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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Thermal analytic model of 30 cm engineering model mercury ion thruster

A lumped parameter thermal nodal network was developed for a 30 cm Engineering Model Mercury Ion Thruster. The network consists of approximately 100 nodes coded in SINDA format for use on the Univac 1106/1108 computer. This model takes into account internal dissipation, radiation, and conduction as well as environmental heating. A series of tests were performed to simulate a wide range of thermal environments on an operating 30 cm thruster, instrumented to measure the temperature distribution within the thruster. The results of these tests were used to calibrate the analytical model. The analytical model along with comparisons between analytical and experimental results for the various operating conditions are presented.

Oglebay, J. C.↗
NASA NTRS1992

LDEF: Dosimetric measurement results (AO 138-7 experiment)

One of the objectives of the AO 138-7 experiment on board the LDEF was a total dose measurement with Thermo Luminescent Detectors (TLD 100). Two identical cases, both including 5 TLDs inside various aluminum shields, are exposed to the space environment in order to obtain the absorbed dose profile induced. Radiation fluence received during the total mission length was computed, taking into account the trapped particles (solar maximum and solar minimum periods) and the cosmic rays; due to the magnetospheric shielding, the solar proton fluences are negligible on the LDEF orbit. The total dose induced by these radiations inside a semi-infinite plane shield of Al are computed with radiation transport codes. TLD reading are performed after flight; due to the mission duration increase, a post-flight calibration was necessary in order to cover the range of the flight induced dose. The results obtained, similar (+ or - 30 pct.) in both cases, are compared with the dose profile computation. In practice, these LDEF results, with less than a factor 1.4 between measurements and forecasts, reinforce the validity of the computation methods and models used for the long term evaluation of space radiation intensity on low inclination Earth orbits.

Bourrieau, J.↗
NASA NTRS1999

Unstructed Navier-Stokes Analysis of Wind-Tunnel Aeroelastic Effects on TCA Model 2

The aim of this work is to demonstrate a simple technique which accounts for aeroelastic deformations experienced by HSR wind-tunnel models within CFD computations. With improved correlations, CFD can become a more effective tool for augmenting the post-test understanding of experimental data. The present technique involves the loose coupling of a low-level structural representation within the ELAPS code, to an unstructured Navier-Stokes flow solver, USM3Dns. The ELAPS model is initially calibrated against bending characteristics of the wind-tunnel model. The strength of this method is that, with a single point calibration of a simple structural representation, the static aeroelastic effects can be accounted for in CFD calculations across a range of test conditions. No prior knowledge of the model deformation during the wind-on test is required. This approach has been successfully applied to the high aspect-ratio planforms of subsonic transports. The current challenge is to adapt the procedure to low aspect-ratio planforms typical of HSR configurations.

Frink, Neal T.↗
DOE OSTI2024

A mechanistic interpretation of Nelson curves for PVP failures under high temperature hydrogen attack

As an empirically established design criterion, Nelson curves that relate the service temperature and the allowable hydrogen partial pressure have been developed and utilized for more than sixty years in pressure vessels and piping (PVP) safety design. Despite a relatively clear thermodynamic understanding of the high-temperature-hydrogen-attack (HTHA) problem, the detailed fracture process on the microstructural length scales, however, remains elusive, and a quantitative assessment of the PVP lifetime under HTHA from the available creep fracture dataset is still not possible. This work develops a microstructure-informed and micromechanics-based model by incorporating a synergy between hydrogen transport and intergranular-cavity-based fracture process. Based on the available creep lifetime data of C-0.5Mo steels, we are able to calibrate material constitutive parameters, and then conduct nonlinear finite element simulations that reveal a real-time stress-induced hydrogen diffusional transport along grain boundaries, coupled with a microstructure-explicit failure process, from which Nelson curves can be computed. Such failure analyses allow us to delineate two distinct regimes on the Nelson curves, i.e., dislocation-creep-controlled or grain boundary diffusion-assisted cavity growth. More importantly, we found that a small change of the pipe thickness and applied stresses can significantly shift these lifetime curves. However, these two parameters are usually not provided in Nelson curves, thus limiting their usage in material selection and safety design. In conclusion, this discrepancy can clearly be mitigated by extensive parametric studies from our micromechanical modeling/simulation framework.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗
DOE OSTI2022

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear voltage dependent partial polarization switching of a ferroelectric field effect transistor to mimic plasticity characteristics of biological synapses. Here, we provide experimental measurements of the synaptic characteristics for a 28nm high-k metal gate technology based device and develop an experimentally calibrated device model for large-scale system performance prediction. Decoupled read-write paths, ultra-low programming energies and the possibility of arranging such devices in a cross-point architecture demonstrate the synaptic efficacy of the device. Our hardware-algorithm co-design analysis reveals that the intrinsic plasticity of the ferroelectric devices has potential to enable unsupervised local learning in edge devices with limited training data

42 ENGINEERING↗
DOE OSTI2024

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Computationally efficient subglacial drainage modelling using Gaussian process emulators: GlaDS-GP v1.0

Subglacial drainage models represent water flow at the ice–bed interface through coupled distributed and channelized systems to determine water pressure, discharge, and drainage system geometry. While they are used to understand processes such as the relationship between surface melt and ice flow, the number of uncertain model parameters and the computational cost of running models makes it difficult to adequately explore the high-dimensional parameter space and evaluate uncertainty in model predictions. Here, we develop Gaussian process (GP) emulators that make fast predictions with associated uncertainty of subglacial drainage model outputs. Using a truncated principal component (PC) basis representation, we construct a GP emulator for diurnally averaged subglacial water pressure. We also explore emulation of scalar variables describing drainage efficiency and configuration. We train the emulators using ensembles of up to 512 simulations varying eight parameters of the Glacier Drainage System (GlaDS) model on a synthetic domain intended to represent an ice-sheet margin. The emulators make predictions ∼ 1000 times faster than GlaDS simulations, with errors <3 % for the water pressure field and ∼ 5 %–9 % for drainage efficiency and configuration. We apply the emulators to explore the eight-dimensional parameter space by computing variance-based parameter sensitivity indices, finding that three parameters (ice flow coefficient, bed bump aspect ratio, and the subglacial cavity system conductivity) explain 90 % of the variance in modelled water pressure in response to parameter changes. The GP emulator approach described here is well suited to integrating observational data with models to make calibrated, credible predictions of subglacial drainage.

58 GEOSCIENCES↗
NASA NTRS1987

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Halyo, Nesim↗
NASA NTRS1996

A historical perspective of the YF-12A thermal loads and structures program

Around 1970, the Y-F-12A loads and structures efforts focused on numerous technological issues that needed defining with regard to aircraft that incorporate hot structures in the design. Laboratory structural heating test technology with infrared systems was largely created during this program. The program demonstrated the ability to duplicate the complex flight temperatures of an advanced supersonic airplane in a ground-based laboratory. The ability to heat and load an advanced operational aircraft in a laboratory at high temperatures and return it to flight status without adverse effects was demonstrated. The technology associated with measuring loads with strain gages on a hot structure was demonstrated with a thermal calibration concept. The results demonstrated that the thermal stresses were significant although the airplane was designed to reduce thermal stresses. Considerable modeling detail was required to predict the heat transfer and the corresponding structural characteristics. The overall YF-12A research effort was particularly productive, and a great deal of flight, laboratory, test and computational data were produced and cross-correlated.

Jenkins, Jerald M.↗
NASA NTRS1999

Scientific Programming Using Java: A Remote Sensing Example

This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

Prados, Don↗
DOE OSTI2023

Uncertainty quantification of bank vegetation impacts on the flood flow field in the American River, California, using large‐eddy simulations

Bank vegetation plays a key role in both hydrodynamics and morphodynamics of natural rivers; however, these effects are often unaccounted for in the computational flow dynamics of natural waterways. Recent studies using the large‐eddy simulation (LES), however, have attempted to gain insights into the impacts of bank vegetation on the mean flow field of the natural rivers using a vegetation model, which applies a sink term to the momentum equations of motion. This approach accounts for the effects of the vegetation and provides a practical approach to account for the complex patches of bank vegetation in large‐scale rivers. To implement the vegetation model, a drag coefficient reflecting the overall resistance of vegetal structures to the flow is needed, but due to the lack of calibrated data and range of size, density and type of vegetation, this parameter can be a significant source of uncertainty in the model results. Here, in this study, we use uncertainty quantification (UQ) to investigate the hydrodynamics and bed shear results when a bank vegetation is incorporated in an LES model. To this end, we used the polynomial chaos expansion and Monte Carlo sampling techniques to determine the uncertainties associated with the drag coefficient in the vegetation model and from uncertainties in the bed roughness and inflow discharge. The UQ analysis provided spatially varying confidence levels for the spanwise and vertical distribution of velocity magnitude and for the bed shear stress distributions. In addition, Sobol indices were computed to indicate the relative influence that each parameter had on the overall uncertainty. In general, it was found that uncertainty in flow discharge was the dominant source of uncertainty; however, the drag coefficient in the vegetation model and the bed roughness parameter also made significant contribution to the uncertainty near the banks and bed, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Viewgraphs for w20_seismicsources [Slides]

Hybrid Optimization Software Suite (HOSS) is based on finite-discrete element modeling to capture the complex physics of explosions. Calibration of near-source modeling for underground explosions in geophysical models is presented, showing the effects of the amplitude of radial and vertical seismic components.

36 MATERIALS SCIENCE↗
NASA NTRS1993

LDEF: Dosimetric measurement results (AO 138-7 experiment)

One of the objectives of the AO 138-7 experiment on board the Long Duration Exposure Facility (LDEF) was a total dose measurement with Thermo Luminescent Detectors (TLD 100). Two identical packages, both of them including five TLD's inside various aluminum shields, are exposed to the space environment in order to obtain the absorbed dose profile. Radiation fluence received during the total mission length was computed, taking into account the trapped particles (AE8 and AP8 models during solar maximum and minimum periods) and the cosmic rays; due to the magnetospheric shielding the solar proton fluences are negligible on the LDEF orbit. The total dose induced by these radiations inside a semi infinite plane shield of aluminum are computed with the radiation transport codes available at DERTS. The dose profile obtained is in good agreement with the evaluation by E.V. Benton. TLD readings are performed after flight; due to the mission duration increase a post flight calibration was necessary in order to cover the range of the in flight induced dose. The results obtained, similar (plus or minus 30 percent) for both packages, are compared with the dose profile computation. For thick shields it seems that the measurements exceed the forecast (about 40 percent). That can be due to a cosmic ray and trapped proton contributions coming from the backside (assumed as perfectly shielded by the LDEF structure in the computation), or to an underestimate of the proton or cosmic ray fluences. A fine structural shielding analysis should be necessary in order to determine the origin of this slight discrepancy between forecast and in flight measurements. For the less shielded dosimeters, mainly exposed to the trapped electron flux, a slight overestimation of the dose (less than 40 percent) appears. Due to the dispersion of the TLD's response, this cannot be confirmed. In practice these results obtained on board LDEF, with less than a factor 1.4 between measurements and forecast, reinforce the validity of the computation methods and models used for the long term evaluation of the radiation levels (flux and dose) encountered in space on low inclination and altitude Earth orbits.

Bourrieau, J.↗
DOE OSTI2020

Predicting the effects of thermally-induced density gradients on the hydrodynamic behavior of PBX 9502

High explosives are often exposed to thermal and mechanical stimuli within normal and abnormal environments. These stimuli can introduce density gradients in the explosive charge but the effect of such gradients is not well-understood. The goal of this work is to develop a comprehensive methodology to model the evolution of density gradients under various thermal conditions and then to predict shock initiation and detonation behavior of the gradated sample. PBX 9502 was chosen for these scoping studies because it has a large coefficient of thermal expansion and because the available shock initiation data indicates that initial temperature strongly affects the shock-to-detonation transition (SDT). The multiphysics code COMSOL was first used to model induced density gradients in a slab of PBX 9502 with asymmetric heating. Then, the gradated sample was constructed in the Pagosa hydrocode to simulate steel flyer impact scenarios, with SDT and detonation propagation following a calibrated Scaled Uniform Reactive Front (SURF) burn model. Furthermore, the gradated material exhibited very different initiation and corner turning behavior compared to homogeneous materials, and the orientation of the gradation was also found to have some effect. The methodology used here can estimate thermomechanical response of the material for non-uniform thermal environments and compute the resulting detonation properties of the PBX.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Tissue scale agent-based simulation of premalignant progressions in Barrett’s esophagus

Barrett’s esophagus (BE) is a benign condition of the distal esophagus that initiates a multistage pathway to esophageal adenocarcinoma (EAC). Short of frequent intrusive (and costly) surveillance, effective screening for neoplasia in BE populations is yet to be established since progressors are rare and virtually undetectable without routine biopsies, which often sample only a small portion of the BE tissue. As a result, reliable estimation of the true prevalence of dysplasia in a BE population and evidence-based optimization of screening for at-risk individuals is challenging. Data-driven microsimulations, i.e., model-generated instances of disease history in a predefined virtual population, have found utility in the EAC screening literature as low-overhead alternatives to real-world hypothesis testing of optimal interventions for dysplasia. Despite the successes, computational limitations, paucity of knowledge and data on Barrett’s dysplasia, and the complexities of disease progression as a multiscale multiphysics process have hindered the treatment of disease progression in BE as a spatial process. Agent-based modeling of nucleation and proliferation processes in dysplasia warrants exploration in this context as an approximation that operates at a trade-off between computational tractability and precise representation of the composition and physics of the substrate (tissue). In this study, we describe spatially resolved simulations of premalignant progression toward EAC in a coarse-grained model of Barrett’s tissue that resolves the metaplastic tissue at a length scale of 0.42 mm (~3300 crypts/mm 2 ). Finally, the model is calibrated to reproduce historical high-grade dysplasia prevalence when model-generated patients are screened using the Seattle protocol.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Convective heating measurement by means of an infrared camera

The development of rapid and accurate wind tunnel techniques to measure convective heating distributions in complex reentry configurations is discussed. Major emphasis was put on the infrared camera technique. Its essence is the measurement of infrared emission from the surface of a wind tunnel model as a function of time. Prior calibration of the infrared camera relates the emission to the surface temperature of the model. The time history of the surface temperature can then be related to the heating rate by standard techniques. The output of the camera is an electrical signal that is tape-recorded in analog form, then digitized and processed by computer, so that automated and relatively rapid data reduction can be accomplished. In addition, the camera produces real-time visual displays of the infrared emission as pictures on an oscilloscope screen. These pictures give immediate indications of hot and cool spots on the model.

Compton, D. L.↗