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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparison of source-location algorithms for atmospheric samplers

Numerous algorithms have been developed to determine the source characteristics for an atmospheric release, e.g., (Bieringer et al., 2017). This study compares three models that have been applied to the data collected by the International Monitoring System operated by the Comprehensive Nuclear-Test-Ban Treaty Preparatory Commission to estimate source event parameters. Each model uses a different approach to estimate the parameters. A deterministic model uses a possible source region (PSR) approach (Ringbom et al., 2014) that is based on the correlation between predicted and measured sample values. An unnamed model developed at Pacific Northwest National Laboratory (herein called BAYEST) uses a Bayesian formulation (Eslinger et al., 2019; Eslinger et al., 2020; Eslinger and Schrom, 2016). The FREAR model uses a different Bayesian formulation (De Meutter and Hoffman, 2020; De Meutter et al., 2021; Pieter De Meutter, 2021). The performance of the three source-location models is evaluated with 100 synthetic release cases for the single xenon isotope, 133 Xe. The release cases resulted in detections in a fictitious network with 120 noble gas samplers. All three source-location models use the same sampling data. The two Bayesian models yield more accurate location estimates than the deterministic PSR model, with FREAR having slightly better location performance than BAYEST. Samplers with collection periods of 3, 6, 8, 12, and 24-h were used. Results from BAYEST show that location accuracy improves with each reduction in sample collection length. The BAYEST model is slightly better for estimating the start time of the release. The PSR model has about the same spread in start times as the FREAR model, but the PSR results have a better average start time. The Bayesian source-location algorithms give more accurate results than the PSR approach, and provide release magnitude estimates, while the base PSR model does not estimate the release magnitude. This investigation demonstrates that a reasonably dense sampling grid will sometimes yield poor location and time estimates regardless of the model. The poor estimates generally coincide with cases where there is a much larger distance between the release point and the first detecting sampler than the average sampler spacing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS2017

Optical Extinction Measurements of Laser Side-Scatter During Tropical Storm Colin

A side-scatter imaging (SSI) technique using a 447 nm, 500 mW laser and a Nikon D80 camera was tested at Kennedy Space Center, Florida during the passing of a rain band associated with Tropical Storm Colin. The June 6, 2016, 22:00 GMT rain event was intense but short-lived owing to the strong west-to-east advection of the rain band. An effort to validate the optical extinction measurement was conducted by setting up a line of three tipping rain gauges along an 80 m east-west path and below the laser beam. Differences between tipping bucket measurements were correlated to the extinction coefficient profile along the lasers path, as determined by the SSI measurement. In order to compare the tipping bucket to the optical extinction data, a Marshall-Palmer DSD model was assumed. Since this was a daytime event, the laser beam was difficult to detect in the camera images, pointing out an important limitation of SSI measurements: the practical limit of DSD density that can be effectively detected and analyzed under daylight conditions using this laser and camera, corresponds to a fairly moderate rainfall rate on the order of 20 mmh (night measurements achieve a much improved sensitivity). The SSI analysis model under test produced promising results, but in order to use the SSI method for routine meteorological studies, improvements to the math model will be required.

optical extinction↗
NASA NTRS1988

Empirical Modeling Of Single-Event Upset

Experimental study presents examples of empirical modeling of single-event upset in negatively-doped-source/drain metal-oxide-semiconductor static random-access memory cells. Data supports adoption of simplified worst-case model in which cross sectionof SEU by ion above threshold energy equals area of memory cell.

Zoutendyk, John A.↗
DOE OSTI2024

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Transmission risk of Oropouche fever across the Americas

Abstract Background Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. Methods To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. Results Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. Conclusions Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Higher-order correlations between different moments of two flow amplitudes in Pb-Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV

The correlations between different moments of two flow amplitudes, extracted with the recently developed asymmetric cumulants, are measured in Pb-Pb collisions at $\sqrt {s_{NN}}$ = 5.02 TeV recorded by the ALICE detector at the CERN Large Hadron Collider. The magnitudes of the measured observables show a dependence on the different moments as well as on the collision centrality, indicating the presence of nonlinear response in all even moments up to the eighth. Furthermore, the higher-order asymmetric cumulants show different signatures than the symmetric and lower-order asymmetric cumulants. Comparisons with state-of-the-art event generators using two different parametrizations obtained from Bayesian optimization show differences between data and simulations in many of the studied observables, indicating a need for further tuning of the models behind those event generators. These results provide new and independent constraints on the initial conditions and transport properties of the system created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

DUNE-PRISM – A New Method to Measure Neutrino Oscillations

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long baseline neutrino oscillation experiment designed to make precision measurements in a 1.2 2.4 MW neutrino beam, which is directed 1285 km from the Fermi National Accelerator Laboratory (Fermilab) to the Sandford Underground Research Facility (SURF) in South Dakota. Neutrinos are measured at two detector facilities: a near detector located at Fermilab close where the beam is produced and a far detector at SURF. The neutrino beam can be configured to be composed primarily of either muon or anti-muon neutrinos. DUNE measures the disappearance of muon and anti-muon neutrinos and appearance electron and anti-electron neutrinos in the neutrino beam. Measuring these neutrino flavour transitions provides DUNE with sensitivity to the neutrino mass ordering, $\delta_{CP}$, $\theta_{13}$, $\theta_{23}$ and the magnitude of $\Delta m^2_{23}$. The DUNE Precision Reaction Independent Spectrum Measurement (DUNE-PRISM) concept presents a novel way to perform a neutrino oscillation analysis, which has the potential to significantly reduce the impact of large systematic uncertainties in the neutrino interaction model. The PRISM method linearly combines measurements of off-axis neutrino interactions at the DUNE near detector to produce data-driven predictions of the oscillated neutrino event rate spectrum at the far detector. By building an oscillated far detector prediction directly from data, any unknown or poorly modelled neutrino interaction effects will be naturally incorporated into the measurement of the parameters of the neutrino oscillation model. This thesis presents the first complete neutrino oscillation analysis for DUNE using the PRISM method. Details of the methodology are fully explained and the prospects for further improvements to the techniques described are highlighted. The expected impact and relative importance of the neutrino flux, cross section and detector systematic uncertainties are described in detail. Finally, this thesis demonstrates that the PRISM method is capable of performing a measurement of the oscillation parameters that is robust against neutrino interaction modelling errors.

Hasnip, Ciaran↗
NASA NTRS2001

Role of Stratospheric Air in a Severe Weather Event: Analysis of Potential Vorticity and Total Ozone

The role of dry stratospheric air descending to low and middle tropospheric levels in a severe weather outbreak in the midwestern United States is examined using ACCEPT Eta model output, Rapid Update Cycle (RUC) analyses, and Earth probe Total Ozone Mapping Spectrometer (EP/TOMS) total ozone data. While stratospheric air was not found to play a direct role in the convection, backward trajectories show stratospheric air descended to 800 hPa just west of the convection. Damaging surface winds not associated with thunderstorms also occurred in the region of greatest stratospheric descent. Small-scale features in the high-resolution total ozone data compare favorably with geopotential heights and potential vorticity fields, supporting the notion that stratospheric air descended to near the surface. A detailed vertical structure in the potential vorticity appears to be captured by small-scale total ozone variations. The capability of the total ozone to identify mesoscale features assists model verification. The total ozone data suggest biases in the RUC analysis and Eta forecast of this event. The total ozone is also useful in determining whether potential vorticity is of stratospheric origin or is diabatically generated in the troposphere.

Goering, Melissa A.↗
NASA NTRS1991

Biogeochemical modeling at mass extinction boundaries

The causes of major mass extinctions is a subject of considerable interest to those concerned with the history and evolution of life on earth. The primary objectives of the proposed plan of research are: (1) to develop quantitative time-dependent biogeochemical cycle models, coupled with an ocean atmosphere in order to improve the understanding of global scale physical, chemical, and biological processes that control the distribution of elements important for life at times of mass extinctions; and (2) to develop a comprehensive data base of the best available geochemical, isotopic, and other relevant geologic data from sections across mass extinction boundaries. These data will be used to constrain and test the biogeochemical model. These modeling experiments should prove useful in: (1) determining the possible cause(s) of the environmental changes seen at bio-event boundaries; (2) identifying and quantifying little-known feedbacks among the oceans, atmosphere, and biosphere; and (3) providing additional insights into the possible responses of the earth system to perturbations of various timescales. One of the best known mass extinction events marks the Cretaceous/Tertiary (K/T) boundary (66 Myr ago). Data from the K/T boundary are used here to constrain a newly developed time-dependent biogeochemical cycle model that is designed to study transient behavior of the earth system. Model results predict significant fluctuations in ocean alkalinity, atmospheric CO2, and global temperatures caused by extinction of calcareous plankton and reduction in the sedimentation rates of pelagic carbonates and organic carbon. Oxygen-isotome and other paleoclimatic data from K/T time provide some evidence that such climatic fluctuations may have occurred, but stabilizing feedbacks may have acted to reduce the ocean alkalinity and carbon dioxide fluctuations.

Rampino, M. R.↗
NASA NTRS2001

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by 1 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5 %) and +/- 5.0 K (+/- 15 %), respectively. At a given tropospheric level, such perturbations can cause a +/- 25 % variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2002

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2013

Jettison Engineering Trajectory Tool

The Jettison Engineering Trajectory Tool (JETT) performs the jettison analysis function for any orbiting asset. It provides a method to compute the relative trajectories between an orbiting asset and any jettisoned item (intentional or unintentional) or sublimating particles generated by fluid dumps to assess whether an object is safe to jettison, or if there is a risk with an item that was inadvertently lost overboard. The main concern is the interaction and possible recontact of the jettisoned object with an asset. This supports the analysis that jettisoned items will safely clear the vehicle, ensuring no collisions. The software will reduce the jettison analysis task from one that could take days to complete to one that can be completed in hours, with an analysis that is more comprehensive than the previous method. It provides the ability to define the jettison operation relative to International Space Station (ISS) structure, and provides 2D and 3D plotting capability to allow an analyst to perform a subjective clearance assessment with ISS structures. The developers followed the SMP to create the code and all supporting documentation. The code makes extensive use of the object-oriented format of Java and, in addition, the Model-View-Controller architecture was used in the organization of the code, allowing each piece to be independent of updates to the other pieces. The model category is for maintaining data entered by the user and generated by the analysis. The view category provides capabilities for data entry and displaying all or a portion of the analysis data in tabular, 2D, and 3D representation. The controller category allows for handling events that affect the model or view(s). The JETT utilizes orbital mechanics with complex algorithms. Since JETT is written in JAVA, it is essentially platform-independent.

Zaczek, Mariusz↗
NASA NTRS2003

Iced Aircraft Flight Data for Flight Simulator Validation

NASA is developing and validating technology to incorporate aircraft icing effects into a flight training device concept demonstrator. Flight simulation models of a DHC-6 Twin Otter were developed from wind tunnel data using a subscale, complete aircraft model with and without simulated ice, and from previously acquired flight data. The validation of the simulation models required additional aircraft response time histories of the airplane configured with simulated ice similar to the subscale model testing. Therefore, a flight test was conducted using the NASA Twin Otter Icing Research Aircraft. Over 500 maneuvers of various types were conducted in this flight test. The validation data consisted of aircraft state parameters, pilot inputs, propulsion, weight, center of gravity, and moments of inertia with the airplane configured with different amounts of simulated ice. Emphasis was made to acquire data at wing stall and tailplane stall since these events are of primary interest to model accurately in the flight training device. Analyses of several datasets are described regarding wing and tailplane stall. Key findings from these analyses are that the simulated wing ice shapes significantly reduced the C , max, while the simulated tail ice caused elevator control force anomalies and tailplane stall when flaps were deflected 30 deg or greater. This effectively reduced the safe operating margins between iced wing and iced tail stall as flap deflection and thrust were increased. This flight test demonstrated that the critical aspects to be modeled in the icing effects flight training device include: iced wing and tail stall speeds, flap and thrust effects, control forces, and control effectiveness.

Ratvasky, Thomas P.↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Martian Atmospheric Circulation and Climate

This project was submitted with four work tasks. The reviews recommended focusing on the following three, with an appropriately reduced budget: 1. In the first, we proposed to use Thermal Emission Spectrometer (TES) data to examine the general circulation of the atmosphere and to better constrain and validate a Mars General Circulation Model (GCM). 2. In the second, we proposed to examine processes responsible for the injection of dust into the atmosphere. We will conduct a global, seasonal survey of dust lifting events, and specifically of dust devil activity, using MGS MOC, MGS TES, and Odyssey THEMIS data. The results of this survey will be compared with model predictions of dust devil and other dust lifting processes. It is expected that some of the observational results will motivate specific simulations with the GCM and mesoscale models. 3. In the third task, we proposed to extract seasonal and spatial near-surface wind information from aeolian streaks. Detailed analysis will focus on streaks in the polar regions and in regions of large topography (such as Tharsis). The streak information will be used along with the mesoscale model to examine the processes that control local and regional scale flow patterns.

Richardson, Mark I.↗
NASA NTRS2022

Comparison of Likelihood Methods for Generalized Linear Mixed Models with Application to Quiet Supersonic Flights 2018 Data

Repeated measurement will be a feature of the survey data collected during the Quesst missionX-59 community response tests (CRT). Since each participant will report his or her categorical level of annoyance in response to multiple events, the responses from any single individual may be correlated with one another. Several models within the class of generalized linear mixed models (GLMM) are pertinent to the analysis of correlated categorical outcomes; the random intercept logistic regression model is one example. Both Bayesian and frequentist methods for fitting these models are available, with frequentist methods relying on some form of approximation (of either an integral or the integrand) that appears in the marginal likelihood function. Given several anticipated similarities of the X-59 CRT data to data collected during a past risk reduction, Quiet Supersonic Flights 2018 (QSF18), this short note is intended to create awareness. It documents an instance in which a reported population average dose-response relationship derived from QSF18 single event data was distorted by the integral approximation applied in likelihood-based methods. We review some of the available literature on the topic, compare the outputs of several different computational approaches implemented in available statistical software, and present simple corrective actions that may be useful during the Quesst mission.

dose-response model↗
NASA NTRS2000

Coupled Model Simulation of Snowfall Events Over the Black Hills

Although many long-term simulations of snow accumulation and oblation have been made using stand-alone land surface models and surface models coupled with GCMs, less research has focused on short-term event simulations. Actually, accurate event simulations of snow-related processes are the basis for successful long-term simulation. Three advantages of event simulations of snowfall and snow melting are availability of: (1) intensive observation data from field experiments for validation; (2) more physically-realistic precipitation schemes for use in atmospheric models to simulate snowfall; and (3) a more detailed analysis of the snow melting processes. In addition to the complexities of snow related processes themselves, terrain-induced effects on snowfall/snow melting make simulations of snow events more difficult. Climatological observations indicate that terrain features such as the Black Hills of South Dakota and Wyoming can exert important effects on snow accumulation and snow oblation processes. One of the primary effects is that the orography causes forced uplift of airflow and causes atmospheric waves to form both upwind and downwind of it. Airflow often splits around the obstacle, converging on the lee side. This convergence may lead to precipitation enhancement. It also provides an elevated heat and moisture source that enhances atmospheric instability. During the period of April 5-May 5, 1999, the Upper Missouri River Basin Pilot Project (UMRBPP) made intensive observations on precipitation events occurring in the Black Hills. Two moderate snowfall events were captured during the period. The resulting high temporal and spatial resolution data provides opportunities to investigate terrain effects on snowfall amount, distribution, and melting. Successful simulation of snowfall amount, distribution, and evolution using atmospheric models is important to subsequent modeling of snow melting using snow sub-models in land surface schemes. In this paper, a coupled model system, consisting of an atmosphere model (ARPS) and a land-surface model (revised NCAR LSM), is used to simulate one of these UMRBPP cases.

Wang, Jianzhong↗
NASA NTRS2018

Modeling the Proton Radiation Belt With Van Allen Probes Relativistic Electron-Proton Telescope Data

An empirical model of the proton radiation belt is constructed from data taken during 2013-2017 by the Relativistic Electron-Proton Telescopes on the Van Allen Probes satellites. The model intensity is a function of time, kinetic energy in the range 18-600 megaelectronvolts, equatorial pitch angle, and L shell of proton guiding centers. Data are selected, on the basis of energy deposits in each of the nine silicon detectors, to reduce background caused by hard proton energy spectra at low L. Instrument response functions are computed by Monte Carlo integration, using simulated proton paths through a simplified structural model, to account for energy loss in shielding material for protons outside the nominal field of view. Overlap of energy channels, their wide angular response, and changing satellite orientation require the model dependencies on all three independent variables be determined simultaneously. This is done by least squares minimization with a customized steepest descent algorithm. Model uncertainty accounts for statistical data error and systematic error in the simulated instrument response. A proton energy spectrum is also computed from data taken during the 8 January 2014 solar event, to illustrate methods for the simpler case of an isotropic and homogeneous model distribution. Radiation belt and solar proton results are compared to intensities computed with a simplified, on-axis response that can provide a good approximation under limited circumstances.

Selesnick, R. S.↗