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At least 1,279 records · Page 71

U.S. department of energy safety design strategy review and approval beyond critical decision 3 for the high-level waste facility - 15525

The Waste Treatment and Immobilization Plant (WTP) in Hanford, Washington, is the nation's largest environmental remediation construction project. In 2012, at the WTP's High-Level Waste (HLW) Facility, the U.S. Department of Energy (DOE), Office of River Protection (ORP) restricted construction work at the Hazard Category 2 nuclear facility because of unresolved technical issues associated with the facility and of misalignment of the design and nuclear safety basis. By 2013, as additional issues were discovered, ORP limited HLW design and procurement activities. Addressing the technical issues and the misalignment of the design basis with the Preliminary Documented Safety Analysis (PDSA) is a priority for ORP. A proposal was developed to use the concept of a safety design strategy (SDS), as documented in DOE-STD-1189-2008, Integration of Safety into the Design Process, as a planning mechanism to support facility design and PDSA alignment. The standard provides the processes to develop an SDS that will ensure safety is integrated into design early in the project, by the start of preliminary design. Ultimately, as design progresses, an SDS is intended to support development of the project's PDSA. However, in this unique case, the HLW Facility design and construction phase has progressed beyond Critical Decision 3 and DOE-STD-1189-2008 was issued in 2008; 6 years after ORP approved the first WTP PDSA. In July 2013, ORP and the contractor recognized that the unresolved technical issues and design - safety basis misalignment should be addressed through a renewed look at nuclear safety requirements, and agreed that developing an SDS tailored to the criteria in DOE-STD-1189-2008 provided the best path forward to better integrate design and safety. Development of the SDS for the HLW Facility was one of many goals ORP established in a plan that describes how ORP will determine whether, and under what conditions, the contractor should be authorized to proceed with production engineering, procurement, and construction activities for the HLW Facility. Over the next several months, the contractor developed the draft SDS, identifying design basis accidents and control strategies for those accidents. ORP monitored progress and, when appropriate, provided recommendations. In April 2014, the contractor provided a draft SDS to ORP for initial review by an independent DOE Review Team. The Review Team was comprised of representatives from nuclear safety, criticality safety, engineering, fire protection, the Office of Environmental Management, the Assistant Manager WTP, and the DOE Chief of Nuclear Safety. A unique draft document review and interactive review process, facilitated through work sessions and continuous communication with the contractor, culminated in the development of 147 technical comments on topics varying from SDS implementation to hydrogen deflagration in vessels. Comment resolution sought to improve project clarity, delineation of control strategies, and, holistically, facilitate integration of safety into design in the SDS, as it will guide the restart of the HLW Facility production engineering and limited procurement and construction activities. All comments were resolved in support of a contractor submission of the final SDS to ORP at the end of June 2014. Successful resolution of these comments was achieved by continuing the real-time response and incorporation interaction with the contractor to ensure that mutual objectives were satisfied. The response times were facilitated through telephone, E-mail, and a shared file server accessible to contractor and DOE reviewers across the DOE complex. As a measure of success of this process, the Safety Basis Approval Authority (ORP Manager) and the WTP Federal Project Director approved the SDS on August 1, 2014, with no conditions of approval. DOE and the contractor recognized that it would be difficult to implement the SDS without changes to the existing contractor's engineering and nuclear safety processes. Accordingly, the contractor developed or revised a significant number of engineering and nuclear safety plans and procedures to implement the SDS into the design process. Over the coming year, the contractor will conduct a gap analysis between the SDS and the presently approved PDSA to incorporate the design basis accidents and preferred control strategies developed from the SDS into the PDSA. In addition, ORP will conduct an assessment of the contractor's implementation of the SDS into the design process at the appropriate stage of implementation, within 6 to 12 months of approval. Although the SDS was developed late in the HLW project timeline, the document will facilitate alignment of design and the safety basis, and is a key step in the return to full production engineering for the HLW Facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluating Contaminant Transport in the Vadose Zone to Support Remedy Decisions at Aqueous-Waste Disposal Sites - 16195

Inorganic contaminants in aqueous waste disposed at land surface have a potential to contaminate groundwater. However, contaminant concentrations are attenuated during transport through the vadose zone. Quantifying contaminant attenuation and the resulting temporal concentration profile of in underlying groundwater is important for assessing the need for, and type of, remediation in the vadose zone and groundwater. An approach was developed for evaluating vadose zone transport and attenuation of aqueous wastes containing inorganic (non-volatile) contaminants that were disposed at land surface (i.e., directly to the ground in cribs, trenches, tile fields, etc.) and their effect on underlying groundwater. The approach provides a structured method to estimate transport of contaminants through the vadose zone and the resulting temporal profile of groundwater contaminant concentrations. A series of numerical model simulations was applied to investigate how different factors affect contaminant transport in the vadose zone and the conditions for which individual factors are important. This analysis demonstrated that, while water flow and contaminant transport can be complex during aqueous-waste disposal, conditions will change over time after disposal ceases and fewer factors will control the contaminant transport rate and resulting temporal profile of groundwater contaminant concentrations. Data verifying that these conditions have been reached can be provided by a few key metrics such as the vertical profile of moisture content, the temporal profile of recharge at the site, and basic information about waste disposal and subsurface properties. Under these conditions, and with information about specific contaminant transport parameters (e.g., for partitioning), estimates of contaminant transport can be made and used to support remedy decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Decision Points and Practical Considerations for AI Projects

In this presentation, I will present business-relevant decisions, risks, and considerations for practical implementations of AI projects. I will use energy efficiency and renewable energy AI projects at NREL as examples and case-studies highlighting the journey from concept to implementation. First, I present challenges, questions, and trade-offs related to system inputs: the data. Next, I will examine issues with system behavior and trust, presenting examples, risks, and mitigation strategies. Finally, I will discuss challenges to effective widespread deployment of AI systems including energy, compute, and time requirements.

AI↗

The Cybersecurity Value-at-Risk Framework: Informing Cybersecurity Decisions

The Cybersecurity Value-at-Risk Framework is a tool that can be used by hydropower plant manager to make more educated cybersecurity investments. Users can take a self guided assessment allowing the tools to generate risk, impact and cybersecurity scores and be given risk-based recommendations to enhance decision-making.

CVF↗

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant (Presentation)

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizable. To address this challenge, this study aims to develop a financial model that quantifies the risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of value at risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and assess the potential reduction in investor risk exposure. This paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verifying the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. This paper’s results present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizeable. To address this challenge, this study aims to develop a financial model that quantifies risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of Value at Risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and to assess the potential reduction in investor risk exposure. The paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verification of the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. The results of this paper present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Perceptions of Radiation Oncologists and Urologists on Sources and Type of Evidence to Inform Prostate Cancer Treatment Decisions

Purpose: To perform a national survey of radiation oncologists and urologists about the type of resources used and the level of evidence needed to change clinical practice in localized prostate cancer. Methods and Materials: From a random sample, 1422 physicians were mailed a survey assessing the types of information used and what level of evidence could alter their clinical practice in prostate cancer. Multivariable logistic regression models were used to identify differences in physician characteristics for each outcome. Results: Survey response rates were similar for radiation oncologists and urologists (44% vs 46%; P=.46). Specialty-specific journals represented the most commonly used resource for informing the clinical practice for radiation oncologists (65%) and urologists (70%). Relative to radiation oncologists, urologists were less likely to report utilizing top-tier medical journals (25% vs 39%; adjusted odds ratio [OR] 0.50; P=.01) or cancer journals (22% vs 51%; adjusted OR 0.50; P<.001) but more likely to rely on clinical guidelines (46% vs 38%; adjusted OR 1.6; P=.006). Both radiation oncologists and urologists most commonly reported large randomized, clinical trials as the level of evidence to change treatment recommendations for localized prostate cancer (85% vs 77%; P=.009). Conclusions: Both specialties rely on their own specialty-specific journals and view randomized, clinical trials as the level of evidence needed to change clinical practice. Our study provides a context on meaningful ways of disseminating evidence for localized prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimal decision-making in high-throughput virtual screening pipelines

Screening large pools of molecular candidates to identify those with specific design criteria or targeted properties is demanding in various science and engineering domains. While a high-throughput virtual screening (HTVS) pipeline can provide efficient means to achieving this goal, its design and operation often rely on experts' intuition, potentially resulting in suboptimal performance. In this paper, we fill this critical gap by presenting a systematic framework that can maximize the return on computational investment (ROCI) of such HTVS campaigns. Based on various scenarios, we empirically validate the proposed framework and demonstrate its potential to accelerate scientific discoveries through optimal computational campaigns, especially in the context of virtual screening.

97 MATHEMATICS AND COMPUTING↗

Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bacterial decision making

Stochastic fluctuations in the expression of genes allow a cell to exhibit a kind of free will.

60 APPLIED LIFE SCIENCES↗

Efficient Decision Trees for Tensor Regressions

Here, we proposed the tensor-input tree (TT) method for scalar-on-tensor and tensor-on-tensor regression problems. We first address scalar-on-tensor problem by proposing scalar-output regression tree models whose input variables are tensors (i.e., multi-way arrays). We devised and implemented fast randomized and deterministic algorithms for efficient fitting of scalar-on-tensor trees, making TT competitive against tensor-input GP models (Yu, Li, and Liu; Sun et al.). Based on scalar-on-tensor tree models, we extend our method to tensor-on-tensor problems using additive tree ensemble approaches. Theoretical justification and extensive experiments, including testing robustness to entrywise input tensor noise, are provided on real and synthetic datasets to illustrate the performance of TT. Our implementation is provided at https://github.com/hrluo/TensorDecisionTreeRegressor. Supplementary materials for this article are available online.

Decision tree regressions↗

An Informative Interpretation of Decision Theory: The Information Theoretic Basis for Signal-to-Noise Ratio and Log Likelihood Ratio

The signal processing concept of signal-to-noise ratio (SNR), in its role as a performance measure, is recast within the more general context of information theory, leading to a series of useful insights. Establishing generalized SNR (GSNR) as a rigorous information theoretic measure inherent in any set of observations significantly strengthens its quantitative performance pedigree while simultaneously providing a specific definition under general conditions. This directly leads to consideration of the log likelihood ratio (LLR): first, as the simplest possible information-preserving transformation (i.e., signal processing algorithm) and subsequently, as an absolute, comparable measure of information for any specific observation exemplar. Furthermore, the information accounting methodology that results permits practical use of both GSNR and LLR as diagnostic scalar performance measurements, directly comparable across alternative system/algorithm designs, applicable at any tap point within any processing string, in a form that is also comparable with the inherent performance bounds due to information conservation.

97 MATHEMATICS AND COMPUTING↗