LAB Announcements

Spotlight

Bhagirath Addepalli

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 8th 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 1st 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 8th 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 92nd 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 60th 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, 59th 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, 58th 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

Cold Fog Amongst Complex Terrain (CFACT)

Fog in a cold pool in the Heber Valley at Solider Hollow, Utah

Supported by the National Science Foundation - PDM 2049100

CFACT website

Investigators, Senior Personnel, and Collaborators:
Zhaoxia Pu (Utah, Principal Investigator)
Eric Pardyjak (Utah, Co-Principal Investigator)

Senior Personnel:
Sebastian Hoch
Gannet Hallar
Ismail Gultepe

Postdocs:
Alexei Perelet
Students:

The project, Cold Fog Amongst Complex Terrain (CFACT), is to investigate cold fog formation in mountain valleys. Fog consists of tiny water droplets or ice crystals suspended in the air at or near the Earth’s surface and is considered as a type of low-lying cloud. Fog forms in high-elevation complex terrain as frequently as over water bodies but is less understood. Because of its impacts on visibility, fog is the second most common cause of weather-related aviation accidents after strong wind events. Fog forecasts have significant impacts on human activities, transportation, air quality, human health, and agriculture. Despite the impacts of fog and historical fog research, fog prediction remains a challenge for weather prediction because of complex interactions between land, water, and atmospheric conditions in fog formation. Poor fog forecasting skills reflect a lack of understanding of fog formation, development, and dissipation, which is the focus of the research. This study is expected to contribute to improving fog forecasting in mountainous regions, enhancing public awareness of fog-weather conditions, and information for decision-making. The project involves the participation of multiple institutions nationally and internationally with graduate and undergraduate training in both classrooms and the field.

The overarching goals of the CFACT project are to 1) investigate cold fog development and environment conditions in complex terrain with latest observation technology, 2) improve microphysical parameterizations and visibility algorithms used in numerical weather prediction (NWP) models, and 3) develop data-assimilation and analysis methods for current and next-generation (e.g., sub-kilometer scale) NWP models. The field project will be conducted in Heber Valley, Utah, during January and February 2022 with deployment of a network of ground-based in-situ instruments and remote sensing platforms to obtain comprehensive measurements of thermodynamic profiling, cloud microphysics, physical and chemical properties of aerosols, and dynamics of the environment. The Weather Research and Forecasting (WRF) model with various physical parameterizations and coupled land-atmosphere data assimilation capabilities will be used to facilitate the studies for improved fog prediction with NWP models. It is anticipated that the efforts will result in 1) improved understanding of cold-fog processes in complex terrain, 2) an evaluation of the bulk nucleation conditions that affect cold-fog microphysics related to visibility prediction, 3) identification of knowledge gaps in the micro- to synoptic- scale kinematic and thermodynamic processes associated with cold-fog life cycles in heterogeneous complex terrain, 4) understanding of interactions between physical (e.g., particle growth, nucleation, condensation, radiation) and dynamic mechanisms (e.g., turbulence, vertical air velocities, and wave motions) during the lifecycle of a fog event, 5) an evaluation of how land-surface conditions, especially snow on the ground, affect near-surface and boundary-layer atmospheric processes including the critical role of the surface radiative balance in cold-fog formation and evolution, and 6) improvement of microscales to mesoscales NWP-model simulations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.