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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania

Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regionsprovide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantageand shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantagediffers between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within theUS context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site ofWaynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a goodrepresentation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected fromstudents, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty andstudents group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personalcharacteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commutersvalue personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to moveback and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show ahigher propensity for using shared shuttles. Furthermore, the findings from this study could be helpful for agencies in improving rural mobility andconsidering such shared mobility services for rural communities

42 ENGINEERING↗
DOE OSTI2024

Simultaneous extraction of the weak radius and the weak mixing angle from parity-violating electron scattering on 12 C

We study the impact of nuclear structure uncertainties on a measurement of the weak charge of 12 C at the future Mainz Energy Recovering Superconducting Accelerator (MESA) facility in Mainz. Information from a large variety of nuclear models, accurately calibrated to the ground-state properties of selected nuclei, suggest that a 0.3% precision measurement of the parity-violating asymmetry at forward angles will not be compromised by nuclear structure effects, thereby allowing a world-leading determination of the weak charge of 12 C . Furthermore, we show that a combination of measurements of the parity-violating asymmetry at forward and backward angles for the same electron-beam energy can be used to extract information on the nuclear weak charge distribution. We conclude that a 0.34% precision on the weak radius of 12 C may be achieved by performing a 3% precision measurement of the parity-violating asymmetry at backward angles.

Electroweak interaction↗
DOE OSTI2026

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating the Effects of Individual Neutron-Induced Defects in Bipolar Junction Transistors

Here, this study investigates neutron-induced displacement damage in Bipolar Junction Transistors (BJTs) using TCAD models informed by Deep-Level-Transient-Spectroscopy (DLTS) data. These models are calibrated and validated against experimental measurements performed at various neutron fluences. Both npn and pnp transistor configurations are studied to analyze the effects of individual traps on carrier recombination and base leakage currents. In npn transistors, deep traps (0.42 eV from the conduction band) dominate at low voltages, while shallow traps (0.17 eV from the conduction band) become prominent at higher voltages. Conversely, pnp transistors have base leakage current predominantly due to deep-level traps. The study observes a notable trend in trap density versus fluence, characterized by a linear relationship on a log-log scale. These insights into defect evolution under radiation conditions are crucial for optimizing semiconductor device reliability and performance in radiation-prone environments.

42 ENGINEERING↗
DOE OSTI2024

Toadstool Deep Learning Framework

SAND2025-11741O Toadstool is a deep learning framework and support library that provides PyTorch boiler plate training and testing loops. This enables the user to remember parts and customize a callback interface. Toadstool also provides useful callbacks and other methods for deep learning experimentation. The framework also implements publicly available temperature and calibration methods, model initialization methods, learning rate schedulers, and model evaluation methods. 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.

Heidbrink, Scott↗
DOE OSTI2026

BayesPPR

SAND2026-17002O BayesPPR performs Bayesian Projection Pursuit Regression (PPR) using MATLAB. A surrogate model for calibration applications, it enables users to efficiently analyze complex datasets and extract meaningful patterns through regression techniques. 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.

Tucker, J. Derek [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2024

Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Implosion simulations and optimum times of radiographic Images in OMEGA high-density-carbon cylinder experiments

The Los Alamos Ignition Threshold team is planning direct-drive cylinder implosion experiments (CylDRT24B) at the OMEGA laser, scheduled for Thursday 23 May 2024, to investigate the effect of granular microstructure in high density carbon (HDC) shells. Granular microstructure is believed to play a crucial role in seeding perturbations, reducing compression, and enhancing mix in the implosion of HDC shells at the National Ignition Facility (NIF). But the ICF community lacks a detailed understanding of how grains induce these effects, owing partly to the practical difficulty of numerically simulating the behavior of tiny nanometer-scale granular structures in laboratory-scale experiments. Our planned experiments are aimed at acquiring data to help constrain simulations and calibrate reduced models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Technical Report for Bayesian Optimization and Reinforcement Learning for Beam Polarization Increase in the BNL Hadron Injectors

This project developed and evaluated physics-informed Bayesian learning and machine learning (ML)-based optimization methods for improving beam polarization preservation in the BNL hadron injector chain. The work focused on uncertainty-aware digital twin modeling, Bayesian calibration of accelerator simulations using beam measurements, and data-efficient optimization strategies including Bayesian optimization and reinforcement learning. These methods were applied to injector tuning and RF control problems in realistic accelerator settings to support improved operational robustness and readiness for RHIC operations and future Electron–Ion Collider facilities. No subject inventions were disclosed under this award.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

PIXE – State of the Art, Systems, Challenges

Particle-induced X-ray emission (PIXE) is an analytical technique for elemental analysis in which a charged-particle beam (most commonly protons, but also alpha particles or heavier ions) ionizes inner-shell electrons in target atoms. When these vacancies are filled by outer-shell electrons, the atom emits characteristic X-rays (e.g., Kα, Kβ, L-series) whose energies are unique to each element. Measuring the X-ray spectrum therefore enables identification of the elements present and, with appropriate calibration and modeling, their concentration. PIXE provides rapid, simultaneous, quantitative multi-element detection with trace-level sensitivity for many mid- to high-Z elements, often with minimal sample preparation. It is widely used across materials science (thin films, alloys, corrosion), geology (mineral chemistry, provenance) and environmental monitoring (aerosols, particulates, soils); semiconductor contamination analysis (wafer surface/trace metals), cultural heritage (pigments, inks, archaeological artifacts) and forensics (gunshot residue, glass/pain), and biological/medical studies (tissue/biomaterial trace-element mapping).

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

Flight test evaluation and analysis of an optical IR PWI system

The flight test results of the optical infrared (IR) Pilot Warning Instrument (PWI) system are presented. The test program is described and the flight test data presented. The data is analyzed and used to calibrate a model that is developed to characterize the system performance. The cumulative probability of detection versus range from a given system threshold is calculated and compared with the PWI performance specification. The comparison indicates that the Optical IR PWI system tested met the specifications for a detection likelihood of 95 percent for a 1 nmi range for an appreciable fraction of the testing time.

Phillips, C. O.↗
NASA NTRS1979

The double seismic zone in downgoing slabs and the viscosity of the mesosphere

The seismic zone beneath several island arcs between about 100 and 200 km depth consists of an upper zone having down-dip compression and a lower zone having down-dip tension. Several numerical models of the Aleutian arc were computed to test the hypothesis that these double seismic zones are due to sagging of the slab under its own weight. This sagging occurs because the asthenosphere (between about 100 and 200 km) provides little support or resistance to the slab, which is supported from below by the more viscous mesosphere and from above by the lithosphere. The viscosity of the mesosphere was constrained to the interval between 0.25 x 10 to the 22nd and 0.5 x 10 to the 22nd P by noting that the slab would have mainly down-dip compression at higher viscosities and mainly down-dip tension at lower viscosities. The deviatoric stress in the slab and the fault plane between the slab and the island arc is about 200-300 bars (expressed as shear stress). The models were calibrated to the observed depth and gravity anomalies in the trench.

Sleep, N. H.↗
NASA NTRS1985

Testing an Energy Balance Model for Estimating Actual Evapotranspiration Using Remotely Sensed Data

An energy-balance model is used to estimate daily evapotranspiration for 3 days for a barley field and a wheat field near Hannover, Federal Republic of Germany. The model was calibrated using once-daily estimates of surface temperatures, which may be remotely sensed. The evaporation estimates were within the 95% error bounds of independent eddy correlation estimates for the daytime periods for all three days for both sites, but the energy-balance estimates are generally higher; it is unclear which estimate is biassed. Soil moisture in the top 2 cm of soil, which may be remotely sensed, may be used to improve these evaporation estimates under partial ground cover. Sensitivity studies indicate the amount of ground data required is not excessive.

Gurney, R. J.↗
NASA NTRS1988

Accuracy requirements and benchmark experiments for CFD validation

The role of experiment in the development of Computation Fluid Dynamics (CFD) for aerodynamic flow prediction is discussed. The CFD verification is a concept that depends on closely coordinated planning between computational and experimental disciplines. Because code applications are becoming more complex and their potential for design more feasible, it no longer suffices to use experimental data from surface or integral measurements alone to provide the required verification. Flow physics and modeling, flow field, and boundary condition measurements are emerging as critical data. Four types of experiments are introduced and examples given that meet the challenge of validation: flow physics experiments; flow modeling experiments; calibration experiments; and verification experiments. Measurement and accuracy requirements for each of these differ and are discussed. A comprehensive program of validation is described, some examples given, and it is concluded that the future prospects are encouraging.

Marvin, Joseph G.↗
NASA NTRS1987

Validating regional differences in modelled satellite microwave signatures

A three-part microwave T(B) brightness temperature model was tested for applicability in regions of differing climatic and vegetation regime. Model parameters were limited to vegetation in the form of the normalized vegetation index (NDVI) and climatically modeled soil moisture. The T(B) model was calibrated for two climatically contrasting areas and subsequently validated on different test sites of similar climatic character. Vegetative characteristics in the form of the mean NDVI was used to partition and lump data from different test sites. Good agreement was realized between estimated T(B) and Nimbus-7 SMMR T(B) at the 6.6 GHz horizontal channel.

Owe, Manfred↗