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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 307 records · Page 17

Machine-Protection System for the PIP-II Linear Accelerator: Architecture and Data Processing Schemes

PIP-II at Fermilab features a brand-new, 800 MeV leading-edge Linear Accelerator (Linac) that will enable the Fermilab complex to deliver more than a megawatt of beam power to the Long Base-line Neutrino Facility (LBNF), requiring a robust Machine Protection System (MPS) to prevent beam-induced damage to delicate cryomodules and vacuum components. Signals in various accelerator components, in both analog and digital format, are collected and processed to assest the operating conditions of the accelerator. In the situation a potential damage is foreseen, the beam permit signal will be drop. A critical element of this system is the fast Analog Machine Protection System, a high-bandwidth platform designed for real-time beam loss monitoring. The system utilizes a modular, FPGA-based architecture to digitize signals from beam-sensing devices, such as AC Current Transformers (ACCTs), non-invasive Ring Pickups (RPUs) and beam scrapers. To eliminate both high frequency as well as 60 Hz noise that might be picked up in the industrial environment, data processing schemes beyond regular digital filtering are planned and implemented.

Wu, Jinyuan [Fermilab] (ORCID:0000000344329521)↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

Generator Frequency Response Droop Monitoring Tool

Monitoring and analyzing the frequency response performance of power generation units is essential for maintaining reliable and secure power system operation. To address this need, an automation tool has been developed to provide a pipeline for processing historical power plant generation data, including large-scale SCADA archives. The tool performs end-to-end processing, including event detection, frequency response (FR) analysis in accordance with NERC standards, and estimation of speed governor droop characteristics. The tool is designed with a modular architecture, allowing individual components of the workflow to be extended, customized, or deployed independently. In addition, the tool provides an API that enables seamless integration with other production systems and operational analytics platforms.

Etingov, PavelV [Pacific Northwest National Labora↗

LAROMance Grade 91 Model Integration in NEML2

New reactor designs are targeting higher operating temperatures for increased thermal efficiency when compared to the current fleet of light water reactors. Designing structural components for these high temperature environments with reliable long-term operations requires material models that can accurately capture the deformation mechanisms active in these environments. The LAROMance surrogate material models are based on a database of mechanistic crystal plasticity simulations for high-temperature conditions. Inputs to the LAROMance models reflect the microstructural pedigree of the material, like dislocation densities and precipitate contents. Based on the evolution of these microstructural features, the LAROMance model provides the engineering scale constitutive model response. The LAROMance model was recently parameterized for Grade 91, a high temperature alloy. In the present work, the Grade 91 LAROMance model is implemented in the New Material Model Library, version 2 (NEML2). NEML2 provides a modular way to build material models from smaller blocks and was developed to vectorize the material update to efficiently run on modern computational architectures with graphics processing unit accelerators. NEML2 constitutive models can be used in simulations based on the multiphysics object-oriented simulation environment (MOOSE). This report provides details on the implementation of the Grade 91 LAROMance model in NEML2 and its verification of engineering scale finite element simulations in MOOSE.

42 - ENGINEERING↗

ParFlow

ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.

Smith, Steven↗

ParFlow

ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.

Smith, Steven↗

A Modularized Urban Scale Building Energy Modeling Framework Designed with An Open Mind

In recent years, physics-based building energy modeling (BEM) has started being used to evaluate the performance of buildings in the context of connected communities and on an urban scale to study their aggregated energy use, interactions, and impacts on the energy supply infrastructure and environment. The development of urban-scale BEM solutions needs extensive effort. Existing attempts tend to focus on different aspects of BEM on an urban scale, such as collecting as-built building data from different information sources, integrating geometry modeling with geographic information systems (GISs), representing operational and occupancy profiles, automating workflow, processing and visualizing the results, and conducting large-scale simulations. Urban-scale BEM development would benefit from multi-disciplinary research areas and from an open platform to adopt advancements on data sources and tools. For these purposes, this research proposes a modularized bottom-up model creation and simulation framework that is built on the state-of-the-art BEM tools and can accommodate different building stock data. This framework uses a standardized schema to describe building design and operational characteristics, and it can be instantiated from different building survey datasets with heterogeneous structures. The paper demonstrates how thousands of surveyed buildings from the 2012 U.S. Energy Information Administration’s Commercial Buildings Energy Consumption Survey (CBECS) were one-to-one converted to EnergyPlus models through the schema and the model generation process, then simulated with distributed computing, and their results are summarized.

Lei, Xuechen↗

Intern Poster Session

This poster has been developed for display during the 2023 Intern Poster Session. The poster is apart of the Nuclear Research and Experiments category. The focus of this poster is on the modifications made to the design of an integral effect test (IET) facility currently being designed for a new Small Modular Reactor (SMR) design. My contributions made to the IET facility are laid out along with an explanation on some of the aspects of designing a new nuclear reactor. This poster covers the ideas and importance of scaling and IET facilities with the context of the standards set by the NRC. There are also graphics of some other examples of IET facilities developed for other reactor designs. My contributions include designing the piping and instrumentation layout of the IET facility using CAD software. This is a key step in the process of designing this IET facility and needs to be designed to avoid excessive head loss.

42 ENGINEERING↗

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗

Promoting the Furan Ring‐Opening Reaction to Access New Donor–Acceptor Stenhouse Adducts with Hexafluoroisopropanol

Abstract Donor–acceptor Stenhouse adducts (DASAs) are visible‐light‐responsive photoswitches with a variety of emerging applications in photoresponsive materials. Their two‐step modular synthesis, centered on the nucleophilic ring opening of an activated furan, makes DASAs readily accessible. However, the use of less reactive donors or acceptors renders the process slow and low yielding, which has limited their development. We demonstrate here that 1,1,1,3,3,3‐hexafluoro‐2‐propanol (HFIP) promotes the ring‐opening reaction and stabilizes the open isomer, allowing greatly reduced reaction times and increased yields for known derivatives. In addition, it provides access to previously unattainable DASA‐based photoswitches and DASA–polymer conjugates. The role of HFIP and the photochromic properties of a set of new DASAs is probed using a combination of 1 H NMR and UV/Vis spectroscopy. The use of sterically hindered, electron‐poor amines enabled the dark equilibrium to be decoupled from closed‐isomer half‐lives for the first time.

Clerc, Michèle↗

Promoting the Furan Ring‐Opening Reaction to Access New Donor–Acceptor Stenhouse Adducts with Hexafluoroisopropanol

Abstract Donor–acceptor Stenhouse adducts (DASAs) are visible‐light‐responsive photoswitches with a variety of emerging applications in photoresponsive materials. Their two‐step modular synthesis, centered on the nucleophilic ring opening of an activated furan, makes DASAs readily accessible. However, the use of less reactive donors or acceptors renders the process slow and low yielding, which has limited their development. We demonstrate here that 1,1,1,3,3,3‐hexafluoro‐2‐propanol (HFIP) promotes the ring‐opening reaction and stabilizes the open isomer, allowing greatly reduced reaction times and increased yields for known derivatives. In addition, it provides access to previously unattainable DASA‐based photoswitches and DASA–polymer conjugates. The role of HFIP and the photochromic properties of a set of new DASAs is probed using a combination of 1 H NMR and UV/Vis spectroscopy. The use of sterically hindered, electron‐poor amines enabled the dark equilibrium to be decoupled from closed‐isomer half‐lives for the first time.

Clerc, Michèle↗

Shining Light on Halide Perovskites: Teaching Analytical Chemistry Using Flexible, Inquiry-Based Experiments

Two-dimensional (2D) metal halide perovskites are promising next generation semiconducting materials at the forefront of research in solar cells, LEDs, and other devices. Here, we report on an undergraduate intermediate analytical chemistry laboratory experience where students were taught fundamental chemistry concepts, including solubility, complexation, spectroscopy, and microscopy, through the introduction and study of 2D halide perovskite materials. Students explore multiple facets of perovskite synthesis, structure, and properties through a modular set of experiments that students used to form a holistic picture of this material. Importantly, this inquiry-based lab supports students through a guided research process, and students report high interest and learning gains from an end of the semester survey. We further discuss ways to adapt this lab to course, student, equipment, and budget needs. Overall, this laboratory experience teaches and applies the fundamental concepts and tools of analytical chemistry to the contemporary materials research field.

Analytical Chemistry↗

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.

computation↗

A reference open-source controller for fixed and floating offshore wind turbines

Abstract. This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5 MW reference wind turbine and International Energy Agency 15 MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10 % compared to the NREL 5 MW reference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30 % when using the platform feedback routine instead of a more traditional low-bandwidth controller.

17 WIND ENERGY↗

Solar light systems, and related components and methods

A solar light system may include two stages of optical concentration with intermediate removal of infrared radiation between the optical concentration stages. A second stage of optical concentration may prepare multiple concentrating beams of processed solar radiation with visible light with each such concentrating beam directed to a different corresponding light conduit for transmission to an interior space for interior lighting. System modularization may provide flexibility to accommodate a variety of interior lighting applications.

14 SOLAR ENERGY↗

Renewable Energy for Industrial Environmental Management

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has grown exponentially as they become cost competitive. Simultaneously, industrial and manufacturing processes have been increasingly seeking ways to reduce emissions and operational costs in highly competitive sectors. With these combined drivers of lower cost and reduced environmental impact, renewable energy may become a viable energy provider for industrial processes such as oil and gas, mining, chemical refining, food production, and manufacturing. Renewable energy technologies may also partner with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization, to create cleaner and circular industrial systems for reduced resource use. The Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of the National Renewable Energy Laboratory (NREL) and five universities and others, has been studying to potential for application of clean energy technologies to the heterogenous energy demands in industry. Dr. Jill Engel-Cox will present an overview of NREL and JISEA, the status and potential future of renewable energy technologies, and collaborations with the oil and gas industry and other industrial sectors to improve their environmental performance and reduce operational costs.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Solid-state rigid-rod polymer composite electrolytes with nanocrystalline lithium ion pathways

A critical challenge for next-generation lithium-based batteries lies in development of electrolytes that enable thermal safety along with use of high-energy-density electrodes. We describe molecular ionic composite (MIC) electrolytes based on an aligned liquid crystalline polymer combined with ionic liquids and concentrated Li salt. This high strength (200 MPa) and non-flammable solid electrolyte possesses outstanding Li + conductivity (1 mS cm -1 at 25 °C) and electrochemical stability (5.6 V vs Li|Li + ) while suppressing dendrite growth and exhibiting low interfacial resistance (32 Ω cm 2 ) and overpotentials (≤ 120 mV @ 1 mA cm -2 ) during Li symmetric cell cycling. A heterogeneous salt doping process modifies a locally ordered polymer-ion assembly to incorporate an inter-grain network filled with defective LiFSI & LiBF 4 nanocrystals, strongly enhancing Li + conduction. Furthermore, this modular material fabrication platform shows promise for safe and high-energy-density energy storage and conversion applications, incorporating the fast transport of ceramic-like conductors with the superior flexibility of polymer electrolytes.

25 ENERGY STORAGE↗

Saltstone Waste Characterization Analysis - Salt Waste Processing Facility (SWPF) Waste Stream (Q4 CY2020)

The Saltstone Production and Disposal Facility is designed and permitted by the state of South Carolina Department of Health and Environmental Control (SCDHEC) to treat and dispose of low-level radioactive and hazardous liquid waste (salt solution) remaining from the processing of radioactive material at the Savannah River Site (SRS). Low-level waste (LEW) aqueous streams from the Effluent Treatment Project (ETP) and decontaminated solutions from the Tank Closure Cesium Removal Unit (TCCR) and the Salt Waste Processing Facility (SWPF) are stored in Tank 50 until the LEW can be transferred to the Saltstone Facility for treatment and disposal. In the past, decontaminated solution from the Modular Caustic Side Solvent Extraction Unit (MCU) was stored in Tank 50 until the LEW could be transferred to the Saltstone Facility for treatment and disposal. MCU is currently in a suspended operations state. LEW that meets the Waste Acceptance Criteria (WAC) can be transferred, stored, and treated in the Saltstone Production Facility (SPF) for subsequent disposal as saltstone grout in the Saltstone Disposal Facility (SDF). Sampling will be conducted as new waste streams are identified for treatment and disposal at the Saltstone Industrial Wastewater Treatment Facility (IWTF) and Z-Area Industrial Solid Waste Landfill (ISWLF), Facility ID# 025500-1603, General Condition B.9 or every six years in accordance with South Carolina (SC) Regulation 61-107.19 Parti C, “Solid Waste Management: Solid Waste Landfills and Structural Fill - General Requirements.”

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗