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At least 271 records · Page 15

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DOE OSTI2026

High-throughput validation of phase formability and simulation accuracy of Cantor alloys

High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density Functional Theory (DFT) and calculation of phase diagrams (CALPHAD), facilitate screening of phase formability as a function of composition and temperature. However, the integration of computational predictions with experimental validation remains challenging in high-throughput studies. In this work, we introduce a quantitative confidence metric to assess the agreement between predictions and experimental observations, providing a quantitative measure of the confidence of machine learning models trained on either DFT or CALPHAD input in accounting for experimental evidence. The experimental dataset was generated via high-throughput in-situ synchrotron X-ray diffraction on compositionally varied FeNiMnCr alloy libraries, heated from room temperature to ~1000 °C. Agreement between the observed and predicted phases was evaluated using either temperature-independent phase classification or a model that incorporates a temperature-dependent probability of phase formation. This integrated approach demonstrates where strong overall agreement between computation and experiment exists, while also identifying key discrepancies, particularly in FCC/BCC predictions at Mn-rich regions to inform future model refinement.

36 - MATERIALS SCIENCE↗

NASA NTRS1993

A comparison of refined models for flexible subassemblies

Interactions between structure response and control of large flexible space systems have challenged current modeling techniques and have prompted development of new techniques for model improvement. Due to the geometric complexity of envisioned large flexible space structures, finite element models (FEM's) will be used to predict the dynamic characteristics of structural components. It is widely accepted that these models must be experimentally 'validated' before their acceptance as the basis for final design analysis. However, predictions of modal properties (natural frequencies, mode shapes, and damping ratios) are often in error when compared to those obtained from Experimental Modal Analysis (EMA). Recent research efforts have resulted in the development of algorithmic approaches for model improvement, also referred to as system or structure identification.

Smith, Suzanne Weaver↗

NASA NTRSDate not supplied

Assessing Performance of Radar and Visual Sensing Techniques for Ground-To-Air Surveillance in Advanced Air Mobility

The safe integration of Unmanned Aircraft Vehicles (UAV) within the civil airspace is of great interest to NASA’s Advanced Air Mobility project, which envisions high density of operations in and around urban areas that include both UAV and AAM aircraft. To enable safe autonomous operations of both platforms, reliable airspace surveillance strategies must be designed and experimentally validated in relevant scenarios, where multiple small UAV operate flying in low altitude conditions. An example of such a scenario is described in this paper which provides performance assessment of various sensing strategies experimentally tested during flight campaigns with four UAV completing simultaneous missions from vertiports. Such campaigns are performed by the High Density Vertiplex subproject which assesses a prototype of Urban Air Mobility ecosystem. For the purposes of this work, the flights are observed from multiple sensing nodes each with radar and camera sensors. The visual detection and tracking algorithms achieved 96.1% to 99.9% average tracking coverage of the UAV above the horizon, reaching detection ranges larger than 1 kilometer for octocopter. Radar-based tracking shows a lower coverage mainly due to ground clutter removal challenges but provides comparable detection ranges and meter-level range accuracy.

Federica Vitiello↗

NASA NTRS1994

Nonlinear dynamics of drops and bubbles and chaotic phenomena

Nonlinear phenomena associated with the dynamics of free drops and bubbles are investigated analytically, numerically and experimentally. Although newly developed levitation and measurement techniques have been implemented, the full experimental validation of theoretical predictions has been hindered by interfering artifacts associated with levitation in the Earth gravitational field. The low gravity environment of orbital space flight has been shown to provide a more quiescent environment which can be utilized to better match the idealized theoretical conditions. The research effort described in this paper is a closely coupled collaboration between predictive and guiding theoretical activities and a unique experimental program involving the ultrasonic and electrostatic levitation of single droplets and bubbles. The goal is to develop and to validate methods based on nonlinear dynamics for the understanding of the large amplitude oscillatory response of single drops and bubbles to both isotropic and asymmetric pressure stimuli. The first specific area on interest has been the resonant coupling between volume and shape oscillatory modes isolated gas or vapor bubbles in a liquid host. The result of multiple time-scale asymptotic treatment, combined with domain perturbation and bifurcation methods, has been the prediction of resonant and near-resonant coupling between volume and shape modes leading to stable as well as chaotic oscillations. Experimental investigations of the large amplitude shape oscillation modes of centimeter-size single bubbles trapped in water at 1 G and under reduced hydrostatic pressure, have suggested the possibility of a low gravity experiment to study the direct coupling between these low frequency shape modes and the volume pulsation, sound-radiating mode. The second subject of interest has involved numerical modeling, using the boundary integral method, of the large amplitude shape oscillations of charged and uncharged drops in the presence of a static or time-varying electric field. Theoretically predicted non linearity in the resonant frequency of the fundamental quadrupole mode has been verified by the accompanying experimental studies. Additional phenomena such as hysteresis in the frequency response of ultrasoncially levitated droplets in the presence of a time varying electric field, and mode coupling in the oscillations of ultrasonically modulated droplets, have also been uncovered. One of the results of this ground-based research has been the identification and characterization of phenomena strictly associated with the influence of the gravitational field. This has also allowed us to identify the specific requirements for potential microgravity investigations yielding new information not obtainable on Earth.

Trinh, Eugene H.↗

NASA NTRS1998

Mathematical Modeling of Loop Heat Pipes

The primary focus of this study is to model steady-state performance of a Loop Heat Pipe (LHP). The mathematical model is based on the steady-state energy balance equations at each component of the LHP. The heat exchange between each LHP component and the surrounding is taken into account. Both convection and radiation environments are modeled. The loop operating temperature is calculated as a function of the applied power at a given loop condition. Experimental validation of the model is attempted by using two different LHP designs. The mathematical model is tested at different sink temperatures and at different elevations of the loop. Tbc comparison of the calculations and experimental results showed very good agreement (within 3%). This method proved to be a useful tool in studying steady-state LHP performance characteristics.

Kaya, Tarik↗

NASA NTRS1993

Motion control of 7-DOF arms - The configuration control approach

Graphics simulation and real-time implementation of configuration control schemes for a redundant 7-DOF Robotics Research arm are described. The arm kinematics and motion control schemes are described briefly. This is followed by a description of a graphics simulation environment for 7-DOF arm control on the Silicon Graphics IRIS Workstation. Computer simulation results are presented to demonstrate elbow control, collision avoidance, and optimal joint movement as redundancy resolution goals. The laboratory setup for experimental validation of motion control of the 7-DOF Robotics Research arm is then described. The configuration control approach is implemented on a Motorola-68020/VME-bus-based real-time controller, with elbow positioning for redundancy resolution. Experimental results demonstrate the efficacy of configuration control for real-time control.

Seraji, Homayoun↗

DOE OSTI2026

Improving Marine Energy Production Through Commercialization of a Low Cost, Drag-Reducing Slippery Coating (CRADA 679 Abstract)

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and we have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing well over 50% cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the government-sponsored two-year program is complete. The main technical goal is to design, manufacture, and experimentally validate a new coating that can reduce hydrodynamic skin friction drag by 20%. The main commercialization goal is to develop a roadmap that identifies activities needed to complete SLIDE-Coat’s development after the conclusion of this project. Year 1 will focus on adaptation and modification of the existing SLIC coating system to optimize drag reduction and assessment and quantification of drag reduction on relevant materials in a laboratory setting. Year 2 will focus on optimizing and demonstrating drag reduction with preferred coatings. The manufacturability, ease of application, adhesion to relevant surfaces, and consistency will be assessed. Quantification of drag reduction on prototype materials in a relevant marine field setting will be executed.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.

Science & Technology - Other Topics↗

DOE OSTI2025

Production Target Studies at the M4 Diagnostic Absorber

High power production targetry is becoming essential to the future of HEP, but our current physics simulations are lacking validation in the lower energy ranges that many proposed secondary beam experiments will use. We propose a study of target materials at the M4 diagnostic absorber to monitor target temperatures during irradiation by an 8 GeV proton beam and provide some experimental validation for our simulations at lower energies as well as potentially perform post-irradiation examination of samples to understand changes to material properties.

Bloomer, Madeleine [UC, Davis] (ORCID:000900080329↗

DOE OSTI2025

Production Target Studies at the M4 Diagnostic Absorber

Bloomer, Madeleine [UC, Davis] (ORCID:000900080329↗

DOE OSTI2025

Temperature-dependent lattice dynamics in polycrystalline ZrN

Zirconium nitride holds promise for improving nuclear reactor components, where thermal conductivity is important, highlighting the need for a detailed understanding of its phonons. However, the phonon dispersion derived from previous inelastic neutron scattering data is in disagreement with modern theoretical calculations, pointing to the necessity for further experimental validation. Here, in this study, we use inelastic neutron scattering experiments on polycrystalline ZrN at 6, 100, 300, 400, and 600 K, and density functional theory (DFT) calculations to study the momentum-resolved scattering and the phonon density of states. Both experimental and theoretical results reveal a phonon cutoff energy near 65 meV, in stark disagreement with previous single-crystal neutron scattering measurements indicating a cutoff near 75 meV. The 65 meV cutoff energy is, however, in reasonable agreement with previous measurements on ZrN 0.9 . Consistency between our theoretical and experimental results confirms that ZrN is a wide phonon band gap system and that DFT provides a reliable description of its phonons.

DFT↗

DOE OSTI2025

Dehumidification energy storage using a stratified liquid desiccant tank

Liquid desiccants can play an important role in reducing dehumidification energy requirements in the built environment. Because they are in a liquid state, the desiccant can be easily stored and then used to dehumidify buildings during peak energy consumption periods. By maintaining stratification between concentrated and diluted desiccant solutions, a single tank can be used to store liquid desiccant for energy storage purposes. Using a stratified tank instead of separate tanks for dilute and concentrated solutions will reduce storage costs and increase energy storage densities for liquid desiccant systems. This paper describes the experimental validation and one-dimensional modeling of a stratified liquid desiccant tank. The stratified tank prototype developed achieved 80 % of the theoretical energy storage density based on an imposed desiccant concentration change. Here, the stratified tank model was able to reasonably reproduce the experimental results. Using this model, the impact of varying operational conditions on the energy density of the stratified liquid desiccant energy storage was evaluated. Depending on the operating conditions, stratified liquid desiccant energy storage using aqueous LiCl up to 40 wt% can achieve energy storage densities in excess of 330 kWh/m 3 .

25 ENERGY STORAGE↗

NASA NTRS2005

Approach and Instrument Placement Validation

The Mars Exploration Rovers (MER) from the 2003 flight mission represents the state of the art technology for target approach and instrument placement on Mars. It currently takes 3 sols (Martian days) for the rover to place an instrument on a designated rock target that is about 10 to 20 m away. The objective of this project is to provide an experimentally validated single-sol instrument placement capability to future Mars missions. After completing numerous test runs on the Rocky8 rover under various test conditions, it has been observed that lighting conditions, shadow effects, target features and the initial target distance have an effect on the performance and reliability of the tracking software. Additional software validation testing will be conducted in the months to come.

Ator, Danielle↗

DOE OSTI2026

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗

DOE OSTI2025

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems

Resource allocation in High Performance Computing (HPC) environments presents a complex and multifaceted challenge for job scheduling algorithms. Beyond the efficient allocation of system resources, schedulers must account for and optimize multiple performance metrics, including job wait time and system throughput. Traditional heuristic-based scheduling algorithms increasingly struggle and lack the efficiency needed to meet the demands and address the complexity and scale of modern HPC systems. Consequently, recent research efforts have focused on leveraging advancements in Artificial Intelligence (AI) and Deep Learning (DL), particularly Reinforcement Learning (RL), to develop more adaptable and intelligent scheduling strategies. Previous RL-based scheduling approaches have explored a range of algorithms, from Deep Q-Networks (DQN) to Proximal Policy Optimization (PPO), and more recently, hybrid methods that integrate Graph Neural Networks (GNNs) with RL techniques. However, a common limitation across these methods is their reliance on relatively small datasets, with few methods being evaluated using large-scale, multi-million-job trace datasets representative of real-world HPC workloads. Moreover, existing RL schedulers face scalability issues due to centralized policy updates, which hinder training efficiency and performance when applied to large datasets. This study introduces a novel RL-based scheduler utilizing Decentralized Distributed Proximal Policy Optimization (DD-PPO) algorithm, which supports large-scale distributed training across multiple workers without requiring parameter synchronization at every step. By eliminating reliance on centralized updates to a shared policy, the DD-PPO scheduler enhances scalability, training efficiency, and sample utilization. Experimental validation using a large real-world dataset containing over 11.5 million job traces collected from petascale HPC systems over six years assesses the influence of dataset scale on training effectiveness and compares DD-PPO performance to traditional and advanced scheduling approaches. The experimental results demonstrate improved scheduling performance in comparison to both heuristic-based schedulers and existing RL-based scheduling algorithms.

AI↗

DOE OSTI2024

Advancing Thermal-Hydraulic Modeling Capabilities for Molten Salt Reactors in Pronghorn

This is an M2 report for the NEAMS program. This work focuses on advancing the modeling and simulation capabilities for Molten Salt Reactors (MSRs) within Pronghorn, addressing key thermal-hydraulic challenges that must be addressed for the safe and efficient operation of these advanced reactors. This report summarizes the development and validation of the following new models in Pronghorn: (i) two-equation RANS turbulence models, (ii) near-wall turbulence corrections due to curvature and roughness, and (iii) multidimensional two-phase drift-flux models. For each of these cases, along with the experimental validation, an application study of interest to MSRs is presented. In addition, this report also presents recent improvements in the domain-overlapping coupling between Pronghorn and SAM to address the cases of weakly compressible flow and flow reversal. Finally, an MSR action that greatly simplifies the setup of MSR models using NEAMS tools is described.

42 ENGINEERING↗

DOE OSTI2025

Final Design for Thermal/Epithermal eXperiments (TEX) with Lithium Absorbers to Provide Validation Benchmarks for Y-12 Electrorefining Facility

One of the main goals of the Thermal/Epithermal eXperiments (TEX) project is to use existing Nuclear Criticality Safety Program (NCSP) assets to create critical experiment plutonium and uranium test beds for materials important to criticality safety that have insufficient benchmark evaluations. The plutonium test bed experiments were completed in 2018 and are published in the 2020 edition of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The uranium test bed assemblies were completed in 2023 and accepted in the 2024 edition of the ICSBEP Handbook. The Nuclear Criticality Safety (NCS) group at Y-12 National Security Complex has identified programmatic need for validation cases for uranium electrorefining operations at Y-12. The electrorefining operation credits lithium enriched in 6 Li in addition to 35 Cl as absorbers in the design criticality safety evaluation for precluding criticality under upset conditions in the large and geometrically unfavorable electro-refiner. There is, however, inadequate experimental validation for the 6 Li absorbers. As an extension of the TEX uranium test bed, TEX-Cl critical experiments were performed with sodium chloride salt to address the 35 Cl thermal absorption as well as other validation needs at Los Alamos National Laboratory (LANL). These experiments were completed in 2024 and accepted into the 2025 ICSBEP Handbook. To continue the methodology used in TEX-Cl, TEX-Li aims to accomplish the same. The overall design of both experiments was to use commercially available, high purity, salts with polyethylene moderator and HEU plates to configure a critical assembly. Three experiments are planned for TEX-Li using encapsulated lithium carbonate (Li 2 CO 3 ), with natural 6 Li abundance. For all experiments, the highly enriched uranium (HEU) Jemima plates will be used as fissile material. Multiple layers will be stacked together with encapsulated Li 2 CO 3 alternated with polyethylene in standard configurations. Standard stacking was found to be optimal in matching the different sensitivity profiles provided by the Y-12 models. Three configurations are proposed with varying polyethylene moderation and a constant 1/4” absorber thickness. The first uses 11 layers of 5/4” polyethylene, the second uses 9 layers of 3/4” polyethylene, and the third uses 10 layers of 1/2” polyethylene. Calculations showed that some alternative forms of lithium-based materials provided slightly less-optimal sensitivity profiles when compared to lithium carbonate but come with other drawbacks. These alternatives included lithium aluminate (LiAlO 2 ), Aluminum-2050 alloy, Aluminum-8090, Aluminum-2095, lithium hydride (LiH), and lithium fluoride (LiF). Lithium aluminate and aluminum-2050 provided comparable sensitivity profiles when compared to lithium carbonate and can be used instead if lithium carbonate cannot be readily procured. After a broad material study, lithium carbonate outperformed any alternative material with a balance in affordability and workability. The assessment of experimental uncertainties of the non-absorber and absorber components was predicted to be 0.00089 and 0.00093 Δk eff , respectively. The largest uncertainties may be reduced with precision dimensional inspection of the components. Many of the parts and equipment for IER 575 have already been fabricated or procured for previous projects and therefore do not contribute significantly to the overall cost of this experiment. This includes the Jemima plates and Comet critical assembly machine, which are existing NCSP assets, as well as the aluminum platen and polyethylene reflector rings, which were fabricated and authorized for the TEX experiment involving HEU with polyethylene. Lithium carbonate containers will be procured by LANL and will be filled by LLNL. The total material costs for TEX-Li experiments are estimated to be on the order of $\$$47,400. Precision inspection, including dimensional, mass, density, and impurity, is recommended for all components for an estimated cost of $\$$12,000.

35Cl↗

DOE OSTI2025

TGCM: (T)rait, (G)ene, and (C)rop Growth (M)odel Directed Targeted Gene Characterization in Sorghum (Final Technical Report)

Understanding which genes control important crop traits could help scientists develop better bioenergy and food crops more efficiently. However, plant genomes contain tens of thousands of genes, and testing each one individually is expensive and time-consuming. This project developed computational tools to predict which genes are most likely to matter, allowing researchers to focus their efforts where they will have the greatest impact. This project developed and validated integrated approaches combining machine learning, quantitative genetics, and crop growth modeling to improve the efficiency of functional gene characterization in sorghum (Sorghum bicolor), a critical bioenergy and food security crop. The research addressed a fundamental challenge in plant biology: the majority of genes in plant genomes lack experimentally validated functions, making it difficult to prioritize which genes to study using resource-intensive reverse genetics approaches.

60 APPLIED LIFE SCIENCES↗