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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Direct Current Arc-Flash Hazards of Solar Photovoltaic Systems

An arc-flash is a rapid release of thermal energy, pressure waves, and electromagnetic interference from a high-power electrical system, caused by such events as unintentional shorting or equipment malfunction. Arc-flashes are hazardous to people and equipment. Incident energy (IE) is a means of quantifying the degree of thermal hazard posed by an arc-flash event. The calculated IE value dictates what level of personal protective equipment (PPE) workers are required to wear when servicing equipment. Overly burdensome PPE may increase a worker’s discomfort and decrease dexterity, which could lead to unintentional shorting, while inadequate PPE also comes with increased safety risks. The majority of arc-flash research to date has focused on alternating current (ac) systems. For example, IE calculations and PPE for ac systems are relatively well understood and have been applied across many equipment types and voltages. IE calculation methodologies in ac systems are backed by a wide range of industry tests and are included in Institute of Electrical and Electronics Engineers (IEEE) and National Fire Protection Association (NFPA) standards. However, very little is known about direct current (dc) arc-flash and its hazards. This is a significant knowledge gap, as an increasing number of dc systems are being deployed: solar photovoltaic (PV) plants, battery storage, and electric vehicles and their charging infrastructure. The dc arc-flash hazard publications are rooted primarily in theory, and their IE calculation methods contradict each other. Insufficient knowledge and data are preventing the formation of industry consensus and standards around dc arc-flash hazard assessment. Here, this white paper highlights the current status and research opportunities for assessing arc-flash hazards in dc systems, with a focus on PV plants. The nonlinear current-voltage characteristics of PV modules make them unique in comparison to other linear dc sources, such as batteries. Also, PV equipment has rapidly evolved from 600 Vdc to 1,500 Vdc (in the United States), increasing potential arc-flash hazards. The operating regime of a PV-array within its I-V characteristic curve during an arc-flash event and the sustainability of arc-flash events in a utility-scale PV plant need to be investigated. Arc-flash experiments on a 1-MWdc nameplate capacity utility-owned ground-mount photovoltaic plant suggest that the PV array acts as a constant-current supply with currents near the short-circuit portion of the I-V characteristic curve of the array, with median arc voltage as 1/3 of the rated voltage. Various engineering software packages (CYME7 by EATON, PTW by SKM, ArcFlash™ by EasyPower, ETAP, and so on) have started offering dc arc-flash calculation features to estimate the risk of arc-flash in dc and PV systems. However, they are reliant on the same simplified arc-flash models, which contradict each other due to differences in assumptions such as characteristics of the power source, arc current, voltage and impedance, arc-operating regime, and so on. Physical arc-flash testing and improved physics-based modeling with correct assumptions representing practical scenarios are two methods to improve understanding and quantify the risks associated with dc arc-flash hazards. The results would inform development of a more accurate calculation procedure for IE and proper PPE levels.

14 SOLAR ENERGY↗
DOE OSTI2025

The Journal of Open Source Software (JOSS): Bringing Open-Source Software Practices to the Scholarly Publishing Community for Authors, Reviewers, Editors, and Publishers

Open-source software (OSS) is a critical component of open science, but contributions to the OSS ecosystem are systematically undervalued in the current academic system. The Journal of Open Source Software (JOSS) contributes to addressing this by providing a venue (that is itself free, diamond open access, and all open-source, built in a layered structure using widely available elements/services of the scholarly publishing ecosystem) for publishing OSS, run in the style of OSS itself. A particularly distinctive element of JOSS is that it uses open peer review in a collaborative, iterative format, unlike most publishers. Additionally, all the components of the process—from the reviews to the papers to the software that is the subject of the papers to the software that the journal runs—are open. We describe JOSS’s history and its peer review process using an editorial bot, and we present statistics gathered from JOSS’s public review history on GitHub showing an increasing number of peer reviewed papers each year. We discuss the new JOSSCast and use it as a data source to understand reasons why interviewed authors decided to publish in JOSS. JOSS’s process differs significantly from traditional journals, which has impeded JOSS’s inclusion in indexing services such as Web of Science. In turn, this discourages researchers within certain academic systems, such as Italy’s, which emphasize the importance of Web of Science and/or Scopus indexing for grant applications and promotions. JOSS is a fully diamond open-access journal with a cost of around US$\$$5 per paper for the 401 papers published in 2023. The scalability of running JOSS with volunteers and financing JOSS with grants and donations is discussed.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A dosimetric evaluation of the Eclipse AAA algorithm and Millennium 120 MLC for cranial intensity-modulated radiosurgery

The aim of this study is to assess the accuracy of a convolution-based algorithm (anisotropic analytical algorithm [AAA]) implemented in the Eclipse planning system for intensity-modulated radiosurgery (IMRS) planning of small cranial targets by using a 5-mm leaf-width multileaf collimator (MLC). Overall, 24 patient-based IMRS plans for cranial lesions of variable size (0.3 to 15.1 cc) were planned (Eclipse, AAA, version 10.0.28) using fixed field-based IMRS produced by a Varian linear accelerator equipped with a 120 MLC (5-mm width on central leaves). Plan accuracy was evaluated according to phantom-based measurements performed with radiochromic film (EBT2, ISP, Wayne, NJ). Film 2D dose distributions were performed with the FilmQA Pro software (version 2011, Ashland, OH) by using the triple-channel dosimetry method. Comparison between computed and measured 2D dose distributions was performed using the gamma method (3%/1 mm). Performance of the MLC was checked by inspection of the DynaLog files created by the linear accelerator during the delivery of each dynamic field. The absolute difference between the calculated and measured isocenter doses for all the IMRS plans was 2.5% ± 2.1%. The gamma evaluation method resulted in high average passing rates of 98.9% ± 1.4% (red channel) and 98.9% ± 1.5% (blue and green channels). DynaLog file analysis revealed a maximum root mean square error of 0.46 mm. According to our results, we conclude that the Eclipse/AAA algorithm provides accurate cranial IMRS dose distributions that may be accurately delivered by a Varian linac equipped with a Millennium 120 MLC.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Using OpenMP for HEP framework algorithm scheduling

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software packages (such as CMSSW, GaudiHive, and ROOT) make use of Intel’s Threading Building Blocks (TBB) library to accomplish the same goal. In these proceedings we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework. This includes both scheduling of different interdependent algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

New approach for calibration the efficiency of HpGe detectors

This work evaluates the efficiency calibrating of HpGe detector coupled with Canberra GC3018 with Genie 2000 software and Ortec GEM25-76-XLB-C with Gamma Vision software; available at Neutron activation analysis laboratory in Malaysian Nuclear Agency (NM). The efficiency calibration curve was constructed from measurement of an IAEA, standard gamma–point sources set composed by {sup 214}Am, {sup 57}Co, {sup 133}Ba, {sup 152}Eu, {sup 137}Cs and {sup 60}Co. The efficiency calibrations were performed for three different geometries: 5, 10 and 15 cm distances from the end cap detector. The polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points. The efficiency equation was established from the known fitted parameters which allow for the efficiency evaluation at particular energy of interest. The study shows that significant deviations in the efficiency, depending on the source-detector distance and photon energy.

42 ENGINEERING↗
DOE OSTI2020

Roadmap on multiscale materials modeling

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-J-227: Breathing Pattern Consistency and Reproducibility: Comparative Analysis for Supine and Prone Body Positioning

Purpose: Evaluate and compare the cycle-to-cycle consistency of breathing patterns and their reproducibility over the course of treatment, for supine and prone positioning. Methods: Respiratory traces from 25 patients were recorded for sequential supine/prone 4DCT scans acquired prior to treatment, and during the course of the treatment (weekly or bi-weekly). For each breathing cycle, the average(AVE), end-of-exhale(EoE) and end-of-inhale( EoI) locations were identified using in-house developed software. In addition, the mean values and variations for the above quantities were computed for each breathing trace. F-tests were used to compare the cycle-to-cycle consistency of all pairs of sequential supine and prone scans. Analysis of variances was also performed using population means for AVE, EoE and EoI to quantify differences between the reproducibility of prone and supine respiration traces over the treatment course. Results: Consistency: Cycle-to-cycle variations are less in prone than supine in the pre-treatment and during-treatment scans for AVE, EoE and EoI points, for the majority of patients (differences significant at p<0.05). The few cases where the respiratory pattern had more variability in prone appeared to be random events. Reproducibility: The reproducibility of breathing patterns (supine and prone) improved as treatment progressed, perhaps due to patients becoming more comfortable with the procedure. However, variability in supine position continued to remain significantly larger than in prone (p<0.05), as indicated by the variance analysis of population means for the pretreatment and subsequent during-treatment scans. Conclusions: Prone positioning stabilizes breathing patterns in most subjects investigated in this study. Importantly, a parallel analysis of the same group of patients revealed a tendency towards increasing motion amplitude of tumor targets in prone position regardless of their size or location; thus, the choice for body positioning during radiation therapy will have to consider the clinical relevance of the two opposing trends - breathing consistency and motion amplitude.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-178: Experimental Study of Acceptable Movement Conditions for SBRT Lung Treatments

Purpose: To experimentally study the acceptable movement conditions for SBRT lung treatments we quantified with film dosimetry the change in dose distributions due to periodic movements of 5 different amplitudes and 4 respiratory gating duty cycles on a SBRT treatment plan. Methods: We planned a SBRT treatment plan for the QUASAR™ (Modus Medical) phantom equipped with the respiratory motion device. We placed a 3 mm water-equivalent sphere simulating a tumour inside the lung-equivalent insert. This sphere is divided in two hemispheres that allow placing films in between. We used radiochromic EBT2™ (Ashland) films. We oriented the lung insert in such a way that sagittal dose distributions could be measured. We applied a sinusoidal movement with 3 s period for 5 different amplitudes of 0(static), 5, 7, 10, 15 and 20 mm without gating. For the 20 mm amplitude we studied the gating technique with 4 duty cycles of 20, 40, 60 and 80% of the respiratory cycle. Each situation was irradiated in a Clinac 2100 linac (Varian) equipped with the RPM™ system. FilmQA Pro™ (Ashland) software together with an Expression 10000XL scanner (EPSON) were used to analyze and compare the measured dose distributions with those planned by the Eclipse™ TPS v. 8.9 (Varian) by means of gamma analysis with 6 criteria: 5%/3mm, 5%/2mm, 5%/1mm, 3%/3mm, 3%/2mm and 2%/2mm (threshold of 10%). Results: Movements with amplitude of less than 7mm do not significantly modified the dosimetry. Gating duty cycles of less than 40% yielded also acceptable results for a 2 cm amplitude movement. Conclusion: To safely perform daily accurate SBRT treatments, movements have to be restricted to 7 mm amplitude (±3.5 mm). Otherwise, a gating strategy should be considered.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A quantification of the effectiveness of EPID dosimetry and software-based plan verification systems in detecting incidents in radiotherapy

Purpose: Complex treatments in radiation therapy require robust verification in order to prevent errors that can adversely affect the patient. For this purpose, the authors estimate the effectiveness of detecting errors with a “defense in depth” system composed of electronic portal imaging device (EPID) based dosimetry and a software-based system composed of rules-based and Bayesian network verifications. Methods: The authors analyzed incidents with a high potential severity score, scored as a 3 or 4 on a 4 point scale, recorded in an in-house voluntary incident reporting system, collected from February 2012 to August 2014. The incidents were categorized into different failure modes. The detectability, defined as the number of incidents that are detectable divided total number of incidents, was calculated for each failure mode. Results: In total, 343 incidents were used in this study. Of the incidents 67% were related to photon external beam therapy (EBRT). The majority of the EBRT incidents were related to patient positioning and only a small number of these could be detected by EPID dosimetry when performed prior to treatment (6%). A large fraction could be detected by in vivo dosimetry performed during the first fraction (74%). Rules-based and Bayesian network verifications were found to be complimentary to EPID dosimetry, able to detect errors related to patient prescriptions and documentation, and errors unrelated to photon EBRT. Combining all of the verification steps together, 91% of all EBRT incidents could be detected. Conclusions: This study shows that the defense in depth system is potentially able to detect a large majority of incidents. The most effective EPID-based dosimetry verification is in vivo measurements during the first fraction and is complemented by rules-based and Bayesian network plan checking.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-61: Treatment Planning Observations for the CivaSheet Directional Brachytherapy Device Using VariSeed 9.0

Purpose: The VariSeed 9.0 brachytherapy TPS is recently available and has new features such as ability to rotate a brachytherapy source away from normal to the imaging plane. Consequently, a dosimetric analysis was performed for a directional brachytherapy source (CivaSheet) with tests of this functionality and experiences from clinical treatment planning were documented. These observations contribute to safe, practical, and accurate use of such new software features. Methods: Several tests were established to evaluate the new rotational feature, specific to the CivaSheet for the first patients treated using this new brachytherapy device. These included suitability of imaging slice-thickness and in-plane resolution, window/level adjustments for brachytherapy source visualization, commissioning the source physical length for performing rotations, and using different planar and 3D window views to identify source orientation. Additional CivaSheet-specific tests were performed to determine the dosimetric influence on target coverage: changing the source tilt angle, source positioning in the treatment plan based on the CivaSheet rectangular array of CivaDots, and influence of prescription depth on the necessary treatment margin for adequate target coverage. Results: Higher imaging-resolution produced better accuracy for source orientation and positioning, with sub-millimeter CT slice-thickness and in-plane resolution preferred. Source rotation was possible only in sagittal or coronal views. The process for validating source orientation required iteratively altering rotations then checking them in the 3D view, which was cumbersome given the absence of quantitative plan documentation to indicate orientation. Given the small Pd-103 source size, influence of source tilt within 30° was negligible for <1.0 cm. Influence of source position was important when the source was positioned in/out of the adjacent source plane, causing changes of 15%, 7%, and 3% at depths of 0.5, 0.7, and 1.0 cm. Conclusion: The new TPS rotational feature worked well, but several issues were identified to improve the treatment planning process. Research supported in part by CivaTech Oncology, Inc. for Dr. Rivard.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Stand Alone Battery Thermal Management System

The objective of this project is research, development and demonstration of innovative thermal management concepts that reduce the cell or battery weight, complexity (component count) and/or cost by at least 20%. The project addresses two issues that are common problems with current state of the art lithium ion battery packs used in vehicles; low power at cold temperatures and reduced battery life when exposed to high temperatures. Typically, battery packs are “oversized” to satisfy the two issues mentioned above. The first phase of the project was spent making a battery pack simulation model using AMEsim software. The battery pack used as a benchmark was from the Fiat 500EV. FCA and NREL provided vehicle data and cell data that allowed an accurate model to be created that matched the electrical and thermal characteristics of the actual battery pack. The second phase involved using the battery model from the first phase and evaluate different thermal management concepts. In the end, a gas injection heat pump system was chosen as the dedicated thermal system to both heat and cool the battery pack. Based on the simulation model. The heat pump system could use 50% less energy to heat the battery pack in -20°C ambient conditions, and by keeping the battery cooler at hot climates, the battery pack size could be reduced by 5% and still meet the warranty requirements. During the final phase, the actual battery pack and heat pump system were installed in a test bench at DENSO to validate the simulation results. Also during this phase, the system was moved to NREL where testing was also done to validate the results. In conclusion, the heat pump system can improve “fuel economy” (for electric vehicle) by 12% average in cold climates. Also, the battery pack size, or capacity, could be reduced 5%, or if pack size is kept constant, the pack life could be increased by two years. Finally, the total battery pack and thermal system cost could be reduced 5% only if the system is integrated with the vehicle cabin air conditioning system. The reason why we were not able to achieve the 20% reduction target is because of the natural decay of the battery cell due to the number of cycles. Perhaps newer battery chemistries that are not so sensitive to cycling would have more potential for reducing the battery size due to thermal issues.

25 ENERGY STORAGE↗
DOE OSTI2016

Predicting Ice Sheet and Climate Evolution at Extreme Scales

A main research objectives of PISCEES is the development of formal methods for quantifying uncertainties in ice sheet modeling. Uncertainties in simulating and projecting mass loss from the polar ice sheets arise primarily from initial conditions, surface and basal boundary conditions, and model parameters. In general terms, two main chains of uncertainty propagation may be identified: 1. inverse propagation of observation and/or prior onto posterior control variable uncertainties; 2. forward propagation of prior or posterior control variable uncertainties onto those of target output quantities of interest (e.g., climate indices or ice sheet mass loss). A related goal is the development of computationally efficient methods for producing initial conditions for an ice sheet that are close to available present-day observations and essentially free of artificial model drift, which is required in order to be useful for model projections (“initialization problem”). To be of maximum value, such optimal initial states should be accompanied by “useful” uncertainty estimates that account for the different sources of uncerainties, as well as the degree to which the optimum state is constrained by available observations. The PISCEES proposal outlined two approaches for quantifying uncertainties. The first targets the full exploration of the uncertainty in model projections with sampling-based methods and a workflow managed by DAKOTA (the main delivery vehicle for software developed under QUEST). This is feasible for low-dimensional problems, e.g., those with a handful of global parameters to be inferred. This approach can benefit from derivative/adjoint information, but it is not necessary, which is why it often referred to as “non-intrusive”. The second approach makes heavy use of derivative information from model adjoints to address quantifying uncertainty in high-dimensions (e.g., basal boundary conditions in ice sheet models). The use of local gradient, or Hessian information (i.e., second derivatives of the cost function), requires additional code development and implementation, and is thus often referred to as an “intrusive” approach. Within PISCEES, MIT has been tasked to develop methods for derivative-based UQ, the ”intrusive” approach discussed above. These methods rely on the availability of first (adjoint) and second (Hessian) derivative code, developed through intrusive methods such as algorithmic differentiation (AD). While representing a significant burden in terms of code development, derivative-baesd UQ is able to cope with very high-dimensional uncertainty spaces. That is, unlike sampling methods (all variations of Monte Carlo), calculational burden is independent of the dimension of the uncertainty space. This is a significant advantage for spatially distributed uncertainty fields, such as threedimensional initial conditions, three-dimensional parameter fields, or two-dimensional surface and basal boundary conditions. Importantly, uncertainty fields for ice sheet models generally fall into this category.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Momentum Users Guide

Momentum is software, written Mark Smith-Nelson, to analyze neutron list-mode data. It contains some features specific to the MC-15 and NPOD neutron multiplicity counters. The MC-15 contains 15 3 He tubes and electronics for recording, in list mode, the time and tube number for each neutron detection. The data depends on many different parameters, including the source material type, source mass and enrichment, alpha ratio, detection efficiency, and multiplication. If some minimum number of these parameters is known, then Momentum can be used to calculate the remaining parameters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Mobile platform for radiological characterization of sites under or after decommissioning - 15139

Nowadays, nuclear industry is facing a crucial need in establishing radiological characterization for the assessment and the monitoring of any remediation work. Regarding its experience in this domain, the French Commission for Atomic Energy and Alternative Energies (CEA) of Fontenay-aux-Roses, established an important feedback and developed a sound methodology for radiological characterization. A clean-up project is managed from the initial surface characterization to the final one, once volumes of contaminated soil have been removed. Samples are collected via recognized methods and data is gathered by real-time acquisition with different conveyance such as all-in-vehicles, cart, walking, helicopter or drone. Accurate radiological analyses are performed on site thanks to the mobile laboratories cluster, called SMaRT. It enables to realize long-time gamma spectroscopy, chemical preparation for alpha spectroscopy or beta liquid scintillation counting. Data is processed with geo-statistics via the software Kartotrak, 2D or 3D mapping are created with the associated uncertainty and probability map. Drilling profiles with geological data (layers composition, particles size, etc.) are studied in order to understand the behavior of the contamination in depth. Source term, contaminated volumes and sanitary impact are calculated in order to determine the optimum excavation depth. Finally, data is stored in an online site that insures the traceability of the whole process. This just-in-time production model allows a fast response and control of costs and avoids the disadvantages of radioactive material transport. This whole innovative process, developed inside the mobile platform, requires all these tools that have been used in France and continuously evolving for more than 10 years thanks to a learning organization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗