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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Synoptic scale wind field properties from the SEASAT SASS

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

Pierson, W. J., Jr.↗
DOE OSTI2023

RADWIND Project Final Technical Report

The Rural Area Distributed Wind Integration Network Development (RADWIND) Project (January 2020-April 2023) was undertaken by NRECA Research, a not-for-profit subsidiary of NRECA focused on underwritten research, with the support of DOE. The project was part of the Wind Energy Technologies Office’s (WETO’s) Wind Integration for Rural Economic Development (WIRED) program, which was developed out of an October 2018 workshop in which NRECA participated in. RADWIND’s end of project goal was “to raise awareness of distributed wind as a solution for the energy, resiliency, and economic development needs of electric cooperatives, and to provide resources and information that reduce barriers and lower costs for co-ops seeking to deploy distributed wind. Through this project, NRECA Research seeks to establish a national distributed wind presence for and by NRECA’s members that delivers these benefits and plans to communicate NRECA’s members that properly deployed distributed wind can be a bankable technology option for rural America.”

17 WIND ENERGY↗
NASA NTRS1997

Earth-Based Radio Tracking of the Galileo Probe for Jupiter Wind Estimation

Although the Galileo probe was designed to communicate only to the orbiter, the probe radio signal was detected at two Earth-based radio observatories where the signal was a billion times weaker. The measured signal frequency was used to derive a vertical profile of the jovian zonal wind speed. Due to the mission geometry, the Earth-based wind estimates are less sensitive to descent trajectory errors than estimates based on probe-orbiter Doppler measurements. The two estimates of wind profiles agree qualitatively; both show high wind speeds at all depths sampled.

Folkner, W. M.↗
NASA NTRS2012

Communicating the Threat of a Tropical Cyclone to the Eastern Range

The 45th Weather Squadron (45 WS) has developed a tool to help visualize the Wind Speed Probability product from the National Hurricane Center (NHC) and to help communicate that information to space launch customers and decision makers at the 45th Space Wing (45 SW) and Kennedy Space Center (KSC) located in east central Florida. This paper reviews previous work and presents the new visualization tool, including initial feedback as well as the pros and cons. The NHC began issuing their Wind Speed Probability product for tropical cyclones publicly in 2006. The 45 WS uses this product to provide a threat assessment to 45 SW and KSC leadership for risk evaluations with an approaching tropical cyclone. Although the wind speed probabilities convey the uncertainty of a tropical cyclone well, communicating this information to customers is a challenge. The 45 WS continually strives to provide the wind speed probability information to customers in a context which clearly communicates the threat of a tropical cyclone. First, an intern from the Florida Institute of Technology (FIT) Atmospheric Sciences department, sponsored by Scitor Corporation, independently evaluated the NHC wind speed probability product. This work was later extended into a M.S. thesis at FIT, partially funded by Scitor Corporation and KSC. A second thesis at FIT further extended the evaluation partially funded by KSC. Using this analysis, the 45 WS categorized the probabilities into five probability interpretation categories: Very Low, Low, Moderate, High, and Very High. These probability interpretation categories convert the forecast probability and forecast interval into easily understood categories that are consistent across all ranges of probabilities and forecast intervals. As a follow-on project, KSC funded a summer intern to evaluate the human factors of the probability interpretation categories, which ultimately refined some of the thresholds. The 45 WS created a visualization tool to express the timing and risk for multiple locations in a single graphic. Preliminary results on an on-going project by FIT will be included in this paper. This project is developing a new method of assigning the probability interpretation categories and updating the evaluation of the performance of the NHC wind speed probability analysis.

Winters, Katherine A.↗
DOE OSTI2013

Assessment of Offshore Wind Farm Effects on Sea Surface, Subsurface and Airborne Electronic Systems (Final Report)

Offshore wind energy is a valuable resource that can provide a significant boost to the US renewable energy portfolio. A current constraint to the development of offshore wind farms is the potential for interference to be caused by large wind farms on existing electronic and acoustical equipment such as radar and sonar systems for surveillance, navigation and communications. The US Department of Energy funded this study as an objective assessment of possible interference to various types of equipment operating in the marine environment where offshore wind farms could be installed. The objective of this project was to conduct a baseline evaluation of electromagnetic and acoustical challenges to sea surface, subsurface and airborne electronic systems presented by offshore wind farms. To accomplish this goal, the following tasks were carried out: (1) survey electronic systems that can potentially be impacted by large offshore wind farms, and identify impact assessment studies and research and development activities both within and outside the US, (2) engage key stakeholders to identify their possible concerns and operating requirements, (3) conduct first-principle modeling on the interactions of electromagnetic signals with, and the radiation of underwater acoustic signals from, offshore wind farms to evaluate the effect of such interactions on electronic systems, and (4) provide impact assessments, recommend mitigation methods, prioritize future research directions, and disseminate project findings. This report provides a detailed description of the methodologies used to carry out the study, key findings of the study, and a list of recommendations derived based the findings.

17 WIND ENERGY↗
DOE OSTI2017

Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. Our paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power forecasts. This conceptual analysis of the state of the art highlights that: (i) end-users should start to look at the forecast's properties in order to map different uncertainty representations to specific wind energy-related user requirements; (ii) a multidisciplinary team is required to foster the integration of stochastic methods in the industry sector. Furthermore, a set of recommendations for standardization and improved training of operators are provided along with examples of best practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distributed Wind Monitoring Best Practices

Accessible performance and operational data have been identified as a key enabler for distributed wind energy industry advancement. While utility-scale wind turbines benefit from reliable and continuous supervisory control and data acquisition (SCADA)-based monitoring platforms, monitoring of the U.S. fleet of distributed wind (DW) turbines has been more inconsistent, unreliable, and sometime difficult to access. Without fleet monitoring data, the industry will never understand and thus work to improve turbine under-performance and reliability issues. For the DW industry to scale up, attract investors, and boost credibility, fleetwide monitoring must be robust and reliable, select data must be made accessible to stakeholders, and the data must be in a format useful to users. To help move the industry toward a more standardized, accessible stream of monitoring data, this distributed wind monitoring best practices report attempts to cover topics including key monitoring channels, hardware, communication strategies, and accessibility. Strategic engagement with DW original equipment manufacturers (OEMs), service providers, lab and university researchers, testing organization, certification bodies, end users and solar photovoltaic (PV) monitoring experts has enabled a better understanding of the current state-of-the-art of monitoring and aided in articulating this set of best practices that will guide OEMs toward harmonized monitoring strategies, aimed at a future goal of achieving accessible performance and operational data for the entire fleet of U.S. distributed wind turbines.

17 WIND ENERGY↗
DOE OSTI2025

Repurposing Offshore Oil and Gas Platforms to Support Wind Power Generation

B. Gibbs, J. McAvoy, S. T. Nutakki and R. Seetharam, "Repurposing Offshore Oil and Gas Platforms to Support Wind Power Generation," 2025 IEEE International Communications Energy Conference (INTELEC), Houstin, TX, USA, 2025, pp. 215-221, doi: 10.1109/INTELEC63987.2025.11214768.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2003

Optimal Observations for Variational Data Assimilation

An important aspect of Ocean state estimation is the design of an observing system that allows the efficient study of climate aspects in the ocean. A solution of the design problem is presented here in terms of optimal observations that emerge as nondimensionalized singular vectors of the modified data resolution matrix. The actual computation is feasible only for scalar quantities in the limit of large observational errors. In the framework of a lo resolution North Atlantic primitive equation model it is demonstrated that such optimal observations when applied to determining the strength of the volume and heat transport across the Greenland-Scotland ridge, perform significantly better than traditional section data. On seasonal to inter-annual time-scales optimal observations are located primarily along the continental shelf and information about heat-transport, wind stress and stratification is being communicated via boundary waves and advective processes. On time-scales of about a month, sea surface height observations appear to be more efficient in reconstructing the cross-ridge heat transport than hydrographic observations. Optimal observations also provide a tool for understanding how the ocean state is effected by anomalies of integral quantities such as meridional heat transport.

Koehl, Armin↗
NASA NTRS2008

Wake Turbulence Mitigation for Departures (WTMD) Prototype System - Software Design Document

This document describes the software design of a prototype Wake Turbulence Mitigation for Departures (WTMD) system that was evaluated in shadow mode operation at the Saint Louis (KSTL) and Houston (KIAH) airports. This document describes the software that provides the system framework, communications, user displays, and hosts the Wind Forecasting Algorithm (WFA) software developed by the M.I.T. Lincoln Laboratory (MIT-LL). The WFA algorithms and software are described in a separate document produced by MIT-LL.

Sturdy, James L.↗
NASA NTRS2017

An Automaton Rover Enabling Long Duration In-Situ Science in Extreme Environments

The Automaton Rover for Extreme Environments (AREE) is a NASA Innovative Advanced Concept (NIAC) funded study focused on enabling long duration science on Venus by replacing vulnerable electronics with an entirely mechanical design. By utilizing high temperature alloys, the rover would survive on the surface of Venus for weeks if not months. The rover concept harvests wind energy using a turbine and stores it in a constant force spring. The mobility system would be guided by a mechanical computer and logic system, programed to carry out the mission. It would collect basic science data such as wind speed, temperature, and seismic events. Communicating the data back to Earth is the most challenging aspect of the system design with multiple options being explored in a trade: a simple electronic high temperature transponder, a retroreflector target or inscribing phonograph style records to be launched via a balloon to a high altitude drone capable of transmitting the data back to Earth. AREE is not only a new exciting in-situ rover concept, but also a paradigm shift to conducting in-situ science in extreme environments. Traditional extreme environment vehicles collect as many diverse data points as possible in the short period of time before system failure. AREE breaks that trend by exploring what can be done with only a few basic scientific measurements, but recorded over long periods of time. In addition to Venus, the concept can be useful in other extreme environments in the solar system including Mercury, Jupiter's radiation belts, the interiors of gas giants, the mantle of the Earth and volcanoes throughout the solar system.

Parness, Aaron↗
NASA NTRSDate not supplied

Informing New Concepts for UAS and Autonomous System Safety Management using Disaster Management and First Responder Scenarios

As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.

In Time Aviation Safety Management System↗
NASA NTRS2006

Global Aspects of Heliosphere-Geosphere Coupling

The magnetosphere serves both to hold off the solar wind and to couple it selectively to the Earth through the auroral zones. It has long been understood that the plasmasphere consists of geogenic plasmas that expand out of the sunlit low latitude ionosphere, but it was initially assumed that the hot low density plasma beyond the plasmasphere is largely of solar wind origin with a minor admixture of ionospheric plasmas, discovered via mass spectrometric observations in the early 70's. Since then, elaborate simulation models have been developed that have taken us from an era of cartoon physics to a new era of quantitative global comparisons between observations and theory. In most current global circulation models of the magnetosphere, the ionospheric load on the system is taken to lie exclusively in the thin F layer of the ionosphere. This layer is coupled with solar wind and magnetospheric plasmas via Maxwell stresses communicated by field aligned current systems, and with the thermosphere via ion-neutral charge exchange and Coulomb collisions. However, recent observations have shown us that ionospheric plasmas flow sporadically in various forms into the plasmasphere and up into the high latitude circulation cells of the outer magnetosphere, as driven by the solar wind and its variable intensity and magnetic field. Under some conditions, ionospheric material is observed to be the principal component of plasmas at the dayside magnetopause and in the plasma sheet and ring current regions. Given a global model of magnetospheric circulation, it is relatively straightforward to investigate the behaviors of ionospheric plasmas in response to solar wind drivers, and we report the results of such efforts here. We find that ionospheric plasmas dominate the plasma pressure in the magnetosphere in some regions, particularly when the solar wind is especially intense and-or southward directed. This result violates the assumption that the ionospheric load is confined to the F layer, and shows that the ionosphere is often an important dynamic element of the solar wind-ionosphere system throughout the magnetosphere, especially during larger geospace storms. This means that future global circulation models must account for ionospheric plasma inertia, heat capacity, and pressure, to be quantitatively credible.

Moore, Thomas E.↗
DOE OSTI2012

Aleutian Pribilof Islands Wind Energy Feasibility Study

Under this project, the Aleutian Pribilof Islands Association (APIA) conducted wind feasibility studies for Adak, False Pass, Nikolski, Sand Point and St. George. The DOE funds were also be used to continue APIA's role as project coordinator, to expand the communication network quality between all participants and with other wind interest groups in the state and to provide continued education and training opportunities for regional participants. This DOE project began 09/01/2005. We completed the economic and technical feasibility studies for Adak. These were funded by the Alaska Energy Authority. Both wind and hydro appear to be viable renewable energy options for Adak. In False Pass the wind resource is generally good but the site has high turbulence. This would require special care with turbine selection and operations. False Pass may be more suitable for a tidal project. APIA is funded to complete a False Pass tidal feasibility study in 2012. Nikolski has superb potential for wind power development with Class 7 wind power density, moderate wind shear, bi-directional winds and low turbulence. APIA secured nearly $\$$1M from the United States Department of Agriculture Rural Utilities Service Assistance to Rural Communities with Extremely High Energy Costs to install a 65kW wind turbine. The measured average power density and wind speed at Sand Point measured at 20m (66ft), are 424 W/m2 and 6.7 m/s (14.9 mph) respectively. Two 500kW Vestas turbines were installed and when fully integrated in 2012 are expected to provide a cost effective and clean source of electricity, reduce overall diesel fuel consumption estimated at 130,000 gallons/year and decrease air emissions associated with the consumption of diesel fuel. St. George Island has a Class 7 wind resource, which is superior for wind power development. The current strategy, led by Alaska Energy Authority, is to upgrade the St. George electrical distribution system and power plant. Avian studies in Nikolski and Sand Point have allowed for proper wind turbine siting without killing birds, especially endangered species and bald eagles. APIA continues coordinating and looking for funding opportunities for regional renewable energy projects. An important goal for APIA has been, and will continue to be, to involve community members with renewable energy projects and energy conservation efforts.

17 WIND ENERGY↗
NASA NTRS2012

Design for the Structure and the Mechanics of Moballs

The moball is envisioned to be a round, self-powered, and wind-driven multifunctioning sensor used in the Gone with the Wind ON-Mars (GOWON) [http://www.lpi.usra.edu/meetings/ marsconcepts2012/pdf/4238.pdf]: A Wind-Driven Networked System of Mobile sensors on Mars. The moballs would have sensing, processing, and communication capabilities. The moballs would perform in situ detection of key environmental elements such as vaporized water, trace gases, wind, dust, clouds, light and UV exposure, temperature, as well as minerals of interest, possible biosignatures, surface magnetic and electric fields, etc. The embedded various low-power micro instruments could include a Multispectral Microscopic Imager (to detect various minerals), a compact curved focal plane array camera (UV/Vis/NIR) with a large field of view, a compact UV/Visible spectrometer, a micro-weather station, etc. The moballs could communicate with each other and an orbiter. Their wind- or gravity-driven rolling movement could be used to harvest and store electric energy. They could also generate and store energy using the sunlight, when available, and the diurnal temperature variations on Mars. The moballs would be self-aware of their (and their neighbors ) positions, energy storage, and memory availability; they would have processing power and could intelligently cooperate with neighboring moballs by distributing tasks, sharing data, and fusing information. The major advantages of using the wind-driven and spherical moball network over rovers or other fixed sensor webs to explore Mars would be: (1) moballs could explore a much larger expanse of Mars in a much faster fashion, (2) they could explore the difficult terrains such as steep slopes and sand dunes, and (3) they would be self-energy- generating and could work together and move around autonomously. The challenge in designing the structure and the mechanics of the moball would be that it should be sturdy enough to withstand the impact of its initial fall, as well as other impacts from obstacles in its way. A mechanism would be needed that could enable hundreds of moballs to be carried while they would be deflated and compact, then would inflate them just after deploying them to their drop site. Furthermore, the moballs should also be light enough to allow them to move easily over obstacles by force of the wind. They also should have some kind of maneuvering mechanism in place to help them avoid very hazardous sharp objects or events, and to enable them to get closer to the objects of interest. The structure of the moballs was designed so that they would have different layers. The outer layer should comprise a sturdy, yet light, polymer that could withstand both the impact of the initial drop, as well as the impact of the different obstacles it would encounter while traversing the surface of Mars. This polymer should not deteriorate with the 100 K daily temperature swings on Mars. The inner layer should consist of a very light gas such as nitrogen or helium. In terms of maneuvering, six very light weights placed at strategic locations would give moballs the ability to turn, or even hop, over hazardous (e.g., sharp) obstacles, or even initiate a movement (before getting more help from the wind to be carried around) when stuck. Maneuvering would be necessary in order to get closer to objects of interest. If the weights would be allowed to move freely, they could also be used to generate energy.

Davoodi, Faranak↗
DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm: Preprint

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10- 15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗
DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10-15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗
DOE OSTI2019

Real-time predictive sensor network and deployable sensor

Deployable, predictive sensor systems may form a sensor network configured to provide environmental data in real-time or near-real-time. The sensors may be deployable sensors that can be launched and/or airdropped in areas that may be contaminated or otherwise unsafe for humans to enter. The predictive sensor network may include sensor tetrapods that may include anemometers for measuring wind speed, radiation sensors, gaseous contaminant sensors, biological sensors, and/or any other desired sensor type. These sensors may inform wind, transport and dispersion models in real-time. The sensor tetrapods may be satellite-linked, linked via a cellular network, linked via RF line-of-sight, a wireless communication link, and/or another compatible wireless network to a wind, dispersal, and deposition model that provides a dispersion pattern, a deposition pattern, and a wind pattern to enable a high-quality remote assessment of the changing scene in real-time.

Hehlen, Markus↗