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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

The Radio Frequency Health Node Wireless Sensor System

The Radio Frequency Health Node (RFHN) wireless sensor system differs from other wireless sensor systems in ways originally intended to enhance utility as an instrumentation system for a spacecraft. The RFHN can also be adapted to use in terrestrial applications in which there are requirements for operational flexibility and integrability into higher-level instrumentation and data acquisition systems. As shown in the figure, the heart of the system is the RFHN, which is a unit that passes commands and data between (1) one or more commercially available wireless sensor units (optionally, also including wired sensor units) and (2) command and data interfaces with a local control computer that may be part of the spacecraft or other engineering system in which the wireless sensor system is installed. In turn, the local control computer can be in radio or wire communication with a remote control computer that may be part of a higher-level system. The remote control computer, acting via the local control computer and the RFHN, cannot only monitor readout data from the sensor units but can also remotely configure (program or reprogram) the RFHN and the sensor units during operation. In a spacecraft application, the RFHN and the sensor units can also be configured more nearly directly, prior to launch, via a serial interface that includes an umbilical cable between the spacecraft and ground support equipment. In either case, the RFHN wireless sensor system has the flexibility to be configured, as required, with different numbers and types of sensors for different applications. The RFHN can be used to effect realtime transfer of data from, and commands to, the wireless sensor units. It can also store data for later retrieval by an external computer. The RFHN communicates with the wireless sensor units via a radio transceiver module. The modular design of the RFHN makes it possible to add radio transceiver modules as needed to accommodate additional sets of wireless sensor units. The RFHN includes a core module that performs generic computer functions, including management of power and input, output, processing, and storage of data. In a typical application, the processing capabilities in the RFHN are utilized to perform preprocessing, trending, and fusion of sensor data. The core module also serves as the unit through which the remote control computer configures the sensor units and the rest of the RFHN.

Valencia, J. Emilio↗
NASA NTRS2022

First-Principles Theory of the Rate of Magnetic Reconnection in Magnetospheric and Solar Plasmas

The rate of magnetic reconnection is of the utmost importance in a variety of processes because it controls, for example, the rate energy is released in solar flares, the speed of the Dungey convection cycle in Earth’s magnetosphere, and the energy release rate in harmful geomagnetic substorms. It is known from numerical simulations and satellite observations that the rate is approximately 0.1 in normalized units, but despite years of effort, a full theoretical prediction has not been obtained. Here, we present a first-principles theory for the reconnection rate in non-relativistic electron-ion collisionless plasmas, and show that the same prediction explains why Sweet-Parker reconnection is considerably slower. The key consideration of this analysis is the pressure at the reconnection site (i.e., the x-line). We show that the Hall electromagnetic fields in antiparallel reconnection cause an energy void, equivalently a pressure depletion, at the x-line, so the reconnection exhaust opens out, enabling the fast rate of 0.1. If the energy can reach the x-line to replenish the pressure, the exhaust does not open out. In addition to heliospheric applications, these results are expected to impact reconnection studies in planetary magnetospheres, magnetically confined fusion devices, and astrophysical plasmas.

Yi-Hsin Liu↗
NASA NTRS2024

Electron Beam Welding of Additively Manufactured Niobium Alloy Heat Pipes

Additively manufactured refractory alloy-liquid metal heat pipes are being developed and tested for thermal management systems within nuclear propulsion and power applications. This study investigated electron beam (EB) welded joints on a laser powder bed fusion printed niobium alloy (C-103) and the impact of multiple joined heat pipe sections on working fluid flow and container leak-tightness. Results showed that EB welded joints connecting multiple heat pipe sections do not impact working fluid wicking behavior and the printed C-103 material and the EB welds joining the tubular sections created a leak-tight container. Interestingly, CT data showed an order of magnitude greater number and volume of porosity indications in the ground mating surface weld compared to the as-printed mating surface weld. The work concluded that AM is a viable manufacturing process for niobium alloy heat pipes and provided valuable insights for future AM heat pipe research and development.

Electron beam welding↗
DOE OSTI2022

Investigation of resistive magnetic field generation by intense proton beams in dense plasmas

Current and future applications of intense proton sources abound, including radiography, cancer therapy, warm dense matter generation, and inertial confinement fusion. With increasingly efficient acceleration and focusing mechanisms, proton current densities may soon approach and exceed 10 10 A/cm 2 , e.g., via intense laser drivers. Simulations have previously shown that in this current density regime, beam-induced field generation plays a significant role in beam transport through dense plasmas. Here, we present a theoretical model for the generation of resistive magnetic fields by intense proton beam transport through solid density plasmas. The theoretical evolution of the magnetic field profile is calculated using an analytic model for aluminum resistivity, heat capacity, and stopping power, applicable from cold matter to hot plasma. The effects of various beam and material parameters on the field are investigated and explained for both monoenergetic and Maxwellian proton beams. For a proton beam with Maxwellian temperature 5 MeV and total energy 10 J, the model calculates resistive magnetic fields up to 150 T in aluminum. In conclusion, the calculated field profiles from several beam cases are compared with 2D hybrid particle-in-cell simulations, with good agreement found in magnitude and time scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Towards Qualification and Certification of Laser Powder Bed Fusion Ti-6Al-4V with In-Situ Process Monitoring and Automated Defect Detection

Qualification and certification of laser powder bed fusion (LPBF) parts are two challenges that must be answered to ensure suitability for critical applications. In-situ monitoring using high frame rate thermal and conventional optical imaging sensors is applied to the LPBF build process. Currently, the large volume of data from such sensors becomes untenable for manual inspection in production environments. This presentation serves to address this in-situ monitoring deficiency in two ways. First, a framework for managing data streams from LPBF process monitoring sensors is described. Second, two candidate image analysis techniques are presented: one is a set of heuristics that are easily interpretable, and the other is an uninterpretable convolutional neural network. These strategies are compared in terms of performance, computational expense, and speed. These methodologies represent platforms for connecting processing conditions to process modeling efforts aligned with the qualification and certification mission for LPBF Ti-6Al-4V components.

Qualification↗
DOE OSTI2020

An Overview of the Hybrid Illinois Device for Research and Applications Material Analysis Test-stand (HIDRA-MAT)

The Hybrid Illinois Device for Research and Applications (HIDRA) at the University of Illinois at Urbana-Champaign is a toroidal plasma device that enables fusion plasma-material interaction testing with both stellarator and tokamak plasmas. HIDRA’s long-pulse steady state stellarator plasmas provide a testbed for plasma facing component (PFC) plasma exposures. The HIDRA Material Analysis Test-stand (HIDRA-MAT) is a material characterization module attached to HIDRA that is being designed and fabricated to include thermal desorption spectroscopy and laser induced breakdown spectroscopy systems for in-vacuo PFC characterization. A specialized rotatable sample holder positions the sample for liquid metal droplet application from a liquid metal droplet injector on HIDRA-MAT. Early experiments look to investigate the effect liquid lithium has on porous tungsten samples’ retention of H, D, and He after plasma exposure. Preliminary results from a dual residual gas analyzer system show the ability to differentiate D2 and He in HIDRA-MAT. Finally, this work aims to advance the understanding of liquid metal PFCs and further the design and development of new fusion PFCs and technologies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Anisotropic angular scattering models of elastic electron-neutral collisions for Monte Carlo plasma simulations

Many laboratory and industrial plasma applications require accurate modeling techniques to understand the interplay between microscopic and macroscopic processes. A prime example of this interplay is how particle and Monte Carlo (MC) simulation codes describe angular scattering of electrons following elastic scattering events. The forward peaked nature of high energy electron elastic scattering is relatively trivial to accurately describe in plasma simulations. However, for lower energy collisions, which produce near isotropic or backward peaked differential cross sections, there is not a strong consensus among the plasma modeling community on how to best describe these angular scattering trends. Here, in this study, we propose a systematic method to approximate the aforementioned non-trivial angular scattering behavior with a formula that can be readily implemented in particle-in-cell (PIC) and/or MC plasma simulation codes. The present approach is specifically applied to fusion relevant atomic hydrogen and helium, as well as for molecular hydrogen, and results are also applicable to the atomic isotopes and homonuclear molecular isotopologues of these species. Comparisons between the present angular distribution function and benchmark scattering data were used to validate the proposed models. In addition, two-term Boltzmann calculations and PIC direct simulation MC simulations revealed that the proposed angular distribution function is accurate, agreeing very well with benchmark convergent close-coupling scattering calculations, and electron transport measurements. These studies confirmed that the present angular distribution function model can be utilized without the need of renormalization to the momentum transfer cross section (as opposed to using the elastic scattering integrated cross section), which has been suggested by several studies in order to correct for deficient angular scattering models, and to agree with transport measurements. Hence, the present anisotropic angular scattering model can be utilized to accurately model the momentum transfer as well as the electron trajectories of elastic collisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

ToF-SIMS spectral analysis of pristine and neutron irradiated single crystal tungsten

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying materials including high spatial resolution and high mass accuracy of elements, molecules, and isotopes. Its ability to resolve isotopes is especially attractive in studying transmutation products of single crystal tungsten (SCW) post neutron irradiation. Tungsten (W) is a contender of plasma facing materials (PFMs) due to its high thermal and radiological stability. PFMs to be used in the construction of fusion vessels are subject to high temperature and neutron irradiation, resulting in changes to materials including transmutation, which ultimately impact material mechanical and thermal properties. We used IONTOF TOF.SIMS V instrument equipped with a 30 keV Bi 3 + primary ion beam to study pristine SCW and irradiated SCW speciemens. Scanning electron microscope coupled with focused ion beam (SEM-FIB) was used to reduce the dosage of neutron irradiated tungsten and prepare for specimens for SIMS analysis. Static ToF-SIMS spectra were obtained, and transmutation product peak identification was presented in this work. Identified molecules and molecular fragments were compared against isotope theoretical mass to charge ratios of tungsten, rhenium, osmium, and other relevant products. Our results show that ToF-SIMS provides a viable means to study transmutation products of W post neutron irradiation. Such applications are suitable to investigate transmutation effects on materials that are being considered and developed for fusion pilot plants.

36 MATERIALS SCIENCE↗
NASA NTRS1992

A neuro-fuzzy architecture for real-time applications

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach.

Ramamoorthy, P. A.↗
NASA NTRS2024

Correlations of Additive Manufacturing Model-Based Process Metrics With Spatter-Induced Porosity in the Powder Bed Fusion-Laser Beam/Metallic Process

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M) additive manufacturing (AM) process comprise a multitude of sequential weld passes. Qualifying materials for components in critical applications requires a thorough understanding of pertinent processing-microstructure-property relationships. Porosity defects have a strong adverse effect on the mechanical properties of a material. The morphology of porosity defects created by lack of fusion in PBF-LB/M often exhibit high aspect ratios that can act as stress concentrators and become crack initiation sites. The occurrence of spatter induced porosity is studied using synchronized AM model-based process metrics and porosity measured by high-resolution X-ray computed tomography. A novel AM process metric is introduced to quantify the relative exposure to spatter ejecta impacts and incorporation throughout the sequence of the PBF-LB/M process. Further characterization using optical metallography and scanning electron microscopy indicated that both keyhole and lack of fusion porosity correlated statistically with the spatter ejecta impact field of the PBF-LB/M process. Both keyhole and lack of fusion porosity can be predicted by the spatter exposure process metric, which can be exploited to control the fusion sequence.

Additive Manufacturing↗
DOE OSTI2024

Overview of physics results from the ADITYA-U tokamak and future experiments

The ADITYA upgrade (ADITYA-U), a medium-sized (R 0 = 75 cm, a = 25 cm) conventional tokamak facility in India, has been consistently producing experiments findings by usingcircular and shaped-plasmas. Recognizing the plasma parameters aligning closely with the design parameters of circular limited plasmas, ADITYA-U shifted its focus toward exploring the operational regime for experimentation on saw-tooth and MHD phenomena. Moreover, ADITYA-U has made consistent advancements toward conducting preliminary plasma shaping experiments through the activation of top and bottom divertor coils utilizing hydrogen as well as deuterium fuels. Confinement is improved by a factor of ~1.5 in D 2 plasmas when compared to H 2 plasmas of ADITYA-U. Further, ADITYA-U operations emphasize preventing disruptions and runaway electrons (REs) to ensure safe operations for future fusion devices. Significant suppression of REs has been achieved in ADITYA-U with the application of pulsed localized vertical magnetic field (LVF) perturbation, thereby establishing the technique's independence from the tokamak device. The successful RE mitigation requires a critical threshold of LVF pulse magnitude, which is approximately 1% of the toroidal magnetic field, and a minimum duration of ~5 ms. Apart from this, several novel findings have been achieved in the ADITYA-U experiments, including the modification of sawtooth duration through gas-puff, the emergence of MHD-induced geodesic acoustic mode-like oscillations, the propagation of fast heat pulses induced by MHD activity, the control of RE dynamics through Gas-puffs, the propagation of pinch-driven cold-pulses, the transport and core accumulations of argon impurities, the mass dependency of plasma toroidal rotation and the detection of 'RICE' scaling, as well as the characterization of edge plasma using wall conditioning methods, such as glow discharge cleaning using a combination of Ar-H 2 mixture, localized wall cleaning by electron cyclotron resonant plasma, and the development of machine learning-based disruption predictions, will be discussed in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Mysteries of Nuclear Fusion: How can we build a star on Earth? [Slides]

This presentation given at the Women's Physics Summer Camp focuses on nuclear fusion as an alternative to fossil fuels, renewable energy sources and nuclear fission energy. The presentation explains plasma physics and how it might be used to generate power. Current attempts and potential applications are outlined. An appeal is made for people trained in mathematics, physics, chemistry, engineering, computer science to solve these problems. If technical problems can be overcome, fusion technology will play a part in a clean, prosperous Earth and expand humanity’s reach to the stars.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A causal data fusion method for the general exposure and outcome

Abstract With the advent of the big data era, the need to combine multiple individual data sets to draw causal effects arises naturally in many medical and biological applications. Especially each data set cannot measure enough confounders to infer the causal effect of an exposure on an outcome. In this article, we extend the method proposed by a previous study to causal data fusion of more than two data sets without external validation and to a more general (continuous or discrete) exposure and outcome. Theoretically, we obtain the condition for identifiability of exposure effects using multiple individual data sources for the continuous or discrete exposure and outcome. The simulation results show that our proposed causal data fusion method has unbiased causal effect estimate and higher precision than traditional regression, meta‐analysis and statistical matching methods. We further apply our method to study the causal effect of BMI on glucose level in individuals with diabetes by combining two data sets. Our method is essential for causal data fusion and provides important insights into the ongoing discourse on the empirical analysis of merging multiple individual data sources.

Li, Hongkai↗
NASA NTRS1987

Fluoride salts and container materials for thermal energy storage applications in the temperature range 973 to 1400 K

Multicomponent fluoride salt mixtures were characterized for use as latent heat of fusion heat storage materials in advanced solar dynamic space power systems with operating temperatures in the range of 973 to 1400 K. The melting points and eutectic composition for many systems with published phase diagrams were verified, and several new eutectic compositions were identified. Additionally, the heats of fusion of several binary and ternary eutectics and congruently melting intermediate compounds were measured by differential scanning calorimetry. The extent of corrosion of various metals by fluoride melts was estimated from thermodynamic considerations, and equilibrium conditions inside a containment vessel were calculated as functions of the initial moisture content of the salt and free volume above the molten salt. Preliminary experimental data on the corrosion of commercial, high-temperature alloys in LiF-19.5CaF2 and NaF-27CaF2-36MgF2 melts are presented and compared to the thermodynamic predictions.

Misra, Ajay K.↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
NASA NTRS1994

Neural network application to comprehensive engine diagnostics

We have previously reported on the use of neural networks for detection and identification of faults in complex microprocessor controlled powertrain systems. The data analyzed in those studies consisted of the full spectrum of signals passing between the engine and the real-time microprocessor controller. The specific task of the classification system was to classify system operation as nominal or abnormal and to identify the fault present. The primary concern in earlier work was the identification of faults, in sensors or actuators in the powertrain system as it was exercised over its full operating range. The use of data from a variety of sources, each contributing some potentially useful information to the classification task, is commonly referred to as sensor fusion and typifies the type of problems successfully addressed using neural networks. In this work we explore the application of neural networks to a different diagnostic problem, the diagnosis of faults in newly manufactured engines and the utility of neural networks for process control.

Marko, Kenneth A.↗
DOE OSTI2025

An elastin-like polymer targeting vascular endothelial growth factor receptor-1 reduces survival in serum-starved endothelial cells

Peptides often exhibit biological activity that depends on the context in which they are displayed and delivered. Understanding and controlling these contextual effects on peptide function is critical for designing targeted and responsive peptide-based biomaterials and therapeutics. Genetically engineered protein polymers such as elastin-like polypeptides (ELPs) can incorporate bioactive peptide motifs and are attractive candidates for biomaterials used in tissue engineering and targeted drug delivery. They also present an opportunity for investigating and modulating cell signaling pathways by presenting a peptide ligand in various defined chemical and physical environments. Vascular endothelial growth factor receptor-1 (VEGFR1) signaling plays important and complex roles in cell survival and angiogenesis, but polymeric materials that interact with this signaling axis are scarce. In this study, a novel genetically engineered elastin-like polymer that targets VEGFR1 is characterized. This polymer, termed R1B-ELP, binds to human endothelial cells in a manner dependent on its VEGFR1-targeting motif and, based on cell proliferation and cytotoxicity assays, demonstrates activity consistent with disrupting pro-survival signaling necessary for endothelial cell function under conditions of environmental stress. Notably, these findings indicate that ELP fusion alters the functional behavior of the targeting peptide. Modulators of VEGFR1 signaling have potential applications in basic studies of angiogenesis as well as in therapeutic applications targeting vascular or inflammatory diseases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transmission electron microscopy with in-situ ion irradiation: Facilities and community

Whilst there is a clear scientific and technological need for the technical capabilities of transmission electron microscopes with in-situ ion irradiation, it also requires a collaborative community of international researchers to support such facilities in successfully meeting this demand. Instruments of this type serve to provide fundamental understanding of the mechanisms which drive changes in materials important to nuclear fission and fusion energy, the semiconductor industry, quantum information systems, space travel, astronomy, geology and many more applications. As these areas continue to evolve and the instrumentation possibilities expand, the capacity of in-situ ion irradiation facilities must also develop hand-in-hand with the user community to deliver an ever-greater diversity of high-fidelity extreme-environment experimentation. Future directions for the field, such as miniaturization from MEMS/microfluidic devices and advanced controls with ML-based analysis, continuously emerge to advance both the hardware and software which support the coupling of TEMs with ion beams. This review sets out to provide up-to-date insights into the community and advancement of current, and development of future, facilities which have the potential to further unlock access to the nanoscale exploration of coupled extreme environments crucial to many of the important science and engineering challenges we face today.

In-situ irradiation↗