Risk management in petroleum development projects: Technical and economic indicators to define a robust production strategy
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Santos, Susana M. G.↗
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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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Water Resources Utilization and Protection in the Coal Mining Area of Northern China
This study investigates multiple types of water resources in the western mining area in China, their supply-demand balance by using the same dimension gray recurrence dynamic model GM (1, 1), and water content coefficients of mines to ease water supply-demand contradiction. A multi-objective programming model is proposed for optimal water resources allocation management. Optimal technical schemes for water resources allocation among different users are obtained. The optimization model improves upon the previous studies by using water demand and water supply forecast. Coordinated development for mining safety, mine water utilization, and remediation and control of water environment is achieved.
54 ENVIRONMENTAL SCIENCES↗
Nanomaterials in Extreme Environments: Fundamentals and Applications Rostislav A. Andrievski and Arsen V. Khatchoyan
Nanomaterials in Extreme Environments Rostislav A. Andrievski and Arsen V. Khatchoyan Springer, 2016 106 pages, $99.00 (e-book $69.99) ISBN 978–3-319–25331–2 This slim volume is an extensive review of our current understanding of the response of nanostructured materials to extreme operating conditions, such as high temperature, flux of high energy neutrons, high pressure, mechanical stress, and oxidizing environments. The emphasis is on metallic materials, especially Cu alloys. Graphene-based materials, fullerenes, polymeric materials, nano-glasses and glass-ceramics are not covered by this review. The book has six chapters including an introduction and a brief conclusion. The introduction documents the growth of scientific interest in nanostructured materials and stresses the need to study the behavior of nanomaterials under extreme conditions. This chapter also presents Herbert Gleiter’s classification of nanomaterials into twelve groups based on the shapes of the nanoscale features and chemical composition of the components of the nanostructure. The second chapter deals with the high temperature environment and the thermodynamics and kinetics of grain growth. The authors identify the lack of reliable thermodynamic data as a key limitation in this field. The discussion brings out the interplay of structural relaxation, redistribution of excess free volume, diffusion, and recrystallization in multicomponent nanostructures at elevated temperature. Chapter 3 focuses on the effects of ion and neutron irradiation on the structure and properties of nanomaterials. The authors do a good job of highlighting recent studies on the radiation tolerance of nanocrystalline oxides and rapid grain growth under irradiation. The material addresses both fission and fusion reactor applications. Chapter 4 reviews the effects of severe plastic deformation and cyclic loading on nanostructure formation and phase transformation. This chapter also explores the challenge of achieving high density while retaining nanostructural features during processing under extreme loads and high temperatures. Chapter 5 discusses the effects of corrosion on nanomaterials. The behavior of a variety of alloys and high melting point compounds in liquid media and high temperature oxidizing environments is reviewed. The concluding chapter identifies areas for further research. The book would have benefited from careful copy editing for use of the English language. Moreover, the excessive use of acronyms makes the text difficult to read. Each chapter ends with a section on the application of nanomaterials and a long list of references. The integration of theoretical approaches and simulation results with experimental data offers fresh insights into the behavior of nanomaterials. Overall, this book will serve as useful reference material for researchers interested in nanomaterials driven to extremes. Reviewer: Ram Devanathan is Technical Group Manager of Reactor Materials and Mechanical Design, Pacific Northwest National Laboratory, USA.
Devanathan, Ram↗
Metering Best Practices: A Guide to Achieving Utility Resource Efficiency, Release 3.0
DOE FEMP guide for metering best practices aligned with the DOE Metering Guidance revision required by the 12/2013 Presidential Memo. The purpose of this guide is to provide information on effective energy and water metering strategies, relevant metering technologies and communications, how to collect and use metered data, and how to develop a metering plan. This guide is designed to serve as a resource for facility, energy, and water management and technical staff. It does not try to represent the universe of metering-related material. Rather, it attempts to: Provide background information on why metering is important, Provide guidance on the structure of an effective metering program, Provide information on metering and communications technologies, and Highlight common uses of metered data.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Status of Progress Made Toward Safety Analysis and Technical Site Evaluations for DOE Managed HLW and SNF.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development (R&D) on generic deep geologic disposal systems (i.e., repositories). This report describes specific activities in FY 2016 associated with the development of a Defense Waste Repository (DWR)a for the permanent disposal of a portion of the HLW and SNF derived from national defense and research and development (R&D) activities of the DOE.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
State Performance-Based Regulation Using Multiyear Rate Plans for U.S. Electric Utilities
Electric utilities today must contain costs at a time when many need to modernize aging systems and all face major changes in technologies, customer preferences and competitive pressures.Most U.S. electric utility facilities are investor-owned, subject to rate and service regulation by state public utility commissions. Regulatory systems under which these utilities operate affect their performance and ability to meet these challenges. In this business environment, multiyear rate plans have some advantages over traditional rate regulation.The report focuses on key design issues and provides case studies of the multiyear rate plan approach, applicable to both vertically integrated and restructured states. Mark Newton Lowry and Matt Makos of Pacific Energy Group Research and Jeff Deason of Berkeley Lab authored the report; Lisa Schwartz, Berkeley Lab, was project manager and technical editor.The report is aimed primarily at state utility regulators and stakeholders in the state regulatory process. The multiyear rate approach also provides ideas on how to streamline oversight of public power utilities and rural electric cooperatives for their governing boards.Two key provisions of multiyear rate plans strengthen cost containment incentives and streamline regulation: 1. Reducing frequency of rate cases, typically to every four or five years 2. Using an attrition relief mechanism to escalate rates or revenue between rate cases to address cost pressures such as inflation and growth in number of customers, independently of the utility’s own cost Better utility performance can be achieved under well-designed multiyear rate plans while achieving lower regulatory costs. Benefits can be shared between utilities and their customers. But plans can be complex and involve significant changes in the regulatory system. Designing plans that stimulate utility performance without undue risk and share benefits fairly can be challenging.This report discusses the rationale for multiyear rate plans and their usefulness under modern business conditions. It then explains critical plan design issues and challenges and presents results from numerical research that considers the extra incentive power achieved under different plan provisions. Next, the report presents several case studies of utilities that have operated under formal multiyear rate plans or, for various reasons, have stayed out of rate cases for more than a decade. These studies consider the effect of multiyear rate plans and rate case frequency on utility cost, reliability and other performance dimensions.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Structural Health Monitoring of Nuclear Spent Fuel Storage Facilities
Interim storage of spent nuclear fuel from reactor sites has gained additional importance and urgency for resolving waste-management-related technical issues. To ensure that nuclear power remains clean energy, monitoring has been identified by DOE as a high priority cross-cutting need, necessary to determine and predict the degradation state of the systems, structures, and components (SSCs) important to safety (ITS). Therefore, nondestructive structural condition monitoring becomes a need to be installed on existing or to be integrated into future storage system to quantify the state of health or to guarantee the safe operation of nuclear power plants (NPPs) during their extended life span. In this project, the lead university and the collaborating national laboratory teamed to develop a nuclear structural health monitoring (n-SHM) system based on in-situ piezoelectric sensing technologies that can monitor structural degradation and aging for nuclear spent fuel DCSS and similar structures. We also aimed to identify and quantify possible influences of nuclear spent fuel environment (temperature and radiation) to the piezoelectric sensor system and come up with adequate solutions and guidelines therefore. We have therefore developed analytical model for piezoelectric based n-SHM methods, with considerations of temperature and irradiation influence on the model of sensing and algorithms in acoustic emission (AE), guided ultrasonic waves (GUW), and electromechanical impedance spectroscopy (EMIS). On the other side, experimentally the temperature and irradiation influence on the piezoelectric sensors and sensing capabilities were investigated. Both short-term and long-term irradiation investigation with our collaborating national laboratory were performed. Moreover, we developed multi-modal sensing, validated in laboratory setup, and conducted the testing on the We performed multi-modal sensing development, verification and validation tests on very complex structures including a medium-scale vacuum drying chamber and a small-scale mockup canister available for the desired testing. Our work developed the potential candidate for long term structural health monitoring of spent fuel canister through piezoelectric wafer sensors and provided the sensing methodologies based on AE and GUW methodologies. It overall provides an innovative system and methodology for enhancing the safe operation of nuclear power plant. All major accomplishments planned in the original proposal were successfully achieved.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
PV Systems Reliability and Outreach
The project purpose was to collaborate with the Electric Power Research Institute (EPRI) to reach out to the photovoltaic (PV) industry to cooperate, collaborate and facilitate establishment and access to PV plant data for use in the Photovoltaic Reliability Operations and Maintenance (PVROM) database. Sandia National Laboratories (SNL) and EPRI conducted this outreach to expand and accelerate the implementation of PVROM by gathering more data for analyzing trends, with a goal of accelerating the adoption of PV systems as a primary power generation source in the United States. SNL and EPRI analyzed the data from the PVROM database to assess industry trends in operations and maintenance (O&M) and develop guidelines for the industry. More specifically, this project was intended to leverage SNL’s expertise in PV plant reliability data collection and analysis, with data sharing partners that own or operate PV systems who wanted to learn about rigorous reliabilitybased data collection to track issues over time and improve O&M activities. The partnership also worked to host multiple workshops as part of the SNL/EPRI PV Systems Symposium to gather industry feedback on O&M process improvement and data standards, and share insights learned from the collaboration between SNL and EPRI in the area of PV system reliability. Additional outreach included multiple ‘expert elicitation’ interviews led by EPRI to gather best practices and paths forward for improving/standardizing PV plant O&M and asset management practices. Technical accomplishments included further development of the PVROM database process, sharing best practices for reliability data collection and improving industry understanding of existing O&M practices, important knowledge, and new and novel techniques for benefitting EPRI utility partners and the broader PV industry. Improved reliability at a PV power plant leads to a lower levelized cost of energy (LCOE), which is reflected most directly in its operating expenses. Electric utilities that utilize PV as a larger share of plants they own and operate are interested in having a high degree of availability or ‘uptime’, similar to other power generation sources in their service area. Having low cost, reliable PV generation can lead to fewer costs that need to be recovered by the utility over the lifetime of the power plant, and less regulatory uncertainty when considering bulk transmission and distribution system reliability. The public and taxpayers benefit by the electric utility passing through lower electricity costs.
14 SOLAR ENERGY↗
Advancing Fusion with Machine Learning Research Needs Workshop
The pursuit of fusion energy has required extensive experimental and theoretical science activities to develop the knowledge needed that will enable design of successful fusion power plants. Even today, following decades of research in many key areas including plasma physics and material science, much remains to be learned to enable optimization of the tokamak or other paths to fusion energy. Data science methods from the fields of machine learning and artificial intelligence (ML/AI) offer opportunities for enabling or accelerating progress toward the realization of fusion energy by maximizing the amount and usefulness of information extracted from experimental and simulation output data. Jointly supported by the Department of Energy Offices of Fusion Energy Science (FES) and Advanced Scientific Computing Research (ASCR), a workshop was organized to identify Priority Research Opportunities (PRO’s) for application of ML/AI methods to enable accelerated solution of fusion problems. The resulting “Advancing Fusion with Machine Learning Research Needs Workshop,” held in Gaithersburg, MD, April 30 – May 2, 2019, brought together ~ 60 experts in fields spanning fusion science, data science, statistical inference and mathematics, machine learning, and artificial intelligence, along with DOE program managers and technical experts, to identify key PRO’s.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Report of the Workshop on Advanced Fusion with Machine Learning, April 30-May 2, 2019
The pursuit of fusion energy has led to extensive activities in both experimental and theoretical science. The central goal of all these activities has been to develop the knowledge necessary for the design of successful fusion power plants. Even today, following decades of research in many key areas including plasma physics and material science, much remains to be learned in order to achieve optimization of the tokamak or other paths to fusion energy. Data science methods from the fields of machine learning and artificial intelligence (ML/AI) offer opportunities for enabling or accelerating progress toward the realization of fusion energy by maximizing the amount and usefulness of information extracted from experimental and simulation output data. From April 30 to May 2 of 2019, a workshop on “Advancing Fusion with Machine Learning Research Needs” was held in Gaithersburg, MD, with joint support from the Fusion Energy Science (FES) and Advanced Scientific Computing Research (ASCR) Programs. The workshop brought together ~ 60 experts in fields spanning fusion science, data science, statistical inference and mathematics, machine learning, and artificial intelligence, along with DOE program managers and technical experts, with the goal of identifying Priority Research Opportunities (PROs) for the application of ML/AI methods to accelerating progress on solving fusion problems. During the workshop, seven key PROs were identified. The description of each PRO includes relevant fusion problems, potentially useful ML/AI approaches, known gaps currently preventing the use of such approaches, and research guidelines to maximize the effective application of ML/AI methods to the PRO. The report containing the full description of the workshop outcomes is available at https://science.osti.gov/-/media/fes/pdf/workshopreports/FES_ASCR_Machine_Learning_Report.pdf
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Energy Intensity Baselining & Tracking Summary Guide: Better Buildings, Better Plants
The Department of Energy (DOE) Better Plants (BP) program is a voluntary energy efficiency leadership initiative for U.S. manufacturers that encourages companies to reduce their energy intensity, typically by 25% within a ten-year period. BP partners are required to report their progress to the DOE annually by establishing an energy intensity baseline and tracking their energy consumption. BP partners receive access to a Technical Account Manager (TAM), DOE resources including software tools and trainings, and recognition when they achieve their goal. This summary guide provides the basics of baselining and tracking your energy intensity. For a more information and special considerations, please see the Energy Intensity Baselining and Tracking Guidance 2020.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Demand Response in Industrial Facilities: Peak Electric Demand
The US Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) is a voluntary energy efficiency leadership initiative for US manufacturers and water/wastewater entities. The program encourages organizations to commit to reducing the energy intensity of their US operations over a 10-year period, typically by 25%. Companies joining Better Plants are recognized by DOE for their leadership in implementing energy efficiency practices and for reducing their energy intensity. Better Plants Partners are assigned to a Technical Account Manager, who can help companies establish energy intensity baselines, develop energy management plans, and identify key resources and incentives from DOE, other federal agencies, states, utilities, and other organizations that can enable them to reach their goals. Better Plants Partners are expected to report their progress to DOE once a year. This involves establishing an energy intensity baseline upon joining the program and then tracking their progress over time. Demand Response in Industrial Facilities: Peak Electrical Demand is intended to help companies understand peak demand response programs offering by their local utility. Manufacturing industries can learn about time-varying rates and smart technologies they can use to help them reduce their energy bills. This guidance document is applicable to companies participating at either the program or challenge level. Although this guide is intended primarily to assist companies participating in Better Plants, the methodologies and guidance within the document are applicable to any organization interested in understanding peak demand response programs.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Supply Chain Risk Mitigation for Scientific Facilities and Tools
In November 2021, the U.S. Department of Energy (DOE) Office of Science (SC) convened a roundtable on “Supply Chain Risk Mitigation for Scientific Facilities and Tools” to gather information about current supply chain challenges in key technology areas unique to SC or critical to its mission. The roundtable brought together technical, project management, and procurement experts from DOE national laboratories, industry, academia, and other government agencies. Panelists explored opportunities, possible partnerships, and mechanisms to strengthen the domestic supply chain for critical SC technologies.
99 GENERAL AND MISCELLANEOUS↗
Demand Response in Industrial Facilities: Peak Electric Demand
The US Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) is a voluntary energy efficiency leadership initiative for US manufacturers and water/wastewater entities. The program encourages organizations to commit to reducing the energy intensity of their US operations over a 10-year period, typically by 25%. Companies joining Better Plants are recognized by DOE for their leadership in implementing energy efficiency practices and for reducing their energy intensity. Better Plants Partners are assigned to a Technical Account Manager, who can help companies establish energy intensity baselines, develop energy management plans, and identify key resources and incentives from DOE, other federal agencies, states, utilities, and other organizations that can enable them to reach their goals. Better Plants Partners are expected to report their progress to DOE once a year. This involves establishing an energy intensity baseline upon joining the program and then tracking their progress over time. Demand Response in Industrial Facilities: Peak Electrical Demand is intended to help companies understand peak demand response programs offering by their local utility. Manufacturing industries can learn about time-varying rates and smart technologies they can use to help them reduce their energy bills. This guidance document is applicable to companies participating at either the program or challenge level. Although this guide is intended primarily to assist companies participating in Better Plants, the methodologies and guidance within the document are applicable to any organization interested in understanding peak demand response programs.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Omar Ishak: Bioengineer by day, sports car tinkerer by night
Omar Ishak was 13 when he got his first car — or rather, the pieces of his first car. He had helped in his dad’s auto shop in the summers from age 10 to 12, but the vehicle that his dad presented, an Acura Integra, was a challenging first car. Missing most of one side and without a working engine, it seemed to Omar as if it were better off as scrap metal. "If you can piece together all the parts," Omar remembers his dad saying, "you can have it." Omar, now a technical project manager in Weapons Production (ALDWP) with the Transition to Operations/Readiness (PPI-3) group, at first felt overwhelmed at the enormity of what needed to be finished. As a child, he’d played with Legos and liked to tinker and take broken things apart. Then he’d become fascinated with building smaller-scaled model cars and, by the time his dad owned that shop, the fascination had manifested into real cars.
99 GENERAL AND MISCELLANEOUS↗
Taking learning to another level
As a technical project manager at Los Alamos National Laboratory, Scott Boise works on programs and projects that make a big impact. Although he spends most of his days in a quiet office, he also makes a big impact on his team. He's well-known for his character and integrity because of the way he develops leadership skills on the team, promotes respect for others and lives a commitment to learning. Scott joined the Lab in June 2021, the period of the COVID-19 pandemic when most new employees began their careers without ever having stepped foot on-site. That experience has continued to serve as a reminder to him that new employees face numerous challenges no matter how and when they start. He's made it his aim to do what he can to lift some of that load. Coming to the Lab from a career in the biomedical industry, Scott arrived with years of project management experience but without a deep understanding of nuclear operations. His dedication to continuous learning has helped him pursue experiential opportunities and ask the proper questions to understand his role.
99 GENERAL AND MISCELLANEOUS↗
Undergraduate Women in STEM Internship Program
In collaboration with the Universities Research Association, Inc. (URA), establishment of the Undergraduate Women in STEM Internship pilot program assists Fermi Research Alliance, LLC (FRA) with honoring its commitment to increasing gender, racial and ethnic workforce diversity. This focused initiative is intended to invite, support and yield a qualified pipeline of alumnae underrepresented in FRA’s science and technology management and technical staff positions. Interns in this program spend 10-12 weeks at Fermilab working under the direct leadership, guidance and supervision of scientists, engineers, computing professionals, technicians and staff across all directorates performing hands-on research. In addition, the intern cohort meets with mentors and advisors to grow their professional networks, to take part in engaging and inclusive intellectual discussions, to directly benefit from workplace resources, and to participate in professional development and social engagement opportunities. The design of each research project and the supervision, mentorship and evaluation is conducted by a scientific, engineering, computing professional at Fermilab.
99 GENERAL AND MISCELLANEOUS↗
Regulators’ Financial Toolbox: Behind-the-Meter (BTM) Energy Storage Summary
On October 10, 2023, NARUC’s Center for Partnerships & Innovation (CPI) hosted a Regulators’ Financial Toolbox Webinar on the topic of Behind-the-Meter (BTM) Energy Storage. The webinar featured opening remarks by the Honorable Katherine Peretick, Commissioner, Michigan Public Service Commission; and presentations by Ryan Chan, Principal Strategic Analyst, Pacific Gas and Electric Company (PG&E); Arushi Sharma Frank, Energy Market Design Lead and Senior Counsel for Energy Regulatory Matters and Greg Thurnher, Technical Program Manager, Tesla; and Mark LeBel, Senior Associate, Regulatory Assistance Project (RAP).
24 POWER TRANSMISSION AND DISTRIBUTION↗