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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 523 records · Page 29

Adsorptive denitrogenation of model aviation fuel using mesoporous silica in a packed bed adsorption system

This study aims to understand the effects of system process parameters such as flow rate, adsorbent particle size, and use of recycled adsorbent on denitrogenation performance of a model fuel using mesoporous silica gel. The goal is to reduce the nitrogen content of the model fuel from 1500 parts per million to single-digit ppm to meet ASTM specifications for drop-in fuels. This work was done with the intent of applying adsorptive denitrogenation to sustainable aviation fuel (SAF) product fractions produced via hydrothermal liquefaction (HTL). The adsorption performance of the silica is evaluated via packed column breakthrough data, with data generated from collecting from the column outlet and quantifying nitrogen content via gas chromatography. Select experiments use a significantly larger (2.5x column diameter and length) column to demonstrate linear scalability of the process. Thermogravimetric analysis data is collected to evaluate the effects of thermal calcination as a sorbent regeneration method. Effects of a more complex feed are also investigated using a known reference fuel with additional added nitrogen containing compounds. The results presented in this work successfully demonstrate up to 99.8 % removal of NCCs from a model fuel fraction at an original NCC concentration of approximately 1500 ppm to single-digit parts per million after treatment. We also examine calcination of sorbent materials to remove the adsorbed species to enable sorbent reuse and minimize waste generation and show that the calcined material can be reused up to 5 cycles with reduced adsorption capacity. Overall, this work indicates that adsorptive denitrogenation using silica gel is a viable solution to enable the integration of HTL-derived aviation fuels into existing fuel infrastructure.

Adsorption techniques↗

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗

The Effect of Planetary Albedo on Solar Orientation of Spacecraft

The analytical expression for the solar orientation error caused by planetary albedo is derived. A typical solar sensor output characteristic is assumed and a computer solution to the analytical is obtained. The computer results are presented for a spacecraft in the vicinity of Earth, Venus, Mars, and the Moon. Each planetary body is assumed to be a spherical diffuse reflector with cylindrical shadows and a constant albedo. The data generated herein permit the selection of an appropriate coarse-sensor to fine-sensor switching angle for solar orientation control systems and facilitate the the interpretation of solar-referenced scientific experiment data.

SPACE ORIENTATION↗

Probabilistic-graphical and phenomenological analysis of combined bending-torsion fatigue reliability data

Fatigue data generated by three combined bending-torsion fatigue reliability research machines at The University of Arizona are probabilistic-graphically and phenomenologically analyzed. Distributions that are applicable to fatique life and static strength data are discussed. Phenomenological justifications for the use of these distributions are presented. It is found that the normal distribution represents the cycles-to-failure data at the highest stress levels best. The lognormal distribution appears to fit the cycles-to-failure data at the lower stress levels best and quite well at all stress levels including the highest. A regression analysis and least-squares goodness-of-fit test was performed for normal and lognormal plots. In most cases, the correlation coefficient gave a better fit to the data using the normal distribution, but the difference between the two was so slight that positive discrimination could not be made.

Kececioglu, D.↗

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗

Capabilities and History of NASA Marshall Space Flight Center's Hydrogen Test Facility

The Hydrogen Test Facility (HTF) has conducted mechanical testing for aerospace materials at NASA's Marshall Space Flight Center for many years. One of the first facilities of its kind to run high-pressure cryogenic permeability tests in liquid hydrogen, HTF is now characterized as a unique national resource capable of overcoming hazardous conditions to perform tests directly in various hydrogen environments. At HTF, custom test systems are operated in eight structurally reinforced test cells from 0 to 68,948 kPa (0 to 10,000 psi) at -253 to 982 C (--423 to 1800 F) in hydrogen, air, helium, and nitrogen, with other environments available upon request. Standard mechanical procedures include compression, fatigue crack growth rate, four-point bend, high/low cycle fatigue, fracture toughness, shear, strain-to-crack, and tensile testing. Cryogenic permeability and thermal conductivity and gaseous creep testing are offered, as well as simulated service under different combinations of operating environment(s), stress, pressure, and ambient-to-extreme temperatures. Advanced tests are routinely developed upon demand, and special component testing is also available. Current efforts include the renovation of two high-pressure gaseous test cells to generate data for a J-2X engine designed for Constellation's Ares I and V vehicles. In the past, HTF has supported other critical NASA programs, such as Apollo, Space Shuttle, and Next Generation Launch Technologies. During the 1990's, hundreds of tests were conducted in liquid hydrogen and liquid nitrogen during development of the Space Shuttle's super lightweight tank, which provided the thrust required to achieve low Earth orbit for the International Space Station. This facility was designed and built in 1963. Originally called the Low Temperature Test Facility, it became known as the Cryogenic Test Facility in the late 1980's and HTF in the early 1990's.

Malone, T. W.↗

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.

36 MATERIALS SCIENCE↗

Event-driven displays for manipulator control

The problem of constructing event-related information displays from multidimensional data generated by proximity, force-torque and tactile sensors integrated with the terminal device of a remotely controlled manipulator is considered. Event-driven displays are constructed by using appropriate algorithms acting on sensory data in real time. Event-driven information displays lessen the operator's workload and improve control performance. The paper describes and discusses several event-driven display examples that were implemented in the JPL teleoperator project, including a brief outline of the data handling system which drives the graphics display in real time. The paper concludes with a discussion of future plans to integrate event-driven displays with visual (TV) information.

Bejczy, A. K.↗

Characterization of radiation-induced damage in high performance polymers by electron paramagnetic resonance imaging spectroscopy

The potential for long-term human activity beyond the Earth's protective magnetosphere is limited in part by the lack of detailed information on the effectiveness and performance of existing structural materials to shield the crew and spacecraft from highly penetrating space radiations. The two radiations of greatest concern are high energy protons emitted during solar flares and galactic cosmic rays which are energetic ions ranging from protons to highly oxidized iron. Although the interactions of such high-energy radiations with matter are not completely understood at this time, the effects of the incident radiation are clearly expected to include the formation of paramagnetic spin centers via ionization and bond-scission reactions in the molecular matrices of structural materials. Since this type of radiation damage is readily characterized by Electron Paramagnetic Resonance (EPR) spectroscopy, the NASA Langley Research Center EPR system was repaired and brought on-line during the 1991 ASEE term. A major goal of the 1992 ASEE term was to adapt the existing core of the LaRC EPR system to meet the requirements for EPR Imaging--a powerful new technique which provides detailed information on the internal structure of materials by mapping the spatial distribution of unpaired spin density in bulk media. Major impetus for this adaptation arises from the fact that information derived from EPRI complements other methods such as scanning electron microscopy which primarily characterize surface phenomena. The modification of the EPR system has been initiated by the construction of specially designed, counterwound Helmholtz coils which will be mounted on the main EPR electromagnet. The specifications of the coils have been set to achieve a static linear magnetic field gradient of 10 gauss/mm/amp along the principal (Z) axis of the Zeeman field. Construction is also in progress of a paramagnetic standard in which the spin distribution is known in all three dimensions. This sample will be used to assess the linearity of the magnetic field gradient and to ensure authentic image reconstruction. A second major task was to secure the computer capability to enable image reconstruction from projection data generated by the magnetic field gradients. To this end, commercially available and public domain software packages which perform inverse Fourier Transform and convoluted (filtered) back projection functions are being integrated into the existing EPR data processing system.

Suleman, Naushadalli K.↗

Use of the Matching Pursuit Algorithm for Flight Flutter Test Data Analysis

The goal of flight flutter testing is to detect possibly destructive modes of aircraft vibration which may arise during flight from interaction of aerodynamic forces with structural dynamic properties of the airframe. This is typically accomplished by exciting the airframe with a time varying force and monitoring the response of the aircraft throughout its flight envelope. The data generated must be analyzed and presented so that the frequency and time of occurrence of excited modes are clearly and unambiguously displayed. Processing and display in near real time is also desirable. Display of data in the time-frequency plane is a natural choice because it is a familiar and intuitive framework. The Matching Pursuit algorithm provides a time-frequency analysis with good adaptability to signal structure and good signal representation in the time-frequency plane. Improvements in efficiency are needed before the algorithm can be used in real time, however.

Nelson, Ronald E.↗

Correlation of Chemical and Physical Test Data For the Environment Ageing of Coflon (PVDF)

This report aims to identify correlations between mechanical property changes and chemical/morphological structure changes for Coflon. It is intended both to illustrate the overall methodology and to indicate the testing that needs to be undertaken in order to obtain correlations. Many fluid exposures have now been carried out on Coflon during the project and many data generated as a result. The report summarises the changes observed in mechanical and physical properties and relates these as well as possible to the chemistry thought to be occurring during ageing. For this purpose, data have been collated from already-issued MERL and TRI technical and progress reports. Most of the mechanical testing of aged testpieces has been performed soon after the completion of the exposure; however, there is of necessity a delay in obtaining chemical analysis of the same testpieces, so that more physical than chemical data are shown. Three fluids have so far caused measurable deterioration of Coflon, these being: methanol (Fluid A), a methanol and amine mixture (Fluid G), and a mixture of methane, carbon dioxide gas and hydrogen sulphide gas plus aqueous amine (Fluid F). Only the effects of these fluids will be dealt with in any detail in this report, although other fluids are assessed to give relevant background information. Relevant test data collated here include: tensile modulus and related properties, mode of sample failure at break, fracture toughness, fatigue crack growth rate and resistance, stress relaxation rate, permeation coefficients, % crystallinity and molecular weight distributions together with changes in fluorine levels, and other observations where appropriate. However, not all of these were obtained for every ageing condition. Because of the wide range of tests employed, and the different ways in which their results are obtained, the following section has been included to serve as a background for making comparisons.

Morgan, G. J.↗

Methodology of Blade Unsteady Pressure Measurement in the NASA Transonic Flutter Cascade

In this report the methodology adopted to measure unsteady pressures on blade surfaces in the NASA Transonic Flutter Cascade under conditions of simulated blade flutter is described. The previous work done in this cascade reported that the oscillating cascade produced waves, which for some interblade phase angles reflected off the wind tunnel walls back into the cascade, interfered with the cascade unsteady aerodynamics, and contaminated the acquired data. To alleviate the problems with data contamination due to the back wall interference, a method of influence coefficients was selected for the future unsteady work in this cascade. In this approach only one blade in the cascade is oscillated at a time. The majority of the report is concerned with the experimental technique used and the experimental data generated in the facility. The report presents a list of all test conditions for the small amplitude of blade oscillations, and shows examples of some of the results achieved. The report does not discuss data analysis procedures like ensemble averaging, frequency analysis, and unsteady blade loading diagrams reconstructed using the influence coefficient method. Finally, the report presents the lessons learned from this phase of the experimental effort, and suggests the improvements and directions of the experimental work for tests to be carried out for large oscillation amplitudes.

Lepicovsky, J.↗

Performance of a Space-Based Wavelet Compressor for Plasma Count Data on the MMS Fast Plasma Investigation

Data compression has been a staple of imaging instruments for years. Recently, plasma measurements have utilized compression with relatively low compression ratios. The Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale (MMS) mission generates data roughly 100 times faster than previous plasma instruments, requiring a higher compression ratio to fit within the telemetry allocation. This study investigates the performance of a space-based compression standard employing a Discrete Wavelet Transform and a Bit Plane Encoder (DWT/BPE) in compressing FPI plasma count data. Data from the first 6 months of FPI operation are analyzed to explore the error modes evident in the data and how to adapt to them. While approximately half of the Dual Electron Spectrometer (DES) maps had some level of loss, it was found that there is little effect on the plasma moments and that errors present in individual sky maps are typically minor. The majority of Dual Ion Spectrometer burst sky maps compressed in a lossless fashion, with no error introduced during compression. Because of induced compression error, the size limit for DES burst images has been increased for Phase 1B. Additionally, it was found that the floating point compression mode yielded better results when images have significant compression error, leading to floating point mode being used for the fast survey mode of operation for Phase 1B. Despite the suggested tweaks, it was found that wavelet-based compression, and a DWT/BPE algorithm in particular, is highly suitable to data compression for plasma measurement instruments and can be recommended for future missions.

plasma↗

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗

National Aeronautics and Space Administration's (NASA) Third-Generation Tracking and Data Relay Satellites (TDRS)

NASA has contracted with Boeing to provide two third-generation Tracking and Data Relay Satellites (TDRS) designated TDRS K and L, with an option to provide two additional satellites designated TDRS M and N. These TDRS will be used to continue and enhance the user support services of the existing first- and second-generation TDRS spacecraft. The existing TDRS, in conjunction with the TDRS Ground Terminals at the White Sands NM Complex (WSC) and Guam, constitute the Tracking and Data Relay Satellite System (TDRSS). The TDRSS, with other supporting elements, is referred to as the Space Network (SN). The launch of the TDRS K is projected for 2012 with TDRS L planned to follow in 2013. The contract also provides for the modifications to the TDRS Ground Terminals at the WSC required for operation of the new TDRS. This paper provides an overview of the customer services provided by the existing and new TDRS. In addition, planned future customer services such as Bandwidth Efficient Modulation (BEM) and new coding schemes are briefly discussed.

Berndt, Allen K.↗

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

58 GEOSCIENCES↗

Reduced Order Model for Guided Wave Propagation on Gas Pipelines to Enable Real-Time Simulation

Reduced order model for simulation of Guided wave propagation is presented here. The utilization of reduced order models ensures efficient data generation for a variety of parameters where it takes huge computational effort to simulate, crucial for timely monitoring and decision-making. Autoencoder based reduced order models are proposed here, which are trained on simulated data from open-source finite element framework, Firedrake.

Bukka, Sandeep Reddy↗

Airborne Optical Communications Demonstrator Design And Preflight Test Results

A second generation optical communications demonstrator (OCD-2) intended for airborne applications like air-to-ground and air-to-air optical links is under development at JPL. This development provides the capability for unidirectional high data rate (2.5-Gbps) transmission at 1550-nm, with the ability to receive an 810-nm beacon to aid acquisition pointing and tracking. The transmitted beam width is nominally 200-(micro)rad. A 3x3 degree coarse field-of-view (FOV) acquisition sensor with a much smaller ~3-mrad FOV tracking sensor is incorporated. The OCD-2 optical head will be integrated to a high performance gimbal turret assembly capable of providing pointing stability of 5- microradians from an airborne platform. Other parts of OCD-2 include a cable harness, connecting the optical head in the gimbal turret assembly to a rugged electronics box. The electronics box will house: command and control processors, laser transmitter, data-generation-electronics, power conversion/distribution hardware and state-of-health monitors. The entire assembly will be integrated and laboratory tested prior to a planned flight demonstrations.

optical communications↗