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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Computer-Based Procedures for Field Workers in Nuclear Power Plants: Development of a Model of Procedure Usage and Identification of Requirements

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field workers. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do so. This paper describes the development of a Model of Procedure Use and the qualitative study on which the model is based. The study was conducted in collaboration with four nuclear utilities and five research institutes. During the qualitative study and the model development requirements and for computer-based procedures were identified.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Model of Procedure Usage – Results from a Qualitative Study to Inform Design of Computer-Based Procedures

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory, the Institute for Energy Technology, and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field operators. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do this. The underlying philosophy in the research effort is “Stop – Start – Continue”, i.e. what features from the use of paper-based procedures should we not incorporate (Stop), what should we keep (Continue), and what new features or work processes should be added (Start). One step in identifying the Stop – Start – Continue was to conduct a baseline study where affordances related to the current usage of paper-based procedures were identified. The purpose of the study was to develop a model of paper based procedure use which will help to identify desirable features for computer based procedure prototypes. Affordances such as note taking, markups, sharing procedures between fellow coworkers, the use of multiple procedures at once, etc. were considered. The model describes which affordances associated with paper based procedures should be transferred to computer-based procedures as well as what features should not be incorporated. The model also provides a means to identify what new features not present in paper based procedures need to be added to the computer-based procedures to further enhance performance. The next step is to use the requirements and specifications to develop concepts and prototypes of computer-based procedures. User tests and other data collection efforts will be conducted to ensure that the real issues with field procedures and their usage are being addressed and solved in the best manner possible. This paper describes the baseline study, the construction of the model of procedure use, and the requirements and specifications for computer-based procedures that were developed based on the model. It also addresses how the model and the insights gained from it were used to develop concepts and prototypes for computer based procedures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Intergovernmental Advanced Stationary PEM Fuel Cell System Demonstration (Final Report)

A program to complete the design, construction and demonstration of a PEMFC system fuelled by Ethanol, LPG or NG for telecom applications was initiated in October 2007. Early in the program the economics for Ethanol were shown to be unfeasible and permission was given by DOE to focus on LPG only. The design and construction of a prototype unit was completed in Jun 2009 using commercially available PEM FC stack from Ballard Power Systems. During the course of testing, the high pressure drop of the stack was shown to be problematic in terms of control and stability of the reformer. Also, due to the power requirements for air compression the overall efficiency of the system was shown to be lower than a similar system using internally developed low pressure drop FC stack. In Q3 2009, the decision was made to change to the Plug power stack and a second prototype was built and tested. Overall net efficiency was shown to be 31.5% at 3 kW output. Total output of the system is 6 kW. Using the new stack hardware, material cost reduction of 63% was achieved over the previous Alpha design. During a November 2009 review meeting Plug Power proposed and was granted permission, to demonstrate the new, commercial version of Plug Power's telecom system at CERL. As this product was also being tested as part of a DOE Topic 7A program, this part of the program was transferred to the Topic 7A program. In Q32008, the scope of work of this program was expanded to include a National Grid demonstration project of a micro-CHP system using hightemperature PEM technology. The Gensys Blue system was cleared for unattended operation, grid connection, and power generation in Aug 2009 at Union College in NY state. The system continues to operate providing power and heat to Beuth House. The system is being continually evaluated and improvements to hardware and controls will be implemented as more is learned about the system's operation. The program is instrumental in improving the efficiency and reducing costs of PEMFC based power systems using LPG fuel and continues to makes steps towards meeting DOE's targets. Plug Power would like to thank DOE for their support of this program.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Reconsolidated Salt as a Geotechnical Barrier

Salt as a geologic medium has several attributes favorable to long-term isolation of waste placed in mined openings. Salt formations are largely impermeable and induced fractures heal as stress returns to equilibrium. Permanent isolation also depends upon the ability to construct geotechnical barriers that achieve nearly the same high-performance characteristics attributed to the native salt formation. Salt repository seal concepts often include elements of reconstituted granular salt. As a specific case in point, the Waste Isolation Pilot Plant recently received regulatory approval to change the disposal panel closure design from an engineered barrier constructed of a salt-based concrete to one that employs simple run-of-mine salt and temporary bulkheads for isolation from ventilation. The Waste Isolation Pilot Plant is a radioactive waste disposal repository for defense-related transuranic elements mined from the Permian evaporite salt beds in southeast New Mexico. Its approved shaft seal design incorporates barrier components comprising salt-based concrete, bentonite, and substantial depths of crushed salt compacted to enhance reconsolidation. This paper will focus on crushed salt behavior when applied as drift closures to isolate disposal rooms during operations. Scientific aspects of salt reconsolidation have been studied extensively. The technical basis for geotechnical barrier performance has been strengthened by recent experimental findings and analogue comparisons. The panel closure change was accompanied by recognition that granular salt will return to a physical state similar to the halite surrounding it. Use of run-of-mine salt ensures physical and chemical compatibility with the repository environment and simplifies ongoing disposal operations. Our current knowledge and expected outcome of research can be assimilated with lessons learned to put forward designs and operational concepts for the next generation of salt repositories. Mined salt repositories have the potential to isolate permanently vast inventories of radioactive and hazardous wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Reconsolidated Salt as a Geotechnical Barrier - 16535

Salt as a geologic medium has several attributes favorable to long-term isolation of waste placed in mined openings. Salt formations are largely impermeable and induced fractures heal as stress returns to equilibrium. Permanent isolation also depends upon the ability to construct geotechnical barriers that achieve nearly the same high-performance characteristics attributed to the native salt formation. Salt repository seal concepts often include elements of reconstituted granular salt. As a specific case in point, the Waste Isolation Pilot Plant recently received regulatory approval to change the disposal panel closure design from an engineered barrier constructed of a salt-based concrete to one that employs simple run-of-mine salt and temporary bulkheads for isolation from ventilation. The Waste Isolation Pilot Plant is a radioactive waste disposal repository for defense related transuranic elements mined from the Permian evaporite salt beds in southeast New Mexico. Its approved shaft seal design incorporates barrier components comprising salt-based concrete, bentonite, and substantial depths of crushed salt compacted to enhance reconsolidation. This paper will focus on crushed salt behavior when applied as drift closures to isolate disposal rooms during operations. Scientific aspects of salt reconsolidation have been studied extensively. The technical basis for geotechnical barrier performance has been strengthened by recent experimental findings and analogue comparisons. The panel closure change was accompanied by recognition that granular salt will return to a physical state similar to the halite surrounding it. Use of run-of-mine salt ensures physical and chemical compatibility with the repository environment and simplifies ongoing disposal operations. Our current knowledge and expected outcome of research can be assimilated with lessons learned to put forward designs and operational concepts for the next generation of salt repositories. Mined salt repositories have the potential to isolate permanently vast inventories of radioactive and hazardous wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Artificial Intelligence for Data Center Operations (AI Ops)

HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analysis and Planning Framework for Nuclear Plant Transformation

Commercial nuclear power in the United States has been an unqualified success by any measure, providing low cost, carbon-free, and safe baseload electricity for decades. The industry today is at the peak of its historical performance in terms of generation output, reliable operations, and demonstrated nuclear safety. However, it is no longer among the lowest-cost electric generation sources with the emergence of subsidized renewables and shale gas generation. The business model that has served the operating nuclear fleet so well over its life is now a drag on cost performance due to its reliance on a large highly skilled labor force. In contrast, digital technology and innovation are enabling dramatic efficiencies in energy production, resulting in fierce competition for a commodity such as electricity. The nuclear power industry has responded to this challenge with many initiatives to improve efficiency and modernize plant equipment, especially where reliability and obsolescence issues are pressing. However, it would be a missed opportunity to merely modernize the plant components and the work processes of an outdated business model that was formulated to manage the technology of the 1960s. Rather, the greater opportunity is to transform that business model to one that fully exploits the capabilities of modern digital technology, resulting in substantially lower production costs and sustainable market viability. One successful example of such transformation is the concept of Integrated Operations, which was introduced into the North Sea oil and gas industry a couple of decades ago when the profitability of operating these fields was severely threatened by low world petroleum prices and the high overhead of operating the offshore oil and gas platforms. This effort resulted in significant changes to how these oil fields were operated and allowed the industry to continue profitable operation of these platforms. This example has some remarkable parallels to the U.S. commercial nuclear industry as described in the next section. This report provides an analysis and planning framework for such a nuclear plant operating model transformation based on the transferable learnings from the North Sea transformation. This framework is termed Integrated Operations for Nuclear or ION. This report describes the key principles and methods of Integrated Operations and how they are being applied in a collaboration between the DOE Light Water Reactor Sustainability Program and Xcel Energy in an initiative to transform its operating model for performance improvement and long-term sustainability. It describes a method to bring the operating costs of a nuclear fleet in line with market-based pricing, transforming work functions to reduce cost with technology innovations. This initiative will continue over the next several years in the detailed development of transformative concepts for nuclear plants, which will be published as follow-up to this initial report on Integrated Operations for Nuclear.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Robotic D and D: Smart robots - 15093

Project' managers continually seek an ever-greater optimization of time between remote handling operations and those carried out manually; therefore, new technological solutions must be deployed. Robotics offers a great opportunity in this new field of technology to carry out, for example, samplings or remediation in hostile, cluttered surroundings. Teams in charge of dismantling at the CEA have therefore first defined robotizable functions. These functions have been assembled from existing technological blocks to arrive at robots which are operating today [RICAIII, patent: FR 2925702]. Lessons learned, particularly from experience with the RICA robot, have enabled the operating technical specifications to be fine-tuned. A new study phase has been launched applying the same principle of adapting existing, proven means. The growing role of robotics today is unquestioned. Led by research and the academic world; robots such as those equipped with wheels, tracks, feet or even helicopter rotors, are today accessible to the general public, particularly via broadening of the 'open source' concept. Added to these we need tools able to manage large component deconstruction systems, like MAESTRO. Industrialization of such high-potential technological solutions has been aided by: - Easy use, - Increasing reliability, - Flexibility of 'open source' solutions, - Widening skill networks, and therefore greater technical support - Lower costs. Decontamination and dismantling (D and D) projects must be able to meet a number of special demands, increasing the number of unit designs, their costs and delivery times. The complexity of dismantling works sites mean that each is a special case to be dealt with almost independently. Such a way of approaching these projects is not on the same wavelength as industry, with tool and method standardization. The answer to the challenge of operations in difficult environments is an eco-system of functions, performed by a set of inter-connected robots. The first step towards the construction of such robot teams is devoted to functions where strength is not necessary: investigating and clean-up in hostile environments. With this in mind, the CEA Marcoule teams have been given the objective of merging the strengthening commercial robotic world with the needs of D and D, and thus to improve the transversal use of the systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Machine Learning Solutions for a Stable Grid Recovery

Grid operating security studies are typically employed to establish operating boundaries, ensuring secure and stable operation for a range of operation under NERC guidelines. However, if these boundaries are severely violated, existing system security margins will be largely unknown, as would be a secure incremental dispatch path to higher security margins while continuing to serve load. As an alternative to the use of complex optimizations over dynamic conditions, this work employs the use of machine learning to identify a sequence of secure state transitions which place the grid in a higher degree of operating security with greater static and dynamic stability margins. Several reinforcement learning solution methods were developed using deep learning neural networks, including Deep Q-learning, Mu-Zero, and the continuous algorithms Proximal Reinforcement Learning, and Advantage Actor Critic Learning. The work is demonstrated on a power grid with three control dimensions but can be scaled in size and dimensionality, which is the subject of ongoing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Chapter 5, "License Renewal and Aging Management for Continued Service

As of August 2011, there were 104 commercial nuclear power reactors licensed to operate in 31 states in the United States. Initial operating licenses in the United States are granted for a period of 40 years. In order to help assure an adequate energy supply, the USNRC has established a timely license renewal process and clear requirements that are needed to ensure safe plant operation for an extended plant life. The principals of license renewal and the basic requirements that address license renewal are identified as well as additional sources of guidance that can be utilized as part of the license renewal process. Aging management program inspections and operating experience related to the concrete and steel containment structures are provided. Finally, several lessons learned are provided based on containment operating experience.

Aging degradation↗
DOE OSTI2019

EGS Collab Project Electrical Resistivity Tomography Characterization and Monitoring

The EGS (Enhanced Geothermal Systems) Collab project is performing stimulation experiments in highly monitored and well-characterized intermediate-scale (~10-20 m) field test beds. The characterization and monitoring system includes an array of electrodes grouted in place within six monitoring wells, with 16 electrodes per well. The electrodes enable characterization of the 3D low-frequency electrical properties of the host rock, and changes in those properties during stimulation and tracer testing using both static and time-lapse Electrical Resistivity Tomography. In this talk we present: 1) ERT array design and installation, 2) baseline (pre-stimulation) imaging results, 3) time-lapse data collected during stimulation operations, and 4) real-time imaging during clean water injections intended to illuminate flow paths as a decrease in bulk electrical conductivity. We will also discuss aspects and lessons learned for conducting ERT imaging operations in the presence of high fluid pressure gradients during stimulation and flow operations. Results to date reveal a highly heterogeneous rock fabric, ranging over four orders of magnitude in bulk electrical conductivity, and high polarization capacity. Baseline imaging results are consistent with borehole logs and core studies. Time-lapse imaging results to identify major flow paths during tracer studies are forthcoming and will be discussed during this presentation. Ultimately the ERT imaging data sets provide useful information for validating and verifying model predictions in preparation for research at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE).

electrical resistivity tomography, geophysics, geo↗
DOE OSTI2026

NN-OpInf

SAND2026-18878O The NN-OpInf tool is a PyTorch-based approach to operator inference that uses composable, structure-preserving neural networks to represent nonlinear operators. Operator inference is a machine learning method for inferring low-dimensional systems from data and polynomial models for system dynamics. However, many systems do not conform to polynomial structures, which NN-OpInf addresses by parameterizing operators with neural networks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2019

Advancing Energy Efficiency in Developing Countries: Lessons Learned from Low-Income Residential Experiences in Industrialized Countries

Energy efficiency has great potential to address economic development, energy security, and environmental protection around the world and in developing countries in particular. Low-income residents of developing countries stand to gain significantly from energy efficiency investments. This report presents lessons learned in delivering energy-efficiency programs for low-income households that are taken from experiences in the United States and other member countries of the Organisation for Economic Co-operation and Development (OECD). Lessons learned in delivering energy-efficiency programs to low-income households of industrial countries are summarized from the perspectives of program design, program delivery, and institutions in order to provide best practices that are applicable to countries in different development stages. This report discusses who to target, how to reduce energy burden, coordinating institutional stakeholders, which efficiency tools to use, how to fund low-income energy efficiency programs, screening tools to prioritize projects, outreach strategies, and evaluation methods. The report concludes with a framework for understanding different levels of energy-efficiency interventions based on institutional capacity, political willpower, and resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Deep anomaly detection for industrial systems: a case study

We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements. We formulate the problem as a self-supervised learning where data under normal operation are used to train a deep neural network autoregressive model, i.e., use a window of time series data to predict future data values. The aim of such a model is to learn to represent the system dynamic behavior under normal conditions, while expect higher model vs. measurement discrepancies under faulty conditions. In real world applications, many control settings are discrete in nature. In this paper, vector embedding and joint losses are employed to deal with such situations. Both LSTM and CNN based deep neural network backbones are studied on the Secure Water Treatment (SWaT) testbed datasets. Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks. Evaluation methods and results are discussed based on the SWaT dataset along with potential pitfalls.

anomaly detection, deep neural network↗
DOE OSTI2023

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

17 WIND ENERGY↗
DOE OSTI2016

Lessons Learned - New Resin Processing System Selection, Procurement, Delivery, Set-up, Training, and Operation - 16615

Energy Northwest's first resin dewatering and drying system was purchased in 1989. Although the system functions acceptably, parts are no longer available and containers are no longer off-the shelf items, which require special manufacturing, thus higher cost, as compared to those used by many plants today. The decision was made to procure a new resin processing system (Self-Engaging Rapid Dewatering System, or SERDS). This paper provides lessons learned regarding each aspect of pre-planning, to procurement, acceptance testing, procedure development, and operation, including challenges as well as successes, which could help others in their decision making when contemplating procurement of a similar system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Fukushima Daiichi Information Repository FY13 Status

The accident at the Fukushima Daiichi nuclear power station in Japan is one of the most serious in commercial nuclear power plant operating history. Much will be learned that may be applicable to the U.S. reactor fleet, nuclear fuel cycle facilities, and supporting systems, and the international reactor fleet. For example, lessons from Fukushima Daiichi may be applied to emergency response planning, reactor operator training, accident scenario modeling, human factors engineering, radiation protection, and accident mitigation; as well as influence U.S. policies towards the nuclear fuel cycle including power generation, and spent fuel storage, reprocessing, and disposal. This document describes the database used to establish a centralized information repository to store and manage the Fukushima data that has been gathered. The data is stored in a secured (password protected and encrypted) repository that is searchable and available to researchers at diverse locations.

97 MATHEMATICS AND COMPUTING↗