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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 1,549 records · Page 86

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DOE OSTI2020

Ultrafast structural response to charge redistribution within a photosinthetic reaction centre

This data set contains stream files, difference maps and SVD maps obtained from data processing of time-resolved serial femtosecond crystallography measurements performed at LCLS XFEL, used to construct the images and perform the analysis published in the paper "Ultrafast structural response to charge redistribution within a photosinthetic reaction centre". Two (2) time points plus a dark state from 2015 ('a' label) as well as five (5) time points plus a dark state from 2016 ('b' label) are provided.

CXI↗

DOE OSTI2018

Berkeley Nuclear Data Cloud (BDC) v2.3

The software was developed to serve and curate arbitrarily large datasets comprising data acquired from various mobile platforms. The software is contained in a number of server and client libraries. The former manage the ingestion, indexing, querying, and serving of the data. The latter libraries are distributed for Linux, Mac OSX, and Windows and enable users to interact with data downloaded from the service either in the form of an HDF5 file or streamed in a BSON data chunk. Using the Berkeley Data Cloud, researchers from varying fields can collaborate, compare results and curate both their raw data and the derived products of their analysis.

Cholia, Shreyas↗

DOE OSTI2021

In Situ Inference for Earth System Predictability

An understanding of future evolution in precipitation extremes is critical to numerous DOE mission questions. Extreme events are by nature short time-scale events that are difficult to diagnose in available model data. Accurate modeling of extreme events necessarily requires high spatial resolution at the storm scale locally. However, the environment in which storms grow is dependent on global, remote, processes. These complex spatiotemporal relationships are impossible to diagnose at resolutions required to accurately model storms responsible for extreme precipitation. At exascale, climate simulations will produce results at fine enough resolution to investigate these relationships. However, the resulting data from these simulations will be far too large to save for post-simulation analysis. We advocate for fitting statistical models inside the simulations as they run, a context known as in situ, which will facilitate scientific investigations using the full fine-scale data stream. Figure 1 shows an example of the type of model we could consider, a Bayesian hierarchical spatial regression model. Precipitation extremes at each grid cell are modeled using extreme value distributions. Since extremes are rare, fitting models to individual grid cells can result in high variance and poor estimates. Instead, the model can be made more robust by smoothing the parameters of the extreme value model across space. Additionally, the parameters themselves can be functionally linked to other variables elsewhere in the simulation. Thus, we can use the fine-scale data to build more robust models for extremes that link extreme behavior to other climate patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

In Situ Inference for Earth System Predictability

Focal Area: Focal Area 3: Insight gleaned from complex simulated data using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: An understanding of future evolution in precipitation extremes is critical to numerous DOE mission questions. Extreme events are by nature short time-scale events that are difficult to diagnose in available model data. Accurate modeling of extreme events necessarily requires high spatial resolution at the storm scale locally. However, the environment in which storms grow is dependent on global, remote, processes. These complex spatiotemporal relationships are impossible to diagnose at resolutions required to accurately model storms responsible for extreme precipitation. At exascale, climate simulations will produce results at fine enough resolution to investigate these relationships. However, the resulting data from these simulations will be far too large to save for post-simulation analysis. We advocate for fitting statistical models inside the simulations as they run, a context known as in situ, which will facilitate scientific investigations using the full fine-scale data stream. Figure 1 shows an example of the type of model we could consider, a Bayesian hierarchical spatial regression model. Precipitation extremes at each grid cell are modeled using extreme value distributions. Since extremes are rare, fitting models to individual grid cells can result in high variance and poor estimates. Instead, the model can be made more robust by smoothing the parameters of the extreme value model across space. Additionally, the parameters themselves can be functionally linked to other variables elsewhere in the simulation. Thus, we can use the fine-scale data to build more robust models for extremes that link extreme behavior to other climate patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Mechanistic Modeling of TEG Dehydrator Emissions in Oil and Gas Industry

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.

MAES↗

NASA NTRS1985

A zonal computational procedure adapted to the optimization of two-dimensional thrust augmentor inlets

A viscous-inviscid interaction methodology based on a zonal description of the flowfield is developed as a mean of predicting the performance of two-dimensional thrust augmenting ejectors. An inviscid zone comprising the irrotational flow about the device is patched together with a viscous zone containing the turbulent mixing flow. The inviscid region is computed by a higher order panel method, while an integral method is used for the description of the viscous part. A non-linear, constrained optimization study is undertaken for the design of the inlet region. In this study, the viscous-inviscid analysis is complemented with a boundary layer calculation to account for flow separation from the walls of the inlet region. The thrust-based Reynolds number as well as the free stream velocity are shown to be important parameters in the design of a thrust augmentor inlet.

Lund, T. S.↗

NASA NTRS1988

An explicit Runge-Kutta method for unsteady rotor/stator interaction

A quasi-three-dimensional rotor/stator analysis has been developed for blade-to-blade flows in turbomachinery. The analysis solves the unsteady Euler or thin-layer Navier-Stokes equations in a body-fitted coordinate system. It accounts for the effects of rotation, radius change, and stream-surface thickness. The Baldwin-Lomax eddy-viscosity model is used for turbulent flows. The equations are integrated in time using a four-stage Runge-Kutta scheme with a constant timestep. Results are shown for the first stage of the Space Shuttle Main Engine high pressure fuel turbopump. Euler and Navier-Stokes results are compared on the scaled single- and multi-passage machine. The method is relatively fast and the quasi-three-dimensional formulation is applicable to a wide range of turbomachinery geometries.

Jorgenson, Philip C. E.↗

NASA NTRS1988

An explicit Runge-Kutta method for unsteady rotor/stator interaction

Jorgenson, Philip C. E.↗

NASA NTRS1987

Contingency support using adaptive telemetry extractor and expert system technologies

The 'telemetry analysis logic for operations support' prototype system constitutes an expert system that is charged with contingency planning for the NASA Hubble Space Telescope (HST); this system has demonstrated the feasibility of using an adaptive telemetry extractor/reformatter that is integrated with an expert system. A test case generated by a simulator has demonstrated the reduction of the time required for analysis of a complex series of failures to a few minutes, from the hour usually required. The HST's telemetry extractor will be able to read real-time engineering telemetry streams and disk-based data. Telemetry format changes will be handled almost instantaneously.

Bryant, Thomas↗

NASA NTRS1988

Propulsive-jet flow field analysis using the three-dimensional Navier-Stokes equations

A three-dimensional Navier-Stokes code has been applied to the analysis of flow fields containing propulsive jets. Specifically, the application was made to a flow field containing a supersonic jet injected at an angle of 90 degrees to a subsonic free stream. Although wind tunnel data were available, the computational results were not readily comparable to the experimental data because of significant differences between the two plume trajectories. Reasons for the differences are suggested in the report and include: (1) incomplete convergence, (2) inadequate grid resolution in the high gradient regions, and (3) use of a low-order turbulence closure model.

Reed, C. L.↗

NASA NTRS1990

Evaluation of thermal loading on a methane injector at high pressure and temperature

Experimental and numerical analyses are conducted to determine the surface temperature on a methane fuel injector used to produce a high enthalpy test stream for a combustion-fed subscale wind tunnel facility. It was found that the ratio of the methane fuel injection velocity to the air stream velocity is a significant factor in the production of high injector surface temperatures which lead to rapid deterioration of the fuel injector structure. The numerical code utilized for the computational analysis was found to be representative of the experimentally measured data since the experimental trends were reproduced by the numerical simulation. The quantitative accuracy of the numerical predictions could not be assessed from the data gathered because of the difficulty of making a noninterfering injector surface temperature measurement. The numerical code can be used for parametric evaluation of combustor parameters and thus will serve as an important tool in the design of such fuel injector systems.

Harvin, Stephen F.↗

NASA NTRS1994

The controlled ecological life support system Antarctic analog project: Analysis of wastewater from the South Pole Station, Antarctica, volume 1

The Controlled Ecological Life Support system (CELSS) Antarctic Analog Project (CAAP) is a joint National Science Foundation (NSF) and NASA project for the development, deployment and operation of CELSS technologies at the Amundsen-Scott South Pole Station. NASA goals are operational testing of CELSS technologies and the conduct of scientific studies to facilitate technology selection and system design. The NSF goals are that the food production, water purification, and waste treatment capabilities which will be provided by CAAP will improve the quality of life for the South Pole inhabitants, reduce logistics dependence, and minimize environmental impacts associated with human presence on the polar plateau. This report presents an analysis of wastewater samples taken from the Amundsen-Scott South Pole Station, Antarctica. The purpose of the work is to develop a quantitative understanding of the characteristics of domestic sewage streams at the South Pole Station. This information will contribute to the design of a proposed plant growth/waste treatment system which is part of the CELSS Antarctic Analog Project (CAAP).

Flynn, Michael T.↗

NASA NTRS1995

Forced Convection and Sedimentation Past a Flat Plate

The steady laminar flow of a well-mixed suspension of monodisperse solid spheres, convected steadily past a horizontal flat plate and sedimenting under the action of gravity, is examined. It is shown that, in the limit as Re approaches infinity and epsilon approaches 0, where Re is the bulk Reynolds number and epsilon is the ratio of the particle radius a to the characteristic length scale L, the analysis for determining the particle concentration profile has several aspects in common with that of obtaining the temperature profile in forced-convection heat transfer from a wall to a fluid stream moving at high Reynolds and Prandtl numbers. Specifically, it is found that the particle concentration remains uniform throughout the O(Re(exp -1/2)) thick Blasius boundary layer except for two O(epsilon(exp 2/3)) thin regions on either side of the plate, where the concentration profile becomes non-uniform owing to the presence of shear-induced particle diffusion which balances the particle flux due to convection and sedimentation. The system of equations within this concentration boundary layer admits a similarity solution near the leading edge of the plate, according to which the particle concentration along the top surface of the plate increases from its value in the free stream by an amount proportional to X(exp 5/6), with X measuring the distance along the plate, and decreases in a similar fashion along the underside. But, unlike the case of gravity settling on an inclined plate in the absence of a bulk flow at infinity considered earlier, here the concentration profile remains continuous everywhere. For values of X beyond the region near the leading edge, the particle concentration profile is obtained through the numerical solution of the relevant equations. It is found that, as predicted from the similarity solution, there exists a value of X at which the particle concentration along the top side of the plate attains its maximum value phi(sub m) and that, beyond this point, a stagnant sediment layer will form that grows steadily in time. This critical value of X is computed as a function of phi(sub s), the particle volume fraction in the free stream. In contrast, but again in conformity with the similarity solution, for values of X sufficiently far removed from the leading edge along the underside of the plate, a particle-free region is predicted to form adjacent to the plate. This model, with minor modifications, can be used to describe particle migration in other shear flows, as, for example, in the case of crossflow microfiltration.

Pelekasis, Nikolaos A.↗

DOE OSTI2012

Humidified Gas Stream Separations at High Temperat

Most industrially relevant high temperature gas se

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗

NASA NTRS1997

An Analysis of the Pressures, Forces and Moments Induced by the Ground Vortex Generated by a Single Impinging Jet

When a jet STOVL aircraft is in STOL operation the jets impinge on the ground and generate wall jets flowing radially outward from the points at which the jets impinge. When the forward flowing part of a wall jet meets the free stream flow it is rolled back on itself forming a parabolic shaped ground vortex. Positive pressures are induced on the lower surface of the configuration ahead of the ground vortex and suction pressures are induced over the ground vortex itself. In addition, the suction pressures induced aft of the jet out of ground effect are reduced and lifting pressures are induced on the upper surface. This study analyzes available pressure and force data and develops a method for estimating the forces and moments induced in ground effect. The method includes the effects of configuration variables, height and operating conditions, as well as the effects of the location, deflection and shape of the jet. However, it is limited to single jets at subcritical nozzle pressure ratios. An analysis of the effects of moving over the ground vs. tests over a fixed ground plane is included.

Kuhn, Richard E.↗

DOE OSTI2018

Text-based Analytics for Biosurveillance

The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when). The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when).

Biomedical NLP↗

DOE OSTI2021

Self-interacting neutrinos, the Hubble parameter tension, and the cosmic microwave background

Here, we perform a comprehensive study of cosmological constraints on nonstandard neutrino self-interactions using cosmic microwave background and baryon acoustic oscillation data. We consider different scenarios for neutrino self-interactions distinguished by the fraction of neutrino states allowed to participate in self-interactions and how the relativistic energy density, N eff , is allowed to vary. Specifically, we study cases in which all neutrino states self-interact and N eff varies; two species free-stream, which we show alleviates tension with laboratory constraints, while the energy in the additional interacting states varies; and a variable fraction of neutrinos self-interact with either the total N eff fixed to the Standard Model value or allowed to vary. In no case do we find compelling evidence for new neutrino interactions or nonstandard values of N eff . In several cases, we find additional modes with neutrino decoupling occurring at lower redshifts z dec ~ 10 3–4 . We do a careful analysis to examine whether new neutrino self-interactions solve or alleviate the so-called H 0 tension and find that, when all Planck 2018 CMB temperature and polarization data are included, none of these examples eases the tension more than allowing a variable N eff comprised of free-streaming particles. Although we focus on neutrino interactions, these constraints are applicable to any light relic particle.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗