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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗
DOE OSTI2018

Bi-material strip based temperature sensor design and optimization through thermo-mechanical multi-physics modeling

With the capability of additive manufacturing, complex structures are easily fabricated to achieve various design purposes. In this work, a bi-material strip temperature sensor with complex periodic pattern design is purposed and investigated through both the analytical modeling and multi-physics finite element analysis. Three design patterns are considered: standard, E-shape and S-shape. In the standard solid strip design, the curvature of the bi-material strip under temperature variation is in a linear relationship with the coefficient of thermal expansion (CTE) difference, but in a reciprocal relationship with the strip thickness. The curvature of the bi-material strip depends on the Young’s modulus ratio and layer thickness ratio of the two materials, but is independent of the magnitude of the materials’ Young’s modulus. Based on analytical derivation and numerical validation, the optimized design parameters can be provided. Compared to S-shape pattern design, E-shape pattern design can significantly increase the temperature sensitivity of the bi-material strip. An analytical prediction of the E-shape pattern’s temperature sensitivity is introduced and discussed. This work proves the concept that new design space becomes available with the capability of additive manufacturing, and provides the general design guideline for a bi-material strip based temperature sensor with possible design patterns.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Parametric and Sensitivity Analysis of a Steam Generator Model Using Python and Machine-Learning Tools

For this study, we used Python and machine-learning tools to perform a comprehensive parametric and sensitivity analysis on a steam generator (SG) model. (The Python model was based on a previously completed MATLAB framework for the Holtec SMR-160 SG.) We investigated the influence of various input parameters (e.g., heat transfer coefficient [HTC], Nusselt number, and heat exchanger effectiveness) on the system’s output. With machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN), which was developed at Idaho National Laboratory, we were then able to perform an automated analysis of the SG inputs’ effect on the HTC. The analysis results give valuable insights into the performance and optimization of SG systems. We found the inlet mass flow rate (MFR) to have the greatest impact on the HTC, followed closely by the inlet temperature, and then pressure. Shifting of the input parameters causes the location of the maximum HTC along the SG length to change incrementally. The cold leg (CL) MFR was also found to impact the HTC magnitude as well as the location of the maximum HTC. At between 0.4–0.9 of the total SG length, the input parameters experience maximum impact on the HTC, leading us to suggest that sensors be efficiently placed on the SG so as to closely and effectively monitor thermal-hydraulic properties during reactor operation. We also found that the sensitivity data calculated manually agrees with the RAVEN – based data, confirming the same range of maximum sensitivity. However, the RAVEN-based analysis showed that cold leg pressure and hot leg temperature have a greater impact on the heat transfer coefficient than the mass flow rate, implying that a manual sensitivity study taking only two samples is not accurate.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Machine learning insights into microstructural origins of transport and mechanical properties in porous microstructures

Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.

Bicontinuous microstructure↗
DOE OSTI2016

Application of Hybrid Genetic Algorithm Routine in Optimizing Food and Bioengineering Processes

Optimization is a crucial step in the analysis of experimental results. Deterministic methods only converge on local optimums and require exponentially more time as dimensionality increases. Stochastic algorithms are capable of efficiently searching the domain space, however convergence is not guaranteed. This article demonstrates the novelty of hybrid genetic algorithm which combines both stochastic and deterministic routine for improved optimization results. A new hybrid genetic algorithm developed is applied to the Ackley benchmark function as well as case studies in foods, biofuels, and biotechnology processes. For each case study the hybrid genetic algorithm found a better optimum candidate than reported by the sources. In the case of food processing the hybrid genetic predicted 5% higher anthocyanin yield. Optimization of bio-oil production using HGA resulted in a 4.73 % higher yield. In enzyme production process HGA predicted 2.18 IU/gds of higher xylanase yield. In conclusion, hybridization of genetic algorithm with a deterministic algorithm resulted in maximum optimum compared to the statistical methods.

09 BIOMASS FUELS↗
DOE OSTI2016

Optimization design of helium circulator diffuser in HTR-PM - 18488

Circulator is very important in HTR-PM. It needs to supply enough pressure rise to circulate cooled helium in the primary loop of HTR-PM to bring heat out. Its pressure rise requirement is the highest among the worldwide circulators. Diffuser is one main component to produce pressure rise for circulator. And the most particular for HTR-PM is that the helium must flow out from two round tubes after flowing through the diffuser, which is very different from other circulators. This special export structure increases flow loss and decreases diffuser efficiency. So it is necessary to optimize diffuser to satisfy high pressure rise requirement of HTR-PM circulator with the special export structure. Four geometrical variables of diffuser have been studied and optimized. Based on the flow and performance analysis, the optimum structure was chosen. Then the detailed simulation was done by combining it with impeller to obtain performance characteristics of the whole circulator. Finally, the simulation results were compared with experimental results. It was obtained that simulation pressure rise was 201 kPa and experimental result was 210 kPa, which verified that optimization design of diffuser was effective. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

The agile alert system for gamma-ray transients

In recent years, a new generation of space missions has offered great opportunities for discovery in high-energy astrophysics. In this article we focus on the scientific operations of the Gamma-Ray Imaging Detector (GRID) on board the AGILE space mission. AGILE-GRID, sensitive in the energy range of 30 MeV-30 GeV, has detected many γ-ray transients of both galactic and extragalactic origin. This work presents the AGILE innovative approach to fast γ-ray transient detection, which is a challenging task and a crucial part of the AGILE scientific program. The goals are to describe (1) the AGILE Gamma-Ray Alert System, (2) a new algorithm for blind search identification of transients within a short processing time, (3) the AGILE procedure for γ-ray transient alert management, and (4) the likelihood of ratio tests that are necessary to evaluate the post-trial statistical significance of the results. Special algorithms and an optimized sequence of tasks are necessary to reach our goal. Data are automatically analyzed at every orbital downlink by an alert pipeline operating on different timescales. As proper flux thresholds are exceeded, alerts are automatically generated and sent as SMS messages to cellular telephones, via e-mail, and via push notifications from an application for smartphones and tablets. These alerts are crosschecked with the results of two pipelines, and a manual analysis is performed. Being a small scientific-class mission, AGILE is characterized by optimization of both scientific analysis and ground-segment resources. The system is capable of generating alerts within two to three hours of a data downlink, an unprecedented reaction time in γ-ray astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

FY2022 Status Report: Cold Spray for Canister SCC Mitigation and Repair

This progress report describes work performed during FY22 at Sandia National Laboratories (SNL) to assess the corrosion performance of cold spray coatings to enable optimization of cold spray for the purposes of mitigation and/or repair of potentially susceptible regions, corrosion, or stress corrosion cracking (SCC) in austenitic stainless steel for spent nuclear fuel (SNF) storage. Of particular concern is SCC, by which a through-wall crack could potentially form in a canister outer wall over time intervals that may be shorter than possible dry storage times. In FY21, initial corrosion explorations of cold spray coating were evaluated and in FY22, an expanded set of cold spray coatings with in-depth analysis of post-exposure accelerated testing was explored. Additionally, relevant atmospheric exposure testing was carried out and initial results are presented herein. The corrosion attack from the accelerated testing and more realistic atmospheric exposures environments were compared to identify potentially deleterious factors for corrosion as well as help to understand the applicability of accelerated testing for cold spray optimization. This initial analysis will help to enable optimization of the corrosion resistance cold spray, one of the more promising coating and repair techniques, for potential application in an SNF environment. Learnings from both are summarized, and implications and future work are presented in this report.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Estimation of LOCA break size using cascaded support vector regression - 334

A failure of emergency core cooling system (ECCS) during a certain small break loss of coolant accident (SBLOCA) can cause a severe core uncovery and fuel failure. The safety injection systems (SISs) might not function properly in case of a SBLOCA, due to the slight change of pressure in the pipes. Early trend of the major parameters has to be observed and the accurate information has to be given to the nuclear power plant (NPP) operators by precisely identifying the break size to effectively manage accidents. In this study, the objective is to provide to operators the information on the break size in a short time by considering the accident situations such as hot-leg LOCA, cold-leg LOCA, steam generator tube rupture (SGTR). A cascaded support vector regression (CSVR) is used in order to estimate the break size. The simulation data set was obtained from the optimized power plant reactor 1000 (OPR1000) using modular accident analysis program (MAAP) code. And genetic algorithm (GA) was used to select the input variables of the CSVR model and optimize its parameters. As a result of this study, the CSVR model estimate very well the break size of LOCAs. If the operators can predict the break size in the LOCA, they can response quickly and properly to LOCA circumstances to prevent the core uncovery and fuel failure. Also, it will be possible to more efficiently manage beyond design basis accidents. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Multimodal analysis and characterization of the boehmite layer formed on AA6061 before and after alkaline etching

Low-enriched uranium (LEU) alloyed with 10% Mo (U-10Mo) is being considered as a promising alternative to oxide-based dispersion fuel with high-enriched uranium for use in research reactors. The configuration of this proposed LEU monolithic LEU fuel plate consists of a U-10Mo plate-type fuel foil with a 25 µm zirconium interlayer barrier clad with an aluminum alloy (AA6061). In certain research reactors, the clad AA6061 is coated with a boehmite layer to prevent corrosion. The boehmite layer has a high-pH passivation range, which makes it resistant to oxidation. Boehmite is usually formed on the AA6061 surface by autoclave processing. Before the boehmite layer is added, the surface of the AA6061 is cleaned using techniques such as polishing and wet etching. In this study, we use multimodal analysis to examine how pretreatment of AA6061 using polishing followed by alkaline etching affects the chemical composition of the boehmite layer. X-ray photoelectron microscopy (XPS), transmission electron microscopy (TEM), and x-ray diffraction (XRD) were used to study the chemical changes in the boehmite layer caused by alkaline etching pretreatment. XPS provides quantitative analysis for the Al:O ratio as well as oxidation states present on the surface, which suggests slight oxidation of the boehmite surface after alkaline etching of the AA6061 surface. We further explored this suggested oxidation of the boehmite surface using high-resolution transmission electron microscopy with selected area electron diffraction (SAED) and grazing incidence x-ray diffraction (GI-XRD), which suggested only a small amount of aluminum oxide at the surface. The multimodal analysis and imaging yielded new insights for optimizing boehmite growth on AA6061 for research reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Chemical Composition on the Microstructure and Properties of the Ag-Ga-Ge Alloys

This study presents a comparison of thermodynamically calculated phase compositions of Ag-Ga-Ge alloys at fixed temperatures with phase analysis results of alloys annealed at respective temperatures. Three isothermal sections of the Ag-Ga-Ge system at 25, 100 and 300 °C have been extrapolated using optimized thermodynamic parameters from the literature. An experimental analysis of the microstructure was carried out using optical microscopy, scanning electron microscopy and energy-dispersive spectrometry. Results obtained by x-ray powder diffraction methods (identified phases and lattice parameters) were compared with the results of the predicted phase equilibria. Good overall agreement between experimental and calculated values was obtained. The Brinell hardness and electrical conductivity of selected alloys were measured and obtained results were analyzed with respect to their overall compositions and phase constituents.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Model independent x-ray standing wave analysis of periodic multilayer structures

We present a model independent approach for the analysis of X-ray fluorescence yield modulated by an X-ray standing wave (XSW), that allow a fast reconstruction of the atomic distribution function inside a sample without fitting procedure. The approach is based on the direct regularized solution of the system of linear equations that characterizes the fluorescence yield. The suggested technique was optimized for, but not limited to, the analysis of periodic layered structures where the XSW is formed under Bragg conditions. The developed approach was applied to the reconstruction of the atomic distribution function for LaN/BN multilayers with 50 periods of 43 Å thick layers. The object is especially difficult to analyze with traditional methods, as the estimated thickness of the interface region between the constituent materials is comparable to the individual layer thicknesses. However, using the suggested technique, it was possible to reconstruct width of the La atomic distribution showing that the La atoms stay localized within the LaN layers and interfaces and do not diffuse into the BN layer. The analysis of the reconstructed profiles showed that the positions of the center of the atomic distribution function can be estimated with an accuracy of 1 Å.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs

The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding the effect of systematic uncertainties on measured signals and testing mitigation strategies for reducing these uncertainties, aiding analysis pipeline development and testing, and survey strategy optimization. The list of applications is growing with improvements in the quality of the catalogs and the details that they can provide. Given the importance of simulated catalogs, it is critical to provide rigorous validation protocols that enable both catalog providers and users to assess the quality of the catalogs in a straightforward and comprehensive way. For this purpose, we have developed the DESCQA framework for the Large Synoptic Survey Telescope Dark Energy Science Collaboration as well as for the broader community. The goal of DESCQA is to enable the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. Here in this paper, we present the design concept and first implementation of DESCQA. In order to establish and demonstrate its full functionality we use a set of interim catalogs and validation tests. We highlight several important aspects, both technical and scientific, that require thoughtful consideration when designing a validation framework, including validation metrics and how these metrics impose requirements on the synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Electrical design analysis and breakdown voltage test aspects of indigenously developed electrical breaks at Cryo temperatures

Electrical insulation breaks are very critical component of large-scale fusion devices employing superconducting magnets and are used to insulate electrically the coil and the cryogenic supply line (kept at ground potential). The electrical insulation of breaks consists of the composites insulations, G-10 GFRP (Glass fiber reinforced plastic), cryogenic compatible epoxy and S-glass boron free fiber in air and helium environment under vacuum. To optimize the design parameters, the detailed electrical analysis have been carried out using the electrostatic solid axi-symmetric model by COMSOL 4.1 multiphysics software for electrodes separation, electrical field strength as well as flashover phenomenon between two electrodes with composite insulator material have been analyzed at different surfaces and contours along with by varying gaps between SS electrodes. We have carried out the high voltage breakdown test (0-35) kV, insulation resistance measurement at 0-5 kV test voltage in Paschen condition of (10{sup 3} -10{sup -5}) mbar in helium gas and air environment at 300 K and 77 K experimentally on in-house developed insulation breaks. (author)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Systems Analysis Approach to Polyethylene Terephthalate and Olefin Plastics Supply Chains in the Circular Economy: A Review of Data Sets and Models

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify datasets, models and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best datasets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this article is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. Here, the preliminary systems analysis of PET bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Thermal Storage System for Electric Vehicle Cabin Heating Component and System Analysis

Cabin heating of current electric vehicle (EV) designs is typically provided using electrical energy from the traction battery, since waste heat is not available from an engine as in the case of a conventional automobile. In very cold climatic conditions, the power required for space heating of an EV can be of a similar magnitude to that required for propulsion of the vehicle. As a result, its driving range can be reduced very significantly during the winter season, which limits consumer acceptance of EVs and results in increased battery costs to achieve a minimum range while ensuring comfort to the EV driver. To minimize the range penalty associated with EV cabin heating, a novel climate control system that includes thermal energy storage from an advanced phase change material (PCM) has been designed for use in EVs and plug-in hybrid electric vehicles (PHEVs). The present paper focuses on the modeling and analysis of this electrical PCM-Assisted Thermal Heating System (ePATHS) and is a companion to the paper Design and Testing of a Thermal Storage System for Electric Vehicle Cabin Heating. A detailed heat transfer model was developed to simulate the PCM heat exchanger that is at the heart of the ePATHS and was subsequently used to analyze and optimize its design. The results from this analysis were integrated into a MATLAB Simulink system model to simulate the fluid flow, pressure drop and heat transfer in all components of the ePATHS. The system model was then used to predict the performance of the climate control system in the vehicle and to evaluate control strategies needed to achieve the desired temperature control in the cabin. The analysis performed to design the ePATHS is described in detail and the system s predicted performance in a vehicle HVAC system is presented.

cabin heating↗
DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗
DOE OSTI2022

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey II: measurements in Fourier space with optimal weights

ABSTRACT We present measurements of the local primordial non-Gaussianity parameter $f_{\mathrm{NL}}^\mathrm{local} $from the clustering of 343 708 quasars with redshifts 0.8 < z < 2.2 distributed over 4808 deg2 from the final data release (DR16) of the extended Baryon Acoustic Oscillation Spectroscopic Survey (eBOSS), the largest volume spectroscopic survey up to date. Our analysis is performed in Fourier space, using the power spectrum monopole at very large scales to constrain the scale-dependent halo bias. We demonstrate the robustness of our analysis pipeline with EZ-mock catalogues that simulate the eBOSS DR16 target selection. We carefully assess the impact of systematics on our measurement, exploiting a novel neural network scheme for cleaning the DR16 sample as well as test multiple contamination removal methods. We estimate the bias due to the overcorrection of the systematic removal to be sub-dominant compared to the statistical uncertainty. We find fNL = −12 ± 21 (68 per cent confidence) for the main clustering sample including quasars with redshifts between 0.8 and 2.2, after applying redshift weighting techniques, designed for non-Gaussianity measurement from large scales structure, to optimize our analysis, which improve our results by 37 per cent.

79 ASTRONOMY AND ASTROPHYSICS↗