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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 NTRS2022

Identification of Best Practices for Predicting Inlet Performance Using FUN3D Part 2: Installed Inlets.

A series of studies were performed to assess the impacts of boundary condition type and placement, grid refinement, and modeling parameters such as turbulence model and flux limiter on the predicted inlet performance for installed inlet configurations using the FUN3D flow solver. Two configurations were considered for the study; a wall-mounted Boundary Layer Ingestion (BLI) inlet and the C607 propulsion model tested in the 8x6 Supersonic Wind Tunnel at the NASA Glenn Research Center. The results of the studies were to be used to recommend best practices, as well as to assess the accuracy of FUN3D for inlet predictions. The results of BLI inlet stud-ies showed a minimal impact of grid refinement on the predicted inlet performance for a constant mass flow rate through the inlet. For the C607 propulsion model, the results showed that while the FUN3D predictions at the Aerodynamic Inter-face Plane (AIP) qualitatively agree with the experimental data, FUN3D showed a tendency to overpredict the circumferential distortion metric (IDCmax) and un-derpredict both the radial distortion metric (IDRmax) and the pressure recovery at the AIP (PRAIP ), with the differences between FUN3D and the experimental data increasing with increasing grid refinement and Mach number. Additionally, the outflow boundary location studies performed for both geometries showed that the solution at the AIP was not significantly impacted by the outflow boundary location as long as it was not placed at the location of the AIP. The modeling parameter studies did not indicate a path forward for improved predictions for either inlet con-figuration. Finally, comparisons between the mass flow plug and outflow geometry versions of the C607 propulsion model illustrated favorable agreement, which indi-cates that the differences observed are not caused by the outflow boundary model for this problem. This problem poses significant challenges to Reynolds-averaged Navier-Stokes (RANS) solvers due to the presence of shocks and flow separation in the inlet.

FUN3D↗
NASA NTRS2008

Virtual Shaker Testing: Simulation Technology Improves Vibration Test Performance

In the field of vibration testing, the interaction between the structure being tested and the instrumentation hardware used to perform the test is a critical issue. This is particularly true when testing massive structures (e.g. satellites), because due to physical design and manufacturing limits, the dynamics of the testing facility often couples with the test specimen one in the frequency range of interest. A further issue in this field is the standard use of a closed loop real-time vibration control scheme, which could potentially shift poles and change damping of the aforementioned coupled system. Virtual shaker testing is a novel approach to deal with these issues. It means performing a simulation which closely represents the real vibration test on the specific facility by taking into account all parameters which might impact the dynamic behavior of the specimen. In this paper, such a virtual shaker testing approach is developed. It consists of the following components: (1) Either a physical-based or an equation-based coupled electro-mechanical lumped parameter shaker model is created. The model parameters are obtained from manufacturer's specifications or by carrying out some dedicated experiments; (2) Existing real-time vibration control algorithm are ported to the virtual simulation environment; and (3) A structural model of the test object is created and after defining proper interface conditions structural modes are computed by means of the well-established Craig-Bampton CMS technique. At this stage, a virtual shaker test has been run, by coupling the three described models (shaker, control loop, structure) in a co-simulation routine. Numerical results have eventually been correlated with experimental ones in order to assess the robustness of the proposed methodology.

Ricci, Stefano↗
NASA NTRS1986

A lumped parameter mathematical model for simulation of subsonic wind tunnels

Equations for a lumped parameter mathematical model of a subsonic wind tunnel circuit are presented. The equation state variables are internal energy, density, and mass flow rate. The circuit model is structured to allow for integration and analysis of tunnel subsystem models which provide functions such as control of altitude pressure and temperature. Thus the model provides a useful tool for investigating the transient behavior of the tunnel and control requirements. The model was applied to the proposed NASA Lewis Altitude Wind Tunnel (AWT) circuit and included transfer function representations of the tunnel supply/exhaust air and refrigeration subsystems. Both steady state and frequency response data are presented for the circuit model indicating the type of results and accuracy that can be expected from the model. Transient data for closed loop control of the tunnel and its subsystems are also presented, demonstrating the model's use as a control analysis tool.

Krosel, S. M.↗
NASA NTRS1990

Distributed parameter estimation for large beam-like structures for general inputs

In this paper, maximum likelihood estimation for distributed parameter models of large flexible structures has been formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics of finite element models. The closed-form solutions for the partial differential equations with general forced inputs have been derived. The closed-form expressions of the sensitivity functions lead to highly efficient algorithms for analyzing ground or on-orbit test results. Numerical simulations with impulse and step inputs to the NASA Mini-MAST trust have been demonstrated. The estimations of modal properties involve its longitudinal elongation modes, lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.

Shen, Ji-Yao↗
DOE OSTI2023

Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference

A multiple input multiple output (MIMO) power line communication (PLC) model for industrial facilities was developed that uses the physics of a bottom-up model but can be calibrated like top-down models. The PLC model considers 4-conductor cables (three-phase conductors and a ground conductor) and has several load types, including motor loads. The model is calibrated to data using mean field variational inference with a sensitivity analysis to reduce the parameter space. The results show that the inference method can accurately identify many of the model parameters, and the model is accurate even when the network is modified.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗
DOE OSTI2023

Comparison and multi-model inference of excess risks models for radiation-related solid cancer

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose–response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing

Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to a single layer and/or small number of particles. Therefore, results from such model configurations may not be generalized to multiple layer processes. In this study, a computationally efficient multi-layer powder spreading DEM simulation model is proposed. The model is calibrated experimentally using static Angle of Repose measurements. The adhesion model parameter, cohesive energy density is related to adhesive surface energy and strain energy release rate parameters. The model results show that interaction between particle and the powder spreading rake leads to noticeable variation in packing density, surface roughness, dynamic angle of repose (AOR), particle size distribution, and particle segregation. Finally, the powder model is experimentally validated using a recoater spreading rig to measure the dynamic AOR at spreading speeds consistent with recoating speeds and layer heights used in AM processes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Search for Wγ resonances in proton-proton collisions at √s=13 TeV using hadronic decays of Lorentz-boosted W bosons

A search for W$\gamma$ resonances in the mass range between 0.7 and 6.0 TeV is presented. The W boson is reconstructed via its hadronic decays, with the final-state products forming a single large-radius jet, owing to a high Lorentz boost of the W boson. The search is based on proton-proton collision data at $\sqrt{s} = $ 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$, collected with the CMS detector at the LHC in 2016-2018. The W$\gamma$ mass spectrum is parameterized with a smoothly falling background function and examined for the presence of resonance-like signals. No significant excess above the predicted background is observed. Model-specific upper limits at 95% confidence level on the product of the cross section and branching fraction to the W$\gamma$ channel are set. Limits for narrow resonances and for resonances with an intrinsic width equal to 5% of their mass, for spin-0 and spin-1 hypotheses, range between 0.17 fb at 6.0 TeV and 55 fb at 0.7 TeV. These are the most restrictive limits to date on the existence of such resonances. In specific narrow-resonance benchmark models, heavy scalar (vector) triplet resonances with masses between 0.75 (1.15) and 1.40 (1.36) TeV are excluded for a range of model parameters. Model-independent limits on the product of the cross section, signal acceptance, and branching fraction to the W$\gamma$ channel are set for minimum W$\gamma$ mass thresholds between 1.5 and 8.0 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Uncertainties in Local Intense Precipitation Flood Modeling

In the Task 1 report for the U.S. Nuclear Regulatory Commission (NRC) funded Local Intense Precipitation (LIP) Probabilistic Flood Hazard Assessment (PFHA) Pilot Study, the Pacific Northwest National Laboratory (PNNL) reviewed hydrologic and hydraulic modeling approaches for estimation of LIP flooding and their implementation in readily available simulation software packages (Prasad and Yuan 2020). NRC’s interest is in developing guidance for performing LIP PFHA at nuclear power plant (NPP) sites. This report describes the work done under Task 2 of the study that focused on describing uncertainties associated with LIP flood modeling. Two main types of uncertainties exist in LIP flood modeling: (1) aleatory uncertainties that arise from the inherent natural variability of the hydrometeorological system and (2) epistemic uncertainties that arise from the analysts’ incomplete knowledge of the hydrometeorological and site configuration. Principal sources for aleatory variability in LIP flood simulations at NPP sites include precipitation (i.e., magnitude, duration, and temporal distribution of LIP events), initial conditions (e.g., soil moisture content, stormwater drainage discharge, surface storage), boundary conditions (e.g., upstream discharge, downstream water surface elevations), and long-term temporal trends (e.g., climate change). This report describes approaches used for estimating the aleatory variability in precipitation including precipitation-frequency analysis, numerical weather prediction, and stochastic weather generation. Data sources that can be used to estimate aleatory variability in initial and boundary conditions are also described. Approaches to include effects of long-term trends like those from climate change into estimation of aleatory variability are summarized. Sources of epistemic uncertainty in LIP flood simulations at NPP sites include process representation (e.g., multiple approaches to represent runoff generation, stormwater drainage, and hydraulic routing), site configurations (e.g., site layout, flow features, status of temporary flood protection, blockage of drains), model resolution, and long-term temporal trends (e.g., known/planned site alterations, land-use changes at and in the vicinity of the site). The report describes alternative process representations (methods and models), particularly those implemented in the LIP flood simulation software packages reviewed in Task 1 report, and lists the associated model parameters. Approaches for estimating model parameters when surface and subsurface water exchanges occur are also described.

42 ENGINEERING↗
NASA NTRS1981

A model of the human observer and decision maker

The decision process is described in terms of classical sequential decision theory by considering the hypothesis that an abnormal condition has occurred by means of a generalized likelihood ratio test. For this, a sufficient statistic is provided by the innovation sequence which is the result of the perception an information processing submodel of the human observer. On the basis of only two model parameters, the model predicts the decision speed/accuracy trade-off and various attentional characteristics. A preliminary test of the model for single variable failure detection tasks resulted in a very good fit of the experimental data. In a formal validation program, a variety of multivariable failure detection tasks was investigated and the predictive capability of the model was demonstrated.

Wewerinke, P. H.↗
NASA NTRS1982

Inversion of data from diffraction-limited multiwavelength remote sensors. II - Nonlinear dependence of observables on the geophysical parameters

Linear shift-invariant spatial filtering is applied to inversion of radiometric measurements of the earth in both polarizations at the following frequencies: 6.6, 10.7, 18, 21, and 37 GHz. For purposes of radiative transfer calculations at these frequencies, the state of the ocean-atmosphere system is described by a seven-parameter model. The parameters are near-surface wind speed, sea surface temperature, integrated water vapor mass, scale height of water vapor in an exponential distribution, integrated liquid water mass, height of the liquid water, and characteristic drop radius in a Best (1950) drop size distribution. Also described is a spatial filtering algorithm by means of which geophysical parameters are retrieved from measurements made over the ocean by the scanning multichannel microwave radiometer on the Nimbus 7 satellite. The parameters here are near-surface wind speed, sea surface temperature, rain rate, integrated atmospheric water vapor content, and integrated liquid water content (including rain).

Rosenkranz, P. W.↗
NASA NTRS1986

Descriptive Linear modeling of steady-state visual evoked response

A study is being conducted to explore use of the steady state visual-evoke electrocortical response as an indicator of cognitive task loading. Application of linear descriptive modeling to steady state Visual Evoked Response (VER) data is summarized. Two aspects of linear modeling are reviewed: (1) unwrapping the phase-shift portion of the frequency response, and (2) parsimonious characterization of task-loading effects in terms of changes in model parameters. Model-based phase unwrapping appears to be most reliable in applications, such as manual control, where theoretical models are available. Linear descriptive modeling of the VER has not yet been shown to provide consistent and readily interpretable results.

Levison, W. H.↗
NASA NTRS1991

Measuring earth orientation with the Global Positioning System

A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level earth orientation information to aid both spacecraft navigation and the study of high-frequency earth orientation-related processes.

Freedman, Adam P.↗
NASA NTRS1992

Evaluating human performance modeling for system assessment: Promise and problems

The development and evaluation of computational human performance models is examined. An intention is to develop models which can be used to interact with system prototypes and simulations to perform system assessment. Currently LR is working on a set of models emulating cognitive, psychomotor, auditory, and visual activity for multiple operator positions of a command and control simulation system. These models, developed in conjunction with BBN Systems and Technologies, function within the simulation environment and allow for both unmanned system assessment and manned (human-in-loop) assessment of system interface and team interactions. These are relatively generic models with built-in flexibility which allows modification of some model parameters. These models have great potential for improving the efficiency and effectiveness of system design, test, and evaluation. However, the extent of the practical utility of these models is unclear. Initial verification efforts comparing model performance within the simulation to actual human operators on a similar, independent simulation have been performed and current efforts are directed at comparing human and model performance within the same simulation environment.

Patterson, Robert W.↗
NASA NTRS1997

Fitting a 3-D analytic model of the coronal mass ejection to observations

The application of an analytic magnetohydrodynamic model is presented to observations of the time-dependent explusion of 3D coronal mass ejections (CMEs) out of the solar corona. This model relates the white-light appearance of the CME to its internal magnetic field, which takes the form of a closed bubble, filled with a partly anchored, twisted magnetic flux rope and embedded in an otherwise open background field. The density distribution frozen into the expanding CME expanding field is fully 3D, and can be integrated along the line of sight to reproduce observations of scattered white light. The model is able to reproduce the three conspicuous features often associated with CMEs as observed with white-light coronagraphs: a surrounding high-density region, an internal low-density cavity, and a high-density core. The model also describes the self-similar radial expansion of these structures. By varying the model parameters, the model can be fitted directly to observations of CMEs. It is shown how the model can quantitatively match the polarized brightness contrast of a dark cavity emerging through the lower corona as observed by the HAO Mauna Loa K-coronameter to within the noise level of the data.

Gibson, S. E.↗
NASA NTRS1998

Space Suit Thermal Dynamics

The present NASA space suit (the Shuttle EMU) is a self-contained environmental control system, providing life support, environmental protection, earth-like mobility, and communications. This study considers the thermal dynamics of the space suit as they relate to astronaut thermal comfort control. A detailed dynamic lumped capacitance thermal model of the present space suit is used to analyze the thermal dynamics of the suit with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The observations from this study are being utilized in two future design efforts, automatic thermal comfort control design for the present space suit and design of future space suit systems for Space Station, Lunar, and Martian missions.

Campbell, Anthony B.↗
NASA NTRS2006

Development of a Numerical Model for High-Temperature Shape Memory Alloys

A thermomechanical hysteresis model for a high-temperature shape memory alloy (HTSMA) actuator material is presented. The model is capable of predicting strain output of a tensile-loaded HTSMA when excited by arbitrary temperature-stress inputs for the purpose of actuator and controls design. Common quasi-static generalized Preisach hysteresis models available in the literature require large sets of experimental data for model identification at a particular operating point, and substantially more data for multiple operating points. The novel algorithm introduced here proposes an alternate approach to Preisach methods that is better suited for research-stage alloys, such as recently-developed HTSMAs, for which a complete database is not yet available. A detailed description of the minor loop hysteresis model is presented in this paper, as well as a methodology for determination of model parameters. The model is then qualitatively evaluated with respect to well-established Preisach properties and against a set of low-temperature cycled loading data using a modified form of the one-dimensional Brinson constitutive equation. The computationally efficient algorithm demonstrates adherence to Preisach properties and excellent agreement to the validation data set.

DeCastro, Jonathan A.↗