196,126 research outputs found
A least square extrapolation method for the a posteriori error estimate of the incompressible Navier Stokes problem
No full textA posteriori error estimators are fundamental tools for providing confidence in the numerical computation of PDEs. To date, the main theories of a posteriori estimators have been developed largely in the finite element framework, for either linear elliptic operators or non-linear PDEs in the absence of disparate length scales. On the other hand, there is a strong interest in using grid refinement combined with Richardson extrapolation to produce CFD solutions with improved accuracy and, therefore, a posteriori error estimates. But in practice, the effective order of a numerical method often depends on space location and is not uniform, rendering the Richardson extrapolation method unreliable. We have recently introduced (Garbey, 13th International Conference on Domain Decomposition, Barcelona, 2002; 379-386; Garbey and Shyy, J. Comput. Phys. 2003; 186:1-23) a new method which estimates the order of convergence of a computation as the solution of a least square minimization problem on the residual. This method, called least square extrapolation, introduces a framework facilitating multi-level extrapolation, improves accuracy and provides a posteriori error estimate. This method can accommodate different grid arrangements. The goal of this paper is to investigate the power and limits of this method via incompressible Navier Stokes flow computations.</p
Touch-less estimation of blood flow speed and vessel location from functional infrared imaging
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Contact-free measurement of cardiac pulse based on the analysis of thermal imagery
No full textWe have developed a novel method to measure human cardiac pulse at a distance. It is based on the information contained in the thermal signal emitted from major superficial vessels. This signal is acquired through a highly sensitive thermal imaging system. Temperature on the vessel is modulated by pulsative blood flow. To compute the frequency of modulation (pulse), we extract a line-based region along the vessel. Then, we apply fast Fourier transform (FFT) to individual points along this line of interest to capitalize on the pulse’s thermal propagation effect. Finally, we use an adaptive estimation function on the average FFT outcome to quantify the pulse. We have carried out experiments on a data set of 34 subjects and compared the pulse computed from our thermal signal analysis method to concomitant ground-truth measurements obtained through a standard contact sensor (piezo-electric transducer). The performance of the new method ranges from 88.52% to 90.33% depending on the clarity of the vessel’s thermal imprint. To the best of our knowledge, it is the first time that cardiac pulse has been measured several feet away from a subject with passive means
Optimal flow conditions of a tracheobronchial model to reengineer lung structures
No full textThe high demand for lung transplants cannot be matched by an adequate number of lungs from donors. Since fully ex-novo lungs are far from being feasible, tissue engineering is actively considering implantation of engineered lungs where the devitalized structure of a donor is used as scaffold to be repopulated by stem cells of the receiving patient. A decellularized donated lung is treated inside a bioreactor where transport through the tracheobronchial tree (TBT) will allow for both deposition of stem cells and nourishment for their subsequent growth, thus developing new lung tissue. The key concern is to set optimally the boundary conditions to utilize in the bioreactor. We propose a predictive model of slow liquid ventilation, which combines a one-dimensional (1-D) mathematical model of the TBT and a solute deposition model strongly dependent on fluid velocity across the tree. With it, we were able to track and drive the concentration of a generic solute across the airways, looking for its optimal distribution. This was given by properly adjusting the pumps’ regime serving the bioreactor. A feedback system, created by coupling the two models, allowed us to derive the optimal pattern. The TBT model can be easily invertible, thus yielding a straightforward flow/pressure law at the inlet to optimize the efficiency of the bioreactor
A Multiscale Model of Atherosclerotic Plaque Development: Toward a Coupling Between an Agent-Based Model and CFD Simulations
No full textComputational models have been widely used to predict the efficacy of surgical interventions in response to Peripheral Occlusive Diseases. However, most of them lack a multiscale description of the development of the disease, which, in our hypothesis, is the key to develop an effective predictive model. Accordingly, in this work we present a multiscale computational framework that simulates the generation of atherosclerotic arterial occlusions. Starting from a healthy artery in homeostatic conditions, the perturbation of specific cellular and extracellular dynamics led to the development of the pathology, with the final output being a diseased artery. The presented model was developed on an idealized portion of a Superficial Femoral Artery (SFA), where an Agent-Based Model (ABM), locally replicating the plaque development, was coupled to Computational Fluid Dynamics (CFD) simulations that define the Wall Shear Stress (WSS) profile at the lumen interface. The ABM was qualitatively validated on histological images and a preliminary analysis on the coupling method was conducted. Once optimized the coupling method, the presented model can serve as a predictive platform to improve the outcome of surgical interventions such as angioplasty and stent deployment
A fully coupled computational fluid dynamics – agent-based model of atherosclerotic plaque development: Multiscale modeling framework and parameter sensitivity analysis
No full textBackground: Peripheral Artery Disease (PAD) is an atherosclerotic disorder that leads to impaired lumen patency through intimal hyperplasia and the build-up of plaques, mainly localized in areas of disturbed flow. Computational models can provide valuable insights in the pathogenesis of atherosclerosis and act as a predictive tool to optimize current interventional techniques. Our hypothesis is that a reliable predictive model must include the atherosclerosis development history. Accordingly, we developed a multiscale modeling framework of atherosclerosis that replicates the hemodynamic-driven arterial wall remodeling and plaque formation. Methods: The framework was based on the coupling of Computational Fluid Dynamics (CFD) simulations with an Agent-Based Model (ABM). The CFD simulation computed the hemodynamics in a 3D artery model, while 2D ABMs simulated cell, Extracellular Matrix (ECM) and lipid dynamics in multiple vessel cross-sections. A sensitivity analysis was also performed to evaluate the oscillation of the ABM output to variations in the inputs and to identify the most influencing ABM parameters. Results: Our multiscale model qualitatively replicated both the physiologic and pathologic arterial configuration, capturing histological-like features. The ABM outputs were mostly driven by cell and ECM dynamics, largely affecting the lumen area. A subset of parameters was found to affect the final lipid core size, without influencing cell/ECM or lumen area trends. Conclusion: The fully coupled CFD-ABM framework described atherosclerotic morphological and compositional changes triggered by a disturbed hemodynamics
Introduction: A road map for computational surgery: Challenges and opportunities
No full text© Springer Science+Business Media New York 2014. This paper introduces the fundamental concepts of computational surgery—Garbey et al. [Computational surgery and dual training, Springer, XVI, 315pp (Hardcover, ISBN: 978-1-4419-1122-3, 2009), 2010]—and proposes a road map for progress in this new multidisciplinary field of applied investigation. Recognizing this introduction will serve as common ground for discussion for both communities, surgeons and computational scientists, the scope of the presentation is broad rather than deep. Indeed, the field of computational surgery is sufficiently young that even the definition of computational surgery is still in the making. In this introduction, we propose multiple areas of investigation where the intersection of surgery and computational sciences is clearly in practice at the present time, though surprisingly unrecognized to date. We present examples of these intersections and demonstrate the usefulness and novelty of computational surgery as a new field of research. While some of the elements we present may be considered as basic for a specialized investigator, the simplicity of the presentation is intended as a proof of principle that basic concepts in computational sciences are of core value in solving many existing problems in clinical surgery; we also hope this initial evaluation will highlight potential obstacles and challenges. As the digital revolution transforms the working environment of the surgeon, close collaboration between surgeons and computational scientists is not only unavoidable but also essential to harness the capabilities of both fields to optimize the surgical care. We believe that this new collaboration will allow the community not only to develop the predictive models for the outcomes of surgery but also to enhance the process of surgery—from procedural planning, to execution of procedures and technology interfaces, to assessment of the healing process—investigations that will potentially provide great impact on patient care that far beyond the operating room
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
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