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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
DOE OSTI2021

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

In recent years, the Artificial Intelligence and Data Mining (AI&DM) models have become popular tools in assisting various aspects of reservoir operation. However, the practical uses are still rarely reported. Comparison experiment of many AI&DM models over a large number of reservoir cases is particularly valuable to help reservoir operators first examine the usefulness and transferability of different AI&DM models, and then identify the most stable and reliable AI&DM model in assist of various decision-making processes. In this study, a total of 12 AI&DM models with different parameterizations and simulation scenarios are comprehensively tested out and compared in simulating the controlled reservoir outflows of 33 reservoir cases over the Upper Colorado Region, United States. Results show that the Random Forecast and the Long-Short-Term-Memory model could consistently derive the best statistical performance than other models under the baseline simulation scenario. The employed AI&DM models could obtain satisfactory statistical interquartile ranges (25–75%) between [0.6–0.9], [0.3–0.8], and [0.2–0.8], for CORR, NSE, and KGE measurements, respectively, and [1.5–6.5], [–15 to 20], and [0.5–8.5] for the normalized RMSE, PBIAS and RSR measurements, respectively. Results also show Multi-Layer Perceptron model and Extreme Gradient Boosting Tree Algorithm produced more stable and superior performance than other models under more complex input scenarios. We also found that the performance of different AI&DM models are closely relevant to the reservoir elevations, sizes, and functionalities. Discussions were made about the sensitivity of AI&DM models’ parameterizations and the key advantages of AI&DM models over the rule-based reservoir models. We further identify that the main advantage of AI&DM models is the flexibility in designing input structures, whereas the rule-based simulation model is rather limited. Future studies were suggested regarding the best way reservoir operators and researchers could use, select, and apply different AI&DM models in simulating reservoir releases under different natural and modeling environments. Finally, this comparison study also serves as a reference and a piece of groundwork for further promoting the practical uses of AI&DM models in assisting reservoir operation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Status of LDEF radiation modeling

The current status of model prediction and comparison with LDEF radiation dosimetry measurements is summarized with emphasis on major results obtained in evaluating the uncertainties of present radiation environment model. The consistency of results and conclusions obtained from model comparison with different sets of LDEF radiation data (dose, activation, fluence, LET spectra) is discussed. Examples where LDEF radiation data and modeling results can be utilized to provide improved radiation assessments for planned LEO missions (e.g., Space Station) are given.

Watts, John W.↗
DOE OSTI2023

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

Intelligent Control for the BEES Flyer

This paper describes the effort to provide a preliminary capability analysis and a neural network based adaptive flight control system for the JPL-led BEES aircraft project. The BEES flyer was envisioned to be a small, autonomous platform with sensing and control systems mimicking those of biological systems for the purpose of scientific exploration on the surface of Mars. The platform is physically tightly constrained by the necessity of efficient packing within rockets for the trip to Mars. Given the physical constraints, the system is not an ideal configuration for aerodynamics or stability and control. The objectives of this effort are to evaluate the aerodynamics characteristics of the existing design, to make recommendaaons as to potential improvements and to provide a control system that stabilizes the existing aircraft for nominal flight and damaged conditions. Towards this several questions are raised and analyses are presented to arrive at answers to some of the questions raised. CART3D, a high-fidelity inviscid analysis package for conceptual and preliminary aerodynamic design, was used to compute a parametric set of solutions over the expected flight domain. Stability and control derivatives were extracted from the database and integrated with the neural flight control system. The Integrated Vehicle Modeling Environment (IVME) was also used for estimating aircraft geometric, inertial, and aerodynamic characteristics. A generic neural flight control system is used to provide adaptive control without the requirement for extensive gain scheduling or explicit system identification. The neural flight control system uses reference models to specify desired handling qualities in the roll, pitch, and yaw axes, and incorporates both pre-trained and on-line learning neural networks in the inverse model portion of the controller. Results are presented for the BEES aircraft in the subsonic regime for terrestrial and Martian environments.

Krishnakumar, K.↗
NASA NTRS1992

Development and application of a 3-D geometry/mass model for LDEF satellite ionizing radiation assessments

A computer model of the three dimensional geometry and material distributions for the LDEF spacecraft, experiment trays, and, for selected trays, the components of experiments within a tray was developed for use in ionizing radiation assessments. The model is being applied to provide 3-D shielding distributions around radiation dosimeters to aid in data interpretation, particularly in assessing the directional properties of the radiation exposure. Also, the model has been interfaced with radiation transport codes for 3-D dosimetry response predictions and for calculations related to determining the accuracy of trapped proton and cosmic ray environment models. The methodology is described used in developing the 3-D LDEF model and the level of detail incorporated. Currently, the trays modeled in detail are F2, F8, and H12 and H3. Applications of the model which are discussed include the 3-D shielding distributions around various dosimeters, the influence of shielding on dosimetry responses, and comparisons of dose predictions based on the present 3-D model vs those from 1-D geometry model approximations used in initial estimates.

Colborn, B. L.↗
NASA NTRS2016

Simulation of a Rapid Dropout Event for Highly Relativistic Electrons with the RBE Model

A flux dropout is a sudden and sizable decrease in the energetic electron population of the outer radiation belt on the time scale of a few hours. We simulated a flux dropout of highly relativistic 2.5 MeV electrons using the Radiation Belt Environment model, incorporating the pitch angle diffusion coefficients caused by electromagnetic ion cyclotron (EMIC) waves for the geomagnetic storm events of 23-26 October 2002. This simulation showed a remarkable decrease in the 2.5 MeV electron flux during main phase of the storm, compared to those without EMIC waves. This decrease was independent of magnetopause shadowing or drift loss to the magnetopause. We suggest that the flux decrease was likely to be primarily due to pitch angle scattering to the loss cone by EMIC waves. Furthermore, the 2.5 MeV electron flux calculated with EMIC waves correspond very well with that observed from Solar Anomalous and Magnetospheric Particle EXplorer spacecraft. EMIC wave scattering is therefore likely one of the key mechanisms to understand flux dropouts. We modeled EMIC wave intensities by the Kp index. However, the calculated dropout is a several hours earlier than the observed one. We propose that Kp is not the best parameter to predict EMIC waves.

Kang, S-B.↗
NASA NTRSDate not supplied

Modeling the Meteoroid Environment Far from the Ecliptic Plane

NASA's Meteoroid Engineering Model (MEM) is a piece of software that describes the meteoroid environment encountered by spacecraft in the inner solar system. MEM's algorithms take advantage of the fact that the vast majority of spacecraft remain close to the ecliptic plane in order to make several simplifying assumptions. However, this results in a model that cannot describe the environment for spacecraft such as Ulysses that travel far from the ecliptic, and limits the potential to validate the model using impact signatures from asteroids on inclined orbits. We present a new version of the code, numbered 3.1-alpha, that correctly computes the meteoroid flux and directionality far from the ecliptic, and compare our results with zodiacal light data.

Althea Moorhead↗
NASA NTRS1990

A flight experiment to measure rarefied-flow aerodynamics

A flight experiment to measure rarefied-flow aerodynamics of a blunt lifting body is being developed by NASA. This experiment, called the Rarefied-Flow Aerodynamic Measurement Experiment (RAME), is part of the Aeroassist Flight Experiment (AFE) mission, which is a Pathfinder design tool for aeroassisted orbital transfer vehicles. The RAME will use flight measurements from accelerometers, rate gyros, and pressure transducers, combined with knowledge of AFE in-flight mass properties and trajectory, to infer aerodynamic forces and moments in the rarefied-flow environment, including transition into the hypersonic continuum regime. Preflight estimates of the aerodynamic measurements are based upon environment models, existing computer simulations, and ground test results. Planned maneuvers at several altitudes will provide a first-time opportunity to examine gas-surface accommondation effects on aerodynamic coefficients in an environment of changing atmospheric composition. A description is given of the RAME equipment design.

Blanchard, Robert C.↗
NASA NTRS2002

A Data Management System for International Space Station Simulation Tools

Groups associated with the design, operational, and training aspects of the International Space Station make extensive use of modeling and simulation tools. Users of these tools often need to access and manipulate large quantities of data associated with the station, ranging from design documents to wiring diagrams. Retrieving and manipulating this data directly within the simulation and modeling environment can provide substantial benefit to users. An approach for providing these kinds of data management services, including a database schema and class structure, is presented. Implementation details are also provided as a data management system is integrated into the Intelligent Virtual Station, a modeling and simulation tool developed by the NASA Ames Smart Systems Research Laboratory. One use of the Intelligent Virtual Station is generating station-related training procedures in a virtual environment, The data management component allows users to quickly and easily retrieve information related to objects on the station, enhancing their ability to generate accurate procedures. Users can associate new information with objects and have that information stored in a database.

Betts, Bradley J.↗
NASA NTRS1998

Comparison of Contamination Model Predictions to LDEF Surface Measurements

Contaminant deposition measurements have been made on species content and depth profiles on three experiments trays from the Long Duration Exposure Facility (LDEF), Auger, Argon sputtering, Electron Spectroscopy for Chemical Analysis (ESCA) and Scanning Electron Microscopy (SEM) analysis. The integrated spacecraft environment model (ISEM) was used to predict the deposition levels of the contaminants measured on the three trays. The details of the modeling and assumptions used are presented along with the predictions for the deposition on select surfaces on the trays. These are compared to the measured results. The trays represent surfaces that have a high atomic oxygen flux, and intermediate oxygen flux, and no oxygen flux. All surfaces received significant solar Ultraviolet flux. It appears that the atomic oxygen was the primary agent that caused significant deposition to occur. Surfaces that saw significant contaminant flux solar UV and no atomic oxygen did not show any appreciable levels of observable deposition. The implications of the atom ic oxygen interaction with contaminant deposits containing silicon contaminant sources is discussed. The primary contaminant sources are DC61104 adhesive and Z306 paint. The results and interpretation of the findings have a potential significant impact on spacecraft surfaces that are exposed to solar UV and atomic oxygen in low Earth orbit.

Gordon, Tim↗
NASA NTRS1991

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Kirlik, Alex↗
NASA NTRS1999

CONSTELL: NASA's Satellite Constellation Model

The CONSTELL program represents an initial effort by the orbital debris modeling group at NASA/JSC to address the particular issues and problems raised by the presence of LEO satellite constellations. It was designed to help NASA better understand the potential orbital debris consequences of having satellite constellations operating in the future in LEO. However, it could also be used by constellation planners to evaluate architecture or design alternatives that might lessen debris consequences for their constellation or lessen the debris effects on other users of space. CONSTELL is designed to perform debris environment projections rapidly so it can support parametric assessments involving either the constellations themselves or the background environment which represents non-constellation users of the space. The projections need to be calculated quickly because a number of projections are often required to adequately span the parameter space of interest. To this end CONSTELL uses the outputs of other NASA debris environment models as inputs, thus doing away with the need for time consuming upfront calculations. Specifically, CONSTELL uses EVOLVE or ORDEM96 debris spatial density results as its background environment, debris cloud snapshot templates to simulate debris cloud propagation, and time dependent orbit profiles of the intact non- functional constellation spacecraft and upper stages. In this paper the environmental consequences of the deployment of particular LEO satellite constellations using the CONSTELL model will be evaluated. Constellations that will undergo a parametric assessment will reflect realistic parameter values. Among other results the increase in loss rate of non-constellation spacecraft, the number of collisions involving constellation elements, and the replacement rate of constellation satellites as a result of debris impact will be presented.

Theall, Jeffrey R.↗
NASA NTRS2019

Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools

Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.

model based mission assurance↗
NASA NTRS2006

Analyzing Electric Field Morphology Through Data-Model Comparisons of the GEM IM/S Assessment Challenge Events

The storm-time inner magnetospheric electric field morphology and dynamics are assessed by comparing numerical modeling results of the plasmasphere and ring current with many in situ and remote sensing data sets. Two magnetic storms are analyzed, April 22,2001 and October 21-23,2001, which are the events selected for the Geospace Environment Modeling (GEM) Inner Magnetosphere/Storms (IM/S) Assessment Challenge (IMSAC). The IMSAC seeks to quantify the accuracy of inner magnetospheric models as well as synthesize our understanding of this region. For each storm, the ring current-atmosphere interaction model (RAM) and the dynamic global core plasma model (DGCPM) were run together with various settings for the large-scale convection electric field and the nightside ionospheric conductance. DGCPM plasmaspheric parameters were compared with IMAGE-EUV plasmapause extractions and LANL-MPA plume locations and velocities. RAM parameters were compared with Dst*, LANL-MPA fluxes and moments, IMAGE-MENA images, and IMAGE-HENA images. Both qualitative and quantitative comparisons were made to determine the electric field morphology that allows the model results to best fit the plasma data at various times during these events. The simulations with self-consistent electric fields were, in general, better than those with prescribed field choices. This indicates that the time-dependent modulation of the inner magnetospheric electric fields by the nightside ionosphere is quite significant for accurate determination of these fields (and their effects). It was determined that a shielded Volland-Stern field description driven by the 3-hour Kp index yields accurate results much of the time, but can be quite inconsistent. The modified Mcllwain field description clearly lagged in overall accuracy compared to the other fields, but matched some data sets (like Dst*) quite well. The rankings between the simulations varied depending on the storm and the individual data sets, indicating that each field description did well for some place, time, and energy range during the events, as well as doing less well in other places, times, and energies. Several unresolved issues regarding the storm-time inner magnetospheric electric field are discussed.

Liemohn, Michael W.↗
NASA NTRS2003

Program for Computing Albedo

Simple Thermal Environment Model (STEM) is a FORTRAN-based computer program that provides engineering estimates of top-of-atmosphere albedo and outgoing long-wave radiation (OLR) for use in analyzing thermal loads on spacecraft near Earth. The thermal environment of a spacecraft is represented in STEM as consisting of direct solar radiation; short-wave radiation reflected by the atmosphere of the Earth, as characterized in terms of the albedo of the Earth; and OLR emitted by the atmosphere of the Earth. STEM can also address effects of heat loads internal to a spacecraft. Novel features of STEM include (1) the use of Earth albedo and OLR information based on time series of measurements by Earth Radiation Budget Experiment satellites in orbit; (2) the ability to address thermal time constants of spacecraft systems by use of albedo and OLR values representing averages over a range of averaging times; and (3) the ability to address effects, on albedo and OLR values, of satellite orbital inclination, the angle between the plane of a spacecraft orbit and the line between the centers of the Earth and Sun, the solar zenith angle, and latitude.

Justus, Carl G.↗
NASA NTRS1994

Aircraft fatigue and crack growth considering loads by structural component

The indisputable 1968 C-130 fatigue/crack growth data is reviewed to obtain additional useful information on fatigue and crack growth. The proven Load Environment Model concept derived empirically from F-105D multichannel recorder data is refined to a simpler method by going from 8 to 5 variables in the spectra without a decrease in accuracy. This approach provides the true fatigue/crack growth and load environment by structural component for both fatigue and strength design. Methods are presented for defining fatigue scatter and damage at crack initiation. These design tools and criteria may be used for both metal and composite aircraft structure.

Yost, J. D.↗
NASA NTRS1997

The historical contribution of solid rocket motors to the one centimeter debris population

The measured small particle population in earth orbit contains cm-sized objects that are not accounted for by breakup fragments. It was proposed that slag ejection during solid rocket motor burn is a contributor to this population. The direct evidence for such slag ejection follows from: observations of the exhausts of vehicles in flight, and engineering data from static firings. A source model is presented to account for the contribution of slag expulsion from solid rocket motors to the debris population. The mass and velocity distribution of the slag effluents are taken into account and used as a source term in the debris environment model. The model is based on the available observation data and on models for slag development and ejection.

Jackson, Albert↗
NASA NTRS2004

Theory, Modeling, Software and Hardware Development for Analytical and Computational Materials Science

The focus of this Cooperative Agreement between the Computational Materials Laboratory (CML) of the Processing Science and Technology Branch of the NASA Glenn Research Center (GRC) and the Department of Theoretical and Applied Mathematics at The University of Akron was in the areas of system development of the CML workstation environment, modeling of microgravity and earth-based material processing systems, and joint activities in laboratory projects. These efforts complement each other as the majority of the modeling work involves numerical computations to support laboratory investigations. Coordination and interaction between the modelers, system analysts, and laboratory personnel are essential toward providing the most effective simulations and communication of the simulation results. Toward these means, The University of Akron personnel involved in the agreement worked at the Applied Mathematics Research Laboratory (AMRL) in the Department of Theoretical and Applied Mathematics while maintaining a close relationship with the personnel of the Computational Materials Laboratory at GRC. Network communication between both sites has been established. A summary of the projects we undertook during the time period 9/1/03 - 6/30/04 is included.

Young, Gerald W.↗