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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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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Multi-element stochastic spectral projection for high quantile estimation

We investigate quantile estimation by multi-element generalized Polynomial Chaos (gPC) metamodel where the exact numerical model is approximated by complementary metamodels in overlapping domains that mimic the model’s exact response. The gPC metamodel is constructed by the non-intrusive stochastic spectral projection approach and function evaluation on the gPC metamodel can be considered as essentially free. Thus, large number of Monte Carlo samples from the metamodel can be used to estimate α-quantile, for moderate values of α. As the gPC metamodel is an expansion about the means of the inputs, its accuracy may worsen away from these mean values where the extreme events may occur. By increasing the approximation accuracy of the metamodel, we may eventually improve accuracy of quantile estimation but it is very expensive. A multi-element approach is therefore proposed by combining a global metamodel in the standard normal space with supplementary local metamodels constructed in bounded domains about the design points corresponding to the extreme events. To improve the accuracy and to minimize the sampling cost, sparse-tensor and anisotropic-tensor quadratures are tested in addition to the full-tensor Gauss quadrature in the construction of local metamodels; different bounds of the gPC expansion are also examined. The global and local metamodels are combined in the multi-element gPC (MEgPC) approach and it is shown that MEgPC can be more accurate than Monte Carlo or importance sampling methods for high quantile estimations for input dimensions roughly below N=8, a limit that is very much case- and α-dependent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
DOE OSTI2023

An Efficient High-Order Solver for Diffusion Equations with Strong Anisotropy on Non-Anisotropy-Aligned Meshes

This paper concerns numerical solution of the diffusion equation with strong anisotropy on meshes not aligned with the anisotropic vector field. In order to resolve the numerical pollution for simulations on a non-anisotropy-aligned mesh and reduce the associated high computational cost we propose an effective preconditioner, extending our previous work. Similar to the anisotropy-aligned mesh case, we apply the auxiliary space preconditioning framework to design a preconditioner where a continuous finite element space is used as the auxiliary space for the discontinuous finite element space. The key component is an effective line smoother that can mitigate the high-frequency errors perpendicular to the magnetic field. We design a graph-based approach to find such a line smoother that is approximately perpendicular to the vector fields when the mesh does not align with the anisotropy. Finally, numerical experiments for several benchmark problems are presented, demonstrating the effectiveness and robustness of the proposed preconditioner when applied to Krylov iterative methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Provably conservative approximations to complex reliability models

Complex models can be the bases for derivation of provably conservative and optimistic reliability models that incorporate a reduced state space and fewer transitions; they accordingly possess solutions that are more cost-effective than those of the original complex models. Design space can thereby be extensively explored without incurring the expense of multiple complex model solutions. A conservative-optimistic pair of derived models produces a band that includes the solution to the complex model. Sensitivity analysis can be performed on this pair of models to determine those parameters of the original model that are most sensitive to change and therefore require further expense in obtaining tighter specifications.

Smotherman, M.↗
DOE OSTI2022

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗
NASA NTRS2004

WaFIRS, a Waveguide Far-IR Spectrometer: Enabling Space-Borne Spectroscopy of High-z Galaxies in the Far-IR and Submm

The discovery of galaxies beyond z approximately equal to 1 which emit the bulk of their luminosity at long wavelengths has demonstrated the need for high sensitivity, broadband spectroscopy in the far-IR/submm/mm bands. Because many of these sources are not detectable in the optical, long wavelength spectroscopy is key to measuring their redshifts and ISM conditions. The continuum source list will increase in the next decade with new ground-based instruments (SCUBA2, Bolocam, MAMBO) and the surveys of HSO and SIRTF. Yet the planned spectroscopic capabilities lag behind, primarily due to the difficulty in scaling existing IR spectrograph designs to longer wavelengths. To overcome these limitations, we are developing WaFIRS, a novel concept for long-wavelength spectroscopy which utilizes a parallel-plate waveguide and a curved diffraction grating. WaFIRS provides the large (approximately 60%) instantaneous bandwidth and high throughput of a conventional grating system, but offers a dramatic reduction in volume and mass. WaFIRS requires no space overheads for extra optical elements beyond the diffraction grating itself, and is two-dimensional because the propagation is confined between two parallel plates. Thus several modules could be stacked to multiplex either spatially or in different frequency bands. The size and mass savings provide opportunities for spectroscopy from space-borne observatories which would be impractical with conventional spectrographs. With background-limited detectors and a cooled 3.5 telescope, the line sensitivity would be better than that of ALMA, with instantaneous broad-band coverage. We have built and tested a WaFIRS prototype for 1-1.6 mm, and are currently constructing Z-Spec, a 100 mK model to be used as a ground-based lambda/DELTAlambda approximately equal to 350 submillimeter galaxy redshift machine.

Bradford, C. M.↗
NASA NTRS1992

Overview of the relevant CFD work at Thiokol Corporation

An in-house developed proprietary advanced computational fluid dynamics code called SHARP (Trademark) is a primary tool for many flow simulations and design analyses. The SHARP code is a time dependent, two dimensional (2-D) axisymmetric numerical solution technique for the compressible Navier-Stokes equations. The solution technique in SHARP uses a vectorizable implicit, second order accurate in time and space, finite volume scheme based on an upwind flux-difference splitting of a Roe-type approximated Riemann solver, Van Leer's flux vector splitting, and a fourth order artificial dissipation scheme with a preconditioning to accelerate the flow solution. Turbulence is simulated by an algebraic model, and ultimately the kappa-epsilon model. Some other capabilities of the code are 2-D two-phase Lagrangian particle tracking and cell blockages. Extensive development and testing has been conducted on the 3-D version of the code with flow, combustion, and turbulence interactions. The emphasis here is on the specific applications of SHARP in Solid Rocket Motor design. Information is given in viewgraph form.

Chwalowski, Pawel↗
NASA NTRS1992

Aerospace applications of SINDA/FLUINT at the Johnson Space Center

SINDA/FLUINT has been found to be a versatile code for modeling aerospace systems involving single or two-phase fluid flow and all modes of heat transfer. Several applications of SINDA/FLUINT are described in this paper. SINDA/FLUINT is being used extensively to model the single phase water loops and the two-phase ammonia loops of the Space Station Freedom active thermal control system (ATCS). These models range from large integrated system models with multiple submodels to very detailed subsystem models. An integrated Space Station ATCS model has been created with ten submodels representing five water loops, three ammonia loops, a Freon loop and a thermal submodel representing the air loop. The model, which has approximately 800 FLUINT lumps and 300 thermal nodes, is used to determine the interaction between the multiple fluid loops which comprise the Space Station ATCS. Several detailed models of the flow-through radiator subsystem of the Space Station ATCS have been developed. One model, which has approximately 70 FLUINT lumps and 340 thermal nodes, provides a representation of the ATCS low temperature radiator array with two fluid loops connected only by conduction through the radiator face sheet. The detailed models are used to determine parameters such as radiator fluid return temperature, fin efficiency, flow distribution and total heat rejection for the baseline design as well as proposed alternate designs. SINDA/FLUINT has also been used as a design tool for several systems using pressurized gasses. One model examined the pressurization and depressurization of the Space Station airlock under a variety of operating conditions including convection with the side walls and internal cooling. Another model predicted the performance of a new generation of manned maneuvering units. This model included high pressure gas depressurization, internal heat transfer and supersonic thruster equations. The results of both models were used to size components, such as the heaters and gas bottles and also to point to areas where hardware testing was needed.

Ewert, Michael K.↗
DOE OSTI2019

Learning nonlinear level sets for dimensionality reduction in function approximation

We developed a Nonlinear Level-set Learning (NLL) method for dimensionality reduction in high-dimensional function approximation with small data. This work is motivated by a variety of design tasks in real-world engineering applications, where practitioners would replace their computationally intensive physical models (e.g., high-resolution fluid simulators) with fast-to-evaluate predictive machine learning models, so as to accelerate the engineering design processes. There are two major challenges in constructing such predictive models: (a) high-dimensional inputs (e.g., many independent design parameters) and (b) small training data, generated by running extremely time-consuming simulations. Thus, reducing the input dimension is critical to alleviate the over-fitting issue caused by data insufficiency. Existing methods, including sliced inverse regression and active subspace approaches, reduce the input dimension by learning a linear coordinate transformation; our main contribution is to extend the transformation approach to a nonlinear regime. Specifically, we exploit reversible networks (RevNets) to learn nonlinear level sets of a high-dimensional function and parameterize its level sets in low-dimensional spaces. A new loss function was designed to utilize samples of the target functions' gradient to encourage the transformed function to be sensitive to only a few transformed coordinates. The NLL approach is demonstrated by applying it to three 2D functions and two 20D functions for showing the improved approximation accuracy with the use of nonlinear transformation, as well as to an 8D composite material design problem for optimizing the buckling-resistance performance of composite shells of rocket inter-stages.

Zhang, Guannan↗
NASA NTRS2020

Optical Design of the Origins Space Telescope

The optical design is presented for the Origins Space Telescope, one of four large missions under study in preparation for the 2020 Decadal Survey in Astronomy and Astrophysics is presented. Sensitive to the mid- and far-infrared spectrum (between 2.8 and 588 µm) and set to launch in approximately 2035, Origins sets out to answer a number of important scientific questions by addressing NASA's three key science goals in astrophysics: How does the universe work?, How did we get here, and Are we alone? To do so, Origins seeks to answer three main questions: 1) How do galaxies form stars, build up metals, and grow their central supermassive black holes from reionization to today? 2) How do the conditions for habitability develop during the process of planet formation? 3) Do planets orbiting M-dwarf stars support life?The Origins telescope has a 5.9 m diameter primary mirror and operates at f/14. The large on-axis primary consists of 18 'keystone' segments of two different prescriptions arranged in two annuli (six inner and twelve outer segments) that together form a circular aperture in the goal of achieving a symmetric point spread function. To simplify the design, the telescope will be launched with both the primary mirror segments and the secondary mirror already deployed. To accommodate the 46 x 15 arcminute full field of view of the telescope at the design wavelength of = 30 µm, a three-mirror anastigmat configuration is used. The design is diffraction-limited across its instruments' fields of view. A brief discussion of each of the three baselined instruments within the Instrument Accommodation Module (IAM) is presented: 1) Origins Survey Spectrometer (OSS), 2) Mid-infrared Spectrometer, Camera (MISC) transit spectrometer channel, and 3) Far-Infrared Polarimeter/Imager (FIP). In addition, the upscope options for the observatory are laid out as well, including a fourth instrument: the Heterodyne Receiver for Origins (HERO).

Howard, Joseph↗
NASA NTRS1977

Comparison of some optimal control methods for the design of turbine blades

This paper attempts a comparative study of some numerical methods for the optimal control design of turbine blades whose vibration characteristics are approximated by Timoshenko beam idealizations with shear and incorporating simple boundary conditions. The blade was synthesized using the following methods: (1) conjugate gradient minimization of the system Hamiltonian in function space incorporating penalty function transformations, (2) projection operator methods in a function space which includes the frequencies of vibration and the control function, (3) epsilon-technique penalty function transformation resulting in a highly nonlinear programming problem, (4) finite difference discretization of the state equations again resulting in a nonlinear program, (5) second variation methods with complex state differential equations to include damping effects resulting in systems of inhomogeneous matrix Riccatti equations some of which are stiff, (6) quasi-linear methods based on iterative linearization of the state and adjoint equation. The paper includes a discussion of some substantial computational difficulties encountered in the implementation of these techniques together with a resume of work presently in progress using a differential dynamic programming approach.

Desilva, B. M. E.↗
NASA NTRS1988

Engineering planetary lasers for interstellar communication

Transmitting large amounts of data efficiently among neighboring stars will vitally support any eventual contact with extrasolar intelligence, whether alien or human. Laser carriers are particularly suitable for high-quality, targeted links. Space laser transmitter systems designed by this work, based on both demonstrated and imminent advanced space technology, could achieve reliable data transfer rates as high as 1 kb/s to matched receivers as far away as 25 pc, a distance including over 700 approximately solar-type stars. The centerpiece of this demonstration study is a fleet of automated spacecraft incorporating adaptive neural-net optical processing active structures, nuclear electric power plants, annular momentum control devices, and ion propulsion. Together the craft sustain, condition, modulate, and direct to stellar targets an infrared laser beam extracted from the natural mesospheric, solar-pumped, stimulated CO2 emission recently discovered at Venus. For a culture already supported by mature interplanetary industry, the cost of building planetary or high-power space laser systems for interstellar communication would be marginal, making such projects relevant for the next human century. Links using high-power lasers might support data transfer rates as high as optical frequencies could ever allow. A nanotechnological society such as we might become would inevitably use 10 to the 20th power b/yr transmission to promote its own evolutionary expansion out of the galaxy.

Sherwood, Brent↗
NASA NTRS1992

Closed Ecological Life Support Systems (CELSS) Test Facility

The CELSS Test Facility (CTF) is being developed for installation on Space Station Freedom (SSF) in August 1999. It is designed to conduct experiments that will determine the effects of microgravity on the productivity of higher (crop) plants. The CTF will occupy two standard SSF racks and will accommodate approximately one square meter of growing area and a canopy height of 80 cm. The growth volume will be isolated from the external environment, allowing stringent control of environmental conditions. Temperature, humidity, oxygen, carbon dioxide, and light levels will all be closely controlled to prescribed set points and monitored. This level of environmental control is needed to prevent stress and allow accurate assessment of microgravity effect (10-3 to 10-6 x g). Photosynthetic rates and respiration rates, calculated through continuous recording of gas concentrations, transpiration, and total and edible biomass produced will be measured. Toxic byproducts will be monitored and scrubbed. Transpiration water will be collected within the chamber and recycled into the nutrient solution. A wide variety of crop plants, e.g., wheat, soy beans, lettuce, potatoes, can be accommodated and various nutrient delivery systems and light delivery systems will be available. In the course of its development, the CTF will exploit fully, and contribute importantly, to the state-of-art in closed system technology and plant physiology.

Macelroy, Robert D.↗
NASA NTRS1997

Current Activities and Capabilities of the Terrestrial Environment Group at NASA's Marshall Space Flight Center

The National Aeronautics and Space Administration (NASA) designated Marshall Space Flight Center (MSFC) the center of excellence for space transportation. The Aerospace Environments and Effects (AEE) team of the Electromagnetics and Aerospace Environments Branch (EL23) in the Systems Analysis and Integration Laboratory at MSFC, supports the center of excellence designation by providing near-Earth space, deep space, planetary, and terrestrial environments expertise to projects as required. The Terrestrial Environment (TE) group within the AEE team maintains an extensive TE data base. Statistics and models derived from this data are applied to the design and development of new aerospace vehicles, as well as performance enhancement of operational vehicles such as the Space Shuttle. The TE is defined as the Earth's atmospheric environment extending from the surface to orbital insertion altitudes (approximately 90 km).

Roberts, Barry C.↗
NASA NTRS2001

Stirling Radioisotope Power System as an Alternative for NASAs Deep Space Missions

The NASA Glenn Research Center (GRC) and the Department of Energy (DOE) are developing a free-piston Stirling convertor for a Stirling Radioisotope Power System (SRPS) to provide on-board electric power for future NASA deep space missions. The SRPS currently being developed provides about 100 watts and reduces the amount of radioisotope fuel by a factor of four over conventional Radioisotope Thermoelectric Generators (RTG). The present SRPS design has a specific power of approximately 4 W/kg which is comparable to an RTG. GRC estimates for advanced versions of the SRPS with improved heat source integration, lightweight Stirling convertors, composite radiators, and chip-packaged controllers improves the specific mass to about 8 W/kg. Additional information is contained in the original extended abstract.

Shaltens, R. K.↗
NASA NTRS2005

Ionizing Radiation Environment on the International Space Station: Performance vs. Expectations for Avionics and Material

The role of structural shielding mass in the design, verification, and in-flight performance of International Space Station (ISS), in both the natural and induced orbital ionizing radiation (IR) environments, is reported. Detailed consideration of the effects of both the natural and induced ionizing radiation environment during ISS design, development, and flight operations has produced a safe, efficient manned space platform that is largely immune to deleterious effects of the LEO ionizing radiation environment. The assumption of a small shielding mass for purposes of design and verification has been shown to be a valid worst-case approximation approach to design for reliability, though predicted dependences of single event effect (SEE) effects on latitude, longitude, SEP events, and spacecraft structural shielding mass are not observed. The Figure of Merit (FOM) method over predicts the rate for median shielding masses of about 10g/cm(exp 2) by only a factor of 3, while the Scott Effective Flux Approach (SEFA) method overestimated by about one order of magnitude as expected. The Integral Rectangular Parallelepiped (IRPP), SEFA, and FOM methods for estimating on-orbit (Single Event Upsets) SEU rates all utilize some version of the CREME-96 treatment of energetic particle interaction with structural shielding, which has been shown to underestimate the production of secondary particles in heavily shielded manned spacecraft. The need for more work directed to development of a practical understanding of secondary particle production in massive structural shielding for SEE design and verification is indicated. In contrast, total dose estimates using CAD based shielding mass distributions functions and the Shieldose Code provided a reasonable accurate estimate of accumulated dose in Grays internal to the ISS pressurized elements, albeit as a result of using worst-on-worst case assumptions (500 km altitude x 2) that compensate for ignoring both GCR and secondary particle production in massive structural shielding.

Koontz, Steven L.↗
NASA NTRS2011

Time Domain Tool Validation Using ARES I-X Flight Data

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.

Hough, Steven↗
NASA NTRS2014

Maneuver Design for the Juno Mission: Inner Cruise

The Juno spacecraft launched in August 2011 and, following a successful Earth flyby in October 2013, is on course for a nominal orbit insertion at Jupiter in July 2016. This paper examines the design and execution of deterministic and statistical trajectory correction maneuvers during the first approximately 27 months of post-launch operations that defined the "Inner Cruise" phase of the Juno mission. Topics of emphasis include the two deep space maneuvers, Earth flyby altitude biasing strategy, and the sequence of trajectory correction maneuvers executed in the weeks prior to the successful Earth gravity assist.

Pavlak, Thomas A.↗