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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
DOE OSTI2021

Characterizing Long COVID: Deep Phenotype of a Complex Condition

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Funding: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2007

Robustness of Modeling of Out-of-Service Gas Mechanical Face Seal

Gas lubricated mechanical face seal are ubiquitous in many high performance applications such as compressors and gas turbines. The literature contains various analyses of seals having orderly face patterns (radial taper, waves, spiral grooves, etc.). These are useful for design purposes and for performance predictions. However, seals returning from service (or from testing) inevitably contain wear tracks and warped faces that depart from the aforementioned orderly patterns. Questions then arise as to the heat generated at the interface, leakage rates, axial displacement and tilts, minimum film thickness, contact forces, etc. This work describes an analysis of seals that may inherit any (i.e., random) face pattern. A comprehensive computer code is developed, based upon the Newton- Raphson method, which solves for the equilibrium of the axial force and tilting moments that are generated by asperity contact and fluid film effects. A contact mechanics model is incorporated along with a finite volume method that solves the compressible Reynolds equation. Results are presented for a production seal that has sustained a testing cycle.

Green, Itzhak↗
DOE OSTI2017

Reinventing Design Principles for Developing Low-Viscosity Carbon Dioxide-Binding Organic Liquids for Flue Gas Clean Up

Anthropogenic carbon dioxide (CO 2 ) emission from point sources, such as coal fired-power plants, account for the majority of the green houses gasses in the atmosphere. Capture, storage and utilization are required to mitigate adverse environmental effects. Aqueous amine-based CO 2 capture solvents are currently considered the industry standard, but deployment to market is limited by their high regeneration energy demand. In that context, energy efficient and less-viscous water-lean transformational solvent systems known as CO 2 Binding Organic Liquids (CO 2 BOLs) are being developed in our group to advance this technology to commercialization. Herein, we present a logical design approach based on fundamental concepts of organic chemistry and computer simulations aimed at lowering solvent viscosity. Conceptually, viscosity reduction would be achieved by systemmatic methods such as introduction of steric hindrance on the anion to minimize the intermolecular cation-anion interactions, fine tuning the electronics, hydrogen bonding orientation and strength, and charge solvation. Conventional standard trial-and-error approaches while effective, are time consuming and economically expensive. Herein, we rethink the metrics and design principles of low-viscosity CO 2 capture solvents using a combined synthesis and computational modeling approach. We critically study the impacts of modyfying factors such as as orientation of hydrogen bonding, introduction of higher degrees of freedom and cation or anion charge solvation and assess if or how each factor impacts viscosity of CO 2 BOL CO 2 capture solvents. Ultimately, we found that hydrogen bond orientation and strength is predominantly influencing the viscosity in CO 2 BOL solvents. With this knowledge, a new 1-MEIPADM-2-BOL CO 2 BOL variant was synthesized and tested, resulting in a solvent that is approximately 60% less viscous at 25 mol% CO 2 loading with respect to our base compound 1-IPADM-2-BOL. The insights gained from the current study redefines the fundamental concepts and understanding of what influences viscosity in concentrated organic CO 2 capture solvents.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Development of a Green Parabolic Trough Collector

This report describes in detail a research project that assesses the potential of a parabolic trough solar collector with a lumber construction to meet ambitious performance, cost, and durability goals. Instead of exploring lumber as a general question for solar collectors, the project focuses on the design optimization, laboratory testing, outdoor testing, and economic modeling of a particular scale of parabolic trough, namely, the 6m aperture and 12m long module that has become the standard in the utility-scale power plant market. As will be appreciated in the report, it is also a scale that matches well the capabilities of lumber as a structural material and the commonly available cross sections. The design and its analysis extend far beyond traditional considerations for wooden structures in the built environment, and includes a computationally efficient coupled structural-optical simulation and the empirical characterization of joint stiffness at small deformations. Laboratory testing is used to characterize cyclic joint behavior, accelerated weathering, and to validate the simulation used as the basis for building a full-scale prototype. The construction and outdoor testing of this prototype is described. A total installed cost model of the collector is presented and the impact of the cost is seen in the context of a full plant techno-economic model. The results of this model in combination with the experience with the first prototype suggest that with improvements to the design and assembly process, this collector type has the potential to lower the levelized cost of heat for industrial solar steam plants used for process heating or cogeneration.

14 SOLAR ENERGY↗
DOE OSTI2016

Using the automata processor for fast pattern recognition in high energy physics experiments. A proof of concept

Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

The small-voxel tracking algorithm for simulating chemical reactions among diffusing molecules

Simulating the evolution of a chemically reacting system using the bimolecular propensity function, as is done by the stochastic simulation algorithm and its reaction-diffusion extension, entails making statistically inspired guesses as to where the reactant molecules are at any given time. Those guesses will be physically justified if the system is dilute and well-mixed in the reactant molecules. Otherwise, an accurate simulation will require the extra effort and expense of keeping track of the positions of the reactant molecules as the system evolves. One molecule-tracking algorithm that pays careful attention to the physics of molecular diffusion is the enhanced Green's function reaction dynamics (eGFRD) of Takahashi, Tănase-Nicola, and ten Wolde [Proc. Natl. Acad. Sci. U.S.A. 107, 2473 (2010)]. We introduce here a molecule-tracking algorithm that has the same theoretical underpinnings and strategic aims as eGFRD, but a different implementation procedure. Called the small-voxel tracking algorithm (SVTA), it combines the well known voxel-hopping method for simulating molecular diffusion with a novel procedure for rectifying the unphysical predictions of the diffusion equation on the small spatiotemporal scale of molecular collisions. Indications are that the SVTA might be more computationally efficient than eGFRD for the problematic class of non-dilute systems. A widely applicable, user-friendly software implementation of the SVTA has yet to be developed, but we exhibit some simple examples which show that the algorithm is computationally feasible and gives plausible results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Extracting spinon self-energies from two-dimensional coherent spectroscopy

Two-dimensional coherent spectroscopy (2DCS) is a nonlinear spectroscopy technique capable of identifying whether apparent continua in linear response are made out of multiplets of sharp deconfined quasiparticles. This makes it a potent tool for experimental identification of fractionalized phases. Previous discussions have focused on limits where the quasiparticles in question are infinitely long lived. In this paper we discuss 2DCS in the regime where the fractionalized quasiparticles can themselves decay. We introduce a powerful path-integral-based approach, whereby the computation of nonlinear susceptibilities reduces to an efficient exercise in diagrammatic perturbation theory. Here, we apply this method to compute the 2DCS response of the one-dimensional transverse field Ising model, in the presence of integrability-breaking perturbations. We discuss aspects of the self-energy of the fractionalized quasiparticles that may be extracted via 2DCS, such as the momentum-dependent decay rate.

1-dimensional spin chains↗
NASA NTRS1978

Energy deposition in a gaseous mixture

Existing models in planetary aeronomy involve a variety of possible gaseous mixtures subjected to charged particle bombardment. In the present paper, a phenomenological approach to electron degradation in such mixtures is proposed to facilitate analysis of such problems. Existing parameterized yield spectra for a variety of gases, computed by a discrete energy bin method, are used as a basis for constructing a parameterized composite yield spectrum for an arbitrary mixture. The approach proposed is an improvement over the continuous slow-down approximation in that discreteness is taken into account phenomenologically. The advantages are in the ease of application to aeronomical problems involving variable mixtures.

Peterson, L. R.↗
NASA NTRS1982

Initial analysis of OSTA-1 ocean color experiment imagery

NASA's Ocean Color Experiment (OCE) was designed to map ocean features with an eight-channel scanning radiometer installed on the second flight of the Space Shuttle Columbia. Digital computer enhancement and band-ratio techniques were applied to radiometrically corrected spectral data in order to emphasize chlorophyll distribution patterns. Such a pattern was evident in the Yellow Sea between Korea and China, and the effects of discharge from the Yangtze and other rivers were also observed. Two scenes, from orbits 30 and 32, revealed the movement of plankton patches in the Gulf of Cadiz. Geometric correction of the images permitted ocean current velocities to be deduced, and water depth variability over the Grand Bahama Bank was estimated by means of OCE's blue-green channel. Bottom-reflected sunlight produced a sensor signal that was inversely related to water depth.

Kim, H. H.↗
NASA NTRS1979

Atomic oxygen between 80 and 120 km - Evidence for a latitudinal variation in vertical transport near the mesopause

Analysis of the OGO 6 OI green line nightglow photometer experiment has been carried out for eight cases when the alignment of the spacecraft was such that local emission rates could be determined below the altitude of maximum emission and down to about 80 km. The results obtained show that the vertical gradient of the emission rate between 95 and 80 km alternates between regions of very rapid variation and very slow variation spaced on a scale of 5-10 deg of latitude. Maps showing isoemissivity contours and isodensity contours for atomic oxygen concentration in vertical meridional planes are presented. The densities are computed under three assumptions concerning excitation mechanisms. Comparisons of the vertical variations of oxygen density with the results of a time dependent theory suggest the regions of strong downward transport alternate in latitude with regions of weak transport near 90 km. In the first case, conversion of O to O3 at night appears to be overwhelmed by downward transport of O.

Wasser, B.↗
NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) algorithm theoretical basis document: Geolocation, calibration, and ERBE-like analyses (subsystems 1-3) - volume 2

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 2 details the techniques used to geolocate and calibrate the CERES scanning radiometer measurements of shortwave and longwave radiance to invert the radiances to top-of-the-atmosphere (TOA) and surface fluxes following the Earth Radiation Budget Experiment (ERBE) approach, and to average the fluxes over various time and spatial scales to produce an ERBE-like product. Spacecraft ephemeris and sensor telemetry are used with calibration coefficients to produce a chronologically ordered data product called bidirectional scan (BDS) radiances. A spatially organized instrument Earth scan product is developed for the cloud-processing subsystem. The ERBE-like inversion subsystem converts BDS radiances to unfiltered instantaneous TOA and surface fluxes. The TOA fluxes are determined by using established ERBE techniques. Hourly TOA fluxes are computed from the instantaneous values by using ERBE methods. Hourly surface fluxes are estimated from TOA fluxes by using simple parameterizations based on recent research. The averaging process produces daily, monthly-hourly, and monthly means of TOA and surface fluxes at various scales. This product provides a continuation of the ERBE record.

Wielicki, B. A.↗
NASA NTRS1999

Engineering Overview of a Multidisciplinary HSCT Design Framework Using Medium-Fidelity Analysis Codes

An objective of the HPCC Program at NASA Langley has been to promote the use of advanced computing techniques to more rapidly solve the problem of multidisciplinary optimization of a supersonic transport configuration. As a result, a software system has been designed and is being implemented to integrate a set of existing discipline analysis codes, some of them CPU-intensive, into a distributed computational framework for the design of a High Speed Civil Transport (HSCT) configuration. The proposed paper will describe the engineering aspects of integrating these analysis codes and additional interface codes into an automated design system. The objective of the design problem is to optimize the aircraft weight for given mission conditions, range, and payload requirements, subject to aerodynamic, structural, and performance constraints. The design variables include both thicknesses of structural elements and geometric parameters that define the external aircraft shape. An optimization model has been adopted that uses the multidisciplinary analysis results and the derivatives of the solution with respect to the design variables to formulate a linearized model that provides input to the CONMIN optimization code, which outputs new values for the design variables. The analysis process begins by deriving the updated geometries and grids from the baseline geometries and grids using the new values for the design variables. This free-form deformation approach provides internal FEM (finite element method) grids that are consistent with aerodynamic surface grids. The next step involves using the derived FEM and section properties in a weights process to calculate detailed weights and the center of gravity location for specified flight conditions. The weights process computes the as-built weight, weight distribution, and weight sensitivities for given aircraft configurations at various mass cases. Currently, two mass cases are considered: cruise and gross take-off weight (GTOW). Weights information is obtained from correlations of data from three sources: 1) as-built initial structural and non-structural weights from an existing database, 2) theoretical FEM structural weights and sensitivities from Genesis, and 3) empirical as-built weight increments, non-structural weights, and weight sensitivities from FLOPS. For the aeroelastic analysis, a variable-fidelity aerodynamic analysis has been adopted. This approach uses infrequent CPU-intensive non-linear CFD to calculate a non-linear correction relative to a linear aero calculation for the same aerodynamic surface at an angle of attack that results in the same configuration lift. For efficiency, this nonlinear correction is applied after each subsequent linear aero solution during the iterations between the aerodynamic and structural analyses. Convergence is achieved when the vehicle shape being used for the aerodynamic calculations is consistent with the structural deformations caused by the aerodynamic loads. To make the structural analyses more efficient, a linearized structural deformation model has been adopted, in which a single stiffness matrix can be used to solve for the deformations under all the load conditions. Using the converged aerodynamic loads, a final set of structural analyses are performed to determine the stress distributions and the buckling conditions for constraint calculation. Performance constraints are obtained by running FLOPS using drag polars that are computed using results from non-linear corrections to the linear aero code plus several codes to provide drag increments due to skin friction, wave drag, and other miscellaneous drag contributions. The status of the integration effort will be presented in the proposed paper, and results will be provided that illustrate the degree of accuracy in the linearizations that have been employed.

Weston, R. P.↗
DOE OSTI2013

Microsegregation effects on the thermal conductivity of silicon-germanium alloys

A silicon-germanium (SiGe) alloy is a promising candidate for thermoelectric materials; while it shows a significantly reduced thermal conductivity (κ) as compared to pure Si and Ge, the κ values obtained from previous experiments and computations tend to be widely scattered. We present here a computational analysis of thermal transport in SiGe, particularly the effects of the local segregation (microsegregation) of alloying elements. Our nonequilibrium molecular dynamics simulations confirm the strong dependence of κ on the Si:Ge ratio and the occurrence of the minimum κ around Si{sub 0.8}Ge{sub 0.2}, consistent with existing experimental observations. Moreover, our study clearly demonstrates that the κ of Si{sub 0.8}Ge{sub 0.2} increases substantially and monotonically as Ge atoms undergo segregation; that is, the magnitude of alloy scattering is found to be sensitive to homogeneity in the distribution of alloying elements. Nonequilibrium Green's function analysis also shows that such microsegregation enhances phonon transmission due to the reduced number of scattering centers. The findings highlight that distribution homogeneity, along with composition, can be a critical factor in determining the κ of SiGe alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The EVcouplings Python framework for coevolutionary sequence analysis

Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Simulation of a Periodic Jet in a Crossflow with a RANS Solver Using an Unstructured Grid

A second-order unstructured-grid code, developed and used primarily for steady aerodynamic simulations, is applied to the synthetic jet in a cross flow. The code, FUN3D, is a vertex-centered finite-volume method originally developed by Anderson[1, 2], and is currently supported by members of the Fast Adaptive Aerospace Tools team at NASA Langley. Used primarily for design[3] and analysis[4] of steady aerodynamic configurations, FUN3D incorporates a discrete adjoint capability, and supports parallel computations using MPI. A detailed description of the FUN3D code can be found in the references given above. The code is under continuous development and contains a variety of flux splitting algorithms for the inviscid terms, two methods for computing gradients, several turbulence models, and several solution methodologies; all in varying states of development. Only the most robust and reliable components, based on experiences with steady aerodynamic simulations, were employed in this work. As applied in this work, FUN3D solves the Reynolds averaged Navier-Stokes equations using the one equation turbulence model of Spalart and Allmaras[5]. The spatial discretization is formed on unstructured meshes using a vertex-centered approach. The inviscid terms are evaluated by a flux-difference splitting formulation using least-squares reconstruction and Roe-type approximate Riemann fluxes. Green-Gauss gradient evaluations are used for viscous and turbulence modeling terms. The discrete spatial operator is combined with a backward time operator which is then solved iteratively using point or line Gauss-Seidel and local time stepping in a pseudo time. For steady flows, the physical time step is set to infinity and the pseudo time step is ramped up with the iteration count. A second-order backward in time operator is used for time accurate flows with 20 to 50 steps in the pseudo time applied at each physical time step. For this effort, FUN3D was modified to support spatially varying boundary and initial conditions, and unsteady boundary conditions. Also, a specialized in/out flow boundary condition was implemented to model the action of the diaphragm. This boundary condition is described below in more detail. The grids were generated using the internally developed codes GridEX[6] for meshing the surfaces and inviscid regions of the domain, and for CAD access; and MesherX[7] for meshing the viscous regions. Grid spacing in on the surfaces and in the inviscid regions are indirectly controlled by specifying sources. The viscous layers are generated using an advancing layer technique. MeshersX allows the user to control the spatial variation of the first step off the surface, growth rates, and the termination criterion by providing small problem dependent subroutines.

Atkins, H. L.↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗
NASA NTRSDate not supplied

A Green’s Function Sensor Fusion Approach for Evaluating Spacecraft Entry Heating From on-Board Thermal Instrumentation

During atmospheric entry, distributed thermal measurements are critical to enable the evaluation of heat loads on spacecraft thermal protection systems (TPS). In recent space exploration missions, Schmidt-Boelter-type heat flux gauges have been integrated into the TPS alongside conventional temperature measurement instrumentation to measure total (convective and radiative) and radiative heat transfer rates1,2. While direct heat flux sensors (HFS) are able to provide valuable information detailing the thermal loads experienced by spacecraft, the interpretation of these measurements in unsteady, convective environments requires a correction factor to account for local heating augmentations at the cold wall HFS surface2,3. Current efforts to estimate cold wall correction factors, and thus recover the hot wall TPS heat flux, rely on time-marching computational fluid dynamics (CFD) simulations2. Simulation-based methods are susceptible to large uncertainties, however, as they require estimations of vehicle trajectory, gas kinetics, wall catalysis models, and other flight conditions as input parameters2,4. Furthermore, CFD simulations are computationally expensive and cannot efficiently survey all possible entry scenarios, exacerbating the uncertainty of reconstructed hot wall heat flux values. These drawbacks motivate the development of alternative hot wall heat flux reconstruction methods that are not reliant on CFD-based correction factors.

Kenneth McAfee↗