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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Ultimate limits to error probabilities for ionospheric models based on solar geophysical indices and how these compare with the state of the art

An ideal model based on a given set of geophysical indices is defined as a model that provides a least squares fit to the data set as a function of the indices considered. Satellite measurements of electron content for three stations at different magnetic latitudes were used to provide such data sets which were each fitted to the geophysical indices. The magnitude of the difference between the measured value and the derived equation for the data set was used to estimate the probability of making an error greater than a given magnitude for such an ideal model. Atmospheric Explorer C data is used to examine the causes of the fluctuations and suggestions are made about how real improvements can be made in ionospheric forecasting ability. Joule heating inputs in the auroral electrojets are related to the AL and AU magnetic indices. Magnetic indices based on the time integral of the energy deposited in the electrojets are proposed for modeling processes affected by auroral zone heating.

Nisbet, J. S.↗
NASA NTRS1995

Model atmospheres for M (sub)dwarf stars. 1: The base model grid

We have calculated a grid of more than 700 model atmospheres valid for a wide range of parameters encompassing the coolest known M dwarfs, M subdwarfs, and brown dwarf candidates: 1500 less than or equal to T(sub eff) less than or equal to 4000 K, 3.5 less than or equal to log g less than or equal to 5.5, and -4.0 less than or equal to (M/H) less than or equal to +0.5. Our equation of state includes 105 molecules and up to 27 ionization stages of 39 elements. In the calculations of the base grid of model atmospheres presented here, we include over 300 molecular bands of four molecules (TiO, VO, CaH, FeH) in the JOLA approximation, the water opacity of Ludwig (1971), collision-induced opacities, b-f and f-f atomic processes, as well as about 2 million spectral lines selected from a list with more than 42 million atomic and 24 million molecular (H2, CH, NH, OH, MgH, SiH, C2, CN, CO, SiO) lines. High-resolution synthetic spectra are obtained using an opacity sampling method. The model atmospheres and spectra are calculated with the generalized stellar atmosphere code PHOENIX, assuming LTE, plane-parallel geometry, energy (radiative plus convective) conservation, and hydrostatic equilibrium. The model spectra give close agreement with observations of M dwarfs across a wide spectral range from the blue to the near-IR, with one notable exception: the fit to the water bands. We discuss several practical applications of our model grid, e.g., broadband colors derived from the synthetic spectra. In light of current efforts to identify genuine brown dwarfs, we also show how low-resolution spectra of cool dwarfs vary with surface gravity, and how the high-regulation line profile of the Li I resonance doublet depends on the Li abundance.

Allard, France↗
NASA NTRS1994

Model-based reconfiguration: Diagnosis and recovery

We extend Reiter's general theory of model-based diagnosis to a theory of fault detection, identification, and reconfiguration (FDIR). The generality of Reiter's theory readily supports an extension in which the problem of reconfiguration is viewed as a close analog of the problem of diagnosis. Using a reconfiguration predicate 'rcfg' analogous to the abnormality predicate 'ab,' we derive a strategy for reconfiguration by transforming the corresponding strategy for diagnosis. There are two obvious benefits of this approach: algorithms for diagnosis can be exploited as algorithms for reconfiguration and we have a theoretical framework for an integrated approach to FDIR. As a first step toward realizing these benefits we show that a class of diagnosis engines can be used for reconfiguration and we discuss algorithms for integrated FDIR. We argue that integrating recovery and diagnosis is an essential next step if this technology is to be useful for practical applications.

Crow, Judy↗
NASA NTRS2012

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Joshi, Suresh M.↗
NASA NTRS2015

Enhanced Engine Performance During Emergency Operation Using a Model-Based Engine Control Architecture

This paper discusses the design and application of model-based engine control (MBEC) for use during emergency operation of the aircraft. The MBEC methodology is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40,000) and features an optimal tuner Kalman Filter (OTKF) to estimate unmeasured engine parameters, which can then be used for control. During an emergency scenario, normally-conservative engine operating limits may be relaxed to increase the performance of the engine and overall survivability of the aircraft; this comes at the cost of additional risk of an engine failure. The MBEC architecture offers the advantage of estimating key engine parameters that are not directly measureable. Estimating the unknown parameters allows for tighter control over these parameters, and on the level of risk the engine will operate at. This will allow the engine to achieve better performance than possible when operating to more conservative limits on a related, measurable parameter.

control theory↗
NASA NTRS2016

Enhanced Engine Performance During Emergency Operation Using a Model-Based Engine Control Architecture

This paper discusses the design and application of model-based engine control (MBEC) for use during emergency operation of the aircraft. The MBEC methodology is applied to the Commercial Modular Aero-Propulsion System Simulation 40k (CMAPSS40k) and features an optimal tuner Kalman Filter (OTKF) to estimate unmeasured engine parameters, which can then be used for control. During an emergency scenario, normally-conservative engine operating limits may be relaxed to increase the performance of the engine and overall survivability of the aircraft; this comes at the cost of additional risk of an engine failure. The MBEC architecture offers the advantage of estimating key engine parameters that are not directly measureable. Estimating the unknown parameters allows for tighter control over these parameters, and on the level of risk the engine will operate at. This will allow the engine to achieve better performance than possible when operating to more conservative limits on a related, measurable parameter.

engine control↗
NASA NTRS2015

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

power load profile↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Bayesian calibration of stochastic agent based model via random forest

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
NASA NTRS1984

Region-based modeling algorithms for remotely-sensed data

Five algorithms being developed for performing region-based modeling operations on classified remotely-sensed images are described. The first algorithm converts images from standard grid structure into topological grid structure, while the remaining algorithms act upon topologically grid-structured images to perform region-based relabelling, overlaying, distance searching, and neighborhood scanning operations. The use of precomputed topological information, through the use of topological grid structure, makes region-based algorithms highly accessible to earth scientists.

Goldberg, M.↗
NASA NTRS2012

Model-Based Verification and Validation of Spacecraft Avionics

Verification and Validation (V&V) at JPL is traditionally performed on flight or flight-like hardware running flight software. For some time, the complexity of avionics has increased exponentially while the time allocated for system integration and associated V&V testing has remained fixed. There is an increasing need to perform comprehensive system level V&V using modeling and simulation, and to use scarce hardware testing time to validate models; the norm for thermal and structural V&V for some time. Our approach extends model-based V&V to electronics and software through functional and structural models implemented in SysML. We develop component models of electronics and software that are validated by comparison with test results from actual equipment. The models are then simulated enabling a more complete set of test cases than possible on flight hardware. SysML simulations provide access and control of internal nodes that may not be available in physical systems. This is particularly helpful in testing fault protection behaviors when injecting faults is either not possible or potentially damaging to the hardware. We can also model both hardware and software behaviors in SysML, which allows us to simulate hardware and software interactions. With an integrated model and simulation capability we can evaluate the hardware and software interactions and identify problems sooner. The primary missing piece is validating SysML model correctness against hardware; this experiment demonstrated such an approach is possible.

MBV&V↗
NASA NTRS2005

Model-Based Trade Space Exploration for Near-Earth Space Missions

We developed a capability for model-based trade space exploration to be used in the conceptual design of Earth-orbiting space missions. We have created a set of reusable software components to model various subsystems and aspects of space missions. Several example mission models were created to test the tools and process. This technique and toolset has demonstrated itself to be valuable for space mission architectural design.

space mission↗
NASA NTRS1991

A computer graphics based model for scattering from objects of arbitrary shapes in the optical region

A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.

Goel, Narendra S.↗
DOE OSTI2026

ReMU: regional minimal updating for model-based derivative-free optimization

Derivative-free optimization (DFO) problems are optimization problems where derivative information is unavailable or extremely difficult to obtain. Model-based DFO solvers have been applied extensively in scientific computing. Powell's NEWUOA (2004) [Powell, The NEWUOA software for unconstrained optimization without derivatives, in Large-Scale Nonlinear Optimization, Nonconvex Optimization and its Applications Vol. 83, G. Di Pillo and M. Roma, eds., Springer, 2006, pp. 255–297] and Wild's POUNDerS (2014) [Wild, Solving derivative-free nonlinear least squares problems with POUNDERS, in Advances and Trends in Optimization with Engineering Applications, T. Terlaky, M.F. Anjos, and S. Ahmed, eds., SIAM, 2017, pp. 529–540] explore the numerical power of the minimal norm Hessian (MNH) model for DFO and contributed to the open discussion on building better models with fewer data to achieve faster numerical convergence. Another decade later, we propose the regional minimal updating (ReMU) models, and extend the previous models into a broader class, including the H 2 norm models [Xie and Yuan, Least H 2 norm updating of quadratic interpolation models for derivative-free trust-region algorithms, IMA J. Numer. Anal. 46 (2025), pp. 21–50]. This paper shows motivation behind ReMU models, computational details, theoretical and numerical results on particular extreme points and the barycentre of ReMU's weight coefficient region, and the associated KKT matrix error and distance. Novel metrics, such as the truncated Newton step error, are proposed to numerically understand the new models' properties. A new algorithmic strategy, based on iteratively adjusting the ReMU model type, is also proposed, and shows numerical advantages by combining and switching between the barycentric model and the classic least Frobenius norm model in an online fashion.

derivative-free trust-region methods↗
NASA NTRS2012

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Galvan, Jose Ramon↗
NASA NTRSDate not supplied

Transition prediction in hypersonic regime on complex geometries with RANS-based models

In the near future, RANS computations will continue to play a significant role in the design of hypersonic vehicles with complex geometries. Therefore, it is imperative to continue testing, benchmarking, and refining the RANS models. In the present study, we evaluate RANS-like, transport equations-based models for predicting laminar-turbulent transition over a full-scale scale model of the BOLT flight configuration that was tested in the CUBRC LENS-II wind tunnel test facility. Based on the availability of the experimental results, comparisons are made between computations from several pre-existing transition models and Computational Fluid Dynamics (CFD) codes, with an emphasis on using the same computational meshes and flow conditions for all computations. The analysis covers the sensitivity of the transition predictions to the input parameters for five different transition models (four mainstream models designed for low-speed flows and a uniquely high-speed model), grid resolution, and the details of model implementation across three different flow solvers. The results show that the phenomenological models can describe significant aspects of the measured transition front. However, a number of additional improvements are required before these models can offer more reliable estimates of transition in high-speed flows.

CFD↗
NASA NTRSDate not supplied

Transition Prediction in Hypersonic Regime on Complex Geometries With Rans-Based Models

In the near future, RANS computations will continue to play a significant role in the design of hypersonic vehicles with complex geometries. Therefore, it is imperative to continue testing, benchmarking, and refining the RANS models. In the present study, we evaluate RANS-like, transport equations-based models for predicting laminar-turbulent transition over a full-scale scale model of the BOLT flight configuration that was tested in the CUBRC LENS-II wind tunnel test facility. Based on the availability of the experimental results, comparisons are made between computations from several pre-existing transition models and Computational Fluid Dynamics (CFD) codes, with an emphasis on using the same computational meshes and flow conditions for all computations. The analysis covers the sensitivity of the transition predictions to the input parameters for five different transition models (four mainstream models designed for low-speed flows and a uniquely high-speed model), grid resolution, and the details of model implementation across three different flow solvers. The results show that the phenomenological models can describe significant aspects of the measured transition front. However, a number of additional improvements are required before these models can offer more reliable estimates of transition in high-speed flows.

CFD↗