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ECP ST Project 2.3.1.06-STPM08-RAJA (Final Report)

Modern high-performance computing architectures are diverse, with hardware designs that feature multicore CPUs and CPUs plus accelerators, such as GPUs or FPGAs. Achieving good application performance often requires using a programming model and managing application data in ways that are best suited to a particular platform. For large codes that are used daily in production, and are under continual development, architecture-specific ports are untenable. Maintainability requires single-source code that is performance portable across a range of architectures and programming model back-ends. This report describes RAJA, Umpire, and CHAI, three software libraries that provide complementary capabilities to enable application portability for high performance computing (HPC) platforms. In particular, these libraries provide software abstractions that insulate application source code from hardware architecture and programming model-specific implementation details. These development of these libraries was motivated by the needs of multiphysics applications in the Weapons Simulation and Computing Program (WSC) at Lawrence Livermore National Laboratory (LLNL). Funding though the Exascale Computing Project (ECP) Software Technology (ST) project 2.3.1.06 RAJA has fostered outreach and collaboration with the ECP application and software technology development communities. In this report, we describe ECP adoption and integration of these tools to this point. The larger goal of the report is to describe to the ECP community what these projects offer, how they are used, and how to approach adoption and integration of them.

97 MATHEMATICS AND COMPUTING↗

Energy Storage Valuation: A Review of Use Cases and Modeling Tools

An enticing prospect that drives adoption of energy storage systems (ESS) is its ability to be used in a diverse set of use cases and the potential to take advantage of multiple unique value streams. The Energy Storage Grand Challenge (ESGC) technology development pathways for storage technologies draw from a set of use cases in the electrical power system, each with their own specific cost and performance needs. In addition to the need for cost and performance improvements for storage technologies, there a need for robust valuation methods to enable effective policy, investment, business models, and resource planning. There are numerous storage valuation tools available to the public, many of which can analyze the value of an ESS project with inputs and characteristics that reflect a specific storage use case. To effectively reach ESS stakeholders that may be interested in learning about valuation models, this report will draw from publicly available tools developed by the Department of Energy (DOE) and frame their functionalities and capabilities within the context of three distinct use case families. This report examines three of the ESGC use case families in depth and provides a methodology in which interested stakeholders can determine which DOE modeling tool is best suited to value ESS for their specific case. The high-level objectives for this report include: (1) Provide specific sub use-cases for each use case family for further characterization; (2) Provide technical parameters and relevant data for three example use cases that could be used in a valuation tool; (3) Identify a list of publicly available DOE tools that can provide energy storage valuation insights for ESS use case stakeholders; (4) Provide information on the capabilities and different options in each modeling tool; (5) Make conclusions on which are best suited for valuing certain functional/performance requirements and which tools might be applicable to other use cases; and (6) Show the methodology that informs a Model Selection Platform (MSP) framework that educates stakeholders on different DOE models and provides a streamlined way to choose the right model that most closely matches their needs.

25 ENERGY STORAGE↗

Recommendations for Distributed Energy Resource Patching

While computer systems, software applications, and operational technology (OT)/Industrial Control System (ICS) devices are regularly updated through automated and manual processes, there are several unique challenges associated with distributed energy resource (DER) patching. Millions of DER devices from dozens of vendors have been deployed in home, corporate, and utility network environments that may or may not be internet-connected. These devices make up a growing portion of the electric power critical infrastructure system and are expected to operate for decades. During that operational period, it is anticipated that critical and noncritical firmware patches will be regularly created to improve DER functional capabilities or repair security deficiencies in the equipment. The SunSpec/Sandia DER Cybersecurity Workgroup created a Patching Subgroup to investigate appropriate recommendations for the DER patching, holding fortnightly meetings for more than nine months. The group focused on DER equipment, but the observations and recommendations contained in this report also apply to DERMS tools and other OT equipment used in the end-to-end DER communication environment. The group found there were many standards and guides that discuss firmware lifecycles, patch and asset management, and code-signing implementations, but did not singularly cover the needs of the DER industry. This report collates best practices from these standards organizations and establishes a set of best practices that may be used as a basis for future national or international patching guides or standards.

97 MATHEMATICS AND COMPUTING↗

Development of cell-based assay for predictively evaluating the FcγR-mediated human immune cell activation by therapeutic monoclonal antibodies

Therapeutic monoclonal antibodies (mAbs) have important roles in treatments for various cancers and inflammatory diseases. Their highly target specificities provide controlled safety profiles. However, therapeutic mAbs commonly pose a risk of the induction of the release of cytokines, which may result in adverse events including infusion reaction and cytokine release syndrome. Several mechanisms are involved in the cytokine releases induced by therapeutic mAbs, and the activation of immune effector cells via Fcγ receptors (FcγRs) is one of the putative mechanisms for most IgG-subclass mAbs. The relationship between cytokine releases and mAbs' Fc functions is not fully understood. Here we developed a simple reporter cell-based assay for estimating the FcγR-mediated activation of human immune effector cells by mAbs. Our use of the cell-based assay to compare Fc-engineered mAbs with different FcγR-activation profiles revealed that the releases of inflammatory cytokines and chemokines from human peripheral blood mononuclear cells (hPBMCs) induced by the mAbs were elevated by treatment with Fc-engineered mAbs with higher FcγR-activation properties. Our results also suggested the involvement of monocytic effector cells in the activation of hPBMCs as sources of released cytokines and chemokines, which may lead to the immune cell-mediated adverse events. Our new reporter cell assay is a promising tool for evaluating and predicting the activation of human immune cells by novel Fc-engineered mAbs. - Highlights: • A simple reporter assay for estimating the FcγR activation by mAbs is developed. • mAbs with higher FcγR-activation properties strongly activate hPBMC. • Monocytic effector cells are involved in the activation of hPBMCs by mAbs. • The reporter assay is useful for predicting the FcγR-mediated responses of hPBMCs.

60 APPLIED LIFE SCIENCES↗

ALSSAT Version 6.0

Advanced Life Support Sizing Analysis Tool (ALSSAT) at the time of this reporting has been updated to version 6.0. A previous version was described in Tool for Sizing Analysis of the Advanced Life Support System (MSC- 23506), NASA Tech Briefs, Vol. 29, No. 12 (December 2005), page 43. To recapitulate: ALSSAT is a computer program for sizing and analyzing designs of environmental-control and life-support systems for spacecraft and surface habitats to be involved in exploration of Mars and the Moon. Of particular interest for analysis by ALSSAT are conceptual designs of advanced life-support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water and process human wastes to reduce the need of resource resupply. ALSSAT is a means of investigating combinations of such subsystems technologies featuring various alternative conceptual designs and thereby assisting in determining which combination is most cost-effective. ALSSAT version 6.0 has been improved over previous versions in several respects, including the following additions: an interface for reading sizing data from an ALS database, computational models of a redundant regenerative CO2 and Moisture Removal Amine Swing Beds (CAMRAS) for CO2 removal, upgrade of the Temperature & Humidity Control's Common Cabin Air Assembly to a detailed sizing model, and upgrade of the Food-management subsystem.

Yeh, Hue-Hsia↗

Automated qualification data tool for high temperature metallic materials

This report describes a framework for storing, processing, and displaying qualification data for high temperature mechanical properties. The framework automates the process of generating design data from mechanical test results, for example for a data qualification report for the ASME Boiler \& Pressure Vessel Code. The framework has three parts: a data storage model with common formats for several types of typical mechanical property tests, a backend based on the \pycreep Python library for correlating and extrapolating the data to generate design material properties and allowable stresses, and a demonstration user interface for displaying, sorting, and filtering the data and exploring different options for modeling the design mechanical properties. The report discusses the options available for data processing, with illustrations from real test data on Alloy 617, Alloy 709, Alloy 740H, and Laser-Powder Bed Fusion 316H. The framework is complete for ASME type data analysis and will be used to store test data generated by the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies sponsored qualification programs. Future work could extend the tool to other types of material properties and/or expand the demo user interface to make it accessible across the AMMT program.

36 MATERIALS SCIENCE↗

Comparing Eyewitness-Derived Trajectories of Bright Meteors to Instrumentally-Observed Data

The NASA Meteoroid Environment Office (MEO) is often called upon to analyze meteors of public interest observed over the United States. Data from meteor networks are often utilized to accomplish this, as are recordings from the general public. When these methods fail, eyewitness reports are the only resource which can be leveraged. The MEO developed a tool to crudely calculate the trajectories of bright meteors from the eyewitness reports submitted to the American Meteor Society. The tool was tested on eyewitness data for 33 cases and compared to observed data from the NASA All Sky Fireball Network. The tool performed better for cases with more than 75 eyewitness reports than those with fewer than 75, by almost a factor of two across all metrics except for the end height. For these cases, the eyewitness-derived trajectory was about 50 km from the observed trajectory, the radiant was within 15deg, and the speed was within 20% of that observed on average. A description of the tool, example case studies, and general trends are described.

D E Moser↗

Development of a CRISPR/Cas9 system for high efficiency multiplexed gene deletion in Rhodosporidium toruloides

The oleaginous yeast Rhodosporidium toruloides is considered a promising candidate for production of chemicals and biofuels thanks to its ability to grow on lignocellulosic biomass, and its high production of lipids and carotenoids. However, efforts to engineer this organism are hindered by a lack of suitable genetic tools. In this paper, we report the development of a CRISPR/Cas9 system for genome editing in R. toruloides based on a fusion 5S rRNA–tRNA promoter for guide RNA (gRNA) expression, capable of greater than 95% gene knockout for various genetic targets. Additionally, multiplexed double-gene knockout mutants were obtained using this method with an efficiency of 78%. Finally, this tool can be used to accelerate future metabolic engineering work in this yeast.

09 BIOMASS FUELS↗

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗

Towards Acceptance Testing at the Exascale Frontier

At the 2007 Cray User Group meeting, the Oak Ridge Leadership Computing Facility (OLCF) introduced the OLCF Test Harness (OTH), a framework[1] used for acceptance testing of the Jaguar supercomputer[2]. Since then, the OTH framework has evolved to version 2.0 which adds new features and streamlines usability. The OTH is the key piece of software used to orchestrate acceptance testing for all OLCF computational resources before they are deployed for production use, including our leadership class high performance computing (HPC) systems. The OTH framework is written in Python and is publicly available[3].In this paper, we first describe the requirements, design, and structure of the OTH. Then, we present specific improvements developed to support acceptance testing of the OLCF’s Summit system[4]. We will also showcase new OTH features that have been added to streamline the acceptance test process as well as the motivation behind those changes. As part of this work, we also evaluated different workflow tools in order to determine whether these tools could complement the OTH in two key areas: automation and reporting. The advantages and disadvantages identified with each tool will be discussed. Lastly, we summarize the challenges and lessons learned collected from using the OTH for the acceptance of the last three flagship systems at the OLCF. These may be useful for other HPC centers developing their own testing frameworks or those interested in using the OTH.

Melesse Vergara, Veronica↗

Software Tools to Support the Assessment of System Health

This presentation provides an overview of three software tools that were developed by the NASA Glenn Research Center to support the assessment of system health: the Propulsion Diagnostic Method Evaluation Strategy (ProDIMES), the Systematic Sensor Selection Strategy (S4), and the Extended Testability Analysis (ETA) tool. Originally developed to support specific NASA projects in aeronautics and space, these software tools are currently available to U.S. citizens through the NASA Glenn Software Catalog. The ProDiMES software tool was developed to support a uniform comparison of propulsion gas path diagnostic methods. Methods published in the open literature are typically applied to dissimilar platforms with different levels of complexity. They often address different diagnostic problems and use inconsistent metrics for evaluating performance. As a result, it is difficult to perform a one ]to ]one comparison of the various diagnostic methods. ProDIMES solves this problem by serving as a theme problem to aid in propulsion gas path diagnostic technology development and evaluation. The overall goal is to provide a tool that will serve as an industry standard, and will truly facilitate the development and evaluation of significant Engine Health Management (EHM) capabilities. ProDiMES has been developed under a collaborative project of The Technical Cooperation Program (TTCP) based on feedback provided by individuals within the aircraft engine health management community. The S4 software tool provides a framework that supports the optimal selection of sensors for health management assessments. S4 is structured to accommodate user ]defined applications, diagnostic systems, search techniques, and system requirements/constraints. One or more sensor suites that maximize this performance while meeting other user ]defined system requirements that are presumed to exist. S4 provides a systematic approach for evaluating combinations of sensors to determine the set or sets of sensors that optimally meet the performance goals and the constraints. It identifies optimal sensor suite solutions by utilizing a merit (i.e., cost) function with one of several available optimization approaches. As part of its analysis, S4 can expose fault conditions that are difficult to diagnose due to an incomplete diagnostic philosophy and/or a lack of sensors. S4 was originally developed and applied to liquid rocket engines. It was subsequently used to study the optimized selection of sensors for a simulation ]based aircraft engine diagnostic system. The ETA Tool is a software ]based analysis tool that augments the testability analysis and reporting capabilities of a commercial ]off ]the ]shelf (COTS) package. An initial diagnostic assessment is performed by the COTS software using a user ]developed, qualitative, directed ]graph model of the system being analyzed. The ETA Tool accesses system design information captured within the model and the associated testability analysis output to create a series of six reports for various system engineering needs. These reports are highlighted in the presentation. The ETA Tool was developed by NASA to support the verification of fault management requirements early in the Launch Vehicle process. Due to their early development during the design process, the TEAMS ]based diagnostic model and the ETA Tool were able to positively influence the system design by highlighting gaps in failure detection, fault isolation, and failure recovery.

Melcher, Kevin J.↗

Ceramic Capacitor Grain Size Analysis Using Electron Backscatter Diffraction (EBSD)

The overall scope of this NESC study was to identify (or develop) a tool, methodology, or process that can inspect a ceramic capacitor and consistently return repeatable grain size distribution results. It is important to note that the development of a machine learning technique was considered as an option for this study, but only if an existing automated tool was not available. This report explains why the Electron Backscatter Diffraction analysis method for grain structure and size distribution was deemed a suitable candidate for this work.

Electron Backscatter Diffraction↗

Process Cost Modeling for Multi-Disciplinary Design Optimization

For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This report outlines the development of a process-based cost model in which the physical elements of the vehicle are costed according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this report is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool. In successive sections, the report addresses the issues of cost modeling as follows. First, an introduction is presented to provide the background for the research work. Next, a quick review of cost estimation techniques is made with the intention to highlight their inappropriateness for what is really needed at the conceptual phase of the design process. The First-Order Process Velocity Cost Model (FOPV) is discussed at length in the next section. This is followed by an application of the FOPV cost model to a generic wing. For designs that have no precedence as far as acquisition costs are concerned, cost data derived from the FOPV cost model may not be accurate enough because of new requirements for shape complexity, material, equipment and precision/tolerance. The concept of Cost Modulus is introduced at this point to compensate for these new burdens on the basic processes. This is treated in section 5. The cost of a design must be conveniently linked to its CAD representation. The interfacing of CAD models and spreadsheets containing the cost equations is the subject of the next section, section 6. The last section of the report is a summary of the progress made so far, and the anticipated research work to be achieved in the future.

Bao, Han P.↗

Commercial PV Property Appraiser Survey: Summary of Results

Solar photovoltaic systems can be a valuable asset when attached to a property. Therefore, providing market participants with information and tools to credibly assess the value that PV adds to property is important. To that end, LBNL, SNL and AI conducted a survey of commercial appraisers to assess methods of valuing commercial properties with existing PV systems, current trends, and factors that help or hurt market adoption. The survey elicited 44 responses. Although an overwhelming majority of the respondents had conducted appraisals of properties with solar, how such systems are valued varied widely. Less than half of the respondents reported utilizing AI-endorsed tools such as PV Value ® or Ei Value ® for assignments, which may indicate a lack of awareness that such tools exist. A number of appraisers have taken the AI Residential & Commercial Valuation of Solar course and/or pursued a number of self-study avenues to increase their knowledge of PV systems. A majority indicated that they would be interested in taking an online course if it was offered. Overall, preliminary results point to a need for standardization of valuation metrics and a method of disseminating (e.g. classes) and utilizing (e.g. assessment tools) such metrics in order for appraisers to consistently evaluate and increase demand of properties with PV systems.

14 SOLAR ENERGY↗

TEAMS Model Analyzer

The TEAMS model analyzer is a supporting tool developed to work with models created with TEAMS (Testability, Engineering, and Maintenance System), which was developed by QSI. In an effort to reduce the time spent in the manual process that each TEAMS modeler must perform in the preparation of reporting for model reviews, a new tool has been developed as an aid to models developed in TEAMS. The software allows for the viewing, reporting, and checking of TEAMS models that are checked into the TEAMS model database. The software allows the user to selectively model in a hierarchical tree outline view that displays the components, failure modes, and ports. The reporting features allow the user to quickly gather statistics about the model, and generate an input/output report pertaining to all of the components. Rules can be automatically validated against the model, with a report generated containing resulting inconsistencies. In addition to reducing manual effort, this software also provides an automated process framework for the Verification and Validation (V&V) effort that will follow development of these models. The aid of such an automated tool would have a significant impact on the V&V process.

Tijidjian, Raffi P.↗

Tools for Design and Scale-Up of Solar Thermochemical Reactors: Cooperative Research and Development Final Report, CRADA Number CRD-13-00530

NREL will be collaborating with the Participant on a United States - Australia Solar Energy Collaboration (USASEC) Project Number 1-USO034 "Tools for design and scale-up of solar thermochemical reactors." The grant funds for the Participant's 3.5 year project number 1-US034 commencing on 1 February 2013 have been awarded to the Participant by the Australian Renewable Energy Agency and NREL will be collaborating with the Participant during the final 28 months of this project. This project seeks to provide basic knowledge required to design solar thermochemical reactors able to perform the required energy conversions. In several proposed and demonstrated reactors, concentrated sunlight directly irradiates small solid particles suspended in fluid, enabling very high heat transfer rates to the particles which are the sites of chemical reaction. The reactors, therefore, involve the complex and couple dynamics of turbulent, chemically reacting, particle-laden flows and their interaction with concentrating solar radiation. A strong understanding of these coupled interactions will be crucial important in predicting and optimizing the performance of prototype reactors, but this understanding does not yet exist, since they have never been studied in any fundamental way. The project has a assembled an internationally leading team from The University of New South Wales (UNSW) and the University of Adelaide in Australia and the NREL in the United States to address this key gap in available know-how. The project will use U.S. Dept. of Energy (DOE) supercomputers, among the most powerful available worldwide, with cutting-edge software tools to perform first-principles simulations of the relevant interactions. These studies will be combined with detailed laser-based measurements in Australia to provide the first comprehensive databases concerning the governing phenomena in directly irradiated solar-thermochemical reactors. The outcomes will be the basic scientific knowledge, engineering knowhow and modeling tools necessary to design new reactor concepts and then scale up from the laboratory bench to practical size systems.

14 SOLAR ENERGY↗