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Results for “differentiable simulation”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Performance and human factors results from thrust vectoring investigations in simulated air combat

In support of research related to advanced fighter technology, the Langley Differential Maneuvering Simulator (DMS) has been used to investigate the effects of advanced aerodynamic concepts, parametric changes in performance parameters, and advanced flight control systems on the combat capability of fighter airplanes. At least five studies were related to thrust vectoring and/or inflight thrust reversing. The aircraft simulated ranged from F-4 class to F-15 class, and included the AV-8 Harrier. This paper presents an overview of these studies including the assumptions involved, trends of results, and human factors considerations that were found.

Pennington, J. E.↗
NASA NTRS1991

High performance computing system for flight simulation at NASA Langley

The computer architecture and components used in the NASA Langley Advanced Real-Time Simulation System (ARTSS) are briefly described and illustrated with diagrams and graphs. Particular attention is given to the advanced Convex C220 processing units, the UNIX-based operating system, the software interface to the fiber-optic-linked Computer Automated Measurement and Control system, configuration-management and real-time supervisor software, ARTSS hardware modifications, and the current implementation status. Simulation applications considered include the Transport Systems Research Vehicle, the Differential Maneuvering Simulator, the General Aviation Simulator, and the Visual Motion Simulator.

Cleveland, Jeff I., II↗
DOE OSTI2023

Learning subgrid-scale models with neural ordinary differential equations

We propose a new approach to learning the subgrid-scale model when simulating partial differential equations (PDEs) solved by the method of lines and their representation in chaotic ordinary differential equations, based on neural ordinary differential equations (NODEs). Solving systems with fine temporal and spatial grid scales is an ongoing computational challenge, and closure models are generally difficult to tune. Machine learning approaches have increased the accuracy and efficiency of computational fluid dynamics solvers. In this approach neural networks are used to learn the coarse- to fine-grid map, which can be viewed as subgrid-scale parameterization. We propose a strategy that uses the NODE and partial knowledge to learn the source dynamics at a continuous level. Our method inherits the advantages of NODEs and can be used to parameterize subgrid scales, approximate coupling operators, and improve the efficiency of low-order solvers. Numerical results with the two-scale Lorenz 96 ODE, the convection-diffusion PDE, and the viscous Burgers' PDE are used to illustrate this approach.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Use of piloted simulation for studies of fighter departure/spin susceptibility

The NASA-Langley Research Center has incorporated into its stall/spin research program on military airplanes the use of piloted, fixed-base simulation to complement the existing matrix of unique research testing techniques. The piloted simulations of fighter stall/departure flight dynamics are conducted on the Langley Differential Maneuvering Simulator (DMS). The paper reviews the objectives of the simulation research, presents the rationale underlying the simulation methods and procedures used in the evaluation of airplane characteristics, and discuss in detail the evaluation steps used to assess fighter stall/departure characteristics. Simulation results are presented to illustrate the flight-dynamics phenomena dealt with. The use of the piloted simulation methods and procedures described has been found very effective in identifying stability and control problem areas and in developing automatic control concepts to alleviate many of these problems. A good level of correlation between simulated flight dynamics and flight-test results has been obtained over the many fighter configurations studied in the simulator.

Gilbert, W. P.↗
NASA NTRS1978

Use of piloted simulation for studies of fighter departure/spin susceptibility

The NASA-Langley Research Center has incorporated into its stall/spin research program on military airplanes the use of piloted, fixed-base simulation to complement the existing matrix of unique research testing techniques. The piloted simulations of fighter stall/departure flight dynamics are conducted on the Langley Differential Maneuvering Simulator (DMS). The objectives of the simulation research are reviewed. The rationale underlying the simulation methods and procedures used in the evaluation of airplane characteristics is presented. The evaluation steps used to assess fighter stall/departure characteristics are discussed. Simulation results are presented to illustrate the flight dynamics phenomena dealt with. The considerable experience accumulated in the conduct of piloted stall/departure simulation indicates that simulation provides a realistic evaluation of an airplane's maneuverability at high angles of attack and an assessment of the departure and spin susceptibility of the airplane. This realism is obtained by providing the pilot a complete simulation of the airplane and control system which can be flown using a realistic cockpit and visual display in simulations of demanding air combat maneuvering tasks. The use of the piloted simulation methods and procedures described were found very effective in identifying stability and control problem areas and in developing automatic control concepts to alleviate many of these problems. A good level of correlation between simulated flight dynamics and flight test results were obtained over the many fighter configurations studied in the simulator.

Gilbert, W. P.↗
NASA NTRS1991

Comparative study on the performance of power and bandwidth efficient modulations in LMSS under fading and interference

Aspects of error performance of various power and bandwidth efficient modulations for the land mobile satellite systems (LMSS) were investigated under multipath fading and interferences by using Monte-Carlo simulation. A differential detection for 16QAM (quadrature amplitude modulation) was proposed to cope with Ricean fading and Doppler shift. Computer simulation results show that the performance of 16QAM with differential detection is as good as that of 16PSK with coherent detection and 3 dB better than that of 16PSK with differential detection, although it degrades by about 4.5 dB as compared to 16QAM with coherent detection under an additive white Gaussian noise (AWGN) channel. For the nonlinear channels, 16QAM with modified signal constellations is introduced and analyzed. The simulation results show that the modified 16QAM exhibits a gain of 2.5 dB over 16PSK under traveling-wave tube nonlinearity, and about 4 dB gain over 16PSK at the bit error rate of 10 exp -5 under AWGN. Computer simulation results for modified 16 QAM under cochannel interference and adjacent-channel interference are also presented.

Liu, Jian↗
NASA NTRS2026

High Temperature Dielectric Properties and Differential Scanning Calorimetry of Lunar Simulants

To guide development of microwave process technology that could be used during in situ construction on the Moon, we measured the high-temperature basic dielectric properties (εʹ and εʺ) of 17 lunar simulants and related materials. In order to confidently use these data one needs to understand the data’s strengths and weaknesses. Therefore, a goal of this publication is to provide insights into the comparative effects of sample composition, pre-treatments, experimental variables, high temperatures, and other factors on the measured response. The dielectric measurements were performed using the cavity perturbation method over a temperature range between room temperature to 1000 °C, or higher, and provided the real and imaginary components of permittivity at six frequencies. The utility of the original values was limited by the varying density of the pellets used in the measurement. Therefore, all of the εʹ and εʺ measurements at the frequency of 2466 MHz have been scaled to a constant density, 1.75 g/cm 3 . Here the data are presented as graphs chosen to aid analysis within and across simulant groups. To gain additional insight into the processes happening at the elevated temperatures in the dielectric measurements, heat capacity data was obtained using differential scanning calorimetry (DSC) on several of the simulant materials. Our data show that over the frequency range 397 MHz – 2985 MHz a material’s behavior does not greatly change, as compared to the scale of differences observed between lunar mare and highland simulants at high temperatures. For example at 1000 °C, the mare simulant JSC-1A absorbs 10 times more power than the highland simulant NUW-LHT-5M. We observe that as melting temperatures are reached both permittivity and dielectric loss rise non-linearly, helping to explain thermal runaway during microware heating. Our data show that even less than a few weight % of many non-lunar minerals, and the use of mixtures in simulants can affect the dielectric behavior at higher temperatures. A comparison of our results with published dielectric data for Apollo samples and with remote sensing of the Moon supports the conclusion the simulants and lunar material at room temperature have very similar dielectric values.

Differential Scanning Calorimetry↗
DOE OSTI2023

Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0

Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0

Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Machine learning of hidden variables in multiscale fluid simulation

Solving fluid dynamics equations often requires the use of closure relations that account for missing microphysics. For example, when solving equations related to fluid dynamics for systems with a large Reynolds number, sub-grid effects become important and a turbulence closure is required, and in systems with a large Knudsen number, kinetic effects become important and a kinetic closure is required. By adding an equation governing the growth and transport of the quantity requiring the closure relation, it becomes possible to capture microphysics through the introduction of ‘hidden variables’ that are non-local in space and time. The behavior of the ‘hidden variables’ in response to the fluid conditions can be learned from a higher fidelity or ab-initio model that contains all the microphysics. In our study, a partial differential equation simulator that is end-to-end differentiable is used to train judiciously placed neural networks against ground-truth simulations. We show that this method enables an Euler equation based approach to reproduce non-linear, large Knudsen number plasma physics that can otherwise only be modeled using Boltzmann-like equation simulators such as Vlasov or particle-in-cell modeling.

42 ENGINEERING↗
NASA NTRS1979

Computer-automated opponent for manned air-to-air combat simulations

Two versions of a real-time digital-computer program that operates a fighter airplane interactively against a human pilot in simulated air combat were evaluated. They function by replacing one of two pilots in the Langley differential maneuvering simulator. Both versions make maneuvering decisions from identical information and logic; they differ essentially in the aerodynamic models that they control. One is very complete, but the other is much simpler, primarily characterizing the airplane's performance (lift, drag, and thrust). Both models competed extremely well against highly trained U.S. fighter pilots.

Hankins, W. W., III↗
NASA NTRS1982

Research through simulation

The design of the computer operating system at Langley Research Center allows for concurrent support of time-critical simulations and background analytical computing on the same machine. Signal path interconnections between computing hardware and flight simulation hardware is provided to allow up to six simulation programs to be in operation at one time. Capabilities and research applications are discussed for the: (1) differential maneuvering simulator; (2) visual motion simulator; (3) terminal configured vehicle simulator; (4) general aviation aircraft simulator; (5) general purpose fixed based simulator; (6) transport simulator; (7) digital fly by wire simulator; (8) general purpose fighter simulator; and (9) the roll-up cockpit. The visual landing display system and graphics display system are described and their simulator support applications are listed.

Copeland, J. L.↗
NASA NTRS2005

An Investigation of the Impact of Aerodynamic Model Fidelity on Close-In Combat Effectiveness Prediction in Piloted Simulation

Several aircraft airframe modeling approaches are currently being used in the DoD community for acquisition, threat evaluation, training, and other purposes. To date there has been no clear empirical study of the impact of airframe simulation fidelity on piloted real-time aircraft simulation study results, or when use of a particular level of fidelity is indicated. This paper documents a series of piloted simulation studies using three different levels of airframe model fidelity. This study was conducted using the NASA Langley Differential Maneuvering Simulator. Evaluations were conducted with three pilots for scenarios requiring extensive maneuvering of the airplanes during air combat. In many cases, a low-fidelity modified point-mass model may be sufficient to evaluate the combat effectiveness of the aircraft. However, in cases where high angle-of-attack flying qualities and aerodynamic performance are a factor or when precision tracking ability of the aircraft must be represented, use of high-fidelity models is indicated.

Persing, T. Ray↗
NASA NTRS1982

Piloted simulator evaluation of a relaxed static stability fighter at high angle-of-attack

A piloted simulator evaluation of the stability and control characteristics of a relaxed static stability fighter aircraft was conducted using a differential maneuvering simulator. The primary purpose of the simulation was to evaluate the effectiveness of the limiters in preventing departure from controlled flight. The simulation was conducted in two phases, the first consisting of open-loop point stability evaluations over a range of subsonic flight conditions, the second concentrating on closed-loop tracking of a preprogrammed target in low speed, high angle-of-attack air combat maneuvering. The command limiters were effective in preventing departure from controlled flight while permitting competent levels of sustained maneuvering. Parametric variations during the study included the effects of pitch control power and wing-body static margin. Stability and control issues were clearly shown to impact the configuration design.

Lapins, M.↗
NASA NTRS1998

Rotaing Systems Used as Microgravity Simulators for Studies of Cartilage Differentiation

Just as Studies of abnormal chondrogenesis produced by mutation or teratogen add to our understanding of the normal chondrogenic process, studying chondrogenesis in space may assist in 1 g studies of chondrogenic defects. Opportunities to study cartilage differentiation in space, however, are limited, so systems have been developed which can be used at 1 g to simulate microgravity. One model used to mimic effects of microgravity is the clinostat a rotating system which converts gravity from a vector quantity to a scalar quantity. In slow rotating clitiostat systems, cells are attached to a substrate as at 1 g, and rotated with the plane of the culture perpendicular to the gravitational field. Another rotating system used as a microgravity simulator is the Slow Turning Lateral Vessel (STLV) which uses a rotating cylindrical vessel, completely filled with medium to culture cells in suspension without subjecting them to damaging shear forces. Embronic limb cells cultured in the slow rotating clinostat, the STLV, and in space exhibit changes in chondrogenesis related to the stage at which the cells are exposed. Clinorotation decreases the number of nodules in micromass cultures, showing an effect on the condensation process. In micromass cultures flown in space, condensation occurred preflight, so the primary effect of microgravity exposure was on matrix production. In chondrocytes in the STLV, as in growth plates of spaceflown rats, hypertrophy was decreased. Future clinostat and spaceflight experiments will examine the effect on adhesive molecules and on cytoskeletal organization because of their involvement in the processes that are affected. The mechanisms by which micro-gravity alters phenotype modulation, matrix production and aggregation, and chondrocyte hypertrophy after the cartilage phenotype is established must also be elucidated. The mechanisms resulting in cartilage defects are to a large extent unknown, and microgravitv may provide a way to identify them.

Duke, Pauline Jackie↗
DOE OSTI2021

MADLens, a python package for fast and differentiable non-Gaussian lensing simulations

Here, we present MADLens a python package for producing non-Gaussian lensing convergence maps at arbitrary source redshifts with unprecedented precision. MADLens is designed to achieve high accuracy while keeping computational costs as low as possible. A MADLens simulation with only particles produces convergence maps whose power agrees with theoretical lensing power spectra up to within the accuracy limits of HaloFit. This is made possible by a combination of a highly parallelizable particle-mesh algorithm, a sub-evolution scheme in the lensing projection, and a machine-learning inspired sharpening step. Further, MADLens is fully differentiable with respect to the initial conditions of the underlying particle-mesh simulations and a number of cosmological parameters. These properties allow MADLens to be used as a forward model in Bayesian inference algorithms that require optimization or derivative-aided sampling. Another use case for MADLens is the production of large, high resolution simulation sets as they are required for training novel deep-learning-based lensing analysis tools. We make the MADLens package publicly available under a Creative Commons License

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of time and spatial domains on monolayer 2D material interface thermal conductance measurement using ns ET-Raman

Raman-based approaches to characterizing thermal properties of nanoscale and microscale materials have proven to be powerful experimental methods. Here, this work explores the potential of energy-transport state-resolved Raman (ET-Raman) for the precise determination of interfacial thermal conductance (G) between monolayer 2D materials and their substrates. ET-Raman employs a continuous wave laser and nanosecond (ns) pulsed laser to induce both steady state and transient heating while simultaneously collecting 2D material temperature information from the Raman signal. A 3D numerical model built using the finite volume method simulates the two differentiated thermal transport processes. The simulated temperature rises are compared with experimental Raman temperature information to extract G. In this study, we investigate the temporal effects of the pulse frequency and pulse width of the ns laser on precise characterization of G. By running multiple simulations for a range of pulsed laser frequencies and pulse widths, we determine that ET-Raman is most sensitive to precise interfacial thermal conductance measurements with short pulse widths (~below 20 ns) and with pulsing frequencies that ensure sufficient cooling time between consecutive pulses (~below 500 kHz). We also conclude that substrate thickness and laser spot size play critical roles in heat distribution and subsequent sensitivity to meaningful G measurements. As both laser spot size and SiO 2 substrate thickness decrease, detection of interfacial thermal transport becomes more difficult. These results offer essential guidance in the design of future Raman-based approaches to thermal measurements using pulsed lasers.

2D materials↗