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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

K_Road (KRoad)

KRoad is a 2-dimensional, lightweight, vehicle driver simulator that uses 3-dimensional vehicle driving model considerations, i.e. state-of-the-art friction models, and enables the driver to make control decisions with less computation time and programmer effort required than is with full-fidelity 3d simulators. KRoad is fully compatible with OpenAI gym, and contains a factored gym framework for composing gyms from various components (process, reward function, observation function, termination conditions, etc.). KRoad is additionally compatible with the RLlib distributed reinforcement learning environment, running under the Ray distributed python framework.

Tripp, CharlesEdison [National Renewable Energy La↗
NASA NTRS2013

Separation-Compliant, Optimal Routing and Control of Scheduled Arrivals in a Terminal Airspace

We address the problem of navigating a set (fleet) of aircraft in an aerial route network so as to bring each aircraft to its destination at a specified time and with minimal distance separation assured between all aircraft at all times. The speed range, initial position, required destination, and required time of arrival at destination for each aircraft are assumed provided. Each aircraft's movement is governed by a controlled differential equation (state equation). The problem consists in choosing for each aircraft a path in the route network and a control strategy so as to meet the constraints and reach the destination at the required time. The main contribution of the paper is a model that allows to recast this problem as a decoupled collection of problems in classical optimal control and is easily generalized to the case when inertia cannot be neglected. Some qualitative insight into solution behavior is obtained using the Pontryagin Maximum Principle. Sample numerical solutions are computed using a numerical optimal control solver. The proposed model is first step toward increasing the fidelity of continuous time control models of air traffic in a terminal airspace. The Pontryagin Maximum Principle implies the polygonal shape of those portions of the state trajectories away from those states in which one or more aircraft pair are at minimal separation. The model also confirms the intuition that, the narrower the allowed speed ranges of the aircraft, the smaller the space of optimal solutions, and that an instance of the optimal control problem may not have a solution at all (i.e., no control strategy that meets the separation requirement and other constraints).

transportation network↗
DOE OSTI2020

Coherent control and high-fidelity readout of chromium ions in commercial silicon carbide

Abstract Transition metal ions provide a rich set of optically active defect spins in wide bandgap semiconductors. Chromium (Cr 4+ ) in silicon-carbide (SiC) produces a spin-1 ground state with a narrow, spectrally isolated, spin-selective, near-telecom optical interface. However, previous studies were hindered by material quality resulting in limited coherent control. In this work, we implant Cr into commercial 4H-SiC and show optimal defect activation after annealing above 1600 °C. We measure an ensemble optical hole linewidth of 31 MHz, an order of magnitude improvement compared to as-grown samples. An in-depth exploration of optical and spin dynamics reveals efficient spin polarization, coherent control, and readout with high fidelity (79%). We report T 1 times greater than 1 s at cryogenic temperatures (15 K) with a T 2 * = 317 ns and a T 2 = 81 μs, where spin dephasing times are currently limited by spin–spin interactions within the defect ensemble. Our results demonstrate the potential of Cr 4+ in SiC as an extrinsic, optically active spin qubit.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Alumina Priming-Mediated Enhanced Binding of Diethylzinc with Carbonyl Groups in Poly(Methyl Methacrylate) during Vapor-Phase Infiltration

Vapor-phase infiltration (VPI) of inorganic materials in polymers is increasingly becoming popular for synthesizing various functional hybrid materials. While AlO x infiltration using trimethylaluminum (TMA) has been extensively studied, the mechanism of diethylzinc (DEZ)-based ZnO x infiltration, especially one that is initiated by AlO x priming, has not received much attention because highly reactive hydroxyl groups generated by AlO x -priming are expected to dominate the initial binding of DEZ, thus enabling the overall ZnO x VPI. Here, we interrogate the ZnO x infiltration mechanism in AlO x -primed poly(methyl methacrylate) (PMMA) in comparison to the control AlO x -only infiltration by utilizing a suite of complementary characterizations, including quartz crystal microbalance mass gain measurement, transmission electron microscopy, infrared reflection–absorption spectroscopy (IRRAS), and synchrotron X-ray absorption spectroscopy (XAS). The multivalent TMA precursor and associated hyperbranched AlO x network can quickly saturate the AlO x infiltration by clogging the polymer-free volume near the top. On the contrary, the ZnO x infiltration using divalent DEZ precursor, once activated via AlO x -priming, can lead to accelerated ZnOx infiltration. With the help of IRRAS, XAS, and density functional theory (DFT) simulations, we uncover that the AlO x -priming enhances the reactivity of neighboring carbonyl groups toward DEZ and opens up simultaneous reaction pathways, leading to accelerated high-fidelity infiltration of ZnO x .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate Dehydrogenation Enthalpies Dataset for Liquid Organic Hydrogen Carriers

This contribution presents a comprehensive extension of the QM9 dataset (originally at 133 K molecules) with the calculation of G4MP2 enthalpies for 9,841 molecules, featuring up to nine heavy atoms. We present QM9-LOHC, a (de)hydrogenation dataset of 10,373 reactions, including a minimum of 5.5% weight hydrogen storage capacity in line with the Department of Energy standards for Liquid Organic Hydrogen Carriers (LOHC). By utilizing the accurate quantum chemical method G4MP2 we expand the QM9 database and explore new avenues for the exploration of hydrogen storage technologies (electrochemical LOHCs, alkali metal-LOHCs, and mixtures of LOHCs). The QM9-LOHC dataset, with its focus on reactions that vary only by hydrogen saturation levels, provides a needed data resource for advancing the design and optimization of both conventional and innovative LOHC systems, and high-fidelity data for molecular discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

IRMA

IRMA (In)elastic Representation of Materials As S(α,β) evaluations IRMA turns one phonon model into three outputs that usually require three separate tool chains: an evaluated nuclear-data file, predicted neutron-scattering spectra, and scattering kernels for Monte Carlo transport. The three outputs draw on a single, consistent description of the material, so the evaluation, the spectroscopy that can validate it, and the transport that uses it always agree about the physics. Nuclear data. IRMA writes ENDF-6 File 7 thermal scattering evaluations on automatically constructed (α, β) grids. This part reimplements and generalizes NJOY's LEAPR: the classic kernels reproduce freshly generated NJOY2016 tapes digit for digit and published reference tapes to about 1e-4, and the generalized paths add the exact coherent one-phonon term, anisotropic Debye-Waller tensors, coherent elastic for arbitrary crystals, and a per-species partition for polyatomic materials. The tapes feed NJOY, AMPX, FUDGE, and every transport code downstream of them. Neutron spectroscopy. The irma.spectra forward model projects the same physics onto an instrument's kinematics and resolution: INS spectra for VISION and generic indirect geometries, and 2-D S(Q,E) powder maps for direct-geometry spectrometers, from a phonopy model or straight from a phonon DOS. It can be used to predict a proposed measurement before beam time; in analysis, it supplies the calculated single-scattering counterpart of a measured spectrum, from the same material description the evaluation was built from. Monte Carlo transport. The irma.ncrystal exporter writes per-temperature scattering kernels for the companion NCrystal plugin, so McStas, OpenMC, and other NCrystal-aware codes sample the same physics. The exported kernels carry the per-site anisotropic Debye-Waller tensors, keeping directional coherent-elastic physics that NCrystal's standard scalar treatment does not represent. With the same physics inside a transport code, an entire beamline becomes a virtual experiment: IRMA's end-to-end validation ran a custom McStas implementation of the ARCS spectrometer, assembled from the existing McVine and McStas models, against measured data. From a bare crystal structure. The irma mlip front end builds the phonon model itself: a structure file and a choice of potential are enough. Nine pretrained machine-learned interatomic potentials are supported, on a laptop CPU, with no first-principles calculation; an approximate phonon model for a new material costs minutes, not a DFT campaign, and the build emits prefilled inputs for all three outputs. The result is a good starting point rather than a finished evaluation: survey-quality physics with every parameter exposed for review. A converged atomistic calculation enters the same way, as a phonopy model, when higher fidelity is needed.

Ramic, Kemal [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2026

Adaptive Sampling Trust Region Method for Bi-fidelity Simulation Optimization [SWR-25-166]

Adaptive Sampling Trust Region Method for Bi-fidelity Simulation Optimization aims to demonstrate the effect of adaptive sampling-based bi-fidelity stochastic trust region method (ASTRO-BFDF). ASTRO-BFDF, derived from a derivative-free adaptive sampling trust-region optimization (ASTRO-DF) (Shashaani et al. 2018, Ha and Shashaani 2023), intended to efficiently solve the bi-fidelity simulation optimization.

Mueller, Juliane [National Laboratory of the Rocki↗
DOE OSTI2022

Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks (ANNs) for forecasting of wind gust occurrence and magnitude. Geophysical predictors from the ERA5 reanalysis are used in conjunction with an autoregressive term in regression and ANN models with different predictors, and varying model complexity. Models are derived and assessed for the warm (April–September) and cold (October–March) seasons for three high passenger volume airports in the United States. Model uncertainty is assessed by deriving models for 1000 different randomly selected training (70%) and testing (30%) subsets. Gust prediction fidelity in independent test samples is critically dependent on inclusion of an autoregressive term. Gust occurrence probabilities derived using five-layer ANNs exhibit consistently higher fidelity than those from regression models and shallower ANNs. Inclusion of the autoregressive term and increasing the number of hidden layers in ANNs from 1 to 5 also improve the model performance for gust magnitudes (lower RMSE, increased correlation, and model standard deviations that more closely approximate observed values). Deeper ANNs (e.g., 20 hidden layers) exhibit higher skill in forecasting strong (17–25.7 m s −1 ) and damaging (≥25.7 m s −1 ) wind gusts. However, such deep networks exhibit evidence of overfitting and still substantially underestimate (by 50%) the frequency of strong and damaging wind gusts at the three airports considered herein. Significance Statement Improved short-term forecasting of wind gusts will enhance aviation safety and logistics and may offer other societal benefits. Here we present a rigorous investigation of the relative skill of models of wind gust occurrence and magnitude that employ different statistical methods. It is shown that artificial neural networks (ANNs) offer considerable skill enhancement over regression methods, particularly for strong and damaging wind gusts. For wind gust magnitudes in particular, application of deeper learning networks (e.g., five or more hidden layers) offers tangible improvements in forecast accuracy. However, deeper networks are vulnerable to overfitting and exhibit substantial variability with the specific training and testing data subset used. Also, even deep ANNs reproduce only half of strong and damaging wind gusts. These results indicate the need for future work to elucidate the dynamical mechanisms of intense wind gusts and advance solutions to their prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Frequency-bin photonic quantum information

Discrete frequency modes, or bins, present a blend of opportunities and challenges for photonic quantum information processing. Frequency-bin-encoded photons are readily generated by integrated quantum light sources, naturally high-dimensional, stable in optical fiber, and massively parallelizable in a single spatial mode. Yet quantum operations on frequency-bin states require coherent and controllable multifrequency interference, making them significantly more challenging to manipulate than more traditional spatial degrees of freedom. In this mini-review, we describe recent developments that have transformed these challenges and propelled frequency bins forward. Focusing on sources, manipulation schemes, and detection approaches, we introduce the basics of frequency-bin encoding, summarize the state of the art, and speculate on the field’s next phases. Given the combined progress in integrated photonics, high-fidelity quantum gates, and proof-of-principle demonstrations, frequency-bin quantum information is poised to emerge from the lab and leave its mark on practical quantum information processing—particularly in networking where frequency bins offer unique tools for multiplexing, interconnects, and high-dimensional communications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Chromosome duplication causes premature aging via defects in ribosome quality control

Down syndrome, caused by an extra copy of Chromosome 21, causes lifelong problems. One of the most common phenotypes among people with Down syndrome is premature aging, including early tissue decline, neurodegeneration, and shortened life span. Yet the reasons for premature systemic aging are a mystery and difficult to study in humans. Here we show that chromosome amplification in wild yeast also produces premature aging and shortens life span. Chromosome duplication disrupts nutrient-induced cell-cycle arrest, entry into quiescence, and cellular health during chronological aging, across genetic background and independent of which chromosome is amplified. Using a genomic screen, we discovered that these defects are due in part to aneuploidy-induced dysfunction in Ribosome Quality Control (RQC). We show that aneuploids entering quiescence display aberrant ribosome profiles, accumulate RQC intermediates, and harbor an increased load of protein aggregates compared to euploid cells. Although they maintain proteasome activity, aneuploids also show signs of ubiquitin dysregulation and sequestration into foci. Remarkably, inducing ribosome stalling in euploids produces similar aging phenotypes, while up-regulating limiting RQC subunits or poly-ubiquitin alleviates many of the aneuploid defects. We propose that the increased translational load caused by having too many mRNAs accelerates a decline in translational fidelity, contributing to premature aging.

Aneuploidy↗
DOE OSTI2025

High-Fidelity, Large-Scale, Realistic Dataset Development

The final report summarizes the work performed for supporting the ARPA-E Grid Optimization Competition (Challenge 2 and Challenge 3) within the stated period. Challenge 2 For the challenge period, the main responsibility of the team is to investigate, gen- erate, and deliver parts of the data sets for the competition, based on the competition model for Challenge 2, existing data sets from Challenge 1, and data source supplied by other data set teams. Challenge 3 For the challenge period, the main responsibility of the team is to propose, create, deliver, and maintain the data format during the competition period. The data format will specify how the benchmark data will be represented and communicated to competitors. It will also specify how competitors should report back the solutions. The data format will be closely aligned with the problem formulation (maintained by the formulation team) and the solution validation process (maintained by the validation team). Our team is also responsible in investigating, generating, and delivering parts of the data sets for the competition. The data sets will be created based on the competition model for Challenge 3, existing data sets from Challenge 1 and Challenge 2, and data source supplied by other data set teams.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Advancing SiC clad fuel performance model: bridging micro- and macro-scale models and experimental validation

This report presents a workflow for advancing fuel performance modeling of SiC composite cladding for light-water reactors by linking microscale, experimental data-informed finite element analysis with rod-scale fuel performance codes such as BISON. The workflow uses X-ray computed tomography (XCT) to capture the actual geometry and processing-induced defects of as-fabricated SiC composite tube specimens, particularly porosity and wall-thickness variations, and converts the segmented XCT volumes into image-based finite element meshes for high fidelity structural analysis.

Koyanagi, Takaaki [Oak Ridge National Laboratory (↗
NASA NTRS1998

Design and Operational Characteristics of the Shuttle Coherent Wind Lidar

NOAA has identified the measurement of atmospheric wind velocities as one of the key unmet data sets for its next generation of sensing platforms. The merits of coherent lidars for the measurement of atmospheric winds from space platforms have been widely recognized; however, it is only recently that several key technologies have advanced to a point where a compact, high fidelity system could be created. Advances have been made in the areas of the diode-pumped, eye-safe, solid state lasers and room temperature, wide bandwidth, semiconductor detectors operating in the near-infrared region. These new lasers can be integrated into efficient and compact optical systems creating new possibilities for the development of low-cost, reliable, and compact coherent lidar systems for wind measurements. Over the past five years, the University of Alabama in Huntsville (UAH) has been working toward further advancing the solid state coherent lidar technology for the measurement of atmospheric winds from space. As part of this effort, UAH had established the design characteristics and defined the expected performance for three different proposed space-based instruments: a technology demonstrator, an operational prototype, and a 7-year lifetime operational instrument. SPARCLE is an ambitious project that is intended to evaluate the suitability of coherent lidar for wind measurements, demonstrate the maturity of the technology for space application, and provide a useable data set for model development and validation. This paper describes the SPARCLE instrument's major physical and environmental design constraints, optical and mechanical designs, and its operational characteristics.

Amzajerdian, Farzin↗
NASA NTRS1999

Helicopter Flight Simulation Motion Platform Requirements

To determine motion fidelity requirements, a series of piloted simulations was performed. Several key results were found. First, lateral and vertical translational platform cues had significant effects on fidelity. Their presence improved performance and reduced pilot workload. Second, yaw and roll rotational platform cues were not as important as the translational platform cues. In particular, the yaw rotational motion platform cue did not appear at all useful in improving performance or reducing workload. Third, when the lateral translational platform cue was combined with visual yaw rotational cues, pilots believed the platform was rotating when it was not. Thus, simulator systems can be made more efficient by proper combination of platform and visual cues. Fourth, motion fidelity specifications were revised that now provide simulator users with a better prediction of motion fidelity based upon the frequency responses of their motion control laws. Fifth, vertical platform motion affected pilot estimates of steady-state altitude during altitude repositioning. Finally, the combined results led to a general method for configuring helicopter motion systems and for developing simulator tasks that more likely represent actual flight. The overall results can serve as a guide to future simulator designers and to today's operators.

Schroeder, Jeffery Allyn↗
NASA NTRS2015

Progress in Open Rotor Research: A U.S. Perspective

In response to the 1970s oil crisis, NASA created the Advanced Turboprop Project (ATP) to mature technologies for high-speed propellers to enable large reductions in fuel burn relative to turbofan engines of that era. Both single rotation and contra-rotation concepts were designed and tested in ground based facilities as well as flight. Some novel concepts configurations that were not well publicized at the time, were proposed as part of the effort. The high-speed propeller concepts did provide fuel burn savings, albeit with some acoustics and structural challenges to overcome. When fuel prices fell, the business case for radical new engine configurations collapsed and the research emphasis returned to high bypass ducted configurations. With rising oil prices and increased environmental concerns there is renewed interest in high-speed propeller based engine architectures. Contemporary analysis tools for aerodynamics and aeroacoustics have enabled a new era of blade designs that have both high efficiency and acceptable noise characteristics. A recent series of tests in the U.S. have characterized the aerodynamic performance and noise from these modern contra-rotating propeller designs. Additionally the installation and noise shielding aspects for conventional airframes and blended wing bodies have been studied. Historical estimates of propfan performance have relied on legacy propeller performance and acoustics data. Current system studies make use of the modern propeller data with higher fidelity installation effects data to estimate the performance of a contemporary aircraft system with favorable results. This paper presents the current state of high-speed propeller open rotor research within the U.S. from an overall viewpoint of the various efforts ongoing. The current projections for the technology are presented.

Aerodynamics↗
NASA NTRS2018

Comparison of Iced Aerodynamic Measurements on a Swept Wing from Two Wind Tunnels

Artificial ice shapes of various geometric fidelity were tested on a wing model based on the Common Research Model. Low Reynolds number tests were conducted at Wichita State University's Beech Memorial Wind Tunnel, and high Reynolds number tests were conducted at ONERA's F1 wind tunnel. The aerodynamic performance data from the two facilities were compared at matched or similar Reynolds and Mach number to ensure that the results and trends observed at low Reynolds number could be applied and continued to high Reynolds number. For both clean and iced configurations, the data from Wichita State University and F1 agreed well at matched or similar Reynolds and Mach numbers. The lift and pitching moment curves agreed very well for most configurations. There appeared to be 0.2-0.3deg offset in the angle of attack between the Wichita State University and F1 data, possibly due to different flow angularities in the test sections of the two facilities. There was also an offset in the drag values between the two facilities from an unknown cause. Overall, the data compared very well between the low Reynolds number test at Wichita State University tunnel and the high Reynolds number test at F1. This indicated that data from the low Reynolds number tests could be used to understand iced-swept-wing aerodynamics at high Reynolds number.

Federal Aviation Administration↗
NASA NTRS2019

Additional Comparison of Iced Aerodynamic Measurements on a Swept Wing From Two Wind Tunnels

Artificial ice shapes of various geometric fidelity were tested on a wing model based on the Common Research Model. Low Reynolds number test were conducted at Wichita State University's Walter H. Beech Memorial Wind utilizing an 8.9% scale model, and high Reynolds number tests were conducted at ONERA's F1 wind tunnel utilizing a 13.3% scale model. Several identical geometrically-scaled ice shapes were tested at both facilities, and the results were compared at overlapping Reynolds and Mach numbers. This was to ensure that the results and trends observed at low Reynolds number could be applied and continued to high, near-flight Reynolds number. The data from Wichita State University and ONERA F1 agreed well at matched Reynolds and Mach numbers. The lift and pitching moment curves agreed very well for most configurations. This confirmed results from previous tests with other ice shapes that indicated the data from the low Reynolds number tests could be used to understand ice-swept-wing aerodynamics at high Reynolds number. This allows ice aerodynamics testing to be performed at low Reynolds number facilities with much lower operating costs and generate results that are applicable to flight Reynolds number.

Scale models↗