Browsing by Subject "uncertainty quantification"

Now showing 1 - 5 of 5
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    A new noninvasive and patient-specific hemodynamic index for the severity of renal stenosis and outcome of interventional treatment
    (Wiley, 2022-07) Yu, Huidan; Khan, Monsurul; Wu, Hao; Du, Xiaoping; Chen, Rou; Rollins, Dave M.; Fang, Xin; Long, Jianyun; Xu, Chenke; Sawchuk, Alan P.; Surgery, School of Medicine
    Renal arterial stenosis (RAS) often causes renovascular hypertension, which may result in kidney failure and life-threatening consequences. Direct assessment of the hemodynamic severity of RAS has yet to be addressed. In this work, we present a computational concept to derive a new, noninvasive, and patient-specific index to assess the hemodynamic severity of RAS and predict the potential benefit to the patient from a stenting therapy. The hemodynamic index is derived from a functional relation between the translesional pressure indicator (TPI) and lumen volume reduction (S) through a parametric deterioration of the RAS. Our in-house computational platform, InVascular, for image-based computational hemodynamics is used to compute the TPI at given S. InVascular integrates unified computational modeling for both image processing and computational hemodynamics with graphic processing unit parallel computing technology. The TPI-S curve reveals a pair of thresholds of S indicating mild or severe RAS. The TPI at S = 0 represents the pressure improvement following a successful stenting therapy. Six patient cases with a total of 6 aortic and 12 renal arteries are studied. The computed blood pressure waveforms have good agreements with the in vivo measured ones and the systolic pressure is statistical equivalence to the in-vivo measurements with p < .001. Uncertainty quantification provides the reliability of the computed pressure through the corresponding 95% confidence interval. The severity assessments of RAS in four cases are consistent with the medical practice. The preliminary results inspire a more sophisticated investigation for real medical insights of the new index. This computational concept can be applied to other arterial stenoses such as iliac stenosis. Such a noninvasive and patient-specific hemodynamic index has the potential to aid in the clinical decision-making of interventional treatment with reduced medical cost and patient risks.
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    Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface
    (ASME, 2021) Wei, Xinpeng; Zhao, Jianxun; He, Xiaoming; Hu, Zhen; Du, Xiaoping; Han, Daoru; Mechanical and Energy Engineering, School of Engineering and Technology
    This paper presents an adaptive Kriging based method to perform uncertainty quantification (UQ) of the photoelectron sheath and dust levitation on the lunar surface. The objective of this study is to identify the upper and lower bounds of the electric potential and that of dust levitation height, given the intervals of model parameters in the one-dimensional (1D) photoelectron sheath model. To improve the calculation efficiency, we employ the widely used adaptive Kriging method (AKM). A task-oriented learning function and a stopping criterion are developed to train the Kriging model and customize the AKM. Experiment analysis shows that the proposed AKM is both accurate and efficient.
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    Inlet and Outlet Boundary Conditions and Uncertainty Quantification in Volumetric Lattice Boltzmann Method for Image-Based Computational Hemodynamics
    (MDPI, 2022-01-10) Yu, Huidan; Khan, Monsurul; Wu, Hao; Zhang, Chunze; Du, Xiaoping; Chen, Rou; Fang, Xin; Long, Jianyun; Sawchuk, Alan P.; Surgery, School of Medicine
    Inlet and outlet boundary conditions (BCs) play an important role in newly emerged image-based computational hemodynamics for blood flows in human arteries anatomically extracted from medical images. We developed physiological inlet and outlet BCs based on patients’ medical data and integrated them into the volumetric lattice Boltzmann method. The inlet BC is a pulsatile paraboloidal velocity profile, which fits the real arterial shape, constructed from the Doppler velocity waveform. The BC of each outlet is a pulsatile pressure calculated from the three-element Windkessel model, in which three physiological parameters are tuned by the corresponding Doppler velocity waveform. Both velocity and pressure BCs are introduced into the lattice Boltzmann equations through Guo’s non-equilibrium extrapolation scheme. Meanwhile, we performed uncertainty quantification for the impact of uncertainties on the computation results. An application study was conducted for six human aortorenal arterial systems. The computed pressure waveforms have good agreement with the medical measurement data. A systematic uncertainty quantification analysis demonstrates the reliability of the computed pressure with associated uncertainties in the Windkessel model. With the developed physiological BCs, the image-based computation hemodynamics is expected to provide a computation potential for the noninvasive evaluation of hemodynamic abnormalities in diseased human vessels.
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    Inlet and Outlet Boundary Conditions and Uncertainty Quantification in Volumetric Lattice Boltzmann Method for Image-Based Computational Hemodynamics
    (MDPI, 2022) Yu, Huidan; Khan, Monsurul; Wu, Hao; Zhang, Chunze; Du, Xiaoping; Chen, Rou; Fang, Xin; Long, Jianyun; Sawchuk, Alan P.; Mechanical and Energy Engineering, School of Engineering and Technology
    Inlet and outlet boundary conditions (BCs) play an important role in newly emerged image-based computational hemodynamics for blood flows in human arteries anatomically extracted from medical images. We developed physiological inlet and outlet BCs based on patients’ medical data and integrated them into the volumetric lattice Boltzmann method. The inlet BC is a pulsatile paraboloidal velocity profile, which fits the real arterial shape, constructed from the Doppler velocity waveform. The BC of each outlet is a pulsatile pressure calculated from the three-element Windkessel model, in which three physiological parameters are tuned by the corresponding Doppler velocity waveform. Both velocity and pressure BCs are introduced into the lattice Boltzmann equations through Guo’s non-equilibrium extrapolation scheme. Meanwhile, we performed uncertainty quantification for the impact of uncertainties on the computation results. An application study was conducted for six human aortorenal arterial systems. The computed pressure waveforms have good agreement with the medical measurement data. A systematic uncertainty quantification analysis demonstrates the reliability of the computed pressure with associated uncertainties in the Windkessel model. With the developed physiological BCs, the image-based computation hemodynamics is expected to provide a computation potential for the noninvasive evaluation of hemodynamic abnormalities in diseased human vessels.
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    Shape optimization of lightweight structures under blast loading
    (2013-05) Israel, Joshua James; Tovar, Andres; Wasfy, Tamer; El-Mounayri, Hazim
    Structural optimization of vehicle components for blast mitigation seeks to counteract the damaging effects of an impulsive threat on occupants and critical components. The strong and urgent need for improved protection from blast events has made blast mitigating component design an active research subject. Standard up-armoring of ground vehicles can significantly increase the mass of the vehicle. Without concurrent modifications to the power train, suspension, braking and steering components, the up-armored vehicles suffer from degraded stability and mobility. For these reasons, there is a critical need for effective methods to generate lightweight components for blast mitigation. The overall objective of this research is to make advances in structural design methods for the optimization of lightweight blast-mitigating systems. This thesis investigates the automated design process of isotropic plates to mitigate the effects of blast loading by addressing the design of blast-protective structures from a design optimization perspective. The general design problem is stated as finding the optimum shape of a protective shell of minimum mass satisfying deformation and envelops constraints. This research was conducted in terms of three primary research projects. The first project was to investigate the design of lightweight structures under deterministic loading conditions and subject to the same objective function and constraints, in order to compare feasible design methodologies through the expansion of the problem dimension in order to reach the limits of performance. The second research project involved the investigation of recently developed uncertainty quantification methods, the univariate dimensional reduction method and the performance moment integration method, to structures under stochastic loading conditions. The third research project involved application of these uncertainty quantification methods to problems of design optimization under uncertainty, in order to develop a methodology for the generation of lightweight reliable structures. This research has resulted in the construction of a computational framework, incorporating uncertainty quantification methods and various optimization techniques, which can be used for the generation of lightweight structures for blast mitigation under uncertainty. Applied to practical structural design problems, the results demonstrate that the methodologies provide a practical tool to aid the design engineer in generating design concepts for blast-mitigating structures. These methods can be used to advance research into the generation of reliable structures under uncertain loading conditions inherent to blast events.