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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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NASA NTRS1984

Energy release in solar flares

On the basis of observations of energy release in solar flares, it is proposed that different processes may operate on four different time scales; (1) the subsecond scale of subbursts that prominently figure in mm-wave records; (2) the few-seconds scale of elementary bursts featured in hard X-ray records; (3) the few-minutes scale of the impulsive phase; and (4) the longer than tens-of-minutes scale of the gradual phase. It is proposed that the magnetic field concentration into 'magnetic knots' at the photosphere is of consequence to coronal magnetic field structure, so that magnetic fields in this region may be seen as an array of elementary flux tubes. It is further proposed that the gradual phase of energy release involves a steady process of reconnection, while the impulsive phase involves a more stochastic process of reconnection due to mode interaction.

Sturrock, P. A.↗
DOE OSTI2024

FLIT: A Generic Fortran Library based on Interfaces and Templates

This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP – a generic Fortran Library based on Interfaces and Templates.

Gao, Kai↗
DOE OSTI2021

IoT Devices and Applications for Wire-Based Hybrid Manufacturing Machine Tools

Hybrid manufacturing machine tools have the potential to be a disruptive technology as they can leverage the benefits of both additive and subtractive manufacturing by incorporating both processes on the same machine while limiting the downsides of the individual processes. Since these machines use two very disparate manufacturing processes and hybrid manufacturing is an emerging technology, it will be useful to monitor data coming from the machine and apply it to improve the manufacturing process, the operation of the machine, and to integrate the machine into the larger digital framework of Industrial Internet of Things (IoT). The present work discusses IoT devices that would be beneficial to add to a hybrid machine tool as well as applications for those devices. The proposed methods discussed in this work have not been experimentally implemented on a hybrid machine tool and so there are no performance data available yet. The hybrid machine tool used as a basis to generate these IoT applications is the Mazak VC-500A/5x AM Hot Wire Deposition, which is a 5-axis machine tool incorporated with a wire feedstock 4kW laser deposition system. Methodologies and applications will be outlined for machine health and process monitoring. Other areas covered include process benchmarking, secure networking options for the proposed IoT framework, and hybrid process improvement. Limitations of these methods and future work for new sensor devices and application areas is also discussed.

Thien, Austen↗
DOE OSTI2020

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Particle Acceleration in Active Galactic Nuclei

The high efficiency of energy generation inferred from radio observations of quasars and X-ray observations of Seyfert active galactic nuclei (AGNs) is apparently achieved only by the gravitational conversion of the rest mass energy of accreting matter onto supermassive black holes. Evidence for the acceleration of particles to high energies by a central engine is also inferred from observations of apparent superluminal motion in flat spectrum, core-dominated radio sources. This phenomenon is widely attributed to the ejection of relativistic bulk plasma from the nuclei of active galaxies, and accounts for the existence of large scale radio jets and lobes at large distances from the central regions of radio galaxies. Reports of radio jets and superluminal motion from galactic black hole candidate X-ray sources indicate that similar processes are operating in these sources. Observations of luminous, rapidly variable high-energy radiation from active galactic nuclei (AGNs) with the Compton Gamma Ray Observatory show directly that particles are accelerated to high energies in a compact environment. The mechanisms which transform the gravitational potential energy of the infalling matter into nonthermal particle energy in galactic black hole candidates and AGNs are not conclusively identified, although several have been proposed. These include direct acceleration by static electric fields (resulting from, for example, magnetic reconnection), shock acceleration, and energy extraction from the rotational energy of Kerr black holes. The dominant acceleration mechanism(s) operating in the black hole environment can only be determined, of course, by a comparison of model predictions with observations. The purpose of the work proposed for this grant was to investigate stochastic particle acceleration through resonant interactions with plasma waves that populate the magnetosphere surrounding an accreting black hole. Stochastic acceleration has been successfully applied to the problem of ion and electron energization in solar flares, and is capable of accounting for a wide range of both neutral and charged particle emissions. It is also a component in diffusive shock acceleration, since pitch-angle scattering (which is necessary for multiple shock crossings) is accompanied by diffusion in momentum space, which in turn yields a net systematic energy gain; however, stochastic energization will dominate the first-order shock process only in certain parameter regimes. Although stochastic acceleration has been applied to particle energization in the lobes of radio galaxies, its application to the central regions of AGNs has only recently been considered, but not in detail. We proposed to systematically investigate the plasma processes responsible for stochastic particle acceleration in black hole magnetospheres along with the energy-loss processes which impede particle energization. To this end we calculated acceleration rates and escape time scales for protons and electrons resonating with Alfven waves, and for electrons resonating with whistlers. Assuming either a Kolmogorov or Kraichnan wave spectrum, accretion at the Eddington limit, magnetic field strengths near equipartition, and turbulence energy densities approx. 10% of the total magnetic field energy density, we find that Alfven waves accelerate protons to Lorentz factors approx, equals 10(exp 4) - 10(exp 6) before they escape from the system. Acceleration of electrons by fast mode and whistler waves can produce a nonthermal population of relativistic electrons whose maximum energy is determined by a competition with radiation losses.

Miller, James A.↗
NASA NTRS1997

Interstellar and Cometary Dust

'Interstellar dust' forms a continuum of materials with differing properties which I divide into three classes on the basis of observations: (a) diffuse dust, in the low-density interstellar medium; (b) outer-cloud dust, observed in stars close enough to the outer edges of molecular clouds to be observed in the optical and ultraviolet regions of the spectrum, and (c) inner-cloud dust, deep within the cores of molecular clouds, and observed only in the infrared by means of absorption bands of C-H, C=O, 0-H, C(triple bond)N, etc. There is a surprising regularity of the extinction laws between diffuse- and outer-cloud dust. The entire mean extinction law from infrared through the observable ultraviolet spectrum can be characterized by a single parameter. There are real deviations from this mean law, larger than observational uncertainties, but they are much smaller than differences of the mean laws in diffuse- and outer-cloud dust. This fact shows that there are processes which operate over the entire distribution of grain sizes, and which change size distributions extremely efficiently. There is no evidence for mantles on grains in local diffuse and outer-cloud dust. The only published spectra of the star VI Cyg 12, the best candidate for showing mantles, does not show the 3.4 micro-m band which appreciable mantles would produce. Grains are larger in outer-cloud dust than diffuse dust because of coagulation, not accretion of extensive mantles. Core-mantle grains favored by J. M. Greenberg and collaborators, and composite grains of Mathis and Whiffen (1989), are discussed more extensively (naturally, I prefer the latter). The composite grains are fluffy and consist of silicates, amorphous carbon, and some graphite in the same grain. Grains deep within molecular clouds but before any processing within the solar system are presumably formed from the accretion of icy mantles on and within the coagulated outer-cloud grains. They should contain a mineral/carbonaceous matrix, without organic refractory mantles, in between the ices. Unfortunately, they may be significantly processed by chemical processes accompanying the warming (over the 10 K of the dark cloud cores) which occurs in the outer solar system. Evidence of this processing is the chemical anomalies present in interplanetary dust particles collected in the stratosphere, which may be the most primitive materials we have obtained to date. The comet return mission would greatly clarify the situation, and probably provide samples of genuine interstellar grains.

Mathis, John S.↗
DOE OSTI2027

Hydrotreating pine-derived catalytic fast pyrolysis oil to jet fuel: Process durability and impact of operating conditions

Hydrotreating woody biomass-derived catalytic fast pyrolysis (CFP) oil to jet fuel has the potential to enhance energy security due to the large abundance of forest and woody resources. CFP oil produced from pine over ZSM-5 was hydrotreated over sulfided NiMo/Al 2 O 3 for 410 h to study the impact of hydrotreating conditions (pressure, temperature, and weight hourly space velocity (WHSV)). The degree of deoxygenation remained high across the tested hydrotreating conditions, and the products contained < 0.01 wt% oxygen. Increasing hydrotreating pressure from 84 to 125 bar enhanced hydrogenation of aromatic rings and the formation of cycloalkanes and increasing the temperature from 385 to 400 degrees C enhanced cracking and the formation of jet-range molecules. Decreasing the weight hourly space velocity from 0.2 to 0.1 g/(g cat h) further enhanced cracking and led to higher gasoline- and lower jet fuel-range fractions. The highest jet fuel fraction (49 wt%) was obtained at 400 degrees C, 125 bar, 0.2 g/(g cat h) WHSV. CFP oils produced from pine over phosphorous-modified ZSM-5 were hydrotreated at this condition for 588 h to investigate the process durability. The hydrogenation performance of the catalyst gradually stabilized in approximately 300 h after which the product composition remained constant. Of the final hydrotreated CFP oil, 53 wt% fell in the jet fuel range with most of the tested fuel properties meeting ASTM D4054 and/or ASTM D7566 specifications. The freeze points were < -50 degrees C vs. guideline of < -40 degrees C and the viscosities at -20 degrees C were 3.8-4.1 mm 2 /s vs guideline of 8 mm 2 /s. Increasing the fraction of cycloalkanes could increase the cetane number and heating value, which did not meet the guidelines.

09 BIOMASS FUELS↗
NASA NTRS2008

Automated and Adaptive Mission Planning for Orbital Express

The Orbital Express space mission was a Defense Advanced Research Projects Agency (DARPA) lead demonstration of on-orbit satellite servicing scenarios, autonomous rendezvous, fluid transfers of hydrazine propellant, and robotic arm transfers of Orbital Replacement Unit (ORU) components. Boeing's Autonomous Space Transport Robotic Operations (ASTRO) vehicle provided the servicing to the Ball Aerospace's Next Generation Serviceable Satellite (NextSat) client. For communication opportunities, operations used the high-bandwidth ground-based Air Force Satellite Control Network (AFSCN) along with the relatively low-bandwidth GEO-Synchronous space-borne Tracking and Data Relay Satellite System (TDRSS) network. Mission operations were conducted out of the RDT&E Support Complex (RSC) at the Kirtland Air Force Base in New Mexico. All mission objectives were met successfully: The first of several autonomous rendezvous was demonstrated on May 5, 2007; autonomous free-flyer capture was demonstrated on June 22, 2007; the fluid and ORU transfers throughout the mission were successful. Planning operations for the mission were conducted by a team of personnel including Flight Directors, who were responsible for verifying the steps and contacts within the procedures, the Rendezvous Planners who would compute the locations and visibilities of the spacecraft, the Scenario Resource Planners (SRPs), who were concerned with assignment of communications windows, monitoring of resources, and sending commands to the ASTRO spacecraft, and the Mission planners who would interface with the real-time operations environment, process planning products and coordinate activities with the SRP. The SRP position was staffed by JPL personnel who used the Automated Scheduling and Planning ENvironment (ASPEN) to model and enforce mission and satellite constraints. The lifecycle of a plan began three weeks outside its execution on-board. During the planning timeframe, many aspects could change the plan, causing the need for re-planning. These variable factors, ranging from shifting contact times to ground-station closures and required maintenance times, are discussed along with the flexibility of the ASPEN tool to accommodate changes to procedures and the daily or long-range plan, which contributed to the success of the mission. This paper will present an introduction to ASPEN, a more in-depth discussion on its use on the Orbital Express mission, and other relative work. A description of ground operations after the SRP deliveries were made is included, and we briefly discuss lessons learned from the planning perspective and future work.

scheduling↗
DOE OSTI2023

Sustainable chemistry with plasmonic photocatalysts

There is a pressing global need to increase the use of renewable energy sources and limit greenhouse gas emissions. Towards this goal, highly efficient and molecularly selective chemical processes that operate under mild conditions are critical. Plasmonic photocatalysis uses optically resonant metallic nanoparticles and their resulting plasmonic, electronic, and phononic light-matter interactions to drive chemical reactions. The promise of simultaneous high-efficiency and product-selective reactions with plasmon photocatalysis provides a compelling opportunity to rethink how chemistry is achieved. Plasmonic nanoparticles serve as nanoscale ‘antennas’ that enable strong light–matter interactions, surpassing the light-harvesting capabilities one would expect purely from their size. Complex composite structures, combining engineered light harvesters with more chemically active components, are a focal point of current research endeavors. In this review, we provide an overview of recent advances in plasmonic catalysis. We start with a discussion of the relevant mechanisms in photochemical transformations and explain hot-carrier generation and distributions from several ubiquitous plasmonic antennae. Then we highlight three important types of catalytic processes for sustainable chemistry: ammonia synthesis, hydrogen production and CO 2 reduction. To help elucidate the reaction mechanism, both state-of-art electromagnetic calculations and quantum mechanistic calculations are discussed. This review provides insights to better understand the mechanism of plasmonic photocatalysis with a variety of metallic and composite nanostructures toward designing and controlling improved platforms for green chemistry in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning-Based Regression Models for Ironmaking Blast Furnace Automation

Computational fluid dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex industrial system that has benefited from CFD-based simulations is the steel blast furnace system. The problem with the CFD-based simulation approach is that it tends to be very slow for generating data. The CFD-only approach may not be fast enough for use in real-time decisionmaking. To address this issue, in this work, the authors propose the use of machine learning techniques to train and test models based on data generated via CFD simulation. Regression models based on neural networks are compared with tree-boosting models. In particular, several areas (tuyere, raceway, and shaft) of the blast furnace are modeled using these approaches. The results of the model training and testing are presented and discussed. The obtained R 2 metrics are, in general, very high. The results appear promising and may help to improve the efficiency of operator and process engineer decisionmaking when running a blast furnace.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

NASA's Unsteady Pressure-Sensitive Paint Research and Operational Capability Developments

In the last three years, several advancements have been made to produce a new state-of-the-art capability in the field of Aerosciences. NASA’s Aerosciences Evaluations and Test Capabilities (AETC) Portfolio Office has funded a multi-year project to produce the unsteady Pressure-Sensitive Paint (uPSP) technology as an operational capability in key ground test facilities at NASA. The research and development has primarily been conducted at NASA Ames Research Center’s (ARC) Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel (TWT). The NASA ARC UPWT is one of the ground test facilities under NASA AETC’s Portfolio Office. AETC’s goals are to provide the tools to deliver the technology innovations and breakthroughs necessary to address increasingly complex research and development challenges. AETC’s integrated approach will consider the complimentary high-end compute capabilities necessary to advance analysis in conjunction with ground experimental capabilities. The uPSP Capability Challenge Project is a demonstration of several different technologies: 1) the unsteady Pressure-Sensitive Paint (uPSP) technology, and 2) Project: Red Rover, establishing a secure, reliable, fast connection between experimental and computation facilities, leveraging NASA’s computational resources within the High-End Compute Capability (HECC) Project for processing, storing, and sharing data efficiently. This project demonstrates the technical diversity and technical inclusion need to advance the field of Aerosciences. The approach to combine subject matter experts in experimental methods, optical methods, production wind tunnel testing, network engineering, high-end computing, signal processing, grid generation, and visualization while establishing the required infrastructure for subject matter experts to have access to the data while the wind tunnel test is being conducted. The most recent advancements for the uPSP technology have focused on three key areas: development of data products, robust processing pipeline, operational efficiencies and uncertainty quantification.

buffet↗
DOE OSTI2022

Can a Nuclear-Assisted Biofuels System Enable Liquid Biofuels as the Economic Low-carbon Replacement for All Liquid Fossil Fuels and Hydrocarbon Feedstocks and Enable Negative Carbon Emissions?

This report integrates the results of a series of studies and workshops to address the question: Can a nuclear-assisted biofuels system enable liquid biofuels as the economic low-carbon replacement for all liquid fossil fuels and hydrocarbon feedstocks and simultaneously enable negative carbon emissions? “Economic” is defined as economically competitive relative to other low-carbon replacement options for crude oil. “All” refers to the capability to replace the 18 million barrels of oil per day used by the United States. “Nuclear-assisted” refers to the provision of massive quantities of low-carbon heat and hydrogen at the refinery to fully utilize the carbon content of the cellulosic biomass feedstocks for liquid hydrocarbon production. A system is proposed that decarbonizes about half of the U.S. economy while improving long-term soil productivity and sequestering carbon from the atmosphere. In the U.S. almost half the energy consumed by the final customer is in the form of liquid hydrocarbons produced from crude oil. Liquid hydrocarbons are used as (1) an energy source, (2) a method for daily-to-seasonal energy storage, (3) a chemical feedstock, (4) a chemical reducing agent, (5) a method to enhance high-temperature heat transfer in many furnaces and industrial processes and (6) other purposes. As a consequence, the U.S. consumes ~18 million barrels of crude oil per day to produce liquid hydrocarbons. While there are substitutes for liquid hydrocarbons for some applications, our assessment is that the costs and difficulty will dramatically increase if liquid hydrocarbon use goes much below the equivalent of 10 million barrels per day of crude oil. New uses of liquid hydrocarbons to partly replace coal and natural gas could increase demand beyond the equivalent of 10 million barrels of oil per day. One can produce and burn liquid hydrocarbons from biomass without any net addition of carbon dioxide to the atmosphere. Plants grow by removing carbon dioxide from the atmosphere; thus, burning biomass does not result in any net addition of carbon dioxide to the atmosphere. Biomass is typically 40% oxygen. To remove this oxygen to create hydrocarbon liquids, there are two options. The first option is to use biomass as (1) a feedstock, (2) an energy source to operate the process and (3) a supply of carbon to remove the biomass oxygen as carbon dioxide. The second option is to use external heat and hydrogen to remove the oxygen as water and produce liquid hydrocarbons. The use of massive quantities of external heat and hydrogen for hydrocarbon liquid fuels production reduces the biomass feedstock per unit of liquid hydrocarbon product by more than a factor of two reducing land use by more than a factor of two. Many cellulosic feedstocks unsuitable for liquid hydrocarbon production are viable feedstocks with external heat and hydrogen inputs. As a result, there is sufficient cellulosic feedstocks to meet U.S. and global liquid fuels hydrocarbon demand without significant impacts on food and fiber prices. The heat and hydrogen (heat plus electricity) are produced using base-load nuclear power plants—the most economic form of nuclear energy. If low-price natural gas, there is also the option of producing hydrogen from natural gas with sequestration of the carbon dioxide. The biomass is locally processed in depots to produce commodity feedstocks that can be shipped long distances to large biorefineries (250,000 barrels per day, oil equivalent) similar to existing refineries except modifications of front-end processes. The depot system enables local recycle of nutrients back to the soil. The biorefinery can produce variable quantities of liquid hydrocarbon fuels and carbon dioxide for sequestration enabling removal of carbon dioxide from the atmosphere. Preliminary estimates are that the liquid hydrocarbon costs are equivalent to crude oil at between $60 and $70 per barrel. The largest cost is for hydrogen with biomass feedstocks and refinery costs a smaller fraction of the total cost.

09 BIOMASS FUELS↗
NASA NTRS1990

Test plan pressure fed thrust chamber technology

Aerojet is developing the technology for the design of a reliable, low cost, efficient, and lightweight LOX/RP-1 pressure fed engine. This technology program is a direct result of Aerojet's liquid rocket booster (LRB) study and previous NASA studies that identified liquid engines using high bulk density hydrocarbon fuels as very attractive for a space transportation system (STS). Previous large thrust LOX/RP-1 engine development programs were characterized by costly development problems due to combustion instability damage. The combustion stability solution was typically obtained through trial and error methods of minimizing instability damage by degrading engine performance. The approach to this program was to utilize existing and newly developed combustion analysis models and design methodology to create a thrust chamber design with features having the potential of producing reliable and efficient operation. This process resulted in an engine design with a unique high thrust-per-element OFO triplet injector utilizing a low cost modular approach. Cost efficient ablative materials are baselined for the injector face and chamber. Technology demonstration will be accomplished through a hot fire test program using appropriately sized subscale hardware. This subscale testing will provide a data base to supplement the current industry data bank and to anchor and validate the applied analysis models and design methodology. Once anchored and validated, these analysis models and design methodology can be applied with greatly increased confidence to design and characterize a large scale pressure fed LOX/RP-1 thrust chamber. The objective of this test program is to generate a data base that can be used to anchor and validate existing analysis models and design methodologies and to provide early concept demonstration of a low cost, efficient LOX/RP-1 thrust chamber. Test conditions and hardware instrumentation were defined to provide data sufficient to characterize combustion stability, performance, and thermal operation over a wide thrust chamber throttling range.

Dunn, Glenn↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2009

Power Sources for Micro-Autonomous Vehicles- Challenges and Prospects

Micro-autonomous vehicle systems are expected to have expanded role in military missions by providing full spectrum intelligence, surveillance and reconnaissance support on the battlefield, suppression of enemy defenses, and enabling co-operative (swarm-like) configurations. Of the numerous demanding requirements of autonomy, sensing, navigation, mobility, etc., meeting the requirement of mission duration or endurance is a very challenging one. This requirement is demanding because of the constraints of mass and volume that limit the quantity of energy that can be stored on-board. Energy is required for mobility, payload operation, information processing, and communication. Mobility requirements typically place an extraordinary demand on the specific energy (Wh/kg) and specific power (W/kg) of the power source; the actual distribution of the energy between mobility and other system functions could vary substantially with the mission type. The power requirements for continuous mobility can vary from 100-1000 W/kg depending on the terrain, ground speed and flight speed. Even with the power source accounting for 30% of the mass of the vehicle, the best of rechargeable batteries can provide only up to 1-2 hours of run-time for a continuous power demand at 100W/kg. In the case of micro-aerial vehicles with flight speed requirements in the range of 5-15 m s-1, the mission times rarely exceed 20 minutes [2]. Further, the power required during take-off and hover can be twice or thrice that needed for steady level flight, and thus the number and sequence of such events is also limited by the mass and size of the power source. For operations such as "perch and stare" or "silent watch" the power demand is often only a tenth of that required during continuous flight. Thus, variation in power demand during various phases of the mission importantly affects the power source selection.

fuel cells↗
DOE OSTI2020

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Finally, future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

Verification↗
NASA NTRSDate not supplied

Characterization of Structural Vibration and Acoustic Radiation with a Beam-Array Doppler Vibrometer

This paper discusses the operational principles of an assembly of two opto-electronic modules with their configurations based on a Laser-Array Doppler Vibrometer (LADV) and a Shack-Hartmann Wavefront Sensor (SHWFS). Both sensors can operate concurrently providing complementary data. While the SHWFS is a well-established system that enables low-bandwidth spatio-temporal characterization of aerodynamic turbulence, the LADV technology allows real-time detection of structural vibrations and associated acoustic radiation fields. Practical examples are shown of the instruments’ capabilities, focusing on the ability to simultaneously capture, visualize and quantitatively characterize full-field non-stationary structural dynamics and unsteady sound fields or transient flow fields around ground test facility airframe models or other structures of interest. The parallel multi-channel architecture of the LADV system enables synchronous detection and temporal correlation of indicators related to the spatio-temporal vibration of the structure under inspection. This unique feature is essential for real time detection and categorization of the structural and acoustic dynamics of transient events. For the present study, the LADV data have been successfully compared with measurements obtained with the SHWFS in the wake of a subsonic scale-model airfoil. The ability of the LADV-SHWFS coupled measurements to perform real time non-intrusive evaluation and characterization of dynamic processes at operationally relevant bandwidths should provide a deeper insight into the complex structural dynamics that contribute to radiated sound fields.

Vladimir B Markov↗