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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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DOE OSTI2022

Common Cause Failure Evaluation of High Safety-significant Safety-related Digital Instrumentation and Control Systems

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes a Platform for Risk Assessment of DI&C (PRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of PRADIC on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In PRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that PRADIC can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Common Cause Failure Evaluation of High Safety Significant Safety-related Digital Instrumentation and Control Systems using IRADIC Technology

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes an integrated risk assessment technology for DI&C systems (IRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of the IRADIC technology on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In IRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that the IRADIC technology can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Integrated Multiphysics Modeling of Environmentally Assisted Brittle Fracture

Brittle materials, such as cement, compose major portions of built infrastructure and are vulnerable to degradation and fracture from chemo-mechanical effects. Currently, methods of modeling infrastructure do not account for the presence of a reactive environment, such as water, on the acceleration of failure. Here, we have developed methodologies and models of concrete and cement fracture that account for varying material properties, such as strength, shrinkage, and fracture toughness due to degradation or hydration. The models have been incorporated into peridynamics, non-local continuum mechanics methodology, that can model intersecting and branching brittle fracture that occurs in multicomponent brittle materials, such as concrete. Through development of new peridynamic capabilities, decalcification of cement and differential shrinkage in clay-cement composites have been evaluated, along with exemplar problems in nuclear waste cannisters and wellbores. We have developed methods to simulate multiphase phenomena in cement and cement-composite materials for energy and infrastructure applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Risk to Ecological Resources on Burial Waste Sites on the Hanford Site, Washington - 20248

The US and other nations have a large nuclear and chemical waste remediation task remaining from World War II, the Cold War, and industrial activities. The US Department of Energy (DOE) has the largest task in the U.S., with Hanford (Washington State) being the most contaminated site, with the longest and most costly cleanup program projected to extend to the end of the century. One of the greatest remediation problems at Hanford are the burial waste facilities, some of which are inside the 200 Areas on the Central Plateau, while others are outside the 200 Areas. These areas are associated with waste sites, pipes, and contaminated trenches, posing technical cleanup challenges to meet DoE's remediation goals, including protection of human health and the environment commensurate with Tri- Party Agreement and current regulatory requirements. In this paper we select one of the legacy waste sites (the BC Cribs and Trenches) as a case study to explore how risk to ecological resources varies during and as a consequence of remediation on sites primarily considered legacy waste sites. We used the risk methodology developed by the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) during the Hanford Site-wide Risk Review. The CRESP methodology included evaluating the risk to receptors, including human health, the Columbia River, groundwater, and ecological and cultural resources. The risk evaluation process for ecological receptors included defining the boundaries of each evaluation unit (EU) to be remediated, definition of a suitable buffer area that might be affected, and consideration of the known resource value based on field work. This information, coupled with known remediation options or strategies, allowed us to develop a risk rating for ecological resources. Site risks were evaluated on a scale of 'not discernible' to 'very high' risk. Consideration of the risks at the buried waste sites was complicated by uncertainties in remediation methods and the degree of restoration that would occur as part of the remediation process. We use the BC Cribs and Trenches as a case study to explore why the risks are low currently but increase during remediation. The current 'not discernible to low' risk rating is due to the lack of high quality ecological resources on the BC Cribs and Trenches EU, except for edge areas (with some state-listed species). During remediation the risks increase to 'medium', mainly due to high quality resources on adjacent buffer lands, which could be disrupted during active remediation. Medium and high quality resources on the edge of the site are continuous with higher quality native shrub-steppe habitat on the buffer. Ecological resources on some of the areas surrounding the 200 East and West Areas are some of the highest quality shrub-steppe areas on the Hanford Site, and risk to these resources could be prevented by planning before and during remediation to minimize disruption. For example, lay down areas for the BC Cribs and Trenches can be minimized by careful planning. Heavy truck and other vehicular traffic can be minimized. Spread of the noxious weeds now on some of the site can be prevented, and the spread of invasive species into the site (particularly near undisturbed shrub-steppe habitat) can be reduced. Further, the areas around and between the 200 East and West Areas have been largely undisturbed and can serve as a source of seeds and propagules for any revegetation that occurs as part of the remediation process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Optimizing district energy systems by integrating Borehole Thermal Energy Storage Using a Mixed-Integer Linear Programming g-function framework with a Multi-Timescale Rolling Horizon method

Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution: two borefields comprising 382 boreholes can meet 8.0 % and 6.6 % of the total campus heating and cooling demand, respectively, at an average energy rate of 0.70–0.77 USD/kWh and carbon intensity of 0.54 kg-CO2/kWh. Short-term analysis reveals a 35%–65% decline in BTES energy flow after 3–6 months of continuous heating/cooling operation, while long-term simulation shows that annual energy production of BTES can vary by up to 12.0 % after four years before stabilizing. Overall, this study develops a novel optimization framework that couples physics-based g-function method with MILP optimization framework, thereby advancing methodological development for shallow-geothermal integration and providing actionable guidance for BTES deployment in district-energy systems.

Yang, Jiahui↗
DOE OSTI2020

Structure retrieval in liquid-phase electron scattering

Electron scattering on liquid samples has been enabled recently by the development of ultrathin liquid sheet technologies. The data treatment of liquid-phase electron scattering has been mostly reliant on methodologies developed for gas electron diffraction, in which theoretical inputs and empirical fittings are often needed to account for the atomic form factor and remove the inelastic scattering background. In this work, we present an alternative data treatment method that is able to retrieve the radial distribution of all the charged particle pairs without the need of either theoretical inputs or empirical fittings. Here, the merits of this new method are illustrated through the retrieval of real-space molecular structure from experimental electron scattering patterns of liquid water, carbon tetrachloride, chloroform, and dichloromethane.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

A Stochastic Framework for Estimating Load Profiles at EV Fast Charging Stations

This paper formulates a methodology for estimating the average daily load profiles of EV fast charging stations over a planning horizon of five to ten years. The developed methodology uses historic vehicle registration data, state-level EV adoption targets, seasonal driving patterns, local demographics, competition, and traffic volume information to predict average station usage. Through Monte Carlo simulations, an average daily load profile is obtained for each month in the planning horizon, and prediction uncertainty is quantified. The proposed framework will facilitate the accurate estimation of energy and demand costs incurred by the charging station over the planning period, thereby informing return-on-investment calculations.

Biswas, Shuchismita↗
DOE OSTI2022

Deterministic modelling of the SPERT IV reactor transients using the multi-physics capability of WIMS

The ANSWERS WIMS reactor physics code is being developed for whole core multi-physics modelling. The established neutronics capability for lattice calculations has recently been extended to be suitable for whole core modelling of Small Modular Reactors (SMRs). A whole core transport, SP3 or diffusion flux solution is combined with fuel assembly resonance shielding. An integrated thermal hydraulic solver permits temperature and density variations to feedback to the neutronics calculation. This capability can be applied to both steady state and time dependent transient problems. Nuclear reactor design and safety case development requires assessment of a range of reactor transients, to inform both normal operation limitations and accident scenario analysis. This paper presents new methodology developed in WIMS to couple the core neutronics to the integrated core thermal hydraulics solver for the simulation of reactor transients in whole core models. To support the validation of the multi-physics capability of WIMS, this capability has been applied to the reactivity insertion transient experiments performed in the plate fuelled SPERT-IV reactor. This study employs WIMS using the whole core solver MERLIN, which calculates the time-dependent flux distribution and magnitude, coupled to ARTHUR, which solves for the time-dependent thermal hydraulics solution, and provides thermal feedback via the cross sections generated by GEOM, which performs resonance shielding calculations and generates cross section data for the plate geometry. This spatial kinetics model, with dynamic cross section generation, allows for variations in the temperature and neutron flux profile with time.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

A short account of thermoelectric film characterization techniques

Thermoelectric films and periodic structures have particularly intriguing electrical and thermal transport features due to their low dimensionality. As a result, they have piqued the attention of researchers from across the spectrum of disciplines. Their applications span from cooling fast CPUs to providing energy for wearable devices. The progress in the techniques for synthesizing TE materials and fabricating thin films has facilitated the emergence of a flourishing research domain in the field of electrical and thermal transport at the nanoscale. Further, a significant proportion of contemporary electronic, opto-electronic, and solar energy components are composed of materials featuring numerous interfaces and nanoscale contacts. Consequently, it is imperative to explore the thermal energy transfer and charge carrier transport across the films with thickness dimensions in the nanometer range. The development of cutting-edge approaches for grasping complicated processes at the nanoscale is critical. This review provides a concise overview of the prevalent methodologies developed over the last two decades and employed for the characterization of the Seebeck coefficient and electrical and thermal conductivity of thermoelectric films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Validation and Demonstration of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an integrated energy system (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. The new RAVEN plugin for grid and capacity optimization (HERON) only addresses the limits that affect the production variables and the corresponding rates of variation (explicit constraints). However, other variables are subject to constraints, and the associated limits should be accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response affects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. To obtain a more accurate approximation of the nonlinear dynamic behavior, a parametric version of the dynamic mode decomposition with control (DMDc) algorithm was developed to derive the state-space representation matrices of the IES components at different scheduling parameter. Thanks to this approach, a more accurate approximation of the system response can be obtained, the limits imposed by thermal mechanical implicit constraints can be translated into power dispatch limits, and the feedbacks to HERON power dispatcher can be provided. To assess the developed methodology, a power dispatching test case composed of three power generating and storage units (Balance of Plant, Secondary Energy Source, Thermal Energy Storage) was developed. The power output of each one of the three units was optimized to meet the imposed time-dependent load demand trajectory and to maximize the IES profitability by meeting both the explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. Here, we also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗
DOE OSTI2023

Microstructure development in a cold worked SRF Nb sheet undergoing 700°C-900°C/3h heat treatments.

Bulk Nb for TESLA shaped SRF cavities is a mature technology, with high gradient (>35 MV/m) and high Q cavities (>1010, ~2K) routinely fabricated. Significant advances are in order to push Q?s to 1011 (~2K), and involve modifications to the sub-surface Nb layers by impurity doping (N, O). In order to achieve the lowest surface resistance any trapped flux needs to be expelled for cavities to reach high Q?s. There is clear evidence that cavities fabricated from polycrystalline sheets meeting current specifications require higher temperatures beyond 800oC leads to better flux expulsion, and hence improves Q. Recently, cavities fabricated with a non-traditional Nb sheet with initial cold work due to cold rolling expelled flux better after 800°C/3h heat treatment than cavities fabricated using fine-grain polycrystalline Nb sheets. Here, we analyze the microstructure development in Nb from the vendor supplied cold work non-annealed sheet that was fabricated into an SRF cavity as a function of heat treatment building upon the methodology development to analyze microstructure being developed by the FSU-MSU-UT-Austin- JLAB collaboration. The results indicate correlation between full recrystallization and better flux expulsion.

Balachandran, S.↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2021

Modeling of Thermal Decomposition of TATB-Based Explosive for Safety Analysis

We investigate and model the cook-off behavior of LX-17 to understand the response of explosive systems in abnormal thermal environments. Decomposition has been explored via conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (Thermo-Gravimetric Analysis), and DSC (Differential Scanning Calorimetry) experiments under isothermal and ramped temperature profiles. The data were used to fit reaction rate parameters for proposed schemes in an ALE3D computational model. This model includes chemical reactions, thermo- and hydro-dynamics, and material properties, including thermal expansion, compressibility, and strength. These parameterizations were carried out utilizing a Python evolutionary optimization method on LLNL’s high-performance computing clusters. Additional experiments are being developed to further characterize and monitor decomposition intermediates to improve the model. Once experimentally validated, this model will be scalable to several applications involving LX-17. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials.

Chemistry - Chemical explosives↗
DOE OSTI2021

Multi‐fidelity digital twin structural model for a sub‐scale downwind wind turbine rotor blade

Abstract This paper presents the development of a multi‐fidelity digital twin structural model (virtual model) of an as‐built wind turbine blade. The goal is to develop and demonstrate an approach to produce an accurate and detailed model of the as‐built blade for use in verifying the performance of the operating two‐bladed, downwind rotor. The digital twin model development methodology, presented herein, involves a novel calibration process to integrate a wide range of information including design specifications, manufacturing information, and structural testing data (modal and static) to produce a multi‐fidelity digital twin structural model: a detailed high‐fidelity model (i.e., 3D finite element analysis [FEA]) and consistent beam‐type models for aeroelastic simulation. A key element is that the multi‐fidelity structural digital twin method follows the rotor from the stages of design, to manufacturing, then to the ground testing and field operation. The result of this comprehensive approach is an accurate multi‐fidelity digital twin structural model for the geometric, structural, and structural dynamic properties of the as‐built blade within a 1% match in mass properties, 3.2% in blade frequencies, and 6% in deflection. The different stages of processing this information within the methodology are discussed. The rotor examined is the SUMR‐Demonstrator (SUMR‐D), which was installed on the Controls Advanced Research Testbed (CART‐2) wind turbine at the National Wind Technology Center. The digital twin model developed here was utilized to design controllers to safely operate SUMR‐D in field tests, which are providing additional data for further evaluation and development of the multi‐fidelity digital twin structural model.

Chetan, Mayank↗
DOE OSTI2025

Wafer-Free Crystalline Silicon Solar Cells (CRADA Final Report)

This CRADA project, based on the DOE Solar Energy Technologies Office (SETO) Solar Prize Voucher program, helped Leap Photovoltaics to develop methodologies to immobilize Si particles by permanently attaching them to an Al-coated substrate and thereby forming carrier-selective electrical contacts to the Si particles. The bigger goal was to help Leap Photovoltaics develop these immobilized and contacted particle arrays into relatively efficient, inexpensive, and industrially relevant solar cells. By using Si particles instead of wafers in a solar cell absorber layer, one can avoid costs associated with growing monocrystalline Si ingots, then diamond-sawing them into wafers, then processing wafers into cells – a mainstream practice in today's high-efficiency Si cell and module technology. Monocrystalline or polycrystalline Si particles can be obtained in various ways: for example, Si kerf from wafer sawing is monocrystalline; recycled Si cell wafers can be ball-milled into particles; particles can be grown using various gas-phase techniques (mostly from SiH4). These Si particles can be assembled onto a substrate and serve as an absorber layer for the solar cell, absorbing photons to generate photocarriers. The challenge with this technique is to collect photocarriers from individual Si particles, with separation of photogenerated electrons to the negative cell’s electrode and positive photogenerated holes to the positive electrode. Therefore, each particle must have two isolated, carrier-selective contacts: one for electrons and one for holes. Plus, particles need to be immobilized onto a solid substrate. The goal of this work was focused on the immobilization of Si particles and creating hole-selective contact to them at the same time, using industrially relevant Si photovoltaic (PV) cell technology: screen printing of Al back-surface field electrodes. This is used in the mainstream Propane Education and Research Council (PERC) technology for hole-collecting contacts at the back of the cell. The work performed at NREL consisted of screen printing of Al metal paste on substrates, spreading Si particles onto it, and thermally processing the structures to form hole-collecting contacts. The final structures were investigated by scanning electron microscopy (SEM) after focused ion beam (FIB) cross-sectioning and polishing. The work was done jointly by NREL staff and Leap Photovoltaics (Leap PV) employees stationed at NREL. The samples were then taken to Leap PV for further processing. Training the Leap PV employee on various NREL techniques (laser cutting, screen printing, thermal processing, characterization) was part of the scope.

14 SOLAR ENERGY↗
DOE OSTI2021

FAST-1.0.1 User Installation and Verification Guide

The purpose of this document is to provide the user information about the installation of FAST-1.0.1 on their computers or servers. General information about the code and supported operating systems is described in Section 1.0.1. Self-service oriented FAST-1.0.1 software licensing steps are described in Section 2.0. An installation verification test suite is provided with FAST-1.0.1 and described in Section 3.0. A convenience script for converting FRAPCON to FAST inputs is discussed in Section 4.0. FAST-1.0.1 was developed and released under a software quality assurance program based upon NQA-1-2017. FAST-1.0.1 is the latest baseline code and the result of a bug fixes to FAST-1.0 with other software and methodology developments. The installation verification test suite contains both steady state and transient Anticipated Operation Occurrences (AOOs). Capability to model accident conditions, such as Reactivity Initiated Accidents (RIAs) and Loss Of Coolant Accidents (LOCAs), are targeted for a later release of FAST. FRAPTRAN-2.0 will continue to be used for accident conditions until the release of FAST with accident condition modeling capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗