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At least 1,387 records · Page 77

RISMC Analysis Framework in Response to Proposed 10 CFR 50.46c Rulemaking

The results obtained from the demonstration calculations indicate that as an automation tool in LOCA analyses, LOTUS has the capability to provide integrated evaluation through seamless interfaces of the data stream in multiple disciplines. With further more development, LOTUS will provide a systematic way to perform uncertainty quantification, sensitivity analysis and risk assessment of the multiple physics involved in the LOCA analysis in response to the proposed 10 CFR 50.46c rulemaking. It can be used to obtain quantitative estimate of design or operational margin loss or gain as well as to assess the impact on LOCA analysis safety metrics associated with various combinations of changes in LOCA analysis inputs. It can also aid plant owners to make decision on evaluating design changes as well as resolving operational issues. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Bistability analysis in mathematical model of M-phase control in Xenopus oocyte extracts

To gain more insight into the molecular mechanism that regulates eukaryotic cell cycle, we propose a modification to an existing Mathematical model of mitosis-promoting factor control in Xenopus oocyte extract. To achieve this, we redirect how cell exits from mitosis using ubiquitin ligase enzyme APCP:Cdc20 which is acting as a modifier in cyclin degradation. We present a modified wiring map using combination of mass action kinetics and Michaelis–Menten kinetics to represent the biochemical processes. This results in a system of non-linear ordinary differential equations. The equilibria of the system were analyzed analytically. Using MPF as a bifurcation parameter, we analytically derived conditions under which bistability can occur in the MPF activation module. We find that for bistability to occur, it is necessary that the rate of phosphorylation of Wee1 must be greater than the rate of its dephosphorylation and that the concentration of MPF must lie in certain range of parameter values. Numerical simulations conducted show that the time taken to exit the cell cycle is shorter than those published in some reports and the sensitivity analysis results suggest that the rate of synthesis of cyclin is the most sensitive parameter in the dynamics of cell cycle. Through numerical experiments, we found new parameter sets that will give rise to bistability in the MPF activation module.

97 MATHEMATICS AND COMPUTING↗

Lyapunov spectrum of the separated flow around the NACA 0012 airfoil and its dependence on numerical discretization

We investigate the impact of numerical discretization on the Lyapunov spectrum of separated flow simulations. The two-dimensional chaotic flow around the NACA 0012 airfoil at a low Reynolds number and large angle of attack is considered to that end. Time, space and accuracy-order refinement studies are performed to examine each of these effects separately. Numerical results show that the time discretization has a small impact on the dynamics of the system, whereas the spatial discretization can dramatically change them. Also, the finite-time Lyapunov exponents associated to unstable modes are shown to be positively skewed, and quasi-homoclinic tangencies are observed in the attractor of the system. The implications of these results on flow physics and sensitivity analysis of chaotic flows are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling Effects of Annealing on Coal Char Reactivity to O 2 and CO 2 , Based on Preparation Conditions

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive computational fluid dynamics (CFD) simulations are valuable tools in evaluating and deploying oxyfuel and other carbon capture technologies, either as retrofit technologies or for new construction. However, accurate predictive combustor simulations require physically realistic submodels with low computational requirements. A recent sensitivity analysis of a detailed char conversion model (Char Conversion Kinetics (CCK)) found thermal annealing to be an extremely sensitive submodel. In the present work, further analysis of the previous annealing model revealed significant disagreement with numerous datasets from experiments performed after that annealing model was developed. The annealing model was accordingly extended to reflect experimentally observed reactivity loss, because of the thermal annealing of a variety of coals under diverse char preparation conditions. The model extension was informed by a Bayesian calibration analysis. In addition, since oxyfuel conditions include extraordinarily high levels of CO 2 , the development of a first-ever CO 2 reactivity loss model due to annealing is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗

Design and analysis of graphene–MoS{sub 2} hybrid layer based SPR biosensor with TiO{sub 2}–SiO{sub 2} nano film for formalin detection: numerical approach

In this paper, a Surface Plasmon Resonance (SPR) biosensor has been numerically developed that used Graphene–MoS{sub 2}–Au–TiO{sub 2}–SiO{sub 2} hybrid structure for the detection of formalin. This developed sensor has been sensed the presence the formalin based on attenuated total reflection (ATR) method by observing the change of “surface plasmon resonance angle-the change of minimum reflectance attributor” and “the resonance frequency characteristics (RFC)-maximum transmittance attributor”. Chitosan has been used as probe sensing medium to accelerate particular reaction with the formalin. Here, graphene is used as biomolecular recognition element because of its high adsorption ability and optical characteristics which helps to improve sensor sensitivity, MoS{sub 2} used for it has larger band gap, high fluroscence quenching ability, higher optical absorption efficiency, TiO{sub 2}–SiO{sub 2} bilayer as the improvement of sensitivity and Gold (Au) as the sharp SPR curve. Numerical results give the impression that the variation of RFC and SPR angle for improper sensing of formalin is quiet negligible that confirms no formalin is detected whereas for proper sensing these change are considerably countable that confirms the detection of formalin. From the sensor sensitivity analysis, owing to add TiO{sub 2}–SiO{sub 2} bilayer with Graphene–MoS{sub 2} Hybrid layer, maximum sensitivity of 85.375% has been numerically resulted. This high sensor performance is for taking advantages of Graphene surface high selectively which detect bio molecular compounds through pi-stacking force, larger work function (5.1 eV) of MoS{sub 2} which allows the high sensitive detection of bio targets and Rich plasmon happens at the TiO{sub 2}–SiO{sub 2} interface.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Environmental life cycle assessment methods applied to amine-ionic liquid hybrid CO 2 absorbents

A hybrid solvent mixture of triethyl(octyl)phosphonium cyanopyrrolide [P2228][2-CNPyr] and aqueous monoethanolamine (MEA) has the potential for absorbing CO 2 from post combustion flue gas. However, previous studies have found that the production of phosphonium based ionic liquids (IL) had significantly higher potential environmental impacts compared to MEA. Literature attributes these higher environmental impacts to the phosphine and phosgene-based intermediates required to produce the phosphonium ion of the ionic liquid. This study proposes a novel synthesis pathway that eliminates the need for phosphine and phosgene intermediates in the production of [P2228][2-CNPyr]. The environmental impacts of producing 1kg of the ionic liquid through this novel synthesis route was evaluated using the TRACI 2.1 methodology within the life cycle assessment (LCA) framework. Additionally, the environmental impacts for the production of 1kg of a hybrid solvent was also evaluated and compared against MEA. The life cycle inventory for the production of the IL and its hybrid solvent were calculated based on the stoichiometry and then scaled up. This study found that the IL and its hybrid solvents had higher environmental impacts among 9 of the 10 environmental impact categories calculated by the TRACI 2.1 methodology, except for the ecotoxicity potential. A sensitivity analysis indicated that these solvents were more sensitive to the assumptions of the material requirements of the phosphonium cation than the overall energy or transportation requirements. Despite this sensitivity, both the solvents demonstrated a lower Ecotoxicity Potential compared to MEA, the rest of the environmental impacts were still found to be higher than that of MEA, thereby underscoring the need to investigate novel synthesis routes for the production of phosphonium cation. The uncertainty analysis performed confirmed the findings that the IL has a higher environmental impact potentials across all categories except ecotoxicity potential. The uncertainty analysis also confirms that the phosphonium cation is a major hotspot in production route of these solvents and a source of uncertainty in the model compared to the anion. Altogether, this study underscores the need for investigating novel green chemistry pathway for the synthesis of phosphonium based ionic liquids, such as [P2228][2-CNPyr], to ensure that the these ILs can be a truly green alternative to MEA by not only offering superior CO₂ capture capacity compared to MEA but also being sustainably produced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of thermal gap conductance using the laser flash method

Thermal gap conductance refers to overall heat conductance through a gas-filled gap as interface thermal resistance between the gas and surface has to be considered. The analysis of new ATR (Advanced Test Reactor) fuel experiments requires experimental data and models for the gap conductance of the cladding/fuel capsule gap, which typically varies from 5 μm to 50 μm and is filled with He at 1-3 atm. Although past research has studied the gap conductance between UO{sub 2} fuel and Zircaloy cladding, new experiments are needed to provide the gap conductance data between HT9 and stainless steel 316, and between advanced fuels and advanced cladding in the Accident Tolerant Fuels program. In this paper, the laser flash method is modified to measure the gap conductance. The gap is formed by welding two stainless steel 316 disks with three spacers. The temperature at the rear surface, after exposure to the laser pulse at the front surface, is modeled with 1D heat transfer through three layers. The analytic solution is then fitted with the measured temperature to determine gap conductance. The sensitivity analysis based on the 1D assumption and 3D numerical simulations were performed to assess the sensitivity and uncertainty of the measurement. It is concluded the heat capacity of the gas in the gap has minimal impact on the measurement, which indicates that the thermal property determined by this method is the thermal conductance, instead of the thermal diffusivity. Convective heat loss through sidewalls under the current experimental design has insignificant influences. Heat transfer through spacers may cause up to 10% overestimation of thermal gap conductance, but the effects can be mostly eliminated by the design of grooves on samples. The result established a pathway for gap conductance determination. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Performance assessment modeling of a generic SNF/HLW repository in salt with coupled thermal-hydrologic effects - 15423

This paper describes advances in performance assessment modeling of deep geologic repositories facilitated by a massively parallel, high-performance computing (HPC) environment. Our new Generic Disposal System Analysis (GDSA) Framework utilizes the massively parallel PFLOTRAN multi-physics code to simulate repository performance in the presence of coupled thermal-hydrologic-chemical processes, linked to DAKOTA, an HPC uncertainty sampling and propagation code that provides nested parallelism for multi-realization performance assessment and sensitivity analysis. This enhanced performance assessment (PA) modeling capability is demonstrated with deterministic and probabilistic simulations of a generic repository for SNF and HLW in bedded salt host rock, by comparing repository performance between a case with heat-generating waste ('thermal' case) and a case without heat generation ('isothermal' case). The simulation results provide preliminary insights into the effect of multi-physics processes and thermal-hydrologic coupling on the long-term behavior of a reference-case salt repository. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Parameter estimation in a thermoelastic composite problem via adjoint formulation and model reduction

Advances in nondestructive material characterization are providing a wealth of information that could be exploited to gain insight into general aspects of material performance and, in particular, discover relationships between microstructure and thermo-mechanical properties in polycrystalline and other complex composite materials. Here, in order to facilitate the integration of such measurements into existing models, as well as inform new physics-based predictions, we developed a C++/MPI computational framework for sensitivity analysis and parameter estimation. The framework utilizes a micro-mechanical modeling based on fast Fourier transforms, direct and adjoint formulations, and Markov chain Monte Carlo sampling techniques. We illustrate the characteristics of this framework and demonstrate its utility by computing the residual stresses arising from thermal expansion of an elastic composite and using data from simulated experiments. Lastly, we show that the availability of nondestructive 3-D measurements is crucial to reduce the uncertainty in predictions, emphasizing the importance of an integrated experimental/modeling/data analysis approach for improved material characterization and design.

36 MATERIALS SCIENCE↗

Evaluation of Maximum Radionuclide Groundwater Concentrations for Basement Fill Model. Zion Station Restoration Project

ZionSolutions is in the process of decommissioning the Zion Nuclear Power Plant in order to establish a new water treatment plant. There is some residual radioactive particles from the plant which need to be brought down to levels so an individual who receives water from the new treatment plant does not receive a radioactive dose in excess of 25 mrem/y⁻¹. The objectives of this report are: (a) To present a simplified conceptual model for release from the buildings with residual subsurface structures that can be used to provide an upper bound on contaminant concentrations in the fill material; (b) Provide maximum water concentrations and the corresponding amount of mass sorbed to the solid fill material that could occur in each building for use in dose assessment calculations; (c) Estimate the maximum concentration in a well located outside of the fill material; and (d) Perform a sensitivity analysis of key parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Using Nuclear Theory, Data and Uncertainties in Monte Carlo Transport Applications

These are slides for a presentation on using nuclear theory, data and uncertainties in Monte Carlo transport applications. The following topics are covered: nuclear data (experimental data versus theoretical models, data evaluation and uncertainty quantification), fission multiplicity models (fixed source applications, criticality calculations), uncertainties and their impact (integral quantities, sensitivity analysis, uncertainty propagation).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗

Shape optimization of single- and two-element airfoils on multiblock grids

A multiblock, discrete sensitivity analysis method is used to couple a direct optimization method and a flow analysis method. The domain is divided into smaller subdomains for which the sensitivities are obtained separately. Then, an effective sensitivity equation is solved to complete the coupling of all the sensitivity information. The flow analysis is based on the thin-layer Navier-Stokes equations solved by an implicit, upwind-biased, finite-volume method. The method of feasible directions is used for the present gradient-based optimization approach. First, a transonic airfoil is optimized to investigate the behavior of the method in highly nonlinear flows as well as the effect of different blocking strategies on the procedure. A supercritical airfoil is produced from an initially symmetric airfoil with multiblocking affecting the path but not the final shape. Secondly, a two-element airfoil is shape optimized in subsonic flow to demonstrate the present method's capability of shaping aerodynamically interfering elements simultaneously. For a very low and a very high Reynolds number cases, the shape of the main airfoil and the flap are optimized to yield improved lift-to-drag ratios.

Lacasse, James M.↗

Thermodynamic analysis of tar reforming through auto-thermal reforming process

Fixed bed gasification is a simple and suitable technology for small scale power generation. One of the disadvantages of this technology is producing tar. So far, tar is not utilized yet and being waste that should be treated into a more useful product. This paper presents a thermodynamic analysis of tar conversion into gas producer through non-catalytic auto-thermal reforming technology. Tar was converted into components, C, H, O, N and S, and then reacted with oxidant such as mixture of air or pure oxygen. Thus, this reaction occurred auto-thermally and reached chemical equilibrium. The sensitivity analysis resulted that the most promising process performance occurred at flow rate of air was reached 43% of stoichiometry while temperature of process is 1100°C, the addition of pure oxygen is 40% and preheating of oxidant flow is 250°C. The yield of the most promising process performance between 11.15-11.17 kmol/h and cold gas efficiency was between 73.8-73.9%.The results of this study indicated that thermodynamically the conversion of tar into producer gas through non-catalytic auto-thermal reformingis more promising.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistical Methods for Effective Spatial and Temporal Scaling in Support of Probabilistic Performance Assessments - 17340

Performance assessments (PAs) for the disposal of low-level radioactive waste have traditionally been performed in a deterministic manner, with inputs specified as single values as if they carry no uncertainty. Modern PAs, however, explicitly incorporate uncertainty through use of probability distributions for inputs instead of single values. While this is clearly an improvement, challenges remain in specifying appropriate distributions, many of which relate to capturing the appropriate spatial and/or temporal scale given the PA model, and matching the scale(s) of data and information to that specified by the model. More careful attention to scaling will lead to more defensible characterizations of physical variability and uncertainty in model inputs, thus leading to more defensible information regarding outcomes of interest to be used in decision making, and hence more defensible decisions. This work introduces general strategies and considerations for explicitly incorporating considerations of scale into distribution development. The strategies are explained as a series of steps and then presented with an example that starts to illustrate the new statistical concepts. This work frames the problem in terms of hierarchical statistical modeling, providing important connections to current statistical approaches to formally and rigorously account for temporal and spatial scaling. The larger goal is to build a more formal and unified approach to distribution development to help teams of modelers, subject matter experts, and statisticians work together to develop distributions and justify the choices made in the process, ultimately leading to more informed decision-making. Without this rigor, statistical distributions are not specified correctly and can have unexpected consequences for modeling and sensitivity analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗

Role of the social factors in success of solar photovoltaic reuse and recycle programmes

By 2050, the cumulative mass of end-of-life photovoltaic (PV) modules may reach 80 Mt globally. The impacts could be mitigated by module recycling, repair and reuse; however, previous studies of PV circularity omit the consideration of critical social factors. Here we used an agent-based model to integrate social aspects with techno-economic factors, which provides a more realistic assessment of the circularity potential for previously studied interventions that assesses additional interventions that cannot be analysed using techno-economic analysis alone. We also performed a global sensitivity analysis using a machine-learning metamodel. We show that to exclude social factors underestimates the effect of lower recycling prices on PV material circularity, which highlights the relevance of considering social factors in future studies. Interventions aimed at changing customer attitudes about used PV boost the reuse of modules, although used modules can only satisfy one-third of the US demand during 2020–2050, which suggests that reuse should be complemented by recycling.

14 SOLAR ENERGY↗