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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 NTRS2004

Specification of ISS Plasma Environment Variability

Quantifying spacecraft charging risks and associated hazards for the International Space Station (ISS) requires a plasma environment specification for the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IRI) model typically only provide long term (seasonal) mean Te and Ne values for the low Earth orbit environment. This paper describes a statistical analysis of historical ionospheric low Earth orbit plasma measurements from the AE-C, AE-D, and DE-2 satellites used to derive a model of deviations of observed data values from IRI-2001 estimates of Ne, Te parameters for each data point to provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output. Application of the deviation model with the IRI-2001 output yields a method for estimating extreme environments for the ISS spacecraft charging analysis.

Minow, Joseph I.↗
NASA NTRS2007

Space Propulsion Design and Analysis

This software provides an improved methodology for predicting launcher base pressure and heat loads for RSRM (Reusable Solid Rocket Motor) launchers by accounting for complex anisotropic stress/strains and variable turbulent Prandtl and Schmidt numbers. A "building block" approach to turbulence model development, and validation has been applied for improved missile/launcher base region analysis. Modifications to existing kappa - epsilon turbulence models and application of scalar variance models are incorporated into a RANS-based method for aeropropulsive flow modeling, directly related to base flow methodology. (RANS stands for Reynolds-averaged Navier-Stokes.) The models are applied in a RANS solver framework and can improve analysis of other complex flow fields. The enhanced models provide a more accurate predictive capability for improving the design and analysis of RSRM launcher configuration. The kappa - epsilon model enhancements have been shown to improve the capability for predicting turbulence effects in base blow environments. The scalar variance models have been assessed over a wide range of flow configurations to improve prediction of turbulent scalar mixing.

Sinha, Neeraj↗
NASA NTRS2018

WFIRST Coronagraph Flight Performance Modeling

As it has for the past few years, numerical modeling is being used to predict the on-orbit, high-contrast imaging performance of the WFIRST coronagraph, which was recently defined to be solely a technology demonstrator. A consequence has been a realignment of modeling priorities and revised applications of modeling uncertainty factors and margins, which apply to multiple factors such as pointing and wavefront jitter, thermally-induced deformations, polarization, and aberration sensitivities. At the same time, the models have increased in fidelity as additional parameters have been added, such as time-dependent pupil shear and mid-spatial-frequency deformations of the primary and secondary mirrors, detector effects, and reaction-wheel-speed-dependent pointing and wavefront jitter.

Trauger, John↗
NASA NTRS2001

A Component-based Programming Model for Composite, Distributed Applications

The nature of scientific programming is evolving to larger, composite applications that are composed of smaller element applications. These composite applications are more frequently being targeted for distributed, heterogeneous networks of computers. They are most likely programmed by a group of developers. Software component technology and computational frameworks are being proposed and developed to meet the programming requirements of these new applications. Historically, programming systems have had a hard time being accepted by the scientific programming community. In this paper, a programming model is outlined that attempts to organize the software component concepts and fundamental programming entities into programming abstractions that will be better understood by the application developers. The programming model is designed to support computational frameworks that manage many of the tedious programming details, but also that allow sufficient programmer control to design an accurate, high-performance application.

Eidson, Thomas M.↗
DOE OSTI2019

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1990

Design and fabrication of a long-life Stirling cycle cooler for space application. Phase 3: Prototype model

A second-generation, Stirling-cycle cryocooler (cryogenic refrigerator) for space applications, with a cooling capacity of 5 watts at 65 K, was recently completed. The refrigerator, called the Prototype Model, was designed with a goal of 5 year life with no degradation in cooling performance. The free displacer and free piston of the refrigerator are driven directly by moving-magnet linear motors with the moving elements supported by active magnetic bearings. The use of clearance seals and the absence of outgassing material in the working volume of the refrigerator enable long-life operation with no deterioration in performance. Fiber-optic sensors detect the radial position of the shafts and provide a control signal for the magnetic bearings. The frequency, phase, stroke, and offset of the compressor and expander are controlled by signals from precision linear position sensors (LVDTs). The vibration generated by the compressor and expander is cancelled by an active counter balance which also uses a moving-magnet linear motor and magnetic bearings. The driving signal for the counter balance is derived from the compressor and expander position sensors which have wide bandwidth for suppression of harmonic vibrations. The efficiency of the three active members, which operate in a resonant mode, is enhanced by a magnetic spring in the expander and by gas springs in the compressor and counterbalance. The cooling was achieved with a total motor input power of 139 watts. The magnetic-bearing stiffness was significantly increased from the first-generation cooler to accommodate shuttle launch vibrations.

Keung, C.↗
DOE OSTI2019

Optimization of Condensed Matter Physics Application with OpenMP Tasking Model

The Density Matrix Renormalization Group (DMRG++) is a condensed matter physics application used to study superconductivity properties of materials. It’s main computations consist of calculating hamiltonian matrix which requires sparse matrix-vector multiplications. This paper presents task-based parallelization and optimization strategies of the Hamiltonian algorithm. The algorithm is implemented as a mini-application in C++ and parallelized with OpenMP. The optimization leverages tasking features, such as dependencies or priorities included in the OpenMP standard 4.5. The code refactoring targets performance as much as programmability. The optimized version achieves a speedup of 8.0× with 8 threads and 20.5× with 40 threads on a Power9 computing node while reducing the memory consumption to 90 MB with respect to the original code, by adding less than ten OpenMP directives.

Criado, Joel↗
DOE OSTI2020

Gaining Perspective on Unconventional Well Design Choices through Play-level Application of Machine Learning Modeling

The recent development of unconventional oil and gas (O&G) reservoirs has led to an abundant hydrocarbon supply, both domestically and globally. However, there is a continued push to develop new and innovative approaches to improve exploration and extraction efficiencies and overall well productivity moving forward. Substantial improvements in unconventional O&G development are expected through optimized well completion and stimulation strategies aimed at maximizing well productivity. Optimizing well designs will require tailoring to the distinctive geologic conditions present for any newly placed well. To better evaluate the impact of well design attributes and their associated interactions on productivity in a major unconventional play, multivariate machine learning-based models that use empirical datasets were developed. A gradient boosted regression tree (GBRT) algorithm was applied. GBRT has been narrowly investigated for O&G applications but enables straightforward parametric importance and influence evaluation, as well as assessment of parameter interaction effects. Models were trained on well design and locational parameters that serve as a proxy for variable geologic conditions to estimate two types of productivity indicator response variables strongly correlated to estimated ultimate recovery (EUR). The dataset utilized consists of over 7,000 well observations that cover the majority of the productive region of the Marcellus Shale. Model performance was evaluated and algorithm parameters tuned by analyzing the goodness-of-fit for simulated results against observed data in a cross-validation approach. Models were found capable of 73–79 percent prediction accuracy on held out testing data of gas equivalent production and can be used to inform future well design and placement decisions for increasing EUR per well and improving overall field-level recovery. Study results indicate that Marcellus well performance improves most with upscaling perforated interval lengths and water and proppant volumes per foot; but relative productivity improvements are spatially dependent across the play. Finally, optimal combinations of water and proppant on well performance were found to vary depending on well location, emphasizing the utility of data-driven models capable of broad application across a play of interest for informing tailored well design approaches prior to their field deployment.

04 OIL SHALES AND TAR SANDS↗
NASA NTRS1990

An ocean scatter propagation model for aeronautical satellite communication applications

In this paper an ocean scattering propagation model, developed for aircraft-to-satellite (aeronautical) applications, is described. The purpose of the propagation model is to characterize the behavior of sea reflected multipath as a function of physical propagation path parameters. An accurate validation against the theoretical far field solution for a perfectly conducting sinusoidal surface is provided. Simulation results for typical L band aeronautical applications with low complexity antennas are presented.

Moreland, K. W.↗
NASA NTRS2012

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗
DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1995

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 2: Integrated loss of vehicle model

The application of the probabilistic risk assessment methodology to a Space Shuttle environment, particularly to the potential of losing the Shuttle during nominal operation is addressed. The different related concerns are identified and combined to determine overall program risks. A fault tree model is used to allocate system probabilities to the subsystem level. The loss of the vehicle due to failure to contain energetic gas and debris, to maintain proper propulsion and configuration is analyzed, along with the loss due to Orbiter, external tank failure, and landing failure or error.

Fragola, Joseph R.↗
NASA NTRS1991

On the application of algebraic turbulence models to high Mach number flows

In this paper the implementation of embedded-function algorithms for conventional algebraic turbulence models is described; using this methodology it is shown that the entire wall layer may be removed from the calculation algorithm (as well as near-wall mixing-length models) with no degradation in the accuracy of predicted results for skin friction. Various difficulties that are associated with the application of conventional algebraic models in high-speed flows are discussed. Alternative algebraic models are proposed which are cast in terms of the Howarth-Dorodnitsyn variable and which lead to a simple 'law of the wall' for both velocity and total enthalpy.

Degani, A. T.↗
NASA NTRS1972

Aspects of investigating STOL noise using large scale wind tunnel models

The applicability of the NASA Ames 40- by 80-ft wind tunnel for acoustic research on STOL concepts has been investigated. The acoustic characteristics of the wind tunnel test section has been studied with calibrated acoustic sources. Acoustic characteristics of several large-scale STOL models have been studied both in the free-field and wind tunnel acoustic environments. The results indicate that the acoustic characteristics of large-scale STOL models can be measured in the wind tunnel if the test section acoustic environment and model acoustic similitude are taken into consideration. The reverberant field of the test section must be determined with an acoustically similar noise source. Directional microphone and extrapolation of near-field data to far-field are some of the techniques being explored as possible solutions to the directivity loss in a reverberant field. The model sound pressure levels must be of sufficient magnitude to be discernable from the wind tunnel background noise.

Falarski, M. D.↗
NASA NTRS1973

Aspects of investigating STOL noise using large-scale wind-tunnel models.

The applicability of the NASA Ames 40- by 80-foot wind tunnel for acoustic research on STOL concepts has been investigated. The acoustic characteristics of the wind-tunnel test section have been studied with calibrated acoustic sources. Acoustic characteristics of several large-scale STOL models have been studied in both the free-field and wind-tunnel acoustic environments. The results of these studies indicate that the acoustic characteristics of large-scale STOL models can be measured in the wind tunnel if the test section acoustic environment and model acoustic similitude are taken into consideration. The reverberant field of the test section must be determined with an acoustically similar noise source. A directional microphone, a phased array of microphones, and extrapolation of near-field data to far-field are some of the techniques being explored as possible solutions to the directivity loss in a reverberant field. The model sound pressure levels must be of sufficient magnitude to be distinguishible from the wind-tunnel background noise.

Falarski, M. D.↗
DOE OSTI2019

Application and Evaluation of Surrogate Models for Radiation Source Search

Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous derivatives preclude the use of gradient-based optimization or data assimilation algorithms. We consider the problem of inferring the 2D location and intensity of a radiation source in an urban environment using a ray-tracing model based on Boltzmann transport theory. Whereas the code implementing this model is relatively efficient, extension to 3D Monte Carlo transport simulations precludes subsequent Bayesian inference to infer source locations, which typically requires thousands to millions of simulations. Additionally, the resulting likelihood exhibits discontinuous derivatives due to the presence of buildings. To address these issues, we discuss the construction of surrogate models for optimization, Bayesian inference, and uncertainty propagation. Specifically, we consider surrogate models based on Legendre polynomials, multivariate adaptive regression splines, radial basis functions, Gaussian processes, and neural networks. We detail strategies for computing training points and discuss the merits and deficits of each method.

Cook, Jared A.↗
DOE OSTI2019

An Accurate Fast Fluid Dynamics Model for Data Center Applications

Traditional CFD is broadly useful in the design and operation of reliable and efficient data centers. It is nevertheless computationally expensive, particularly when employed for design optimization, which usually requires multiple simulations. To speed-up calculations while retaining essential airflow physics, several researchers have turned to an alternative CFD methodology, namely, fast fluid dynamics (FFD). FFD has been reported to be much faster than traditional CFD, but at an assumed (acceptable) trade-off of reduced accuracy. However, a recent comparison of FFD and traditional CFD for data center plenum applications produced nearly indistinguishable results and suggested that previously-reported FFD/traditional-CFD differences were due primarily to inconsistent: 1) advection schemes, 2) computational grids, and 3) turbulence models. The present paper extends this FFD/traditional-CFD comparison to the data center whitespace and confirms the finding that a true like-for-like comparison produces nearly identical predictions. Our FFD implementation utilizes a first-order upwind finite-volume scheme for advection like traditional CFD, so alternative advection schemes (e.g., semi-Lagrangian) are not considered further here. Likewise, the effect of grid choice on traditional-CFD predictions is well known. However, the effect of turbulence model for data center applications has not been reported extensively so we do consider this topic further here. We compare the standard k-e and a simpler algebraic model to benchmark experimental data from a real data center. We find that the algebraic turbulence model predicts rack-inlet temperatures at a similar level-of-accuracy as the k-e model for our fairly-simple-airflow reference data center.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

Occupant behavior (OB) is one of the significant sources of uncertainty in building performance simulation. While OB modeling has received increased attention in the past decade, research on the degree of granularity or level of detail (LoD) required for representing occupants is still in the nascent stages. This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment. A medium-sized prototype office building located in Chicago, Illinois is used as the simulation case study. Ten occupant-centric attributes are adopted to develop the LoDs for OB representation. We first demonstrate the different modeling approaches required for simulating the three fidelity levels. Later, we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages. Furthermore, this study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗