An environmental model for Van Allen belt protons
Energy spectrum and distribution of Van Allen proton belt
ENERGY SPECTRUM↗
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Results for “environmental modeling”
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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Development of environmental models for NASA space vehicle design - Program status
Aerospace environment models development by NASA for engineering use in Space Vehicle Design Criteria program
Charak, M. T.↗
Calibration and verification of environmental models
The problems of calibration and verification of mesoscale models used for investigating power plant discharges are considered. The value of remote sensors for data acquisition is discussed as well as an investigation of Biscayne Bay in southern Florida.
Lee, S. S.↗
Implications of outer-zone radiations on operations in the geostationary region utilizing the AE4 environmental model
The radiation exposure in the region of geostationary orbits is examined in search for means of optimizing human performance. It is found that the use of slightly inclined circular orbits is one means by which exposure and spacesuit thickness requirements can be reduced. Another effective technique is to limit the extravehicular activity to those days when the short term fluctuations result in low exposure. Space-suit shielding approaching 1/2 sq cm or less may be possible by utilizing work stoppages and inclined orbits. If aluminum and other low-atomic-number materials are used to construct the habitat, then excessive wall thicknesses are required. If special bremsstrahlung shielding is used, then the habitat shield may be reduced to as low as 2 g/sq cm. Numerous tables and graphs are presented for future analysis of dose in the geostationary region.
Wilson, J. W.↗
A program of research in environmental modeling
A theoretical framework for the interpretation of satellite measurements of stratospheric temperature and trace gases is provided. This problem is quite complicated since the distributions of trace gases are dependent on dynamics and photochemistry. Therefore, the problem was attacked with models employing varying degrees of photochemical and dynamical complexity. The relationship between dynamics and trace gas transport and wave transience, dissipation and critical levels and the net (permanent) transport of trace gases, the role of photochemistry in trace gas transport, photochemistry and dynamics and altering the mean-zonal distribution of stratospheric ozone, and approximations to simplify the interpretation of observations and General Circulation Models are discussed.
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Environmental modeling and recognition for an autonomous land vehicle
An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perceptual structure database, the grouping processes that operate over this, schemas, and the long term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given.
Lawton, D. T.↗
Radiation Environments and Environmental Models: Probability Model for Cumulative Solar Proton Event Fluences
In this viewgraph presentation, the following space radiations are covered: solar particle events, galactic cosmic rays, and trapped particles. Characteristics and models for each are presented.
Xapsos, M. A.↗
The Chandra X-Ray Observatory Radiation Environmental Model Update
CRMFLX (Chandra Radiation Model of ion FLUX) is a radiation environment risk mitigation tool for use as a decision aid in planning the operation times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space where Chandra must operate. In addition, on-board particle detectors do not measure proton flux levels of the required energy range. CRMFLX is an engineering environment model developed to predict the proton flux in the solar wind, magnetosheath, and magnetosphere phenomenological regions of geospace. This paper describes the upgrades to the ion flux databases for the magnetosphere, magnetosheath, and solar wind regions. These data files were created by using Geotail and Polar spacecraft flux measurements only when the Advanced Composition Explorer (ACE) spacecraft's 0.14 MeV particle flux was below a threshold value. This new database allows for CRMFLX output to be correlated with both the geomagnetic activity level, as represented by the Kp index, as well as with solar proton events. Also, reported in this paper are results of analysis leading to a change in Chandra operations that successfully mitigates the false trigger rate for autonomous radiation events caused by relativistic electron flux contamination of proton channels.
Blackwell, William C.↗
GCR Environmental Models I: Sensitivity Analysis for GCR Environments
Accurate galactic cosmic ray (GCR) models are required to assess crew exposure during long-duration missions to the Moon or Mars. Many of these models have been developed and compared to available measurements, with uncertainty estimates usually stated to be less than 15%. However, when the models are evaluated over a common epoch and propagated through to effective dose, relative differences exceeding 50% are observed. This indicates that the metrics used to communicate GCR model uncertainty can be better tied to exposure quantities of interest for shielding applications. This is the first of three papers focused on addressing this need. In this work, the focus is on quantifying the extent to which each GCR ion and energy group, prior to entering any shielding material or body tissue, contributes to effective dose behind shielding. Results can be used to more accurately calibrate model-free parameters and provide a mechanism for refocusing validation efforts on measurements taken over important energy regions. Results can also be used as references to guide future nuclear cross-section measurements and radiobiology experiments. It is found that GCR with Z>2 and boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. This finding is important given that most of the GCR models are developed and validated against Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer (ACE/CRIS) measurements taken below 500 MeV/n. It is therefore possible for two models to very accurately reproduce the ACE/CRIS data while inducing very different effective dose values behind shielding.
Slaba, Tony C.↗
GCR Environmental Models III: GCR Model Validation and Propagated Uncertainties in Effective Dose
This is the last of three papers focused on quantifying the uncertainty associated with galactic cosmic rays (GCR) models used for space radiation shielding applications. In the first paper, it was found that GCR ions with Z>2 and boundary energy below 500 MeV/nucleon induce less than 5% of the total effective dose behind shielding. This is an important finding since GCR model development and validation have been heavily biased toward Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer measurements below 500 MeV/nucleon. Weights were also developed that quantify the relative contribution of defined GCR energy and charge groups to effective dose behind shielding. In the second paper, it was shown that these weights could be used to efficiently propagate GCR model uncertainties into effective dose behind shielding. In this work, uncertainties are quantified for a few commonly used GCR models. A validation metric is developed that accounts for measurements uncertainty, and the metric is coupled to the fast uncertainty propagation method. For this work, the Badhwar-O'Neill (BON) 2010 and 2011 and the Matthia GCR models are compared to an extensive measurement database. It is shown that BON2011 systematically overestimates heavy ion fluxes in the range 0.5-4 GeV/nucleon. The BON2010 and BON2011 also show moderate and large errors in reproducing past solar activity near the 2000 solar maximum and 2010 solar minimum. It is found that all three models induce relative errors in effective dose in the interval [-20%, 20%] at a 68% confidence level. The BON2010 and Matthia models are found to have similar overall uncertainty estimates and are preferred for space radiation shielding applications.
Slaba, Tony C.↗
DebriSat: A Hypervelocity Experiment and Its Impact on Environmental Models
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Heather Cowardin↗
Optical Characterization of DebriSat Fragments in Support of Orbital Debris Environmental Models
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Heather M. Cowardin↗
WTK-LED: The WIND Toolkit Long-Term Ensemble Dataset
To satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have, we aimed at developing an updated version of the meteorological WIND Toolkit, named WIND Toolkit Long-term Ensemble Dataset (WTK-LED), which is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: 1) Numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). 2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. 3) Specific long-term,high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind data set. This report focuses on a description of the land-based WTK-LED for CONUS, Hawaii, and Alaska, for the 3-year 2-km/5-min dataset and the 20-year 4-km/hourly dataset, as well as the uncertainty quantification method. We also provide limited validation results. Based on our results to date, we suggest use cases and applications for each dataset of the WTK-LED.
17 WIND ENERGY↗
NISAR Spacecraft Environmental Torque Modeling During Operations
Environmental torques imparted on the NISAR (NASA-ISRO (NASA Jet PropulsionLaboratory (JPL)-Indian Space Research Organization (ISRO) Synthetic Aperture Radar) spacecraft are modeled. The environmental torques comprise of the gravity gradient, atmospheric drag, and solar radiation pressure. These torques act as external disturbances on the spacecraft and cause momentum to accumulate. This momentum needs to be unloaded via attitude control hardware. In order to size the hardware, it is important to determine the environmental torques imparted on the spacecraft. The results indicate that the worst case gravity gradient, drag, and solar radiation pressure torques are 7.4 by 10 (sup -3) Nm (Newton meters), 6.01 by 10 (sup -3) Nm, and 14.03 by 10(sup -3) Nm, respectively.
Rizvi, Farheen↗
Pioneer Venus spacecraft charging model
Five environmental models were constructed to represent the solar wind and the upper, middle, and lower ionosphere of Venus. The spacecraft structure was modeled with over 140 passive electrical elements representing structural elements of the spacecraft. Electron, ion, secondary electron, and photocurrents to the spacecraft from the plasma were calculated, ignoring sheath effects. In all but one case, potentials of interest were less than 1 volt. Potential differences between widely separated points on the equipment shelf were less than 1 mV. The one area of concern is the solar panel potential when the orbiter is passing through the bowshock region.
Robinson, P. A., Jr.↗
A Knowledge-Based Representation Scheme for Environmental Science Models
One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.
Keller, Richard M.↗
Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke
Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.
Exposure assessment↗
International Conference on Environmental Sensing and Assessment, Las Vegas, Nev., September 14-19, 1975, Proceedings. Volumes 1 & 2
The papers deal with the detection of hazardous environmental pollutants, the development of emission control plans, and the design of compliance monitoring systems. Topics include remote sensing techniques in environmental pollution monitoring, monitoring of atmospheric particulate matter, air pollution due to sulfur dioxide and other inorganic compounds, marine pollution, atmospheric aerosols, industrial pollution, and legal aspects of pollution monitoring. Other papers examine the toxic effects of heavy metals and halogenated hydrocarbons, pollution associated with waste-disposal processes, pesticide residues in soil and groundwater, evaluations of groundwater quality, and monitoring of nuclear wastes. The interaction of climate and pollution is also discussed along with global pollutant transport, environmental modeling, ambient environmental air quality, aircraft and ground-vehicle emissions, and pollution associated with energy extraction and utilization processes. Individual items are announced in this issue.
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