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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Microfluidic Extraction of Biomarkers using Water as Solvent

A proposed device, denoted a miniature microfluidic biomarker extractor (mu-EX), would extract trace amounts of chemicals of interest from samples, such as soils and rocks. Traditionally, such extractions are performed on a large scale with hazardous organic solvents; each solvent capable of dissolving only those molecules lying within narrow ranges of specific chemical and physical characteristics that notably include volatility, electric charge, and polarity. In contrast, in the mu-EX, extractions could be performed by use of small amounts (typically between 0.1 and 100 L) of water as a universal solvent. As a rule of thumb, in order to enable solvation and extraction of molecules, it is necessary to use solvents that have polarity sufficiently close to the polarity of the target molecules. The mu-EX would make selection of specific organic solvents unnecessary, because mu-EX would exploit a unique property of liquid water: the possibility of tuning its polarity to match the polarity of organic solvents appropriate for extraction of molecules of interest. The change of the permittivity of water would be achieved by exploiting interactions between the translational states of water molecules and an imposed electromagnetic field in the frequency range of 300 to 600 GHz. On a molecular level, these interactions would result in disruption of the three-dimensional hydrogen-bonding network among liquid-water molecules and subsequent solvation and hydrolysis of target molecules. The mu-EX is expected to be an efficient means of hydrolyzing chemical bonds in complex macromolecules as well and, thus, enabling analysis of the building blocks of these complex chemical systems. The mu-EX device would include a microfluidic channel, part of which would lie within a waveguide coupled to an electronically tuned source of broad-band electromagnetic radiation in the frequency range from 300 to 600 GHz (see figure). The part of the microfluidic channel lying in the waveguide would constitute an interaction volume. The dimensions of the interaction volume would be chosen in accordance with the anticipated amount of solid sample material needed to ensure extraction of sufficient amount of target molecules for detection and analysis. By means that were not specified at the time of reporting the information for this article, the solid sample material would be placed in the interaction volume. Then the electromagnetic field would be imposed within the waveguide and water would be pumped through the interaction volume to effect the extraction.

Amashukeli, Xenia↗
NASA NTRSDate not supplied

Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗
NASA NTRSDate not supplied

Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗
DOE OSTI2019

Effects of Nucleus Density and Dendritic Growth Influenced by Ti and Nb on Solidification Structure of Fe-18 Pct Cr Ferritic Stainless Steel

The effects of nucleus density and dendritic growth influenced by Ti and Nb on the solidification structure of Fe-18 pct Cr ferritic stainless steel (FSS) ingots were investigated. The equiaxed zone ratios (EZR) were 8.5, 28.8, 67.5, and 57.3 pct in the blank, Nb-bearing, Ti-bearing, and Ti-Nb-bearing FSS ingots, respectively. The grain size was the smallest in the Ti-Nb-bearing ingot. Silicon oxide was present in the blank sample and Nb-bearing ingot, but the complex nuclei that were composed of TiO{sub x}-Ti(C, N) and TiO{sub x}-(Ti, Nb){sub x}(C, N){sub y} existed in the Ti-bearing and Ti-Nb-bearing ingots, respectively. The bulk density of the complex nucleus decreased by 70 pct when the Ti content decreased from 0.16 to 0.14 mass pct. Thermodynamic calculations indicate that the phase transformation from Ti{sub 3}O{sub 5} to Ti{sub 2}O{sub 3} was delayed in the ingot with a lower Ti content and that the Ti{sub 2}O{sub 3} shows more potential for TiN nucleation compared with Ti{sub 3}O{sub 5} according to the disregistry theory. The increased EZR mechanism was illustrated by a cellular-automaton–finite-element method with actual distribution statistics of the complex nucleus and dendritic-growth-kinetic analysis. The heterogeneous nucleation effect of the complex nucleus by Ti addition and the variations in dendritic-growth kinetics by Ti and Nb contribute to the EZR increase of FSS.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Kinetic principles of interaction of components in complex biological systems

A biomathematical analysis of component interaction in biological systems is given. Two primary types of systems are discussed - open systems and closed systems. The applicability of these systems to life support equipment in spacecraft is analyzed and formulae are provided to demonstrate the effect (theoretical) of closed and open systems in life support systems.

Rubin, A. B.↗
NASA NTRS1975

Solar activity and its relation to certain parameters of phenomena in the geophysical complex

Results of a detailed analysis of solar activity in 1957-1965 are compared with the data on solar activity with variations of cosmic ray activity, and geomagnetic, ionospheric and terrestrial currents. Cosmic ray variations are investigated with reference to the asymmetry of solar hemispheres. All storms in the IGY are classified and a symbolic diagram of the time sequence is drawn up.

Razmadze, T. S.↗
NASA NTRS1975

Jovian magnetic fields is complex, Pioneer 11 shows

An analysis of the magnetic field of the planet Jupiter is presented. The data are based on the information returned by Pioneer 11 space probe. It was determined that the magnetic field stretches across 9 million miles of space at some times and shrinks in volume by three-fourths or more at other times. It was also determined that electrons trapped in the magnetic field of Jupiter are 10,000 times more intense than those in the Van Allen radiation belts which circle the earth. Additional data were obtained on the polar regions, atmospheric circulation, and the nature of the moons.

Panagakos, N.↗
NASA NTRS1984

Three-dimensional transonic potential flow about complex 3-dimensional configurations

An analysis has been developed and a computer code written to predict three-dimensional subsonic or transonic potential flow fields about lifting or nonlifting configurations. Possible condfigurations include inlets, nacelles, nacelles with ground planes, S-ducts, turboprop nacelles, wings, and wing-pylon-nacelle combinations. The solution of the full partial differential equation for compressible potential flow written in terms of a velocity potential is obtained using finite differences, line relaxation, and multigrid. The analysis uses either a cylindrical or Cartesian coordinate system. The computational mesh is not body fitted. The analysis has been programmed in FORTRAN for both the CDC CYBER 203 and the CRAY-1 computers. Comparisons of computed results with experimental measurement are presented. Descriptions of the program input and output formats are included.

Reyhner, T. A.↗
NASA NTRSDate not supplied

Maximizing Spaceflight Biological Data with Omics Analytics: The NASA GeneLab Database

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

Sylvain Vincent Costes↗
NASA NTRSDate not supplied

GeneLab: The NASA System Biology Platform for Space Omics Repository, Analysis and Visualization

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

GeneLab↗
DOE OSTI2025

5f-Shell Covalency in Actinide Complexes

This talk will focus on the theoretical description & analysis of 5f-shell covalency in actinide complexes, as well as the manifestation of this covalency in spectroscopic parameters such as the pre-edge peak energies and intensities in X-ray absorption near-edge structure (XANES) and related types of spectra, or ligand NMR chemical shifts, according to quantum chemical calculations. We are now able to analyze 5f covalency in the context of the participating atomic orbitals, their energies and interactions in a given molecule, and their overlap. A related issue is the assignment of oxidation states. Examples that will be discussed in the talk are [AnCl6](2-) with An = U, Np, Pu, various organometallic complexes with U and Th, and a recently reported ‘berkelocene’ sandwich complex.

Autschbach, Jochen↗
NASA NTRS2009

Integrated Safety Analysis Tiers

Commercial partnerships and organizational constraints, combined with complex systems, may lead to division of hazard analysis across organizations. This division could cause important hazards to be overlooked, causes to be missed, controls for a hazard to be incomplete, or verifications to be inefficient. Each organization s team must understand at least one level beyond the interface sufficiently enough to comprehend integrated hazards. This paper will discuss various ways to properly divide analysis among organizations. The Ares I launch vehicle integrated safety analyses effort will be utilized to illustrate an approach that addresses the key issues and concerns arising from multiple analysis responsibilities.

Shackelford, Carla↗
DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗
NASA NTRS1981

Systems engineering challenges of the Space Shuttle

Problems encountered during the Space Shuttle's development that were due to the unique configuration of the vehicle are discussed. While conventional rocket space vehicles have been symmetric, greatly simplifying the analysis and integration of constituent elements, the Space Shuttle's combination of a winged orbiter with side-mounted solid rocket boosters and a large propellant tank presented a more complex system for the analysis and testing of ascent flight control, propulsion system, aerothermodynamics and structural dynamics. Attention is given first and second stage flight operations, return-to-launch-site, abort-once-around and abort-to-orbit mission modes, propulsion system and propulsion test development, and the aerothermodynamics of the external propellant tank and Orbiter.

Day, L. E.↗
NASA NTRS1997

Efficient Multidisciplinary Analysis Procedure Using Multi-Level Parallelization Approach

Multidisciplinary applications are suitable for parallel computing environment by adopting the domain decomposition method. Immediately, a multidisciplinary application can be parallelized by solving each discipline separately. In order to perform coupled multidisciplinary analysis, coupling of each discipline can be accomplished by exchanging boundary data at the interfaces. This is regarded as discipline-level parallelization. Next level could be a "coarse-grain" parallelization of each discipline, which mainly depends on the physical geometry and nature of each discipline. For example, it is almost impossible for structured-grid based computational fluid dynamics codes to do flow analysis of an aircraft by using a single grid because of the complexity of its configuration. Thus, multi-block grid is commonly used to describe the details of complex geometry. Similarly, in structural analysis, the structure is frequently subdivided into substructures. Thus, the computation of each subdomain can be easily parallelized since each subdomain is solved separately independent of other domains. The parallelization is accomplished by solving each subdomain separately on a separate processor and exchanging the boundary conditions at domain interfaces periodically. However, the physical decomposition of the domain introduces explicit boundary conditions at the domain interfaces. This is not desirable for critical areas such as those containing shock waves or flow separations. Thus, a "fine-grain" parallelization is introduced to overcome this problem. The "fine-grain" parallelization is one that solves exactly the same system of equations of a subdomain by using more than one processors without introducing any explicit boundary conditions. An efficient multidisciplinary analysis procedure can be accomplished by successfully combining the above multi-level parallelism. A multidisciplinary analysis code, ENSAERO developed at NASA Ames Research Center is used in this study to implement the proposed approach. The communication data structure required for the proposed approach will be studied in detail. This work will demonstrate the feasibility of using multi-level parallelization approach in multidisciplinary analysis applications.

Byun, Chansup↗
DOE OSTI2019

Scoping Sampling at the Site 300 Water Line Project: Soil Sampling and Analysis Plan/Quality Assurance Plan

Lawrence Liverniore National Laboratory’s (LLNL) Mechanical Utilities Division (MUD) is currently scoping a project with the Project Management Office (PMO) Experimental Test Site 300 (S300) to install/upgrade roughly six miles of water line along established roads within the complex. This Sampling and Analysis Plan (SAP) outlines the requirements to collect an initial round of soil samples from the proposed alignment of the water line to provide preliminary data and information that can be used during project design. The samples will be submitted to an offsite contract laboratory for analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil Carbon and Nitrogen Elemental Analysis and Middle Infrared Spectroscopy from the Kougarok Fire Complex, Seward Peninsula, Alaska, 2022

In September and October of 2022, soil samples were collected at the Kougarok Fire Complex near mile marker 86 of the Nome-Taylor Highway on the Seward Peninsula of Alaska. This study site was chosen due to its unique fire history, as the Kougarok Fire Complex has experienced multiple wildfires since 1971. As the Arctic warms, the risk of Arctic tundra fires continues to increase due to warmer summer temperatures and higher frequency of lightning. Burned soil carbon or pyrogenic carbon (PyC) is an important component of C cycling after wildfire, and one that is often overlooked in tundra systems where wildfires are historically rare. To better understand PyC signatures and quantify PyC presence in post-regeneration permafrost regions, soils were sampled from soil pits within the 1971, 2002, and 2019 burn sites, as well as two unburned control sites. At each site, three soil pits were dug to the permafrost table. Soil samples were collected with a trowel from the face of each pit at 10 cm increments down to the permafrost table. Thaw depth, maximum vegetation height, vegetation species composition, and O horizon depth were also collected at each soil pit. An HS2 Hydrosense II Handheld Soil Moisture Sensor was used to collect volumetric soil moisture content at each 10 cm sampling increment. This dataset includes one *.csv of middle infrared spectroscopy measurements of soil samples, one *.csv of field observations, one *.csv of carbon and nitrogen analysis of soil samples, and one *.kml of sampling locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗