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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification

SInkhorn Dynamic Domain Adaptation (SIDDA) supplements the experiments presented in 2501.14048, SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks. SIDDA introduces a semi-supervised, automatic domain adaptation method that leverages Sinkhorn divergences to dynamically adjust the regularization in the optimal transport plan and the weighting between classification and domain adaptation loss terms during training.

Pandya, Sneh [Fermi National Accelerator Laborator↗
DOE OSTI2020

An Adaptive Framework for Extreme Deformation and Failure in Solids

Recent developments at Sandia in meshfree methods have delivered improved robustness in solid mechanics problems that prove difficult for traditional Lagrangian, mesh-based finite elements. Nevertheless, there remains a limitation in accurately predicting very large material deformations. It seems robust meshfree discretizations and integration schemes are necessary, but not sufficient, to close this capability gap. This state of affairs directly impacts current and future LEPs, whose simulation needs are not well met for extremely large deformation problems. We propose to use a new numerical framework, the Optimal Transportation Meshfree (OTM) method enhanced by meshfree adaptivity, as we believe that a combination of both will provide a novel way to close this capability gap.

36 MATERIALS SCIENCE↗
DOE OSTI2026

MadGraph5_aMC@NLO + Pythia 8.3 event samples for cell resampling studies (13 TeV, Z+jets and top quark pair production)

This record contains two simulated proton–proton collision samples at a center-of-mass energy of √s = 13 TeV, each of 100,000 events, stored as complete truth-level particle records. The samples were produced for a study of optimal-transport-based cell resampling of negatively weighted Monte Carlo events, and are released so that the study can be reproduced and to support further work on negative-weight reduction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

leblanc-lab/ot-cres

Optimal-transport-based cell resampling for negative MC event weights (EMD / spectral EMD metrics, XMD bias measure). Code for arXiv:2607.08723.

Jain, Rishabh [Brown Univ., Providence, RI (United↗
DOE OSTI2022

Diversification of multipotential postmitotic mouse retinal ganglion cell precursors into discrete types

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Direct optimization of neoclassical ion transport in stellarator reactors

Abstract We directly optimize stellarator neoclassical ion transport while holding neoclassical electron transport at a moderate level, creating a scenario favorable for impurity expulsion and retaining good ion confinement. Traditional neoclassical stellarator optimization has focused on minimizing ϵ eff , the geometric factor that characterizes the amount of radial transport due to particles in the 1 / ν regime. Under expected reactor-relevant conditions, core electrons will be in the 1 / ν regime and core fuel ions will be in the ν regime. Traditional optimizations thus minimize electron transport and rely on the radial electric field ( E r ) that develops to confine the ions. This often results in an inward-pointing E r that drives high- Z impurities into the core, which may be troublesome in future reactors. In this work, we increase the ratio of the thermal transport coefficients L 11 e / L 11 i , which previous research has shown can create an outward-pointing E r . This effect is very beneficial for impurity expulsion. We obtain self-consistent density, temperature, and E r profiles at reactor-relevant conditions for an optimized equilibrium. This equilibrium is expected to enjoy significantly improved impurity transport properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

Physics↗
DOE OSTI2023

Simulating and Optimizing Quantum State Transport

The goal of this project was to produce an accurate simulator of the “pitch and catch” process of sending quantum states between SRF cavities, and to find a method for optimizing the control pumps. We developed a program in C++ to integrate the equations of motion with high speed and precision, and used this as a basis for finding an optimal control function to maximize the state transfer efficiency. To demonstrate this we have shown an example of an optimal drive function and the resulting system dynamics, as well as a heat map of the cost function for a range of drive amplitudes.

Weston, Jacob↗
DOE OSTI2025

Energy-efficient multimodal mobility networks in transportation digital twins: Strategies and optimization

The study proposes a comprehensive Transportation Mobility (TransitMo) framework covering conceptual design, model formulation, optimization, simulation, and impact analysis of the transportation mobility system. TransitMo is composed of a transportation digital twin developed in Simulation of Urban MObility (SUMO) and an Intelligent Traffic Management and Control Center (ITMCC) that identifies the best ways to improve the movement of people within urban areas using various modes of transportation. This study encompasses advanced modeling techniques, algorithms, and strategic testing to optimize energy efficiency and mobility in a multimodal shared mobility network. TransitMo’s practical applications are exemplified through a city-scaled simulation network in Chattanooga, TN, employing demographic data to analyze historical traffic patterns and forecast future demands. Central to this methodology are three models: the User Preference Model (UP), the Energy Consumption Model (EC), and the System Optimization Model (SO). These models work in concert to iteratively devise the optimal travel incentives and minimize the total system cost in a real-time manner. In conclusion, test results verified that the proposed adaptive incentive program and optimized bus scheduling can improve network performance by increasing public transit ridership.

42 ENGINEERING↗
DOE OSTI2023

Optimizing the electron transport chain to sustainably improve photosynthesis

Abstract Genetically improving photosynthesis is a key strategy to boosting crop production to meet the rising demand for food and fuel by a rapidly growing global population in a warming climate. Many components of the photosynthetic apparatus have been targeted for genetic modification for improving photosynthesis. Successful translation of these modifications into increased plant productivity in fluctuating environments will depend on whether the electron transport chain (ETC) can support the increased electron transport rate without risking overreduction and photodamage. At present atmospheric conditions, the ETC appears suboptimal and will likely need to be modified to support proposed photosynthetic improvements and to maintain energy balance. Here, I derive photochemical equations to quantify the transport capacity and the corresponding reduction level based on the kinetics of redox reactions along the ETC. Using these theoretical equations and measurements from diverse C3/C4 species across environments, I identify several strategies that can simultaneously increase the transport capacity and decrease the reduction level of the ETC. These strategies include increasing the abundances of reaction centers, cytochrome b6f complexes, and mobile electron carriers, improving their redox kinetics, and decreasing the fraction of secondary quinone–nonreducing photosystem II reaction centers. I also shed light on several previously unexplained experimental findings regarding the physiological impacts of the abundances of the cytochrome b6f complex and plastoquinone. The model developed, and the insights generated from it facilitate the development of sustainable photosynthetic systems for greater crop yields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A holistic approach to the optimization of neutron beam transport at the LANSCE facility

An advanced neutron beam collimation system has been developed as part of an effort to optimize neutron beam transport at the Weapons Neutron Research (WNR) Facility, located within the Los Alamos Neutron Science Center (LANSCE). The goal of this work was to develop and demonstrate techniques to tailor neutron delivery in order to provide maximum available flux on sample with a specific beam profile, while simultaneously reducing unwanted background. A holistic approach was taken, upgrading the facility spallation target, facility metrology infrastructure, and flight path shutter insert to support the implementation of this advanced collimation system. Here, modern instruments and software were employed to conduct facility surveys, characterization of as-built geometry of critical components, 3D ray tracing and neutron transport calculations. Beam images and flux measurements were acquired after installation to evaluate the performance of the collimation system and to demonstrate consistent agreement with MCNP simulations which showed an 87% increase of flux on sample while providing suppression of background neutron impingement on the sample frame by 10 3 .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network

Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.

Kumarasamy, Vijayalakshmi K [The University of Ten↗
DOE OSTI2021

Optimization of Source Material for in-situ Arsenic Doping via Vapor Transport Deposition of CdTe Films

In-situ doping of CdTe/CdSeTe films with arsenic is performed using pre-doped source material prepared by high pressure Bridgman (HPB) melt growth. Arsenic level in the source material is varied from 1018-1020 cm-3. Correspondingly, dopant incorporation in the films prepared using vapor transport deposition (VTD) varied from 3x1017 cm-3–1x1018cm-3. In this range, dopant activation is found to inversely correlate with the dopant incorporation, suggesting compensation. The results from this study indicate film properties can be adjusted by source material.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Optimization of the electron transport layer in quantum dot light-emitting devices

Quantum dot light-emitting devices have emerged as an important technology for display applications. Their emission is a result of recombination between positive and negative charge carriers that are transported through the hole and electron conductive layers, respectively. The selection of electron or hole transport materials in these devices not only demands the alignment of energy levels between the layers but also balances the flow of electrons and holes toward the recombination sites. In this work, we examine a method for device optimization through control of the charge carrier kinetics. We employ impedance spectroscopy to examine the mobility of charge carriers through each of the layers. The derived mobility values provide a path to estimate the transition time of each charge carrier toward the emitting layer. We suggest that an optimal device structure can be obtained when the transition times of both charge carriers toward the active layer are similar. Finally, we examine our hypothesis by focusing on thickness optimization of the electron transport layer.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗
DOE OSTI2026

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗