Photovoltaic cable jackets A comparison of representative products using combined-accelerated stress testing
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Miller, David C. (ORCID:0000000246985277)↗
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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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Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations
Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. In this study, we evaluate MCS simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25? horizontal resolution. We track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCS based on both cloud-top brightness temperature (Tb) and surface precipitation. Results from using Tb only to define MCS, commonly used in previous studies, are also discussed. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in the tropics and contiguous United States. This is mainly attributed to the underestimated precipitation intensity in EAMv2. In contrast, the simulated MCS frequency becomes more comparable to observations if MCSs are defined only based on cloud-top Tb. The Tb-based MCS tracking method, however, includes many cloud systems with very weak precipitation which conflicts with the MCS definition. This result illustrates the importance of accounting for precipitation in evaluating simulated MCSs. We also find that the new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are generally not improved. This suggests that simulating MCSs will remain a challenge for the next version of E3SM.
Zhang, Meng↗
A Fast Algorithm for Computing Zigzag Representatives
Zigzag filtrations of simplicial complexes generalize the usual filtrations by allowing simplex deletions in addition to simplex insertions. The barcodes computed from zigzag filtrations encode the evolution of homological features. Although one can locate a particular feature at any index in the filtration using existing algorithms, the resulting representatives may not be compatible with the zigzag: a representative cycle at one index may not map into a representative cycle at its neighbor. For this, one needs to compute compatible representative cycles along each bar in the barcode. It is known that the barcode for a zigzag filtration with m insertions and deletions can be computed $O(m^ω)$ in time, where $ω < 2.373$ is the matrix multiplication exponent. However, it is not known how to compute the compatible representatives so efficiently. For a non-zigzag filtration, the classical matrix-based algorithm provides representatives in $O(m^3)$ time, which can be improved to $O(m^ω)$. However, no known algorithm for zigzag filtrations computes the representatives with the $O(m^3)$ time bound. We present an $O(m^3 n)$ time algorithm for this problem, where $n ≤ m$ is the size of the largest complex in the filtration.
Persistent homology↗
Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response
Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive, that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the analysis. A representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response to evaluate the predictions representativeness, and thus relevance, of a microstructure scale electrochemical model. The microstructure parameter deviation propagations to the electrochemical response have been quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Representativity analysis determines a cell FOV of 144.4 × 154.4 μm 2 is large enough to establish a convergence on the representative section areas for low-intermediate C-rate (≤2.5 C), therefore positively concludes on the model representativeness for these rates, but is not large enough to conclude for higher rates.
25 ENERGY STORAGE↗
Representativity error scaling of models of the high temperature test facility
Error scaling is a critical step toward the validation of modeling capabilities for high-temperature gas-cooled reactors (HTGRs). Extensive effort is being made to bring HTGRs into the validation basis of numerous thermal-hydraulics codes. Here, this paper demonstrates how systems-level codes can be leveraged to perform error scaling analyses between an experimental facility and a plant-to-be facility. Specifically, we focus on two conduction cooldown experiments from the High Temperature Test Facility (HTTF) and the General Atomics 350 MW th modular high-temperature gas-cooled reactor (MHTGR-350). The error scaling methodology employed in this study is representativity, which in the context of this work was used to quantify how well experiments captured the physics of the plant facility by comparing sensitivity vectors between the two facilities. In addition, two different RELAP5–3D models of the HTTF were included in the comparison to determine if modeling methodologies notably impact the representativity results. The key figures of merit are the maximum block temperature and the coolant outlet temperature. The time-dependent maximum block temperature had a low representativity of below 0.1 for both models across both transients. The coolant outlet temperature had a higher representativity of around 0.6 for both models during the pressurized conduction cooldown, but it was below 0.2 for the depressurized conduction cooldown. Overall, the HTTF experiments were not representative of the transients in the MHTGR-350. However, these results can play a significant role in informing future potential experiments for HTGR systems that iterate on what the HTTF accomplished.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Impact of representative ground motion level on seismic PSA with the boundary between overestimation and underestimation
One commonly used approach in seismic probabilistic safety assessment (PSA) is the discrete method. This method follows the standard PSA framework and can be applied to various models, such as multi-unit models, while reducing computational costs using standard software. However, due to the inability to subdivide intervals infinitely, the discrete method approximates with a finite number of subintervals. In practice, different numbers of subintervals are applied, and the representative ground motion level is selected based on expert judgment. When employing a smaller number of subintervals, it is important to take caution to prevent underestimation. This study analyzes the impact of the representative ground motion level on seismic risk. It confirms that underestimation can occur with a small number of subintervals depending on the representative ground motion level. This study also proposes a method for determining the boundary of underestimation and overestimation. The method is demonstrated through examples, providing a mathematical foundation for selecting appropriate representative ground motion levels. By avoiding underestimation, this research helps prevent the oversight of significant risk contributors and enhances the understanding of seismic risk.
99 - GENERAL AND MISCELLANEOUS↗
The Freundlich isotherm equation best represents phosphate sorption across soil orders and land use types in tropical soils of Puerto Rico
Biomass production in the lowland wet tropical forest is greater than in any other biome, and it is typically limited by soil phosphorus (P) availability. However, the mechanisms involved in the P cycle remain poorly represented in Earth System Models (ESMs). Soil P sorption processes are key in the P cycle and for understanding the extent of P limitation for plant productivity. Currently, a few ESMs include isotherm equations to model these processes. Although the Langmuir equation is widely cited, other isotherm equations may better describe sorption in tropical soils. Here, we use a diverse range of soil samples from Puerto Rico to test the validity of the Langmuir, Freundlich, and Temkin equation. We found that across four soil orders (Inceptisols, Mollisols, Oxisols, Ultisols), and forested and cultivated land use types, the Freundlich equation best represented soil P sorption. Furthermore, the Langmuir and the Temkin equations poorly represent soil P adsorption, especially at low P concentrations. Specifically, the Langmuir equation underestimated soil P adsorption by 40% and the Temkin equation overestimated adsorption by 76%. We also found, as expected, that soil clay content and pH were the most important parameters explaining the variability of the Freundlich (K f ) constant. Greater clay content and lower pH, common in highly weathered Ultisols and Oxisols which are abundant in the tropics, led to greater K f values. Overall, our results suggest that a diversity of soils can prompt underestimation of P sorption when using the Langmuir isotherm, which leads to an overestimation of available P that can have repercussions on ESM predictions of the P cycle and tropical forest productivity.
Earth system models↗
A New Shutdown Dose Rate Benchmark Problem for Representative Fusion Applications
Here, this work introduces a new benchmark problem for calculating shutdown dose rates (SDDRs) aimed at fusion reactor applications. The model is designed to represent a simplified version of a typical ITER port plug. The responses of interest include neutron flux, gamma flux, and gamma SDDR at 12 different locations scattered throughout the port. This article outlines the geometry specifications of the problem, provides material definitions for the components, specifies the required responses to be calculated, and presents the source definition information. The need for this benchmark arises from the limited availability of publicly accessible references, with only one benchmark representing the typical dimensions and materials found in fusion systems. This existing benchmark has been cited extensively, reflecting the demand within the scientific community to test both established and novel workflows for SDDR calculations. However, since its presentation at a conference in 2011, the results have become increasingly well known. Moreover, the absence of formal publication and peer review has led to the details of this benchmark being extracted from secondary sources, such as subsequent studies that reference it. As a result, analysts are left with significant flexibility in interpreting the key parameters, which can be adjusted to account for unknown systematic errors, ultimately reproducing the already well-known responses. This new benchmark serves as an updated version of that earlier work, with the aim of providing a more reliable description of the materials and their impurities, which is crucial for assessing activation and subsequent gamma emission. Additionally, it seeks to provide a geometry that more closely represents an ITER port plug. The improvements in the problem definition will lead to a more reproducible benchmark problem, while also presenting the radiation transport community with a completely new challenge. The results will be published in a future article to allow analysts adequate time to analyze this problem independently.
Benchmark↗
On the bulk compaction of brittle granular materials, Part II: Representing interparticle comminution by K COMP
An applied and empirical compaction fracture resistance parameter, K COMP , was developed to represent the compression-induced interparticle-comminution response of granular brittle materials (e.g., ceramic or glass particles). The development of K COMP is an outcome from Part I of this three-paper series. The K COMP represents a continuum response of compaction fracture resistance and was adapted from established Griffith linear elastic fracture mechanics theory. From that, the K COMP relates macroscopically applied compressive stress to a corresponding inverse-square-root representative particle size, where the latter is estimated from an entire particle size distribution or specific surface area measurement. In conclusion, the K COMP value was not constant over a wide range of stresses for all examined brittle granular materials, and this is indicative of a change in the dominant mode of permanent deformation at higher compaction stresses.
brittle↗
Do we have globally representative data to understand soil processes?
Understanding and modeling soils and soil organic matter (SOM) are central to a variety of human needs, from food production to ecosystem management. Soil data have been collected for over a century, but the global spatial and process representativeness of soil data remains unclear. We assessed the representativeness of currently available soil data that could be used to understand a variety of SOM processes. We used 16 open-source soil databases and data from over 281,000 unique locations globally, categorizing the databases into three main data types necessary to understand SOM processes: soil carbon stocks and fluxes, mechanistic drivers of these stocks and fluxes, and soil carbon gain or loss potential. We found that stock and driver data have extensive global coverage. However, data on soil carbon gain or loss potential, particularly data describing change in soils over time such as time series data, are severely limited in their global coverage. We conclude that while significant strides have been made in measuring soil carbon stocks and fluxes, and their drivers, we are limited in global data related to changes in soils over time. Our recommendations for soil data generators are to ensure precise metadata reporting and prioritizing sampling in underrepresented areas like tropical, arctic, mountainous, wetland and arid regions. We also encourage designing revisit schemes that explicitly support change detection and reporting multi-modal datasets that can aid in model development. Targeted measurement of low coverage soil data types and regions is necessary for a range of applications including current and future biogeochemical predictions, and their management and policy implications.
carbon fluxes↗
RAVEN Template for Dynamic Representativity Analysis of the High Temperature Test Facility
These slides present a walkthrough of the template that has been developed for using RAVEN to perform representativity analysis using models of the High Temperature Test Facility and the General Atomics Modular High Temperature Gas-cooled Reactor. The presentation provides participants in the HTTF benchmark with a walkthrough on how to use RAVEN for their sensitivity analysis and how to read results from the MHTGR-350 to perform representativity
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Fully implicit crystal plasticity models representing orientations with modified Rodrigues parameters
Here, this work describes a crystal plasticity formulation combining several mathematical, numerical, and implementation choices to produce a highly efficient model. Specifically, the key choices in the implementation are (1) representing orientations with modified Rodrigues parameters, (2) implementing a fully coupled implicit time integration for the elastic stretch, the crystal orientations, and the model internal variables, (3) implementing the model in the NEML2 constitutive modeling framework, based on PyTorch, to vectorize the calculations and port the computation to GPUs and other hardware accelerators, and (4) an exact implementation of the consistent tangent matrix, even for arbitrary coupling to other field variables beyond the displacements, like temperature, neutron fluence, etc. The first two features of the model are, to our knowledge, novel. The paper considers each of these choices individually as well as the final model as a whole. This includes a full description of modified Rodrigues parameters, their advantages over other representations of orientations, the mathematical formulae and tools required to implement a model with modified Rodrigues parameters, and a detailed description of the geometry of the space of modified Rodrigues parameters (in an appendix). It also includes a description of a fully implicit time integration scheme for the orientations and the advantages in representing orientations with modified Rodrigues parameters in implementing such a model. The work then assess, via numerical examples, the advantages of fully coupled implicit time integration versus more common decoupled and explicit time integration schemes. These studies demonstrate the computational advantages of fully coupled integration versus other time integration algorithms, though the performance of the competing models depends on the complexity of the underlying single crystal model. The study concludes by demonstrating that the choice of time integration method affects the sharpness of the predicted texture, with explicit methods for integrating the orientations overestimating texture sharpness and implicit methods underestimating texture sharpness.
Crystal plasticity↗
Representing Anthropogenic Dust From Agricultural Sources in E3SMv1: Implementation, Evaluation, and Assessment of the Radiative Forcing
Dust emissions related to anthropogenic activities (i.e., anthropogenic dust) is not represented in most global climate models and its radiative impact remains unassessed. In this study, we develop a new and physically based method to parameterize anthropogenic dust emission from agricultural sources (i.e., agricultural dust, or AD) based on the DOE's Energy Exascale Earth System Model version 1 (E3SMv1). This method relates AD emission to the crop land use fraction in the E3SMv1 land component. Major AD sources simulated by our parameterization include those over Central America, the Sahel, North India, and North China. The annual averaged AD emission with diameter less than 10 μm is 567 Tg yr −1 in present-day (year 2000), which contributes to 13.3% of total dust emission. Model evaluation against satellite and ground-based observations shows that the new parameterization can represent AD emissions and global dust cycle reasonably well. We find that the total dust emission increases by 13.1% (495 Tg yr −1 ) from 1850 to 2000 due to the cropland land use fraction changes without considering the impact from climate changes. This induces a net dust direct effective radiative forcing of −0.041 W m −2 at top of the atmosphere. This dust-induced cooling exceeds 10% of the total anthropogenic aerosol direct effective radiative forcing from 1750 to 2014 estimated by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Our findings indicate an important role of anthropogenic dust in global climate change, which should be included in future climate change assessments.
agricultural dust↗
Generalized representative structures for atomistic systems
A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. the chemical disorder) of a large random alloy within a small crystal structure. The ability to generate small representations of random alloys, along with the restriction to crystal systems, results from using the fixed-lattice cluster correlations to describe structural characteristics. A more general description of the structural characteristics of atomic systems is obtained using complete sets of atomic environment descriptors. These are used within for generating representative atomic structures without restriction to fixed lattices. A general data-driven approach is provided here utilizing the atomic cluster expansion (ACE) basis. The N-body ACE descriptors are a complete set of atomic environment descriptors that span both chemical and spatial degrees of freedom and are used within for describing atomic structures. The generalized representative structure (GRS) method presented within generates small atomic structures that reproduce ACE descriptor distributions corresponding to arbitrary structural and chemical complexity. It is shown that systematically improvable representations of crystalline systems on fixed parent lattices, amorphous materials, liquids, and ensembles of atomic structures may be produced efficiently through optimization algorithms. With the GRS method, we highlight reduced representations of atomistic machine-learning training datasets that contain similar amounts of information and small 40–72 atom representations of liquid phases. The ability to use GRS methodology as a driver for informed novel structure generation is also demonstrated. The advantages over other data-driven methods and state-of-the-art methods restricted to high-symmetry systems are highlighted.
atomic cluster expansion↗
Derivation of A Representative Elementary Volume (REV) for Upscaled Two-Phase Flow in Porous Media
Relative permeability plays an important role in the upscaling of multiphase flow in porous media from the pore scale to the Darcy scale. The entire concept of relative permeability is contingent on the existence of a representative elementary volume (REV). As we move to smaller samples to measure relative permeability, such as with digital core analysis, the concept of a classical REV has become increasingly unlikely when using the conventional approach to defining a representative volume. The “‘conventional”’ understanding of an REV is that a large enough volume must be considered such that spatial variability averages out. In digital rock methods, such as pore-scale simulations based on micro-computed tomography (CT) images, the domain size is typically 2 to 4 mm. This is approximately the length scale of a single-phase flow REV using the classic REV approach. However, the single-phase perspective does not consider the complex dynamics and fluctuations often observed in multiphase flow systems, even at centimeter-scale experiments and/or simulations. A fundamental question is, therefore, whether the domain size commonly used in digital rock simulations can provide a consistent energy budget such that the concept of relative permeability exists. Based on first principles, relative permeability accounts for the rate of energy dissipated in a stationary process. If the dynamics are fluctuating, the energy dissipated can vary but will average out over a long enough timescale. The key to determining the validity of the relative permeability is the timescale of the measurement, not the spatial scale. The conventional REV theory assumes that spatial, temporal, and ensemble averages are equivalent in an ergodic system, but it does not provide a way to test this assumption. We provide a formal way to identify the timescale where the relative permeability accurately captures energy dissipation as a way to validate relative permeability measurements and quantitatively assess their accuracy. This result will be tested for a practical SCAL test, determining how long a flow experiment needs to be run to accurately characterize the rate of energy dissipation by the flow. The outcome will be a best practice guide for the determination of relative permeability from core-scale experiments and/or digital core simulations that ensure the energy budget is fully accounted for in the relative permeability coefficient.
Mcclure, James [Virginia Tech, Blacksburg]↗
Qualitative and Quantitative Evaluation for Representative Human Reliability Analysis Methods
The Korea Institute of Nuclear Safety (KINS) is the regulatory expert organization established by the Korean government to strengthen the nation’s technical capabilities relating to nuclear safety regulation. KINS oversees the technical aspects of nuclear safety regulation, including safety reviews, inspections, education, and safety research—all conducted based on technical knowledge and accumulated regulatory experience. In 2023, KINS requested that Idaho National Laboratory (INL) validates representative human reliability analysis (HRA) methods used throughout the world, thus affording KINS with a basis for determining an HRA method adequate for its domestic regulatory purposes. The present paper mainly examines INL’s efforts in this regard. The resulting INL study covered four representative HRA methods widely used by nuclear utilities and regulatory institutes. These methods were qualitatively evaluated by applying specific evaluation criteria and determining how well each method reflected critical HRA issues. For this assessment, INL benchmarked the Halden International HRA Empirical Study. Using the Halden empirical data, along with information on human failure events (HFEs), the present study employed the selected HRA methods to estimate human error probabilities (HEPs) for the HFEs. It also performed statistical analyses to compare the HEPs predicted via the HRA methods against those from the Halden empirical data.
99 - GENERAL AND MISCELLANEOUS↗
Energy efficiency and thermal resilience analysis for row houses using representative building energy models
Row houses, a prevalent medium-density urban archetype, were popularized during industrial era to accommodate the working class in the U.S. cities. Today, many of these structures are deteriorating, exacerbating the energy cost for residents with limited economic resources. Moreover, many households that lack Air Conditioning (AC) are vulnerable to extreme summer heat, an issue expected to worsen in the future. Energy-efficient retrofits can help mitigate these challenges. However, current literature provides limited insight into how existing building energy codes impact the energy efficiency and thermal resilience of row houses in current and future weather scenarios. This study provides a detailed method to address this gap by employing calibrated representative energy models of row houses as a baseline, and evaluating the annual energy savings and summertime thermal safety improvements from code compliant retrofits under current and future typical weather conditions. Using Baltimore City as a case study, results show that under current weather, retrofitting row houses yields significant energy savings along with notable thermal resilience improvements. The end unit row house realizes higher energy savings, whereas the interior unit experiences greater thermal resilience improvement after retrofitting. In future, retrofitted row houses can still save energy, but residents will face numerous hours of fatal indoor temperatures without AC in summer. Additionally, findings reveal stark zone-wise variations in thermal safety, and elevated humidity risks in certain zones post-retrofit, emphasizing the need for zonal retrofit strategies and better natural ventilation strategies.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Effects of non-monochromaticity in laboratory XPS: Representative example of pyrimidine
The Mg and Al K α radiation used in standard laboratory sources for X-Ray Photoelectron Spectroscopy, XPS, is not naturally monochromatic because the spin orbit splitting of the Mg and Al 2p shells is not normally resolved. However, since the 2p spin-orbit splitting of the K α1 and K α2 X-Rays in these light atoms is small, it is normally ignored. In the present work, the consequences of the departure from monochromaticity is explicitly shown to be extremely small for the representative case of the C(1 s) ionizations in the XPS of the pyrimidine molecule. Furthermore, this conclusion is general and does not depend on the particular molecule studied since the K α1 and K α2 BE splittings reflect the spin-orbit splittings in the X-Ray source.
Binding Energies (BEs)↗