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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A Best Practice for Developing Availability Guarantee Language in Photovoltaic (PV) O&M Agreements.

This document outlines the foundation for developing language that can be utilized in an Equipment Availability Guarantee, typically included in an O&M services agreement between a PV system or plant owner and an O&M services provider, or operator. Many of the current PV O&M service agreement Availability Guarantees are based on contracts used for traditional power generation, which create challenges for owners and operators due to the variable nature of grid-tied photovoltaic generating technologies. This report documents language used in early PV availability guarantees and presents best practices and equations that can be used to more openly communicate how the reliability of the PV system and plant equipment can be expressed in an availability guarantee. This work will improve the bankability of PV systems by providing greater transparency into the equipment reliability state to all parties involved in an O&M services contract.

Klise, Geoffrey Taylor↗
DOE OSTI2018

Perspective: Ab initio force field methods derived from quantum mechanics

It is often desirable to accurately and efficiently model the behavior of large molecular systems in the condensed phase (thousands to tens of thousands of atoms) over long time scales (from nanoseconds to milliseconds). In these cases, ab initio methods are difficult due to the increasing computational cost with the number of electrons. A more computationally attractive alternative is to perform the simulations at the atomic level using a parameterized function to model the electronic energy. Many empirical force fields have been developed for this purpose. However, the functions that are used to model interatomic and intermolecular interactions contain many fitted parameters obtained from selected model systems, and such classical force fields cannot properly simulate important electronic effects. Furthermore, while such force fields are computationally affordable, they are not reliable when applied to systems that differ significantly from those used in their parameterization. They also cannot provide the information necessary to analyze the interactions that occur in the system, making the systematic improvement of the functional forms that are used difficult. Ab initio force field methods aim to combine the merits of both types of methods. The ideal ab initio force fields are built on first principles and require no fitted parameters. Ab initio force field methods surveyed in this perspective are based on fragmentation approaches and intermolecular perturbation theory. This perspective summarizes their theoretical foundation, key components in their formulation, and discusses key aspects of these methods such as accuracy and formal computational cost. The ab initio force fields considered here were developed for different targets, and this perspective also aims to provide a balanced presentation of their strengths and shortcomings. Finally, this perspective suggests some future directions for this actively developing area.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Liquid helium fluid dynamics studies. Final Technical Report

Future high energy physics accelerators depend on a number of advanced technologies to open the many doors of scientific discovery. Among these advanced technologies, superconducting magnets and superconducting radio frequency (SRF) cavities are the backbone of the accelerator and detector systems. But all these low temperature systems depend critically on successful and reliable operation of their supporting technologies, among which the liquid helium cooling system is of the utmost importance. To improve the quality of these systems both in terms of efficiency and reliability, a robust helium cryogenics research and development (R&D) effort is required. The proposed research to be conducted by the FSU cryogenics group aims to produce fundamental knowledge that meets this R&D need. The projects that we have completed over the past grant period at Florida State University consist of experimental research on liquid helium fluid dynamics and heat transfer problems relevant to the development of future superconducting particle physics accelerators. Liquid helium is the coolant used in all such facilities and in many of these facilities He II (the low temperature phase of liquid helium also known as superfluid helium) is preferred due to its outstanding heat transfer characteristics. The work consists of two main experimental studies that probe both fundamental as well as practical aspects of liquid helium cooling. The first is a broad and fundamental study of the heat and mass transfer processes that can occur during a sudden catastrophic loss of vacuum (SCLV) incident in a superconducting accelerator. SCLV refers to the remote but extremely critical accident scenario where atmospheric pressure air is allowed to flood into the insulating vacuum system and impinge on the liquid helium cooled surfaces in the accelerator. Safe performance and recovery from such accidents is essential to the reliable operation of superconducting accelerators. The dynamics of this process is quite complex and so our approach is to conduct a series of well-orchestrated experiments that probe the various physical phenomena that can occur during an SCLV event. The experiments are coupled with analytic and numerical analysis in an effort to develop a general understanding of the process and to assist with future accelerator design and development. The second activity is directed toward fundamental understanding of heat and mass transfer in He II, which is essential to the design of superconducting magnets and radio frequency cavities in accelerators. The work consists of flow visualization of the dynamics of He II using laser assisted techniques. Two complementary techniques are used to study the fundamentals of the turbulent state. The first technique uses neutrally buoyant solid hydrogen particles to probe the flow fields of the superfluid and normal fluid components. The other technique uses laser excited He2* molecules as tracers of the normal fluid motion within the He II. The activities also included an effort to use visualization techniques to locate transient hot spots in radio frequency superconducting cavities. Such work provides valuable information about the heat transfer process in He II and its impact on the performance of superconducting devices. The research effort at Florida State University is not directly in support of a specific high energy physics experiment or facility. Rather, the work is general and coordinated with HEP accelerator laboratories to provide valuable insight that can assist with future accelerator development.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

On-Ramp Wireless: Program Final Report

The objective of the project was to develop and demonstrate a centrally managed, wide area wireless distribution grid sensor and faulted circuit indicator system capable of monitoring underground and other hard-to-reach distribution circuits while delivering the reliability, ease of installation, security, battery life and low cost structure required to be a commercially viable product for the electric utility industry. This integrated wireless grid monitoring system enables utilities across the United States to enhance the reliability of their distribution grids, improve performance metrics (i.e., SAIFI, CAIDI, SAIDI), support dynamic load management and predictive maintenance, and enable future remote monitoring applications necessary to achieve the goals of the Smart Grid. This project scope included: conceptual design; trade studies focused on maximizing ease of installation, sensing capabilities, power budget analysis to reduce maintenance costs and time to replace; sensor product development; and field technology demonstration. The trade studies included Radio Frequency (RF) propagation. The RF Trade Study was completed for the 2.4 GHz ISM-band and not extended to 1 GHz band due to availability of suitable radio solutions and associated impacts to overall commercial value of the solution. The technology demonstrations/field trials were performed in partnership with Southern California Edison and San Diego Gas and Electric. The sensing systems included fault indicator and wireless analog sensor devices from Schweitzer Engineering Labs (SEL) and smart transformer monitoring devices from Gridsense. Both SEL and Gridsense worked with ORW during this project to During the demonstration phase, sensors were deployed in multiple locations. Resulting data was analyzed for the following: RF performance, communication systems reliability, sensor system capabilities, and system level analytics relative to the commercial value to the smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Future-proofing photovoltaics module reliability through a unifying predictive modeling framework

Solar energy, especially photovoltaics (PV), plays a significant role in the global energy transition required for decarbonization. Technological advancements in increasing efficiencies coupled with cost reductions through economies of scale made PV a cost-competitive energy source set to exceed the milestone of 1 TW globally deployed capacity in 2022. However, ongoing downward price pressure coupled with increasing service life expectations creates tremendous challenges for reliability engineers in ensuring the safe and reliable operation of PV modules and systems over the anticipated service life. Today's reliability research efforts aim for module lifetimes of up to 50 years. Still, our current tools fall short in accurately assessing degradation mechanisms and failure modes over such extended periods. We argue that the well-established PV reliability learning cycle needs to be accelerated to keep up with the rapid technological advancements and high expectations that are put on PV and its role in the global energy transition. In this article, we explore the evolution of the PV reliability learning cycle and highlight the significance that predictive modeling capabilities will have on future PV module reliability. We propose creating a unifying modeling framework - which once established will enable the holistic assessment of PV module reliability, accelerate the PV reliability learning cycle, and bring us closer to quantitative service life predictions of PV modules.

14 SOLAR ENERGY↗
DOE OSTI2023

Model-Free Probabilistic Forecasting of Nodal Voltages in Distribution Systems

As the penetration of distributed energy resources (DERs) into distribution systems increases, so does the interest in forecasting relevant system variables to help mitigate the associated challenges. One such challenge is the more frequent occurrence of excessive voltages in distribution systems with higher shares of DERs. Accurate and reliable estimates together with forecasts of system states (i.e., nodal voltages) will therefore play a key role in improving the utilization of these variable and uncertain sources while mitigating potential operational risks. Whilst recent literature has explored machine learning (ML) methods for voltage estimation and their extrapolation for a short-time period into the future, few have taken uncertainty quantification into account, and these methods have not yet been translated into operations. This paper discusses the advantages offered by probabilistic voltage forecasts and proposes a non-parametric Bayesian method suitable for forecasting nodal voltages at short-term time horizons while accounting for uncertainties in load and distributed photovoltaic (PV) generation. We demonstrate the value of the proposed Gaussian process (GP) model for a case study using historical forecasts and observation data.

distribution system↗
DOE OSTI2017

A Pattern Language for High-Performance Computing Resilience

High-performance computing systems (HPC) provide powerful capabilities for modeling, simulation, and data analytics for a broad class of computational problems. They enable extreme performance of the order of quadrillion floating-point arithmetic calculations per second by aggregating the power of millions of compute, memory, networking and storage components. With the rapidly growing scale and complexity of HPC systems for achieving even greater performance, ensuring their reliable operation in the face of system degradations and failures is a critical challenge. System fault events often lead the scientific applications to produce incorrect results, or may even cause their untimely termination. The sheer number of components in modern extreme-scale HPC systems and the complex interactions and dependencies among the hardware and software components, the applications, and the physical environment makes the design of practical solutions that support fault resilience a complex undertaking. To manage this complexity, we developed a methodology for designing HPC resilience solutions using design patterns. We codified the well-known techniques for handling faults, errors and failures that have been devised, applied and improved upon over the past three decades in the form of design patterns. In this paper, we present a pattern language to enable a structured approach to the development of HPC resilience solutions. The pattern language reveals the relations among the resilience patterns and provides the means to explore alternative techniques for handling a specific fault model that may have different efficiency and complexity characteristics. Using the pattern language enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack.

Hukerikar, Saurabh↗
DOE OSTI2016

Technical Basis for Evaluating Software-Related Common-Cause Failures

The instrumentation and control (I&C) system architecture at a nuclear power plant (NPP) incorporates protections against common-cause failures (CCFs) through the use of diversity and defense-in-depth. Even for well-established analog-based I&C system designs, the potential for CCFs of multiple systems (or redundancies within a system) constitutes a credible threat to defeating the defense-in-depth provisions within the I&C system architectures. The integration of digital technologies into the I&C systems provides many advantages compared to the aging analog systems with respect to reliability, maintenance, operability, and cost effectiveness. However, maintaining the diversity and defense-in-depth for both the hardware and software within the digital system is challenging. In fact, the introduction of digital technologies may actually increase the potential for CCF vulnerabilities because of the introduction of undetected systematic faults. These systematic faults are defined as a “design fault located in a software component” and at a high level, are predominately the result of (1) errors in the requirement specification, (2) inadequate provisions to account for design limits (e.g., environmental stress), or (3) technical faults incorporated in the internal system (or architectural) design or implementation. Other technology-neutral CCF concerns include hardware design errors, equipment qualification deficiencies, installation or maintenance errors, instrument loop scaling and setpoint mistakes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Abuse Tolerance Improvements

As lithium-ion battery technologies mature, the size and energy of these systems continues to increase (> 50 kWh for EVs); making safety and reliability of these high energy systems increasingly important. While most material advances for lithium-ion chemistries are directed toward improving cell performance (capacity, energy, cycle life, etc.), there are a variety of materials advancements that can be made to improve lithium-ion battery safety. Issues including energetic thermal runaway, electrolyte decomposition and flammability, anode SEI stability, and cell-level abuse tolerance continue to be critical safety concerns. This report highlights work with our collaborators to develop advanced materials to improve lithium-ion battery safety and abuse tolerance and to perform cell-level characterization of new materials.

25 ENERGY STORAGE↗
DOE OSTI2019

Energy Storage System Safety: ESS-Related Proposed Changes to the Group B 2018 ICC International Codes. Special Briefing Paper

The goal of the DOE OE ESS Safety Roadmap is to foster confidence in the safety and reliability of energy storage systems (ESSs). Three interrelated objectives support the realization of that goal: research, codes and standards, and communication/coordination. The objective focused on codes and standards is as follows: To apply research and development (R&D) to support efforts that are focused on ensuring that codes and standards are available to enable the safe implementation of ESSs in a comprehensive, non-discriminatory and science-based manner. The following activities support that objective and realization of the goal: a. Review and assess codes and standards that affect the design, installation, and operation of ESSs. b. Identify gaps in knowledge that require research and analysis that can serve as a basis for criteria in those codes and standards. c. Identify areas in codes and standards that potentially need revision or enhancement and can benefit from activities conducted under R&D. d. Develop input for new or revisions to existing codes and standards through individual stakeholders, facilitated task forces, or through laboratory staff supporting these efforts. The purpose of this special briefing paper is to support the above objective by providing information about current and upcoming efforts being conducted by U.S. standards and model code developing organizations, specifically code changes associated with the 2018 Group B International Codes (I-Codes) of the International Code Council (100)2 that are relevant to ESSs.

25 ENERGY STORAGE↗
DOE OSTI2019

Analyzing a Five-Year Failure Record of a Leadership-Class Supercomputer

Extreme-scale computing systems are required to solve some of the grand challenges in science and technology. From astrophysics to molecular biology, supercomputers are an essential tool to accelerate scientific discovery. However, large computing systems are prone to failures due to their complexity. It is crucial to develop an understanding of how these systems fail to design reliable supercomputing platforms for the future. This paper examines a five-year failure and workload record of a leadership-class supercomputer. To the best of our knowledge, five years represents the vast majority of the lifespan of a supercomputer. This is the first time such analysis is performed on a top 10 modern supercomputer. We performed a failure categorization and found out that: i) most errors are GPU-related, with roughly 37% of them being double-bit errors on the cards; ii) failures are not evenly spread across the physical machine, with room temperature presumably playing a major role; and iii) software errors of the system bring down several nodes concurrently. Our failure rate analysis unveils that: i) the system consistently degrades, being at least twice as reliable at the beginning, compared to the end of the period; ii) Weibull distribution closely fits the mean-time-between-failure data; and iii) hardware and software errors show a markedly different pattern. Finally, we correlated failure and workload records to reveal that: i) failure and workload records are weakly correlated, except for certain types of failures when segmented by the hours of the day; ii) several categories of failures make jobs crash within the first minutes of execution; and iii) a significant fraction of failed jobs exhaust the requested time with a disregard of when the failure occurred during execution.

Rojas, Elvis↗
DOE OSTI2024

Model-Based Approaches to Generate Knowledge from Data in a Plant Reliability Context

One challenge that nuclear power plant system engineers are facing is that the amount of equipment reliability (ER) data being continuously generated are extremely large. These data elements come in different forms: textual (e.g., condition reports) and numeric (e.g., generated by monitoring systems) and they provide system engineers with valuable insights and information regarding the discovery of anomalous behaviors or degradation trends, the identification of the possible causes behind such behaviors and trends, and the prediction of their direct consequences. This paper directly targets the generation of knowledge from ER data by putting “data into context”. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional (i.e., cause-effect) relations. ER data elements are processed by identifying first which elements of the developed MBSE elements they are referring to. This task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process “knowledge extraction” where our methods to extract knowledge from textual data. Lastly, once numeric and textual ER data elements have been processed and “understood”, we discover possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if there is a temporal relation among them. The logic and temporal are the two main ingredients to perform “machine reasoning” from ER data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

DOE OE Energy Storage Systems Safety Roadmap Focus on Proposed Changes to the ICC International Codes Special Briefing Paper — Unofficial Hearing Results April 2018

The goal of the DOE OE ESS Safety Roadmap1 is to foster confidence in the safety and reliability of energy storage systems (ESSs). Three interrelated objectives support the realization of that goal: research, codes and standards, and communication/coordination. The objective focused on codes and standards is - To apply research and development (R&D) to support efforts that are focused on ensuring that codes and standards are available to enable the safe implementation of ESSs in a comprehensive, non-discriminatory and science-based manner. The purpose of this special briefing paper is to support the above objective by providing information about current and upcoming efforts being conducted by U.S. standards developing organizations, specifically code changes associated with the 2018 Group A International Codes (I-Codes) of the International Code Council (ICC) that are relevant to ESSs.

25 ENERGY STORAGE↗
DOE OSTI2025

Model-driven prediction for accelerator magnet diagnostics to improve operation reliability

Reliability is one of the most critical metrics for accelerator operation, especially in user facilities. To reduce costly facility downtime and provide an operational environment where system performance can be reliably predicted in support of scientific studies, we are developing a model-driven approach for prediction and anomaly detection. Here, in this study, we present the application of a model-driven method that employs a linear regression model to predict the future temperature, in real time, of accelerator magnets at the NSLS-II light source. This approach enables proactive identification of magnet-heating issues, facilitating magnet flushing prior to the occurrence of permanent damage without interrupting machine operation. The implementation of this method in the NSLS-II control room is described and the analysis of the online results is presented. The results demonstrate the model’s effectiveness in providing early alerts to engineers and improving the reliability of accelerator operations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of a MOOSE thermal model of the MPC-32 canister and HI-STORM overpack

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. Safe management of spent nuclear fuel (SNF) is a key aspect of the back end of the nuclear fuel cycle, and SNF dry storage systems are becoming a popular, effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution for maintaining SNF (~60 years) prior to final disposal. This project aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack, using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. This study will investigate and demonstrate the thermal-hydraulics capabilities of the MOOSE framework, including natural circulation, heat transfer, porous flows, etc. The ultimate goal of the project is to verify whether MOOSE tools (including Pronghorn) can be used to study the thermal performance of the SNF dry cask storage system. This study provides reliable and inclusive solving strategy for dry cask problems. The detailed information about the solving scheme and the governing equations related to the physics of the system is provided in the report. The results for thermal-hydraulic analysis of the HI-STORM system is produced with using open source modules of the MOOSE framework. This results highlights the flexibility and modularity of the MOOSE which makes it a unique candidate for the frameworks and code packages. Therefore, integration of the MOOSE to UNF ST&DARDS will improve the thermal-hydraulic capability of the system while providing distinctive features to users.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Higher order mode analysis of a 915 MHz 2-cell cavity for a prototype industrial accelerator

A possible solution to reduce the complexity posed by the cryogenic systems in a superconducting RF accelerator for industrial applications, is to capitalize on the advances achieved by the Nb3Sn superconducting RF technology, as well as the feasibility of a reliable 4 K cooling system, based on commercial cryocoolers. Following this philosophy, the conceptual design for a prototype, conduction-cooled, 4 MeV, 20 kW SRF electron linac, is being developed at Jefferson Lab. Such design is based on a 915 MHz two-cell Nb3Sn cavity. In this contribution, we present the proposed cavity design, including the fundamental power coupler, and the analysis of the Higher Order Modes, using numerical simulations to estimate the potentially dangerous modes and to provide the requirements for damping for reliable operations with a cryocooler.

Rimmer, Robert↗
DOE OSTI2019

Blackcomb2: Hardware-Software Co-design for Nonvolatile Memory in Exascale Systems

The impending shift from DRAM and Flash to fast nonvolatile memory (NVM) provides a game-changing opportunity to rethink traditional system architectures; to address their energy inefficiencies; to leverage the new devices for greater performance; and to exploit the new capability of nonvolatility to enhance system resilience, even in the face of larger system scale and degraded reliability of components. Building on the accomplishments of the Blackcomb Project, funded in 2010, we propose to identify, evaluate, and optimize the most promising NVM hardware and software technologies, which are essential to provide the necessary memory capacity, performance, resilience, and energy efficiency in exascale systems. Capacity and energy are the key drivers. Today's pressing application requirements mandate exascale computing; the datasets and concurrency of these applications demand memory capacity that cannot be met by traditional memory technologies. Although charge-based DRAM will endure, experts foresee only modest DRAM capacity gains. And, as moving data between levels of the hierarchy, and storing and accessing data on disk consumes significant energy, a more energy efficient solution is required. We, therefore, posit that exascale systems will need high density, energy-efficient storage technologies, such as nonvolatile memory for access, transformation, and management of exascale data. To address these issues, in this renewal request, we propose continue the work of our vertically- integrated, focussed team, where our co-design is informed by proxies and interactions with DOE co-design centers. In software, we start by assuming that nonvolatility requires new abstractions and new infrastructure, allowing persistent objects, and delivering performance gains for _le systems and robustness through fast checkpointing. In architecture, we evaluate the tradeoffs of performance and energy by employing a scalable and accurate simulation system to analyze realistic proxy applications. Through this co-design process, we rethink the whole memory architecture, from the cell to the array to the device, with ECC, wearout management, and interfaces. Finally, we provide open-source software models of these NVM-based memory systems.

97 MATHEMATICS AND COMPUTING↗