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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

THE HAWAII INFRARED PARALLAX PROGRAM. II. YOUNG ULTRACOOL FIELD DWARFS

We present a large, uniform analysis of young (≈10–150 Myr) ultracool dwarfs, based on new high-precision infrared (IR) parallaxes for 68 objects. We find that low-gravity (vl-g) late-M and L dwarfs form a continuous sequence in IR color–magnitude diagrams, separate from the field population and from current theoretical models. These vl-g objects also appear distinct from young substellar (brown dwarf and exoplanet) companions, suggesting that the two populations may have a different range of physical properties. In contrast, at the L/T transition, young, old, and spectrally peculiar objects all span a relatively narrow range in near-IR absolute magnitudes. At a given spectral type, the IR absolute magnitudes of young objects can be offset from ordinary field dwarfs, with the largest offsets occurring in the Y and J bands for late-M dwarfs (brighter than the field) and mid-/late-L dwarfs (fainter than the field). Overall, low-gravity (vl-g) objects have the most uniform photometric behavior, while intermediate gravity (int-g) objects are more diverse, suggesting a third governing parameter beyond spectral type and gravity class. We examine the moving group membership for all young ultracool dwarfs with parallaxes, changing the status of 23 objects (including 8 previously identified planetary-mass candidates) and fortifying the status of another 28 objects. We use our resulting age-calibrated sample to establish empirical young isochrones and show a declining frequency of vl-g objects relative to int-g objects with increasing age. Notable individual objects in our sample include high-velocity (≳100 km s{sup −1}) int-g objects, very red late-L dwarfs with high surface gravities, candidate disk-bearing members of the MBM20 cloud and β Pic moving group, and very young distant interlopers. Finally, we provide a comprehensive summary of the absolute magnitudes and spectral classifications of young ultracool dwarfs, using a combined sample of 102 objects found in the field and as substellar companions to young stars.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Airframe noise measurements by acoustic imaging

Studies of the noise produced by flow past wind tunnel models are presented. The central objective of these is to find the specific locations within a flow which are noisy, and to identify the fluid dynamic processes responsible, with the expectation that noise reduction principles will be discovered. The models tested are mostly simple shapes which result in types of flow that are similar to those occurring on, for example, aircraft landing gear and wheel cavities. A model landing gear and a flap were also tested. Turbulence has been intentionally induced as appropriate in order to simulate full-scale effects more closely. The principal technique involves use of a highly directional microphone system which is scanned about the flow field to be analyzed. The data so acquired are presented as a pictorial image of the noise source distribution. An important finding is that the noise production is highly variable within a flow field and that sources can be attributed to various fluid dynamic features of the flow. Flow separation was not noisy, but separation closure usually was.

Kendall, J. M.↗
NASA NTRS1996

Optimization of Residual Stresses in MMC's through Process Parameter Control and the use of Heterogeneous Compensating/Compliant Interfacial Layers. OPTCOMP2 User's Guide

A user's guide for the computer program OPTCOMP2 is presented in this report. This program provides a capability to optimize the fabrication or service-induced residual stresses in unidirectional metal matrix composites subjected to combined thermomechanical axisymmetric loading by altering the processing history, as well as through the microstructural design of interfacial fiber coatings. The user specifies the initial architecture of the composite and the load history, with the constituent materials being elastic, plastic, viscoplastic, or as defined by the 'user-defined' constitutive model, in addition to the objective function and constraints, through a user-friendly data input interface. The optimization procedure is based on an efficient solution methodology for the inelastic response of a fiber/interface layer(s)/matrix concentric cylinder model where the interface layers can be either homogeneous or heterogeneous. The response of heterogeneous layers is modeled using Aboudi's three-dimensional method of cells micromechanics model. The commercial optimization package DOT is used for the nonlinear optimization problem. The solution methodology for the arbitrarily layered cylinder is based on the local-global stiffness matrix formulation and Mendelson's iterative technique of successive elastic solutions developed for elastoplastic boundary-value problems. The optimization algorithm employed in DOT is based on the method of feasible directions.

Pindera, Marek-Jerzy↗
NASA NTRS1993

ROBOSIM: An intelligent simulator for robotic systems

The purpose of this paper is to present an update of an intelligent robotics simulator package, ROBOSIM, first introduced at Technology 2000 in 1990. ROBOSIM is used for three-dimensional geometrical modeling of robot manipulators and various objects in their workspace, and for the simulation of action sequences performed by the manipulators. Geometric modeling of robot manipulators has an expanding area of interest because it can aid the design and usage of robots in a number of ways, including: design and testing of manipulators, robot action planning, on-line control of robot manipulators, telerobotic user interface, and training and education. NASA developed ROBOSIM between 1985-88 to facilitate the development of robotics, and used the package to develop robotics for welding, coating, and space operations. ROBOSIM has been further developed for academic use by its co-developer Vanderbilt University, and has been in both classroom and laboratory environments for teaching complex robotic concepts. Plans are being formulated to make ROBOSIM available to all U.S. engineering/engineering technology schools (over three hundred total with an estimated 10,000+ users per year).

Fernandez, Kenneth R.↗
NASA NTRS1990

Satellite simulations utilizing CLIPS

Simulations provide necessary testbeds for system designs. Currently we are developing software whose main requirement is to produce CLIPS executable simulation code of a user prespecified system. This process minimizes the amount of engineering effort required to specify a system thereby reducing cost and providing the capability to quickly revise system definitions. Modeling satellite systems is the primary objective toward which testing has, and is, being conducted using satellite specifications. This paper describes the modeling software being developed, its formatted input and the CLIPS system simulation it produces.

Pauls, Barbara↗
DOE OSTI2021

Modeling Framework for Evaluating Grid Disturbances

Recent research in the literature proposed parameter-based functional forms to quantify the impact of disturbances on electric power grids. This modeling was based on a concept of generalized grid disturbances that harmonized reliability and resilience. Three main stages—avoid, react, and recover—were identified, and to support practicality, were intended to be independently planned. An objective of the grid disturbance model was to fairly analyze the potential impacts of novel mitigations like transactive energy systems (TES) on grid reliability and resilience. Quantitative evaluation of a common performance metric (e.g., area under the curve of percentage customers online before, during, and after an event) over time was shown as an effective tool for such analysis. Such quantification may also enable system planners to assess the impact of appropriate mitigative actions for improving grid performance against potential disturbances. This is the focus of this report, i.e., presenting an evaluation modeling framework that can be utilized to evaluate grid performance against disturbances, under a variety of existing and possible new mitigative actions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2010

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗
DOE OSTI2018

Dynamic elastic-plastic response of a 2-DOF mass-spring system.

The objective of the work presented here arose from abnormal, drop scenarios and specifically the question of how the accelerations and accumulation of plastic strains of internal components could be a ected by the material properties of the external structure. In some scenarios, the impact loads can induce cyclic motion of the internal components. Therefore, a second objective was to explore di erences that could be expected when simulations are conducted using isotropic hardening vs. kinematic hardening plasticity models. The simplest model that can be used to investigate the objectives above is a two-degree-offreedom mass/spring model where the springs exhibit elastic-plastic behavior. The purpose of this memo is to develop such model and present a few results that address the objectives.

42 ENGINEERING↗
NASA NTRS2026

Developing a Pyrolysis Gas Thermal Blocking Model for Reentry Demise

In NASA’s Object Reentry Survival Analysis Tool (ORSAT), aerodynamic drag and aerothermal heating coefficients are computed for each of the free-molecular, continuum, and transitional flow regimes using analytical and semi-analytical methods. These heating coefficients were derived for typical metallic materials that melt and do not have a strong gas-phase contribution to the flow in the boundary layer. Modern satellites typically feature fiber-reinforced polymer (FRP) components, such as solar array booms, facesheets of sandwich panels, or overwraps for composite-overwrapped pressure vessels (COPV). These FRP materials do not behave the same as metals in the reentry environment, but instead will pyrolyze and develop significant volumes of gas into the boundary layer. Accurately predicting the reentry demise of FRP components is critical to assessing the reentry casualty risk for modern spacecraft. Research in recent years has shown that this demisability can depend heavily on how the expulsion of gaseous pyrolysis products through the outer surface of the material affects the heat flux at the surface. The ODPO has been developing a reduced-order model of the effect of pyrolysis gas blowing on the heat flux based on correlations between a blowing factor and a non-dimensional heat flux to be incorporated in the upcoming version 7.3 of the Object Reentry Survivability Analysis Tool (ORSAT). This presentation discusses the progress of this development project and the challenges remaining for generalizing the model across families of FRP materials.

Benton Greene↗
NASA NTRS1993

Test model designs for advanced refractory ceramic materials

The next generation of space vehicles will be subjected to severe aerothermal loads and will require an improved thermal protection system (TPS) and other advanced vehicle components. In order to ensure the satisfactory performance system (TPS) and other advanced vehicle materials and components, testing is to be performed in environments similar to space flight. The design and fabrication of the test models should be fairly simple but still accomplish test objectives. In the Advanced Refractory Ceramic Materials test series, the models and model holders will need to withstand the required heat fluxes of 340 to 817 W/sq cm or surface temperatures in the range of 2700 K to 3000 K. The model holders should provide one dimensional (1-D) heat transfer to the samples and the appropriate flow field without compromising the primary test objectives. The optical properties such as the effective emissivity, catalytic efficiency coefficients, thermal properties, and mass loss measurements are also taken into consideration in the design process. Therefore, it is the intent of this paper to demonstrate the design schemes for different models and model holders that would accommodate these test requirements and ensure the safe operation in a typical arc jet facility.

Tran, Huy Kim↗
NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗
DOE OSTI2021

Hypernetwork Science: From Multidimensional Networks to Computational Topology

As data structures and mathematical objects used for complex systems modeling, hypergraphs sit nicely poised between on the one hand the world of network models, and on the other that of higher-order mathematical abstractions from algebra, lattice theory, and topology. They are able to represent complex systems interactions more faithfully than graphs and networks, while also being some of the simplest classes of systems representing topological structures as collections of multidimensional objects connected in a particular pattern. In this paper we discuss the role of (undirected) hypergraphs in the science of complex networks, and provide a mathematical overview of the core concepts needed for hypernetwork modeling, including duality and the relationship to bicolored graphs, quantitative adjacency and incidence, the nature of walks in hypergraphs, and available topological relationships and properties. We close with a brief discussion of two example applications: biomedical databases for disease analysis, and domain-name system (DNS) analysis of cyber data.

Joslyn, Cliff A.↗
NASA NTRS1985

A model of the polarization position-angle swings in BL Lacertae objects

The polarization position-angle swings that have been measured in a number of BL Lacertae objects and highly variable quasars are interpreted in terms of shock waves which illuminate (by enhanced synchrotron radiation) successive transverse cross sections of a magnetized, relativistic jet. The jet is assumed to have a nonaxisymmetric magnetic field configuration of the type discussed in the companion paper on the equilibria of force-free jets. For a jet that is viewed at a small angle to the axis, the passage of a shock will give rise to an apparent rotation of the polarization position angle whose amplitude can be substantially larger than 180 deg. The effects of freely propagating shocks are compared with those of bow shocks which form in front of dense obstacles in the jet, and specific applications to 0727 - 115 and BL Lacertae are considered. In the case of 0727 - 115, it is pointed out that the nonuniformity of the swing rate and the apparent oscillations of the degree of polarization could be a consequence of relativistic aberration.

Konigl, A.↗
NASA NTRS1987

Magnetic suspension and balance system (MSBS) advanced study.I - System design

A magnetic suspension and balance system is designed to support models of aircraft or other objects in wind tunnels by means of magnetic forces. Major design improvements have been achieved, resulting in reductions of the system size, weight, and cost. These improvements are due to: (1) the use of holmium in the model core to increase its magnetic moment, (2) the use of a powerful new permanent magnet material in the model wings, (3) a new arrangement for the roll coils, and (4) the use of a nonmetallic structure to eliminate eddy current losses. The conceptual design of the holmium core superconductive solenoid and of the new permanent magnet wing assembly is described in detail. The discussion includes comparisons of the pole strengths for different model core magnets, the design of a superconducting solenoid and cryostat, and the analysis of model wing magnetic requirements.

Boom, Roger W.↗
DOE OSTI2020

Expanding the design space of stratospheric aerosol geoengineering to include precipitation-based objectives and explore trade-offs

Previous climate modeling studies demonstrate the ability of feedback-regulated, stratospheric aerosol geoengineering with injection at multiple independent latitudes to meet multiple simultaneous temperature-based objectives in the presence of anthropogenic climate change. However, the impacts of climate change are not limited to rising temperatures but also include changes in precipitation, loss of sea ice, and many more; knowing how a given geoengineering strategy will affect each of these climate metrics is vital to understanding the limits and trade-offs of geoengineering. Here, we first introduce a new method of visualizing the design space in which desired climate outcomes are represented by 2-D surfaces on a 3-D graph. Surface orientations represent how different injection choices influence that objective, and intersecting surfaces represent objectives which can be met simultaneously. Using this representation as a guide, we present simulations of two new strategies for feedback-regulated aerosol injection, using the Community Earth System Model with the Whole Atmosphere Community Climate Model – CESM1(WACCM). The first simultaneously manages global mean temperature, tropical precipitation centroid, and Arctic sea ice extent, while the second manages global mean precipitation, tropical precipitation centroid, and Arctic sea ice extent. Both simulations control the tropical precipitation centroid to within 5 % of the goal, and the latter controls global mean precipitation to within 1% of the goal. Additionally, the first simulation overcompensates sea ice, while the second undercompensates sea ice; all of these results are consistent with the expectations of our design space model. In addition to showing that precipitation-based climate metrics can be managed using feedback alongside other goals, our simulations validate the utility of our design space visualization in predicting our climate model behavior under a given geoengineering strategy, and together they help illustrate the fundamental limits and trade-offs of stratospheric aerosol geoengineering.

58 GEOSCIENCES↗
NASA NTRS1978

Dynamic model verification of large structural systems

The objective of the present methodology is two-fold: (1) to process test data obtained from either modal survey tests, or slow sine-sweep tests, to extract a set of orthogonal modes best matching the test data while being commensurate with the dynamic model, and (2) to modify submatrices of the dynamic model mass and stiffness matrices to adjust the model to best fit the test data. The method has been implemented using a linear statistical sequential estimator for computation on a CDC computer. Demonstration problems involving Space Shuttle quarter-scale vibration test data and dynamic models have been run. This paper will discuss the general methodology and experience to date.

Lee, L. T.↗
DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗