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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 235 records · Page 13

pvlib python: 2023 project update

pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).

14 SOLAR ENERGY↗

Towards Demonstration of Electron Cooling with Bunched Electron Beam

All electron cooling systems which were in operation so far employed electron beam generated with an electrostatic electron gun in DC operating mode, immersed in a longitudinal magnetic field. At low energies magnetic field is also being used to transport electron beam through the cooling section from the gun to the collector. At higher energies (few MeV), it was shown that one can have simpler electron beam transport without continuous magnetic field. Because of a rather weak magnetic field on the cathode and in the cooling section the latter approach was referred to as “non-magnetized cooling”, since there was no suppression of the transverse angular spread of the electron beam with the magnetic field in the cooling section. Such a cooler successfully operated at FNAL (2005-11) at electron beam energy of 4.3 MeV. Providing cooling at even higher energies would be easier with RF acceleration of electron beam, and thus using bunched electron beam for cooling. Significant efforts were devoted to explore various aspects of such bunched electron beam cooling as part of R&D of high-energy electron cooling for RHIC. However, experimental studies of such cooling are still lacking. Establishing this technique experimentally would be extremely useful for future high-energy applications. Presently there is an ongoing effort to build Proof-of-Principle (PoP) experiment of Coherent Electron Cooling (CEC) at RHIC, which promises to be superior to conventional electron cooling for high energies. Since the CEC experiment is based on bunched electron beam and it has sections where electron beam co-propagates with the ion beam at the same velocity, it also provides a unique opportunity to explore experimentally conventional electron cooling but for the first time with a bunched electron beam. As a result, it allows us to explore techniques needed for the high-energy electron cooling such as “painting” with a short electron beam and control of ion beam distribution under cooling which is essential if cooling is provided in a collider. The software needed for comparison with the experiments is already developed as part of the previous high-energy electron cooling studies for RHIC. Since electron beam will be non-magnetized and there will be no magnetic field in the cooling section it will be also a first demonstration of fully non-magnetized cooling. The purpose of these studies was to explore whether we would be able to observe conventional electron cooling with parameters expected in the CEC PoP experiment. Below we summarize requirements on electron beam and cooling section needed for such demonstration.

43 PARTICLE ACCELERATORS↗

nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]

The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection. Related to: https://github.com/NREL/Wattile

Frank, Stephen↗

WTFgenes: What's The Function of these genes? Static sites for model-based gene set analysis

A common technique for interpreting experimentally-identified lists of genes is to look for enrichment of genes associated with particular ontology terms. The most common test uses the hypergeometric distribution; more recently, a model-based test was proposed. These approaches must typically be run using downloaded software, or on a server. We develop a collapsed likelihood for model-based gene set analysis and present WTFgenes, an implementation of both hypergeometric and model-based approaches, that can be published as a static site with computation run in JavaScript on the user's web browser client. Apart from hosting files, zero server resources are required: the site can (for example) be served directly from Amazon S3 or GitHub Pages. A C++11 implementation yielding identical results runs roughly twice as fast as the JavaScript version. WTFgenes is available from https://github.com/evoldoers/wtfgenes under the BSD3 license. A demonstration for the Gene Ontology is usable at https://evoldoers.github.io/wtfgo.

Mungall, Christopher J.↗

Ducted Assembly Steady-State Heat Transfer Software (DASSH): Theory Manual

The Ducted Assembly Steady-State Heat transfer software (DASSH) is being developed at Argonne National Laboratory to obtain a steady-state thermal fluids result for the coolant flow and temperature distribution in a hexagonally gridded reactor core with ducted assemblies. In DASSH, each assembly is assumed to contain a hexagonal bundle of wire-wrapped pins. DASSH divides the coolant in the pin bundle into subchannels on which it applies energy balances to determine coolant and duct temperatures. DASSH offers multiple models for inter assembly heat transfer and features the ability to calculate pin temperatures. This document describes the models and equations implemented in DASSH. It includes a description of the geometric system to which the models are applied and a derivation of the subchannel energy balance formulation is presented. It also reviews the available correlations and provides an overview of the process by which power distributions are generated. Finally, it covers the code execution procedure, discussing the main code objects and their interactions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

MO-H-19A-03: Patient Specific Bolus with 3D Printing Technology for Electron Radiotherapy

Purpose: Bolus is widely used in electron radiotherapy to achieve desired dose distribution. 3D printing technologies provide clinicians with easy access to fabricate patient specific bolus accommodating patient body surface irregularities and tissue inhomogeneity. This study presents the design and the clinical workflow of 3D printed bolus for patient electron therapy in our clinic. Methods: Patient simulation CT images free of bolus were exported from treatment planning system (TPS) to an in-house developed software package. Bolus with known material properties was designed in the software package and then exported back to the TPS as a structure. Dose calculation was carried out to examine the coverage of the target. After satisfying dose distribution was achieved, the bolus structure was transferred in Standard Tessellation Language (STL) file format for the 3D printer to generate the machine codes for printing. Upon receiving printed bolus, a quick quality assurance was performed with patient resimulated with bolus in place to verify the bolus dosimetric property before treatment started. Results: A patient specific bolus for electron radiotherapy was designed and fabricated in Form 1 3D printer with methacrylate photopolymer resin. Satisfying dose distribution was achieved in patient with bolus setup. Treatment was successfully finished for one patient with the 3D printed bolus. Conclusion: The electron bolus fabrication with 3D printing technology was successfully implemented in clinic practice.

60 APPLIED LIFE SCIENCES↗

BSM (Bioenergy Scenario Model) FKA: Biomass Scenario Model [SWR-09-09]

The U.S. Department of Energy's Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario Model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry—feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.

Bush, Brian↗

BSM (Bioenergy Scenario Model) 2023 FKA: Biomass Scenario Model [SWR-09-09]

The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry—feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.

Bush, Brian↗

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CG-Kit: Code Generation Toolkit for performant and maintainable variants of source code applied to Flash-X hydrodynamics simulations

CG-Kit is a new Code Generation tool-Kit that we have developed as a part of the solution for portability and maintainability for multiphysics computing applications. The development of CG-Kit is rooted in the urgent need created by the shifting landscape of high-performance computing platforms and the algorithmic complexities of a particular large-scale multiphysics application: Flash-X. To efficiently use computing resources on a heterogeneous node, an application must have a map of computation to resources and a mechanism to move the data and computation to the resources according to the map. Most existing performance portability solutions are focussed on abstracting the expression of computations so that a unified source code can be specialized to run on different resources. However, such an approach is insufficient for a code like Flash-X, which has a multitude of code components that can be assembled in various permutations and combinations to form different instances of applications. Similar challenges apply to any code that has composability, where a single specified way of apportioning work among devices may not be optimal. Additionally, use cases arise where the optimal control flow of computation may differ for different devices while the underlying numerics remain identical. This combination leads to unique challenges including handling an existing large code base in Fortran and/or C/C++, subdivision of code into a great variety of units supporting a wide range of physics and numerical methods, different parallelization techniques for distributed and shared memory systems and accelerator devices, and heterogeneity of computing platforms requiring coexisting variants of parallel algorithms. All of these challenges demand that scientific software developers apply existing knowledge about domain applications, algorithms, and computing platforms to determine custom abstractions and granularity for code generation. There is a critical lack of tools to tackle those problems. CG-Kit is designed to fill this gap by providing a user with the ability to express their desired control flow and computation-to-resource map in the form a pseudocode-like recipe. It consists of standalone tools that can be combined into highly specific and, we argue, highly effective portability and maintainability toolchains. Here we present the design of our new tools: parametrized source trees, control flow graphs, and recipes. The tools are implemented in Python. They are agnostic to the programming language of the source code targeted for code generation. In conclusion, we demonstrate the capabilities of the toolkit with two examples, first, multithreaded variants of the basic AXPY operation, and second, variants of parallel algorithms within a hydrodynamics solver, called Spark, from Flash-X that operates on block-structured adaptive meshes.

Algorithmic portability↗

KIVA-Update June 2012

Development of a fractional step, a Predictor-Corrector Split (PCS), or what is often known as a projection method combining hp-adaptive system in a Finite Element Method (FEM) for combustion modeling has been achieved. This model will advance the accuracy and range of applicability of the KIVA combustion model and software used typically for internal combustion engine modeling. This abstract describes a PCS hp-adaptive FEM model for turbulent reactive flow spanning all velocity regimes and fluids that is being developed for the new KIVA combustion algorithm, particularly for internal combustion engines. The method and general solver is applicable to Newtonian and non- Newtonian fluids and also for incompressible solids, porous media, solidification modeling, and fluid structure interaction problems. The fuel injection and injector modeling could easily benefit from the capability of solving the fluid structure interaction problem in an injector, helping to understand cycle to cycle variation and cavitation. This is just one example where the new algorithm differs from the old, in addition to handling Conjugate Heat Transfer (CHT), although there a numerous features that makes the new system more robust and accurate. In these ways, the PCS hp-adaptive algorithm does not compete with commercial software packages, those often used in conjunction with the currently distributed KIVA codes for engine combustion modeling. In addition, choosing a local ALE method on immersed moving parts represented by overset grid that is 2nd order spatially accurate, allows for easy grid generation from CAD to fluid grid while also provide for robustness in handling any possible moving parts configuration without any code modifications. The combined methods employed produce a minimal amount of computational effort as compared to fully resolved grids at the same accuracy. We demonstrate the solver on benchmark problems for the all flow regimes as follows: (1) 2-D backward-facing step using h-adaption, (2) 2-D driven cavity, (3) 2-D natural convection in a differentially heat cavity with h-adaptation, (4) NACA 0012 airfoil in 2-D, (5) supersonic flows over compression ramps, (6) 2-D natural convection in a differentially heat cavity with hp-adaptation, (7) 3-D natural convection in a differentially heat sphere with hp-adaptation. In addition, we show the new moving parts algorithm for working for a 2-D piston; the immersed moving parts method also for valves and pistons, vanes, etc... The movement is performed using an overset grid method and is 2nd order accurate in space, and never produces a tangle grid, that is, robust system at any resolution and any parts configuration. We also show CHT for the currently distributed KIVA-4mpi software and some fairly automatic grid generation using Sandia's Cubit unstructured grid generator. A new electronic web-based manual for KIVA-4 has been developed as well.

02 PETROLEUM↗

SU-G-BRB-17: Dosimetric Evaluation of the Respiratory Interplay Effect During VMAT Delivery Using IPAGAT Polymer Gel Dosimeter

Purpose: To evaluate the dosimetric impact of the interplay effect between multileaf collimator (MLC) movement and tumor respiratory motion during delivery of volumetric modulate arc therapy (VMAT) by using customized polymer gel dosimeter. Methods: Polyacrylamide-based gel dosimeter contained magnesium chloride as a sensitizer (iPAGAT) was used in this study. An excellent gas barrier PAN (BAREX) techno bottle (φ8 cm, 650 mL) filled with iPAGAT was set to the QUASAR™ respiratory motion phantom, and was moved with motion amplitudes of 1 and 2 cm with a 4 second period during VMAT delivery by the Novalis Tx linear accelerator (Varian/BrainLAB). Two spherical tumors with a 2 cm diameter (GTV1 and GTV2) were defined, and ITV1 (GTV1+1 cm) and ITV2 (GTV2+2 cm) with expansion in the superior-inferior (S-I) direction were also defined with simulated respiratory motion. PTV margin was 2 mm around the ITV considering the setup uncertainty. Two single arc VMAT plans with 30 Gy at 3 Gy per fraction (GTV: D98>100%, PTV: D95=100%) were generated by the Varian Eclipse treatment planning system. Three-dimensional dose distribution in iPAGAT was read out by the Signa 1.5T MRI system (GE), and was evaluated by dose-volume histogram (DVH) using in-house developed software. Results: According to DVH analysis by iPAGAT, D98 of GTV1 and GTV2 were more than 100% of the prescribed dose. In contrast, D95 of PTV1 and PTV2 were about 85% and 65%, respectively. Furthermore, low-to-intermediate dose was widespread with motion amplitude of 2 cm. Conclusion: DVH analysis using iPAGAT polymer gel dosimeter was performed in this study. As a result, interplay effect was negligible, since dose coverage of GTV was sufficient during VMAT delivery with simulated respiratory motion. However, the dose reduction of PTV and the spread of low-to-intermediate dose compared to the planned dose require scrupulous attention for large tumor respiratory motion.

60 APPLIED LIFE SCIENCES↗

Ducted Assembly Steady-State Heat Transfer Software (DASSH)

The Ducted Assembly Steady-State Heat transfer software (DASSH) is being developed at Argonne National Laboratory to perform a steady-state thermal fluids calculation to determine the coolant flow and temperature distribution for a hexagonal reactor core configuration with ducted assemblies. DASSH is intended to be used in the early stages of the reactor design process when assembly components can be undefined or are undergoing considerable design changes. DASSH provides a rapid assessment of the temperature and flow distribution to allow quick characterization of the system and identification of problem areas. This document is a guide for DASSH users. It summarizes the core capabilities of DASSH and highlights differences between DASSH and SE2-ANL. Instructions for obtaining and installing DASSH are provided along with some guidelines and recommendations for newer Python users. It covers the structure of the input file, provides directions for running DASSH, describes the various output files produced by the code, and provides instructions for visualizing data. Examples demonstrating various DASSH options are included. DASSH is under active development, so it is anticipated that this guide will grow and evolve as the code is updated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation and Suitability of Using SERI QC Software for Estimating Measurement Uncertainty

SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report (the first of six in the Data Quality and Uncertainty Integration project) reviews and evaluates the software to determine its suitability for determining the estimated expanded measurement uncertainty of solar measurement data by including operational factors. Using redundancy incorporated in three-component (global, direct, diffuse) solar measurements, SERI QC can quantify the standard uncertainty estimates for estimating uncertainty. With minor modifications, SERI QC will provide an operational uncertainty to be used in conjunction with the National Renewable Energy Laboratory method for instrument uncertainty to provide an integrated estimate of solar measurement data sets. These modifications will capitalize on SERI QC's evaluation of data quality, including data input validation and a variety of built-in solar routines, and will further develop the utility of the software.

14 SOLAR ENERGY↗

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

Node-red Software Architecture For Soec System Control

The software workflows that have been developed are open-source and therefore can be accessed and utilized by researchers and students all around the world for free of cost. The software is flexible and easily modifiable to suit the needs for testing bench-scale to system-level setups, and is not limited to just hydrogen generation facilities. The web-interface of the code allows for easy remote access and management, which is especially useful for distributed systems. This is more challenging with traditional PLCs, which often require direct connections or specialized software, making remote troubleshooting more cumbersome. Additionally, since the underlying interface is open-source, with an active community contributing to its development, regular updates, new features, and a wealth of community support and shared solutions will keep improving the overall architecture without excessive fees for upgrades.

Shigrekar, Amey [Idaho National Laboratory (INL), ↗

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

Gap Resolution

Gap Resolution is a software package that was developed to improve Newbler genome assemblies by automating the closure of sequence gaps caused by repetitive regions in the DNA. This is done by performing the follow steps:1) Identify and distribute the data for each gap in sub-projects. 2) Assemble the data associated with each sub-project using a secondary assembler, such as Newbler or PGA. 3) Determine if any gaps are closed after reassembly, and either design fakes (consensus of closed gap) for those that closed or lab experiments for those that require additional data. The software requires as input a genome assembly produce by the Newbler assembler provided by Roche and 454 data containing paired-end reads.

Labutti, Kurt↗