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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Advanced Supersonic Parachute Inflation Research and Experiment-2 (ASPIRE2) Flight Mechanics Modeling and Simulation

Introduction: The Advanced Supersonic Para-chute Inflation Research Experiment-2 (ASPIRE2) program is a sounding rocket flight test to be conducted at Wallops Island, VA in early 2025. This program is a risk mitigation exercise for the Mars Sample Retrieval Lander (MSRL) program and builds upon the success of the 2017 & 2018 ASPIRE program, [1,2]. While the ASPIRE program certified the strengthened 21.5 m diameter disk-gap-band (DGB) deployed at Mach 1.7, ASPIRE2 will certify a 24 m diameter DGB deployed at Mach 2.1. The need to certify this increased parachute performance is driven the increased lander mass for MSRL; over 50% increase in comparison to M2020. Modeling: Like its predecessor, ASPIRE2 is developing a multi-body flight dynamics simulation to predict parachute dynamics and aide in designing the flight test that will target Mars-relevant flight conditions, as shown in Figure 1. This work de-scribes the parachute modeling, flight mechanics simulations (from payload separation to splash-down), and design trades used to prepare for the 2025 ASPIRE2 flight. Discussed herein are comparisons between ASPIRE and ASPIRE2, noting key differences in the parachute modeling and vehicle configuration. A study on the attitude control system performance impacts with respect to payload section design will also be presented. This work will quantify the pre-flight parachute performance in the presence of uncertainties, such as those associated with the separation from the sounding rocket, atmosphere, the parachute system, and vehicle mass. The pre-flight predictions will include Monte Carlo analyses, powered by the flight mechanics simulations to show the ASPIRE2 vehicle performance in meeting program requirements on parachute deployment conditions (Mach & dynamic pressure), parachute loads, vehicle attitude at key milestones, and the vehicle splashdown conditions.

Entry Descent and Landing↗
DOE OSTI2022

1.2.4.404 - Data-Driven Approach for Hydropower Plant Controller Prototyping Using Remote Hardware in the Loop (DR-HIL)

Real-time prototyping of hydropower plant controls is important for reducing the cost and the risk of field deployment. This project will 1) collect design and operational data from actual hydro plants and 2) use a physics-informed machine learning approach for real-time emulation of hydropower plants, including hydro turbine and hydrodynamics. The data-driven models will be interfaced with digital real-time simulation at NREL’s Flatirons campus for hardware-in-the-loop (HIL) testing of the governor hardware device or controller-HIL (CHIL). The proposed approach will also establish the connectivity based remote CHIL testing capability using real-time data streams from an actual hydro plant. This integrated hydro-plant emulation with CHIL will be used to prototype hydro-governor controls and eventually provide an opportunity to test hydropower integrated with various technologies (e.g. conventional and renewable generation, energy conversion, etc.) as HIL.

controls prototyping↗
DOE OSTI2026

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation induced reactions is therefore key to innovating and optimizing next generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct dissolution–based reprocessing strategies. We will explore time resolved electron pulse radiolysis and alpha and gamma dose accumulation studies, integrated with multiscale computational modeling, to elucidate the molecular level roles of radiation driven, non equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2021

Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements

Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.

PMU, noise emulation, synthetic measurements, deep↗
DOE OSTI2020

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services: Preprint

Flexible loads have great potential to improve the power grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. The paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environment impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

control↗
NASA NTRS2002

Rocket Engine Oscillation Diagnostics

Rocket engine oscillating data can reveal many physical phenomena ranging from unsteady flow and acoustics to rotordynamics and structural dynamics. Because of this, engine diagnostics based on oscillation data should employ both signal analysis and physical modeling. This paper describes an approach to rocket engine oscillation diagnostics, types of problems encountered, and example problems solved. Determination of design guidelines and environments (or loads) from oscillating phenomena is required during initial stages of rocket engine design, while the additional tasks of health monitoring, incipient failure detection, and anomaly diagnostics occur during engine development and operation. Oscillations in rocket engines are typically related to flow driven acoustics, flow excited structures, or rotational forces. Additional sources of oscillatory energy are combustion and cavitation. Included in the example problems is a sampling of signal analysis tools employed in diagnostics. The rocket engine hardware includes combustion devices, valves, turbopumps, and ducts. Simple models of an oscillating fluid system or structure can be constructed to estimate pertinent dynamic parameters governing the unsteady behavior of engine systems or components. In the example problems it is shown that simple physical modeling when combined with signal analysis can be successfully employed to diagnose complex rocket engine oscillatory phenomena.

Nesman, Tom↗
DOE OSTI2026

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the “dark complex,” modulate metabolic flux at a conserved regulatory node of the Calvin–Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.

Johnson, Connah G.↗
NASA NTRS1990

Design of a CO2 laser power control system for a Spacelab microgravity experiment

The surface tension driven convection experiment (STDCE) is a Space Transportation System flight experiment manifested to fly aboard the USML-1 Spacelab mission. A CO2 laser is used to heat a spot on the surface of silicone oil contained inside a test chamber. Several CO2 laser control systems were evaluated and the selected system will be interfaced with the balance of the experimental hardware to constitute a working engineering model. Descriptions and a discussion of these various design approaches are presented.

Wenzler, Carl J.↗
DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗
NASA NTRSDate not supplied

L2-Charged Particle Environment (L2-CPE)Low Energy Radiation Fluence Model

The L2 Charged Particle Environment (L2-CPE) model provides estimates of number flux and fluence for the low energy electron, proton, and alpha particle populations in the near Earth solar wind and the Earth’s distant magnetosheath and magnetotail. The model is an engineering tool for specifying radiation environments over an energy range from a few eV to a few MeV of importance to surface dose and radiation damage to thin space exposed materials and is intended for use in space system design applications. Mission fluences are obtained by simulating a spacecraft flight trajectory through time-dependent bow shock and magnetopause boundaries with dimensions and orientations driven by solar wind parameters. Monte Carlo sampling of flux environments within individual plasma regimes and/or fluence accumulated along a fight trajectory through multiple regimes is used to determine statistical variations (means and extremes) of the differential number flux and fluence environments for each of the three charged particle species. Model output is differential (in energy) number fluence and flux for the three particle species in units of particles/cm2-keV and particles/cm2-sec-keV, respectively. Users can select the energy range of interest but the current version of the code (L2-CPE Version 1.4.2d) is limited to an energy range of 1 eV to 10 MeV. Flux is integrated over angle to give flux and fluence to surfaces in the ±XGSE, ±YGSE, and/or ±ZGSE directions. Figure 1 shows the opening screen from the L2-CPE graphical user interface (GUI) with options for flux, fluence, plotting model output. The flux scene generate is not currently implemented in the GUI.

Joseph I Minow↗
DOE OSTI2026

Neural entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws

We propose a neural entropy-stable conservative flux form neural network (NESCFN) for learning hyperbolic conservation laws and their associated entropy functions directly from solution trajectories, without requiring any predefined numerical discretization. While recent neural network architectures have successfully integrated classical numerical principles into learned models, most rely on prior knowledge of the governing equations or assume a fixed discretization. Our approach removes this dependency by embedding entropy-stable design principles into the learning process itself, enabling the discovery of physically consistent dynamics in a fully data-driven setting. By jointly learning both the flux function and a corresponding entropy, NESCFN promotes conservation and entropy dissipation, which is critical for long-term stability and fidelity in the system of hyperbolic conservation laws. Furthermore, numerical results demonstrate that the method achieves stability and conservation over extended time horizons and accurately captures shock propagation speeds, even without oracle access to future-time solution profiles in the training data.

Conservative flux form↗
NASA NTRS1992

Space suits and life support systems for the exploration of Mars

The requirements and technologies needed for space suits to be used for the manned exploration of Mars are examined. Alternative concepts are proposed for both the space suit and the portable life support system (collectively called the Extravehicular Mobility Unit, or EMU) needed for Mars exploration. EMU system requirements are outlined. It is pointed out that the most fundamental difference between a Mars EMU and those that preceded it is that the design of a Mars EMU must be driven by science and permanent habitability requirements, while all prior EMU designs have been driven by engineering requirements. The EMU weight issues are discussed, and the system mass and mobility concerns are addressed, along with the backpack-to-body-weight ratio. The challenges of thermal and cosmic radiation protection, micrometeorite protection, and EMU system and crew heat rejection are dealt with briefly, as well as the physiological issues of pressure regulation and bacterial or contaminant isolation. A mathematical model is then presented for evaluation of candidate EMU designs and for concept optimization and selection. Lead technology issues are also discussed.

Kuznetz, Lawrence H.↗
DOE OSTI2026

Observation of Transition from Rate Law to Butler–Volmer Controlled Water Oxidation Kinetics on Hematite Photoanodes

Despite its central role in photoelectrochemical (PEC) water splitting, the mechanistic pathway of water oxidation on metal oxides remains unresolved, with population-based and Butler–Volmer (BV) models offering distinct views on how surface valence band holes drive the reaction. Here, we bring together these two perspectives by combining operando photoinduced absorption (PIA) spectroscopy with photocurrent analyses on α-Fe 2 O 3 (hematite) photoanodes as a function of light intensity. We find a crossover from population-controlled, rate law water oxidation at low hole densities to a BV-like, potential driven regime at high densities, triggered by band edge unpinning once surface M–OH species are fully oxidized, and excess holes accumulate without compensation. This mechanistic transition unifies competing models of interfacial charge transfer and reveals design principles for optimizing water oxidation in metal oxide photoelectrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effect of Glacial/Interglacial Recharge Conditions on Flow of Meteoric Water Through Deep Orogenic Faults: Insights Into the Geothermal System at Grimsel Pass, Switzerland

Many meteoric-recharged, fault-hosted geothermal systems in amagmatic orogenic belts have been active through the Pleistocene glacial/interglacial climate fluctuations. The effects of such climate-induced recharge variations on fluid flow patterns and residence times of the thermal waters are complex and may influence how the geothermal and mineralization potential of the systems are evaluated. We report systematic thermal–hydraulic simulations designed to reveal the effects of recharge variations, using a model patterned on the orogenic geothermal system at Grimsel Pass in the Swiss Alps. Fault-bound circulation of meteoric water through the Grimsel fault is driven to depths of ~10 km by the high alpine topography. Simulations suggest that the current single pass flow is typical of interglacial periods, during which 1) meteoric recharge into the fault is high (above tens of centimeters per year), 2) conditions are at or somewhat below the critical Rayleigh number, and 3) the hydraulic connectivity along the fault plane is extensive (an extent of at least 10 km into increasingly higher terrain is required to explain the 10 km penetration depth). The subcritical condition constrains the bulk fault permeability to < 1e-14 m2. In contrast, the limited recharge during the numerous Pleistocene glaciation events likely induced a layered flow system with single pass flow confined to shallow depths while non-Rayleigh convection occurred in the deep fault. The same layering can be observed at low aspect ratios (length/depth) of the fault plane, when the available recharge area limits the flux through the fault.

58 GEOSCIENCES↗
DOE OSTI2023

Quick Talk: Resilient Communities, Maryland

Groundswell, Inc., in partnership with the Maryland Energy Administration (MEA), Ayika Solutions, the National Renewable Energy Lab (NREL), and the Baltimore Office of Sustainability, is advancing a vision for resilient, community-centered energy systems in Maryland. This effort aligns with Groundswell's commitment to a clean energy economy that equitably benefits all communities, closing gaps in representation, wages, and access to wealth generation, savings, and local jobs within a diverse energy supply chain. Project Vision and Objectives The project emphasizes "energy resilience," defined as a community’s capacity to anticipate, adapt to, and swiftly recover from power disruptions through inclusive planning and technical solutions. The approach centers on Resilience Hubs—designated community facilities equipped to support residents before, during, and after power-related disruptions. These hubs offer emergency resources, coordinate communications, and deliver essential services while reducing carbon emissions, ultimately enhancing residents' quality of life. Additionally, Resilience Hubs foster social connections, support disaster preparedness, and provide spaces for community programming and everyday use. The goals of Resilient Communities Maryland include: Developing a replicable framework for community energy resilience, applicable beyond Maryland. Defining community-led indicators of social impact and resilience. Establishing equitable decision-making processes in project design and implementation. Informing MEA of practical, community-based resilience strategies to shape future state initiatives. Approach Groundswell and its partners prioritize collaborative engagement with local stakeholders, ensuring that solutions are responsive to each community's unique needs. By integrating feedback from residents, local organizations, and government entities, the team has developed a holistic model for resilience that balances immediate benefits, such as improved emergency response, with long-term gains in social equity and environmental sustainability. Key Outcomes This initiative has produced valuable resources and insights, including: A Community Energy Resilience Framework: Designed to guide other communities in establishing energy resilience strategies tailored to their specific needs. Case Studies: Documenting best practices and lessons learned from pilot projects to serve as models for future resilience efforts. Community-Driven Impact Metrics: Highlighting the positive social impacts that resilience initiatives can bring, such as improved social connectedness and local decision-making power. Recommendations for MEA: Offering evidence-based insights to inform policies and funding opportunities that support resilient energy infrastructure in vulnerable communities. Next Steps Groundswell's final report will detail findings, including the potential for scaling resilience hubs across Maryland and other regions, with a focus on equitable access and community-driven outcomes. This project underscores the importance of aligning energy resilience with social equity, reinforcing community agency, and building systems that withstand and recover from future challenges effectively and sustainably.

14 SOLAR ENERGY↗
DOE OSTI2024

Cable-Driven Parallel Robot (CDPR) for Panelized Envelope Retrofits: Feasible Workspace Analysis

Recent decades have seen remarkable progress in the field of robotic-assisted construction. Cable-driven parallel robots (CDPRs) emerge as promising tools for automating construction processes, due to their advantageous features such as scalability, reconfigurability, compact design, and high payload-to-weight ratio. This paper uses a simple static model to determine the feasibility of a CDPR for overclad panel installation in building envelope retrofits. Given that the building facade needs to be a subset of the CDPR’s wrench-feasible workspace, we focus on the sensitivity of the workspace concerning various cable arrangements and CDPR frame sizes (e.g., height and width extensions). Our analysis indicates that no cable arrangement satisfies the requirement of complete facade coverage and avoids cable-to-panel collisions. Thus, frame extension is needed to enhance coverage. However, in densely populated areas where width extension is limited by space constraints, height extension alone is insufficient to guarantee full facade coverage. This paper pioneers the investigation of CDPRs for panelized envelope retrofits, showcasing their advantages and limitations and paving the way for further research and development.

Liu, Yifang↗
NASA NTRS1986

Implementation of and Ada real-time executive: A case study

Current Ada language implementations and runtime environments are immature, unproven and are a key risk area for real-time embedded computer system (ECS). A test-case environment is provided in which the concerns of the real-time, ECS community are addressed. A priority driven executive is selected to be implemented in the Ada programming language. The model selected is representative of real-time executives tailored for embedded systems used missile, spacecraft, and avionics applications. An Ada-based design methodology is utilized, and two designs are considered. The first of these designs requires the use of vendor supplied runtime and tasking support. An alternative high-level design is also considered for an implementation requiring no vendor supplied runtime or tasking support. The former approach is carried through to implementation.

Laird, James D.↗
NASA NTRS1987

Electronic prototyping

The potential benefits of automation in space are significant. The science base needed to support this automation not only will help control costs and reduce lead-time in the earth-based design and construction of space stations, but also will advance the nation's capability for computer design, simulation, testing, and debugging of sophisticated objects electronically. Progress in automation will require the ability to electronically represent, reason about, and manipulate objects. Discussed here is the development of representations, languages, editors, and model-driven simulation systems to support electronic prototyping. In particular, it identifies areas where basic research is needed before further progress can be made.

Hopcroft, J.↗