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Numerical and experimental analysis of an in-scale masonry cross-vault prototype up to failure

A heterogeneous full 3D non-linear FE approach is validated against experimental results obtained on an in-scale masonry cross vault assembled with dry joints, and subjected to various loading conditions consisting on imposed displacement combinations to the abutments. The FE model relies into a discretization of the blocks by means of few rigid-infinitely resistant parallelepiped elements interacting by means of planar four-noded interfaces, where all the deformation (elastic and inelastic) occurs. The investigated response mechanisms of vault are the shear in-plane distortion and the longitudinal opening and closing mechanism at the abutments. After the validation of the approach on the experimentally tested cross-vault, a sensitivity analysis is conducted on the same geometry, but in real scale, varying mortar joints mechanical properties, in order to furnish useful hints for safety assessment, especially in presence of seismic action.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IAEA Initiatives that Integrate Stakeholders, Models and Decision Making - 18646

The International Atomic Energy Agency (IAEA) has initiated an effort to provide stakeholder support services as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) programs. The intent of this sub-group of CIDER II is to provide members states support in areas of stakeholder communication, engagement and participation, with the goal of building trust in decommissioning and environmental remediation (D and ER) decisions for radioactive contamination and facilities. IAEA has also initiated a follow-on effort to address Modeling and Data for Radiological Impact Assessments (MODARIA II), which is aimed at enhancing the capabilities of Member States to simulate radionuclide transfer in the environment, and to ensure appropriate levels of protection from ionizing radiation. Working Group 1 of MODARIA II is focused on the integration of modeling and decision analysis. These two groups have complementary and supporting objectives, which provides an opportunity for collaboration and mutual benefit. The technical integrator is the approach of structured decision making, which follows a five-step process that combines stakeholder values with models through a technically defensible decision analysis. Briefly, the steps are: 1. Provide the context and decision context for the problem; 2. Obtain costs, values and concerns from stakeholders, to develop objectives that need to be achieved (e.g., improve human health, minimize costs, increase jobs); 3. Identify options that might achieve the objectives (e.g., cleanup, institutional controls, education); 4. Develop probabilistic models that connect options to objectives so that the objectives can be evaluated collectively (e.g., a fate and transport and risk model to address the objective of reducing human health risk, a cost model to address costs of taking action); and, 5. Model evaluation, including sensitivity analysis, to determine if an action can be taken with sufficient certainty, or if collection of more data is needed to decrease uncertainty before a decision is made. This approach also supports adaptive management as new data are collected. This approach clarifies the roles of stakeholders and subject matter experts in the decision-making process, where stakeholders specify values, and subject matter experts focus on the models that are needed to evaluate the options. It also provides a technically defensible, reproducible, transparent and traceable approach to all of the components necessary to properly solve the types of complex decision problems that plague radioactive waste management, decommissioning and environmental remediation. This paper introduces the major challenges to implementing such a broad scale of decision analysis, and approaches to overcoming those challenges, which include not only the technical challenges, but also the need to develop capacity in a range of skills not usually accommodated in environmental modeling and includes the need for the IAEA to address decision making in different countries, and with different cultures, religions, political affiliations, and languages. This paper explores the potential for IAEA to benefit from both the CIDER II and MODARIA II programs, and hence to develop a fully integrated approach to effective decision making for radioactive waste management and environmental remediation. Note that there are many people involved in these efforts at the IAEA, and credit belongs to those people for the progress that has been made to date. Our intent here is simply to introduce these IAEA programs at the WM2018 Symposium to provide our perspective and some awareness of some of the directions in which IAEA appears to be headed regarding stakeholder engagement, environmental and risk modeling, data science, and decision analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Modeling Total Dissolved Gas for Optimal Operation of Multireservoir Systems

One important environmental issue of hydropower in the Columbia and Snake River Basins (Pacific Northwest region of United States) is elevated total dissolved gas (TDG) downstream of a dam, which has the potential to cause gas bubble disease in affected fish. Gas supersaturation in the Columbia River Basin primarily occurs due to dissolution of bubbles entrained during spill events. This paper presents a physically based TDG model that can be used to optimize spill operations in multireservoir hydropower systems. Independent variables of the model are forebay TDG, tailwater elevation, spillway and powerhouse discharges, project head, and environmental parameters such as temperature and atmospheric pressure. The model contains seven physically meaningful experimental parameters, which were calibrated and validated against TDG data collected downstream of Rock Island Dam (Washington) from 2008 to 2012. In conclusion, a sensitivity analysis was performed to increase the understanding of the relationships between TDG downstream of the dam and processes such as air entrainment, lateral powerhouse flow, and dissolution.

13 HYDRO ENERGY↗

Influence of emitter ring manufacturing tolerances on electron beam quality of high power gyrotrons

A sensitivity analysis of manufacturing imperfections and possible misalignments of the emitter ring in the gyrotron cathode structure on the electron beam quality has been performed. It has been shown that a possible radial displacement of the emitter ring of the order of few tens of microns can cause dramatic effects on the beam quality and therefore the gyrotron operation. Two different design approaches are proposed in order to achieve an electron beam which is less sensitive to manufacturing imperfections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Individualized Positron Emission Tomography–Based Isotoxic Accelerated Radiation Therapy Is Cost-Effective Compared With Conventional Radiation Therapy: A Model-Based Evaluation

Purpose: To evaluate long-term health effects, costs, and cost-effectiveness of positron emission tomography (PET)-based isotoxic accelerated radiation therapy treatment (PET-ART) compared with conventional fixed-dose CT-based radiation therapy treatment (CRT) in non-small cell lung cancer (NSCLC). Methods and Materials: Our analysis uses a validated decision model, based on data of 200 NSCLC patients with inoperable stage I-IIIB. Clinical outcomes, resource use, costs, and utilities were obtained from the Maastro Clinic and the literature. Primary model outcomes were the difference in life-years (LYs), quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness and cost/utility ratio (ICER and ICUR) of PET-ART versus CRT. Model outcomes were obtained from averaging the predictions for 50,000 simulated patients. A probabilistic sensitivity analysis and scenario analyses were carried out. Results: The average incremental costs per patient of PET-ART were €569 (95% confidence interval [CI] €−5327-€6936) for 0.42 incremental LYs (95% CI 0.19-0.61) and 0.33 QALYs gained (95% CI 0.13-0.49). The base-case scenario resulted in an ICER of €1360 per LY gained and an ICUR of €1744 per QALY gained. The probabilistic analysis gave a 36% probability that PET-ART improves health outcomes at reduced costs and a 64% probability that PET-ART is more effective at slightly higher costs. Conclusion: On the basis of the available data, individualized PET-ART for NSCLC seems to be cost-effective compared with CRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

14 SOLAR ENERGY↗

The Prompt Fission Neutron Spectrum: From Experiment to the Evaluated Data and its Impact on Critical Assemblies

After a brief introduction concerning nuclear data, prompt fission neutron spectrum (PFNS) evaluations and the limited PFNS covariance data in the ENDF/B-VII library, and the important fact that cross section uncertainties ~ PFNS uncertainties, the author presents background information on the PFNS (experimental data, theoretical models, data evaluation, uncertainty quantification) and discusses the impact on certain well-known critical assemblies with regard to integral quantities, sensitivity analysis, and uncertainty propagation. He sketches recent and ongoing research and concludes with some final thoughts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Benchmarking FFTF LOFWOS Test# 13 using SAM code: Baseline model development and uncertainty quantification

The development and deployment of advanced reactors, such as the sodium-cooled fast reactor (SFR), relies on sophisticated modeling tools to ensure the safety of the design under various transients. The predictive capability of these advanced modeling tools requires validation to garner trust in supporting the licensing of the advanced reactors. For this reason, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13.In this study, we present and discuss the benchmarking efforts of the modern system code SAM on the FFTF LOFWOS Test #13. Further, the SAM baseline model was developed according to the benchmark specification, which included a detailed core model with reactivity feedback. Generally, good agreement was observed between the baseline results and benchmark measurements; however, discrepancies persisted, particularly in predicted fuel assembly coolant outlet temperatures. Utilizing the baseline model, uncertainty quantification (UQ) and sensitivity analysis (SA) were conducted with the assistance of various statistical learning and machine learning methods, including kernel density estimation, Gaussian processes, and Sobol indices. Following the baseline model prediction and UQ and SA results, we discuss the reasons for the simulation discrepancies and propose further improvements to the model. This benchmarking effort adheres to the best-estimate plus uncertainty approach and can serve as a valuable example for supporting risk-informed licensing of advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Spatially localized measurement of thermal conductivity using a hybrid photothermal technique

A photothermal technique capable of measuring thermal conductivity with micrometer lateral resolution is presented. This technique involves measuring separately the thermal diffusivity, D, and thermal effusivity, e, to extract the thermal conductivity, k=(e2/D)1/2. To generalize this approach, sensitivity analysis was conducted for materials having a range of thermal conductivities. Experimental validation was sought using two substrate materials, SiO2 and CaF2, both coated with thin titanium films. The measured conductivities compare favorably with literature values.

36 MATERIALS SCIENCE↗

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant At or Near Delayed Critical

The derivation of a non-invasive prompt neutron decay constant sensitivity coefficient is provided in this work. The computation of the sensitivity coefficient derived in this work does not require modification of Monte Carlo source code and is based on capabilities available in Monte Carlo N-Particle R© Code Version 6.2. The prompt neutron decay constant sensitivity coefficients are calculated for 44-group and 252-group energy structures for specific nuclide-reaction pairs in the Jezebel benchmark experiment. The nuclide-reaction pairs investigated in this work include Pu- 239(n,f), Pu-240(n,f), and Pu-241(n,f). Physical explanations of the sensitivity profiles exhibited by the 252-group energy structure are investigated for the prompt neutron multiplication factor, mean neutron lifetime, and prompt neutron decay constant. The prompt neutron decay constant sensitivity coefficients calculated for the 44-group and 252-group energy structure of Pu-239(n,f) are compared. Lastly, the 44-group energy structure sensitivity coefficients calculated are used for nuclear-data induced uncertainty quantification of the neutron multiplication factor. This work shows that a reduction in the nuclear data-induced uncertainty of the neutron multiplication factor is possible for all nuclide-reaction pairs investigated when prompt neutron decay constant sensitivity coefficients are utilized. This is important for new critical experiment design optimization studies of measurement configurations. This work provides a basis for more detailed sensitivity analysis and uncertainty quantification of nuclide, reaction, and energy-specific cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced simulation capability for environmental management, integrated tool-sets and simulator to enhance public communication - 15186

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater Remediation, is supporting multi-laboratory development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. ASCEM facilitates transparent, efficient and integrated approaches to modeling and site characterization, and provides robust and standardized assessments of performance and risk for EM cleanup and closure activities. Site subsurface simulation modeling and performance assessments are complex and involve sensitivity evaluations and uncertainty quantification to better understand the risks at a site. The ASCEM tool-set was designed in close collaboration with the sites and other potential end-users (both the public and regulators) to allow better communication and understanding of these complex modeling efforts. ASCEM's integrated tool-sets provide a user interface and tools for managing work-flows, including conceptual model development, management of data and metadata for model input, sensitivity analysis, model calibration and uncertainty analysis, model execution on diverse computational platforms, and processing of model output, including visualization. The hierarchical and modular design of ASCEM HPC simulator Amanzi easily lends itself to translating this conceptual model of a site into a numerical model that can easily be spatially and temporally discretized to run on the HPC simulator. Together this integrated work-flow allows for a seamless and integrated analysis tracking all provenance information and modeling uncertainties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Disposition of Hanford Tank Waste sludge from tank 241-AY-102 and the 241-Aa/241-AX farm tanks - 15298

WRPS must retrieve the waste from double-shell tank 241-AY-102 and the single-shell tanks in the 241A and -AX Tank Farms, while finishing the ongoing retrieval of tanks in the 241-C Tank Farm. Given the limited availability of double-shell tank space, the challenge is to identify an optimum combination of double-shell tanks that can safely and efficiently serve as receiver tanks for the combined inventory of sludge wastes from these source tanks. A multiple-criteria, weighted-sum decision-making process, in conjunction with sensitivity analysis and a Pareto evaluation, was used to determine the optimum set of receiver tanks. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Eigensensitivity analysis of subgrid-scale stresses in large-eddy simulation of a turbulent axisymmetric jet

The study of complex turbulent flows by means of large-eddy simulation approaches has become increasingly popular in many scientific and engineering applications. The underlying filtering operation of the approach enables to significantly reduce the spatial and temporal resolution requirements by means of representing only large-scale motions. However, the small-scale stresses and their effects on the resolved flow field are not negligible, and therefore require additional modeling. As a consequence, the assumptions made in the closure formulations become potential sources of model-form uncertainty that can impact the quantities of interest. The objective of this work, thus, is to perform a model-form sensitivity analysis in large-eddy simulations of an axisymmetric turbulent jet following an eigenspace-based strategy recently proposed. The approach relies on introducing perturbations to the decomposed subgrid-scale stress tensor within a range of physically plausible values. These correspond to discrepancy in magnitude (trace), anisotropy (eigenvalues) and orientation (eigenvectors) of the normalized, small-scale stresses with respect to a given tensor state, such that propagation of their effects can be assessed. As a result, the generality of the framework with respect to the six degrees of freedom of the small-scale stress tensor makes it also suitable for its application within data-driven techniques for improved subgrid-scale modeling.

42 ENGINEERING↗

BioSTEAM-LCA: An Integrated Modeling Framework for Agile Life Cycle Assessment of Biorefineries under Uncertainty

Biorefineries will play a critical role in sustainable bioeconomies, but projections of their environmental impacts vary widely. A core challenge with life cycle assessments (LCAs) of biorefineries is that they are often disconnected from biorefinery design, simulation, and techno-economic analysis (TEA). This lack of integration is a barrier to early stage technology and process evaluations, reducing consistency and transparency across sustainability indicators while limiting our understanding of the relative importance of individual factors (e.g., design decisions, greenhouse gas emission accounting procedures), how these factors interact, and trade-offs or synergies with process economics. In this study, we propose a new agile LCA framework, BioSTEAMLCA, which layers onto BioSTEAM (Biorefinery Simulation and Techno-Economic Analysis Modules, which automates biorefinery design, simulation, and TEA) to characterize the environmental impacts of biorefineries across a landscape of designs, technology performance assumptions, and contexts. Inventory databases and impact assessment methods are integrated to enable flexible user defined LCA system models, and the implications of uncertainties throughout the production system are characterized via Monte Carlo simulation. To demonstrate the capabilities of BioSTEAMLCA, we present a case study for sugarcane ethanol production. Overall, BioSTEAM-LCA enables computationally efficient, agile gate-to-gate LCA to evaluate biorefinery processes, the production of candidate biofuels and bioproducts, and trade-offs among productivity, economics, and environmental impacts under uncertainty.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stakeholder Engaged Structured Decision Making to Improve Performance and Reduce Costs While Protecting Human Health and the Environment - 18645

The objective of the Best Practice is to facilitate a paradigm shift when it comes to approaches to the decision making process for nuclear waste management, disposal, and remediation decisions. The stakeholder-engaged structured decision making (SDM) paradigm shift provides a transparent framework for developing optimal solutions to complex problems (Keeney, 1992, Gregory et al, 2012). This is a deliberative-analytical process. The deliberative side centers on understanding stakeholder concerns and values, and developing objectives while identifying options that may achieve those objectives. SDM is implemented with the aid of computer tools that are aimed specifically at capturing these deliberative aspects of a decision analysis. SDM captures this information in a structured format that allows access to the values, objectives, and options that have been identified to help. Through this approach we achieve transparency, traceability, and reproducibility. The goal of SDM at this stage is to provide a formal structure for capturing and processing deliberative information. The deliberative part sets the stage for the analytical part of SDM. A variety of Subject matter experts (SMEs) are engaged in how to evaluate the options through the objectives. Objectives often include minimizing human health risk and minimizing cost, but in the full scope of a sustainability-based approach to decision making, it can include objectives related to economic, environmental and social issues. Subject matter experts might provide other options for achieving the objectives, but their primary role is to evaluate/model the options to the endpoint defined by the objectives or in other words perform a consequence analysis. The structure of SDM makes it clear exactly what is needed from the SMEs, because the options are identified, and the endpoint (objectives) are defined - evaluations and/or models are needed to connect options to objectives. This consequence analysis completes the evaluation, and directly addresses which of the options is the best option. The same SDM approach to finding the best options can also be used for prioritization and resource allocation. Because all of the information is captured in a formal system with the help of computer tools (a software framework for implementing SDM), the decision models that are developed for an application can be fully evaluated numerically and for the insights gained from using a formal process for managing the multiple factors that need to be considered for complex decisions. This includes uncertainty and sensitivity analysis that can be used to guide the need for further data/information collection if the optimal decision is not adequately supported - that is, if there is insufficient confidence in the decision. Also, this feeds directly into adaptive management therefore if more data/information are collected then the efficacy of the current decision can be evaluated, potentially leading to a change in decisions if warranted. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulation of a main steam line break with steam generator tube rupture using trace

A simulation of the OECD/NEA ROSA-2 Project Test 5 was made with the thermal-hydraulic code TRACE5. Test 5 performed in the Large Scale Test Facility (LSTF) reproduced a Main Steam Line Break (MSLB) with a Steam Generator Tube Rupture (SGTR) in a Pressurized Water Reactor (PWR). The result of these simultaneous breaks is a depressurization in the secondary and primary system in loop B because both systems are connected through the SGTR. Good approximation was obtained between TRACE5 results and experimental data. TRACE5 reproduces qualitatively the phenomena that occur in this transient: primary pressure falls after the break, stagnation of the pressure after the opening of the relief valve of the intact steam generator, the pressure falls after the two openings of the PORV and the recovery of the liquid level in the pressurizer after each closure of the PORV. Furthermore, a sensitivity analysis has been performed to know the effect of varying the High Pressure Injection (HPI) flow rate in both loops on the system pressures evolution. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments

This paper presents the first application of model calibration to neutron multiplicity counting (NMC) experiments for cross-section optimization that is informed by adjoint-based sensitivity analysis (SA) and first-order uncertainty quantification (UQ). We summarize previous work on SA applied to NMC and describe notable modifications and additions. We give the procedure for first-order UQ and Bayesian-inference-based parameter estimation (PE). We then discuss model calibration applied to NMC of a 4.5-kg sphere of weapons-grade, alpha-phase plutonium metal (the BeRP ball) with the nPod neutron multiplicity counter. For the BeRP ball in bare and polyethylene-reflected configurations, we discuss the sensitivity of the first- and second-moment detector responses (i.e., first and second moments of the NMC distribution, respectively) to the cross sections. We describe the sources of uncertainty in the measured and simulated responses. Specifically, uncertainty in the measured responses is due to both random and systematic sources. Uncertainty in the simulated responses is due to the cross-section covariances. We describe in detail the adjustment to the cross sections and cross-section covariances due to the optimization. Due to the contribution of systematic uncertainties to the measured response uncertainties, the adjustment to the cross sections is similar in trend but larger in magnitude compared to that recommended by previous work. We compare the measured responses to responses simulated with nominal and optimized cross sections, demonstrating that the best-estimate cross sections produce simulations of NMC experiments that are more accurate with reduced uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗