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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 757 records · Page 42

LightForce: An Update on Orbital Collision Avoidance Using Photon Pressure

We present an update on our research on collision avoidance using photon-pressure induced by ground-based lasers. In the past, we have shown the general feasibility of employing small orbit perturbations, induced by photon pressure from ground-based laser illumination, for collision avoidance in space. Possible applications would be protecting space assets from impacts with debris and stabilizing the orbital debris environment. Focusing on collision avoidance rather than de-orbit, the scheme avoids some of the security and liability implications of active debris removal, and requires less sophisticated hardware than laser ablation. In earlier research we concluded that one ground based system consisting of a 10 kW class laser, directed by a 1.5 m telescope with adaptive optics, could avoid a significant fraction of debris-debris collisions in low Earth orbit. This paper describes our recent efforts, which include refining our original analysis, employing higher fidelity simulations and performing experimental tracking tests. We investigate the efficacy of one or more laser ground stations for debris-debris collision avoidance and satellite protection using simulations to investigate multiple case studies. The approach includes modeling of laser beam propagation through the atmosphere, the debris environment (including actual trajectories and physical parameters), laser facility operations, and simulations of the resulting photon pressure. We also present the results of experimental laser debris tracking tests. These tests track potential targets of a first technical demonstration and quantify the achievable tracking performance.

Stupl, Jan↗

Simulation of Dust-Laden Flow in the DLR L2K Facility

An integrated CFD-particle trajectory code called US3D-DUST is used to simulate the dusty flow environments performed in the German Aerospace Center (DLR) L2K arcjet facility. The particle trajectory code uses a Lagrangian approach, where the particle trajectories through the shock layer can be computed using a set of coupled ordinary differential equations. The L2K experiments measured mass loss to flat-face shaped samples of the Norcoat-Liège thermal protection system material. The US3D-DUST simulations were able to reproduce particle velocity and stagnation point heating rate data. When applied to the L2K dusty flow conditions, the US3D-DUST predictions of mass loss due to particle impacts and surface recession rates over-predicted the experimental values. It is recommended to perform additional dusty flow tests in the L2Kto provide and improve the surface damage model for Norcoat-Liège.

Thermal protection systems↗

Theoretical Tools and Software for Modeling, Simulation and Control Design of Rocket Test Facilities

A rocket test stand and associated subsystems are complex devices whose operation requires that certain preparatory calculations be carried out before a test. In addition, real-time control calculations must be performed during the test, and further calculations are carried out after a test is completed. The latter may be required in order to evaluate if a particular test conformed to specifications. These calculations are used to set valve positions, pressure setpoints, control gains and other operating parameters so that a desired system behavior is obtained and the test can be successfully carried out. Currently, calculations are made in an ad-hoc fashion and involve trial-and-error procedures that may involve activating the system with the sole purpose of finding the correct parameter settings. The goals of this project are to develop mathematical models, control methodologies and associated simulation environments to provide a systematic and comprehensive prediction and real-time control capability. The models and controller designs are expected to be useful in two respects: 1) As a design tool, a model is the only way to determine the effects of design choices without building a prototype, which is, in the context of rocket test stands, impracticable; 2) As a prediction and tuning tool, a good model allows to set system parameters off-line, so that the expected system response conforms to specifications. This includes the setting of physical parameters, such as valve positions, and the configuration and tuning of any feedback controllers in the loop.

Richter, Hanz↗

The AEDC aerospace chamber 7V: An advanced test capability for infrared surveillance and seeker sensors

An advanced sensor test capability is now operational at the Air Force Arnold Engineering Development Center (AEDC) for calibration and performance characterization of infrared sensors. This facility, known as the 7V, is part of a broad range of test capabilities under development at AEDC to provide complete ground test support to the sensor community for large-aperture surveillance sensors and kinetic kill interceptors. The 7V is a state-of-the-art cryo/vacuum facility providing calibration and mission simulation against space backgrounds. Key features of the facility include high-fidelity scene simulation with precision track accuracy and in-situ target monitoring, diffraction limited optical system, NIST traceable broadband and spectral radiometric calibration, outstanding jitter control, environmental systems for 20 K, high-vacuum, low-background simulation, and an advanced data acquisition system.

Simpson, W. R.↗

Mach 6 Integrated Systems Tests of Lewis' Hypersonic Tunnel Facility

A series of 15 integrated systems tests were conducted at the NASA Lewis Research Center's Hypersonic Tunnel Facility (HTF) with test conditions simulating flight up to Mach 6. Facility stagnation conditions up to 3050 R and 1050 psia were obtained with typical test times of 20 to 45 sec.

Source record↗

A PC-based collapse factor analysis for high pressure cryogenic systems

A collapse factor simulation computer program, suitable for use on personal computers, for supercritical cryogen system pressurization is examined. The available literature is previewed, individual component models are developed, and the overall simulation program logic is examined. Extensive use is made of existing thermodynamic and transport property evaluation packages. Heat transfer is estimated using natural convection correlations, and transient wall heat conduction is considered. Examples of the simulation are demonstrated for two facilities. Partial validation is achieved by comparing the simulation output with data from an existing test facility. Preliminary results indicate that the collapse factors will seldom exceed 1.15 during supercritical operation of high-pressure cryogenic systems. Recommendations for improvements in the component models and the simulation are made.

Hodge, B. K.↗

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗

Numerical simulation of tornado wind loading on structures

A numerical simulation of a tornado interacting with a building was undertaken in order to compare the pressures due to a rotational unsteady wind with that due to steady straight winds used in design of nuclear facilities. The numerical simulations were performed on a two-dimensional compressible hydrodynamics code. Calculated pressure profiles for a typical building were then subjected to a tornado wind field and the results were compared with current quasisteady design calculations. The analysis indicates that current design practices are conservative.

Maiden, D. E.↗

Research and development at the Marshall Space Flight Center Neutral Buoyancy Simulator

The Neutral Buoyancy Simulator (NBS), a facility designed to imitate zero-gravity conditions, was used to test the Experimental Assembly of Structures in Extravehicular Activity (EASE) and the Assembly Concept for Construction of Erectable Space Structures (ACCESS). Neutral Buoyancy Simulator applications and operations; early space structure research; development of the EASE/ACCESS experiments; and improvement of NBS simulation are summarized.

Kulpa, Vygantas P.↗

Application of data to piloted simulators

The application of a further developed analytical model and JAWS data to a piloted simulator is addressed. The Ames simulator provides a facility for the development of piloting procedures, and for the selection of training scenarios. The system is operational with the new wind shear models and comprehensive data output. The use of these models with the simulator is dicussed in detail.

Bray, Richard S.↗

VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run

This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to announce access to the data collection from global 1-km nature run (NR) simulations using the Integrated Forecast System (IFS) with explicit convection. We invite you to join us in exploring this precursor to a digital twin of the earth! The NR simulations reveal unprecedented detail of the earth’s atmosphere, and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale. The project also won the 2020 HPCwire Readers Choice Award for Best Use of HPC in Physical Sciences. A set of two NR seasonal simulations have been completed, one corresponding to the northern hemispheric winter months (NDJF) and the other for the North Atlantic tropical cyclone season (ASO). The project used the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). The simulations were facilitated with an INCITE award from the US Department of Energy Office of Science. For the first seasonal run of four months (NDJF), the hydrostatic IFS model was initialized at 00Z on 1 November 2018. The NR for the TC season (AS) was initialized at 00Z on 1 August 2019. The NR simulations were constrained only by sea surface temperatures (SST) at the lower boundary. The IFS output was saved every 3 hours. After feedback and interest from the scientific community, the simulations were rerun for four specific extreme events, with output every 15 minutes. The special cases include a tropical cycle and three severe storm events over the continental USA.

54 ENVIRONMENTAL SCIENCES↗

Robosphere1: Building A Self-Sustaining Robotic Ecology for Mars Exploration

Robotic exploration of Mars has been a "one shot" approach where each surface mission is planned typically with a rover that will perform a series of experiments for a few weeks or months, until the robot becomes unable to operate in the harsh Mars conditions and simply "dies". It would clearly be desirable to have robots on Mars that can last for much longer periods of time, I propose that there is an approach to sustained robotic exploration that can also pave the way to future human presence. The idea is to continue building a robotic infrastructure with every mission we send. The approach is to built a team of modular robots that could repair individual members when they break down. We could "seed" areas of interest with sturdy power stations (solar, chemical) that teams of robots could use to recharge themselves. We could also seed parts and modules the robots could access for self-repair. No mission could really "fail" if we simply keep adding to and maintaining the existing infrastructure. Simply landing a package of parts will be a success. In time we create a loose infrastructure that can be controlled and augmented from earth on a continuing basis, and which could eventually pave the way for human exploration. I propose that we could begin to build this infrastructure from relatively simple modular robots. Imagine 2 "spider-like" robots built out of small modular snap-in pieces, a bin of these pieces and a bin of snap-in end effectors. One of the spiders breaks down, i.e. one of its modules needs to be replaced. The second spider comes to the rescue and helps the first one replace the broken module. Assuming the input of fresh modules, this process can continue indefinetly. Now start separating robotic explorers from robotic "mechanics", start adding, a category of mechanics that are able to fix at least some of the broken modules (and which in turn can be fixed by the original mechanics), The need for a fresh influx of modules is thus reduced. I submit that we could bootstrap a robotic ecology until it needs very little material from earth and can rely mostly on in-situ resources., We can experiment with this concept in an earthbound facility that can also simulate Mars conditions. I propose that we call this facility Robosphere1.

Colombano, Silvano P.↗

Simulation of a Flywheel Electrical System for Aerospace Applications

A Flywheel Energy Storage Demonstration Project was initiated at the NASA Glenn Research Center as a possible replacement for the battery energy storage system on the International Space Station (ISS). While the hardware fabrication work was being performed at a university and contractor's facility, the related simulation activity was begun at Glenn. At the top level, Glenn researchers simulated the operation of the ISS primary electrical system (as described in another paper) with the Flywheel Energy Storage Unit (FESU) replacing one Battery Charge and Discharge Unit (BCDU). The FESU consists of a Permanent Magnet Synchronous Motor/Generator (PMSM), which is connected to the flywheel; the power electronics that connects the PMSM to the ISS direct-current bus; and the associated controller. The PMSM model is still under development, but this paper describes the rest of the FESU model-the simulation of the converter and the associated control system that regulates energy transfer to and from the flywheel.

Truong, Long V.↗

Evaluation of candidate working fluid formulations for the electrothermal-chemical wind tunnel

A new hypersonic test facility which can simulate conditions typical of atmospheric flight at Mach numbers up to 20 is currently under study at the NASA/LaRC Hypersonic Propulsion Branch. In the proposed research, it was suggested that a combustion augmented electrothermal wind tunnel concept may be applied to the planned hypersonic testing facility. The purpose of the current investigation is to evaluate some candidate working fluid formulations which may be used in the chemical-electrothermal wind. The efforts in the initial phase of this research were concentrated on acquiring the code used by GASL to model the electrothermal wind tunnel and testing it using the conditions of GASL simulation. The early version of the general chemical kinetics code (GCKP84) was obtained from NASA and the latest updated version of the code (LSENS) was obtained from the author Dr. Bittker. Both codes are installed on a personal computer with a 486 25 MHz processor and 16 Mbyte RAM. Since the available memory was not sufficient to debug LSENS, for the current work GCKP84 was used.

Akyurtlu, Jale F.↗

Advanced Simulation and Computing (FY22 Implementation Plan Rev 0)

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY22. The Initial IP, effective , should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

ASC FY2023 Implementation Plan Revision 0

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing: FY25 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

97 MATHEMATICS AND COMPUTING↗