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All sources NASA NTRS DOE OSTI

DOE OSTI2016

Comparative analysis of numerical models of pipe handling equipment used in offshore drilling applications

Design of offshore drilling equipment is a task that involves not only analysis of strict machine specifications and safety requirements but also consideration of changeable weather conditions and harsh environment. These challenges call for a multidisciplinary approach and make the design process complex. Various modeling software products are currently available to aid design engineers in their effort to test and redesign equipment before it is manufactured. However, given the number of available modeling tools and methods, the choice of the proper modeling methodology becomes not obvious and – in some cases – troublesome. Therefore, we present a comparative analysis of two popular approaches used in modeling and simulation of mechanical systems: multibody and analytical modeling. A gripper arm of the offshore vertical pipe handling machine is selected as a case study for which both models are created. In contrast to some other works, the current paper shows verification of both systems by benchmarking their simulation results against each other. Such criteria as modeling effort and results accuracy are evaluated to assess which modeling strategy is the most suitable given its eventual application.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Fluence Capsules for the SAM-2 Experiment MPO# 00239221/SOW-17494, Rev. 0

The statement of work (SOW) applies to the fabrication and analysis of flux wire capsules that will be used in the SAM-2 experiment. This experiment is a drop-in design slated for irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The 8 neutron fluence capsules will be used to determine the neutron exposure that the specimens have received. For Task 1 Pacific Northwest National Laboratory (PNNL) will prepare eight (8) neutron fluence monitors for irradiation in the ATR. Task 2 will involve analysis port-irradiation; the monitors will be returned to PNNL for analysis in FY21 after irradiation. The analysis report will include the neutron fluences and radiation damage calculations for all irradiated positions in the experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2012

Materials, Turbomachinery and Heat Exchangers for Supercritical CO2 Systems

The objective of this project is to produce the necessary data to evaluate the performance of the supercritical carbon dioxide cycle. The activities include a study of materials compatibility of various alloys at high temperatures, the heat transfer and pressure drop in compact heat exchanger units, and turbomachinery issues, primarily leakage rates through dynamic seals. This experimental work will serve as a test bed for model development and design calculations, and will help define further tests necessary to develop high-efficiency power conversion cycles for use on a variety of reactor designs, including the sodium fast reactor (SFR) and very high-temperature gas reactor (VHTR). The research will be broken into three separate tasks. The first task deals with the analysis of materials related to the high-temperature S-CO 2 Brayton cycle. The most taxing materials issues with regard to the cycle are associated with the high temperatures in the reactor side heat exchanger and in the high-temperature turbine. The system could experience pressures as high as 20MPa and temperatures as high as 650°C. The second task deals with optimization of the heat exchangers required by the S-CO 2 cycle; the S-CO 2 flow passages in these heat exchangers are required whether the cycle is coupled with a VHTR or an SFR. At least three heat exchangers will be required: the pre-cooler before compression, the recuperator, and the heat exchanger that interfaces with the reactor coolant. Each of these heat exchangers is unique and must be optimized separately. The most challenging heat exchanger is likely the pre-cooler, as there is only about a 40°C temperature change but it operates close to the CO{sub 2} critical point, therefore inducing substantial changes in properties. The proposed research will focus on this most challenging component. The third task examines seal leakage through various dynamic seal designs under the conditions expected in the S-CO 2 cycle, including supercritical, choked, and two-phase flow conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

Plasma-Based Ambient Desorption/Ionization Mass Spectrometry for the Analysis of Liquid Crystals Employed in Display Devices

Liquid-crystal displays (LCDs) are the most frequently used display technology worldwide these days. Due to the rather complex manufacturing process and purity requirements for the chemicals used, quality control and display failure analysis are important analytical tasks. Currently, the state-of-the-art techniques (e.g., high-performance liquid chromatography (HPLC), gas chromatography (GC) coupled to mass spectrometry (MS), time-of-flight secondary ion mass spectrometry (TOF-SIMS), or high-resolution microscopy) are costly and time-consuming. Hence, a new pathway to precisely analyze liquid-crystalline materials and LCDs in their native state is reported. A new approach for direct analysis via plasma-based ambient desorption/ionization mass spectrometry (ADI-MS) offers an inexpensive and faster alternative. In this study, direct analysis in real time (DART), the low-temperature plasma (LTP) probe, and flowing atmospheric-pressure afterglow (FAPA) ADI sources coupled to high-resolution mass spectrometry (HR-MS) are compared based on their capabilities and performance for liquid-crystal analysis. These sources enable direct analyte desorption from a sample surface at ambient conditions and ionize the vaporized analyte molecules in a subsequent step. Primarily, the ionization capabilities of the three ADI sources are compared for individual liquid-crystal standards, mixtures of liquid crystals (LCs), and complex liquid crystal/additive mixtures applied in commercially available LCDs. Furthermore, direct surface analysis from a glass substrate is also performed with ADI-MS to compare their applicability to this type of sample matrix. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

PacWave Anchoring and Mooring Study

PacWave, with its location in some of the most energetic waters in the nation and a buildout to support grid-connected devices, is poised to become a leader in field testing of wave energy converters (WECs) at high technology readiness levels. As part of the device deployment and testing protocols at PacWave, the client is responsible for providing all mooring system components, since there are currently no mooring system components specified for PacWave. NREL and PNNL have been tasked with conducting a preliminary analysis of permanent or temporary mooring systems at the PacWave South site. Previous work for this task included a global trade study of mooring systems used for WECs, and a site characterization of PacWave South. This current report will use the results of the previous studies to inform the design of various mooring systems to be installed at PacWave, which will allow cost analyses to be performed to compare the costs of acquisition of these mooring systems and the costs of mooring systems designed specifically for clients' devices.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Calorimeter Pileup Deconvolution for Online Trigger Primitives

In high energy physics experiment, as the luminosity increases, pile-up issues on detectors such as calorimeters become non-negligible. Deconvolution approaches with mathematic pre-assumptions such as Sparse Representation are developed for data analysis stage. For online computation tasks such as for trigger primitive creation, signal availability is significantly different as in offline data analysis stage, and therefore, different (yet simpler) algorithms should be explored. In this document, several approaches of deconvolution suitable for FPGA implementation are discussed.

Wu, Jin-yuan [Fermilab] (ORCID:0000000344329521)↗

DOE OSTI2021

Autonomous Tools for Attack Surface Reduction (Final Report)

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society, and its secure and reliable operation is of paramount importance to national security and economic wellbeing. However, recent findings documented in authoritative sources indicate the threat of cyber-based attacks growing in numbers and sophistication. However, securing the grid against stealthy cyberattacks is a challenging task due to legacy nature of the infrastructure coupled with dynamic nature of threat landscape and ever-growing sophistication of the adversaries. Additionally, the grid’s attack surface continues to grow with the increased dependence on digital communications and control that now extends to each consumer through smart meters and distributed energy resources. Unfortunately, this expansive surface increases the grid’s vulnerability and further exposes critical control systems in both substations and control centers. To respond to this emerging need, we had successfully assembled an interdisciplinary team with academic- industry partnership to successfully conduct research, development, evaluation, demonstration, and commercialization of attack surface reduction tools, whose goal was to significantly reduce the cyber attack surface in the North American power grid. Our proposed project was a synergistic collaborative effort leveraging the synergistic expertise of the team members across power systems, cyber security and CPS security, testbeds, field deployments and demonstration, and successful commercialization. The following are the specific tasks that have been successfully completed two phases (2016-2020). Phase I: Task 1: Developed and implemented a robust Project Management and Data Management Plan, coupled with a well thought out Risk Mitigation Plan. Task 2.1: Developed a comprehensive framework that continually assesses and autonomously reduces the attack surface for the power grid control environment spanning across substations, control center and the SCADA network to significantly reduce the risks of cyber attacks. Task 2.2: Developed attack surface analysis techniques, metrics, and tools that assess the attack surface at multiple levels including the control center, substations, and the SCADA network. Task 2.3: Developed attack surface reduction techniques and tools that dynamically reduce attack surface and hence increase attacker’s cost without interfering in the critical functions of the system. Task 2.4: Prototyped, implemented, and quantitatively evaluated/validated the techniques and tools on a realistic industrial CPS security testbed environment by leveraging the unique resources of the team. Task 3: Developed Commercialization plan to transition the developed tools into power system industry stakeholders for a broader adoption by leveraging the expertise of our industrial members. Phase II: Task 4: Successfully completed field demonstration, verification, and evaluation of the effectiveness of the attack surface analysis and reduction techniques on a realistic utility testbed environment. This also involved the development of realistic scenarios, sound metrics, data sets, evaluation criteria, and documentation. Technology integration & Field demonstration: The project had significantly advanced the state-of-the-art research and practice in improving the cybersecurity of our nation’s power grid infrastructure against cyber threats. In particular, the proposed, designed, and deployed attack surface analysis and reduction algorithms and tools have contributed to significantly reducing the exposure and risk of the devices, substations, and the integrated SCADA/EMS/ DMS grid environment to cyber threat. Strong demonstration and evaluation techniques have verified the feasibility of the developed techniques on realistic cyber-physical testbeds and utility partner's real grid environment, and collaborative research and evaluation of attack surface reduction techniques (for wide-are monitoring and control) within a vendor (GE) EMS platform. The Attack Host Analyzer (AHA) tool that was developed through this project was made available through GitHub.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Feasibility and Safety Assessment for Advanced Reactor Concepts Using Vented Fuel

Recent interest in fast reactor technology has led to renewed analysis of past reactor concepts such as Gas Fast Reactors and Sodium Fast Reactors. In an effort to make these reactors more economic, the fuel is required to stay in the reactor for extended periods of time; the longer the fuel stays within the core, the more fertile material is converted into usable fissile material. However, as burnup of the fuel-rod increases, so does the internal pressure buildup due to gaseous fission products. In order to reach the 30 year lifetime requirements of some reactor designs, the fuel pins must have a vented-type design to allow the buildup of fission products to escape. The present work aims to progress the understanding of the feasibility and safety issues related to gas reactors that incorporate vented fuel. The work was separated into three different work-scopes: 1. Quantitatively determine fission gas release from uranium carbide in a representative helium cooled fast reactor; 2. Model the fission gas behavior, transport, and collection in a Fission Product Vent System; and, 3. Perform a safety analysis of the Fission Product Vent System. Each task relied on results from the previous task, culminating in a limited scope Probabilistic Risk Assessment (PRA) of the Fission Product Vent System. Within each task, many key parameters lack the fidelity needed for comprehensive or accurate analysis. In the process of completing each task, the data or methods that were lacking were identified and compiled in a Gap Analysis included at the end of the report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2012

Quantitative Assessment of Workload and Stressors in Clinical Radiation Oncology

Purpose: Workload level and sources of stressors have been implicated as sources of error in multiple settings. We assessed workload levels and sources of stressors among radiation oncology professionals. Furthermore, we explored the potential association between workload and the frequency of reported radiotherapy incidents by the World Health Organization (WHO). Methods and Materials: Data collection was aimed at various tasks performed by 21 study participants from different radiation oncology professional subgroups (simulation therapists, radiation therapists, physicists, dosimetrists, and physicians). Workload was assessed using National Aeronautics and Space Administration Task-Load Index (NASA TLX). Sources of stressors were quantified using observational methods and segregated using a standard taxonomy. Comparisons between professional subgroups and tasks were made using analysis of variance ANOVA, multivariate ANOVA, and Duncan test. An association between workload levels (NASA TLX) and the frequency of radiotherapy incidents (WHO incidents) was explored (Pearson correlation test). Results: A total of 173 workload assessments were obtained. Overall, simulation therapists had relatively low workloads (NASA TLX range, 30-36), and physicists had relatively high workloads (NASA TLX range, 51-63). NASA TLX scores for physicians, radiation therapists, and dosimetrists ranged from 40-52. There was marked intertask/professional subgroup variation (P<.0001). Mental demand (P<.001), physical demand (P=.001), and effort (P=.006) significantly differed among professional subgroups. Typically, there were 3-5 stressors per cycle of analyzed tasks with the following distribution: interruptions (41.4%), time factors (17%), technical factors (13.6%), teamwork issues (11.6%), patient factors (9.0%), and environmental factors (7.4%). A positive association between workload and frequency of reported radiotherapy incidents by the WHO was found (r = 0.87, P value=.045). Conclusions: Workload level and sources of stressors vary among professional subgroups. Understanding the factors that influence these findings can guide adjustments to the workflow procedures, physical layout, and/or communication protocols to enhance safety. Additional evaluations are needed in order to better understand if these findings are systemic.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

Monadjemi, Shayan [ORNL] (ORCID:0000000293855969)↗

DOE OSTI2024

Role of the likelihood for elastic scattering uncertainty quantification

In the last decade, uncertainty quantification (UQ) for optical model potentials (OMPs) has become a focal point for nuclear reaction theory, and several competing approaches for OMP UQ have recently been developed. Here, we clarify recent efforts to compare frequentist and Bayesian approaches in the context of OMP UQ [G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019)]. We replicate a portion of that OMP UQ study but use independent statistical tools. Specifically, we compare two methods for OMP parameter inference from elastic scattering data: the Levenberg-Marquardt algorithm for χ 2 minimization on one hand and Markov chain Monte Carlo (MCMC) sampling on the other. Separately, we assess the common practice of using a renormalized likelihood (χ 2 /N), N being the number of data points, instead of the canonical weighted-least-squares likelihood (χ 2 ), as a way of accounting for unknown data correlations. Here, we show that for a generic linear model and for a five-parameter OMP analysis, frequentist and uniform-prior Bayesian approaches recover the same optimum and uncertainty estimates—not systematically larger uncertainties for the Bayesian approach, as was concluded in G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019). Further, we show that if an additional, near-degenerate parameter is introduced into the same OMP analysis such that the parameter posterior becomes non-Gaussian, then covariance-based estimates of uncertainty become unreliable. Finally, we show that regardless of optimization approach, if χ 2 /N is used for the likelihood, the resulting parametric uncertainties increase by $\sqrt{N}$, and that this is responsible for the conclusions drawn in the revisited study. Based on our replication results, we find that a fortuitous cancellation of unreported errors and the renormalization factor can lead to improvement in empirical coverages, as was the case in the original comparative study. We emphasize that developing and applying a realistic likelihood function is an essential task in a UQ analysis, and that several recent UQ studies that employed a renormalized likelihood (i.e., including a 1/N factor) may have yielded unrealistically large uncertainties for elastic-scattering observables. If the parameter posterior deviates from multivariate-normal, a sampling-based approach like MCMC has a clear advantage over methods that assume the Laplace approximation holds. We note that empirical coverage can serve as an important internal check for the analyst whose model or data may have additional, unaccounted-for uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Rapid Quadrupole-Time-of-Flight Mass Spectrometry Method Quantifies Oxygen-Rich Lignin Compound in Complex Mixtures

Complex mixture analysis is a costly and time-consuming task facing researchers with foci as varied as food science and fuel analysis. When faced with the task of quantifying oxygen-rich bio-oil molecules in a complex diesel mixture, we asked whether complex mixtures could be qualitatively and quantitatively analyzed on a single mass spectrometer with mid-range resolving power without the use of lengthy separations. To answer this question, we developed and evaluated a quantitation method that eliminated chromatography steps and expanded the use of quadrupole-time-of-flight mass spectrometry from primarily qualitative to quantitative as well. To account for mixture complexity, the method employed an ionization dopant, targeted tandem mass spectrometry, and an internal standard. This combination of three techniques achieved reliable quantitation of oxygen-rich eugenol in diesel from 300 to 2500 ng/mL with sufficient linearity (R{sup 2} = 0.97 ± 0.01) and excellent accuracy (percent error = 0% ± 5). To understand the limitations of the method, it was compared to quantitation attained on a triple quadrupole mass spectrometer, the gold standard for quantitation. The triple quadrupole quantified eugenol from 50 to 2500 ng/mL with stronger linearity (R{sup 2} = 0.996 ± 0.003) than the quadrupole-time-of-flight and comparable accuracy (percent error = 4% ± 5). This demonstrates that a quadrupole-time-of-flight can be used for not only qualitative analysis but also targeted quantitation of oxygen-rich lignin molecules in complex mixtures without extensive sample preparation. The rapid and cost-effective method presented here offers new possibilities for bio-oil research, including: (1) allowing for bio-oil studies that demand repetitive analysis as process parameters are changed and (2) making this research accessible to more laboratories. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Bayesian Adaptive Polynomial Chaos Expansions

Polynomial chaos expansions (PCEs) are widely used for uncertainty quantification (UQ) tasks, particularly in the applied mathematics community. However, PCE has received comparatively less attention in the statistics literature, and fully Bayesian formulations remain rare—especially with implementations in R. Motivated by the success of adaptive Bayesian machine learning models such as BART, BASS and BPPR, we develop a new fully Bayesian adaptive PCE method with an efficient and accessible R implementation: khaos. Our approach includes a novel proposal distribution that enables data-driven interaction selection and supports a modified g-prior tailored to PCE structure. Through simulation studies and real-world UQ applications, we demonstrate that the Bayesian adaptive PCE provides competitive performance for surrogate modeling, global sensitivity analysis and ordinal regression tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Scalability Analysis of Gleipnir: A Memory Tracing and Profiling Tool, on Titan

Application performance is hindered by a variety of factors but most notably driven by the well know CPU-memory speed gap (also known as the memory wall). Understanding application s memory behavior is key if we are trying to optimize performance. Understanding application performance properties is facilitated with various performance profiling tools. The scope of profiling tools varies in complexity, ease of deployment, profiling performance, and the detail of profiled information. Specifically, using profiling tools for performance analysis is a common task when optimizing and understanding scientific applications on complex and large scale systems such as Cray s XK7. This paper describes the performance characteristics of using Gleipnir, a memory tracing tool, on the Titan Cray XK7 system when instrumenting large applications such as the Community Earth System Model. Gleipnir is a memory tracing tool built as a plug-in tool for the Valgrind instrumentation framework. The goal of Gleipnir is to provide fine-grained trace information. The generated traces are a stream of executed memory transactions mapped to internal structures per process, thread, function, and finally the data structure or variable. Our focus was to expose tool performance characteristics when using Gleipnir with a combination of an external tools such as a cache simulator, Gl CSim, to characterize the tool s overall performance. In this paper we describe our experience with deploying Gleipnir on the Titan Cray XK7 system, report on the tool s ease-of-use, and analyze run-time performance characteristics under various workloads. While all performance aspects are important we mainly focus on I/O characteristics analysis due to the emphasis on the tools output which are trace-files. Moreover, the tool is dependent on the run-time system to provide the necessary infrastructure to expose low level system detail; therefore, we also discuss any theoretical benefits that can be achieved if such modules were present.

Janjusic, Tommy↗

DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗

DOE OSTI2011

Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging

Purpose: This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters. Methods: The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d') for tasks ranging in contrast and frequency content, and d' was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine trade-offs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner. Results: The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M {approx} 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of {approx}65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive results--e.g., {approx}0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to {approx}0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 x 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 x 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist. Conclusions: A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

ASC CSSE Level 2 Milestone #6362: Resilient Asynchronous Many Task Programming Model

This report is an outcome of the ASC CSSE Level 2 Milestone 6362: Analysis of Re- silient Asynchronous Many-Task (AMT) Programming Model. It comprises a summary and in-depth analysis of resilience schemes adapted to the AMT programming model. Herein, performance trade-offs of a resilient-AMT prograrnming model are assessed through two ap- proaches: (1) an analytical model realized by discrete event simulations and (2) empirical evaluation of benchmark programs representing regular and irregular workloads of explicit partial differential equation solvers. As part of this effort, an AMT execution simulator and a prototype resilient-AMT programming framework have been developed. The former permits us to hypothesize the performance behavior of a resilient-AMT model, and has undergone a verification and validation (V&V) process. The latter allows empirical evaluation of the perfor- mance of resilience schemes under emulated program failures and enabled the aforementioned V&V process. The outcome indicates that (1) resilience techniques implemented within an AMT framework allow efficient and scalable recovery under frequent failures, that (2) the abstraction of task and data instances in the AMT programming model enables readily us- able Application Program Interfaces (APIs) for resilience, and that (3) this abstraction enables predicting the performance of resilient-AMT applications with a simple simulation infrastruc- ture. This outcome will provide guidance for the design of the AMT programming model and runtime systems, user-level resilience support, and application development for ASC's next generation platforms (NGPs).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Quantitative Analysis Guidance in Safety Software Validation

Quantitative analysis in software development has been a challenging topic over the years in safety software. While qualitative processes for vigorous safety software verification and validation (V and V) have been provided through standard such as IEEE 1012, quantitative analysis for V and V tasks such as correctness, completeness or accuracy evaluation have not been formally defined. In practice, there are quantitative analyses in terms of using software metrics. Many of these software metrics are useful in analyzing the test results. Some of them are used for providing guidance in code evaluation activities e.g. numbers of line of codes not exceeding certain limits, recursive calls are not allowed, etc. However, few can be used for providing quantitative analysis guidance for the V and V tasks such as completeness evaluation. AREVA Federal Services (AFS) has provided services for many nuclear projects in US. Through compliance with IEEE 1012, AFS V and V processes have provided vigorous qualitative processes ensuring quality level of the software products used in the project meeting the required nuclear software level. In addition, quantitative analysis is developed to provide structured validation framework ensuring 'zero defect' in the software products. This paper describes some aspects of the quantitative approaches using a sample safety application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗