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DOE OSTI2021

Characterizing Impacts of Storage Faults on HPC Applications: A methodology and insights

In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses, which urges high-performance computing (HPC) platforms to equip with more advanced storage infrastructures such as solid-state disks (SSDs). While SSDs offer high-performance I/O, it remains unclear about the reliability challenges faced by the HPC applications under the SSD-related failures, in particular, failures resulting in data corruptions. The goal of this paper is to understand the impact of SSD-related data corruptions on the behaviors of complex HPC applications. To this end, we propose FFIS, a FUSE-based fault injection framework that systematically introduces storage faults into the application layer to model the errors originated from SSDs. FFIS is able to plant different I/O related faults into the data returned from underlying file systems, which also enables the investigation on the error resilience characteristics of the scientific file format for the first time. We demonstrate the use of FFIS with three representative real HPC applications, show how each application reacts to the data corruptions, and provide insights on the error resilience of the widely-adopted HDF5 file format for the HPC applications.

Fang, Bo↗

NASA NTRS1996

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology

Structural failure is rarely a "sudden death" type of event, such sudden failures may occur only under abnormal loadings like bomb or gas explosions and very strong earthquakes. In most cases, structures fail due to damage accumulated under normal loadings such as wind loads, dead and live loads. The consequence of cumulative damage will affect the reliability of surviving components and finally causes collapse of the system. The cumulative damage effects on system reliability under time-invariant loadings are of practical interest in structural design and therefore will be investigated in this study. The scope of this study is, however, restricted to the consideration of damage accumulation as the increase in the number of failed components due to the violation of their strength limits.

Onwubiko, Chin-Yere↗

NASA NTRS2020

Application of Risk Informed Decision Making to Highly Reliable Three Dimensionally Woven Thermal Protection System for Mars Sample Return

The NASA Risk Informed Decision Making process is used to assess a trade space of three dimensionally woven thermal protection systems for application to the Mars Sample Return Earth Entry Vehicle. Candidate architectures are assessed based on mission assurance, technical development, cost, and schedule risk. Assessment methodology differed between the architectures, utilizing a four-point quantitative scale for mission assurance and technical development and highly tailored PERT techniques for cost and schedule. Risk results are presented, in addition to a review of RIDM effectiveness for this application.

Needels, J.↗

DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Investigation into Sizing Photovoltaic with Energy Storage for Off-Grid Transactive Scenarios

In this study, a novel sizing methodology was developed for centralized and interconnected operating strategies of transactive microgrids and several variables were investigated including starting month, initial charge of battery, load variability, unit cost of solar panels and energy storage, number of systems, climate, and required reliability to determine their effect on total cost. The centralized strategy improved cost by seven to ten percent compared to the isolated strategy in every case. The interconnected strategy saved an incremental amount of money consistently compared to the isolated standard. The number of connected systems was not a strong effect. It was thought that increasing the number of systems would increase the benefit of energy sharing. Climate zones studied (“Cold”; “Hot-Dry/Mixed Dry”; “Mixed Humid”; and “Cold but with lower solar irradiation”) showed a large variation on cost with the Hot-Dry/Mixed Dry being the least expensive and Cold, with lower solar irradiation being the most expensive. Cost sensitivity analysis was performed showing that the unit cost of solar has a greater effect on the total cost. Required reliability of power, measured in outage hours, exhibited an inverse relation with cost.

14 SOLAR ENERGY↗

DOE OSTI2022

Operator Insights and Usability Evaluation of Machine Learning Assistance for Power Grid Contingency Analysis

Introducing machine learning (ML) assistance into any established process comes with adoption barriers, including entrenched procedures, technological and human readiness levels, human-machine trust, and work culture resistance to change. These barriers are even greater in critical operations such as operating a national or regional power grid, in which both regulatory frameworks and the importance of maintaining reliability levels causes additional resistance to the adoption of new computational support. Developers of future systems and job aides must consider not only technical aspects, but also whether new systems are usable by power system operators. This work presents the methodology and results of a study to evaluate the usability and readiness of a prototype recommender system for power grid contingency analysis. We explore operator cognitive load and evaluate operator performance when solving a collection of scenarios both with and without recommender assistance. We also examine operator trust in the system. We report insights gained on the readiness of the system using a collection of evaluation techniques.

Human-Machine Teaming, Power Systems, usability ev↗

NASA NTRS1976

A reliable dual-redundant sensor FDI system for the NASA F8C-DFBW aircraft

In this paper we outline the structure of a sensor failure detection and identification (FDI) system designed for the NASA F8C DFBW aircraft. The system is for use in a dual-redundant environment, and it takes maximal advantage of all functional and kinematic relationships among the sensed variables. The technique is reliable in that we have designed the system to account for a variety of unmodeled effects and have introduced a new concept - the quality sequential probability ratio (QSPR) - that provides a useful measure of our confidence in each test. The methodology used for determining detector parameters and the 'outer loop logic' for combining the various sources of information are described.

Deckert, J. C.↗

NASA NTRS1988

Rocket engine control and monitoring expert system

This paper focuses on the application of expert systems technology to the automatic detection, verification and correction of anomalous rocket engine operations through interfacing with an intelligent adaptive control system. The design of a reliable and intelligent propulsion control and monitoring system is outlined which includes the architecture of an Integrated Expert System (IES) serving as the core component. The IES functions include automatic knowledge acquisition, integrated knowledge base, and fault diagnosis and prediction methodology. The results of fault analysis and diagnostic techniques are presented for an example fault in the SSME main combustion chamber injectors.

Ali, Moonis↗

NASA NTRS1992

An assessment of waste processing/resource recovery technologies for lunar/Mars life applications

NASA's future manned missions to explore the solar system are by nature of long duration, mandating extensive regeneration of life support consumables from wastes generated in space-based habitats. Long-duration exploration missions would otherwise be prohibitive due to the number and frequency of energy-intensive resupply missions from Earth. Resource recovery is therefore a critical component of the controlled ecological life support system (CELSS). In order to assess resource recovery technologies for CELSS applications, the Crew and Thermal Systems Division at NASA-Johnson Space Center convened a three-day workshop to assess potential resource recovery technologies for application in a space-based CELSS. This paper describes the methodology of assessing and ranking of these technologies. Recommendations and issues are identified. Evaluations focused on the processes for handling and treatment of inedible plant biomass, human waste, and human generated trash. Technologies were assessed on the basis of safety, reliability, technology readiness, and performance characteristics.

Verostko, Charles E.↗

NASA NTRS1994

Implementing Software Safety in the NASA Environment

Until recently, NASA did not consider allowing computers total control of flight systems. Human operators, via hardware, have constituted the ultimate safety control. In an attempt to reduce costs, NASA has come to rely more and more heavily on computers and software to control space missions. (For example. software is now planned to control most of the operational functions of the International Space Station.) Thus the need for systematic software safety programs has become crucial for mission success. Concurrent engineering principles dictate that safety should be designed into software up front, not tested into the software after the fact. 'Cost of Quality' studies have statistics and metrics to prove the value of building quality and safety into the development cycle. Unfortunately, most software engineers are not familiar with designing for safety, and most safety engineers are not software experts. Software written to specifications which have not been safety analyzed is a major source of computer related accidents. Safer software is achieved step by step throughout the system and software life cycle. It is a process that includes requirements definition, hazard analyses, formal software inspections, safety analyses, testing, and maintenance. The greatest emphasis is placed on clearly and completely defining system and software requirements, including safety and reliability requirements. Unfortunately, development and review of requirements are the weakest link in the process. While some of the more academic methods, e.g. mathematical models, may help bring about safer software, this paper proposes the use of currently approved software methodologies, and sound software and assurance practices to show how, to a large degree, safety can be designed into software from the start. NASA's approach today is to first conduct a preliminary system hazard analysis (PHA) during the concept and planning phase of a project. This determines the overall hazard potential of the system to be built. Shortly thereafter, as the system requirements are being defined, the second iteration of hazard analyses takes place, the systems hazard analysis (SHA). During the systems requirements phase, decisions are made as to what functions of the system will be the responsibility of software. This is the most critical time to affect the safety of the software. From this point, software safety analyses as well as software engineering practices are the main focus for assuring safe software. While many of the steps proposed in this paper seem like just sound engineering practices, they are the best technical and most cost effective means to assure safe software within a safe system.

Wetherholt, Martha S.↗

NASA NTRS1995

Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

Tavana, Madjid↗

NASA NTRS2014

Adapting a Large-Scale Multi-Mission Ground System for Low-Cost CubeSats

The majority of today's CubeSat fleet consists of Earth-orbiting missions that mostly use existing ground systems developed by universities because of availability, simplicity, and low-cost. The Interplanetary NanoSpacecraft Pathfinder In Relevant Environment (INSPIRE) mission is a revolutionary CubeSat mission that will launch a pair of CubeSats into deep space to study the feasibility of CubeSats beyond low-Earth orbit. This uncovers a new set of systems and software engineering challenges to the development of a robust and reliable ground system in a low-cost environment. In this paper, we discuss the approach to these challenges by using the Jet Propulsion Laboratory's (JPL) Advanced Multimission Operation System (AMMOS) Ground Data System (GDS) as well as the methodologies used to engineer the flight system to work with an existing ground system developed for large-scale missions. Specifically we will focus on the command and telemetry subsystem of AMMOS, the Multimission Data Processing and Control System. We conclude with a retrospective on the challenges encountered and a brief discussion on our efforts to provide AMMOS to support future deep space CubeSat missions.

Quach, William L.↗

DOE OSTI2024

Detection and Quantitation of Hydrogen Emissions Role and Status of Detection Technology

Hydrogen is a critical strategy to decarbonize energy and manufacturing industries. Hydrogen is nontoxic and can be handled safely, but potential for secondary greenhouse impacts. Hydrogen releases arise from a variety of mechanisms (process, design features, "leaks") that contribute to total hydrogen releases. Detection methodologies will be critical to detect and quantify hydrogen emissions. Detection is to be integrated with advanced analytics (AI) and behavior modelling to effectively identify, quantify, and source locate hydrogen releases. Modelling of emissions will contribute to facility safety and reliability. DOE is committed to develop the tools to model and mitigate the impact of hydrogen releases which include: Support modeling to elucidate released hydrogen degradation; Support the development of tools for emissions quantitation; and Support engineering advancements to minimize hydrogen losses along the value chain (including process, design features, and leaks).

detection↗

NASA NTRS2020

Application of Risk Informed Decision Making to a Highly Reliable Three-Dimensionally Woven Thermal Protection System for Mars Sample Return

Needels, J.↗

NASA NTRS2014

Test Driven Development of Scientific Models

Test-Driven Development (TDD), a software development process that promises many advantages for developer productivity and software reliability, has become widely accepted among professional software engineers. As the name suggests, TDD practitioners alternate between writing short automated tests and producing code that passes those tests. Although this overly simplified description will undoubtedly sound prohibitively burdensome to many uninitiated developers, the advent of powerful unit-testing frameworks greatly reduces the effort required to produce and routinely execute suites of tests. By testimony, many developers find TDD to be addicting after only a few days of exposure, and find it unthinkable to return to previous practices.After a brief overview of the TDD process and my experience in applying the methodology for development activities at Goddard, I will delve more deeply into some of the challenges that are posed by numerical and scientific software as well as tools and implementation approaches that should address those challenges.

Overview of TDD Process↗

DOE OSTI2024

Automated Bayesian high-throughput estimation of plasma temperature and density from emission spectroscopy

Here, this paper introduces a novel approach for automated high-throughput estimation of plasma temperature and density using atomic emission spectroscopy, integrating Bayesian inference with sophisticated physical models. We provide an in-depth examination of Bayesian methods applied to the complexities of plasma diagnostics, supported by a robust framework of physical and measurement models. Our methodology is demonstrated using experimental observations in the field of magneto-inertial fusion, focusing on individual and sequential shot analyses of the Plasma Liner Experiment at LANL. The results demonstrate the effectiveness of our approach in enhancing the accuracy and reliability of plasma parameter estimation and in using the analysis to reveal the deep hidden structure in the data. This study not only offers a new perspective of plasma analysis but also paves the way for further research and applications in nuclear instrumentation and related domains.

Bayesian inference↗

DOE OSTI2024

Frontier system-on-chip (SoC) technology for microwave diagnostics (invited)

The next generation of fusion reactors, exemplified by projects such as the Demonstration Power Plant following the International Thermonuclear Experimental Reactor, faces the monumental challenge of proving the viability of generating electricity through thermonuclear fusion. This pursuit introduces heightened complexities in diagnostic methodologies, particularly in microwave-based diagnostics. The increased neutron fluence necessitates significant reductions in vessel penetrations and the elimination of internal diagnostics, posing substantial challenges. SoC technology offers a promising solution by enabling the miniaturization, modularization, integration, and enhancing the reliability of microwave systems. After seven years of research, our team successfully pioneered the V- and W-band system-on-chip approach, leading to the development of active transmitters and passive receiver modules applied in practical settings, notably within the DIII-D tokamak project. Arrays of these modules have supported microwave imaging diagnostics. New physics measurement results from the Electron Cyclotron Emission Imaging system on DIII-D provide compelling evidence of improved diagnostics following the adoption of SoC technology. Furthermore, we achieved a breakthrough in developing an F-band SoC, advancing higher frequency capabilities for fusion devices. These achievements represent a significant leap forward in fusion diagnostic technology, marking substantial progress toward establishing reliable and efficient plasma diagnostics for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Robust historical evapotranspiration trends across climate regimes

Evapotranspiration (ET) links the hydrological, energy and carbon cycles on the land surface. Quantifying ET and its spatio-temporal changes is also key to understanding climate extremes such as droughts, heatwaves and flooding. Regional ET estimates require reliable observation-based gridded ET datasets, and while many have been developed using physically based, empirically based and hybrid techniques, their efficacy, and particularly the efficacy of their uncertainty estimates, is difficult to verify. In this work, we extend the methodology used in Hobeichi et al. (2018) to derive two new versions of the Derived Optimal Linear Combination Evapotranspiration (DOLCE) product, with observationally constrained spatio-temporally varying uncertainty estimates, higher spatial resolution, more constituent products and extended temporal coverage (1980–2018). After demonstrating the efficacy of these uncertainty estimates with out-of-sample testing, we derive novel ET climatology clusters for the land surface, based on the magnitude and variability of ET at each location on land. The new clusters include three wet and three dry regimes and provide an approximation of Köppen–Geiger climate classes. The verified uncertainty estimates and extended time period then allow us to examine the robustness of historical trends spatially and in each of these six ET climatology clusters. We find that despite robust decreasing ET trends in some regions these do not correlate with behavioural ET clusters. Each cluster, and the majority of the Earth's surface, shows clear robust increases in ET over the recent historical period. The new datasets DOLCE V2.1 and DOLCE V3 can be used for benchmarking global ET estimates and for examining ET trends respectively.

54 ENVIRONMENTAL SCIENCES↗