Relevant bibliographies by topics / Multi-index Monte Carlo

Academic literature on the topic 'Multi-index Monte Carlo'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Multi-index Monte Carlo"

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Crisan, Dan, Pierre Del Moral, Jeremie Houssineau, and Ajay Jasra. "Unbiased multi-index Monte Carlo." Stochastic Analysis and Applications 36, no. 2 (December 7, 2017): 257–73. http://dx.doi.org/10.1080/07362994.2017.1394880.

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Jasra, Ajay, Kengo Kamatani, Kody J. H. Law, and Yan Zhou. "A MULTI-INDEX MARKOV CHAIN MONTE CARLO METHOD." International Journal for Uncertainty Quantification 8, no. 1 (2018): 61–73. http://dx.doi.org/10.1615/int.j.uncertaintyquantification.2018021551.

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Haji-Ali, Abdul-Lateef, Fabio Nobile, and Raúl Tempone. "Multi-index Monte Carlo: when sparsity meets sampling." Numerische Mathematik 132, no. 4 (June 27, 2015): 767–806. http://dx.doi.org/10.1007/s00211-015-0734-5.

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Wang, Christoph Reisinger and Zhenru. "Analysis of Multi-Index Monte Carlo Estimators for a Zakai SPDE." Journal of Computational Mathematics 36, no. 2 (June 2018): 202–36. http://dx.doi.org/10.4208/jcm.1612-m2016-0681.

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Robbe, Pieterjan, Dirk Nuyens, and Stefan Vandewalle. "A Multi-Index Quasi--Monte Carlo Algorithm for Lognormal Diffusion Problems." SIAM Journal on Scientific Computing 39, no. 5 (January 2017): S851—S872. http://dx.doi.org/10.1137/16m1082561.

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LI, TING, HUI GONG, and QINGMING LUO. "MCVM: MONTE CARLO MODELING OF PHOTON MIGRATION IN VOXELIZED MEDIA." Journal of Innovative Optical Health Sciences 03, no. 02 (April 2010): 91–102. http://dx.doi.org/10.1142/s1793545810000927.

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The Monte Carlo code MCML (Monte Carlo modeling of light transport in multi-layered tissue) has been the gold standard for simulations of light transport in multi-layer tissue, but it is ineffective in the presence of three-dimensional (3D) heterogeneity. New techniques have been attempted to resolve this problem, such as MCLS, which is derived from MCML, and tMCimg, which draws upon image datasets. Nevertheless, these approaches are insufficient because of their low precision or simplistic modeling. We report on the development of a novel model for photon migration in voxelized media (MCVM) with 3D heterogeneity. Voxel crossing detection and refractive-index-unmatched boundaries were considered to improve the precision and eliminate dependence on refractive-index-matched tissue. Using a semi-infinite homogeneous medium, steady-state and time-resolved simulations of MCVM agreed well with MCML, with high precision (~100%) for the total diffuse reflectance and total fractional absorption compared to those of tMCimg (< 70%). Based on a refractive-index-matched heterogeneous skin model, the results of MCVM were found to coincide with those of MCLS. Finally, MCVM was applied to a two-layered sphere with multi-inclusions, which is an example of a 3D heterogeneous media with refractive-index-unmatched boundaries. MCVM provided a reliable model for simulation of photon migration in voxelized 3D heterogeneous media, and it was developed to be a flexible and simple software tool that delivers high-precision results.
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Haji-Ali, Abdul-Lateef, and Raúl Tempone. "Multilevel and Multi-index Monte Carlo methods for the McKean–Vlasov equation." Statistics and Computing 28, no. 4 (September 12, 2017): 923–35. http://dx.doi.org/10.1007/s11222-017-9771-5.

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Ramdhani, Faisal, and Hartrisari Hardjomidjojo. "ANALISIS INDEKS KINERJA USAHA KECIL MENENGAH DI KOTA BOGOR." JURNAL REKAYASA DAN MANAJEMEN AGROINDUSTRI 7, no. 1 (April 2, 2019): 133. http://dx.doi.org/10.24843/jrma.2019.v07.i01.p14.

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Small and Medium Enterprises (SMEs) is the locomotive of economic development of Indonesia. Within the framework of the national economy, SMEs have contributed to the recruitment of labor, the increase of Gross Domestic Product (GDP) as well as the increase of export value and national investment. In the vision and mission of Bogor city government, SMEs are expected to become the economic buffer of the city of Bogor in the face of free market competition. Currently there are 13.953 SMEs in the city of Bogor. Sustainability Index based on multi dimensional scaling can be used to measure the performance status of SMEs and formulate specific strategies that need to be done to improve their competitiveness. This research was conducted from dimension setting, attribute determination, attribute review, multidimentional scaling analysis, Monte Carlo and Leverage. The value of Stress and R2 resulted is less than 0.25 and more than 0.80 so that the data has good of fit. The Monte Carlo analysis results for all SMEs have been valid because it has sustainability index ratio with Monte Carlo index less than 5%. The results show that the average sustainability index for SMEs in Bogor city is 49.8, which means that the city of Bogor is in sufficient condition (index value is below 50). The result also shows that ecological and economical factors are the important factors for increasing the performance of SMEs. The simulation results show that changes in related dimensions can increase the average value of the sustainability index to above 60 (good category). Key Words : Small and Medium Enterprises (SMEs), Sustainability Index, competitiveness, multi dimensional scaling.
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Shao, Jiang, Keyong Zhu, Xiaochuan Liu, Guodong Shi, and Yong Huang. "A general Monte Carlo method for polarized radiative transfer in multi-dimensional graded-index media." Journal of Quantitative Spectroscopy and Radiative Transfer 278 (February 2022): 108041. http://dx.doi.org/10.1016/j.jqsrt.2021.108041.

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Nazmul Huda, A. S., and Rastko Živanovic. "Estimation of Distribution Systems Expected Energy Not Supplied Index by Multi-level Monte Carlo Method." Electric Power Components and Systems 47, no. 9-10 (June 15, 2019): 810–22. http://dx.doi.org/10.1080/15325008.2019.1628120.

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Dissertations / Theses on the topic "Multi-index Monte Carlo"

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Chelda, Samir. "Simulation du parcours des électrons élastiques dans les matériaux et structures. Application à la spectroscopie du pic élastique multi-modes MM-EPES." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2010. http://tel.archives-ouvertes.fr/tel-00629659.

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La spectroscopie EPES (Elastic Peak Electron Spectroscopy) permet de mesurer le pourcentage he d'électrons rétrodiffusés élastiquement par la surface d'un échantillon soumis à un bombardement électronique. C'est une méthode non destructive et extrêmement sensible à la surface. L'objectif de ce travail est de modéliser le cheminement des électrons élastiques dans la matière grâce à une simulation informatique basée sur la méthode Monte Carlo. Cette simulation contribue de manière essentielle à la connaissance et à l'interprétation des résultats expérimentaux obtenus par spectroscopie EPES. Nous avons, de plus, adapté cette simulation à différentes surfaces transformées à l'échelle micrométrique et nanométrique. A l'aide d'une méthode originale, basée sur une description couche par couche du matériau, j'ai réalisé un programme informatique (MC1) rendant compte du cheminement des électrons élastiques dans les différentes couches du matériau. Le nombre d'électrons ressortant de la surface dépend de nombreux paramètres comme : la nature du matériau à étudier, l'énergie des électrons incidents, l'angle d'incidence, les angles de collection des analyseurs. De plus, je me suis intéressé à l'effet de la rugosité de la surface et j'ai démontré qu'elle joue un rôle déterminant sur l'intensité du pic élastique. Ensuite, grâce à l'association de la spectroscopie EPES et de la simulation Monte Carlo, j'ai déduit les modes de croissance de l'or sur substrat d'argent et de cuivre. Les effets de l'arrangement atomique et des pertes énergétiques de surfaces ont ensuite été étudiés. Pour cela, une deuxième simulation MC2 tenant compte de ces deux paramètres a été réalisée permettant d'étudier les surfaces à l'échelle nanométriques. Ces paramètres jusqu'alors non pris en compte dans notre simulation MC1, joue un rôle essentiel sur l'intensité élastique. Ensuite, j'ai obtenu une formulation simple et exploitable pour l'interprétation des résultats obtenus par la simulation MC2 pour un analyseur RFA. Afin de valider, les différents résultats de la simulationMC2, j'ai réalisé des surfaces de silicium nanostructurées, à l'aide de masques d'oxyde d'alumine réalisés par voie électrochimique. J'ai pu créer des nano-pores par bombardement ionique sous ultravide sur des surfaces de silicium. Afin de contrôler la morphologie de la surface, j'ai effectué de l'imagerie MEB ex-situ. La simulation Monte Carlo développée associée aux résultats EPES expérimentaux permet d'estimer la profondeur, le diamètre et la morphologie des pores sans avoir recours à d'autres techniques ex-situ.Cette simulation MC2 permet de connaître la surface étudiée à l'échelle nanométrique.
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Haji, Ali Abdul Lateef. "Efficient Multilevel and Multi-index Sampling Methods in Stochastic Differential Equations." Diss., 2016. http://hdl.handle.net/10754/610543.

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Most problems in engineering and natural sciences involve parametric equations in which the parameters are not known exactly due to measurement errors, lack of measurement data, or even intrinsic variability. In such problems, one objective is to compute point or aggregate values, called “quantities of interest”. A rapidly growing research area that tries to tackle this problem is Uncertainty Quantification (UQ). As the name suggests, UQ aims to accurately quantify the uncertainty in quantities of interest. To that end, the approach followed in this thesis is to describe the parameters using probabilistic measures and then to employ probability theory to approximate the probabilistic information of the quantities of interest. In this approach, the parametric equations must be accurately solved for multiple values of the parameters to explore the dependence of the quantities of interest on these parameters, using various so-called “sampling methods”. In almost all cases, the parametric equations cannot be solved exactly and suitable numerical discretization methods are required. The high computational complexity of these numerical methods coupled with the fact that the parametric equations must be solved for multiple values of the parameters make UQ problems computationally intensive, particularly when the dimensionality of the underlying problem and/or the parameter space is high. This thesis is concerned with optimizing existing sampling methods and developing new ones. Starting with the Multilevel Monte Carlo (MLMC) estimator, we first prove its normality using the Lindeberg-Feller CLT theorem. We then design the Continuation Multilevel Monte Carlo (CMLMC) algorithm that efficiently approximates the parameters required to run MLMC. We also optimize the hierarchies of one-dimensional discretization parameters that are used in MLMC and analyze the tolerance splitting parameter between the statistical error and the bias constraints. An important contribution of this thesis is the novel Multi-index Monte Carlo (MIMC) method which is an extension of MLMC in high dimensional problems with significant computational savings. Under reasonable assumptions on the weak and variance convergence, which are related to the mixed regularity of the underlying problem and the discretization method, the order of the computational complexity of MIMC is, at worst up to a logarithmic factor, independent of the dimensionality of the underlying parametric equation. We also apply the same multi-index methodology to another sampling method, namely the Stochastic Collocation method. Hence, the novel Multi-index Stochastic Collocation method is proposed and is shown to be more efficient in problems with sufficient mixed regularity than our novel MIMC method and other standard methods. Finally, MIMC is applied to approximate quantities of interest of stochastic particle systems in the mean-field when the number of particles tends to infinity. To approximate these quantities of interest up to an error tolerance, TOL, MIMC has a computational complexity of O(TOL-2log(TOL)2). This complexity is achieved by building a hierarchy based on two discretization parameters: the number of time steps in an Milstein scheme and the number of particles in the particle system. Moreover, we use a partitioning estimator to increase the correlation between two stochastic particle systems with different sizes. In comparison, the optimal computational complexity of MLMC in this case is O(TOL-3) and the computational complexity of Monte Carlo is O(TOL-4).
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Book chapters on the topic "Multi-index Monte Carlo"

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Robbe, Pieterjan, Dirk Nuyens, and Stefan Vandewalle. "A Dimension-Adaptive Multi-Index Monte Carlo Method Applied to a Model of a Heat Exchanger." In Springer Proceedings in Mathematics & Statistics, 429–45. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91436-7_24.

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Conference papers on the topic "Multi-index Monte Carlo"

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Vogt, William C., and Christopher G. Rylander. "Coupled Poroviscoelastic and Optical Monte Carlo Simulation of Dynamic Light Transport Through Indented Soft Tissue." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14683.

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Biological tissues are heterogeneous materials that may be considered mixtures of water, proteins, and cells. The large mismatch in refractive index between these constituents causes tissues to be highly turbid, diffusing light and limiting the efficacy of optical diagnostic and therapeutic techniques [1]. Mechanical optical clearing is a technique for reducing tissue scattering and absorption using controlled tissue deformation. Mechanical optical clearing is performed using indentation to locally modify tissue optical properties, including refractive index [2] and reduced scattering coefficient [3]. This effect is attributed to transient changes in tissue water distribution as a result of interstitial fluid flow due to tissue compression. In this study, we have developed a multi-domain mathematical framework for simulating mechanical optical clearing effects on tissue mechanical and optical behavior, including hyperelasticity, viscoelasticity, porous flow, and light transport. This model was then fitted to mechanical force data and used to predict experimentally measured optical transmission.
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Kazancioglu, Emre, Guangquan Wu, Jeonghan Ko, Stanislav Bohac, Zoran Filipi, S. Jack Hu, Dennis Assanis, and Kazuhiro Saitou. "Robust Optimization of an Automotive Valvetrain Using a Multiobjective Genetic Algorithm." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/dac-48714.

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A robust optimization of an automobile valvetrain is presented where the variation of engine performances due to the component dimensional variations is minimized subject to the constraints on mean engine performances. The dimensional variations of valvetrain components are statistically characterized based on the measurements of the actual components. Monte Carlo simulation is used on a neural network model built from an integrated high fidelity valvetrain-engine model, to obtain the mean and standard deviation of horsepower, torque and fuel consumption. Assuming the component production cost is inversely proportional to the coefficient of variation of its dimensions, a multi-objective optimization problem minimizing the variation in engine performances and the total production cost of components is solved by a multi-objective genetic algorithm (MOGA). The comparisons using the newly developed Pareto front quality index (PFQI) indicate that MOGA generates the Pareto fronts of substantially higher quality, than SQP with varying weights on the objectives. The current design of the valvetrain is compared with two alternative designs on the obtained Pareto front, which suggested potential improvements.
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Tan, Changbai, Theodor Freiheit, Kira Barton, Mihaela Banu, and S. Jack Hu. "Robustness Optimization of Product Assembly Architecture for Personalization." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23654.

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Abstract Personalization has received extensive attention as a new manufacturing paradigm to address increased market demand for personalized products. An open product architecture that assembling common, customized, and personalized modules is regarded as a key enabler for product personalization, which can deliver one-of-a-kind products for individual customers at near mass production efficiency. Offering the best product architecture should consider the variations in design variables and parameters that influence the performance of a product architecture. This is especially true when designing open architecture for personalized products as many uncertain design quantities need to be considered in early product design stage. A robustness optimization method is proposed to simultaneously optimize product variety, module variant selection, and configuration of personalized module variants for a personalized assembly architecture. First, a profit model is developed to measure the performance of a product architecture, which incorporates individual customer preferences and manufacturing cost. A three-step process is proposed to model heterogeneous customer preferences: conjoint analysis of the preferences of a sample of customers from target market, market segmentation by a multi-variate normal mixture method, and simulation of personal preferences for a broader market by Monte-Carlo simulation. Thus, the simulated individual customer preferences are used to predict the sales and profit of product offerings. Second, the variation of profit associated with a product family architecture due to the uncertainty in customer preference and manufacturing cost estimates is formulated by a sensitivity analysis. A robustness index is defined by combining the objectives of maximizing profit and minimizing its variation. Lastly, a robustness optimization model is established to optimize product architecture by maximizing its robustness index. The proposed method is demonstrated with a personalized bicycle architecture design example.
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Bao, Shiyi, Zhibin Li, Lijia Luo, and Zengliang Gao. "Reliability Analysis of Spring Operated Pressure Relief Valve." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97303.

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Pressure relief valve (PRV) is an important automatic overpressure protection system in the process industry. Because of the operating characteristics, the performance of PRV is supposed to be proved by the proof test. However, it’s difficult to determine the proof test intervals and the availability of the PRV between two proof tests. Based on stochastic Petri nets (SPN), the reliability modeling and analysis procedure of spring operated full lift pressure relief valve which is the most widely used PRV is depicted in this paper. Firstly, the FMECA method is used to analyze the causes and effects of the typical six failure modes of the PRV, such as vibration, leakage, frequency hopping, unable to open, open before the settings and the low back seat pressure. Second, the corresponding fault tree (FT) models of the PRV are built through the multi-component failure analysis. Third, the SPN models of the PRV are established by employing the logical relations in the FT models. Based on the collected failure data of the PRVs, the steady state and transient reliability index are calculated by Monte Carlo simulation based on the SPN software SPN@. Last, the idea about PRV reliability data collection in domestic process industries is proposed. The result of the reliability analysis can provide the basis for determination the proof test intervals of the PRV, and the proposed procedure also bears significance in its application in the reliability analysis of general system in process industry.
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Dao, Cuong D., Behzad Kazemtabrizi, and Christopher J. Crabtree. "Impacts of Reliability on Operational Performance and Cost of Energy Evaluation of Multi-Megawatt, Far-Offshore Wind Turbines." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95561.

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Abstract Wind energy is growing at a fast pace around the world. According to a report published by WindEurope, 55% of total power capacity installations in the EU came from wind in 2017. In this context, offshore wind plays a decisive role, with countries such as the UK leading the development of large-scale offshore wind projects within Europe and around the world. It is essential that the cost of energy from offshore wind remains competitive with other sources of energy to encourage further investment in offshore wind developments. One way to maintain and further reduce the cost of offshore wind energy is to take advantage of economies of scale by increasing the megawatt ratings of offshore wind turbines. On the other hand, the operational expenditure of the turbines could also be reduced significantly. In this paper, we present a new integrated operation simulation framework for performance evaluation of multi-megawatt direct drive wind turbines suitable for use in far offshore wind farms. The operation simulation considers several essential wind turbine data such as component reliability, i.e. failure rates and downtimes per failure, historical wind speed, turbine information, and repair cost per failure to estimate the operational and economic performance of the wind turbine in its entire lifetime. In the proposed operation simulation, component reliability models and a wind power model are coupled together to simulate wind turbine operation over its entire lifetime using a time-sequential Monte Carlo simulation. Since the reliability data for large-scale offshore wind turbines are scarce and/or restricted to only direct stakeholders, a range of operational profiles for the turbines based on different level of reliability are simulated. In addition, the economic performance of the turbine is measured by defining an index for levelised cost of energy as a function of component reliability. In this way, the wind turbine reliability, power output, failure cost and levelised cost of energy are estimated under the variation of input reliability data. The results of this paper can inform wind turbine performance depending on the reliability of its components, and provide useful information for critical components identification and economic assessment of future far offshore wind turbines.
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Amirpourabasi, Arezoo, Mohammad Pourgol-Mohammad, and Hanieh Niroomand-Oscuii. "Reliability Evaluation for Biomechanics Transient Stresses: Case Study of Biological Cell Vitality in Freezing Process." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-39468.

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This research proposes reliability evaluation for performance of biological transient mechanical stresses scenarios. This is part of a broader research done by the authors for comprehensive analysis of the biological reliability analysis [1]. A literature review is conducted in area of biomechanics phenomenological processes in order to classify the approaches for success criteria determination and reliability metrics calculation based on their merits and limitations. A limited failure mode and effect analysis is performed as a pre-processor for identification of the corresponding figure of merits. Biological environment is complex in correlated occurrence of microscopic and macroscopic phenomena. Therefore the modeling of this complex medium, in context of mechanical stresses, requires numerical solution of conservation equation and inclusion of corresponding constitution models. Determination of success criteria (first phase for reliability calculation in this research) is a challenging object, and requires consideration of several dependent figures of merits (e.g. temperature, mass and etc.). The developed success criteria matrix is based on the approaches of representation of the figures of merit. A multi-objective criteria is developed according to the phenomena occurrence in the intended study and the selected proper figure(s) of merit. The matrix determines the region of acceptance as well as the rejection area. The reliability index is proposed to estimate the probability of the success based on the calculated system performance in a non-deterministic (stochastic parameters) approach. By augmentation of developed success criteria and the system analysis calculation, a decision is made on the success and rejection of the system performance the methodology is applied to the case of cell cryopreservation phenomenon. The process of freezing in living cells is considerably more complicated than in a solution, primarily due to the presence of cellular structure. The process is considered a transient mechanical stress on the cell structure including the thermal and mass transport. The success criteria is determined based on two figures of merit of temperature and mass and their rate of change. Numerical calculation is completed for study of thermal and mass behavior for the transient of the cell. The uncertain parameters are considered random and Monte Carlo simulation is conducted for inclusion of their variation in the calculation. The situation are specified for the observation of the success criteria and occurrence of the failure.
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Miller, Fletcher J., and Arlon J. Hunt. "Developing the Small Particle Heat Exchange Receiver for a Prototype Test." In ASME 2012 6th International Conference on Energy Sustainability collocated with the ASME 2012 10th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/es2012-91337.

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The concept of absorbing concentrated solar radiation volumetrically, rather than on a surface, is being researched by several groups with differing designs for high temperature solar receivers. The Small Particle Heat Exchange Receiver (SPHER), one such design, is a gas-cooled central receiver capable of producing pressurized air in excess of 1100 C designed to be directly integrated into a Brayton-cycle power block to generate electricity from solar thermal power. The unique heat transfer fluid used in the SPHER is a low-density suspension of carbon nano-particles (diameter ∼ 200 nm) to absorb highly concentrated solar radiation directly in a gas stream, rather than on a fixed absorber like a tube or ceramic foam. The nano-particles are created on-demand by pyrolyzing a small flow of natural gas in an inert carrier gas just upstream of the receiver, and the particle stream is mixed with air prior to injection into the receiver. The receiver features a window (or multiple windows, depending on scale) on one end to allow concentrated sunlight into the receiver where it is absorbed by the gas-particle suspension prior to reaching the receiver walls. As they pass through the receiver the carbon nano-particles oxidize to CO2 resulting a clear gas stream ready to enter a downstream combustor or directly into the turbine. The amount of natural gas consumed or CO2 produced is miniscule (1–2%) compared to what would be produced if the natural gas were burned directly to power a gas turbine. The idea of a SPHER, first proposed many years ago, has been tested on a kW scale by two different groups. In the new work, the engineering for a multi-MW SPHER is reported. An in-house Monte Carlo model of the radiation heat transfer in the gas-particle mixture has been developed and is coupled to FLUENT to perform the fluid dynamic calculations in the receiver. Particle properties (size distribution and complex index of refraction) are obtained experimentally from angular scattering and extinction measurements of natural gas pyrolysis in a lab-scale generator, and these are corroborated using image analysis of Scanning Electron Microscope (SEM) pictures of particles captured on a filter. A numerical model of the particle generator has been created to allow for scale-up for a large receiver. We have also designed a new window for the receiver that will allow pressurized operation up to 10 bar with a 2 m diameter window. Recent progress on overcoming the engineering challenges in developing this receiver for a prototype test is reported.
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