Transcatheter aortic heart valve replacement (TAVR) is a procedure to replace a failing aortic valve and is becoming the new standard of care for patients that are not candidates for open-heart surgery [2]. However, t...
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Transcatheter aortic heart valve replacement (TAVR) is a procedure to replace a failing aortic valve and is becoming the new standard of care for patients that are not candidates for open-heart surgery [2]. However, this minimally invasive technique has shown to cause ischemic brain lesions, or "silent infarcts", in 90% of TAVR patients, which can increase the patient's risk for stroke by two to four times in future years [3]. Claret Medical Inc., a medical device company, has developed a cerebral protection system that filters and captures embolic debris released during endovascular procedures, such as TAVR. This thesis utilized CT scans from Claret Medical to create a physical construct of the aortic arch to experimentally validate a theoretical computermodel through flow visualization. The hypothesis was that the empirical model can accurately mimic the fluid dynamic properties of the aortic arch in order validate an in silico model using the finite elements program COMSOL MultiPhysics® modeling Software. The physical model was created from a patient CT scan of the aortic arch using additive manufacturing (3D printing) and polymer casting, resulting in the shape of the aortic arch within a transparent, silicone material. Fluid was pumped through the model to visualize and quantify the velocity of the fluid within the aortic arch. COMSOL MultiPhysics® was used to model the aortic arch and obtain velocity measurements, which were statistically compared to the velocity measurements from the physical model. There was no significant difference between the values of the physical model and the computermodel, confirming the hypothesis. Overall, this study successfully used CT scans to create an anatomically accurate physical model that was validated by a computermodel using a novel technique of flow visualization. As TAVR and similar procedures continue to develop, the need for experimental evaluation and visualization of devices will continue to grow, making this pro
A major question for the application of computermodels is Does the computermodel adequately represent reality? Viewing the computermodels as a potentially biased representation of reality, Bayarri et al. [M. Bayarr...
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A major question for the application of computermodels is Does the computermodel adequately represent reality? Viewing the computermodels as a potentially biased representation of reality, Bayarri et al. [M. Bayarri, J. Berger, R. Paulo, J. Sacks, J. Cafeo, J. Cavendish, C. Lin, J. Tu, A framework for validation of computermodels, Technometrics 49 (2) (2007) 138-154] develop the simulator assessment and validation engine (SAVE) method as a general framework for answering this question. In this paper, we apply the SAVE method to the challenge problem which involves a thermal computermodel designed for certain devices. We develop a statement of confidence that the devices modeled can be applied in intended situations. (C) 2007 Elsevier B.V. All rights reserved.
Background: The trend towards optimizing stabilization of the craniomaxillofacial skeleton (CMFS) with the minimum amount of fixation required to achieve union, and away from maximizing rigidity, requires a quantitati...
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Background: The trend towards optimizing stabilization of the craniomaxillofacial skeleton (CMFS) with the minimum amount of fixation required to achieve union, and away from maximizing rigidity, requires a quantitative understanding of craniomaxillofacial biomechanics. This study uses computational modeling to quantify the structural biomechanics of the CMFS under maximal physiologic masticatory loading. Methods: Using an experimentally validated subject-specific finite element (FE) model of the CMFS, the patterns of stress and strain distribution as a result of physiological masticatory loading were calculated. The trajectories of the stresses were plotted to delineate compressive and tensile regimes over the entire CMFS volume. Results: The lateral maxilla was found to be the primary vertical buttress under maximal bite force loading, with much smaller involvement of the naso-maxillary buttress. There was no evidence that the pterygo-maxillary region is a buttressing structure, counter to classical buttress theory. The stresses at the zygomatic sutures suggest that two-point fixation of zygomatic complex fractures may be sufficient for fixation under bite force loading. Conclusions: The current experimentally validated biomechanical FE model of the CMFS is a practical tool for in silico optimization of current practice techniques and may be used as a foundation for the development of design criteria for future technologies for the treatment of CMFS injury and disease. (C) 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
Radiation hydrodynamics and radiative shocks are of fundamental interest in the high-energy-density physics research due to their importance in understanding astrophysical phenomena such as supernovae. In the laborato...
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Radiation hydrodynamics and radiative shocks are of fundamental interest in the high-energy-density physics research due to their importance in understanding astrophysical phenomena such as supernovae. In the laboratory, experiments can produce shocks with fundamentally similar physics on reduced scales. However, the cost and time constraints of the experiment necessitate use of a computer algorithm to generate a reasonable number of outputs for making valid inference. We focus on modeling emulators that can efficiently assimilate these two sources of information accounting for their intrinsic differences. The goal is to learn how to predict the breakout time of the shock given the information on associated parameters such as pressure and energy. Under the framework of the Kennedy-O'Hagan model, we introduce an emulator based on adaptive splines. Depending on the preference of having an interpolator for the computer code output or a computationally fast model, a couple of different variants are proposed. Those choices are shown to perform better than the conventional Gaussian-process-based emulator and a few other choices of nonstationary models. For the shock experiment dataset, a number of features related to computer model validation such as using interpolator, necessity of discrepancy function, or accounting for experimental heterogeneity are discussed, implemented, and validated for the current dataset. In addition to the typical Gaussian measurement error for real data, we consider alternative specifications suitable to incorporate noninformativeness in error distributions, more in agreement with the current experiment. Comparative diagnostics, to highlight the effect of measurement error model on predictive uncertainty, are also presented. Supplementary materials for this article are available online.
Agent-based simulation models are an important tool to study the effectiveness of policy interventions on the uptake of residential photovoltaic systems by households, a cornerstone of sustainable energy system transi...
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ISBN:
(数字)9781665408967
ISBN:
(纸本)9781665408967
Agent-based simulation models are an important tool to study the effectiveness of policy interventions on the uptake of residential photovoltaic systems by households, a cornerstone of sustainable energy system transition. In order for these models to be trustworthy, they require rigorous validation. However, the canonical approach of validating emulation models through calibration with parameters that minimize the difference of model results and reference data fails when the model is subject to many stochastic influences. The residential photovoltaic diffusion model PVact features numerous stochastic influences that prevent straightforward optimization-driven calibration. From the analysis of the results of a case-study on the cities Dresden and Leipzig (Germany) based on three error metrics (mean average error, root mean square error and cumulative average error), this research identifies a parameter range where stochastic fluctuations exceed differences between results of different parameterization and a minimization-based calibration approach fails. Based on this observation, an approach is developed that aggregates model behavior across multiple simulation runs and parameter combinations to compare results between scenarios representing different future developments or policy interventions of interest.
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