and C. Sikorski, Efficient adaption of simulated annealing and genetic algorithms to atmospheric inverse-source problems, in AIChE Annual Meeting. 2010: Salt Lake City, UT.
d) Addepalli, B. and C. Sikorski, Tools to characterize the source of hazardous releases, in 1^st National Conference on Advancing Tools and Solutions for Nuclear Material Detection. 2010: Salt Lake City, UT.
e) Addepalli, B., M.J. Brown, E.R. Pardyjak and I. Senocak. Evaluation of the QUIC-URB wind model using wind-tunnel data for step-up street canyons, in Seventh Symposium on the Urban Environment. 2007: San Diego, CA.
f) Addepalli, B. and E.R. Pardyjak. 2D PIV Measurements of street canyon flow for buildings with varying angles and separation distances. in American Meteorological Society Sixth Symposium on the Urban Environment. 2006: Atlanta, GA.

D) Conference Presentations:
a) Addepalli, B., E.R. Pardyjak, P. Willemsen and D.E. Johnson. GPU-MCDM: A new module of the Quick Urban and Industrial Complex (QUIC) dispersion modeling system for urban form optimization. in the 8^th International Conference on Urban Climate - ICUC 8. 2012: Dublin, Ireland.
b) Addepalli, B., E.R. Pardyjak, P. Willemsen and D.E. Johnson. Development of a multiple criteria decision making (MCDM) tool for urban form optimization. in 92^nd AMS Annual Meeting. 2012: New Orleans, LA.
c) Addepalli, B., E.R. Pardyjak, P. Willemsen and D.E. Johnson. Urban form optimization for air quality applications using simulated annealing and genetic algorithms. in Ninth Symposium on the Urban Environment. 2010: Keystone, CO.
d) Addepalli, B., M.J. Brown, E.R. Pardyjak and I. Senocak. Investigation of the flow structure around step-up, step-down, deep canyon, and isolated tall building configurations using wind-tunnel PIV measurements, in Seventh Symposium on the Urban Environment. 2007: San Diego, CA.
e) Addepalli, B., E.R. Pardyjak and M.J. Brown. The effect of geometry on the wake structure of a surface mounted obstacle. in 60^th Annual Meeting of the APS Divison of Fluid Dynamics. 2007: Salt Lake City, UT.
f) Addepalli, B. and E.R. Pardyjak. Experimental investigation of the effect of Reynolds number and HΔ value on flow fields in street canyons with cubical Buildings. in American Physical Society, 59^th Annual Meeting of the APS Division of Fluid Dynamics. 2006: Tampa Bay, FL.
g) Addepalli, B. and E.R. Pardyjak. 2D PIV measurements of flow between a pair of model buildings with varying geometries. in American Physical Society, 58^th Annual Meeting of the Division of Fluid Dynamics. 2005: Chicago, IL.

E) Technical Reports:
a) Addepalli, B., C. Sikorski and E.R. Pardyjak. Source Characterization of atmospheric releases using quasi-random sampling and gradient optimization. Report submitted to the School of Computing, University of Utah. Report number: UUCS 09-001.
b) Nelson, M., B. Addepalli, D. Boswell and M.J. Brown. QUIC Start Guide (v 4.5). Los Alamos National Labratory. LA-UR-07-2799.

Contact: addbugs@gmail.com

PREEVENTS Track 2: A fast-response wildland fire modeling framework for prediction and risk assessment

Fire Vortex at the USDA Fire Sciences Lab in Missoula

Supported by the National Science Foundation - PREEVENTS 1664175

Investigators, Senior Personnel, and Collaborators:
Steven Krueger (Utah, Principal Investigator)
Jan Mandel (CU, Denver, Co-Principal Investigator)
Peter Willemsen (Univ. of Minn., Duluth, Co-Principal Investigator)
Eric Pardyjak (Utah, Co-Principal Investigator)
Adam Kochanski (Utah, Co-Principal Investigator)
Rob Stoll (Utah, Senior Personnel)
Mary Ann Jenkins (Utah, Senior Personnel)
Natailie Wagenbrenner (Collaborator, USDA Fire Sciences Lab)

Students:

Wildfires are increasingly common throughout the US and have significant impacts on populated areas. Current rapid-response management is based on empirical or semi-empirical models developed more than 40 years ago. The focus of this project is to create a Multistage Wildfire Research and Prediction System (MWRPS) that links several existing community, open source models developed. This new model has the potential to change how fire is studied, and significantly improve operational wildfire and smoke forecasting. MWRPS will serve as tool for fire professionals, urban and environmental planners, and disaster managers who need to determine the societal and ecological impacts of wildfire and smoke. As a community model, MWRPS will be available to the public to examine a variety of hazard-related issues. In addition to graduate student and postdoctoral training, the project includes a plan for K-12 outreach through the Hi-GEAR program. Sudden changes in flow at the fire line are crucial to extreme fire behavior and associated hazards. Because flow at the fire line can significantly impact fire spread and subsequently all wildfire behavior, prediction and simulation of coupled atmosphere-fire flow must be accurate from synoptic down to fire line scales. Accurate prediction requires the ability to model rapid synoptically-driven changes in local winds, realistically render flow in complex terrain, and capture the impacts of the fire itself on local weather. To meet this challenge, the Multistage Wildfire Research and Prediction System (MWRPS), a multi-scale model, 3D model will be developed based on fundamental fluid dynamical principles. MWRPS will have the ability to resolve buildings, trees, and land cover, to incorporate the effects of complex terrain, different vegetation types and geometries, to disperse smoke, and to represent radiation, sensible, and latent heating in the wildfire environment. Predicted wildfire properties from this model will include high resolution temporal and spatial evolution of the fire perimeter and intensity; behavior for both surface and crown fires; smoke production and dispersion in the Wildland Urban Interface (WUI) or through tree canopies (crucial for planning a proposed prescribed burn); and impacts of smoke concentrations and of heat flux in safety zones and on WUI structures. In addition to the model development, three aspects of extreme wildfire behavior will be addressed: the roles of (1) fuel heterogeneity, (2) complex topography, and (3) fire interactions. A data-driven system will be developed for atmosphere-fire models to steer simulations from a multitude of sources including: weather data, sensors, airborne fire images, and satellite remote sensing in a statistically sound manner.