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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

How to Build a Rover: An Overview of the Mars 2020 Mission’s Vehicle System Testbed

While NASA’s Mars rover Perseverance continues to make groundbreaking achievements on the Red Planet, its twin is hard at work here on Earth. The Operational Perseverance Twin for the Integration of Mechanisms and Instruments Sent to Mars, or OPTIMISM, is the Mars 2020 Vehicle System Testbed (VSTB) rover operated by NASA Jet Propulsion Laboratory (JPL) in Pasadena, California. OPTIMISM’s home is the JPL Mars Yard; an outdoor field with red soil that simulates the terrain encountered by Perseverance. The VSTB is a full-scale engineering model of the flight rover, serving a number of functions to ensure mission operations can continue smoothly and on schedule. The VSTB possesses instrumentation, computers, mechanisms, cameras, and a Mobility subsystem that are nearly identical to its extraterrestrial twin. Its high fidelity allows the rover to be a highly effective tool to fully test system functionality and performance prior to commanding the flight rover. The early stages of building OPTIMISM began a few months prior to Perseverance departing JPL for Cape Canaveral, FL in early 2020. Electrical integration of the flight system avionics, and compatibility checkouts of the electrical ground support equipment ensured that the foundation of the electrical system was operational and in place. Next, the internal harnessing was installed and compatibility checks of the rover instrumentation and mechanisms were performed to confirm the system was prepared for full buildup. Finally, mechanical assembly of the rover chassis with its external components completed the integration of the system before it was moved to the Mars Yard for its initial phase of testing to perform verification & validation (V&V) of the Mobility subsystem requirements. By the time Perseverance landed at Jezero Crater in February 2021, the first phase of VSTB operations was underway. Surface guidance, navigation, and control (SGNC) testing for the Mobility subsystem ensured functionality and performance requirements were met for various capabilities such as visual odometry (VO), mapping, and automatic navigation (AutoNav). Subsequent integration of the robotic arm (RA) onto the VSTB enabled the V&V campaign for surface sampling operations (SSO) to commence. As the mission’s engineering operations (EO) have gotten underway, the VSTB has been utilized for an array of purposes including troubleshooting software anomalies, and performing dry-runs for first time activities (FTAs) prior to sending the commands to Perseverance. OPTIMISM will continue to serve mission critical functions as long as Perseverance is roving the Red Planet.

Rojas, Jose Trujillo↗
NASA NTRSDate not supplied

Cryogenic Flow Boiling Parabolic Flight Experiment and Universal Correlations for Cryogens

Cryogenic fluids are employed in many industries and play crucial roles in space applications, including nuclear thermal propulsion systems, LOX/LCH4 ascent and descent stage feedlines, LOX/LH2 transfer lines for in-space fuel depots, and LHe transfer lines that cool space experiments. Due to the ultra-low boiling point of cryogens, phase change is inevitable in these systems, which leads to complex boiling behavior in reduced gravity. For cost-effective design and sizing of the aforementioned systems, accurate knowledge of two-phase parameters such as pressure drop, heat transfer coefficient (HTC), and critical heat flux (CHF) is desired. Since 2018, researchers from Purdue University and NASA Glenn Research Center (GRC) have been collaborating to investigate the effects of reduced gravity on cryogenic pool boiling, flow boiling ins tubes, and spray cooling. Using a variety of both terrestrial and parabolic flight experimental rigs, extensive LN2 data have been amassed and combined with cryogenic data from World literature to develop both ‘universal’ empirical correlations and CFD models, which are expected to serve as foundation for design of future space systems involving cryogenic fluids. This presentation will provide an overview of both the experimental work and predictive tools that have resulted from the joined Purdue-Glenn studies.

Flow Boiling↗
NASA NTRSDate not supplied

Hemispheric Airborne Measurements of Air Quality (HAMAQ)

Under NASA’s Earth Venture Suborbital program, Hemispheric Airborne Measurements of Air Quality (HAMAQ) will conduct a series of campaigns in 2028 under the Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite instrument. HAMAQ plans include two deployments, including the Mexico City megalopolis and another North American site yet to be selected. The effort will include two aircraft, NASA’s B777 for in situ sampling and G-III for remote sensing. These aircraft will be used to complete a system of integrated observations, combining satellite observations, ground-based monitoring and research observations with air quality modeling. HAMAQ field intensives will serve multiple objectives to include: improving the use of satellite observations in concert with traditional ground monitoring to inform air quality; assessing emissions to better understand their timing and source apportionment; advancing the development of satellite proxies for air quality; and assessing the factors controlling local air quality in each location sampled. Given the long lead time for this campaign, this poster welcomes discussion from the community on strategies and candidate sites for the second deployment. Given the broad applicability of the HAMAQ science objectives and observing strategy, possible partnerships to extend the pursuit of the larger vision of HAMAQ to also sample in Asia and Europe are of interest.

James H Crawford↗
DOE OSTI2019

Stochastic Molecular Dynamics

I can not pass up the opportunity to honor Graeme Bird, a true gentleman and a real scholar, if there ever was one. When we first met at a rarefied gas dynamics conference, it was instant mutual admiration. Furthermore, we met rarely thereafter at subsequent rarefied gas meetings since I attended them infrequently as a physicist interested in hydrodynamics, where often even a rarefied gas without deterministic collisions can serve as a simple fluid model but Graeme attended them regularly. In that rst meeting I became aware of DSMC, read Graeme paper and found to my astonishment that the only reference in that paper was to my molecular dynamics work2. Indeed DSMC is computationally faster competitor to molecular dynamics and it is this feature that I would like to emphasize in this brief note. It is for this reason that I entitled this contribution \stochastic molecular dynamics". I once told Graeme that that would have been a more descriptive name to his method than DSMC. DSMC is also a good demonstration that an algorithm developed for an entirely different purposes can also be very useful for other applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations: Preprint

The US Department of Energy has identified Exascale-Class wind farm simulation tools as critical to wind energy scientific discovery. A primary objective of the Exawind project is to build high-performance, predictive Computational Fluid Dynamics tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next generation, Exascale-Class, platforms. Here, we report on our efforts for preparing the Exawind unstructured mesh solver, Nalu-Wind, for Exascale-Class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is not sufficient. One needs novel algorithms that are application aware, memory efficient, and optimized for latest generation GPU devices to get high-performance. The result of our efforts are unstructured mesh simulations of wind turbines that use 1/6 the compute resources of Summit supercomputer at Oak Ridge National Lab. In particular, we demonstrate a first-of-its-kind, simulation using Algebraic Multigrid solvers on over 4000 GPUs.

algebraic multigrid↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
NASA NTRS1999

A Quasi-Linear Behavioral Model and an Application to Self-Directed Learning

A model is presented that describes the relationship between one's knowledge of the world and the concomitant personal behaviors that serve as a mechanism to obtain desired outcomes. Integrated within this model are the differing roles that outcomes serve as motivators and as modifiers to one's worldview. The model is dichotomized between general and contextual applications. Because learner self-directedness (a personal characteristic) involves cognition and affection while self-directed learning (a pedagogic process) encompasses conation, behavior and introspection, the model can be dichotomized again in another direction. Presented also are the roles that cognitive motivation theories play in moving an individual through this behavioral model and the roles of wishes, self-efficacy, opportunity and self-influence.

Ponton, Michael K.↗
DOE OSTI2021

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

In recent years, the Artificial Intelligence and Data Mining (AI&DM) models have become popular tools in assisting various aspects of reservoir operation. However, the practical uses are still rarely reported. Comparison experiment of many AI&DM models over a large number of reservoir cases is particularly valuable to help reservoir operators first examine the usefulness and transferability of different AI&DM models, and then identify the most stable and reliable AI&DM model in assist of various decision-making processes. In this study, a total of 12 AI&DM models with different parameterizations and simulation scenarios are comprehensively tested out and compared in simulating the controlled reservoir outflows of 33 reservoir cases over the Upper Colorado Region, United States. Results show that the Random Forecast and the Long-Short-Term-Memory model could consistently derive the best statistical performance than other models under the baseline simulation scenario. The employed AI&DM models could obtain satisfactory statistical interquartile ranges (25–75%) between [0.6–0.9], [0.3–0.8], and [0.2–0.8], for CORR, NSE, and KGE measurements, respectively, and [1.5–6.5], [–15 to 20], and [0.5–8.5] for the normalized RMSE, PBIAS and RSR measurements, respectively. Results also show Multi-Layer Perceptron model and Extreme Gradient Boosting Tree Algorithm produced more stable and superior performance than other models under more complex input scenarios. We also found that the performance of different AI&DM models are closely relevant to the reservoir elevations, sizes, and functionalities. Discussions were made about the sensitivity of AI&DM models’ parameterizations and the key advantages of AI&DM models over the rule-based reservoir models. We further identify that the main advantage of AI&DM models is the flexibility in designing input structures, whereas the rule-based simulation model is rather limited. Future studies were suggested regarding the best way reservoir operators and researchers could use, select, and apply different AI&DM models in simulating reservoir releases under different natural and modeling environments. Finally, this comparison study also serves as a reference and a piece of groundwork for further promoting the practical uses of AI&DM models in assisting reservoir operation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Evaluating a Priori Ozone Profile Information Used in TEMPO (Tropospheric Emissions: Monitoring of Pollution) Tropospheric Ozone Retrievals

A primary objective for TOLNet is the evaluation and validation of space-based tropospheric O3 retrievals from future systems such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite. This study is designed to evaluate the tropopause-based O3 climatology (TB-Clim) dataset which will be used as the a priori profile information in TEMPO O3 retrievals. This study also evaluates model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time (NRT) data assimilation model products (NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS-5) Forward Processing (FP) and Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2)) and full chemical transport model (CTM), GEOS-Chem, simulations. The TB-Clim dataset and model products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations to demonstrate the accuracy of the suggested a priori dataset and information which could potentially be used in TEMPO O3 algorithms. This study also presents the impact of individual a priori profile sources on the accuracy of theoretical TEMPO O3 retrievals in the troposphere and at the surface. Preliminary results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles observed by TOLNet, model-simulated profiles from a full CTM (GEOS-Chem is used as a proxy for CTM O3 predictions) resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly (diurnal cycle evaluation) and daily-averaged (daily variability evaluation) TOLNet observations. Furthermore, it was determined that when large daily-averaged surface O3 mixing ratios are observed (65 ppb), which are important for air quality purposes, TEMPO retrieval values at the surface display higher correlations and less bias when applying CTM a priori profile information compared to all other data products. The primary reason for this is that CTM predictions better capture the spatio-temporal variability of the vertical profiles of observed tropospheric O3 compared to the TB-Clim dataset and other NRT data assimilation models evaluated during this study.

Pollution↗
DOE OSTI2018

Molecular tools enabling pennycress (Thlaspi arvense) as a model plant and oilseed cash cover crop

Thlapsi arvense L. (pennycress) is being developed as a profitable oilseed cover crop for the winter fallow period throughout the temperate regions of the world, controlling soil erosion and nutrients run-off on otherwise barren farmland. We demonstrate that pennycress can serve as a user-friendly model system akin to Arabidopsis that is well-suited for both laboratory and field experimentation. We sequenced the diploid genome of the spring-type Spring 32-10 inbred line (1C DNA content of 539 Mb; 2n = 14), identifying variation that may explain phenotypic differences with winter-type pennycress, as well as predominantly a one-to-one correspondence with Arabidopsis genes, which makes translational research straightforward. We developed an Agrobacterium-mediated floral dip transformation method (0.5% transformation efficiency) and introduced CRISPR-Cas9 constructs to produce indel mutations in the putative FATTY ACID ELONGATION1 (FAE1) gene, thereby abolishing erucic acid production and creating an edible seed oil comparable to that of canola. We also stably transformed pennycress with the Euonymus alatus diacylglycerol acetyltransferase (EaDAcT) gene, producing low-viscosity acetyl-triacylglycerol-containing seed oil suitable as a diesel-engine drop-in fuel. Adoption of pennycress as a model system will accelerate oilseed-crop translational research and facilitate pennycress’ rapid domestication to meet the growing sustainable food and fuel demands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations

Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of tenuous aerosols. Here, we conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Observational Constraint on Cloud Susceptibility Weakened by Aerosol Retrieval Limitations

Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of ten- uous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.

Ma, Po-Lun↗
NASA NTRS2026

Hybrid Modeling Study on Grain Evolution in the Metal Welding Process and Its Potential Lunar Application

Metal is most commonly used structural material in a wide range of spacecraft, and welding is the principal method for joining metal components into functional systems. However, conducting welding experiments under extreme environments—such as microgravity or vacuum conditions in space—is prohibitively expensive and experimentally challenging. To overcome these limitations, multi-physics computational welding models provide a cost-effective and versatile alternative. In this work, the authors have developed a coupled thermal (fluid) microstructure simulation framework to model metal welding under varying gravity conditions. The framework integrates a mixed-mode heat transfer formulation (conduction, convection, and radiation) with molten pool fluid dynamics, enabling accurate prediction of temperature fields and weld-pool geometry. A grain growth model is further incorporated to capture the spatial and temporal evolution of microstructure, including grain size distribution and morphological transitions during solidification. This approach provides detailed insight into molten pool evolution and grain-level microstructure development throughout the welding process. By explicitly parameterizing environmental conditions, the model supports extrapolation to off-Earth manufacturing scenarios such as welding on the lunar surface. Tantalum—chosen in this study due to its high melting point, oxidation resistance, and mechanical stability at elevated temperatures—serves as the material system for model demonstration. Beyond Tantalum, the integrated multi-physics framework offers broad applicability for predictive welding simulations of various structural and refractory metals or alloys used in extreme terrestrial or extraterrestrial environments.

kinetic Monte Carlo (SPPARKS)↗
DOE OSTI2026

Onset of High-Harmonic Fast Wave Propagation in Annulus Geometry

Previous experiments on NSTX have reported high-harmonic fast wave (HHFW) power losses in the scrape-off layer (SOL), with dependencies on the wave parallel wavenumber, plasma density, and magnetic field. This study presents an analysis of HHFW propagation in the SOL plasma, focusing on parasitic coupling to the waveguide mode bounded by the steep gradient pedestal and the outer wall boundary. The analytic and finite element wave models are discussed using a 2D annulus geometry, which serves as a simplified representation of the NSTX-U plasma. The model shows that a minimum radial gap width is required to support wave propagation, analogous to the higher-order modes in coaxial geometries. The impact of several factors, including gap width, wave parallel phasing, and magnetic field strength, on parasitic wave coupling is examined, highlighting the role of the geometric dimension in relation to the wave perpendicular wavelength. The findings suggest that controlling the edge/SOL density profile (gap control) is crucial for mitigating parasitic coupling when the density in front of the antenna exceeds the density cutoff.

Baek, Seung-Gyou [Massachusetts Inst. of Technolog↗
DOE OSTI2025

Measurement of Close-in Ground Motion from an Underground Chemical Explosion

Understanding the geophysical response near an underground explosion is crucial for generating insights into the source and emplacement conditions that produce distinct observations in monitoring scenarios occurring at greater distances. Recently, Shot A of the Low Yield Nuclear Monitoring (LYNM) Physics Experiment 1 (PE1) series was conducted at the Nevada National Security Site to provide ground truth for subsurface explosion signal models. This experiment resulted in measuring near-source ground motion at distances ranging from 70 to 1000 m/kt with a 99% success rate, yielding high-fidelity knowledge of the near-field response that can serve as benchmarks for future numerical modeling and experiment planning. However, technical challenges exist in observing near-source phenomena while safeguarding sensitive data acquisition components from the detrimental effects of ground motion in the subsurface. This report outlines tools and techniques to address challenges associated with observing near-source accelerations and within the tunnel drift of the PE1 test bed. Additionally, we describe key systems designed with both modern advancements and legacy guidance to maximize the collection of high-quality ground motion data, which may be applied to constitutive and computational models, leading to new or improved understanding of the near- and far-field signals produced by underground explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully--coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110km grid spacing), ocean and sea ice (60km in the mid-latitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima (CMIP6 DECK) simulations consisting of a long pre-industrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO 2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between pre-industrial (1850) and present-day, the trajectory of the warming diverges from observations in the second half of the 20th century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERF ari+aci = -1.65 W m -2 ) and high equilibrium climate sensitivity (ECS = 5.3 K).

58 GEOSCIENCES↗
DOE OSTI2021

Out of the Dark and Into the Light: A New View of Phytochrome Photobodies

Light is a critical environmental stimulus for plants, serving as an energy source via photosynthesis and a signal for developmental programming. Plants perceive light through various light-responsive proteins, termed photoreceptors. Phytochromes are red-light photoreceptors that are highly conserved across kingdoms. In the model plant Arabidopsis thaliana , phytochrome B serves as a light and thermal sensor, mediating physiological processes such as seedling germination and establishment, hypocotyl growth, chlorophyll biogenesis, and flowering. In response to red light, phytochromes convert to a biologically active form, translocating from the cytoplasm into the nucleus and further compartmentalizes into subnuclear compartments termed photobodies. PhyB photobodies regulate phytochrome-mediated signaling and physiological outputs. However, photobody function, composition, and biogenesis remain undefined since their discovery. Based on photobody cellular dynamics and the properties of internal components, photobodies have been suggested to undergo liquid-liquid phase separation, a process by which some membraneless compartments form. Here, we explore photobodies as environmental sensors, examine the role of their protein constituents, and outline the biophysical perspective that photobodies may be undergoing liquid-liquid phase separation. Understanding the molecular, cellular, and biophysical processes that shape how plants perceive light will help in engineering improved sunlight capture and fitness of important crops.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Understanding activity engagement across weekdays and weekend days: A multivariate multiple discrete-continuous modeling approach

This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are important complementary relationships and competing tradeoffs involved in scheduling and allocating time to various activities across days of the week. Both limited survey data availability and methodological challenges in modeling week-long activity-travel schedules have precluded the development of multi-day activity-travel demand models. With passive and technology-based data collection methods increasingly in vogue, the collection of multi-day travel data may become increasingly commonplace in the years ahead. This paper addresses the methodological challenge associated with modeling multi-day activity-travel demand by formulating a multivariate multiple discrete-continuous probit (MDCP) model system. The comprehensive framework ties together two MDCP model components, one corresponding to weekday time allocation and the other to weekend activity-time allocation. By tying the two MDCP components together, the model system also captures relationships in activity-time allocation between weekdays on the one hand and weekend days on the other. Model estimation on a week-long travel diary data set from the United Kingdom shows that there are significant inter-relationships between weekdays and weekend days in activity-travel scheduling behavior. In conclusion, the model system presented in this paper may serve as a higher-level multi-day activity scheduler in conjunction with existing daily activity-based travel models.

30 DIRECT ENERGY CONVERSION↗