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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantum multi-programming for Grover’s search

Quantum multi-programming is a method utilizing contemporary noisy intermediate-scale quantum computers by executing multiple quantum circuits concurrently. Despite early research on it, the research remains on quantum gates or small-size quantum algorithms without correlation. In this paper, we propose a quantum multi-programming (QMP algorithm for Grover's search. Our algorithm decomposes Grover's algorithm by the partial diffusion operator and executes the decomposed circuits in parallel by QMP. We proved that this new algorithm increases the rotation angle of the Grover operator which, as a result, increases the success probability. The new algorithm is implemented on IBM quantum computers and compared with the canonical Grover's algorithm and other variations of Grover's algorithms. So, the empirical tests validate that our new algorithm outperforms other variations of Grover's algorithms as well as the canonical Grover's algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hydrogen wide area monitoring of LH2 releases

The characterization of liquid hydrogen (LH2) releases has been identified as an international research priority to expand the safe use of hydrogen as an energy carrier. The elucidation of LH2 release behavior will require the development of dispersion and other models, guided and validated by empirical field measurements such as those afforded by Hydrogen Wide Area Monitoring (HyWAM). HyWAM can be defined as the quantitative spatial and temporal three-dimensional monitoring of planned or unintentional hydrogen releases. With support provided through the FCH JU Prenormative Research for the Safe Use of Liquid Hydrogen (PRESLHY) program, HSE performed a series of LH2 releases to characterize the dispersion and pooling behavior of cold hydrogen releases. The NREL Sensor Laboratory developed a HyWAM system based upon a distributed array of point sensors that is amenable for profiling cold hydrogen plumes. The NREL Sensor Laboratory and HSE formally committed to collaborate on profiling the LH2 releases. This collaboration included the integration of the NREL HyWAM into the HSE LH2 release hardware. This was achieved through a deployment plan jointly developed by the NREL and HSE personnel. Under this plan, the NREL Sensor Laboratory provided multiple HyWAM modules that accommodated 32 sampling points for near-field hydrogen profiling during the HSE PRESLHY LH2 releases. The NREL HyWAM would be utilized throughout the LH2 release study performed under PRESLHY by HSE, including Work Package 3 (WP3—Release and Mixing--Rainout) and subsequent work packages (WP4—Ignition and WP5—Combustion). Under the auspices of the PRESLHY WP6 (Implementation), data and findings from the HSE LH2 Releases are to be made available to stakeholders in the hydrogen community. Comprehensive data analysis and dissemination is ongoing, but the integration of the NREL HyWAM into the HSE LH2 Release Apparatus and its performance as well as some key outcomes of the LH2 releases in WP3 are presented.

08 HYDROGEN↗
DOE OSTI2025

Modeling Mycorrhizal Carbon Costs in Temperate Forests: The Impacts of Functional Diversity and Global Change Factors

Mycorrhizal fungi form symbiotic relationships with most plant species, facilitating nutrient acquisition while consuming a significant fraction of the plant's photosynthetic carbon (C), which we define as the mycorrhizal C cost. Drivers of the mycorrhizal C cost, which is crucial for predicting environmental impacts on plant productivity, remain under-explored and difficult to quantify. Ecosystem models that incorporate mycorrhizae can offer insights into mycorrhizal C cost dynamics, but their predictions have rarely been validated against empirical data. Here, in this study, we used the Myco-CORPSE model, which explicitly simulates mycorrhizal processes alongside soil carbon and nitrogen cycling, to investigate the drivers of mycorrhizal C cost in temperate forests. Applying this model to over 1,800 forest inventory plots across the eastern United States, we found that the simulations matched published data, showing higher C allocation to ectomycorrhizal (ECM) fungi (16.0% of net primary production (NPP)) compared to arbuscular mycorrhizal (AM) fungi (5.8% of NPP). Further analysis showed that mixed forests, co-dominated by both AM and ECM trees, allocated less C to mycorrhizal fungi compared to forests dominated by either AM or ECM fungi alone, due to complementary nutrient acquisition strategies. Elevated Nitrogen (N) deposition and higher temperatures reduce mycorrhizal C costs, favoring AM strategies. Conversely, elevated CO 2 (eCO 2 ) increased plant N demand and mycorrhizal C costs, favoring ECM strategies that access organic N sources. These findings underscore the critical role of mycorrhizal functional diversity in plant nutrient acquisition and C dynamics, providing new insights into how mycorrhizal symbioses respond to global change.

Shao, Siya [Dartmouth College, Hanover, NH (United↗
DOE OSTI2023

Taxonomic and environmental distribution of bacterial amino acid auxotrophies

Abstract Many microorganisms are auxotrophic—unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of ‘streamlined’ life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗
DOE OSTI2025

Improved internal short circuit models for thermal runaway simulations in lithium-ion batteries

Thermal runaway (TR) modeling is one of the primary tools that can be used to overcome challenges associated with lithium-ion battery (LIB) safety. Among all LIB accidents that have occurred over the past decade, Internal Short Circuit (ISC) remains the most common trigger mechanism. Many available models in the literature either use a simplified approach to simulate ISC or completely ignore its contribution. The aim of this study is to understand the nature of the heat released for different types of ISC scenarios, including aluminum-anode, anode–cathode, and copper-cathode ISC. We study ISC behavior using a coupled electrochemical–thermal model with an integrated TR chemical kinetics solver built in the COMSOL Multiphysics framework. The time duration of heat release and the magnitude of the peak ISC current are studied as functions of parameters such as the size of the penetrating filament and the capacity of the cell. The numerical results are used to build an empirical model validated against the published experimental TR propagation data. Our model can be successfully used as a viable low-cost substitute in lower order (lumped) TR simulations to enable TR prevention and mitigation.

Singh, Bakhshish Preet (ORCID:0000000264751992)↗
DOE OSTI2024

Silicon Carbide Composite Cladding Qualification

This report examines the process to qualify a new fuel-cladding type focusing on the data requirements and types of irradiation testing necessary to meet the regulatory burden and related guidance applicable to fuel qualification of accident-tolerant fuel. The report considers the use of accelerated fuel qualification techniques and lead-test specimen programs that may shorten the timeline for qualifying fuel for use in a nuclear reactor at the desired burnup. The assessment framework particularly emphasizes the identification of key fuel manufacturing parameters, the specification of a fuel performance envelope to inform testing requirements, the use of evaluation models in the fuel qualification process, and the assessment of the experimental data used to develop and validate the empirical models and empirical safety criteria.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Post-DTL Beam Delivery

Ensuring that the beam delivered from the upgraded Front-End (FE) meets the Key Performance Parameters (KPPs) at each user facility is critical to the success of the LANSCE Accelerator Modernization Project (LAMP). For a high-intensity, multi-user facility like LANSCE, compliance with beam loss and radiation thresholds is as important as the charge delivered to each target. While early LAMPF/LANSCE operations relied on iterative tuning to minimize losses from beam halo and tail particles, the new FE may introduce different beam distributions and loss modes—making predictive modeling essential. To manage this, the F2E (Front-End to End) effort is developing detailed particle-tracking models that reflect realistic beamline conditions, including halo formation and expected diagnostic readings. These "snapshot" simulations aim to benchmark live machine performance at a given moment. This will help quantify how beam quality from the new FE will propagate downstream through the facility. Only by validating these models can we confidently assess and mitigate the potential impacts of the LAMP FE on beam delivery. Post-DTL, the beam splits to serve five major user facilities. Historically, low-energy beam transport has been modeled using TRACE, and higher-energy sections with TRANSPORT. These have now been unified into MAD-X format and validated with codes such as Elegant, pyOrbit, XSuite, Impact-Z, and HPSim. The primary focus now is on accurate modeling of full particle distributions (including beam halo) as they traverse the accelerator and beamlines to each experimental station. All models are at various stages of validation with empirical data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Characterization of Infrasonic Signatures of Earth-Grazing Fireballs as Analogues to Hypersonic Vehicles (Final Report)

Accurate detection, discrimination, and characterization of high-altitude hypersonic events using infrasonic monitoring are critical to planetary defense and global strategic surveillance. This report synthesizes recent advances achieved through rigorous analysis of infrasonic signatures from natural meteoroids, emphasizing shallow entry-angle meteoroids as essentially proxies for artificial hypersonic systems. Meteoroids naturally encompass diverse velocities, trajectories, altitudes, and fragmentation behaviors, enabling systematic validation of empirical period–yield relationships, waveform morphology classifiers, and trajectory-induced back-azimuth deviation models. Integration of adaptive array-processing enhancements within Cardinal software further extends infrasonic detection sensitivity and signal classification reliability. Collectively these advances, based solely on infrasonic signatures or limited optical data, offer robust methodologies for distinguishing natural from artificial hypersonic sources, significantly reducing event geolocation uncertainties and refining source-function determination. The outcomes detailed herein lay foundational groundwork for improved global hypersonic event-surveillance frameworks, supporting improved security preparedness and informing strategic monitoring and defense policies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Synchrotron emissivity from mildly relativistic particles

A simple approximate method for the evaluation of the spectrum and directivity of the synchrotron radiation from an ensemble of particles in a given magnetic field is considered, taking into account the results of this method for the total emissivity at high harmonics. The general formula is presented along with the details of the derivation of the emissivity for an arbitrary energy spectrum and pitch angle distribution of particles. The emissivities for some commonly encountered particle distributions are provided and some empirical formulae valid for a large range of the parameters are given. The results from the analytic expressions are compared with those obtained by detailed numerical calculations. For isotropic pitch angle distributions, spectra from the simple analytic expressions agree with the numerical results to a high degree of accuracy even at lower harmonics.

Petrosian, V.↗
NASA NTRS1991

Dissociation of diatomic gases

The Landau-Zener theory of reactive cross sections has been applied to diatomic molecules dissociating from a ladder of rotational and vibrational states. Although the preexponential factor of the Arrhenius rate expression is shown to be a complex function of the dimensionless activation energy, the average over all states in the ladder is well represented by a single factor that varies about as T exp (-n), where the coefficient n is the order of unity. This relation agrees very well with experimental data for dissociation of O2 and N2, for example. The results validate previous empirical assignment of a single preexponential factor in the Arrhenius expression and justify the extrapolation of the expression well beyond the range of data. The theory is then used to calculate the effect of vibrational nonequilibrium on dissociation rate. For Morse oscillators the results are about the same as for harmonic oscillators, and the dissociation from a ladder of equilibrium rotational and nonequilibrium vibrational states is close to an analytic approximation provided by Hammerling, Kivel, and Teare for harmonic oscillators all dissociating from the ground rotational state.

Hansen, C. F.↗
NASA NTRS2000

Modeling Heat-Transfer in Animal Habitats in the Shuttle Orbiter Middeck

A mathematical model has been developed to evaluate the heat transfer characteristics of an Animal Enclosure Module (AEM) in the microgravity environment. The AEM is a spaceflight habitat that provides life support for up to six rodents in the Space Shuttle Middeck. Currently, temperatures within the AEM are recorded in real time using a solid state data recorder; however, the data are only available for analysis post-flight. This temperature information is useful for characterizing the thermal environment of the AEM for researchers, but is unavailable during flight operations. Because animal health in microgravity is directly linked to the thermal environment, the ability to predict internal AEM temperatures is extremely useful to life science researchers. NASA flight crews typically carry hand-held temperature measurement devices which allow them to provide ground researchers with near real time readings of AEM inlet temperature; however, higher priority operations limit the frequency at which these measurements can be made and subsequently downlinked. The mathematical model developed allows users to predict internal cage volume temperatures based on knowledge of the ambient air temperature entering the AEM air intake ports. Additionally, an average convective heat transfer coefficient for the AEM has been determined to provide engineers with the requisite information to facilitate future design improvements and product upgrades. The model has been validated using empirical data from a series of three Space Shuttle missions.

Eodice, Michael T.↗
NASA NTRSDate not supplied

A Machine Learning Approach to Predict Martensitic Transition Temperatures for Shape Memory Alloys

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature by varying the alloy composition. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions involving ternary, quaternary, or higher additions being considered. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches including machine learning. We present results from a developed machine learning model capable of accurately predicting the transition temperature of SMAs across a wide range of compositions. Our model has the added benefit of interpretability and even provides confidence intervals for our predictions. This model will make rapid screening and design of new SMA materials possible. Predictions from the machine learning model can be validated by empirical and/or atomistic scale modeling.

Shreyas Honrao↗
DOE OSTI2023

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

ABSTRACT We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). We run the pipeline on multiple effective Zel’dovich (EZ) mock galaxy catalogs with the corresponding cuts applied and compare the results with the mock sample covariance to assess the accuracy and its fluctuations. We propose an extension of the previously developed formalism for catalogs processed with standard reconstruction algorithms. We consider methods for comparing covariance matrices in detail, highlighting their interpretation and statistical properties caused by sample variance, in particular, non-trivial expectation values of certain metrics even when the external covariance estimate is perfect. With improved mocks and validation techniques, we confirm a good agreement between our predictions and sample covariance. This allows one to generate covariance matrices for comparable data sets without the need to create numerous mock galaxy catalogs with matching clustering, only requiring 2PCF measurements from the data itself. The code used in this paper is publicly available at https://github.com/oliverphilcox/RascalC.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Develop a Model Component

During my internship at NASA, I was a model developer for Ground Support Equipment (GSE). The purpose of a model developer is to develop and unit test model component libraries (fluid, electrical, gas, etc.). The models are designed to simulate software for GSE (Ground Special Power, Crew Access Arm, Cryo, Fire and Leak Detection System, Environmental Control System (ECS), etc. ~.) before they are implemented into hardware. These models support verifying local control and remote software for End-Item Software Under Test (SUT). The model simulates the physical behavior (function, state, limits and 110) of each end-item and it's dependencies as defined in the Subsystem Interface Table, Software Requirements & Design Specification (SRDS), Ground Integrated Schematic (GIS), and System Mechanical Schematic.(SMS). The software of each specific model component is simulated through MATLAB's Simulink program. The intensiv~ model development life cycle is a.s follows: Identify source documents; identify model scope; update schedule; preliminary design review; develop model requirements; update model.. scope; update schedule; detailed design review; create/modify library component; implement library components reference; implement subsystem components; develop a test script; run the test script; develop users guide; send model out for peer review; the model is sent out for verific~tionlvalidation; if there is empirical data, a validation data package is generated; if there is not empirical data, a verification package is generated; the test results are then reviewed; and finally, the user. requests accreditation, and a statement of accreditation is prepared. Once each component model is reviewed and approved, they are intertwined together into one integrated model. This integrated model is then tested itself, through a test script and autotest, so that it can be concluded that all models work conjointly, for a single purpose. The component I was assigned, specifically, was a fluid component, a discrete pressure switch. The switch takes a fluid pressure input, and if the pressure is greater than a designated cutoff pressure, the switch would stop fluid flow.

Ensey, Tyler S.↗
NASA NTRS2009

Findings from the Supersonic Qualification Program of the Mars Science Laboratory Parachute System

In 2012, the Mars Science Laboratory Mission (MSL) will deploy NASA's largest extra-terrestrial parachute, a technology integral to the safe landing of its advanced robotic explorer on the surface. The supersonic parachute system is a mortar deployed 21.5 m disk-gap-band (DGB) parachute, identical in geometric scaling to the Viking era DGB parachutes of the 1970's. The MSL parachute deployment conditions are Mach 2.3 at a dynamic pressure of 750 Pa. The Viking Balloon Launched Decelerator Test (BLDT) successfully demonstrated a maximum of 700 Pa at Mach 2.2 for a 16.1 m DGB parachute in its AV4 flight. All previous Mars deployments have derived their supersonic qualification from the Viking BLDT test series, preventing the need for full scale high altitude supersonic testing. The qualification programs for Mars Pathfinder, Mars Exploration Rover, and Phoenix Scout Missions were all limited to subsonic structural qualification, with supersonic performance and survivability bounded by the BLDT qualification. The MSL parachute, at the edge of the supersonic heritage deployment space and 33% larger than the Viking parachute, accepts a certain degree of risk without addressing the supersonic environment in which it will deploy. In addition, MSL will spend up to 10 seconds above Mach 1.5, an aerodynamic regime that is associated with a known parachute instability characterized by significant canopy projected area fluctuation and dynamic drag variation. This aerodynamic instability, referred to as "area oscillations" by the parachute community has drag performance, inflation stability, and structural implications, introducing risk to mission success if not quantified for the MSL parachute system. To minimize this risk and as an alternative to a prohibitively expensive high altitude test program, a multi-phase qualification program using computation simulation validated by subscale test was developed and implemented for MSL. The first phase consisted of 2% of fullscale supersonic wind tunnel testing of a rigid DGB parachute with entry-vehicle to validate two high fidelity computational fluid dynamics (CFD) tools. The computer codes utilized Large Eddy Simulation and Detached Eddy Simulation numerical approaches to accurately capture the turbulent wake of the entry vehicle and its coupling to the parachute bow-shock. The second phase was the development of fluid structure interaction (FSI) computational tools to predict parachute response to the supersonic flow field. The FSI development included the integration of the CFD from the first phase with a finite element structural model of the parachute membrane and cable elements. In this phase, a 4% of full-scale supersonic flexible parachute test program was conducted to provide validation data to the FSI code and an empirical dataset of the MSL parachute in a flight-like environment. The final phase is FSI simulations of the full-scale MSL parachute in a Mars type deployment. Findings from this program will be presented in terms of code development and validation, empirical findings from the supersonic testing, and drag performance during supersonic operation.

EDL↗