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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Analysing the effects of heating and gas puffing in Proto-MPEX helicon and auxiliary heated plasmas

The Material Plasma Exposure Experiment (MPEX) is being constructed at Oak Ridge National Laboratory to investigate critical fusion reactor issues, such as plasma–material interactions (PMIs) under reactor-relevant conditions and time scales. The linear device Proto-MPEX was used as a test bed to address anticipated research and development issues associated with heating scenarios and establish the physics basis for MPEX. The SOLPS-ITER code suite has been applied to understand plasma and neutral transport in Proto-MPEX and to increase confidence in predictive simulations for MPEX. Coupling between COMSOL and SOLPS is performed to implement a 2D electron heating profile of the helicon source. The simulations show reasonable agreement with the experimental data for plasma with helicon and auxiliary electron cyclotron heating (ECH). Both Bohm and constant diffusion (D$_\perp$: 0.5 m 2 s –1 and $\chi_\perp$: 1 m 2 s –1 ) simulations show similar levels of agreement with respect to the sparse experimental data available, assuming a few per cent impurity concentration. ECH significantly increases the target electron temperature, however, the target electron density is reduced compared to helicon-only heated plasmas due to an increase in flow velocity and radial losses. The simulations show that further increasing the ECH power results in an increase in the target electron density due to increased recycling flux and ionization. The results indicate that ECH significantly enhances the target heat flux, with ECH power of 50 kW increasing the target heat flux from 0.4 to 17 MW m –2 . It is found that a small amount of gas puffing (GP) near the target plate can further increase the target heat fluxes at the higher ECH power cases, but the target heat flux is reduced at higher GP conditions due to a significant reduction in electron temperature via radiation. ECH and GP scenarios can generate a higher target flux, facilitating improved PMI studies with more reactor-relevant plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Is tokenization needed for masked particle modeling?

In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements of a set, a learning objective that requires no labels and can be applied directly to experimental data. We achieve significant performance improvements over previous work on MPM by addressing inefficiencies in the implementation and incorporating a more powerful decoder. We compare several pre-training tasks and introduce new reconstruction methods that utilize conditional generative models without data tokenization or discretization. We show that these new methods outperform the tokenized learning objective from the original MPM on a new test bed for foundation models for jets, which includes using a wide variety of downstream tasks relevant to jet physics, such as classification, secondary vertex finding, and track identification.

conditional generative models↗
DOE OSTI2019

Single-Submodule Open-Circuit Fault Diagnosis for a Modular Multi-level Converter Using Artificial Intelligent-based Techniques

Modular multi-level converters (MMCs) are one of the promising topologies in recent years for medium or high voltage applications. They are considered as the next generation DC/AC converters for medium/high voltage (MV/HV) motor drive applications due to their transform-less structures, high efficiency and modularity. Reliability is one of the most important challenges in MMCs, since a large number of power switching devices are used and each of these devices can be considered as a potential failure point. It is significant to detect and locate the fault accurately and apply appropriate protections in a timely manner. This paper investigates the behavior of the failure submodules and healthy submodules and use artificial neural network (ANN) classification algorithms for singlesubmodule open-circuit fault diagnosis. The ANN algorithm is implemented in field programmable gate array (FPGA) and the ANN parameters training is completed offline in Matlab. Experimental results of the proposed fault diagnosis for a singlemodule open-circuit fault are presented in this paper.

artificial intelligent↗
DOE OSTI2017

Band Edge Positions and Their Impact on the Simulated Device Performance of ZnSnN 2 -Based Solar Cells

ZnSnN 2 (ZTN) has been proposed as a new earth abundant absorber material for PV applications. While carrier concentration has been reduced to values suitable for device implementation, other properties such as ionization potential, electron affinity and work function are not known. Here, we experimentally determine the value of ionization potential (5.6 eV), electron affinity (4.1 eV) and work function (4.4 eV) for ZTN thin film samples with Zn cation composition Zn/(Zn+Sn) = 0.56 and carrier concentration n = 2x10 19 cm -3 . Using both experimental and theoretical results, we build a model to simulate the device performance of a ZTN/Mg:CuCrO 2 solar cell, showing a potential efficiency of 23% in the limit of no defects present. We also investigate the role of band tails and recombination centers on the cell performance. In particular device simulations show that band tails are highly detrimental to the cell efficiency, and recombination centers are a major limitation if present in concentration comparable to the net carrier density. The effect of the position of the band edges of the p-type junction partner was assessed too. Through this study, we determine the major bottlenecks for the development of ZTN-based solar cell and identify avenues to mitigate them.

14 SOLAR ENERGY↗
DOE OSTI2026

Testing of a 15 kA Superconducting Transformer

Here, the manufacturing of superconducting magnets for High Energy Physics (HEP) and Fusion Energy Sciences (FES) applications requires high-current conductors to generate stronger magnetic fields without increasing the inductance of the magnet. Increased inductance is undesirable due to the associated AC losses, which reduce the temperature margin; and the quench protection also becomes complicated. Testing high-current conductors with a direct current (DC) room temperature power supply is unfeasible for two primary reasons: 1) the limited capacity to supply large currents, and 2) the significant heat load losses at the current leads. A superconducting transformer offers a solution to both challenges. A 50-kA superconducting transformer is planned for manufacturing and commissioning at Brookhaven National Laboratory as part of its user facility upgrade. This transformer will facilitate the testing of superconducting cables, conductors, joints, and insert coils under high magnetic field conditions (10 T) and with currents up to 50-kA. To evaluate the manufacturing process and validate the theoretical models, the magnet division has developed and tested a 15-kA prototype transformer. A control loop has been implemented to ensure precise current delivery to the sample. This paper presents the coil design, manufacturing, and experimental results from the cold tests.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

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

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗
DOE OSTI2017

Development and Implementation of CFD-Informed Models for the Advanced Subchannel Code CTF

The research described in this PhD thesis contributes to the development of efficient methods for utilization of high-fidelity models and codes to inform low-fidelity models and codes in the area of nuclear reactor core thermal-hydraulics. The objective is to increase the accuracy of predictions of quantities of interests using high-fidelity CFD models while preserving the efficiency of low-fidelity subchannel core calculations. An original methodology named Physics- based Approach for High-to-Low Model Information has been further developed and tested. The overall physical phenomena and corresponding localized effects, which are introduced by the presence of spacer grids in light water reactor (LWR) cores, are dissected in corresponding four building basic processes, and corresponding models are informed using high-fidelity CFD codes. These models are a spacer grid-directed cross-flow model, a grid-enhanced turbulent mixing model, a heat transfer enhancement model, and a spacer grid pressure loss model. The localized CFD-models are developed and tested using the CFD code STAR-CCM+, and the corresponding global model development and testing in sub-channel formulation is performed in the thermal- hydraulic subchannel code CTF. The improved CTF simulations utilize data-files derived from CFD STAR-CCM+ simulation results covering the spacer grid design desired for inclusion in the CTF calculation. The current implementation of these models is examined and possibilities for improvement and further development are suggested. The validation experimental database is extended by including the OECD/NRC PSBT benchmark data. The outcome is an enhanced accuracy of CTF predictions while preserving the computational efficiency of a low-fidelity subchannel code.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

This report focuses on integrating TEG and WSN simulators with DC-DC converter as an interface. Here DC stands for direct current. DC-DC converter is essential to balance a wide range of analog, digital, and radio loads acting on the energy source. Also, the voltage level generated by TEGs under varying temperature conditions could be low, irregular, and insufficient to operate WSN, therefore DC-DC is required to boost up the voltage to a desired level. Most of the main problems of DC-DC converters used in TEG system are related to impedance matching between the internal resistance of TEG and the input resistance of DC-DC converter. This report would address the issue associated with dynamic impedance matching under varying temperature conditions in the effort to integrate TEG and WSN. In this effort, dynamic impedance matching algorithms like perturb and observe (P&O) and extremum seeking control (ESC) algorithms will de implemented and compared to achieve maximum peak power tracking (MPPT). In addition, the report will summarize the experimental study performed at BSU on profiling behavior of WSN prototype.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Tailoring Cementitious Materials Towards Value-Added Use of Large CO 2 Volumes

A novel method was developed for the use of carbon dioxide as a raw material in production of hydraulic cements. The solid raw materials were selected to produce a chemistry that is amenable to the formation of alkali aluminosilicate hydrates and carbonates. These raw materials were first pelletized using a relatively low moisture content in the presence of carbon dioxide gas. The resulting pellets were then subjected to milling action in the presence of carbon dioxide in order to mechanochemically transform them into a hydraulic cement comprising largely of alkali aluminosilicates and metastable carbonates. Hydration of this hydraulic cement produces an integrated binder comprising largely of alkali aluminosilicate hydrates and finely dispersed crystalline carbonates. Analytical chemistry and physical test methods were employed in order to evaluate the composition and properties of pellets and the resultant hydraulic cement. The CO 2 uptake of the cement was measured at about 10 wt.%, which was raised with increasing milling duration in a carbon dioxide environment. The composition of the hydraulic cement was refined to further increase the use of abundant and market-limited industrial byproducts as raw materials, and to produce a balance of performance characteristics that meet standard requirements. Concrete materials were prepared with the hybrid hydraulic cement developed in the project, and were thoroughly characterized. The hydraulic cement formulation was further refined in order to produce concrete materials with desired deicer salt scaling resistance. The fresh mix attributes of the hybrid cement concrete were thoroughly characterize in order to evaluate its rheological characteristics, bleeding and plastic shrinkage cracking resistance. The resultant concrete was found to produce mechanical, physical and durability characteristics that were superior to those of conventional Portland cement concrete. The fresh mix rheology, bleeding and plastic shrinkage cracking resistance of the hybrid cement concrete were found to be compatible with the mainstream construction practices. Scalability and compatibility with industrial-scale practices are key to the commercial success of the new class of hydraulic cements developed in this project. These attributes cannot be easily assessed in laboratory-scale investigations. Energy-based models were developed to enable scale-up of the process. Pilot-scale implementation of the process in a power plant was successful. Theoretical analyses complemented with pilot-scale experimental investigations indicated that the transformation from laboratory- to pilot-scale mechanochemical processing can reduce the milling duration by up to 85%. The data produced in pilot-scale processing of the hydraulic cement was used to assess the net carbon footprint of the resultant binder, which was found to be negative due to uptake of carbon dioxide in the process. The energy content of the new hydraulic cement was significantly below that of Portland cement, and it also offered favorable economics. Significant support has been raised for industrial-scale demonstration and commercialization of the technology. A theoretical framework was established based on thermodynamic and diffusion principles to explain the mechanochemical capture and value-added use of carbon dioxide in hydraulic cement production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Beam-, Target- and Double- Spin Asymmetry Measurements in Deeply Virtual π 0 , π + and π - Meson Production

This thesis presents measurements of spin asymmetries in single pion electroproduction from the EG1-DVCS experiment carried out at the Thomas Jefferson National Accelerator Facility in 2009 with use of the CEBAF Large Acceptance Spectrometer. The experiment made use of a 6 GeV longitudinally polarised electron beam and (dynamically) longitudinally polarised targets of 14 NH 3 and 14 ND 3 (giving access to protons and deuterons), providing the means to measure three spin asymmetries: beam-, target-, and double-spin. Deeply Virtual Meson Production for the π 0 , π + and π - channels were studied for the kinematic range of Q 2 > 1 GeV 2 and W > 2 GeV. The collection of measurements includes the analysis of numerous reconstruction topologies, as well as making use of different target materials. These are the world's first charged pion spin asymmetry measurements in this kinematic regime. The sPlot maximum likelihood fit based background subtraction technique was implemented in the data analysis, showing strong agreement with a traditional and commonly used cuts-based approach. This novel technique was thoroughly tested to develop implementation and execution. The results obtained will provide a reference point for future analyses at the upgraded experimental facility and motivate the use of the sPlot technique. These measurements will provide insight into the structure of nucleons through their interpretation in relation to Generalised Parton Distributions which describe substructure correlations between longitudinal momentum and transverse position of partons. In particular, here the spin asymmetries dependence on t , the squared four-momentum transfer to the target nucleon, carries information on the spatial parton distributions in the transverse plane.

Murdoch, Gavin↗
DOE OSTI2025

Assessment of Self-interrogation Safeguards Signatures for Pebble Bed Reactor Fuel

New reactor designs, such as pebble-bed reactors, present challenges for the safeguarding of fissile material. Due to the multi-pass fuel circulation design and the non-uniform path a pebble may traverse through a pebble-bed reactor, there will be variations in the irradiation history of spent fuel pebbles. The standard approach of estimating actinide quantities based on fission gamma spectra or neutron emission paired with depletion modeling may yield uncertainties too large for safeguards and material accountancy. This project investigated, through modeling and experimentation, the potential of neutron self-interrogation of spent fuel pebbles as an innovative method to implement materials accountability. As an example, our feasibility studies indicate that the mass of U-235, U-238, Pu-239 and Pu-241 can be predicted to 4.1, 0.86, 13 and 13 % accuracy, respectively, when measuring 100 closely packed end-of-life spent fuel pebbles over approximately 12 days using a 4π counting geometry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters

The predominance of Kohn–Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software implementations which are capable of leveraging the latest advances in modern high-performance computing (HPC). With recent trends in HPC leading toward increasing reliance on heterogeneous accelerator-based architectures such as graphics processing units (GPU), existing code bases must embrace these architectural advances to maintain the high levels of performance that have come to be expected for these methods. In this work, we purpose a three-level parallelism scheme for the distributed numerical integration of the exchange-correlation (XC) potential in the Gaussian basis set discretization of the Kohn–Sham equations on large computing clusters consisting of multiple GPUs per compute node. In addition, we purpose and demonstrate the efficacy of the use of batched kernels, including batched level-3 BLAS operations, in achieving high levels of performance on the GPU. We demonstrate the performance and scalability of the implementation of the purposed method in the NWChemEx software package by comparing to the existing scalable CPU XC integration in NWChem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Phase 0 study for a geothermal superheated water proof of concept facility

A Phase 0 study for the selection of a representative liquid-dominated geothermal resource of moderate salinity and temperature is discussed. Selection and conceptual design of a nominal 10-MWe energy conversion system, and implementation planning for Phase 1: subsystem (component, experiments) and Phase 2: final design, construction, and operation of experimental research facilities are reported. The objective of the overall program is to demonstrate the technical and economic viability of utilizing moderate temperature and salinity liquid-dominated resources with acceptable environmental impact, and thus encourage commercial scale development of geothermal electrical power generation.

Douglass, R. H.↗
NASA NTRS1982

Simulation and testing of digital control on a flexible beam

Large space structures are expected to have control problems due to low stiffness and damping, and control laws for these structures must deal with shape and configuration control as well as attitude and orbit maintenance. In general, these control tasks must be accomplished without adversely interacting with the lightly damped and low frequency vibration modes of the structure. Modal control schemes have been proposed to deal with these problems. A discrete time parameter adaptive control scheme which uses modal control has been proposed by Montgomery and Johnson (1978). In the present investigation the method considered by Montgomery and Johnson is applied to a homogeneous free-free beam in both numerical simulation and laboratory experimentation. Mathematical modeling of the beam is treated in a manner expedient for digital simulation and control implementation.

Williams, J. P.↗
NASA NTRS1982

Development of a Priest interferometer for measurement of the thermal expansion of a graphite epoxy in the temperature range 116-366 K

The thermal expansion behavior of graphite epoxy laminates between 116 and 366 degrees Kelvin was investigated using as implementation of the Priest interferometer concept. The design, construction and use of the interferometer along with the experimental results it was used to generate are described. The experimental program consisted of 25 tests on 25.4 mm and 6.35 mm wide, 8 ply pi/4 quasi-isotropic T300-5208 graphite/epoxy specimens and 3 tests on a 25.4 mm wide unidirectional specimen. Experimental results are presented for all tests along with a discussion of the interferometer's limitations and some possible improvements in its design.

Short, J. S.↗
NASA NTRS1982

Thermoelastohydrodynamic analysis of an oil pumping ring seal

The selection and evaluation of the numerical methods used in the thermoelastohydrodynamic analysis of an oil pumping ring seal are described, and the results from test problems used to demonstrate the validity of the implementing computer program are presented. A sampling of predicted pumping ring performance values is compared with existing experimental data. Agreement between prediction and test performance is obtained, yielding detailed information concerning fluid and solid parameters.

Smith, P. J.↗
NASA NTRS1986

Measurement and application of fault latency

The time interval between the occurrence of a fault and the detection of the error caused by the fault is divided by the generation of that error into two parts: fault latency and error latency. Since the moment of error generation is not directly observable, all related works in the literature have dealt with only the sum of fault and error latencies, thereby making the analysis of their separate effects impossible. To remedy this deficiency, (1) a new methodology for indirectly measuring fault latency is presented; the distribution of fault latency is derived from the methodology; and (3) the knowledge of fault latency is applied to the analysis of two important examples. The proposed methodology has been implemented for measuring fault latency in the Fault-Tolerant Multiprocessor (FTMP) at the NASA Airlab. The experimental results show wide variations in the mean fault latencies of different function circuits within FTMP. Also, the measured distributions of fault latency are shown to have monotone hazard rates. Consequently, Gamma and Weibull distributions are selected for the least-squares fit as the distribution of fault latency.

Shin, K. G.↗