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RELAP5-3D Developmental Assessment: Comparison of Versions 4.1.3is and 4.0.3is

Figures have been generated comparing the parameters used in the developmental assessment of the RELAP5-3D code using versions 4.1.3is and 4.0.3is. The figures, which are the same as those used in Volume III of the RELAP5-3D code manual, compare calculations using the semi-implicit solution scheme with available experiment data. These figures provide a quick, visual indication of how the code predictions changed between these two code versions and can be used to identify cases in which the assessment judgment may need to be changed in Volume III of the code manual. Changes to the assessment judgments made after reviewing all of the assessment cases are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RELAP5-3D Developmental Assessment: Comparison of Versions 4.2.1i and 4.1.3i

Figures have been generated comparing the parameters used in the developmental assessment of the RELAP5-3D code using versions 4.2.1i and 4.1.3i. The figures, which are the same as those used in Volume III of the RELAP5-3D code manual, compare calculations using the semi-implicit solution scheme with available experiment data. These figures provide a quick, visual indication of how the code predictions changed between these two code versions and can be used to identify cases in which the assessment judgment may need to be changed in Volume III of the code manual. Changes to the assessment judgments made after reviewing all of the assessment cases are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RELAP5-3D Developmental Assessment: Comparison of Versions 4.3.4i and 4.2.1i

Figures have been generated comparing the parameters used in the developmental assessment of the RELAP5-3D code using versions 4.3.4i and 4.2.1i. The figures, which are the same as those used in Volume III of the RELAP5-3D code manual, compare calculations using the semi-implicit solution scheme with available experiment data. These figures provide a quick, visual indication of how the code predictions changed between these two code versions and can be used to identify cases in which the assessment judgment may need to be changed in Volume III of the code manual. Changes to the assessment judgments made after reviewing all of the assessment cases are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States

This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption - such as increased productivity or expanded value streams enabled by electric and/or grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption in all major sectors - transportation, commercial and residential buildings, and industry - and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption, such as increased productivity or expanded value streams enabled by electric and grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.

2050↗

Research Technology Laboratory (RTL) Disposition Program Final Status Survey Report

As part of the Battelle Facility Restoration Program (Smoter and Biebesheimer 2017), the Research Technology Laboratory (RTL) Complex was remediated through demolition and surveyed to show it meets the radiological release criteria for unrestricted use under the clearance process (DOE 2011). The restoration program has directed the implementation of the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) methodology (NRC 2011) to verify the suitability of the site to be released for unrestricted use under the clearance process in U.S. Department of Energy (DOE) Order 458.1 (Biebesheimer 2018a; DOE 2011). The use of MARSSIM is accepted by federal and state agencies, including DOE. This report documents how the MARSSIM process was used to assure any residual radioactivity is within acceptable levels and as low as reasonably achievable. Past land use for the RTL Complex property included agricultural, residential, and industrial activity. The historical site assessment (HSA) (Lindenmeier et al. 2015; Biebesheimer 2018b) identified use of radionuclides in past RTL Complex research and development activities from commissioning in 1966 until it was vacated in 2017. Based on the information provided in the HSA, the RTL Complex was delineated into six survey units. The 520 building footprint, tank vault and 530 building footprint, other building footprints, and pipeline survey units included excavated areas. The paved areas and open areas survey units were unexcavated areas. Survey units were all determined to be Class 3, with low probability of containing residual radioactivity, after demolition of the structures within the RTL Complex. The Research Technology Laboratory (RTL) Disposition Program: Final Status Survey Plan (Bunn et al. 2018) was designed and conducted to provide quantitative data regarding the residual radioactivity present in each survey unit. Authorized radiological release limits were developed and approved by the DOE Office of Science in December 2016 (DOE 2017). Fourteen random sample locations were identified within each survey unit. Forty-four specific judgmental sample locations were selected across the site based on information in the HSA. The number of sample locations within a survey unit ranged from 15 to 28, for a total of 127 random and judgmental sample locations identified across the RTL Complex. Sampling for the final status survey occurred over 12 days between November 11 and December 7, 2018. Laboratory results were independently validated by Analytical Quality Associates prior to evaluation. All of the over 880 residual radioactivity measurements were less than the release limits and action levels established through the RTL Disposition Program. A sum of fractions calculation for each survey unit resulted in values that were less than unity. Based on the results presented in this report, the restoration program recommends that the RTL Complex be released for unrestricted use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Psychosocial and Cultural Modeling in Human Computation Systems: A Gamification Approach

“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural biases on human judgment can be curtailed through collaborative and competitive reasoning. By reducing biases on human judgment, gamification allows human computation systems to exploit human creativity relatively unhindered by human error. Operationally, gamification uses simulation to harvest human behavioral data that provide valuable insights for the solution of real-world problems.

Sanfilippo, Antonio P.↗

A paradigm shift - the key to optimal, defensible and transparent waste management, disposal and remediation decisions - 15236

Current methods for structuring nuclear waste management, disposal, and remediation decisions are subject to three major limitations. First, they are based on a series of extraordinarily conservative assumptions. The dominant way of thinking is that, for example, conservative models yield better, safer decisions. Second, they lack methods to meaningfully address and incorporate the 'human dimension'. The dominant way of thinking is that the current approach is sufficient to bring together the values and interests of both internal and external stakeholders in making a decision. And third, they lack a formal method through which both internal and external stakeholders are encouraged collectively to 'think through' complex problems that contain multiple competing objectives so that wise, socially acceptable, and scientifically-defensible decisions are made. To overcome these limitations, a paradigm shift is needed towards a holistic, integrated approach to structure nuclear waste management, disposal and remediation decisions. The first requirement of this paradigm shift is the realization and recognition that the problems faced are decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Decision analysis, very simply, is formalized common sense. The reason it is needed for complex problems is that there are too many moving parts (variables) for humans to manage with out the formalism. Decision analysis leads to addressing problem solving using a combination of a science-based model and a costs/values model. Expectation ('realism') and uncertainty are addressed in the science-based models, whereas stakeholder values, preferences, and desires are addressed when modeling costs and value judgments. Science-based modeling tools have been developed, improved, and used since the current regulatory setting was introduced about 30 years ago. However, modeling of costs and value judgments has not often been addressed using any formal approach, despite the openings that exist in regulations (e.g., CERCLA's modifying criteria and the concept of 'as low as reasonably achievable' referenced in DOE Orders). A discussion of the need and rationale for this paradigm shift is presented, followed by a description of the technical basics of this approach to decision modeling, and ending with an explanation of the steps that are taken in this approach to structured decision-making. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is introduced that supports this paradigm shift. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Paradigm Shift continued: An Application of Structured Decision Making for Sustainable Waste Management - 16486

Structured decision making presents an opportunity for DOE and others engaged in solving complex environmental and waste management problems to find solutions that are stakeholder engaged and cost effective. This approach represents a paradigm shift that was introduced in a series of papers and a panel session at the WM2015 Symposium. The advantages of structured decision making over less formal approaches to decision making include technical defensibility, traceability and transparency. Structured decision making also overcomes the limitations of misapplication of conservatism in modeling, addresses stakeholder concerns and competing objectives directly, and provides a formal method through which internal and external stakeholders are encouraged to collectively and carefully consider all relevant attributes of solving complex problems. The first requirement of this paradigm shift is a realization and recognition that the problems faced are inherently decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Structured decision making is, very simply, formalized common sense. The formalities include: framing the problem; identification of objectives and measures for valuing those objectives; costs or values associated with those objectives; management options or alternatives for taking action that are tied directly to the objectives; and, science-based models to evaluate the options. Decision analysis is used to evaluate objectives and choose management options by balancing probability and consequence. The science-based models are built probabilistically based on expectation and uncertainty, and costs and value judgments are used to fulfill addressing stakeholder concerns. Consequently, this approach avoids misplaced conservatism in science-based modeling and properly places values in the objectives component of a decision model. This approach honestly addresses uncertainty and value judgments and balances these competing components to find the most effective decision. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is used to support an application of this paradigm shift towards structured decision making. In this application objectives and management options for a waste disposal problem at the Los Alamos National Laboratory are identified, and features, events and processes are described and defined to form the basis of a conceptual site model. This establishes the decision model structure. Objectives are addressed through the three pillars of sustainability - economic, environmental, and social - and also address regulatory concerns or constraints. Management options include removal of waste to another location and engineering designs for leaving waste in place. Using structured decision making, the relationship between objectives, management options, and the conceptual site model is made clear, and leads to a comprehensive, defensible, transparent and traceable approach to effective decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Inverse Uncertainty Quantification of Reactor Simulation with Polynomial Chaos Surrogate Model

Reliable uncertainty quantification (UQ) and sensitivity analysis (SA) is significant part of modelling and simulation. This is particularly important in the nuclear community due to the fact that the licensing of nuclear installations has shifted from conservative to Best Estimate plus Uncertainty (BEPU) methodologies. UQ can be broadly classified as forward UQ and inverse UQ. Forward UQ is the process of quantifying the uncertainties in simulation outputs by propagating the uncertainties in input parameters. It requires knowledge in the input uncertainty, which is often specified by ad-hoc expert judgment which lacks mathematical rigor. The inverse UQ is the process to determine the uncertainty in input parameters given observations of the output. The purpose of this paper is to replace such ad-hoc expert judgment of the statistical properties of input model parameters in nuclear reactor simulation. This summary presents work on inverse UQ of a nonlinear Point Reactor Kinetics Equations - lumped thermal-hydraulics parameter coupled problem. Bayesian inference and Markov Chain Monte Carlo (MCMC) are used for the inverse UQ. Because MCMC requires a large number of simulations which is impractical for models that are computationally expensive, surrogate models is constructed by generalized Polynomial Chaos (PC) expansion technique. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Stakeholder-Engaged Structured Decision Making for the Los Alamos Legacy Cleanup Mission - 20501

The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multifunctional skin-like electronics for quantitative, clinical monitoring of cutaneous wound healing

Non-invasive, biomedical devices have the potential to provide important, quantitative data for the assessment of skin diseases and wound healing. Traditional methods either rely on qualitative visual and tactile judgments of a professional and/or data obtained using instrumentation with forms that do not readily allow intimate integration with sensitive skin near a wound site. In this paper, an electronic sensor platform that can softly and reversibly laminate perilesionally at wounds to provide highly accurate, quantitative data of relevance to the management of surgical wound healing is reported. Clinical studies on patients using thermal sensors and actuators in fractal layouts provide precise time-dependent mapping of temperature and thermal conductivity of the skin near the wounds. Analytical and simulation results establish the fundamentals of the sensing modalities, the mechanics of the system, and strategies for optimized design. The use of this type of “epidermal” electronics system in a realistic clinical setting with human subjects establishes a set of practical procedures in disinfection, reuse, and protocols for quantitative measurement. Finally, the results have the potential to address important unmet needs in chronic wound management.

60 APPLIED LIFE SCIENCES↗

Modeling golden eagle‐vehicle collisions to design mitigation strategies

ABSTRACT The incidental take of golden eagles ( Aquila chrysaetos ) as a result of wind energy development requires some form of compensatory mitigation. Although several options have been proposed, only one has been formerly accepted and implemented, and the lack of options can limit the permit process for wind facilities. We developed a model to estimate numbers of golden eagles that die when struck by vehicles when eagles scavenge road kill to evaluate removal of road‐killed carcasses as an additional mitigation option. Our model estimates vehicle collision rates as a function of eagle densities, road traffic volume, and animal carcass abundance at the scale of a Wyoming, USA, county during fall‐winter, and quantifies the effects of different mitigation strategies, including estimates of uncertainty. We evaluated the plausibility of our model estimates by predicting mortality rates for each county in Wyoming and comparing overall state mortality to current estimates of mortality using derived estimates from expert judgment. We also developed a context‐dependent analysis of potential mitigation credits controlling for carcass number, traffic volume, and background carcass removals. We found that mitigation credit should be highest in areas with greatest number of carcasses. Collision mitigation is a potentially useful addition to the mitigation toolbox for wind energy development or other activities that need to offset predicted golden eagle mortality and satisfy incidental take permit requirements. © 2018 The Authors. Journal of Wildlife Management Published by Wiley Periodicals, Inc.

Lonsdorf, Eric↗

Quantitative metrics for assessment of chemical image quality and spatial resolution

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest in an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗

Quantifying the sensitivity of ephemeral streams to land disturbance activities in arid ecosystems at the watershed scale

Large areas of public lands administered by the Bureau of Land Management and located in arid regions of the southwestern United States are being considered for the development of utility-scale solar energy facilities. Land-disturbing activities in these desert, alluvium-filled valleys have the potential to adversely affect the hydrologic and ecologic functions of ephemeral streams. Regulation and management of ephemeral streams typically falls under a spectrum of federal, state, and local programs, but scientifically based guidelines for protecting ephemeral streams with respect to land-development activities are largely nonexistent. This study developed an assessment approach for quantifying the sensitivity to land disturbance of ephemeral stream reaches located in proposed solar energy zones (SEZs). The ephemeral stream assessment approach used publicly-available geospatial data on hydrology, topography, surficial geology, and soil characteristics, as well as highresolution aerial imagery. These datasets were used to inform a professional judgment-based score index of potential land disturbance impacts on selected critical functions of ephemeral streams, including flow and sediment conveyance, ecological habitat value, and groundwater recharge. The total sensitivity scores (sum of scores for the critical stream functions of flow and sediment conveyance, ecological habitats, and groundwater recharge) were used to identify highly sensitive stream reaches to inform decisions on developable areas in SEZs. Total sensitivity scores typically reflected the scores of the individual stream functions; some exceptions pertain to groundwater recharge and ecological habitats. The primary limitations of this assessment approach were the lack of high-resolution identification of ephemeral stream channels in the existing National Hydrography Dataset, and the lack of mechanistic processes describing potential impacts on ephemeral stream functions at the watershed scale.The primary strength of this assessment approach is that it allows watershed-scale planning for low-impact development in arid ecosystems; the qualitative scoring of potential impacts can also be adjusted to accommodate new geospatial data, and to allow for expert and stakeholder input into decisions regarding the identification and potential avoidance of highly sensitive stream reaches.

Arid ecosystems↗

Challenge clusters facing LCA in environmental decision-making—what we can learn from biofuels

Purpose: Bioenergy is increasingly used to help meet greenhouse gas (GHG) and renewable energy targets. However, bioenergy’s sustainability has been questioned, resulting in increasing use of life cycle assessment (LCA). Bioenergy systems are global and complex, and market forces can result in significant changes, relevant to LCA and policy. The goal of this paper is to illustrate the complexities associated with LCA, with particular focus on bioenergy and associated policy development, so that its use can more effectively inform policymakers. Methods: The review is based on the results from a series of workshops focused on bioenergy life cycle assessment. Expert submissions were compiled and categorized within the first two workshops. Over 100 issues emerged. Accounting for redundancies and close similarities in the list, this reduced to around 60 challenges, many of which are deeply interrelated. Some of these issues were then explored further at a policy-facing workshop in London, UK. The authors applied a rigorous approach to categorize the challenges identified to be at the intersection of biofuels/bioenergy LCA and policy. Results and discussion: The credibility of LCA is core to its use in policy. Even LCAs that comply with ISO standards and policy and regulatory instruments leave a great deal of scope for interpretation and flexibility. Within the bioenergy sector, this has led to frustration and at times a lack of obvious direction. This paper identifies the main challenge clusters: overarching issues, application and practice and value and ethical judgments. Many of these are reflective of the transition from application of LCA to assess individual products or systems to the wider approach that is becoming more common. Uncertainty in impact assessment strongly influences planning and compliance due to challenges in assigning accountability, and communicating the inherent complexity and uncertainty within bioenergy is becoming of greater importance. Conclusions: The emergence of LCA in bioenergy governance is particularly significant because other sectors are likely to transition to similar governance models. LCA is being stretched to accommodate complex and broad policy-relevant questions, seeking to incorporate externalities that have major implications for long-term sustainability. As policy increasingly relies on LCA, the strains placed on the methodology are becoming both clearer and impedimentary. The implications for energy policy, and in particular bioenergy, are large.

09 BIOMASS FUELS↗

Integrated Approach to Density-Based Spatial Clustering of Applications with Noise and Dynamic Time Warping for Breakout Prediction in Slab Continuous Casting

Mold breakout is a catastrophic accident that has serious impacts on smooth production, slab quality, and caster equipment. Accurate identification and prediction of an impending breakout are always top priorities in continuous casting operations. In view of crucial common features of mold copper plate temperatures during a breakout, such as time lag and space inversion, the concepts of density-based spatial clustering of applications with noise and dynamic time warping are introduced, and an integrated novel method for breakout prediction is developed. Through extracting and fusing the representative singularity and approximation of temperature variation, the typical temporal and spatial temperature characteristics during breakout can be distinguished and predicted accurately. Compared with traditional methods of logical judgment and artificial neural network, the method based on clustering does not need to modify forecast thresholds or parameters artificially, which overcomes the limitation of model dependence on human beings, and demonstrates excellent adaptability and robustness for online abnormality prevention.

36 MATERIALS SCIENCE↗

The Onco-cardiologist Dilemma: to Implant, to Defer, or to Avoid Transcatheter Aortic Valve Replacement in Cancer Patients with Aortic Stenosis?

Purpose of Review: Aging is associated with an increased prevalence of both cancer and heart disease. The progression of aortic valve calcification to aortic stenosis may be accelerated by both cardiovascular risk factors and cancer treatments, such as radiotherapy with mediastinal involvement. Symptomatic aortic stenosis is occasionally diagnosed in cancer patients undergoing cardiovascular evaluation; likewise, cancer is often recognized during assessment preceding aortic valve interventions. In these complex cases, physicians face difficult treatment decisions. Due to a myriad of clinical presentations of cancer and valve disease, specific guidelines for this patient population are not currently in place. Management is currently based on clinical judgment, on an individual basis. Recent Findings: Patients with cancer in remission or with a favorable prognosis should be treated according to current cardiovascular guidelines. In these patients, aortic valve replacement can be performed either by surgery or transcatheter. Significant challenges arise in patients with active cancer, especially those receiving anti-cancer treatment. Recent data suggests that these patients can be offered aortic valve replacement, with a trend of favoring the transcatheter route in order to minimize perioperative risk and complications associated with major surgery. Patients with advanced cancer and severe aortic stenosis should be offered palliative care and can benefit from aortic balloon valvuloplasty if indicated. Modern cancer treatments associated with improved long-term prognosis may allow the appropriate cure of aortic stenosis. Summary: We discuss the protocol, outcomes, and evolving recommendations of aortic valve replacement in cancer patients with aortic stenosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗