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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 271 records · Page 15

Numerical simulation of supersonic inlets using a three-dimensional viscous flow analysis

A three dimensional fully viscous computer analysis was evaluated to determine its usefulness in the design of supersonic inlets. This procedure takes advantage of physical approximations to limit the high computer time and storage associated with complete Navier-Stokes solutions. Computed results are presented for a Mach 3.0 supersonic inlet with bleed and a Mach 7.4 hypersonic inlet. Good agreement was obtained between theory and data for both inlets. Results of a mesh sensitivity study are also shown.

Anderson, B. H.↗

Mapping Environmental Contaminants at Ray Mine, AZ

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

McCubbin, Ian↗

M2-SCREAM: A Stratospheric Composition Reanalysis of Aura MLS

Stratospheric composition and transport patterns are changing because of increasing greenhouse gas concentrations and declining levels of ozone depleting substances. Superimposed on forced trends are: dynamical variability at a range of time scales and unforeseen perturbations such as those resulting from injections of volcanic material and smoke from PyroCb events. Chemical reanalyses can be powerful tools for studying the composition of the stratosphere and disentangling forced responses from internal variability. This presentation introduces a new chemical reanalysis of stratospheric constituents developed and produced at NASA’s Global Modeling and Assimilation Office (GMAO) using the recently developed GMAO Constituent Data Assimilation System. Called the MERRA-2 Stratospheric Composition Reanalysis with Aura MLS (M2-SCREAM), this reanalysis consists of assimilated global three-dimensional fields of stratospheric ozone, water vapor, hydrogen chloride (HCl), nitric acid (HNO3) and nitrous oxide (N2O) mixing ratios and covers the period since the beginning of MLS observations in September 2004 to the present. M2-SCREAM assimilates version 4.2 MLS profiles of the five constituents alongside total ozone column from the Ozone Monitoring Instrument. The dynamics and tropospheric water vapor are constrained by assimilated meteorological fields from MERRA-2. The assimilated constituent fields and meteorology are provided to users at a 50-km horizontal resolution and a three-hourly frequency. Monthly analysis uncertainties and flags are also provided to the users. M2-SCREAM is an accurate and dynamically consistent high-resolution data record of the five constituents, all of which are of primary importance to stratospheric chemistry and transport studies. We will present a description of M2-SCREAM and selected results of a process-based evaluation of this product using independent data. As an illustration, we will discuss the perturbation to stratospheric composition from the eruption of Hunga Tonga–Hunga Ha'apai in January 2022 as seen in the reanalysis. We will also propose potential scientific applications of M2-SCREAM and outline plans for an upcoming comprehensive composition reanalysis that is being developed at NASA GMAO.

MERRA-2↗

LDRD Abbreviated report: High-Order General-Discrete-Ordinates Method Enabling Efficient Deterministic Transport in Hydrodynamic Simulations

Deterministic transport simulations for national-security and energy applications often operate in high-dimensional phase-space, where accuracy and cost both become major challenges. A common numerical artifact in such problems is the “ray-effect,” which appears as unphysical streaks. Beyond misinterpretation, these artifacts can contaminate tightly coupled physics, such as fluid dynamics, radiation-hydrodynamics, and laser-plasma interactions, eroding the predictive capability of entire multiphysics workflows. Our objective was to make high-dimension studies practical on modern hardware while mitigating the ray-effect without relying on prohibitively expensive sampling approaches such as Monte Carlo methods. We developed the Generic Discretization Library (GenDiL), a Graphics Processing Unit (GPU)-first framework that uses high-order Discontinuous Galerkin (DG) methods and matrix-free algorithms to reduce memory usage and improve computational efficiency, critical for phase-space simulations. GenDiL supports phase-space adaptivity in both mesh size and polynomial order (hp-adaptivity) to place resolution only where it is needed. A central capability is Local Dimensional Refinement (LDR), which couples lower-dimension continuum models to higher-dimension kinetic models through stable and conservative interfaces, so that high-fidelity physics is applied only in regions where it is essential. Building on the GenDiL framework, we developed the General SN (GSN) family of algorithms as a true generalization of the polar SN approach (discrete ordinates, often denoted SN). Rather than tying discrete ordinates to a specific polar change of coordinates, GSN formulates transport on an arbitrary change of coordinates chosen to reduce ray-effect. We studied two complementary variants: an analytic variant, where the coordinate map is prescribed in advance by a closed-form function; and a data-driven variant, where a quantity of interest, such as the net flux, guides the coordinate system. GenDiL provides the library infrastructure for efficient GPU execution, but the GSN concept is algorithmic and independent of any one library. Across representative high-dimension tests, including non-symmetric solutions, both variants delivered strong ray-effect mitigation at practical cost, moving four- to six-dimensional analysis toward repeatable, routine studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An analysis of the vapor flow and the heat conduction through the liquid-wick and pipe wall in a heat pipe with single or multiple heat sources

A numerical analysis is presented for the overall performance of heat pipes with single or multiple heat sources. The analysis includes the heat conduction in the wall and liquid-wick regions as well as the compressibility effect of the vapor inside the heat pipe. The two-dimensional elliptic governing equations in conjunction with the thermodynamic equilibrium relation and appropriate boundary conditions are solved numerically. The solutions are in agreement with existing experimental data for the vapor and wall temperatures at both low and high operating temperatures.

Chen, Ming-Ming↗

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

Distortion Representation of Forecast Errors for Model Skill Assessment and Objective Analysis

We proposed a novel characterization of errors for numerical weather predictions. In its simplest form we decompose the error into a part attributable to phase errors and a remainder. The phase error is represented in the same fashion as a velocity field and is required to vary slowly and smoothly with position. A general distortion representation allows for the displacement and amplification or bias correction of forecast anomalies. Characterizing and decomposing forecast error in this way has two important applications, which we term the assessment application and the objective analysis application. For the assessment application, our approach results in new objective measures of forecast skill which are more in line with subjective measures of forecast skill and which are useful in validating models and diagnosing their shortcomings. With regard to the objective analysis application, meteorological analysis schemes balance forecast error and observational error to obtain an optimal analysis. Presently, representations of the error covariance matrix used to measure the forecast error are severely limited. For the objective analysis application our approach will improve analyses by providing a more realistic measure of the forecast error. We expect, a priori, that our approach should greatly improve the utility of remotely sensed data which have relatively high horizontal resolution, but which are indirectly related to the conventional atmospheric variables. In this project, we are initially focusing on the assessment application, restricted to a realistic but univariate 2-dimensional situation. Specifically, we study the forecast errors of the sea level pressure (SLP) and 500 hPa geopotential height fields for forecasts of the short and medium range. Since the forecasts are generated by the GEOS (Goddard Earth Observing System) data assimilation system with and without ERS 1 scatterometer data, these preliminary studies serve several purposes. They (1) provide a testbed for the use of the distortion representation of forecast errors, (2) act as one means of validating the GEOS data assimilation system and (3) help to describe the impact of the ERS 1 scatterometer data.

Hoffman, Ross N.↗

UWB Tracking System Design with TDOA Algorithm

This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).

Ni, Jianjun↗

Analysis of Pyrolysis Products from Ablative TPS

NASA’s state-of-the-art ablative materials are composed of a three-dimensional network of carbon fibers impregnated with polymers that dissipate thermal energy through pyrolysis. A fundamental understanding of the decomposition mechanisms and pyrolysis product distributions of various classes of polymers is instrumental in the design of new ablative materials. Furthermore, innovative experiments are essential to the continuous modernization of material response models by providing high-fidelity data. Thus, an apparatus has been designed to measure pyrolysis products from polymers and composite materials by implementing in-situ mass spectrometric techniques. Initial results from experiments performed on siloxane resins and a common phenolic resin will be discussed. Both classes of polymers exhibit heating-rate-dependent decomposition mechanisms. At the onset of heating, phenolic polymers decompose through competitive reactions to form gaseous products and a carbonaceous char. Gas phase products of phenolic resins are typically composed of molecular hydrogen, water, and aromatic hydrocarbons. Pyrolysis products from siloxane polymers include molecular hydrogen, small molecules, and cyclic oligomers from the polymer.

Pyrolysis↗

In situ multi-tier auto-ignition detection applied to dual-fuel combustion simulations

Here we use an anomaly detection methodology that is centered on analyzing fourth-order joint moments (co-kurtosis), particularly focusing on its application in auto-ignition of combustion problems with large numbers of species. Unsupervised anomaly detection is challenging to generalize across problem types and domains. A recent technique, centered on analyzing information in the fourth-order joint moment co-kurtosis, has shown promise, especially for high-dimensional scientific data. In this work we present developments to the co-kurtosis based anomaly detection method needed to make it effective and scalable for large-scale distributed scientific data, such as those generated by massively parallel simulations. An in situ co-kurtosis algorithm is employed as the anomaly detection method for identifying ignition kernels in simulations of turbulent combustion. Here, we extend an existing methodology which identifies regions of the domain where anomalies are present, and add another tier of anomaly detection where the individual samples contributing to the anomaly are identified. We apply this algorithm on-the-fly to a variety of turbulent reacting flow problems and compare it to the widely used (but significantly more expensive) chemical explosive mode analysis (CEMA). We demonstrate the ability of the method to detect and identify the onset of low and high temperature ignition which can be used for computational steering, as chemical and combustion anomalies occur intermittently at spatio-temporal locations unknown a priori. Finally, we apply our lightweight in situ algorithm to an exascale high-fidelity simulation with a total of 2.4 Trillion degrees of freedom, performed using an adaptive mesh refinement solver. Furthermore, through a scalability analysis, we show that the relative computational cost of this in-situ anomaly detection algorithm compared to an iteration of the reacting flow solver is negligible.

97 MATHEMATICS AND COMPUTING↗

Utilizing 3D-DIC on Mars 2020 Rover Wheel Assembly: Test-Analysis Correlation

Following the successful implementation of full-field photogrammetry, more specifically three-dimensional Digital Image Correlation (3D-DIC), on the Mars 2020 Heat Shield Structural Failure Review assessment, 3D-DIC was selected as one of the primary measurement techniques for the Mars 2020 Rover wheel assembly qualification test at the NASA Jet Propulsion Laboratory (JPL). To validate the Rover wheel landing loads simulations, it was extremely important to have high confidence in the wheel models. Due to the large deformations and strains that the wheel would be subject to during landing, traditional instrumentation such as linear variable displacement transducers (LVDTs), electrical-resistance strain gages and string potentiometers, would not be sufficient on their own to provide all the necessary validation data. Therefore, the NASA Engineering and Safety Center (NESC) provided the 3D-DIC expertise and support to measure the high deformation and strain in the wheel flexures and qualify the overall structural response of the Mars 2020 rover wheel assembly. There were two key objectives for the photogrammetry technique: (1) monitor the wheel response in real-time, guarding against anomalous behavior and failure, and (2) provide test data for test-analysis correlation to validate and/or improve the high-fidelity computational model. The contents of this paper will focus on the challenges of applying 3D-DIC to the Mars 2020 Rover wheel assembly and how these challenges were overcome. Examples of test-analysis correlation during the stiffness characterization and structural qualification will be presented and discussed in detail. Experimental results were compared with the analysis and showed excellent agreement between the predicted behavior and helped validate the high-fidelity models.

Mars 2020 Rover Wheel↗

LSENS, a general chemical kinetics and sensitivity analysis code for homogeneous gas-phase reactions. 2: Code description and usage

LSENS, the Lewis General Chemical Kinetics Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 2 of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part 2 describes the code, how to modify it, and its usage, including preparation of the problem data file required to execute LSENS. Code usage is illustrated by several example problems, which further explain preparation of the problem data file and show how to obtain desired accuracy in the computed results. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions. Part 1 (NASA RP-1328) derives the governing equations describes the numerical solution procedures for the types of problems that can be solved by lSENS. Part 3 (NASA RP-1330) explains the kinetics and kinetics-plus-sensitivity-analysis problems supplied with LSENS and presents sample results.

Radhakrishnan, Krishnan↗

LSENS, A General Chemical Kinetics and Sensitivity Analysis Code for Homogeneous Gas-Phase Reactions: Code Description and Usage - Part 2

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part II of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part II describes the code, how to modify it, and its usage, including preparation of the problem data file required to execute LSENS. Code usage is illustrated by several example problems, which further explain preparation of the problem data file and show how to obtain desired accuracy in the computed results. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions. Part I (NASA RP-1328) derives the governing equations and describes the numerical solution procedures for the types of problems that can be solved by LSENS. Part III (NASA RP-1330) explains the kinetics and kinetics-plus-sensitivity-analysis problems supplied with LSENS and presents sample results.

Radhakrishnan, Krishnan↗

Helicopter Model Rotor-Blade Vortex Interaction Impulsive Noise: Scalability and Parametric Variations

Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade-vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model-scale data were compared with averaged full-scale, in-flight acoustic data under similar non-dimensional test conditions using an improved data analysis technique. At low advance ratios (mu = 0.164 - 0.194), the BVI impulsive noise data scale remarkably well in level, waveform, and directivity patterns. At moderate advance ratios (mu = 0.224 - 0.270), the scaling deteriorates, suggesting that the model-scale rotor is not adequately simulating the full-scale BVI noise. Presently, no proved explanation of this discrepancy exists. Measured BVI noise radiation is highly sensitive to all of the four governing nondimensional parameters--hover tip Mach number, advance ratio, local inflow ratio, and thrust coefficient.

Boxwell, D. A.↗

26th Space Simulation Conference Proceedings. Environmental Testing: The Path Forward

Topics covered include: A Multifunctional Space Environment Simulation Facility for Accelerated Spacecraft Materials Testing; Exposure of Spacecraft Surface Coatings in a Simulated GEO Radiation Environment; Gravity-Offloading System for Large-Displacement Ground Testing of Spacecraft Mechanisms; Microscopic Shutters Controlled by cRIO in Sounding Rocket; Application of a Physics-Based Stabilization Criterion to Flight System Thermal Testing; Upgrade of a Thermal Vacuum Chamber for 20 Kelvin Operations; A New Approach to Improve the Uniformity of Solar Simulator; A Perfect Space Simulation Storm; A Planetary Environmental Simulator/Test Facility; Collimation Mirror Segment Refurbishment inside ESA s Large Space; Space Simulation of the CBERS 3 and 4 Satellite Thermal Model in the New Brazilian 6x8m Thermal Vacuum Chamber; The Certification of Environmental Chambers for Testing Flight Hardware; Space Systems Environmental Test Facility Database (SSETFD), Website Development Status; Wallops Flight Facility: Current and Future Test Capabilities for Suborbital and Orbital Projects; Force Limited Vibration Testing of JWST NIRSpec Instrument Using Strain Gages; Investigation of Acoustic Field Uniformity in Direct Field Acoustic Testing; Recent Developments in Direct Field Acoustic Testing; Assembly, Integration and Test Centre in Malaysia: Integration between Building Construction Works and Equipment Installation; Complex Ground Support Equipment for Satellite Thermal Vacuum Test; Effect of Charging Electron Exposure on 1064nm Transmission through Bare Sapphire Optics and SiO2 over HfO2 AR-Coated Sapphire Optics; Environmental Testing Activities and Capabilities for Turkish Space Industry; Integrated Circuit Reliability Simulation in Space Environments; Micrometeoroid Impacts and Optical Scatter in Space Environment; Overcoming Unintended Consequences of Ambient Pressure Thermal Cycling Environmental Tests; Performance and Functionality Improvements to Next Generation Thermal Vacuum Control System; Robotic Lunar Lander Development Project: Three-Dimensional Dynamic Stability Testing and Analysis; Thermal Physical Properties of Thermal Coatings for Spacecraft in Wide Range of Environmental Conditions: Experimental and Theoretical Study; Molecular Contamination Generated in Thermal Vacuum Chambers; Preventing Cross Contamination of Hardware in Thermal Vacuum Chambers; Towards Validation of Particulate Transport Code; Updated Trends in Materials' Outgassing Technology; Electrical Power and Data Acquisition Setup for the CBER 3 and 4 Satellite TBT; Method of Obtaining High Resolution Intrinsic Wire Boom Damping Parameters for Multi-Body Dynamics Simulations; and Thermal Vacuum Testing with Scalable Software Developed In-House.

Packard, Edward A.↗

Analysis of Pyrolysis Products from Ablative Thermal Protection Systems

NASA’s state-of-the-art ablative materials are composed of a three-dimensional network of carbon fibers impregnated with polymers that dissipate thermal energy through pyrolysis. A fundamental understanding of the decomposition mechanisms and pyrolysis product distributions of various classes of polymers is instrumental in the design of new ablative materials. Furthermore, innovative experiments are essential to the continuous modernization of material response models by providing high-fidelity data. Thus, an apparatus has been designed to measure pyrolysis products from polymers and composite materials by implementing in-situ mass spectrometric techniques. Initial results from experiments performed on siloxane resins and a common phenolic resin will be discussed. Both classes of polymers exhibit heating-rate-dependent decomposition mechanisms. At the onset of heating, phenolic polymers decompose through competitive reactions to form gaseous products and a carbonaceous char. Gas phase products of phenolic resins are typically composed of molecular hydrogen, water, and aromatic hydrocarbons. Pyrolysis products from siloxane polymers include molecular hydrogen, small molecules, and cyclic oligomers from the polymer backbone.

Pyrolysis↗

Finite element analysis of the Space Shuttle Main Engine (SSME) high pressure fuel turbopump turbine blade (HPFTP)

Cracking of the turbine blades of the SSME HPFTP is studied using two- and three-dimensional finite element analysis. The development and composition of the two- and three-dimensional models are described. Analyses are conducted under the speed, pressure, and thermal load conditions that occur during the full power level of the engine. The effects of friction on the two-dimensional model are examined. The strain and life cycle data reveal that the LCF cracking in the first stage is not probable unless the effects of fit-up tolerance between the blade and rotor are present, and for the second stage it is predicted that hydrogen assisted LCF cracking will occur under the present thermal environment. Design modifications to alleviate this cracking are discussed.

Lee, H. M.↗

Space shuttle orbit maneuvering engine reusable thrust chamber. Task 10: Data dump comparison of 8- and 10- inch diameter thrust chambers

An analytical and design study was conducted to compare the high and low contraction ratio thrust chambers for regenratively cooled orbit maneuvering engines for the space shuttle was conducted. The design concepts were evaluated on the basis of weight, pressure drop, and performance. Only the basic thrust chamber assembly was considered. The assembly consists of the injector, the regeneratively cooled thrust chamber, and the radiation cooled nozzle. A two dimensional thermal analysis of the channel section is provided.

Pauckert, R. P.↗