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At least 775 records · Page 43

Commercial Energy Code Compliance – Just the Facts, Ma’am

What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. This paper builds on the methodology presented at the 2016 Summer Study and provides a first glimpse of the results as seen in the field. The field study team has implemented the pilot methodology, compiling a data set of over 200 office and retail buildings in climate zones 2A and 5A. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This paper will review the findings of that analysis, discuss critical aspects of the methodology, such as sampling and recruitment strategies, and identify areas where the greatest return—bang for the buck—exists in improving compliance with codes in commercial buildings. In addition, the team will make specific recommendations for jurisdictions looking to use the methodology to maximize energy code savings achieved in the field.

Cheslak, Kimberly↗

SCALE 6.3 Validation: Reactor Physics

This study was performed to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the ENDF/B-VII.1 AMPX 56-group library for light-water reactor analysis by comparing the simulated results with the measured data for critical experiments and operating light-water reactors. Uncertainties of the SCALE/Polaris–PARCS code procedure for light-water reactor physics analysis were evaluated in the validation for key nuclear parameters such as reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors. In addition, the SCALE/TRITON v6.3.1 procedure with the ENDF/B-VII.1 and VIII.0 252-group and continuous-energy cross sections was validated for non-lightwater reactors including the HTR-10 reactor, the High-Temperature Test Reactor, the Molten Salt Reactor Experiment, and the Experimental Breeder Reactor II.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Code-verification techniques for hypersonic reacting flows in thermochemical nonequilibrium

The study of hypersonic flows and their underlying aerothermochemical reactions is particularly important in the design and analysis of vehicles exiting and reentering Earth's atmosphere. Computational physics codes can be employed to simulate these phenomena; however, code verification of these codes is necessary to certify their credibility. To date, few approaches have been presented for verifying codes that simulate hypersonic flows, especially flows reacting in thermochemical nonequilibrium. In this work, we present our code-verification techniques for verifying the spatial accuracy and thermochemical source term in hypersonic reacting flows in thermochemical nonequilibrium. Additionally, we demonstrate the effectiveness of these techniques on the Sandia Parallel Aerodynamics and Reentry Code (SPARC).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Neural network acceleration of large-scale structure theory calculations

Here, we make use of neural networks to accelerate the calculation of power spectra required for the analysis of galaxy clustering and weak gravitational lensing data. For modern perturbation theory codes, evaluation time for a single cosmology and redshift can take on the order of two seconds. In combination with the comparable time required to compute linear predictions using a Boltzmann solver, these calculations are the bottleneck for many contemporary large-scale structure analyses. Here, we construct neural network-based surrogate models for Lagrangian perturbation theory (LPT) predictions of matter power spectra, real and redshift space galaxy power spectra, and galaxy-matter cross power spectra that attain ~ 0.1% (at one sigma) accuracy over a broad range of scales in a ωCDM parameter space. The neural network surrogates can be evaluated in approximately one millisecond, a factor of 1000 times faster than the full Boltzmann code and LPT computations. In a simulated full-shape redshift space galaxy power spectrum analysis, we demonstrate that the posteriors obtained using our surrogates are accurate compared to those obtained using the full LPT model. We make our surrogate models public at https://github.com/sfschen/EmulateLSS, so that others may take advantage of the speed gains they provide to enable rapid iteration on analysis settings, something that is essential in complex contemporary large-scale structure analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗

Transformational challenge reactor analysis to inform preconceptual core design decisions: Sensitivity study of transient analysis in a hydride-moderated microreactor

The Transformational Challenge Reactor (TCR) program aims to demonstrate a revolutionary design approach enabled by advanced manufacturing and data analytics in the design of nuclear reactors. This article discusses scoping analyses of preconceptual designs to inform TCR design decisions and the evaluation of sensitivities and uncertainties on postulated transient scenarios. The applicability of the systems codes TRACE and RELAP5-3D to TCR transient analysis are examined, and RELAP5-3D models are used to examine the transient response of two candidate core designs at multiple power levels. Then, the uncertainty quantification code RAVEN is used to quantify the effect of several design parameters on reactivity-initiated accident (RIA) progression at hot zero power (HZP) and hot full power (HFP) as well as to assess the impact of uncertainties in transient parameters for the pressurized loss of forced cooling (PLOFC).When results were compared, TRACE and RELAP5-3D showed good agreement in their ability to predict system behavior, but RELAP5-3D calculations were closer to analytical predictions for the RIA. Furthermore, models for a PLOFC accident in two designs (a UO2 and TRISO core) at multiple power levels showed greater temperature margins for the TRISO core at all power levels. Using this information, along with other scoping analyses and constraints, the TCR design team selected a power level of 3 MWth and a TRISO-based core design. For this design RAVEN was applied to vary RIA parameters in RELAP5-3D models at HZP and HFP to understand the effect on figures of merit such as peak power, fuel and coolant temperature, and energy deposition. This sensitivity study found that the inserted reactivity worth was the most important parameter controlling all figures of merit, but for insertion up to 1.5$ no failure of TCR fuel is anticipated. For constant reactivity insertions, the magnitude of the fuel temperature coefficient was found to have the greatest effect on all figures of merit under most circumstances. These results not only demonstrate the anticipated robust safety of the proposed TCR fuel form but also provide a reference for future metal-hydride moderated systems to understand RIA behavior. In the PLOFC, the impact of heat transfer enhancement due to wavy flow channel effects dominated the variance in peak temperatures, and variations in heat exchanger elevation provided the greatest control on natural circulation flow rate. Additionally, no fuel particle failure is anticipated in the PLOFC.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

OC6 Phase IV: Validation of CFD Models for Stiesdal TetraSpar Floating Offshore Wind Platform

ABSTRACT With only a few floating offshore wind turbine (FOWT) farms deployed anywhere in the world, FOWT technology is still in its infancy, building on a modicum of real‐world experience to advance the nascent industry. To support further development, engineers rely heavily on modeling tools to accurately portray the behavior of these complex systems under realistic environmental conditions. This reliance creates a need for verification and validation of such tools to improve reliability of load and dynamic response prediction and analysis capabilities of FOWT systems. The Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project was created under the framework of the International Energy Agency to address this need and considers a three‐sided verification and validation between engineering level models, computational fluid dynamics (CFD), and experimental results. In this paper, a novel floating offshore wind platform, the Stiesdal TetraSpar, is simulated using CFD under the load conditions defined by Phase IV of the OC6 project. The comparison of these CFD results against the experimental results demonstrated the ability to predict the platform response to waves when imposing the measured wave signals as input. Although validation versus experiment was largely successful, the damping behavior was impacted by uncertainties likely originating from the mooring system and sensor umbilical cable. This extensive comparison effort with multiple CFD practitioners offers insight into best practices to achieve reliable results.

17 WIND ENERGY↗

Performance of U 3 Si 2 in an LWR following a cladding breach during normal operation

High-density fuels have been proposed as a possible replacement for uranium-dioxide as a fuel for light water reactors (LWRs) due to their increased loading of fissionable material. The objectives of this proposal are (1) to increase reactor cycle length and reactor power, and (2) to offset any neutronic penalty associated with advanced cladding systems. Of the high-density fuels under consideration, there is particular interest in triuranium disilicide (U 3 Si 2 ) due to its increased metal density and favorable thermal properties as compared to UO 2 . However, there are concerns regarding the chemical compatibility of U 3 Si 2 with water and steam as used for LWR coolant.This paper summarizes research on fuel-coolant chemical compatibility for UO 2 LWR fuel during a cladding breach and highlights that generally, because of its chemical inertness, UO 2 -coolant reactions are of little consequence to reactor operation. However, the volumetric expansion associated with the reaction of UO 2 and oxygen is a concern for possible conditions encountered during air ingress of dry storage. These same concerns arise for U 3 Si 2 , which exhibits greater volumetric expansion than UO 2 when exposed to water or steam. These reactions ultimately result in increased fuel volume that the cladding must accommodate, as well as additional heat generated as the fuel reacts.The BISON fuel performance code was used to perform a comparative analysis on the behavior of UO 2 and U 3 Si 2 under normal operation. Silicide fuel simulations were then extended to demonstrate how varying thermodynamic and chemical kinetics influence fuel expansion and subsequent cladding performance during a cladding breach. These simulations were further extended to a 3D subsection of a fuel rod to demonstrate the characteristics of the resulting cladding crack.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ATLAS-MAP: An Automated Test Station for Gated Electronic Transport Measurements

The diversification of electronic materials in devices provides a strong incentive for methods to rapidly correlate device performance with fabrication decisions. In this work, we present a low-cost automated test station for gated electronic transport measurements of field-effect transistors. Utilizing open-source PyMeasure libraries for transparent instrument control, the “ATLAS-MAP” system serves as a customizable interface between sourcemeters and samples under test and is programmed to conduct transfer curve and van der Pauw methods with static and sweeping gate voltages. Zinc oxide transistors of variable thickness (5, 10, and 20 nm) and channel size (50 μm to 3 mm, of equal length and width) were fabricated to validate the design. Standardization of testing procedures and raw data formatting enabled automated data analysis. A detailed list of parts and code files for the system are provided.

36 MATERIALS SCIENCE↗

Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design workflow of a symmetric traveling wave antenna for fast ion production on DD tokamaks

Initial computational plasma physics scoping and a finite element method antenna modeling design workflow for a symmetric center-fed high-field side high harmonic fast wave traveling wave array (TWA) antenna are reported here. The TWA is designed to generate a test population of fast deuterium ions in an existing D–D tokamak by heating neutral beam deuterium ions, accelerating them from 80 keV to several hundred keV. The resulting fast particles are tailored to mimic key reactor energetic particle parameters with regards to exciting Alfven eigenmode instabilities, allowing for a D–D tokamak like DIII-D or ASDEX-U to replicate reactor-relevant conditions experimentally. Initial scenario scoping for high single-pass absorption as well as good preferential fast ion damping relative to electron damping was completed using the ray-tracing/Fokker–Planck codes GENRAY and CQL3D. Python RF network analysis packages were used to create a custom TWA optimization tool to inform a COMSOL flat antenna design, and Petra-M was used to study cold plasma effects. The TWA produced by this workflow has several novel features when compared to previous TWA studies, including symmetric center feeding, and passive end straps for image current cancellation for reduced impurity production. We show here that the antenna design workflow can readily produce TWA antennas optimized for reflection coefficient, image current cancellation, and launched power spectrum shape; and that a population of fast ions can be generated in the correct region of parameter space, warranting future more detailed studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

Abstract The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein–protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Genetics & Heredity↗

Evidence for triaxial shape coexistence in 74 Ge

The deformation properties of the low-lying states in 74 Ge have been investigated using multistep Coulomb excitation. The measurements were carried out with the advanced 𝛾-ray tracking array, GRETINA, and the CHICO2 particle detector. A comprehensive set of 𝐸⁢2 transition and diagonal matrix elements was deduced following an analysis with the semiclassical coupled-channels code GOSIA. The data were compared with results of calculations carried out within the framework of the generalized triaxial rotor model as well as with the configuration interaction shell model and the symmetric rotor model. Results from calculations with covariant density functional theory were used to construct a five-dimensional collective Hamiltonian for further comparisons with the data. Collectively, the calculations provide an accurate reproduction of the experimental matrix elements and further support an understanding in terms of the coexistence of two axially asymmetric shapes. In conclusion, this leads to an overall interpretation of the underlying structure of 74 Ge requiring triaxiality, as is also the case in the neighboring even-mass Ge isotopes.

59 ≤ A ≤ 89↗

ChemEnv : a fast and robust coordination environment identification tool

Coordination or local environments have been used to describe, analyze and understand crystal structures for more than a century. Here, a new tool called ChemEnv, which can identify coordination environments in a fast and robust manner, is presented. In contrast to previous tools, the assessment of the coordination environments is not biased by small distortions of the crystal structure. Its robust and fast implementation enables the analysis of large databases of structures. The code is available open source within the pymatgen package and the software can also be used through a web app available on http://crystaltoolkit.org through the Materials Project.

42 ENGINEERING↗

Shifting Left for Machine Learning: An Empirical Study of Security Weaknesses in Supervised Learning-based Projects

Context: Supervised learning-based projects (SLPs), i.e., software projects that use supervised learning algorithms, such as decision trees are useful for performing classification-related tasks. Yet, security weaknesses, such as the use of hard-coded passwords in SLPs, can make SLPs susceptible to security attacks. A characterization of security weaknesses in SLPs can help practitioners understand the security weaknesses that are frequent in SLPs and adopt adequate mitigation strategies. Objective: The goal of this paper is to help practitioners se-curely develop supervised learning-based projects by conducting an empirical study of security weaknesses in supervised learning-based projects. Methodology: We conduct an empirical study by quantifying the frequency of security weaknesses in 278 open source SLPs. Results: We identify 22 types of security weaknesses that occur in SLPs. We observe ‘use of potentially dangerous function’ to be the most frequently occurring security weakness in SLPs. Of the identified 3,964 security weaknesses, 23.79 % and 40.49 % respectively, appear for source code files used to train and test models. We also observe evidence of co-location, e.g., instances of command injection co-locates with instances of potentially dangerous function. Conclusion: Based on our findings, we advocate for a shift left approach for SLP development with security-focused code reviews, and application of security static analysis.

Bhuiyan, Farzana Ahamed↗

Analysis of prescribed fire days in climate model output

This code analyzes openly available, downscaled climate model output and counts days in a year that are available to conduct prescribed fire based on meteorological prescription data obtained from US land management agencies.

Jonko, Alexandra↗

LDES-Sizing-and-siting-model (Power grid test cases for long-duration energy storage (LDES) siting) [SWR-25-75]

This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). This analysis involves moving the LDES component to different buses in the system, running a simulation, and considering the production cost of the simulation. Different system configurations are also analyzed with these scripts (such as moving load or renewable dispatch generators to different buses) to observe the impacts the system configuration has on optimal siting. This repository contains three sub directories discussed below. Both the 5-bus and RTS systems have two different initial configurations for the renewable energy components in them, one that is predominantly PV-driven and one that is predominantly wind-driven. Sienna suite can be found here: https://github.com/NREL-Sienna

Cole, David [University of Wisconsin]↗