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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design Methods, Tools, and Data for Ceramic Solar Receivers

This report presents the development of tools and methods for evaluating the reliability and performance of ceramic materials in high temperature solar receivers. As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat requirements, current high temperature metallic materials face challenges in maintaining structural integrity. This report explores advanced ceramics as a promising alternative, given their superior high temperature strength and lower thermal expansion, compared to metals. To address the need for effective ceramic receiver design tools, this report integrates statistical failure models of ceramics into the existing srlife tool: an open-source software package designed to estimate the life of high temperature CSP components. These failure models account for the inherent variability and flaw distribution in ceramics, as well as the impact of subcritical crack growth under high temperature cyclic loads. The report also presents experimental data collected for a commercially available ceramic material, SiC, and details the process of estimating reliability model parameters from these data. A comparative design analysis is then performed between ceramic (SiC) and metallic (current nickel-based superalloys A740H and A282) receiver. This comparison demonstrates that SiC receivers can achieve service life exceeding 30 years under high incident heat flux conditions, compared to just a few years for metallic receivers.

14 SOLAR ENERGY↗
DOE OSTI2022

LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)

The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.

14 SOLAR ENERGY↗
DOE OSTI2026

Hardware Aware Mitigation of Timing Side-Channel Vulnerabilities in Critical Infrastructure Software

Program runtime/timing attacks exploit variations in a program’s execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime sidechannel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware/device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. We propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C/C++/Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzAR in terms of execution time overhead (up to −46%), code size overhead (up to −10%), and correctness (no failures) on five different embedded/edge devices.

Suha, Tasneem [University of Maine]↗
DOE OSTI2020

HOSS: Hybrid Optimization Software Suite

HOSS software, developed at LANL, is a powerful, flexible, and parallelized package that enables the user to predict deformation and failure of materials in a variety of situations. LANL’s HOSS software is an R&D 100 finalist that integrates solid mechanics and computational fluid dynamics into a multi-physics platform able to handle millions of interacting and fracturing solids and/or particle systems. This nextgeneration simulation software integrates solid mechanics and computational fluid dynamics into a multi-physics platform able to provide state-of-the-art simulation solutions for a wide field of applications including oil and gas, construction, mining, defense, material sciences, and biomechanics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New Physics in the Hot Electron Furnace (Final Report)

The primary purpose of this award was experiments and simulations related to the idea of a ‘Hot Electron Furnace’ where nonlocal heat transport would allow unique new experimental opportunities at x-ray free electron lasers. The period of this award included beamtime at the MEC endstation of the LCLS, and the execution of those experiments was a primary goal. Unfortunately, the beamtime had limited success due to (1) inability of the LCLS to deliver the expected two-color operations mode, and (2) failure of the MEC endstation’s own software to save the cavity timing data that would have allowed inference of time delays for the few hours when two-color mode briefly operated. The beamtime was then switched to operate in single-color (one pulse) mode, and studies were performed of x-ray heating and probe, simultaneously. Two interesting manuscripts are finally near submission, having been delayed by student graduations, need for collaborator simulations of x-ray heating processes, and then COVID. I am hopeful that they will soon be submitted (especially the paper on x-ray heating of MgO) because one of the principal students involved has returned from industry to take a postdoc position at SLAC. Below, we first list all publications and other work products (including the two that are nearing submission) and then summarize several outcomes from this effort. During the term of this award three UW physics graduate students were at least partially supported, and all three received their Ph.D.’s with significant components of their supported work in the dissertation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

DIVA/DeviceEditor v6.1.2

DIVA is an end-to-end DNA design and construction management platform that streamlines how researchers design, build, and receive sequence-verified DNA constructs. Through a web-based BioCAD interface (DeviceEditor), researchers independently design DNA constructs and submit them to a centralized queue with a single action. Designs progress transparently through standardized states which allow researchers to track status and access finished constructs via a central DNA repository. Submitted designs are reviewed by dedicated staff for feasibility and optimization, reducing costly failures and improving downstream execution. Automated DNA assembly software optimizes construction strategies by reusing existing parts where possible and sourcing synthetic DNA only when needed. Standardized, sequence-agnostic assembly methods enable many independent constructs to be built in parallel using lab automation, dramatically increasing throughput. High-throughput next-generation sequencing is used to verify construct accuracy, with flexible platforms selected based on task requirements. Throughout the process, detailed success and failure data are captured and analyzed, enabling continuous improvement of assembly protocols. Compared to traditional, manual DNA construction workflows, DIVA offers higher scalability, transparency, reproducibility, and data-driven optimization.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2025

Pyomo: Accidentally outrunning the bear

Pyomo is an open-source optimization modeling software that has undergone significant evolution since its inception in 2008. Pyomo has evolved to enhance flexibility, solver integration, and community engagement. Modern collaborative tools for open-source software have facilitated the development of new Pyomo functionality and improved our development process through automated testing and performance-tracking pipelines. However, Pyomo faces challenges typical of research software, including resource limitations and knowledge retention. The Pyomo team’s commitment to better development practices and community engagement reflects a proactive approach to these issues. We describe Pyomo’s development journey, highlighting both successes and failures, in the hopes that other open-source research software packages may benefit from our experiences.

automation↗
DOE OSTI2026

DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities

Program runtime/timing attacks exploit variations in a program’s execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware/device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. Here, we propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C/C++/Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzaR in terms of execution time overhead, code size overhead, and correctness on five different embedded/edge devices.

Timing/runtime side-channel↗
DOE OSTI2026

Evaluation of Hardware and Software Bill of Materials (HBOMs/SBOMs) Extraction Methods

Hardware and software bills of materials (HBOMs and SBOMs) provide important visibility into the components, dependencies, and supply chain relationships within programmable digital devices. This visibility is critical for advanced nuclear reactor applications, where use of common or shared hardware components, software libraries, suppliers, or manufacturing processes may create common cause failure (CCF) vulnerabilities despite apparent diversity. This paper evaluates current approaches for obtaining and analyzing HBOMs and SBOMs in support of CCF, diversity and defense-in-depth (D3) assessments, and begins to explore potential methods for artificial intelligence/machine learning-based analysis. The availability of BOM information from advanced reactor manufacturers and vendors, representative hardware and software categories found in advanced reactor systems continues to limit research [13]. This paper compares commonly used BOM formats, including CycloneDX, SPDX, and SWID. It also surveys publicly available tools for generating BOMs from source code, compiled binaries, and hardware-related information, noting limitations in language coverage, system age, and format interoperability. Finally, this paper evaluates methods for correlating BOM data with vulnerability and exploitability information, including VEX, CVE, and CWE resources. The findings indicate that publicly available nuclear-vendor BOMs are limited, making third-party extraction and research into novel analysis techniques necessary.

Cybersecurity↗
DOE OSTI2023

Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP-SAIL)

The Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP) project was conducted to help improve the understanding of precipitation formation in orographically influenced terrain. Special focus is put on the two processes of riming and secondary ice production and their external drivers. Two instruments, a polarimetric W-band simultaneous transmission simultaneous reception (STSR) Doppler cloud radar manufactured by Radiometer Physics GmbH (RPG, instrument type RPG-FMCW-94-DP), from now on named LIMRAD94, and the video in situ snowfall sensor (VISSS), were deployed at the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) site in Gothic, Colorado between November 2022 and June 2023 during the second SAIL winter. Note that the exact dates of data availability differ between the instruments. Both instruments arrived at Gothic on November 2, 2022, 09:20 local time. VISSS, described by Maahn et al., is equipped with two camera systems with telecentric lenses. The two cameras are at a 90° angle to each other. This configuration allows for size-independent measurements by capturing images of hydrometeors from two sides at a high frame rate of 250 Hz. With a minimum detection size of 200 μm, VISSS provides valuable insights into particle size, number, shape, complexity, and fall velocity. The VISSS was deployed on the grassland next to the ARM facility with the amazing help of the ARM employees on site. The setup started on November 2, 2022, and was finished on November 5, 2022, without major problems. VISSS measurements were started on November 6, 2022. LIMRAD94 was installed on a scaffolding platform near Orehouse (Gothic) on November 9, 2022, with the great help of RMBL staff. LIMRAD94 was mounted on a cold temperature scanner prototype. After a short test of the setup on November 9, 2022, the digital control of the scanner elevation stopped working for (at that time) unknown reasons. All attempts to resolve the problem failed. This malfunction made it impossible to operate LIMRAD94 in scanning mode. The scanner was then manually moved to zenith pointing mode and between November 10 and November 15, 2022, vertical observations for polarimetric calibration were performed. On November 15, 2022, after the polarimetric calibration was applied, the scanner was manually moved to 40° elevation with azimuthal view towards the Ka-band ARM Zenith Radar (KAZR) and measurements were continued at constant elevation. Investigation of the scanner malfunction on February 6, 2023, by Benn Schmatz revealed a disengagement between the cogwheel of the elevation motor and the cogwheel moving the scanner in elevation. This mechanical issue was temporarily solved by re-engaging the cogwheels. This made the scanner operational again for about four weeks, until mechanical force disengaged the cogwheels again on March 15, 2023. This repeated scanner failure remained undetected for about three weeks until April 8, 2023; during this time the scanner was stuck at 72° elevation. However, the radar software continued to produce data files falsely indicating that the scanner was still operational. After the scanner failure was noticed, scanning was stopped again, and we returned to constant elevation measurements. On May 15, 2023, the cogwheels of the elevation motor were secured with additional screws sent by the manufacturer. At some point in May, the cogwheels of the azimuth motor were also disengaged by mechanical force, which still allowed for range height indicator (RHI) but no plan position indicator (PPI) scans in the last weeks of the campaign. The azimuth motor was repaired in Germany after the end of the campaign. Throughout the campaign, RMBL and ARM staff kept the radar and the VISSS free of snow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Holistic Measurement Driven Resilience: Combining Operational Fault and Failure Measurements and Fault Injection for Quantifying Fault Detection, Propagation and Impact. Final report

For HPC systems to date, application resilience to faults and failures has been accomplished by the brute- force method of checkpoint/restart, which allows an application to make forward progress in the face of system and application faults, errors, and failures independent of root cause or end result. It has remained the primary resilience mechanism because we lack a way to identify faults and anticipate consequences early enough to take meaningful mitigating action. However, checkpoint/restart implementations put a tremendous burden on system resources and on the applications themselves and is becoming less feasible at scale. Because we have not yet operated at scales at which checkpoint/restart fails to provide forward progress, despite increasing costs, vendors have had little motivation to provide the instrumentation necessary for early identification of faults and failures. However, as we move from petascale to exascale, component mean time to failure (MTTF) will render the existing techniques ineffectual and/or too expensive. Furthermore, fault recovery mechanisms such as failover and/or error correction introduce performance inconsistency. Instrumentation allowing early indication of problems and tools to enable use of such information by systems, operating systems, and applications offer an alternative, more scalable and less costly solution. In the HMDR project, we built on our experience and expertise developed and accumulated over years of research on design, monitoring, measurement, and assessment of resilient computing systems. Analysis of field data on the current and past generations of extreme-scale systems revealed several challenges that, if not addressed in increasingly larger and more complex systems, may hinder the effectiveness of future exascale computing systems. Specifically, i) file systems and interconnects in current-generation large-scale systems already operate at the margins of resiliency, including consistent performance, and may not scale to larger deployments; ii) automated, software-based failover mechanisms are frequently inadequate and can introduce wider failures, such that failures during recovery may lead to system/application failures, including system-wide outages; and iii) silent data corruption represents a critical fault mode and will require efficient detection mechanisms if next-generation applications are to take full advantage of exascale hardware. To address the above challenges, we assembled a team of world-renowned experts in resilient extreme- scale computing from the University of Illinois (Electrical and Computer Engineering, Computer Science, and NCSA), SNL, LANL, NERSC, and Cray. Our team includes representatives from centers that house many of the largest HPC resources in the world, both today and over the coming years. The team has a unique track record of research in i) system and application failure characterization based on the analysis of field data, ii) data-driven design of fault/error detection mechanisms, and iii) experimental characterization of system/application resiliency. The team includes system owners/operators who provide continuous data collection and access and ensure installation of appropriate analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗
DOE OSTI2022

The False Dilemma: Rethinking AF Science and Technology Officer Talent Management

In 2019, Secretary of the Air Force (SECAF) Heather Wilson launched the 2030 Science and Technology (S&T) Strategy by stating, “The advantage will go to those who create the best technologies and who integrate and field them in creative operational ways that provide military advantages.” In 2021, 15% of Air Force general officers responsible for creating and integrating this technological edge had a science, technology, engineering, and math (STEM) graduate degree, and less than 1% of generals had a STEM doctorate. As one point of comparison, at least 32% and 13% of founding CEOs of Fortune 500 technology companies had a master’s and doctoral STEM degree, respectively. The gulf is larger when you consider that these CEOs used their technical degrees throughout their careers whereas most general officers do not. In large organizations, if the leader does not possess technical knowledge, it is difficult to drive innovation systems and connect ideas to reality. The evidence for this disconnect is abundant in acquisition challenges for high-tech systems, significant pushback to the “revolution in military affairs”, and failure of the “Third Offset” to take hold and deliver capabilities to offset Chinese and Russian capabilities. Indeed, when the former Air Force and Space Force Chief Software Officer, Nicolas M. Chaillan, offered his resignation, one of the main reasons for leaving was “the failure of OSD and the Joint Staff to deliver on their own alleged top ‘priority’, JADC2 – they couldn’t ‘walk the walk.’” Senior leaders have recognized this disconnect, and several inquiries and studies regarding STEM competency have been conducted. Many have posed a false dilemma: a large, STEM-cognizant or small, STEM-expert force. However, current and future STEM human capital needs are managed at the unit and functional area level. This leads to “silos” and the tactical “needs of the present” dominating the strategic “needs of the future”, highlighted by only two functional areas systematically tracking future STEM needs. Therefore, the decision on force structure appears to have been historically made by default through these and other perceived structural realities, and a vast majority of recommendations have focused on the small STEM community – an exercise in diminishing returns. In essence, the solution often boils down to finding unicorns – officers that have chartered the unforgiving pathway through the traditional “gates” to general officer while obtaining sufficient STEM proficiency along the way. Fortunately for the Air Force, these officers exist, albeit at a rate below what the evidence would suggest is necessary. However, this approach fundamentally limits the ability to develop a deep pool of officers with the ability to create and integrate technologies and ensures the Dunning-Kruger effect is prevalent. The Dunning-Kruger effect is a cognitive bias where those with limited knowledge in an area lack the expertise necessary to recognize their lack of expertise and consequently are prone to overestimate their knowledge and performance. In short, we need less leaders overestimating their STEM knowledge and more with hard-earned STEM competency required to “walk the walk” to create and integrate technologies for military advantage. This will not be accomplished by restricting the emphasis to the traditional scientists and engineering (S&E) career fields – the pool, only 10% of line officers, and general officer progression is just too small. Fortunately, the recent SECAF’s Management Initiatives and Chief of Staff’s (CSAF) Action Orders, both containing emphasis on organic expertise to “accrue advantage in military-technological competition,” present an opportunity to truly develop a framework for the force of the future.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Field Experience Detecting PV Underperformance in Real Time Using Existing Instrumentation

Maintenance at large-scale photovoltaic plants employs a mix of preventative and corrective maintenance practices. Large outages, such as an inverter tripping offline, are often easy to detect. More subtle sub-inverter faults and failures can accumulate and go unnoticed for months or years. A software-based fault detection method has been developed to analyze commonly measured data from large-scale PV plants for more timely detection of subtle underperformance. The method has been demonstrated on eight datasets from large-scale plants with high accuracy of detection. Results are validated using aerial infrared scanning. String outages are detected with a true positive rate of 73 percent and tracker issues are detected with a true positive rate of 88 percent. The developed method can be uniformly applied to photovoltaic plants across a range of scales and configurations to assess performance, quickly detect underperformance, and determine the source and location of failures. The results inform and improve operations and maintenance at PV plants, ultimately aiding in improved affordability, reliability, availability, and resiliency of solar electricity.

14 SOLAR ENERGY↗
DOE OSTI2023

Advanced Monitoring and Control in the ANL METL Facility Using an Engineering Digital Twin

The potential benefits of using an engineering digital twin to achieve greater autonomy for monitoring and control functions in advanced reactors was investigated for the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The METL sodium purification system served as a representative system as it requires significant human in-the-loop interaction to accomplish its design function. The objective was to demonstrate how real-time operation could be automated while preserving oversight of the operator for ensuring that the system design functions are met. A digital twin model of the purification system was developed for both the cold trap purification loop and plugging meter diagnostic loop using information from the METL piping and instrumentation diagram (P&ID). Automated monitoring and diagnosis of component degradation in the METL facility was demonstrated in tests using the PRO-AID health monitoring software with the digital twin model incorporated in the library of components. Component failures were introduced and were successfully diagnosed in real time. These tests serve to demonstrate an advanced monitoring capability able to differentiate sensor degradation from component degradation, to generate a rank ordering of probabilities of different failure mechanisms that serves to circumvent the false alarm problem with current anomaly detection methods, and how facility monitoring can be transformed from anomaly detection to identification of a specific fault. Automated control of the purification system was demonstrated through simulations that exercised a model predictive controller designed using the digital twin model. Results of these simulations compared favorably with experimental data showing very good reference tracking response with negligible overshoot. In conclusion, these pilot tests and simulations successfully demonstrated the use of a digital twin for improved automation of monitoring and control. It was shown how the digital twin enables switching between control modes from cold trap operation where impurities are removed to plugging meter operation where impurity concentrations are measured.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures

Digital Instrumentation and Control (I&C) systems have a key role in nuclear power plants in the upgrade of aging analog systems. Digital systems improve plant safety and reliability through features such as increased hardware reliability and stability and improved failure detection capability. There is no consensus on which of the current probabilistic risk assessment methods are most suitable for use in the reliability analysis of digital I&C systems. While the traditional event-tree/fault-tree (ET/FT) approach is still used for their reliability modeling, there are concerns regarding this approach in properly accounting for dynamic interactions among system components since potentially significant dependencies among failure events may not be identified and/or their likelihood may not be properly quantified. Dynamic methodologies are expected to provide a much more accurate representation of probabilistic evolution of the I&C systems in time due to their capability to more properly account for complex interactions than the static approach. The applicability of dynamic PRA methodologies for digital I&C system is investigated using the criteria presented in the NUREG/CR-6901, and the comparisons made in NUREG/CR-6901 are updated in light of the latest studies. The Dynamic Event Tree (DET) approach has been identified as one of the top dynamic methods when evaluated against the requirements for the reliability modeling of digital I&C systems. The DET method is a strong candidate for integration into existing PRA studies, as it bears many similarities to the traditional ET approach. In this study, the DET approach has been applied to the Plant Protection System of the APR1400 design, and the results are compared to results from its available traditional ET/FT analysis. Possible approaches to evaluate and quantify the effects of common cause failures on system safety using dynamic methods are also examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

HSNMon: High-Speed Monitoring Software for Omni-Path

HSNMon is a robust high speed network monitoring daemon that provides insight into network availability, hardware failure, and network performance for switches and network cards. HSNMon collects counters, forwarding tables, and error information at high resolution using publicly available Omni-Path Management APIs. The collected data can be forwarded into multiple logging infrastructures including syslog and message queuing systems. HSNMon is only the infrastructure for collecting the network data. It does not include any collected data or proprietary LANL information

Holman, Brett↗