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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Decision support systems and methods for complex networks

Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Effect of Epistemic Uncertainty Modeling Approach on Decision-Making: Example using Equipment Performance Indicator

Quantitative risk assessments are an integral part of risk-informed regulation of current and future nuclear plants in the U.S. The Bayesian approach to uncertainty, in which both stochastic and epistemic uncertainties are represented with precise probability distributions, is the standard approach to modeling uncertainties in such quantitative risk assessments. However, there are long-standing criticisms of the Bayesian approach to epistemic uncertainty from many perspectives, and a number of alternative approaches have been proposed. Among these alternatives, the most promising (and most rapidly developing) would appear to be the concept of imprecise probability. In this paper, we employ a performance indicator example to focus the discussion. We first give a short overview of the traditional Bayesian paradigm and review some its controversial aspects, for example, issues with so-called noninformative prior distributions. We then discuss how the imprecise probability approach treats these issues and compare it with two other approaches: sensitivity analysis and hierarchical Bayes modeling. We conclude with some practical implications for risk-informed decision making.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

An Integrated Modeling and Data Management Strategy for Cellulosic Biomass Production Decisions

Emerging cellulosic bioenergy markets can provide land managers with additional options for crop production decisions. Integrating dedicated bioenergy crops such as perennial grasses and short rotation woody species within the agricultural landscape can have positive impacts on several environmental processes including increased soil organic matter in degraded soils, reduced sediment loading in watersheds, lower green house gas (GHG) fluxes, and reduced nutrient loading in watersheds. Implementing this type of diverse bioenergy production system in a way that maximizes potential environmental benefits requires a dynamic integrated modeling and data management strategy. This paper presents a strategy for designing diverse bioenergy cropping systems within the existing row crop production landscape in the midwestern United States. The integrated model developed quantifies a wide range environmental processes including soil erosion from wind and water, soil organic matter changes, and soil GHG fluxes within a geospatial data management framework. This framework assembles and formats information from multiple spatial and temporal scales. The data assembled includes yield and productivity data from harvesting equipment at the 1m scale, surface topography data from LiDAR mapping at the less than 1m scale, soil data from US soil survey databases at the 10m to 100m scale, and climate data at the county scale. These models and data tools are assembled into an integrated computational environment that is used to determine sustainable removal rates for agricultural residues for bioenergy production at the sub-field scale under a wide range of land management practices. Using this integrated model, innovative management practices including cover cropping are then introduced and evaluated for their impact on bioenergy production and important environmental processes. The impacts of introducing dedicated energy crops onto high-risk landscape positions currently being manage in row crop production are also investigated.

09 BIOMASS FUELS↗
DOE OSTI2012

Making Risk Models Operational for Situational Awareness and Decision Support

Modernization of nuclear power operations control systems, in particular the move to digital control systems, creates an opportunity to modernize existing legacy infrastructure and extend plant life. We describe here decision support tools that allow the assessment of different facets of risk and support the optimization of available resources to reduce risk as plants are upgraded and maintained. This methodology could become an integrated part of the design review process and a part of the operations management systems. The methodology can be applied to the design of new reactors such as small nuclear reactors (SMR), and be helpful in assessing the risks of different configurations of the reactors. Our tool provides a low cost evaluation of alternative configurations and provides an expanded safety analysis by considering scenarios while early in the implementation cycle where cost impacts can be minimized. The effects of failures can be modeled and thoroughly vetted to understand their potential impact on risk. The process and tools presented here allow for an integrated assessment of risk by supporting traditional defense in depth approaches while taking into consideration the insertion of new digital instrument and control systems.

cyber security↗
DOE OSTI2015

Reimagining What's Possible: How NREL's Energy Analysis and Decision Support Capabilities are Guiding Energy Systems Transformation at Home and Around the World; NREL (National Renewable Energy Laboratory)

This engaging brochure shows examples of how NREL enables energy system transformation through robust capabilities in energy analysis and decision support. By reimagining what's possible for renewable energy, NREL contributes to the Department of Energy mission to create energy systems that are cleaner, more reliable, and more secure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Texas Clean Energy Project: Decision Point Application, Section 2: Topical Report - Phase 1, February 2010-October 2013

Summit Texas Clean Energy, LLC (STCE) is developing the Texas Clean Energy Project (TCEP or the Project) to be located near Penwell, Texas. The TCEP will include an Integrated Gasification Combined Cycle (IGCC) power plant with a nameplate capacity of 400 megawatts electric (MWe), combined with the production of urea fertilizer and the capture, utilization and storage of carbon dioxide (CO 2 ) sold commercially for regional use in enhanced oil recovery (EOR) in the Permian Basin of west Texas. The TCEP will utilize coal gasification technology to convert Powder River Basin subbituminous coal delivered by rail from Wyoming into a synthetic gas (syngas) that will be cleaned and further treated so that at least 90 percent of the overall carbon entering the IGCC facility will be captured. The clean syngas will then be divided into two highhydrogen (H 2 ) concentration streams, one of which will be combusted as a fuel in a combined cycle power block for power generation and the other converted into urea fertilizer for commercial sale. The captured CO 2 will be divided into two streams: one will be used in producing the urea fertilizer and the other will be compressed for transport by pipeline for offsite use in EOR and permanent underground sequestration. The TCEP was selected by the U.S. Department of Energy (DOE) Office of Fossil Energy (FE) for cost-shared co-funded financial assistance under Round 3 of its Clean Coal Power Initiative (CCPI). A portion of this financial assistance was budgeted and provided for initial development, permitting and design activities. STCE and the DOE executed a Cooperative Agreement dated January 29, 2010, which defined the objectives of the Project for all phases. During Phase 1, STCE conducted and completed all objectives defined in the initial development, permitting and design portions of the Cooperative Agreement. This topical report summarizes all work associated with the project objectives, and additional work required to complete the financing of the Project. In general, STCE completed project definition, a front-end, engineering and design study (FEED), applied for and received its Record of Decision (ROD) associated with the NEPA requirements summarized in a detailed Environmental Impact Statement. A topical report covering the results of the FEED is the subject of a separate report submitted to the DOE on January 26, 2012. References to the FEED report are contained herein. In August 2013, STCE executed fixed-price turnkey EPC contracts and previously, in December 2011 a long-term O&M agreement, with industry-leading contractors. Other work completed during Phase 1 includes execution of all commercial input and offtake agreements required for project financing. STCE negotiated long-term agreements for power, CO 2 and urea offtake. A contract for the purchase of coal feedstock from Cloud Peak Energy’s Cordero Rojo mine was executed, as well as necessary agreements (supplementing the tariff) with the Union Pacific Railroad (UPRR) for delivery of the coal to the TCEP site. STCE executed firm agreements for natural gas transportation with ONEOK for long-term water supply with a private landowner. In addition, STCE secured options for critical easements and rights-of-way, completed and updated a transmission study, executed an interconnection agreement and has agreed a target October 31, 2013 financial closing date with debt and conventional and tax equity.

Mattes, Karl↗
DOE OSTI2012

Decision Point 3 of Statement of Project Objectives (SOPO) “Recovery Act: Development of ITM Oxygen Technology for Integration with Advanced Industrial Systems”

Air Products is carrying out a scope of work under Phase 5 of the ITM Oxygen Cooperative Agreement to design, build, and operate a ceramic membrane fabrication facility (the -CerFabII) to enable production of membrane modules to supply a conceptual 2000 ton per day (TPD) ITM Oxygen facility (the -ITM Oxygen Development FacilityII), and to perform supporting development tasks in materials development and engineering development toward industrial, carbon capture and sequestration applications. Air Products is executing this project under the American Recovery and Reinvestment Act (ARRA) with the objective to accelerate the adoption of ITM Oxygen technology to help meet the country’s goals for deploying clean power plants. The objective of this Topical Report is to address the requirements of Decision Point 3 (DP3), which pertains to the status of all Tasks within Phase 5 and most notably the project status of the CerFab (Task 30) prior to authorization of funds for equipment purchase and construction of the facility. The intent of the DP3 is to provide the opportunity for DOE-NETL to review the status of these tasks and to make recommendations on forward project direction, including a recommendation to pass into Budget Period 8. In the area of Materials Development, Air Products has specified a high pressure dilatometer system which will enable measurements of material expansion of ITM ceramic compounds at very high oxygen partial pressures consistent with CCS applications. Under Task 28.2, subcontractor Ceramatec has made significant progress since DP2 in materials selection and process development and improvement for advanced architecture module fabrication. Ceramatec has determined a materials specification, and has selected a process for making the material. Ceramatec has further developed and selected the process for applying the membrane to unsintered advanced architecture wafers with a Two Step process. Ceramatec has built submodules meeting leak rate specifications and intact 1-TPD modules compromised of advanced architecture components. Equipment and processes required for implementation of the advanced architecture design in the CerFab have been identified and are included in the Task 30 scope of equipment supply. Under Task 29.0, Air Products has developed conceptual ideas for implementation of ITM Oxygen in a 2000 TPD test unit. These concepts are proposed for scale up of the ITM technology to large scale with reduced commercial risk. Under Task 30, Air Products and Ceramatec have collaborated to re-design the CerFab process with the advanced architecture wafer production process as primary, and laid out the new process in the Tooele building; the required process equipment have been specified. The project team updated the project cost and schedule estimates, including all environmental permit schedules. The team also re-assessed project risk and costs for the commissioning and operating phases of the program. Newly projected costs for the CerFab, for which details are provided here as attachments, indicate a savings of approximately $100,000 relative to the original estimate at the time of Phase 5 contract definitization. However, an assessment of risks associated with the equipment, process, and operations of the CerFab indicate that approximately $2.9 million of costs should be expected to address various issues in the project. In addition, $1.6 million of additional spending is expected relative to the original estimate to operate the facility during Task 30.2. Air Products proposes a plan to re-direct funds from Tasks 28, 29, and 31 to Task 30 as necessary to allow the CerFab to meet the Phase 5 program objectives.

Armstrong, Phillip↗
DOE OSTI2016

Transportation Big Data: Unbiased Analysis and Tools to Inform Sustainable Transportation Decisions

Today, transportation operation and energy systems data are generated at an unprecedented scale. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is the go-to source for expertise in providing data and analysis to inform industry and government transportation decision making. The lab's teams of data experts and engineers are mining and analyzing large sets of complex data -- or 'big data' -- to develop solutions that support the research, development, and deployment of market-ready technologies that reduce fuel consumption and greenhouse gas emissions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2014

Gila San Francisco Decision Support Tool - 2010

The Gila-San Francisco Decision Support Tool analyzes the water demand and supply for the Gila San Francisco region spanning four counties in southwestern New Mexico (Catron, Hidalgo, Luna and Grant). Catalyzed by the 2004 Arizona Water Settlement Act and prompted by a keen awareness for the unique ecology in the region, the model was developed by Sandia with a collaborative modeling team from federal, state, local, and public stakeholders

Sun, Amy Cha-Tien↗
DOE OSTI2017

Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability

The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluating the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.

Guillen, Donna P.↗
DOE OSTI2018

Decision support system for outage management and automated crew dispatch

A decision support system is provided for utility operations to assist with crew dispatch and restoration activities following the occurrence of a disturbance in a multiphase power distribution network, by providing a real-time visualization of possible location(s). The system covers faults that occur on fuse-protected laterals. The system uses real-time data from intelligent electronics devices coupled with other data sources such as static feeder maps to provide a complete picture of the disturbance event, guiding the utility crew to the most probable location(s). This information is provided in real-time, reducing restoration time and avoiding more costly and laborious fault location finding practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Integrated Decision Methodology for Final Disposal of Radioactive Sources

Radioactive sources are used throughout the world, and their beneficial uses are many. Sources are at the core of many applications in different branches of industry, medicine, agriculture and research. Sources are present in a very wide range of equipment that is used for, inter alia, cancer treatment, killing bacteria in food, sterilizing medical supplies, measuring instruments such as gauges used to measure soil moisture and soil density and many other components, irradiating seeds for enhancing food production, protecting buildings from lightning strikes, mapping underground sources of water, prospecting for oil and gas reserves, measuring density of soil for construction projects, or even detecting smoke. At their “cradle” and when in use, radioactive sources are usually properly managed and controlled. It is when a source has reached the end of its useful life when they are at a higher risk of being under inadequate control, poorly managed, or even becoming orphan. Sources that have reached the end of their useful life must be carefully and safely managed. The “grave” of disused sources needs a proper disposal process to prevent them from posing a potential threat to people or the environment. To protect the public and the environment from the potential hazards of ionizing radiation, and to prevent disused sources from becoming orphan, a “cradle-to-grave” control of radioactive sources is essential, as promoted by the Code of Conduct on the Safety and Security of Radioactive Sources. This approach requires a national policy and strategy, an adequate legal and regulatory framework, and adequate resources and infrastructure. Many IAEAMember States have expressed the need for effective solutions to this challenge. There is also a gap related to the life cycle costs of potential disposal practices. This paper proposes a multi-attribute decision making methodology to compare disposal options using both economic and non-economic criteria leading to a preferred option for disposal and a strategy for final disposal of disused radioactive sources that is specific and optimized for each IAEA Member State.

Beatty, Randy↗
DOE OSTI2018

City Energy: From Data to Decisions. Hutchinson, Minnesota: Evaluating Local Solar Energy Generation Potential

The City of Hutchinson, Minnesota, partnered with the Energy Department and the National Renewable Energy Laboratory (NREL) to demonstrate how data and analysis can inform more strategic energy decisions. NREL based its analysis in part on the City Energy Profiles on the State and Local Energy Data (SLED) website (eere.energy.gov/sled). The profiles contain data compiled by SLED and the Cities Leading through Energy Analysis and Planning (Cities-LEAP) program. Cities across the country can follow the same approach and use data-driven analysis in their own energy planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

City Energy: From Data to Decisions. Rochester, New York: Reducing Energy Costs for Low-Income Households

The City of Rochester partnered with the Energy Department and the National Renewable Energy Laboratory (NREL) to demonstrate how data and analysis can inform more strategic energy decisions. NREL based its analysis in part on the State and Local Energy Data (SLED) website's City Energy Profiles (eere.energy.gov/sled). The profiles contain data compiled by SLED and the Cities Leading through Energy Analysis and Planning (Cities-LEAP) program. Cities across the country can follow the same approach and use data-driven analysis in their own energy planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Intelligently-Automated Facilities Expansion with the HEPCloud Decision Engine

The next generation of High Energy Physics experiments are expected to generate exabytes of data---two orders of magnitude greater than the current generation. In order to reliably meet peak demands, facilities must either plan to provision enough resources to cover the forecasted need, or find ways to elastically expand their computational capabilities. Commercial cloud and allocation-based High Performance Computing (HPC) resources both have explicit and implicit costs that must be considered when deciding when to provision these resources, and to choose an appropriate scale. In order to support such provisioning in a manner consistent with organizational business rules and budget constraints, we have developed a modular intelligent decision support system (IDSS) to aid in the automatic provisioning of resources---spanning multiple cloud providers, multiple HPC centers, and grid computing federations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

HEPCloud, an Elastic Hybrid HEP Facility using an Intelligent Decision Support System

HEPCloud is rapidly becoming the primary system for provisioning compute resources for all Fermilab-affiliated experiments. In order to reliably meet the peak demands of the next generation of High Energy Physics experiments, Fermilab must plan to elastically expand its computational capabilities to cover the forecasted need. Commercial cloud and allocation-based High Performance Computing (HPC) resources both have explicit and implicit costs that must be considered when deciding when to provision these resources, and at which scale. In order to support such provisioning in a manner consistent with organizational business rules and budget constraints, we have developed a modular intelligent decision support system (IDSS) to aid in the automatic provisioning of resources spanning multiple cloud providers, multiple HPC centers, and grid computing federations. In this paper, we discuss the goals and architecture of the HEPCloud Facility, the architecture of the IDSS, and our early experience in using the IDSS for automated facility expansion both at Fermi and Brookhaven National Laboratory.

Mhashilkar, Parag↗
DOE OSTI2018

Reliability Indexing of Intra-Facility Dispatch Decisions

The Powertrain Reliability Index (PRI) quantifies the trade-offs made in system reliability for efficiency, water use, and environmental purposes for relevant stakeholders. Using historical data from five North American hydroelectric facilities on a shared river system, this metric characterizes the annual probabilistic reliability of intra-facility dispatch decisions. The metric characterizes the operational risk of actual dispatch based on the lowest risk-exposed dispatch and the highest risk-exposed dispatch. By normalizing facility reliability by the number of components described within the facility, constraining operation by the historic dispatch total of unit starts and generating hours, and bounding by required grid flexibility, each facility’s dispatch can be scored for reliability.

Signore, Stephen R.↗