5 Aug 2022

South Pole Station Snowdrift Model

Abstract: The elevated building at Scott-Amundsen South Pole Station was designed to mitigate the effects of windblown snow on it and the surrounding infrastructure. Because the elevation of the snow surface increases annually, the station is periodically lifted on its support columns to maintain its design height above the snow surface. To assist with planning these lifts, this effort developed a computational model to simulate snowdrift formation around the elevated building. The model uses computational fluid dynamics methods and synthetic wind record generation derived from statistical analysis of meteorological data. Simulations assessed the impact of several options for the lifting operation on drifts surrounding the elevated building. Simulation results indicate that raising the eastern-most building section (Pod A), or the entire station all at once, can reduce drift accumulation rates over the nearby arches structures. Long-term analyses, spanning 5–6 years, determine whether an equilibrium drift condition may be reached after a long period of undisturbed drift development. These simulations showed that after about 6 years, the rate of growth of the upwind drift slows, appearing to approach an equilibrium condition. However, the adjacent drifts were still increasing in depth at a roughly linear rate, indicating that equilibrium for those drifts was still several seasons away.

5 Aug 2022

SAGE-PEDD Theory Manual: Modeling Windblown Snow Deposition around Buildings

Abstract: Numerical modeling of snowdrifting is a useful tool for assessing the im-pact of building design on operations and facility maintenance. Here we outline the theory for the SAGE-PEDD snowdrift model that has applica-tion for determining snowdrift accumulation around buildings. This model uses the SAGE computational fluid dynamics code to determine the flow field in the computational domain. A particle entrainment, dis-persion, and deposition (PEDD) model is coupled to SAGE to simulate the movement and deposition of the snow within the computational do-main. The report also outlines areas of future development that upgrades to the SAGE-PEDD model should address.

5 Aug 2022

SAGE-PEDD User Manual

Abstract: SAGE-PEDD is a computational model for estimating snowdrift shapes around buildings. The main inputs to the model are wind speed, wind direction, building geometry and initial ground or snow-surface topography. Though developed mainly for predicting snowdrift shapes, it has the flexibility to accept other soil types, though this manual addresses snow only. This manual provides detailed information for set up, running, and viewing the output of a SAGE-PEDD simulation.

5 Aug 2022

Simulating Environmental Conditions for Southwest United States Convective Dust Storms Using the Weather Research and Forecasting Model v4.1

Abstract: Dust aerosols can pose a significant detriment to public health, transportation, and tactical operations through reductions in air quality and visibility. Thus, accurate model forecasts of dust emission and transport are essential to decision makers. While a large number of studies have advanced the understanding and predictability of dust storms, the majority of existing literature considers dust production and forcing conditions of the underlying meteorology independently of each other. Our study works towards filling this research gap by inventorying dust-event case studies forced by convective activity in the Desert Southwest United States, simulating select representative case studies using several configurations of the Weather Research and Forecasting (WRF) model, testing the sensitivity of forecasts to essential model parameters, and assessing overall forecast skill using variables essential to dust production and transport. We found our control configuration captured the initiation, evolution, and storm structure of a variety of convective features admirably well. Peak wind speeds were well represented, but we found that simulated events arrived up to 2 hours earlier or later than observed. Our results show that convective storms are highly sensitive to initialization time and initial conditions that can preemptively dry the atmosphere and suppress the growth of convective storms.

12 Jul 2022

A Tutorial on the Rapid Distortion Theory Model for Unidirectional, Plane Shearing of Homogeneous Turbulence

Abstract: The theory of near-surface atmospheric wind noise is largely predicated on assuming turbulence is homogeneous and isotropic. For high turbulent wavenumbers, this is a fairly reasonable approximation, though it can introduce non-negligible errors in shear flows. Recent near-surface measurements of atmospheric turbulence suggest that anisotropic turbulence can be adequately modeled by rapid-distortion theory (RDT), which can serve as a natural extension of wind noise theory. Here, a solution for the RDT equations of unidirectional plane shearing of homogeneous turbulence is reproduced. It is assumed that the time-varying velocity spectral tensor can be made stationary by substituting an eddy-lifetime parameter in place of time. General and particular RDT evolution equations for stochastic increments are derived in detail. Analytical solutions for the RDT evolution equation, with and without an effective eddy viscosity, are given. An alternative expression for the eddy-lifetime parameter is shown. The turbulence kinetic energy budget is examined for RDT. Predictions by RDT are shown for velocity (co)variances, one-dimensional streamwise spectra, length scales, and the second invariant of the anisotropy tensor of the moments of velocity. The RDT prediction of the second invariant for the velocity anisotropy tensor is shown to agree better with direct numerical simulations than previously reported.

23 May 2022

Ballistic Protection Using Snow

Abstract: Small (5.56 mm, 7.62 mm and 9 mm) and medium (12.7 mm) arms rounds were fired at snow-filled 1.5m cubic gabions in a mid-winter condition in Fairbanks, Alaska. The rounds were excavated and penetration by each ammunition type was measured. A distribution and average of penetration depth was determined. All 320 rounds fired were captured within 1.5m after entering the snow barrier. Comparison with published models of ballistics penetration of snow showed mixed results with several matching our data within 10% and all but one within 32%. However, most of these models are simplistic in that they accommodate limited variables and therefore may not be expected to perform well in all settings. We conclude that snow-based ballistics protection structures can be quickly and efficiently erected in suitable environments and with minimal size, can provide reliable protection against small and medium arms fire.

2 May 2022

Summary of Ground-Based Snow Measurements for the Northeastern United States

ABSTRACT: Snow is an important resource for both communities and ecosystems of the Northeastern United States. Both flood risk management and water supply forecasts for major municipalities, including New York City, depend on the collection of snowpack information. Therefore, the purpose of this study is to summarize all of the snowpack data from ground-based networks currently available in the Northeast. The collection of snow-depth and snow water equivalent information extends back several decades, and there are over 2,200 active sites across the region. Sites are distributed across the entire range of elevations in the region. The number of locations collecting snow information has increased substantially in the last 20 years, primarily from the expansion of the CoCoRaHS (Community Collaborative Rain, Hail, and Snow) network. Our summary of regional snow measurement locations provides a foundation for future studies and analysis, including a template for other regions of the United States.

31 Mar 2022

Continued Investigation of Thermal and Lidar Surveys of Building Infrastructure

ABSTRACT: We conducted a combined lidar and thermal infrared survey from both ground-based and Unmanned Aerial System (UAS) platforms at McMurdo Station, Antarctica, in February 2020 to assess the building thermal envelope and infrastructure of the Crary Lab and the wet utility corridor (utilidor). These high-accuracy, coregistered data produced a 3-D model with assigned temperature values for measured surfaces, useful in identifying thermal anomalies and areas for potential improvements and for assessing building and utilidor infrastructure by locating and quantifying areas settlement and structural anomalies. The ground-based survey of the Crary Lab was similar to previous work performed by the team at both Palmer (2015) and South Pole (2017) Stations. The UAS platform focused on approximately 10,500 linear-feet of utilidor throughout McMurdo Station. The datasets of the two survey areas overlapped, allowing us to combine them into a single, georeferenced 3-D model of McMurdo Station. Coincident exterior temperature and atmospheric measurements and Global Navigation Satellite System real-time kinematic surveys provided further insights. Finally, we assessed the thermal envelope of the Crary Lab and the structural features of the utilidor. The resulting dataset is available for analysis and quantification.

25 Mar 2022

Assessment of the COVID-19 Infection Risk at a Workplace Through Stochastic Microexposure Modeling

Abstract: The COVID-19 pandemic has a significant impact on economy. Decisions regarding the reopening of businesses should account for infection risks. This paper describes a novel model for COVID-19 infection risks and policy evaluations. The model combines the best principles of the agent-based, microexposure, and probabilistic modeling approaches. It takes into account specifics of a workplace, mask efficiency, and daily routines of employees, but does not require specific interagent rules for simulations. Likewise, it does not require knowledge of microscopic disease related parameters. Instead, the risk of infection is aggregated into the probability of infection, which depends on the duration and distance of every contact. The probability of infection at the end of a workday is found using rigorous probabilistic rules. Unlike previous models, this approach requires only a few reference data points for calibration, which are more easily collected via empirical studies. The application of the model is demonstrated for a typical office environment and for a real-world case. The proposed model allows for effective risk assessment and policy evaluation when there are large uncertainties about the disease, making it particularly suitable for COVID-19 risk assessments.

15 Mar 2022

Autonomous GPR Surveys using the Polar Rover Yeti

Abstract: The National Science Foundation operates stations on the ice sheets of Antarctica and Greenland to investigate Earth’s climate history, life in extreme environments, and the evolution of the cosmos. Understandably, logistics costs predominate budgets due to the remote locations and harsh environments involved. Currently, manual ground-penetrating radar (GPR) surveys must preceed vehicle travel across polar ice sheets to detect subsurface crevasses or other voids. This exposes the crew to the risks of undetected hazards. We have developed an autonomous rover, Yeti, specifically to conduct GPR surveys across polar ice sheets. It is a simple four-wheel-drive, battery-powered vehicle that executes autonomous surveys via GPS waypoint following. We describe here three recent Yeti deployments, two in Antarctica and one in Greenland. Our key objective was to demonstrate the operational value of a rover to locate subsurface hazards. Yeti operated reliably at −30 ◦C, and it has good oversnow mobility and adequate GPS accuracy for waypoint-following and hazard georeferencing. It has acquired data on hundreds of crevasse encounters to improve our understanding of heavily crevassed traverse routes and to develop automated crevasse-detection algorithms. Importantly, it helped to locate a previously undetected buried building at the South Pole. Yeti can improve safety by decoupling survey personnel from the consequences of undetected hazards. It also enables higher-quality systematic surveys to improve hazard-detection probabilities, increase assessment confidence, and build datasets to understand the evolution of these regions. Yeti has demonstrated that autonomous vehicles have great potential to improve the safety and efficiency of polar logistics.