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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Advancing Precipitation Estimation, Prediction, and Impact Studies

Precipitation exhibits a large variability over a wide range of space and time scales: from seconds to years and decades in time; from the millimeter scale of microphysical processes to regional and global scales in space. It also exhibits a large variability in magnitude and frequency, from low extremes resulting in prolonged droughts to high extremes resulting in devastating floods. Improving precipitation estimation and prediction has great societal impact for decision support in water resources management, infrastructure protection and design under accelerating climate extremes, quantifying water and energy balances at the regional to global scales, and predicting hurricanes, tornadoes, floods and droughts that affect the economy and security around the world (e.g., Blunden and Arndt, 2019). Yet, despite significant advances in observations and physical understanding, precipitation still remains one of the most challenging variables to model and predict at local, regional and global scales with significant implications for our ability to quantify water and energy cycle dynamics, inform decision making, and predict hydro-geomorphic hazards in response to precipitation extremes (e.g. Maggioni and Massari, 2019).

Efi Foufoula-Georgiou↗
NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗
NASA NTRSDate not supplied

Updates on the Predictive Materials Modeling Software Tools

Updates on NASA‘s efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. The PMM effort is part of the Entry Systems Modeling (ESM) project under NASA’s Game Changing Development (GCD) program. To reduce the need for extensive testing and accelerate the design cycle process, ESM is developing simulation and modeling tools that enable the characterization of the properties of thermal protection materials and their response to extremely hot plasma. The Porous Microstructure Analysis (PuMA) software has been developed to compute effective material properties and perform material response simulations on digitized microstructures of porous media. PuMA is able to import three-dimensional digital images obtained from X-ray microtomography or to generate artificial microstructures that mimic real materials. PuMA also provides a module for interactive 3D visualizations. Version 3, which was recently released as open-source, includes modules to compute simple morphological properties such as porosity, volume fractions, pore diameter, and specific surface area. Additional capabilities include the determination of effective thermal and electrical conductivity (both radiative and solid conduction - including the ability to simulate local anisotropy for the latter); effective diffusivity and tortuosity from the continuum to the rarefied regime; techniques to determine the local material orientation, as well as mechanical properties (elasticity coefficients), and permeability. Computed properties are then used to inform a macro-scale material response model, such as those implemented in the Porous material Analysis Toolbox based on OpenFOAM (PATO) software developed within ESM. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale, assuming Local Thermal Equilibrium. Recent efforts include the development of a mechanical erosion model as well as a unified model allowing an intrinsic coupling between fluid and material. Comparison to flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI] and Mars 2020 MEDLI2) is critical in order to validate these computational tools. Examples of ablative material response using the code will be presented, including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrated the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains through the use of massively parallel computations.

material modeling↗
NASA NTRS2022

Orbiting Laser Configuration and Sky Coverage: Coherent Reference for Breakthrough Starshot Ground-based Laser Array

We present the concept of using an orbiting laser as a coherent optical reference to phase a several kilometer diameter array of ground-based lasers designed to accelerate interstellar nano-spacecraft to 20% light-speed using laser propulsion. We investigate the geometrical and temporal constraints for the initial case of the target star Proxima b in the Alpha Centauri system using a laser ground site in the southern hemisphere. Based on these constraints, we detail requirements for the mission architecture for an orbiting laser to be used as an optical reference. We then present two orbits that can meet all given requirements and represent a range of engagement times and days between engagements. We also present a range of orbits with periods from 3 to 4 days and engagement times from 660 to 800 s. If desired, the orbit can be matched to the sidereal day, so each orbit period, the beacon can align with the ground station and the same target star without maneuvers. A discussion of the tradeoff between the Earth-based site latitude, time on engagement, and days between engagements is presented.

Breakthrough Starshot; interstellar spacecraft; co↗
NASA NTRSDate not supplied

MOC Automation with GMSEC and the Generic Extendable Message Utility (GEMU)

Automation has become critical for ground systems, improving efficiency and reliability while reducing costs across mission operations. The Goddard Mission Services Evolution Center (GMSEC) software suite has played a significant role in enabling this automation, leveraging its publish/subscribe paradigm through a message bus architecture to facilitate seamless communication and data flow. Historically, the GMSEC suite, through components like Criteria Action Table (CAT) has been pivotal in automating ground system capabilities. However, as technology advances, limitations in automation with CAT have emerged, creating an opportunity to enhance ground system automation through the introduction of GEMU. This new GMSEC component brings new capabilities and addresses specific automation constraints that CAT could not overcome, allowing for more sophisticated, flexible, and efficient message processing. GEMU, at its core, is designed to accelerate the development of custom GMSEC-compliant applications. It enables users to construct automated message processing pipelines quickly, supporting both drag-and-drop web-based configuration and scripting through a simple domain-specific language. This advancement not only simplifies the process but also reduces the time needed for implementing automated solutions. This presentation will outline GEMU’s potential value in improving mission operations automation. It will highlight the benefits of transitioning from CAT to GEMU and offer insights into how GEMU can drive operational efficiencies. We will also provide an overview of the automation capabilities of GEMU and its potential impact on mission operations centers (MOCs).

GMSEC↗
DOE OSTI2024

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Forced RF generation of CW magnetrons for superconducting accelerators

CW magnetrons, designed and optimized for industrial RF heaters, were suggested to power Superconducting RF cavities due to their higher efficiency and lower cost than traditional klystrons, IOT’s, or solid-state amplifiers. RF amplifiers driven by a master-oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. Very large regenerative gain causes instability with intense noise when a magnetron operates with the anode voltage higher than the threshold of self-excitation. Traditionally for stabilization of magnetrons is used injection-locking by a quite small signal. In this case the CW magnetrons do not provide correlation of the magnetron startup with the injection-locking signal. Thus, the magnetron except the injection locked oscillations may generate large noise. This may increase emittance of the beam in SRF accelerators. Recently we have developed mode for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The mode is most suitable for SRF accelerators. The mode is briefly described below.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗
NASA NTRS2007

Wavefront Sensing With Switched Lenses for Defocus Diversity

In an alternative hardware design for an apparatus used in image-based wavefront sensing, defocus diversity is introduced by means of fixed lenses that are mounted in a filter wheel (see figure) so that they can be alternately switched into a position in front of the focal plane of an electronic camera recording the image formed by the optical system under test. [The terms image-based, wavefront sensing, and defocus diversity are defined in the first of the three immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] Each lens in the filter wheel is designed so that the optical effect of placing it at the assigned position is equivalent to the optical effect of translating the camera a specified defocus distance along the optical axis. Heretofore, defocus diversity has been obtained by translating the imaging camera along the optical axis to various defocus positions. Because data must be taken at multiple, accurately measured defocus positions, it is necessary to mount the camera on a precise translation stage that must be calibrated for each defocus position and/or to use an optical encoder for measurement and feedback control of the defocus positions. Additional latency is introduced into the wavefront sensing process as the camera is translated to the various defocus positions. Moreover, if the optical system under test has a large focal length, the required defocus values are large, making it necessary to use a correspondingly bulky translation stage. By eliminating the need for translation of the camera, the alternative design simplifies and accelerates the wavefront-sensing process. This design is cost-effective in that the filterwheel/lens mechanism can be built from commercial catalog components. After initial calibration of the defocus value of each lens, a selected defocus value is introduced by simply rotating the filter wheel to place the corresponding lens in front of the camera. The rotation of the wheel can be automated by use of a motor drive, and further calibration is not necessary. Because a camera-translation stage is no longer needed, the size of the overall apparatus can be correspondingly reduced.

Dean, Bruce H.↗
NASA NTRS1961

Design and Flight Tests of an Adaptive Control System Employing Normal-Acceleration Command

An adaptive control system employing normal-acceleration command has been designed with the aid of an analog computer and has been flight tested. The design of the system was based on the concept of using a mathematical model in combination with a high gain and a limiter. The study was undertaken to investigate the application of a system of this type to the task of maintaining nearly constant dynamic longitudinal response of a piloted airplane over the flight envelope without relying on air data measurements for gain adjustment. The range of flight conditions investigated was between Mach numbers of 0.36 and 1.15 and altitudes of 10,000 and 40,000 feet. The final adaptive system configuration was derived from analog computer tests, in which the physical airplane control system and much of the control circuitry were included in the loop. The method employed to generate the feedback signals resulted in a model whose characteristics varied somewhat with changes in flight condition. Flight results showed that the system limited the variation in longitudinal natural frequency of the adaptive airplane to about half that of the basic airplane and that, for the subsonic cases, the damping ratio was maintained between 0.56 and 0.69. The system also automatically compensated for the transonic trim change. Objectionable features of the system were an exaggerated sensitivity of pitch attitude to gust disturbances, abnormally large pitch attitude response for a given pilot input at low speeds, and an initial delay in normal-acceleration response to pilot control at all flight conditions. The adaptive system chatter of +/-0.05 to +/-0.10 of elevon at about 9 cycles per second (resulting in a maximum airplane normal-acceleration response of from +/-0.025 g to +/- 0.035 g) was considered by the pilots to be mildly objectionable but tolerable.

McNeill, Water E.↗
NASA NTRS2002

The Role of Formal Experiment Design in Hypersonic Flight System Technology Development

Hypersonic airbreathing engine (scramjet) powered vehicles are being considered to replace conventional rocket-powered launch systems. Effective utilization of scramjet engines requires careful integration with the air vehicle. This integration synergistically combines aerodynamic forces with propulsive cycle functions of the engine. Due to the highly integrated nature of the hypersonic vehicle design problem, the large flight envelope, and the large number of design variables, the use of a statistical design approach in design is effective. Modern Design-of-Experiments (MDOE) has been used throughout the Hyper-X program, for both systems analysis and experimental testing. Application of MDOE fall into four categories: (1) experimental testing; (2) studies of unit phenomena; (3) refining engine design; and (4) full vehicle system optimization. The MDOE process also provides analytical models, which are also used to document lessons learned, supplement low-level design tools, and accelerate future studies. This paper will discuss the design considerations for scramjet-powered vehicles, specifics of MDOE utilized for Hyper-X, and present highlights from the use of these MDOE methods within the Hyper-X Program.

McClinton, Charles R.↗
DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗
DOE OSTI2026

Exploring Causes of Beam Loss at CEBAF

At Jefferson Lab, the Continuous Electron Beam Accelerator (CEBAF) features a unique design with two linear accelerators and two arc sections allowing for multiple turns of the electron beam, as well as four experimental end stations. This topology leads to increased beam losses, especially in the spreader and recombiner regions connecting the arcs to the linacs and in the extraction regions connecting the experimental end stations to the accelerator. These losses result in equipment activation and operational interruptions. Recent upgrades to the facility’s diagnostic systems, including the addition of xenon ion chambers, have provided higher-resolution data regarding these loss events. Building on this improved observational capability, we are developing a simulation framework using optics codes and the Geant4-based BDSIM to model beam extinction and halo formation in these regions. This work aims to correlate simulation results with experimental data to isolate the causes of beam loss and inform future machine tuning strategies. We present a summary of conclusions drawn from recent operational studies and outline a plan to model the beam loss and validate the simulations.

Matthews, C. [Old Dominion Univ., Norfolk, VA (Uni↗
NASA NTRS2007

Deployable Landing Leg Concept for Crew Exploration Vehicle

The NASA Exploration program is investigating the merits of land landing concepts for the Crew Exploration Vehicle (CEV). Four options are under investigation: retro-rockets which fire and slow the vehicle before contact with the landing surface, deployable crushable material which deploys just before landing and crushes during land contact, airbags which deploy just before landing and deflate during land contact, and deployable legs which deploy before landing and contain material that absorbs energy during land contact. The purpose of the present work is to determine the effectiveness of the deployable leg concept. To accomplish this goal, structural models of the deployable leg concept are integrated with the Crew Model (CM) and computational simulations are performed to determine vehicle and component loadings and acceleration levels. Details of the modeling approach, deployable leg design, and resulting accelerations are provided.

Lawrence, Charles↗