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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cubesat system

Small cubesat systems may be available for a lower cost, have a higher reliability, and be much simpler to use than conventional cubesats. A complete turnkey system solution may be provided, including the ground station and remote field units. The satellite, ground station, and field unit may be provided separately as kits that are ready to go out-of-the-box as soon as they arrive. This enables universities, researchers, and hobbyists to obtain and deploy their own functional satellites. Furthermore, theoretical designs and functionality may be rapidly prototyped and demonstrated, which allows for proof-of-concept without needing to build a larger, more expensive satellite system and hope that the new design or functionality works as intended.

Judd, Stephen↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. In this paper, how we have developed one of the HUNTER modules, the individual module for evaluating performance shaping factors (PSFs), is introduced. The PSF refers to any factor that influences human performance such as workload or complexity. It has been used for highlighting human errors and adjusting the error probabilities in the existing HRA. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, which is the representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also design the individual module composed of the two functions: 1) the PSF qualification function that automatically or manually evaluates a PSF level, and 2) the PSF quantification function that dynamically or statically determines the PSF multiplier values and integrate them to adjust human error probabilities (HEPs). How each function works with the SPAR-H PSFs and how the PSFs adjust the HEPs are investigated through literature and discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. This paper explores how we developed one of the HUNTER modules: namely, the Individual module for evaluating performance shaping factors (PSFs). A PSF is any factor that influences human performance (e.g., workload or complexity). In the existing HRA, they are used to highlight human errors and adjust error probabilities. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, a representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed the human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also designed the Individual module to consist of two functions: (1) the PSF qualification function for automatically or manually evaluating PSF levels, and (2) the PSF quantification function for dynamically or statically determining PSF multiplier values and integrating them to adjust human error probabilities (HEPs). How each function works in regard to the SPAR-H PSFs, and how the PSFs serve to adjust the HEPs, were investigated via literature review and are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Development of a calculation framework coupling Monte Carlo neutronics, subchannel thermal-hydraulics and 1.5D fuel thermo-mechanics

A coupled calculation system consisting of the Monte Carlo neutronic solver SERPENT and the fuel behaviour solver TRANSURANUS was extended with the sub-channel thermal-hydraulic solver SUBCHANFLOW to form a coupled calculation framework for multi-physics reactor analyses. The coupling between the 3 solvers was accomplished via a driver program written in Perl that runs the solvers, processes and transfers the output data between the solvers and monitors the convergence. While some features of the coupling are still under development, a steady-state coupled calculation resulting in convergence was performed for a single hexagonal fuel assembly to demonstrate that the base functionalities work as expected. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1986

Constructing a working taxonomy of functional Ada software components for real-time embedded system applications

A major impediment to a systematic attack on Ada software reusability is the lack of an effective taxonomy for software component functions. The scope of all possible applications of Ada software is considered too great to allow the practical development of a working taxonomy. Instead, for the purposes herein, the scope of Ada software application is limited to device and subsystem control in real-time embedded systems. A functional approach is taken in constructing the taxonomy tree for identified Ada domain. The use of modular software functions as a starting point fits well with the object oriented programming philosophy of Ada. Examples of the types of functions represented within the working taxonomy are real time kernels, interrupt service routines, synchronization and message passing, data conversion, digital filtering and signal conditioning, and device control. The constructed taxonomy is proposed as a framework from which a need analysis can be performed to reveal voids in current Ada real-time embedded programming efforts for Space Station.

Wallace, Robert↗
DOE OSTI2022

Global calculation of two-neutrino double- β decay within the finite amplitude method in nuclear density functional theory

Two-neutrino double-beta (2νββ) decay has been used to constrain the neutron-proton part of effective interactions, which in turn is used to compute the nuclear matrix elements for neutrinoless double-beta decay, the observation of which would have important consequences for fundamental physics. We carefully examine 2νββ matrix elements within the proton-neutron quasiparticle random-phase approximation with nuclear energy density functionals. Here we work with functionals that are fit globally to single-beta-decay half-lives and charge-exchange giant-resonance energies, but not to 2νββ half-lives themselves, to evaluate the 2νββ nuclear matrix elements for all important nuclei, including those whose half-lives have not yet been measured. Such a comprehensive evaluation in large model spaces without configuration truncation requires an efficient computational scheme; we employ a double contour integration within the finite amplitude method. The results generally reproduce the nuclear matrix element extracted from half-lives well, without the use of any of those half-lives in the fitting procedure. We present predictions of the matrix elements in a total of 27 nuclei with half-lives that are still unmeasured.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2009

NASA Constellation Program (CxP) Key Driving Requirements and Element Descriptions for International Architecture Working Group (IAWG) Functional Teams Human Transportation Cargo Transportation

The NASA Constellation uncrewed cargo mission delivers cargo to any designated location on the lunar surface (or other staging point) in a single mission. This capability is used to deliver surface infrastructure needed for lunar outpost construction, to provide periodic logistics resupply to support a continuous human lunar presence, and potentially deliver other assets to various locations.In the nominal mission mode, the Altair lunar lander is launched on Ares V into Low Earth Orbit (LEO), following a short Low Earth Orbit (LEO) loiter period, the Earth Departure Stage (EDS) performs the Trans Lunar Injection (TLI) burn and is then jettisoned. The Altair performs translunar trajectory correction maneuvers as necessary and performs the Lunar Orbit Insertion (LOI) burn. Altair then descends to the surface to land near a designated target, presumably in proximity to an Outpost location or another site of interest for exploration.Alternatively, the EDS and Altair Descent Stage could deliver assets to various staging points within their propulsive capabilities.

Martinez, Roland M.↗
DOE OSTI2022

Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley's K-function

This work presents novel multiscale spatial data analytics using Ripley's K-function, as a measure of spatial interaction, to study one-dimensional arrangement of fractures. Fracture spatial arrangements are classified into clustered, anticlustered, or indistinguishable from random by testing statistical significance of the calculated Ripley's K-function. Characterizations of fracture arrangements are performed as a function of length scale and position. Analysis of the K-function along the study interval identifies where fracture clustering and anticlustering occur. Here, a simulation technique is also introduced here to statistically reconstruct spatial arrangements and to generate fracture realizations that are spatially similar to the fractures observed in the field. With this simulation technique, one can also fill spatial gaps in fracture measurements where data are absent, unreliable, or unused. Synthetic as well as field-measured 1D fracture datasets are used for testing and demonstration. Methods introduced in this work can be readily applied to fracture datasets observed in outcrops, borehole image logs, and cores.

58 GEOSCIENCES↗
DOE OSTI2022

Zero-cost corrections to influence functional coefficients from bath response functions

Recent work has shown that it is possible to circumvent the calculation of the spectral density and directly generate the coefficients of the discretized influence functionals using data from classical trajectory simulations. However, the accuracy of this procedure depends on the validity of the high temperature approximation. In this work, an alternative derivation based on the Kubo formalism is provided. This enables the calculation of additional correction terms that increases the range of applicability of the procedure to lower temperatures. Because it is based on the Kubo-transformed correlation function, this approach allows the direct use of correlation functions obtained from methods such as ring-polymer molecular dynamics and centroid molecular dynamics in determining the influence functional coefficients for subsequent system-solvent simulations. The accuracy of the original procedure and the corrected procedure is investigated across a range of parameters. It is interesting that the correction term comes at zero additional cost. Furthermore, it is possible to improve upon the correction using zero-cost physical intuition and heuristics making the method even more accurate.

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

Theoretical framework for soft X-ray Fourier transform spectroscopy using the Wigner function

This work presents a theoretical framework for the propagation of partially coherent Gaussian radiation in a modified Mach–Zehnder interferometer designed for Fourier transform spectroscopy (FTS) applications. Using the Wigner function formalism, we analytically propagate the radiation through the system and benchmark our approach by comparing the resulting interference pattern and interferogram with previous works in the diffraction limit. Our analysis reveals that the transverse coherence length requirement of the incident light field for detectable modulation is less stringent than previously assumed. Additionally, we provide theoretical demonstrations of FTS performance across various wavelengths using the proposed setup. These findings underscore the potential of this interferometer to achieve high-resolution FTS in the soft X-ray regime.

Fourier transform spectroscopy↗
DOE OSTI2024

Augmenting machine learning of Grad–Shafranov equilibrium reconstruction with Green's functions

This work presents a method for predicting plasma equilibria in tokamak fusion experiments and reactors. The approach involves representing the plasma current as a linear combination of basis functions using principal component analysis of plasma toroidal current densities (J t ) from the EFIT-AI equilibrium database. Then utilizing EFIT's Green's function tables, basis functions are created for the poloidal flux (ψ) and diagnostics generated from the toroidal current (J t ). Similar to the idea of a physics-informed neural network (NN), this physically enforces consistency between ψ, J t , and the synthetic diagnostics. First, the predictive capability of a least squares technique to minimize the error on the synthetic diagnostics is employed. The results show that the method achieves high accuracy in predicting ψ and moderate accuracy in predicting J t with median R 2 = 0.9993 and R 2 = 0.978, respectively. A comprehensive NN using a network architecture search is also employed to predict the coefficients of the basis functions. The NN demonstrates significantly better performance compared to the least squares method with median R 2 = 0.9997 and 0.9916 for J t and ψ, respectively. The robustness of the method is evaluated by handling missing or incorrect data through the least squares filling of missing data, which shows that the NN prediction remains strong even with a reduced number of diagnostics. Additionally, the method is tested on plasmas outside of the training range showing reasonable results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Electrocatalytic grafting of polyvinyl chloride plastics

Polyvinyl chloride (PVC) plastics require high loadings of plasticizers and stabilizers to achieve commercially useful bulk properties. However, these non-covalent additives leach from PVC over time, resulting in the loss of their tailored functionality. This work details the electrocatalytic functionalization of PVC to covalently graft plasticizing additives directly onto the polymer backbone. Here, mechanistic insights guided the design of electrocatalysts capable of modifying C–Cl bonds of PVC under mild conditions with high selectivity while suppressing side reactions such as elimination and chain scission. Functional groups that mimic PVC plasticizers are covalently installed into the backbone of PVC to create new materials with distinct bulk properties from the original polymer. The degree of polymer grafting is easily controlled by simply changing the redox capacity that is passed during electrolysis. This strategy is employed to create chemically- and leach-resistant PVC materials by directly electrolyzing mixtures of consumer PVC products

Zackasee, Jordan L.S.↗
DOE OSTI2025

SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions

Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation functions on the edges of the computational graph followed by summation on nodes. The learnable edge activation functions in the original implementation are basis spline functions (B-Spline). Here, we present a model in which learnable grids of B-Spline activation functions are replaced by grids of re-weighted sine functions (SineKAN). We evaluate numerical performance of our model on a benchmark vision task. We show that our model can perform better than or comparable to B-Spline KAN models and an alternative KAN implementation based on periodic cosine and sine functions representing a Fourier Series. Further, we show that SineKAN has numerical accuracy that could scale comparably to dense neural networks (DNNs). Compared to the two baseline KAN models, SineKAN achieves a substantial speed increase at all hidden layer sizes, batch sizes, and depths. Current advantage of DNNs due to hardware and software optimizations are discussed along with theoretical scaling. Additionally, properties of SineKAN compared to other KAN implementations and current limitations are also discussed.

Reinhardt, Eric↗
DOE OSTI2021

Reconfiguration of Amorphous Complex Oxides: A Route to a Broad Range of Assembly Phenomena, Hybrid Materials, and Novel Functionalities

This work demonstrate that reconfiguration of amorphous oxide layers drives the assembly of oxide-based and freestanding nanomembranes into 3D structures with a radius of a few hundred nanometers. Reconfiguration-driven assembly is a versatile approach to impart large strains and strain gradients in a broad palette of complex oxides. This capability allows for manipulating and enhancing ferroelectricity, flexoelectricity, piezoelectricity, superconductivity, and ferromagnetism in complex oxides. Moreover, by the approach presented in this work, strain-engineered oxides are obtained in the form of 3D structures that can be fabricated in parallel on any substrate, including large-area and single crystalline semiconductor substrates. This approach will create a vast expanse of possibilities to investigate and leverage strain-tunable effects in amorphous, poly-crystalline, and single-crystalline complex oxides. Reconfiguration-driven assembly of NMs also allows combining different materials in a radial geometry and through scalable processes. For example, radial superlattices of Si (or GaAs) and various complex oxides or alternating layers of different complex oxides (e.g., SrTiO 3 and LaAlO 3 ) could be fabricated by release and heating of bilayer NMs. Here, a broad palette of electronic band structures and spin–orbit interactions could then be obtained by tailoring the curvature of the self-assembled NMs and the materials that the heterostructure comprises.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Non-coding RNAs: update on mechanisms and therapeutic targets from the ESC Working Groups of Myocardial Function and Cellular Biology of the Heart

Abstract Vast parts of mammalian genomes are actively transcribed, predominantly giving rise to non-coding RNA (ncRNA) transcripts including microRNAs, long ncRNAs, and circular RNAs among others. Contrary to previous opinions that most of these RNAs are non-functional molecules, they are now recognized as critical regulators of many physiological and pathological processes including those of the cardiovascular system. The discovery of functional ncRNAs has opened up new research avenues aiming at understanding ncRNA-related disease mechanisms as well as exploiting them as novel therapeutics in cardiovascular therapy. In this review, we give an update on the current progress in ncRNA research, particularly focusing on cardiovascular physiological and disease processes, which are under current investigation at the ESC Working Groups of Myocardial Function and Cellular Biology of the Heart. This includes a range of topics such as extracellular vesicle-mediated communication, neurohormonal regulation, inflammation, cardiac remodelling, cardio-oncology as well as cardiac development and regeneration, collectively highlighting the wide-spread involvement and importance of ncRNAs in the cardiovascular system.

Bär, Christian↗
NASA NTRS1996

Functional and Multifunctional Polymers: Materials for Smart Structures

The ultimate goal of the research in smart structures and smart materials is the development of a new generation of products/devices which will perform better than products/devices built from passive materials. There are a few examples of multilayer polymer systems which function as smart structures, e.g. a synthetic muscle which is a multilayer assembly of a poly(ethylene) layer, a gold layer, and a poly(pyrrole) layer immersed in a liquid electrolyte. Oxidation and reductions of the active pyrrole layer causes the assembly to reversibly deflect and mimic biological muscles. The drawback of such a setup is slow response times and the use of a liquid electrolyte. We have developed multifunctional polymers which will eliminate the use of a liquid electrolyte, and also because the functionalities of the polymers are within a few hundred angstroms, an improved response time to changes in the external field should be possible. Such multifunctional polymers may be classified as the futuristic 'smart materials.' These materials are composed of a number of different functionalities which work in a synergistic fashion to function as a device. The device performs on the application of an external field and such multifunctional polymers may be scientifically labeled as 'field responsive polymers.' Our group has undertaken a systematic approach to develop functional and multifunctional polymers capable of functioning as field responsive polymers. Our approach utilizes multicomponent polymer systems (block copolymers and graft copolymers), the strategy involves the preparation of block or graft copolymers where the functionalities are limited to different phases in a microphase separated system. Depending on the weight (or volume) fractions of each of the components, different microstructures are possible. And, because of the intimate contact between the functional components, an increase in the synergism between the functionalities may be observed. In this presentation, three examples of multifunctional polymers developed in our labs will be reported. The first class of multifunctional polymers are the microphase separated mixed (ionic and electronic) conducting or MIEC block copolymers. The second class being developed in our labs are the biocompatible conductive materials and the conductive fluids. The final class may be considered microwave active smart polymers.

Arnold, S.↗