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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Thermal Analysis for SRS Saltstone Disposal Unit Facility

Saltstone Disposal Units (SDU) are long term disposal units for low activity grout produced from the solidification of decontaminated non-hazardous salt waste at SRS. The unit is a cylindrical disposal vault of 150 ft. in diameter and 23 ft. in height. The total volume the SDU can hold is 3 million gallons of grout. The hydration process of the grout material produces heat from an exothermic chemical reaction. If the grout reaches temperatures higher than the maximum safety temperature of 95 deg. C, cracks can start forming leading to contamination of the environment. The purpose of this study is to develop the optimal baseline domain boundary conditions and to perform a sensitivity analysis with respect to the baseline modeling conditions. The following assumptions were made for the modeling calculations: - The system geometry is axisymmetric; - The system was at steady state; - Ambient temperature was set to 100 deg. F; - Air was assumed to be an incompressible ideal gas; - Radiation was neglected for a conservative estimation; - Natural convection for the SDU vapor space is assumed to be turbulent because Rayleigh number based on typical operating conditions is higher than 10{sup 8}; - Water tables were not taken into consideration. The following sensitivity analyses were performed to find the optimal domain boundary: - Mesh size sensitivity; - Soil depth sensitivity - Soil depth varied from 30 ft to 250 ft with a soil thickness of 90 ft; - Soil thickness sensitivity - Soil thickness varied from 30 ft to 270 ft with a soil depth of 180 ft; - Soil conductivity sensitivity - Soil thermal conductivity varied from 0.25 W/m-K to 1 W/m-K; - Ambient Temperature Sensitivity - Ambient temperature varied from 70 deg. F to 110 deg. F. For the thermal calculations, the temperature of the bottom of the soil was set to 17.4 deg. C. The heat flux on the roof of the building and surface of the earth is 163.2 W/m{sup 2}. The soil sides are set to be adiabatic. The sensitivity analysis shows that the mesh size has no effect on the numerical results. This is mainly due to a small convection zone and large conduction zones in the modeling domain. The optimal domain boundary was found to be a soil thickness of 90 ft and a soil depth of 150 ft. The different sensitivity analysis performed here shows the optimal boundary domain to be used for thermal calculations is a soil depth of 150 ft beneath the SDU and a soil thickness of 90 ft. Anything larger would produce similar solutions but at a longer computational time to solve. The maximum temperature was more sensitive to soil properties as shown here. While the ambient temperature affected the max temperature linearly. Most of the heat transfer takes place downward vertically between the SDU and the soil beneath it. Using the optimal domain boundary determined by the sensitivity analyses, the maximum thermal loading to keep the maximum grout temperature below 95 deg. C is 1.646 W/m{sup 3}.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Multiwavelength investigations of PKS 2300–18: S-shaped radio quasar with precessing jets and double-peaked broad emission-line spectrum

ABSTRACT S-shaped radio galaxy jets are prime sources for investigating the dynamic interplay between the central active galactic nucleus (AGN), the jets, and the ambient intergalactic medium. These sources are excellent candidates for studying jet precession, as their S-shaped inversion symmetry strongly indicates underlying precession. We present a multiwavelength analysis of the giant inversion-symmetric S-shaped radio galaxy PKS 2300$-$18, which spans 0.76 Mpc. The host is a quasar at a redshift of 0.128, displaying disturbed optical morphology due to an ongoing merger with a companion galaxy. We conducted a broad-band radio spectral study using multifrequency data ranging from 183 MHz to 6 GHz, incorporating dedicated observations with the upgraded Giant Metrewave Radio Telescope (uGMRT) and Karl G. Jansky Very Large Array (JVLA) alongside archival radio data. A particle injection model was fitted to the spectra of different regions of the source to perform ageing analysis, which was supplemented with a kinematic jet precession model. The ageing analysis revealed a maximum plasma age of $\sim$ 40 Myr, while the jet precession model indicated a precession period of $\sim$ 12 Myr. ROentgen SATellite (ROSAT) data revealed an X-ray halo of Mpc size, and from Chandra the AGN X-ray spectrum was modelled using thermal and power-law components. The optical spectrum displaying double-peaked broad emission lines was modelled, indicating complex broad-line region kinematics at the centre with the possibility of a binary SMBH. We present the results of our multiwavelength analysis of the source, spanning scales from a few light-days to a few Mpc, and discuss its potential evolutionary path.

Misra, Arpita↗
DOE OSTI2018

Mathematical Analysis of the Solidification Behavior of Plain Steel Based on Solute- and Heat-Transfer Equations in the Liquid–Solid Zone

An analytical approximate solution to non-linear solute- and heat-transfer equations in the unsteady-state mushy zone of Fe-C plain steel has been obtained, assuming a linear relationship between the solid fraction and the temperature of the mushy zone. The heat transfer equations for both the solid and liquid zone along with the boundary conditions have been linked with the equations to solve the whole equations. The model predictions (e.g., the solidification constants and the effective partition ratio) agree with the generally accepted values and with a separately performed numerical analysis. The solidus temperature predicted by the model is in the intermediate range of the reported formulas. The model and Neuman’s solution are consistent in the low carbon range. A conventional numerical heat analysis (i.e., an equivalent specific heat method using the solidus temperature predicted by the model) is consistent with the model predictions for Fe-C plain steels. The model presented herein simplifies the computations to solve the solute- and heat-transfer simultaneous equations while searching for a solidus temperature as a part of the solution. Thus, this model can reduce the complexity of analyses considering the heat- and solute-transfer phenomena in the mushy zone.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Space Station Solar Dynamic Module modelling and simulation

Efforts to model and simulate the Solar Dynamic Power Module (SDPM) for the Space Station are discussed. The SDPM configuration is given and the SDPM subsytems are described, including the concentrator assembly, the fine pointing and tracking system, the power generation system, the heat rejection assembly, the electrical equipment, the interface structure and integration hardware, and the beta gimbal assembly. Performance requirements and design considerations are given. The development of models to simulate the SDPM is examined, noting research on models such as the Electric Power System Transient Analysis Model, the Electric Power System on Orbit Performance model, and a spatial flux distribution function.

Tylim, A.↗
DOE OSTI2020

Quantitative assessment of eddy viscosity rans models for turbulent mixed convection in a differentially heated plane channel

Turbulent mixed convection between two vertical, infinite parallel plates at different temperatures is studied using various two-equation turbulence models. The numerical simulations are performed at a turbulent Reynolds number of Re τ = 150 and a Grashof number of Gr = 9.6 × 10 5 . Comparisons are made against the highly trusted DNS results. Consistent with the DNS approach, the current simulations are performed using constant properties and the Boussinesq approximation to predict the influence of buoyancy. Previous studies have provided assessments of two-equation turbulence models for various scenarios, but often rely on a qualitative “eye” test in order to determine the most appropriate model to predict a given flow. This study aims to provide a new form of quantitative assessment that accounts for both the physics captured by the turbulence model as well as the magnitude of the system response quantities (SRQ) using a modified symmetric mean absolute percent error (SMAPE) method. This method is designed to be approachable to researchers at any level and can be applied to system response quantities from multiple research fields. Uncertainty quantification is also performed to determine the discretization error for each turbulence model. Recommendations are made as to which turbulence models best capture the physics – hydrodynamically and thermally – using both local and global validation metrics. Lastly, a sensitivity analysis is performed on the damping functions used in the most accurate models. This underpins the potential of model developments and adjustments most worth pursuing for buoyant flows. Finally, this framework provides a more physics-based comparative analysis of the selected turbulence models.

42 ENGINEERING↗
DOE OSTI2017

Keys to the House: Unlocking Residential Savings With Program Models for Home Energy Upgrades

After more than 40 years of effort, energy efficiency program administrators and associated contractors still find it challenging to penetrate the home retrofit market, especially at levels commensurate with state and federal goals for energy savings and emissions reductions. Residential retrofit programs further have not coalesced around a reliably successful model. They still vary in design, implementation and performance, and they remain among the more difficult and costly options for acquiring savings in the residential sector. If programs are to contribute fully to meeting resource and policy objectives, administrators need to understand what program elements are key to acquiring residential savings as cost effectively as possible. To that end, the U.S. Department of Energy (DOE) sponsored a comprehensive review and analysis of home energy upgrade programs with proven track records, focusing on those with robustly verified savings and constituting good examples for replication. The study team reviewed evaluations for the period 2010 to 2014 for 134 programs that are funded by customers of investor-owned utilities. All are programs that promote multi-measure retrofits or major system upgrades. We paid particular attention to useful design and implementation features, costs, and savings for nearly 30 programs with rigorous evaluations of performance. This meta-analysis describes program models and implementation strategies for (1) direct install retrofits; (2) heating, ventilating and air-conditioning (HVAC) replacement and early retirement; and (3) comprehensive, whole-home retrofits. We analyze costs and impacts of these program models, in terms of both energy savings and emissions avoided. These program models can be useful guides as states consider expanding their strategies for acquiring energy savings as a resource and for emissions reductions. We also discuss the challenges of using evaluations to create program models that can be confidently applied in multiple jurisdictions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

Methodology for predictive testing of fuel cells

A perturbation testing method has been developed and tested for predictive testing of fuel cells. This method involves application of small changes to the operating conditions of the cell in a predetermined sequence. The resultant response of the cell is then measured and statistically correlated with the corresponding test conditions. This method has been applied to the phosphoric acid fuel cell, and the effect of operating and cell-component variables on cell-performance degradation has been studied. A strong effect of the cell temperature and cathode potential on fuel-cell-performance degradation has been observed. A cell-performance degradation model has been formulated, and the unknown parameters in the model have been estimated by a regression analysis of the experimental data. A reasonable agreement between the fuel cell performance predicted by this model (derived from the perturbation experiments) and the unperturbed test data supports fthe applicability of the perturbation method.

Patel, D. N.↗
NASA NTRS2004

Summary of the key features of seven biomathematical models of human fatigue and performance

BACKGROUND: Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. METHODS: An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. RESULTS: Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers provided published papers describing their models, with three of the models being proprietary. CONCLUSIONS: Although all models appear to have been fundamentally influenced by the two-process model of sleep regulation by Borbely, there is considerable diversity among them in the number and type of input and output variables, and their stated goals and capabilities.

Fatigue/physiopathology↗
DOE OSTI2018

A Learning Framework for Control-Oriented Modeling of Buildings

Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

buildings↗
NASA NTRS1977

Solar concentration by curved-base Fresnel lenses

The solar concentration performance of idealized curved base line focusing Fresnel lenses is analyzed. A simple optical model was introduced to study the effects of base curvature and lens f-number. Thin lens ray tracing and the laws of reflection and refraction are used to develop expression for lens transmittance and image plane intensity profiles. The intensity distribution over the solar spectrum, lens dispersion effects, and absorption by the lens material are included in the analysis. Model capabilities include assessment of lens performance in the presence of small transverse tracking errors and the sensitivity of solar image characteristics to focusing.

Cosby, R. M.↗
NASA NTRSDate not supplied

SPACE-Gateway: Modeling the Electrical Performance of the Gateway Power & Propulsion Element (PPE) Solar Arrays

The System Power Analysis for Capability Evaluation (SPACE) computer model was originally developed in 1988 at NASA Glenn Research Center to model the International Space Station (ISS) electrical power system (EPS). Since then, SPACE development has continued with the rise of new NASA human spaceflight missions. Today, SPACE’s uniquely complex and robust solar array model is being leveraged to model the solar arrays on the Gateway Power & Propulsion Element (PPE) for NASA's Artemis Program. This presentation will discuss the model’s integrated features, including its solar cell current-voltage (IV) curve, degradation, temperature, and on-orbit shadowing components. The presentation will also discuss recent SPACE advancements to meet the needs of NASA's latest spaceflight missions.

SPACE↗
DOE OSTI2025

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty

Engineering and applied science rely on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and sampling-intensive studies often require prohibitively many simulations for acceptable accuracy. Surrogate models provide a means of circumventing the high computational expense of sampling such complex models. In particular, polynomial chaos expansions (PCEs) have been successfully used for uncertainty quantification studies of deterministic models where the dominant source of uncertainty is parametric. We discuss an extension to conventional PCE surrogate modeling to enable surrogate construction for stochastic computational models that have intrinsic noise in addition to parametric uncertainty. We develop a PCE surrogate on a joint space of intrinsic and parametric uncertainty, enabled by Rosenblatt transformations, which are evaluated via kernel density estimation of the associated conditional cumulative distributions. Furthermore, we extend the construction to random field data via the Karhunen–Loève expansion. We then take advantage of closed-form solutions for computing PCE Sobol indices to perform a global sensitivity analysis of the model which quantifies the intrinsic noise contribution to the overall model output variance. Additionally, the resulting joint PCE is generative in the sense that it allows generating random realizations at any input parameter setting that are statistically approximately equivalent to realizations from the underlying stochastic model. The method is demonstrated on a chemical catalysis example model and a synthetic example controlled by a parameter that enables a switch from unimodal to bimodal response distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Bounding the Chemistry Conditions in the HM Solvent Extraction Process Criticality Safety Analyses

An approach new to the H-Canyon facility criticality safety analysis has been performed using highly detailed models of the H-Modified (HM) process mixer settlers. The HM process uses tributyl phosphate (TBP) in organic n-paraffin to extract and purify uranium from used nuclear fuel. This occurs in two cycles of counter-current solvent extraction. The aqueous stream is a weak to moderate nitric acid and the feed stock is an aqueous stream. The first Cycle, consisting of two 16-stage banks (A and B-Banks) and one 12-stage bank (C-Bank), is a three step process that separates uranium from the fuel matrix, fission products, and most of the transuranic actinide content. The first Cycle aqueous product is concentrated, adjusted for acidity and fed to the second Cycle. The second Cycle, consisting of one 16-stage bank (D-Bank) and one 12-stage bank (E-Bank), is a two-step process that further purifies the uranium and removes to a great extent remaining actinides and fission products Each stage of the mixer settler banks is modeled as three unique compositions: the mixer as a combined composition of aqueous and organic components and the settler one aqueous and one organic component. This work addresses what is believed to be normal, credible abnormal, and beyond credible abnormal conditions for a particular postulated series of process parameter upsets. The level of detail and the source for the stage-wise compositions are both new and unique to criticality safety analyses of the HM process. Initial work was presented in Ref. 1 and has since been refined. A predictive chemistry model for flowsheet development has been used to solve the solvent extraction equations for the prescribed conditions and the output of that model was then transformed into compositions for each mixture in each stage. The remaining question upon which to achieve consensus is if the approach was appropriately conservative by concluding the chemistry is appropriately bounded. Computational modeling for criticality calculations was performed using KENO-VI in the SCALE 6.1 code package. Computational modeling of the chemistry was performed using the SEPHIS Modification 4 code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2002

ISO Key Project: Exploring The Full Range of Quasar/AGN Properties

While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the sub topic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets, As a result the team has requested and been granted an obtained a no-cost extension to this program, through December 31, 2003. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic data bases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: (1) refine the data analysis of ISO observations, to obtain deeper and better SNR results on selected sources. The ISO data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the ISO teams in 2001. The Fabry-Perot database in particularly sensitive to noise can slight calibration errors. (2) model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; (3) attend scientific meetings and workshops; (4) do E&PO activities related to infrared astrophysics and/or spectroscopy.

Wilkes, Belinda↗
NASA NTRS1999

A Spreadsheet Simulation Tool for Terrestrial and Planetary Balloon Design

During the early stages of new balloon design and development, it is necessary to conduct many trade studies. These trade studies are required to determine the design space, and aid significantly in determining overall feasibility. Numerous point designs then need to be generated as details of payloads, materials, mission, and manufacturing are determined. To accomplish these numerous designs, transient models are both unnecessary and time intensive. A steady state model that uses appropriate design inputs to generate system-level descriptive parameters can be very flexible and fast. Just such a steady state model has been developed and has been used during both the MABS 2001 Mars balloon study and the Ultra Long Duration Balloon Project. Using Microsoft Excel's built-in iteration routine, a model was built. Separate sheets were used for performance, structural design, materials, and thermal analysis as well as input and output sheets. As can be seen from figure 1, the model takes basic performance requirements, weight estimates, design parameters, and environmental conditions and generates a system level balloon design. Figure 2 shows a sample output of the model. By changing the inputs and a few of the equations in the model, balloons on earth or other planets can be modeled. There are currently several variations of the model for terrestrial and Mars balloons, as well there are versions of the model that perform crude material design based on strength and weight requirements. To perform trade studies, the Visual Basic language built into Excel was used to create an automated matrix of designs. This trade study module allows a three dimensional trade surface to be generated by using a series of values for any two design variables. Once the fixed and variable inputs are defined, the model automatically steps through the input matrix and fills a spreadsheet with the resulting point designs. The proposed paper will describe the model in detail, including current variations. The assumptions, governing equations, and capabilities will be addressed. Detailed examples of the model in practice will also be used.

Raquea, Steven M.↗
DOE OSTI2026

buhito

buhito is a Python library for graph analysis and machine learning. Graphs can represent networks with objects as nodes and their relationships as edges. buhito focuses on graphlet methods that study graphs through enumerating their component subgraphs to enable interpretable and fast models of complex systems. The package provides tools for different algorithmic designs for computing, analyzing, and applying graphlets to research problems such as machine learning, data compression, and anomaly detection in graph-structured data. A central feature is performing decomposition data analysis on graphs for machine learning models. Implemented in Python and built upon open-source scientific libraries such as NetworkX, NumPy, and SciPy, buhito provides high-performance methods for researchers exploring the mathematical and computational foundations of graphlet analysis applicable to systems of different sizes.

Pimonova, Yulia↗
NASA NTRS2017

MPCV Exercise Operational Volume Analysis

In order to minimize the loss of bone and muscle mass during spaceflight, the Multi-purpose Crew Vehicle (MPCV) will include an exercise device and enough free space within the cabin for astronauts to use the device effectively. The NASA Digital Astronaut Project (DAP) has been tasked with using computational modeling to aid in determining whether or not the available operational volume is sufficient for in-flight exercise.Motion capture data was acquired using a 12-camera Smart DX system (BTS Bioengineering, Brooklyn, NY), while exercisers performed 9 resistive exercises without volume restrictions in a 1g environment. Data were collected from two male subjects, one being in the 99th percentile of height and the other in the 50th percentile of height, using between 25 and 60 motion capture markers. Motion capture data was also recorded as a third subject, also near the 50th percentile in height, performed aerobic rowing during a parabolic flight. A motion capture system and algorithms developed previously and presented at last years HRP-IWS were utilized to collect and process the data from the parabolic flight [1]. These motions were applied to a scaled version of a biomechanical model within the biomechanical modeling software OpenSim [2], and the volume sweeps of the motions were visually assessed against an imported CAD model of the operational volume. Further numerical analysis was performed using Matlab (Mathworks, Natick, MA) and the OpenSim API. This analysis determined the location of every marker in space over the duration of the exercise motion, and the distance of each marker to the nearest surface of the volume. Containment of the exercise motions within the operational volume was determined on a per-exercise and per-subject basis. The orientation of the exerciser and the angle of the footplate were two important factors upon which containment was dependent. Regions where the exercise motion exceeds the bounds of the operational volume have been identified by determining which markers from the motion capture exceed the operational volume and by how much. A credibility assessment of this analysis was performed in accordance with NASA-STD-7009 prior to delivery to the MPCV program.

mathematical models↗