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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Assessment of Different Discrete Particle Methods Ability To Predict Gas-Particle Flow in a Small-Scale Fluidized Bed

Several discrete particle methods exist in the open literature to simulate fluidized bed systems, such as discrete element method (DEM), time driven hard sphere (TDHS), coarse-grained particle method (CGPM), coarse grained hard sphere (CGHS), and multi-phase particle-in-cell (MP-PIC). These different approaches usually solve the fluid phase in a Eulerian fixed frame of reference and the particle phase using the Lagrangian method. The first difference between these models lies in tracking either real particles or lumped parcels. The second difference is in the treatment of particle-particle interactions: by calculating collision forces (DEM and CGPM), using momentum conservation laws (TDHS and CGHS), or based on particle stress model (MP-PIC). These major model differences lead to a wide range of results accuracy and computation speed. However, these models have never been compared directly using the same experimental dataset. In this research, a small-scale fluidized bed is simulated with these methods using the same open-source code MFIX. The results indicate that modeling the particle-particle collision by TDHS increases the computation speed while maintaining good accuracy. Also, lumping few particles in a parcel increases the computation speed with little loss in accuracy. However, modeling particle-particle interactions with solids stress leads to a big loss in accuracy with a little increase in computation speed. The MP-PIC method predicts an unphysical particle-particle overlap, which results in incorrect voidage distribution and incorrect overall bed hydrodynamics. Based on this study, we recommend using the CGHS method for fluidized bed simulations due to its computational speed that rivals that of MPPIC while maintaining a much better accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Transcriptional profile of a myotube starvation model of atrophy

Skeletal muscle wasting is a pervasive phenomenon that can result from a wide range of pathological conditions as well as from habitual muscular inactivity. The present work describes a cell-culture condition that induces significant atrophy in skeletal muscle C2C12 myotubes. The failure to replenish differentiation media in mature myotubes leads to rapid atrophy (53% in diameter), which is referred to here as starvation. Affymetrix microarrays were used to develop a transcriptional profile of control (fed) vs. atrophied (nonfed) myotubes. Myotube starvation was characterized by an upregulation of genes involved in translational inhibition, amino acid biosynthesis and transport, and cell cycle arrest/apoptosis, among others. Downregulated genes included several structural and regulatory elements of the extracellular matrix as well as several elements of Wnt/frizzled and TGF-beta signaling pathways. Interestingly, the characteristic transcriptional upregulation of the ubiquitin-proteasome system, calpains, and cathepsins known to occur in multiple in vivo models of atrophy were not seen during myotube starvation. With the exception of the downregulation of extracellular matrix genes, serine protease inhibitor genes, and the upregulation of the translation initiation factor PHAS-I, this model of atrophy in cell culture has a transcriptional profile quite distinct from any study published to date with atrophy in whole muscle. These data show that, although the gross morphology of atrophied muscle fibers may be similar in whole muscle vs. myotube culture, the processes by which this phenotype is achieved differ markedly.

NASA Discipline Musculoskeletal↗
DOE OSTI2020

Utah FORGE: Phase 3 Magnetotelluric (MT) Data

New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rocks, to define the heat sources, and to derive baseline 3D resistivity structure for later MT monitoring of temporal changes in resistivity structure following well stimulation in the EGS reservoir. There are three files here related to Utah FORGE magnetotelluric (MT) data acquisition and processing. The FORGE MT EDIs zip file contains the observed MT responses in industry-standard EDI format. For each site, there is an EDI response file that utilized a local independent reference for noise cancellation, and a file that utilized a distant reference cancelling noise associated with the DC transmission line of the Delta IPP passing down the west side of Milford Valley. These two site files could be merged as appropriate. The FORGE Model Cell Center file contains the model volume of the 3D Forge MT inversion for characterizing the resistivity structure in the project area. It was derived using finite element inversion methodology described in Wannamaker et al, in the attached FORGE Phase3 Geophysics paper, from the MT observation EDI files. It is ASCII format (.dat) and entries are defined at top of the file in a simple x-y-z-Rho listing in UTM coordinates. The element layers drape the topography so the Rho value layers are not purely horizontal slices. This greatly simplifies the listing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Explicit temperature treatment in Monte Carlo neutron tracking routines - First results

This article discusses the preliminary implementation of the new explicit temperature treatment method to the development version Monte Carlo reactor physics code Serpent 2 and presents the first practical results calculated using the method. The explicit temperature treatment method, as introduced in [1], is a stochastic method for taking the effect of thermal motion into account on-the-fly in a Monte Carlo neutron transport calculation. The method is based on explicit treatment of the motion of target nuclei at collision sites and requires cross sections at 0 K temperature only, regardless of the number of temperatures in the problem geometry. The method includes a novel capability of modelling continuous temperature distributions. Test calculations are performed for two test cases, a PWR pin-cell and a HTGR system. The resulting k{sub eff} and flux spectra are compared to a reference solution calculated using Serpent 1.1.16 with Doppler-broadening rejection correction [2]. The results are in very good agreement with the reference and also the increase in calculation time due to the new method is on acceptable level although not fully insignificant. On the basis of the current study, the explicit treatment method can be considered feasible for practical calculations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Modeling particle-induced electron emission in a simplified plasma Test Cell

Particle-induced electron emission (PIE) is modeled in a simplified, well-characterized plasma Test Cell operated at UCLA. In order for PIE to be a useful model in this environment, its governing equations are first reduced to lower-order models which can be implemented in a direct simulation Monte Carlo and Particle-in-Cell framework. These reduced-order models are described in full and presented as semi-empirical models. The models are implemented to analyze the interaction of low- and high-energy ({approx}1-2 keV) xenon ions and atoms with the stainless steel electrodes of the Test Cell in order to gain insight into the emission and transport of secondary electrons. Furthermore, there is a lack of data for xenon-stainless steel atom- and ion-surface interactions for similar environments. Using experimental data as a reference, both total yields and emitted electron energy distribution functions can be deduced by observing sensitivities of current collection results to these numerical models and their parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗
DOE OSTI2016

Formation of supported lipid bilayers containing phase-segregated domains and their interaction with gold nanoparticles

The cell membrane represents an important biological interface that nanoparticles may encounter after being released into the environment. Interaction of nanoparticles with cellular membranes may alter membrane structure and function, lead to their uptake into cells, and elicit adverse biological responses. Supported lipid bilayers have proven to be valuable ex vivo models for biological membranes, allowing investigation of their mechanisms of interaction with nanoparticles with a degree of control impossible in living cells. To date, the majority of research on nanoparticle interaction with supported lipid bilayers has employed membranes composed of single or binary mixtures of phospholipids. Cellular membranes contain a wide variety of lipids and exhibit lateral organization. Ordered membrane domains enriched in specific membrane components are referred to as lipid rafts and have not been explored with respect to their interaction with nanoparticles. Here we develop model lipid raft-containing membranes amenable to investigation by a variety of surface-sensitive analytical techniques and demonstrate that lipid rafts influence the extent of nanoparticle attachment to model membranes. We determined conditions that allow reliable formation of bilayers containing rafts enriched in sphingomyelin and cholesterol and confirmed their morphology by structured illumination and atomic force microscopies. We demonstrate that lipid rafts increase attachment of cationic gold nanoparticles to model membranes under near physiological ionic strength conditions (0.1 M NaCl) at pH 7.4. We anticipate that these results will serve as the foundation for and motivate further study of nanoparticle interaction with compositionally varied lipid rafts.

cellular membranes↗
DOE OSTI2019

NEAMS Thermal-Fluids Test Stand for Fluoride-Slat Cooled, High Temperature Reactor Development (Final CRADA Report)

The work performed in this CRADA resulted in significant progress toward the development of a Thermal-fluid test-stand based on NEAMS tools. Significant work has been achieved in this area with simulations performed in Nek5000 of the heat and fluid flow in twisted tube heat exchangers and various software and modeling improvements in SAM geared toward heat exchanger simulations. In particular a set of simulations of flow and heat transfer in twisted elliptical tube geometries has been performed with Nek5000. The method was validated by simulating a case at a moderate Reynolds number and relatively high Froude number. This case was demonstrated to predict a Nusselt number in excellent agreement with the applicable correlation found in literature. It was further shown that at lower Froude numbers, this agreement becomes much worse. Additional cases were then simulated with low Froude numbers for both a square and a triangular unit cell to test the effect of pitch-to-maximum diameter ratio for the purposes of future CFD modeling. The results have proven invaluable to understand the flow physics in twisted tubes and provide reference data for design. Results have been summarized in a conference article. Moreover, work in SAM has led to significant improvement of software quality, the creation of a set of benchmarks for natural circulation and other significant software improvement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Energy Deposition Analysis of VERA Progression Problems using MCNP6

The current energy deposition model in the CASL neutronics code MPACT assumes all the fission energy is deposited locally. This approximation limits the accurate represen tation of the heating source distribution in the reactor core, which is essential for the thermal/hydraulic coupling calculations. There has been ongoing work to develop im proved models in MPACT to account for the energy deposition distribution of gamma rays, including direct fission gamma (prompt and delayed) and the gamma rays from neutron capture. Also, the neutron/photon coupling transport calculation has been considered as a potential capability to be added in MPACT to provide high-fidelity heating calculations. In order to provide a reference solution for these gamma heating models, MCNP has been used in this work to develop a set of energy deposition bench mark problems, based on the elective VERA Progression Problems, including single pin cells, 2-D assemblies and 2-D quarter core cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

SOMAFOAM: An OpenFOAM based solver for continuum simulations of low-temperature plasmas

Here, we report the development of SOMAFOAM, a finite volume framework for performing continuum simulations of low-temperature plasmas. The primary goal of this work is to discuss the features of SOMAFOAM along with representative results provided as examples for a range of operating conditions and geometries. This includes plasma and plasma–dielectric systems operating in direct current, radio frequency, and microwave regimes from pressures as low as 100 mTorr to atmospheric pressure. The code has several useful features including the ability to run massively parallel simulations using arbitrary geometries, structured/unstructured meshes, choice of models such as drift–diffusion/full-momentum at runtime, and species-dependent timesteps to name a few. The verification/validation studies presented include comparison with previously published continuum simulations (low-pressure direct current and radio frequency plasma), with experiments (Gaseous Electronics Conference Reference Cell and microwave microplasma ignited in a split ring resonator), and previously published kinetic simulations (low-pressure radio frequency plasma). Other examples provided include a direct current atmospheric pressure microplasma bounded by dielectric sidewalls and a helium–nitrogen plasma ignited using a needle electrode facing a dielectric. The performance of the code is also discussed with serial and distributed memory parallel runs demonstrated up to 512 cores. The design and implementation of the code in a modular object-oriented framework allows for easy extension and seamless coupling with other codes and can be expected to play an important role in both academia and industry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

The Archaeal Proteome Project advances knowledge about archaeal cell biology through comprehensive proteomics

Abstract While many aspects of archaeal cell biology remain relatively unexplored, systems biology approaches like mass spectrometry (MS) based proteomics offer an opportunity for rapid advances. Unfortunately, the enormous amount of MS data generated often remains incompletely analyzed due to a lack of sophisticated bioinformatic tools and field-specific biological expertise for data interpretation. Here we present the initiation of the Archaeal Proteome Project (ArcPP), a community-based effort to comprehensively analyze archaeal proteomes. Starting with the model archaeon Haloferax volcanii , we reanalyze MS datasets from various strains and culture conditions. Optimized peptide spectrum matching, with strict control of false discovery rates, facilitates identifying > 72% of the reference proteome, with a median protein sequence coverage of 51%. These analyses, together with expert knowledge in diverse aspects of cell biology, provide meaningful insights into processes such as N-terminal protein maturation, N -glycosylation, and metabolism. Altogether, ArcPP serves as an invaluable blueprint for comprehensive prokaryotic proteomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Electron and proton conductivity of Fe-N-C cathodes for PEM fuel cells: A model-based electrochemical impedance spectroscopy measurement

Impedance spectra of a PEM fuel cell with three Fe-N-C cathodes have been measured under the H 2 /N 2 testing regime. The spectra have been fitted using a recently developed physics-based impedance model, which takes into account finite proton ($σ_p$) and electron ($σ_e$) conductivity of the oxygen-free cathode catalyst layer. Fitting allowed to extract numerical data for $σ_p$, $σ_e$, the double layer capacitance, and the inductance of cables used for measuring impedance spectra. The values of σp and σe are close to what previously found for standard Pt/C electrodes, which is found for the first time using PGM-free catalysts. The method enables simultaneous measurement of reference proton and electron conductivity of PEMFC cathode.

25 ENERGY STORAGE↗
DOE OSTI2013

Verification & Validation of High-Order Short-Characteristics-Based Deterministic Transport Methodology on Unstructured Grids

The research team has developed a practical, high-order, discrete-ordinates, short characteristics neutron transport code for three-dimensional configurations represented on unstructured tetrahedral grids that can be used for realistic reactor physics applications at both the assembly and core levels. This project will perform a comprehensive verification and validation of this new computational tool against both a continuous-energy Monte Carlo simulation (e.g. MCNP) and experimentally measured data, an essential prerequisite for its deployment in reactor core modeling. Verification is divided into three phases. The team will first conduct spatial mesh and expansion order refinement studies to monitor convergence of the numerical solution to reference solutions. This is quantified by convergence rates that are based on integral error norms computed from the cell-by-cell difference between the code’s numerical solution and its reference counterpart. The latter is either analytic or very fine- mesh numerical solutions from independent computational tools. For the second phase, the team will create a suite of code-independent benchmark configurations to enable testing the theoretical order of accuracy of any particular discretization of the discrete ordinates approximation of the transport equation. For each tested case (i.e. mesh and spatial approximation order), researchers will execute the code and compare the resulting numerical solution to the exact solution on a per cell basis to determine the distribution of the numerical error. The final activity comprises a comparison to continuous-energy Monte Carlo solutions for zero-power critical configuration measurements at Idaho National Laboratory’s Advanced Test Reactor (ATR). Results of this comparison will allow the investigators to distinguish between modeling errors and the above-listed discretization errors introduced by the deterministic method, and to separate the sources of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hybrid-VPIC: An open-source kinetic/fluid hybrid particle-in-cell code

Hybrid-VPIC is an extension of the open-source high-performance particle-in-cell (PIC) code VPIC incorporating hybrid kinetic ion/fluid electron solvers. This paper describes the models that are available in the code and gives an overview of applications of the code to space and laboratory plasma physics problems. Particular choices in how the hybrid solvers were implemented are documented for reference by users. A few solutions for handling numerical complications particular to hybrid codes are also described. Finally, special emphasis is given to the computationally taxing problem of modeling mix in collisional high-energy-density regimes, for which more accurate electron fluid transport coefficients have been implemented for the first time in a hybrid PIC code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Hydrogen Infrastructure Analysis for the Port Applications [Slides]

The International Maritime Organization has committed to 50% reduction in GHG emissions by 2050 worldwide as of 2023. This analysis includes performing an inventory and modeling efforts to understand the energy, equipment and cost requirements to support decarbonization of cargo handling and shore power at U.S. Ports, along with assessment of zero- and near- zero emission fuel supplies at or near U.S. ports focused upon Hydrogen technologies. Initial market assessment for ocean going vessels for harbor support and ocean-going vessels is explored. An energy analysis is performed on the port system using a holistic approach and considering the port as an entire ecosystem that functions as a transportation and energy node. Presently, a comprehensive view is lacking for future analysis efforts, this analysis seeks to address this gap in data by evaluating four representative port types and the potential for utilizing hydrogen for the maritime industry. Every port is different, but broadly they could be bracketed into reference cases with scaling factors for the relative size of the port operations. These reference ports are for future use, potentially as baselines for analysis and development of demonstration programs. An equipment inventory for each reference port type (container, bulk, breakbulk, and inland waterway) is presented. A comparative analysis of fuel cell electric and battery electric equipment is conducted based on the following criteria: technology readiness level, refueling/charging time, operational range, energy consumption, and fuel cost savings compared to baseline internal combustion engine equipment. The tradeoffs and synergies between two alternative powertrains is highlighted. Based on energy and infrastructure analysis, average and high equipment utilization profiles across different port types is identified and quantified baseline fuel and electricity demand for various decarbonization scenarios. Based on the portfolio of equipment converted to fuel cell electric, the estimates of initial capital investment are provided for hydrogen refueling stations across ports. An energy demand model is developed that predicts well the all-electric cargo handling equipment annual energy consumption for ports with annual tonnage under 2 million twenty-foot equivalent units (TEUs). The model is a good rubric to follow for further energy demand models that can create a scalable solution to understand the energy needs of cargo handling equipment, whether they are all-electric, hydrogen fuel cell, or powered by another fuel-type. Zero and near-zero emission fuel supply at ports is evaluated looking into the characteristics of hydrogen, ammonia, and methanol as an alternative fuel, as well as the bunkering status. The readiness of reference ports to produce ammonia or methanol and bunker the fuel is examined based on the framework developed by the Global Maritime Forum and Rocky Mountain Institute.

08 HYDROGEN↗
NASA NTRS1999

Langmuir Probe Distortions and Probe Compensation in an Inductively Coupled Plasma

In many RF discharges, Langmuir probe measurements are usually made against a background of sinusoidal (and not so sinusoidal) fluctuations in the plasma parameters such as the plasma potential (Vp), the electron number density (ne), and the electron temperature (Te). The compensation of sinusoidal fluctuations in Vp has been extensively studied and is relatively well understood. Less attention has been paid to the possible distortions introduced by small fluctuations in plasma density and/or plasma temperature, which may arise in the sheath and pre-sheath regions of RF discharges. Here, we present the results of a model simulation of probe characteristics subject to fluctuations in both Vp and ne. The modeling of probe distortion due to possible fluctuations in Te is less straightforward. A comparison is presented of calculations with experimental measurements using a compensated and uncompensated Langmuir probe in an inductively coupled GEC reference cell plasma, operating on Ar and Ar/CF4 mixtures. The plasma parameters determined from the compensated probe characteristics are compared to previous measurements of others made in similar discharges, and to our own measurements of the average electron density derived from electrical impedance measurements.

Ji, J. S.↗