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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing EV Motor Design Through Knowledge-Based AI and Hierarchical Fuzzy Logic Model

This work presents a novel approach to optimizing electric vehicle motor design through the integration of Knowledge-Based Artificial Intelligence (KB-AI) and Hierarchical Fuzzy Logic. Traditional motor design processes are time-intensive, relying heavily on iterative simulations and domain-specific expertise. These processes are further complicated by the nonlinear relationships between key design parameters. The proposed framework addresses these challenges by systematically encoding expert knowledge from scientific literature into a fuzzy logic system, allowing for the efficient handling of complex design variables. The hierarchical fuzzy logic model reduces computational complexity by decomposing the nonlinear relationships into manageable rule sets while maintaining design accuracy. The proposed methodology was applied to the design of a 100 kW motor, yielding optimal values for key parameters. This resulted in a compact motor design with a volume of 2.2 liters, showcasing the framework’s ability to deliver high-performance, application-specific motor configurations.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
NASA NTRS1998

Pulse Shaped 8-PSK Bandwidth Efficiency and Spectral Spike Elimination

The most bandwidth-efficient communication methods are imperative to cope with the congested frequency bands. Pulse shaping methods have excellent effects on narrowing bandwidth and increasing band utilization. The position of the baseband filters for the pulse shaping is crucial. Post-modulation pulse shaping (a low pass filter is located after the modulator) can change signals from constant envelope to non-constant envelope, and non-constant envelope signals through non-linear device (a SSPA or TWT) can further spread the power spectra. Pre-modulation pulse shaping (a filter is located before the modulator) will have constant envelope. These two pulse shaping methods have different effects on narrowing the bandwidth and producing bit errors. This report studied the effect of various pre-modulation pulse shaping filters with respect to bandwidth, spectral spikes and bit error rate. A pre-modulation pulse shaped 8-ary Phase Shift Keying (8PSK) modulation was used throughout the simulations. In addition to traditional pulse shaping filters, such as Bessel, Butterworth and Square Root Raised Cosine (SRRC), other kinds of filters or pulse waveforms were also studied in the pre-modulation pulse shaping method. Simulations were conducted by using the Signal Processing Worksystem (SPW) software package on HP workstations which simulated the power spectral density of pulse shaped 8-PSK signals, end to end system performance and bit error rates (BERS) as a function of Eb/No using pulse shaping in an AWGN channel. These results are compared with the post-modulation pulse shaped 8-PSK results. The simulations indicate traditional pulse shaping filters used in pre-modulation pulse shaping may produce narrower bandwidth, but with worse BER than those in post-modulation pulse shaping. Theory and simulations show pre- modulation pulse shaping could also produce discrete line power spectra (spikes) at regular frequency intervals. These spikes may cause interference with adjacent channel and reduce power efficiency. Some particular pulses (filters), such as trapezoid and pulses with different transits (such as weighted raised cosine transit) were found to reduce bandwidth and not generate spectral spikes. Although a solid state power amplifier (SSPA) was simulated in the non-linear (saturation) region, output power spectra did not spread due to the constant envelope 8-PSK signals.

Tao, Jian-Ping↗
NASA NTRS2008

From Lunar Regolith to Fabricated Parts: Technology Developments and the Utilization of Moon Dirt

The U.S. Space Exploration Policy has as a cornerstone the establishment of an outpost on the moon. This lunar outpost wil1 eventually provide the necessary planning, technology development, testbed, and training for manned missions in the future beyond the Moon. As part of the overall activity, the National Aeronautics and Space Administration (NASA) is investigating how the in situ resources can be utilized to improve mission success by reducing up-mass, improving safety, reducing risk, and bringing down costs for the overall mission. Marshall Space Flight Center (MSFC), along with other NASA centers, is supporting this endeavor by exploring how lunar regolith can be mined for uses such as construction, life support, propulsion, power, and fabrication. An infrastructure capable of fabrication and nondestructive evaluation will be needed to support habitat structure development and maintenance, tools and mechanical parts fabrication, as well as repair and replacement of space-mission hardware such as life-support items, vehicle components, and crew systems, This infrastructure will utilize the technologies being developed under the In Situ Fabrication and Repair (ISFR) element, which is working in conjunction with the technologies being developed under the In Situ Resources Utilization (ISRU) element, to live off the land. The ISFR Element supports the Space Exploration Initiative by reducing downtime due to failed components; decreasing risk to crew by recovering quickly from degraded operation of equipment; improving system functionality with advanced geometry capabilities; and enhancing mission safety by reducing assembly part counts of original designs where possible. This paper addresses the need and plan for understanding the properties of the lunar regolith to determine the applicability of using this material in a fabrication process. This effort includes the development of high fidelity simulants that will be used in fabrication processes on the ground to drive down risk and increase the Technology Readiness Level (TRL) prior to implementing this capability on the moon. Also discussed in this paper is the on-going research using Electron Beam Melting (EBM) technology as a possible solution to manufacturing parts and spares on the Moon's surface.

McLemore, C. A.↗
NASA NTRS1991

Macromolecular recognition: Structural aspects of the origin of the genetic system

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of the evolution of life. Using computational and modeling techniques and guided by analogies from present day systems, we seek to understand the emergence of the genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. Modeling of the ancestral aminoacyl-tRNA-synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. The minimal structural requirements for the catalysis of tRNA aminoacylation are being explored. A formation of an aminoacyl adenylate was studied in the framework of ab initio molecular orbital theory. The role of individual residues in the vicinity of the TyrRS active site was examined, and the effect of all possible amino acids substitutions near the active site was examined. A formation of aminoacyl tRNA was studied by the molecular modeling system SYBYL with the high resolution crystallographic structures of the present day tRNA, aRS's complexes. The ultimate goal is to propose a simple RNA segment that is small enough to be build in the primordial chemical environment but maintains the specificity and catalytic activity of the contemporary RNA enzyme. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation were studied. The structural characteristics of the target helices, particularly a possible role for the G-T pair, is also studied by a molecular dynamics (MD) simulation technique.

Rein, Robert↗
NASA NTRS1973

Laboratory simulation of graphite formation in stellar envelopes

A technique has been developed which permits laboratory simulation of graphite condensation in the envelopes of cool, late sequence stars. Processes in the stellar envelope were simulated by allowing hydrogen-carbon mixtures of typical circumstellar composition and temperature to expand freely into vacuum, cooling and supersaturating the vapor. Expansion products were determined mass spectrometrically through the use of molecular beam techniques. The results of laboratory expansions were scaled to those occurring near M and N stars by comparing the number of collisional events in each case. Kinetic considerations indicate that the important rate process in rarefied envelopes will be C2 formation; consequently scaling by termolecular collisions was employed. Results of this study imply that envelope expansions near M giants contribute at most .01 of the observed interstellar grain density. In the case of pulsating N stars, on the other hand, the results are not inconsistent with previous predictions of essentially complete carbon condensation.

Dorfeld, W. G.↗
DOE OSTI2025

Acceleration of the particle-in-cell code Osiris with graphics processing units

Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments

We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗
DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗
NASA NTRS1990

Laboratory experiments on stability and entrainment of oceanic stratocumulus. Part 1: Instability experiment

The existence and persistence of marine stratocumulus play a significant role in the overall energy budget of the earth. Their stability and entrainment process are important in global climate studies, as well as for local weather forecasting. The purposes of the experimental simulations are to study this process and to address this paradox. The effects of buoyancy reversal is investigated, followed by two types of experiments. An instability experiment involves the behavior of a fully turbulent wake near the inversion generated by a sliding plate. Due to buoyancy reversal, the heavy, mixed fluid starts to sink, turning the potential energy created by the mixing process into kinetic energy, thereby increasing the entrainment rate. An entrainment experiment, using a vertically oscillating grid driven by a controllable speed motor, produces many eddy-induced entrainments at a surface region on scales much less than the depth of the layer.

Shy, Shenqyang S.↗
NASA NTRS1992

Simulating the arcjet thruster using a nonlinear active load

Arcjet thrusters are known to have distinctly nonlinear electrical characteristics with negative incremental resistance throughout their normal operating region. The 1-kW arcjet simulator proposed here accurately mimics these characteristics statically, and dynamically up to 40 kHz. Testing with a power-processing unit (PPU) and the simulator, a 1-kW arcjet, and a resistive load bank established that the simulator accurately predicted the transient behavior of the PPU-arcjet combination, while the resistive load bank did not. The simulator uses resistors and insulated-gate bipolar transistors to dissipate the PPU output power; a nonlinear feedback is applied to produce the desired v-i characteristics. This feedback is analyzed dynamically. The arcjet simulator allows development of a PPU to a higher level of confidence before beginning testing at an arcjet facility.

Altenburger, Gene P.↗
NASA NTRS2001

A Coupled Plasma and Sheath Model for High Density Reactors

We present a coupled plasma and collisionless; sheath model for the simulation of high density plasma processing reactors. Due to inefficiencies in numerical schemes and the resulting computational burden, a coupled multidimensional plasma and sheath simulation has not been possible model for gas mixtures and high density reactors of practical interest. In this work we demonstrate that with a fully implicit algorithm and a refined computational mesh, a self-consistent plasma and sheath simulation is feasible. We discuss the details of the model equations, the importance of ion inertia, and the resulting sheath profiles for argon and chlorine plasmas. We find that at low operating pressures (10-30 mTorr), the charge separation occurs only within a 0.5 mm layer near the surface in a 300 mm inductively coupled plasma etch reactor. A unified model eliminates the use of off-line or loosely coupled sheath models with simplifying assumptions which generally lead to uncertainties in ion flux and sheath electrical properties.

Deepak, Bose↗
NASA NTRS2026

NASA JSC’s Simulant Development Lab Capabilities and Artemis Testing

The Simulant Development Lab (SDL) is a multifunctional collaborative workspace that supports the development, curation, analysis, testing, and distribution of planetary regolith simulants – including lunar, Martian, asteroidal, and other granular materials. The lab provides a multidisciplinary setting for scientific characterization of simulant physical properties and for engineering evaluations conducted with simulant test beds. To enable this work, the SDL curates and maintains a stock of more than 35 metric tons of simulant material. To evaluate these materials and support testing goals, the lab is equipped with a comprehensive suite of processing tools and analytical instruments. These capabilities enable the SDL’s mission at NASA’s Johnson Space Center to distribute, develop, process, characterize, and test regolith simulants for mission relevant applications. Through controlled and repeatable testing environments that replicate the physical and compositional properties of lunar regolith, the SDL supports Artemis hardware maturation, providing safe, Earth‑based analogs for evaluating systems that must withstand regolith dust interactions, physical wear and abrasion, and operational loads. The facility’s extensive simulant inventory and integrated geological and engineering test infrastructure accelerate technology readiness for Artemis and future exploration campaigns (e.g., future crewed or robotic missions to Mars).

Simulant Development Lab↗
NASA NTRS1989

PRIME: A bottom-up approach to probabilistic rule development

PRIME is a system to be used by an intelligent machine to allow it to operate in an abstract but uncertain (or stochastic) environment. It maintains a model of the effects of the machine's actions in the form of a rule base, which is induced from experience. This bottom-up approach to rule development allows the model to adapt to changes in the environment. Each rule consists of a condition under which the rule is active, an action, the effect of the action on the environment, and an estimate of the probability of this effect occurring. The effect probabilities are used to model the uncertainty in the environment, permitting multiple possible effects for a single action under a particular set of conditions. The objective of the intelligent machine is to satisfy user-specified goals with maximum probability of success. PRIME fulfills this requirement in two ways: it continuously updates the rule base with the most recent information, to ensure the validity of the model; and it generates plans which have the maximum probability of achieving the goals, based on the probability estimates in the rule base. PRIME is composed of three main processes: exploration, generalization, and planning. In exploration, the machine executes various randomly chosen actions, observes the effects on the environment, and updates the rule base accordingly. This process is used to develop the rule base in simulation, as well as to supplement the current knowledge during normal operation. Generalization is the procedure used to induce general rules from experience, which is encoded in the form of specific rules. These general rules extend the machine's knowledge to situations which have not been encountered yet, thereby increasing the capability of the machine to plan effectively. Planning is the process of constructing an optimal sequence of actions to satisfy a goal, using the rule base to predict the effects of these actions and to determine the probability of success of the plan. The rule representation and many other data structures were specifically chosen to maximize the efficiency of these processes. A simulated environment was designed to test the performance of PRIME. The results of experimentation were largely negative. The main problem was that the domain coverage of the rules was inadequate for the number of rules stored in the rule base, due to redundancies in general rules and numerous rules covering ineffective actions. It was determined that a more efficient generalization, and some form of goal-directed exploration, are necessary in order to solve most of the current deficiencies in PRIME.

Miller, Scott A.↗
DOE OSTI2025

Processing behavior evolution of recycled polypropylene: An integrated experimental and Computer-Aided engineering simulation study

Polypropylene (PP) comprises 21% of global plastics production and 18% of plastics waste, yet less than 1% of solid-waste PP is recycled in the United States (U.S.), representing significant environmental and economic challenges. Mechanical recycling, the most prevalent recycling method, subject's materials to thermomechanical stresses, which typically degrade polymer properties, affecting the quality of polymer products. This study replicates the impact of mechanical recycling through multiple extrusion cycles to examine the effects on PP's processing behavior. Dynamic scanning calorimetry (DSC) measurements showed stable melting behavior across all processing conditions, while crystallization analysis exhibited consistent shifts in kinetic parameters. Rheological characterization demonstrated progressive viscosity reductions through successive cycles, particularly pronounced at elevated reprocessing temperatures. Here, the integration of this experimental data into injection molding simulations showed that recycled PP maintains viable processing characteristics. Our findings establish quantitative correlations between processing history and material behavior, enabling optimization of processing parameters directly rather than relying on trial-and-error approaches. While these results reflect idealized recycling conditions with minimal contamination, they provide a framework for understanding fundamental property evolution during mechanical recycling.

42 ENGINEERING↗
NASA NTRS1971

An analysis of approach navigation accuracy and guidance requirements for the grand tour mission to the outer planets

The navigation and guidance process for the Jupiter, Saturn and Uranus planetary encounter phases of the 1977 Grand Tour interior mission was simulated. Reference approach navigation accuracies were defined and the relative information content of the various observation types were evaluated. Reference encounter guidance requirements were defined, sensitivities to assumed simulation model parameters were determined and the adequacy of the linear estimation theory was assessed. A linear sequential estimator was used to provide an estimate of the augmented state vector, consisting of the six state variables of position and velocity plus the three components of a planet position bias. The guidance process was simulated using a nonspherical model of the execution errors. Computation algorithms which simulate the navigation and guidance process were derived from theory and implemented into two research-oriented computer programs, written in FORTRAN.

Jones, D. W.↗
DOE OSTI2026

From Pyrolysis Oil to Advanced Biographite Anode: Unravelling Biocoke Structural Evolution and Delayed Coking Effects

Catalytic graphitization of biomass-derived carbon offers a promising route to produce biographite as a sustainable alternative to petroleum-based synthetic graphite for lithium-ion battery (LIB) anodes. This study investigates the physicochemical properties of biocokes produced from pyrolysis oil at carbonization temperatures ranging from 150 degrees C to 500 degrees C. Using an iron (Fe) catalyst, graphitization was performed at 1500 degrees C, significantly lower than the ~3000 degrees C required for conventional synthetic graphite. The effects of introducing an intermediate-temperature hold (400 degrees C-600 degrees C) prior to graphitization were evaluated, simulating a "delayed coking" process to enable the coproduction of sustainable aviation fuels (SAFs). Chemical structure evolution during biocoke formation was analyzed, and proposed mechanisms are presented. Biographites produced via the delayed coking pathway exhibited high crystallinity and excellent electrochemical performance in both half-cell and full-cell LIB configurations. The full cells exhibited an initial discharge capacity close to the theoretical capacity of the NMC622 cathode (175 mAh/g at 4.2 V), and high capacity retention (~88%) after 150 cycles. Notably, the graphitic and electrochemical properties remained stable across the range of intermediate hold temperatures. These findings provide a foundation for optimizing temperature parameters in delayed coking systems to enable scalable, integrated production of biographite and SAFs from pyrolysis oil.

09 BIOMASS FUELS↗
DOE OSTI2025

Semi-supervised permutation invariant particle-level anomaly detection

The development of analysis methods to distinguish potential beyond the Standard Model phenomena in a model-agnostic way can significantly enhance the discovery reach in collider experiments. However, the typical machine learning (ML) algorithms employed for this task require fixed length and ordered inputs that break the natural permutation invariance in collision events. To address this, a semi-supervised anomaly detection tool is presented that takes a variable number of particle-level inputs and leverages a signal model to encode this information into a permutation invariant, event-level representation via supervised training with a Particle Flow Network (PFN). Data events are then encoded into this representation and given as input to an autoencoder for unsupervised ANomaly deTEction on particLe flOw latent sPacE (ANTELOPE), classifying anomalous events based on a low-level and permutation invariant input modeling. Performance of the ANTELOPE architecture is evaluated on simulated samples of hadronic processes in a high energy collider experiment, showing good capability to distinguish disparate models of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗