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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 19 records

Co-design for Embedded ViscoPlasticity

CoEVP (Co-design for Embedded ViscoPlasticity) is an implementation of a Lagrangian hydrodynamic model utilizing an embedded viscoplasticity model to provide constitutive parameters. The purpose of CoEVP is to provide a highly simplified "proxy" materials science application for use by the Exascale Materials in Extreme Environments (ExMatEx) codesign center to improve the ability of exascale computers being developed over the next several years to address materials science applications of importance to DOE and the Laboratory.

Source record↗

Electrically heated particulate filter embedded heater design

An exhaust system that processes exhaust generated by an engine is provided. The system generally includes a particulate filter (PF) that filters particulates from the exhaust wherein an upstream end of the PF receives exhaust from the engine and wherein an upstream surface of the particulate filter includes machined grooves. A grid of electrically resistive material is inserted into the machined grooves of the exterior upstream surface of the PF and selectively heats exhaust passing through the grid to initiate combustion of particulates within the PF.

42 ENGINEERING↗

Embedded Sensors and Controls to Improve Component Performance and Reliability -- Loop-scale Testbed Design Report

Embedded instrumentation and control systems that can operate in extreme environments are challenging to design and operate. Extreme environments limit the options for sensors and actuators and degrade their performance. Because sensors and actuators are necessary for feedback control, these limitations mean that designing embedded instrumentation and control systems for the challenging environments of nuclear reactors requires advanced technical solutions that are not available commercially. This report details the development of testbed that will be used for cross-cutting embedded instrumentation and control research for nuclear power applications. This research is funded by the Department of Energy's Nuclear Energy Enabling Technology program's Advanced Sensors and Instrumentation topic. The design goal of the loop-scale testbed is to build a low temperature pump that utilizes magnetic bearing that will be incorporated into a water loop to test control system performance and self-sensing techniques. Specifically, this testbed will be used to analyze control system performance in response to nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics and gyroscopic effects, and impeller disturbances. This testbed will also be used to characterize the performance losses when using self-sensing position measurement techniques. Active magnetic bearings are a technology that can reduce failures and maintenance costs in nuclear power plants. They are particularly relevant to liquid salt reactors that operate at high temperatures (700 C). Pumps used in the extreme environment of liquid salt reactors provide many engineering challenges that can be overcome with magnetic bearings and their associated embedded instrumentation and control. This report will give details of the mechanical design and electromagnetic design of the loop-scale embedded instrumentation and control testbed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Design and Analysis of Embedded I&C for a Fully Submerged Magnetically Suspended Impeller Pump

Improving nuclear reactor power system designs and fuel-processing technologies for safer and more efficient operation requires the development of new component designs. In particular, many of the advanced reactor designs such as the molten salt reactors and high-temperature gas-cooled reactors have operating environments beyond the capability of most currently available commercial components. To address this gap, new cross-cutting technologies need to be developed that will enable design, fabrication, and reliable operation of new classes of reactor components. The Advanced Sensor Initiative of the Nuclear Energy Enabling Technologies initiative is investigating advanced sensor and control designs that are capable of operating in these extreme environments. Under this initiative, Oak Ridge National Laboratory (ORNL) has been developing embedded instrumentation and control (I&C) for extreme environments. To develop, test, and validate these new sensing and control techniques, ORNL is building a pump test bed that utilizes submerged magnetic bearings to levitate the shaft. The eventual goal is to apply these techniques to a high-temperature (700°C) canned rotor pump that utilizes active magnetic bearings to eliminate the need for mechanical bearings and seals. The technologies will benefit the Next Generation Power Plant, Advanced Reactor Concepts, and Small Modular Reactor programs. In this paper, we will detail the design and analysis of the embedded I&C test bed with submerged magnetic bearings, focusing on the interplay between the different major systems. Then we will analyze the forces on the shaft and their role in the magnetic bearing design. Next, we will develop the radial and thrust bearing geometries needed to meet the operational requirements of the test bed. In conclusion, we will present some initial system identification results to validate the theoretical models of the test bed dynamics.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

j5 v2.8.4

j5 automates and optimizes the design of the molecular biological process of cloning/constructing DNA. j5 enables users to benefit from (combinatorial) multi-part scar-less SLIC, Gibson, CPEC, Golden Gate assembly, or variants thereof, for which automation software does not currently exist, without the intense labor currently associated with the process. j5 inputs a list of the DNA sequences to be assembled, along with a Genbank, FASTA, jbei-seq, or SBOL v1.1 format sequence file for each DNA source. Given the list of DNA sequences to be assembled, j5 first determines the cost-minimizing assembly strategy for each part (direct synthesis, PCR/SOE, or oligo-embedding), designs DNA oligos with Primer3, adds flanking homology sequences (SLIC, Gibson, and CPEC; optimized with Primer3 for CPEC) or optimized overhang sequences (Golden Gate) to the oligos and direct synthesis pieces, and utilizes BLAST to check against oligo mis-priming and assembly piece incompatibility events. After identifying DNA oligos that are already contained within a local collection for reuse, the program estimates the total cost of direct synthesis and new oligos to be ordered. In the instance that j5 identifies putative assembly piece incompatibilities (multiple pieces with high flanking sequence homology), the program suggests hierarchical subassemblies where possible. The program outputs a comma-separated value (CSV) file, viewable via Excel or other spreadsheet software, that contains assembly design information (such as the PCR/SOE reactions to perform, their anticipated sizes and sequences, etc.) as well as a properly annotated genbank file containing the sequence resulting from the assembly, and appends the local oligo library with the oligos to be ordered j5 condenses multiple independent assembly projects into 96-well format for high-throughput liquid-handling robotics platforms, and generates configuration files for the PR-PR biology-friendly robot programming language. j5 thus provides a new way to design DNA assembly procedures much more productively and efficiently, not only in terms of time, but also in terms of cost. To a large extent, however, j5 does not allow people to do something that could not be done before by hand given enough time and effort. An exception to this is that, since the very act of using j5 to design the DNA assembly process standardizes the experimental details and workflow, j5 enables a single person to concurrently perform the independent DNA construction tasks of an entire group of researchers. Currently, this is not readily possible, since separate researchers employ disparate design strategies and workflows, and furthermore, their designs and workflows are very infrequently fully captured in an electronic format which is conducive to automation.

Hillson, Nathan↗

Electronic Spin Qubit Candidates Arrayed within Layered Two-Dimensional Polymers

Molecular electronic spin qubits are promising candidates for quantum information science applications because they can be reliably produced and engineered via chemical design. Embedding electronic spin qubits within two-dimensional polymers (2DPs) offers the possibility to systematically engineer inter-qubit interactions while maintaining long coherence times, both of which are prerequisites to their technological utility. Here, we introduce electronic spin qubits into a diamagnetic 2DP by n-doping naphthalene diimide subunits with varying amounts of CoCp 2 and analyze their spin densities by quantitative electronic paramagnetic resonance spectroscopy. Low spin densities (e.g., 6.0 × 10 12 spins mm –3 ) enable lengthy spin–lattice (T 1 ) and spin–spin relaxation (T 2 ) times across a range of temperatures, ranging from T 1 values of 164 ms at 10 K to 30.2 μs at 296 K and T 2 values of 2.36 μs at 10 K to 0.49 μs at 296 K for the lowest spin density sample examined. Higher spin densities and temperatures were both found to diminish T 1 times, which we attribute to detrimental cross-relaxation from spin–spin dipolar interactions and spin–phonon coupling, respectively. Higher spin densities decreased T 2 times and modulated the T 2 temperature dependence. Here, we attribute these differences to the competition between hyperfine and dipolar interactions for electron spin decoherence, with the dominant interaction transitioning from the former to the latter as spin density and temperature increase. Overall, this investigation demonstrates that dispersing electronic spin qubits within layered 2DPs enables chemical control of their inter-qubit interactions and spin decoherence times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Miniature lowpass filters in low loss 9k7 LTCC

DuPont 9k7 low temperature cofired ceramic (LTCC) is a low loss, or high quality factor Q, tape system targeting at radio frequency (RF) applications. This paper reports the effect of a critical process parameter, heating rate, on the densification and dielectric properties of the 9k7 LTCC. The role of competing densification and crystallization during the sintering of 9k7 is discussed. The high Q of DuPont 9K7 can be used to improve RF system performance, for example a better receiver noise figure, by designing embedded passive RF components such as inductors, capacitors and filters. As a result, miniaturized multilayer low pass filters (LPF) with a wide stopband were fabricated to showcase the technology.

36 MATERIALS SCIENCE↗

Miniature low-pass filter in low-loss 9k7 LTCC

DuPont 9k7 low-temperature cofired ceramic (LTCC) is a low-loss, or high-quality-factor Q, tape system targeting at radio frequency (RF) applications. This paper reports on the effect of a critical process parameter, the heating rate, on the densification and dielectric properties of the 9k7 LTCC. The role of competing densification and crystallization during the sintering of 9k7 is discussed. The high Q of DuPont 9K7 can be used to improve RF system performance, for example a better receiver noise figure, by designing embedded passive RF components such as inductors, capacitors and filters. Furthermore, miniaturized multilayer low-pass filters (LPF) with a wide stopband were fabricated to showcase the technology.

36 MATERIALS SCIENCE↗

Embedded Sensors and Controls to Improve Component Performance and Reliability -- Bench-scale Testbed Design Report

Embedded instrumentation and control systems that can operate in extreme environments are challenging due to restrictions on sensors and materials. As a part of the Department of Energy's Nuclear Energy Enabling Technology cross-cutting technology development programs Advanced Sensors and Instrumentation topic, this report details the design of a bench-scale embedded instrumentation and control testbed. The design goal of the bench-scale testbed is to build a re-configurable system that can rapidly deploy and test advanced control algorithms in a hardware in the loop setup. The bench-scale testbed will be designed as a fluid pump analog that uses active magnetic bearings to support the shaft. The testbed represents an application that would improve the efficiency and performance of high temperature (700 C) pumps for liquid salt reactors that operate in an extreme environment and provide many engineering challenges that can be overcome with embedded instrumentation and control. This report will give details of the mechanical design, electromagnetic design, geometry optimization, power electronics design, and initial control system design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An finite element analysis surrogate model with boundary oriented graph embedding approach for rapid design

Abstract In this work, we present a boundary oriented graph embedding (BOGE) approach for the graph neural network to assist in rapid design and digital prototyping. The cantilever beam problem has been solved as an example to validate its potential of providing physical field results and optimized designs using only 10 ms. Providing shortcuts for both boundary elements and local neighbor elements, the BOGE approach can embed unstructured mesh elements into the graph and performs an efficient regression on large-scale triangular-mesh-based finite element analysis (FEA) results, which cannot be realized by other machine-learning-based surrogate methods. It has the potential to serve as a surrogate model for other boundary value problems. Focusing on the cantilever beam problem, the BOGE approach with 3-layer DeepGCN model achieves the regression with mean square error (MSE) of 0.011 706 (2.41% mean absolute percentage error) for stress field prediction and 0.002 735 MSE (with 1.58% elements having error larger than 0.01) for topological optimization. The overall concept of the BOGE approach paves the way for a general and efficient deep-learning-based FEA simulator that will benefit both industry and Computer Aided Design (CAD) design-related areas.

42 ENGINEERING↗

Design and analysis of embedded I and C for loop-scale magnetically suspended pump - 261

Improving nuclear reactor designs and fuel processing technologies for safer and more efficient operation require the development of new component designs. In particular, many of the advanced reactor design such as the molten salt reactors and high-temperature gas cooled reactors have operating environments beyond the ability of many currently commercially available components. To address this, new cross-cutting technologies need to be developed that will enable the design, fabrication, and reliable operation of new classes of reactor components. The Advanced Sensor Initiative of the Nuclear Energy Enabling Technologies initiative is investigating advanced sensor and control designs that are capable of operating in these extreme environments. Under this initiative Oak Ridge National Laboratory (ORNL) has been developing embedded instrumentation and control for extreme environments. To develop, test, and validate these new sensing and control techniques, ORNL is building a pump testbed with submerged magnetic bearings. The eventual goal is to apply these techniques to a high temperature (700 deg. C) canned rotor pump that utilizes active magnetic bearings to eliminate the need for mechanical bearings and seals. The technologies will benefit the Next Generation Power Plant, Advanced Reactor Concepts, and Small Modular Reactor programs. In this paper we will detail the design and analysis of the embedded I and C testbed with submerged magnetic bearings. Then we will analyze the fluid forces on the shaft. Finally, we will develop the radial and thrust bearing geometries needed to meet the force requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Novel Framework for Performance Evaluation and Design Optimization of PCM Embedded Heat Exchangers for the Built Environment

This research sheds light on the performance evaluation and design optimization of PCM-HXs for the built environment, addressing several barriers to practical issues to PCM-HX commercialization such as modeling aspects (i.e., modeling expertise and computational / time investment, etc.), manufacturing aspects (i.e., at-scale manufacturing, cost assessments, etc.) and experimental performance assessment (i.e., reliable experimental data, assessment of multiple PCM-working fluid combinations, etc.). We present a novel, comprehensive, and experimentally-validated design optimization framework for PCM-HXs capable of simulating any PCM-HX geometry with reasonable accuracy and significant computational time savings when compared to traditional CFD-based design practices. The framework was validated for a wide range of PCM-HX configurations, including a design optimization for a domestic hot water heater application where TES partially replaces electrical heating input. The resulting PCM-HXs were found to deliver 34-68% of the total daily hot water supply with only 5-10% package volume increase from the water heater, thus within U.S. DOE targets for TES systems. To identify the most promising HXs for PCM applications, first-order geometry and cost analyses were conducted based on off-the-shelf HX products. As part of this work, 9 PCM-HX prototypes were manufactured using additive and conventional manufacturing methods. Detailed economy-of-scale assessments were conducted for the most promising PCM-HXs and were found to have a good outlook for the next 5-10 years. The PCM-HX design optimization framework was validated through comprehensive in-house experimental testing using newly-developed PCM-to-fluid test facilities. In total,10 total in-house component-level experiments were conducted using these prototypes, including 9 with water and 1 with refrigerant (R410A) as the working fluid. It was found that the framework can successfully predict experimental thermal-hydraulic performance within ±10-20% the first time without manual design changes, eliminating the need for time-consuming and expensive prototyping efforts as part of the design process. As part of this work, a publicly-available PCM web tool was released which includes a PCM property database (531 PCMs) and PCM-HX modeling tool to assist the design community on common PCM-HX use-cases, e.g., single/multiple flow path(s) fluid-to-PCM and air-to-fluid-to-PCM configurations (https://ceeeweb.umd.edu/pcmapp/). This work will accelerate the design and time to market for next generation PCM-HXs.

25 ENERGY STORAGE↗

Multilevel graph embedding

The goal of the present paper is the design of embeddings of a general sparse graph into a set of points in $\mathbb{R}^d$ for appropriate d ≥ 2. The embeddings that we are looking at here aim to keep vertices that are grouped in communities together and keep the rest apart. To achieve this property, we utilize coarsening that respects possible community structures of the given graph. We employ a hierarchical multilevel coarsening approach that identifies communities (strongly connected groups of vertices) at every level. The multilevel strategy allows any given (presumably expensive) graph embedding algorithm to be made into a more scalable (and faster) algorithm. We demonstrate the presented approach on a number of given embedding algorithms and large-scale graphs and achieve speed-up over the methods in a recent paper.

97 MATHEMATICS AND COMPUTING↗