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Global 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

EFD Lab DEID Data Visualization

Please note these data are experimental. These data are only here to allow people immediately involved in the project quick access. The user assumes the entire risk associated with its use of these data. The University of Utah shall not be held liable for any use or misuse of the data described and/or contained herein. The User bears all responsibility in determining whether these data are fit for the User's intended use.

Figure 1 (above) Profile of snow accumulation and snow density (% water)

Figure 2 (above) SWE accumulation as a function of time.

Figure 3 (above) SWE rate as a function of time.

Figure 4 (above) Visibility (km) as a function of time. (maximum visibility is set 10 km)

Figure 5 (above) Profile of snow accumulation (in mm) and % water and snowflake complexity is on the right y-axis.

Figure 6 (above) Time series of snow-liquid-ratio (SLR).

Figure 7 (above) Stability index. As the stability index approaches one the likelihood of a natural avalanche increasess.

Figure 8 (above) Expected time to failure.

Figure 9 (above) Basal layer stength and overburden stress.

The DEID is a new hydrometeor (snow and rain) measurement device. The acronym stands for Differential Emissivity Imaging Disdrometer, which is being developed at the Universtiy of Utah. DEID data discussion will go here. This site is currently under construction.

Development of the DEID has been supported by a sub-contract to the University of Utah through a grant to Particle Flux Analytics Inc from the U.S. Department of Energy (DOE) Atmospheric System Research program award number DE-SC0016282. A patent is pending. The DEID work has also been made possible by the Transportation Avalanche Research Pool (TARP), AltaDave Richards and the Alta Avalanche Office, and the U.S. National Science Foundation (grant number PDM-1841870).