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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Summer Work Experience: Determining Methane Combustion Mechanisms and Sub-Scale Diffuser Properties for Space Transporation System Engine Testing

To assess engine performance during the testing of Space Shuttle Main Engines (SSMEs), the design of an optimal altitude diffuser is studied for future Space Transportation Systems (STS). For other Space Transportation Systems, rocket propellant using kerosene is also studied. Methane and dodecane have similar reaction schemes as kerosene, and are used to simulate kerosene combustion processes at various temperatures. The equations for the methane combustion mechanism at high temperature are given, and engine combustion is simulated on the General Aerodynamic Simulation Program (GASP). The successful design of an altitude diffuser depends on the study of a sub-scaled diffuser model tested through two-dimensional (2-D) flow-techniques. Subroutines given calculate the static temperature and pressure at each Mach number within the diffuser flow. Implementing these subroutines into program code for the properties of 2-D compressible fluid flow determines all fluid characteristics, and will be used in the development of an optimal diffuser design.

Williams, Powtawche N.↗
NASA NTRS1995

Interactions of CO2, temperature and management practices: simulations with a modified version of CERES-Wheat

A new growth subroutine was developed for CERES-Wheat, a computer model of wheat (Triticum aestivum) growth and development. The new subroutine simulates canopy photosynthetic response to CO2 concentrations and light levels, and includes the effects of temperature on canopy light-use efficiency. Its performance was compared to the original CERES-Wheat V-2 10 in 30 different cases. Biomass and yield predictions of the two models were well correlated (correlation coefficient r > 0.95). As an application, summer growth of spring wheat was simulated at one site. Modeled crop responses to higher mean temperatures, different amounts of minimum and maximum warming, and doubled CO2 concentrations were compared to observations. The importance of irrigation and nitrogen fertilization in modulating the wheat crop climatic responses were also analyzed. Specifically, in agreement with observations, rainfed crops were found to be more sensitive to CO2 increases than irrigated ones. On the other hand, low nitrogen applications depressed the ability of the wheat crop to respond positively to CO2 increases. In general, the positive effects of high CO2 on grain yield were found to be almost completely counterbalanced by the negative effects of high temperatures. Depending on how temperature minima and maxima were increased, yield changes averaged across management practices ranged from -4% to 8%.

NASA Discipline Life Support Systems↗
NASA NTRS2004

Improved Nuclear Reactor and Shield Mass Model for Space Applications

New technologies are being developed to explore the distant reaches of the solar system. Beyond Mars, solar energy is inadequate to power advanced scientific instruments. One technology that can meet the energy requirements is the space nuclear reactor. The nuclear reactor is used as a heat source for which a heat-to-electricity conversion system is needed. Examples of such conversion systems are the Brayton, Rankine, and Stirling cycles. Since launch cost is proportional to the amount of mass to lift, mass is always a concern in designing spacecraft. Estimations of system masses are an important part in determining the feasibility of a design. I worked under Michael Barrett in the Thermal Energy Conversion Branch of the Power & Electric Propulsion Division. An in-house Closed Cycle Engine Program (CCEP) is used for the design and performance analysis of closed-Brayton-cycle energy conversion systems for space applications. This program also calculates the system mass including the heat source. CCEP uses the subroutine RSMASS, which has been updated to RSMASS-D, to estimate the mass of the reactor. RSMASS was developed in 1986 at Sandia National Laboratories to quickly estimate the mass of multi-megawatt nuclear reactors for space applications. In response to an emphasis for lower power reactors, RSMASS-D was developed in 1997 and is based off of the SP-100 liquid metal cooled reactor. The subroutine calculates the mass of reactor components such as the safety systems, instrumentation and control, radiation shield, structure, reflector, and core. The major improvements in RSMASS-D are that it uses higher fidelity calculations, is easier to use, and automatically optimizes the systems mass. RSMASS-D is accurate within 15% of actual data while RSMASS is only accurate within 50%. My goal this summer was to learn FORTRAN 77 programming language and update the CCEP program with the RSMASS-D model.

Robb, Kevin↗
NASA NTRS2005

The M-Integral for Computing Stress Intensity Factors in Generally Anisotropic Materials

The objective of this project is to develop and demonstrate a capability for computing stress intensity factors in generally anisotropic materials. These objectives have been met. The primary deliverable of this project is this report and the information it contains. In addition, we have delivered the source code for a subroutine that will compute stress intensity factors for anisotropic materials encoded in both the C and Python programming languages and made available a version of the FRANC3D program that incorporates this subroutine. Single crystal super alloys are commonly used for components in the hot sections of contemporary jet and rocket engines. Because these components have a uniform atomic lattice orientation throughout, they exhibit anisotropic material behavior. This means that stress intensity solutions developed for isotropic materials are not appropriate for the analysis of crack growth in these materials. Until now, a general numerical technique did not exist for computing stress intensity factors of cracks in anisotropic materials and cubic materials in particular. Such a capability was developed during the project and is described and demonstrated herein.

Warzynek, P. A.↗
NASA NTRS2010

NAIF Toolkit - Extended

The Navigation Ancillary Infor ma tion Facility (NAIF) at JPL, acting under the direction of NASA s Office of Space Science, has built a data system named SPICE (Spacecraft Planet Instrument Cmatrix Events) to assist scientists in planning and interpreting scientific observations (see figure). SPICE provides geometric and some other ancillary information needed to recover the full value of science instrument data, including correlation of individual instrument data sets with data from other instruments on the same or other spacecraft. This data system is used to produce space mission observation geometry data sets known as SPICE kernels. It is also used to read SPICE kernels and to compute derived quantities such as positions, orientations, lighting angles, etc. The SPICE toolkit consists of a subroutine/ function library, executable programs (both large applications and simple utilities that focus on kernel management), and simple examples of using SPICE toolkit subroutines. This software is very accurate, thoroughly tested, and portable to all computers. It is extremely stable and reusable on all missions. Since the previous version, three significant capabilities have been added: Interactive Data Language (IDL) interface, MATLAB interface, and a geometric event finder subsystem.

Acton, Charles H., Jr.↗
NASA NTRS2005

Generating Solid Models from Topographical Data

A method of generating solid models of terrain involves the conversion of topographical data into a form useable by a rapid-prototyping (RP) machine. The method was developed to enable the use of the RP machine to make solid models of Martian terrain from Mars Orbiter laser-altimeter topographical data. The method is equally applicable to the generation of models of the terrains of other astronomical bodies, including other planets, asteroids, and Earth. Topographical data describe a terrain in terms of a set of three-dimensional coordinates [e.g., Cartesian (x,y,z) or polar (latitude, longitude, radius) coordinates] of points or nodes on the terrain surface. The input data for the RP machines are required to provide a three-dimensional description, not of a single surface, but of a volume in this case, a ground volume that underlies the terrain surface. The description is required to be in the form of triangular elements that connect the nodes of all the surfaces and that completely bound the volume, with no open areas, no overlap of triangles, and no extraneous geometric elements. The software used in the present model-generation method was written in IDL - an advanced programming language that affords a number of tools, including subroutines that triangularize surfaces. The software creates a volume from the topographical surface data by adding sides to the edges of the terrain surface and joining the sides with a bottom surface. Each of the sides is triangularized by use of IDL subroutines, and then the software searches for extraneous elements and removes them. Topographical data are usually presented in a grid corresponding to polar coordinates, so that a model generated from such data is equivalent to a topographical map in Mercator projection. However an RP machine is fully capable of including the curvature of a planetary body in a model that it makes. Therefore, the software also offers a capability to transform the topographical data to a projection onto a surface having a curvature corresponding to that of the surface of the modeled planet.

Keller, John W.↗
NASA NTRS2013

Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS

The Mars Exploration Rovers (MERs), Spirit and Opportunity, far exceeded their original drive distance expectations and have traveled, at the time of this reporting, a combined 29 kilometers across the surface of Mars. The Rover Sequencing and Visualization Program (RSVP), the current program used to plan drives for MERs, is only a kinematic simulator of rover movement. Therefore, rover response to various terrains and soil types cannot be modeled. Although sandbox experiments attempt to model rover-terrain interaction, these experiments are time-intensive and costly, and they cannot be used within the tactical timeline of rover driving. Imaging techniques and hazard avoidance features on MER help to prevent the rover from traveling over dangerous terrains, but mobility issues have shown that these methods are not always sufficient. ARTEMIS, a dynamic modeling tool for MER, allows planned drives to be simulated before commands are sent to the rover. The deformable soils component of this model allows rover-terrain interactions to be simulated to determine if a particular drive path would take the rover over terrain that would induce hazardous levels of slip or sink. When used in the rover drive planning process, dynamic modeling reduces the likelihood of future mobility issues because high-risk areas could be identified before drive commands are sent to the rover, and drives planned over these areas could be rerouted. The ARTEMIS software consists of several components. These include a preprocessor, Digital Elevation Models (DEMs), Adams rover model, wheel and soil parameter files, MSC Adams GUI (commercial), MSC Adams dynamics solver (commercial), terramechanics subroutines (FORTRAN), a contact detection engine, a soil modification engine, and output DEMs of deformed soil. The preprocessor is used to define the terrain (from a DEM) and define the soil parameters for the terrain file. The Adams rover model is placed in this terrain. Wheel and soil parameter files can be altered in the respective text files. The rover model and terrain are viewed in Adams View, the GUI for ARTEMIS. The Adams dynamics solver calls terramechanics subroutines in FORTRAN containing the Bekker-Wong equations.

Trease, Brian P.↗
NASA NTRS2016

Accuracy of RT Code SORD for Realistic Atmospheric Profiles

We discuss accuracy of our recently developed RT code SORD using 2 benchmark scenarios published by the IPRT group in 2015. These scenarios define atmospheres with a complicate dependence of scattering and absorption properties over height (profile). Equal step, dh=1km, is assumed in the profiles. We developed subroutines that split such atmospheres into layers of the same optical thickness, d tau. We provide full text of the subroutines with comments in Appendix. The d tau is a step for vertical integration in the method of successive orders. Modification of the input profiles from "equal step over h" to "equal step over tau" changes input for RT simulations. This may cause errors at or above the acceptable level of the measurement uncertainty. We show errors of the RT code SORD for both intensity and polarization. In addition to that, using our discrete ordinates RT code IPOL, we discuss one more IPRT scenario, in which changes in height profile indeed cause unacceptable errors. Clear understanding of source and magnitude of these errors is important, e.g. for the AERONET retrieval algorithm. SORD is available from ftp://maiac.gsfc.nasa.gov/pub/skorkin/SORD_IP_16B/ or by email request from the first author.

polarization↗
NASA NTRSDate not supplied

Quantum-accelerated Global Constraint Filtering

Motivated by recent advances in quantum algorithms and gate-model quantum computation, we introduce quantum-accelerated filtering algorithms for global constraints in constraint programming. We adapt recent work in quantum algorithms for graph problems and identify quantum subroutines that accelerate the main domain consistency algorithms for the all different constraint and the global cardinality constraint (gcc). The subroutines are based on quantum algorithms for finding maximum matchings and strongly connected components in graphs, and provide speedups over the best classical algorithms. We detail both complete and bounded-probability frameworks for quantum-accelerated global constraint filtering algorithms within backtracking search.

Quantum algorithms↗
NASA NTRSDate not supplied

Single and Multi-Node Modeling of Direct, Submerged, and Self-Pressurization of A Cryogenic Propellant Tank Using Nodal Tools

The pressurization of cryogenic propellant tanks will always be an important process so long as cryogenic liquids are being considered as fuel sources or used for other in-space applications. Pressure control of the tank ullage is necessary for managing propellant flowrates to an engine or a receiver tank, and modeling of the process is used to predict the pressurant requirements and the amount of propellant boiloff. Direct ullage pressurization is the more traditional approach to tank pressurization, as the physics are straight-forward, and ample test (flight) data have been collected and analyzed over the past several decades. Submerged injection pressurization is an alternate method for tank pressurization and has been shown to reduce pressurant requirements, subcool the propellant, and reduce the risk of ullage collapse. Additionally, the pressurant gas entering the ullage is usually much colder when using the submerged pressurization approach, resulting in reduced propellant boiloff. These benefits are at the expense of vaporizing a small percentage of the propellent. Both tank pressurization methods are viable options for current and future space missions, and it is important to have the capability of analyzing the tank ullage conditions for both approaches. Our previous work has demonstrated the development of a Generalized Fluid System Simulation Program (GFSSP) model, which contains a thermodynamic equilibrium heat and mass transfer subroutine capable of effectively analyzing both direct and submerged pressurization systems [1-2]. This subroutine has most recently been enhanced to include the non-equilibrium effect of pressurant dissolution into the propellant. To date the ullage has always been represented as a single node, and although the simulated single-node temperatures have good comparison with the volume-averaged ullage temperatures computed from test data, the physics of the thermal stratification in the ullage were never captured, and adjustment factors in the model were required. The purpose of this paper is to introduce the development of a multi-node ullage model using GFSSP and to discuss the improvements of the simulated ullage temperature distribution and its resulting effects on ullage heat transfer processes. Test data from the Cryogenic Propellant Storage and Transfer Engineering Developmental Unit (CPST EDU) was used for model validation. For additional comparison, a Thermal Desktop (TD) model was also developed to analyze the CPST EDU direct ullage pressurization tests using both a single node and multi-node approach. The model includes the direct pressurant line, vent line, fill/drain line, and a TD FloCAD Compartment. The TD FloCAD Compartment is employed to represent the liquid and ullage as single volumes inside the tank, to include a liquid/vapor interface, and to generate network level objects such as lumps (analogous to nodes in GFSSP), paths, and ties between the fluid and thermal elements. An established heat load on the model tank was leveraged from a pre-existing higher-fidelity model correlated to CPST EDU test data.

pressurization↗
NASA NTRSDate not supplied

Monte Carlo Tree Search for Integrated Planning, Learning, and Execution in Nondeterministic Python

We present a novel use of Monte Carlo Tree Search (MCTS),adapted to explore a search space produced by the choice points embedded in Python code. The choice points are non-deterministic assignment statements and subroutine calls. We present MCTS extensions required for doing tree search in this context which includes control constructs like hierarchical decomposition (subroutine calls), iterative while loops and conditional statements. We demonstrate how the system works in a simulated rideshare scenario in an urban setting, and present preliminary experiments as a proof of concept.

Automatic planning↗
DOE OSTI2024

Validating automated resonance evaluation with synthetic data

The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Exploring the impact of hydro-mechanical coupling on compaction localization

In deep subsurface environments, where porous rocks are saturated with fluids, hydromechanical coupling plays a critical role in the formation and propagation of localized deformation zones, such as compaction bands. In this study, we numerically investigate the influence of fluid-rock interactions on the development of compaction localization in fluid-saturated rocks. For this purpose, it uses a numerical framework that adapts the heat equation to model the diffusion of pore pressure caused by deformation. This is achieved with specialized subroutines for material behavior and heat transfer formulated within the ABAQUS platform and by allowing changes in rock permeability during strain localization. The results highlight that hydromechanical coupling significantly alters the compaction behavior compared to dry conditions. Under high confining stress, excess pore pressure inhibits the progression of compaction fronts, while in time-dependent processes like rock creep, pore pressure transients accelerate deformation by creating feedback loops between mechanical forces and fluid flow. These findings underscore the importance of saturation in controlling the dynamics of compaction localization and provide insights into the interplay between pore pressure, deformation, and permeability. The implications of this study extend to applications in geological storage, resource extraction, and subsurface geomechanics, offering a deeper understanding of coupled hydromechanical processes in porous rocks.

58 GEOSCIENCES↗
DOE OSTI2024

Group-theoretic error mitigation enabled by classical shadows and symmetries

Abstract Estimating expectation values is a key subroutine in quantum algorithms. Near-term implementations face two major challenges: a limited number of samples required to learn a large collection of observables, and the accumulation of errors in devices without quantum error correction. To address these challenges simultaneously, we develop a quantum error-mitigation strategy called symmetry-adjusted classical shadows , by adjusting classical-shadow tomography according to how symmetries are corrupted by device errors. As a concrete example, we highlight global U(1) symmetry, which manifests in fermions as particle number and in spins as total magnetization, and illustrate their group-theoretic unification with respective classical-shadow protocols. We establish rigorous sampling bounds under readout errors obeying minimal assumptions, and perform numerical experiments with a more comprehensive model of gate-level errors derived from existing quantum processors. Our results reveal symmetry-adjusted classical shadows as a low-cost strategy to mitigate errors from noisy quantum experiments in the ubiquitous presence of symmetry.

Zhao, Andrew (ORCID:0000000202990277)↗
DOE OSTI2026

Hamiltonian simulation in Zeno subspaces

Here, we investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an ancilla qubit register can be used to simulate quantum dynamics on a target qubit register with a circuit complexity similar to randomized approaches. The classical sampling overhead in the latter approaches is traded for ancilla qubit overhead in Zeno-based approaches. A second-order Zeno sequence is developed to improve scaling and implementations through unitary kicks are discussed. We derive rigorous error bounds that allow for identifying the associated circuit complexities for the first- and second-order Zeno sequences. We show that the circuits over the combined register can be identified as a subroutine commonly used in post-Trotter Hamiltonian simulation methods. We build on this observation to reveal connections between different Hamiltonian simulation algorithms.

Hamiltonian simulation↗