Uncertainty propagation through a point model for steady-state two-phase pipe flow

Uncertainty propagation is used to quantify the uncertainty in model predictions in the presence of uncertain input variables. In this study, we analyze a steady-state point-model for two-phase gas-liquid flow. We present prediction intervals for holdup and pressure drop that are obtained from knowledge of the measurement error in the variables provided to the model. The analysis also uncovers which variables the predictions are most sensitive to. Sensitivity indices and prediction intervals are calculated by two different methods, Monte Carlo and polynomial chaos. The methods give similar prediction intervals, and they agree that the predictions are most sensitive to the pipe diameter and the liquid viscosity. However, the Monte Carlo simulations require fewer model evaluations and less computational time. The model predictions are also compared to experiments while accounting for uncertainty, and the holdup predictions are accurate, but there is bias in the pressure drop estimatespublishedVersio

Application of a strong FSI coupling scheme for the numerical simulation of bileaflet mechanical heart valve dynamics: study of wall shear stress on the valve leaflets

One of the major challenges in the design of Bileaflet Mechanical Heart Valves (BMHVs) is reduction of the blood damage generated by non-physiological blood flow. Numerical simulations provide relevant insights into the (fluid) dynamics of the BMHV and are used for design optimisation. In this paper, a strong coupling algorithm for the partitioned Fluid-Structure Interaction (FSI) simulation of a BMHV is presented. The convergence of the coupling iterations between the flow solver and the leaflet motion solver is accelerated by using a numerically calculated Jacobian with the derivatives of the pressure and viscous moments acting on the leaflets with respect to the leaflet accelerations. The developed algorithm is used to simulate the dynamics of a 3D BMHV in three different geometries, allowing an analysis of the solution process. Moreover, the leaflet kinematics and the general flow field are discussed, with special focus on the shear stresses on the valve leaflets

A fast strong coupling algorithm for the partitioned fluid–structure interaction simulation of BMHVs

The numerical simulation of Bileaflet Mechanical Heart Valves (BMHVs) has gained strong interest in the last years, as a design and optimisation tool. In this paper, a strong coupling algorithm for the partitioned fluidstructure interaction simulation of a BMHV is presented. The convergence of the coupling iterations between the flow solver and the leaflet motion solver is accelerated by using the Jacobian with the derivatives of the pressure and viscous moments acting on the leaflets with respect to the leaflet accelerations. This Jacobian is numerically calculated from the coupling iterations. An error analysis is done to derive a criterion for the selection of useable coupling iterations. The algorithm is successfully tested for two 3D cases of a BMHV and a comparison is made with existing coupling schemes. It is observed that the developed coupling scheme outperforms these existing schemes in needed coupling iterations per time step and CPU time

Analytical results for wave propagation in compliant vessels

International audienceIn this paper we revisit the Womersley-theory, and present a 1D approach for analytical estimates of the pulse wave velocity and the damping factor, which both may be useful for validation of FSI-codes

Uncertainty quantification and sensitivity analysis of material parameters in crystal plasticity finite element models

A number of studies have directly compared measurements of polycrystals’ deformation to the solution of a crystal plasticity model of the same polycrystal. An accurate representation of the full 3D microstructure and the boundary conditions has been shown to be important to obtain a good correspondence between the behaviour of the real and the simulated polycrystal. However, much less is known about the relationship between the global and the local solutions of crystal plasticity models and the influence of material parameters on the local response of the polycrystal. To address these questions, uncertainty quantification and sensitivity analysis are performed on finite element models of oligocrystals with a crystal plasticity material model. The results show significant variations in the simulated stress and strain fields due to variations in the material parameters. Sensitivity analysis is used to quantify the contribution of crystal orientation, latent hardening and other material model parameters to the variability of the crystal plasticity finite element model solution. The uncertainty in the stress and strain fields and their sensitivities vary between the oligocrystals, but nevertheless, some distinct trends can be identified. The most prominent trend is that, in general, the solution is most sensitive to the variations of the latent hardening description and the crystallographic orientations of the constituent crystals.acceptedVersio

Optimization of topological complexity for one-dimensional arterial blood flow models

As computational models of the cardiovascular system are applied in modern personalized medicine, maximizing certainty of model input becomes crucial. A model with a high number of arterial segments results in a more realistic description of the system, but also requires a high number of parameters with associated uncertainties. In this paper, we present a method to optimize/reduce the number of arterial segments included in one-dimensional blood flow models, while preserving key features of flow and pressure waveforms. We quantify the preservation of key flow features for the optimal network with respect to the baseline networks (a 96-artery and a patient-specific coronary network) by various metrics and quantities like average relative error, pulse pressure and augmentation pressure. Furthermore, various physiological and pathological states are considered. For the aortic root and larger systemic artery pressure waveforms a network with minimal description of lower and upper limb arteries and no cerebral arteries, sufficiently captures important features such as pressure augmentation and pulse pressure. Discrepancies in carotid and middle cerebral artery flow waveforms that are introduced by describing the arterial system in a minimalistic manner are small compared with errors related to uncertainties in blood flow measurements obtained by ultrasound

Closure Law Model Uncertainty Quantification

The prediction uncertainty in simulators for industrial processes is due to uncertainties in the input variables and uncertainties in specification of the models, in particular the closure laws. In this work, the uncertainty in each closure law was modeled as a random variable and the parameters of its distribution were optimized to correctly quantify the uncertainty in predictions. We have developed two methods for optimization, based on the integrated quadratic distance and the energy score. The proposed methods were applied to the commercial multiphase flow simulator LedaFlow with the liquid volume fraction and pressure gradient as output variables. Two datasets were analyzed. Both describe two-phase gas-liquid flow, but are otherwise fundamentally different. One is gas-dominated stratified/annular flow and the other is liquid-dominated slug flow. The closure law for the gas-wall friction factor is decisive for the gas-dominated predictions, and the estimated relative standard deviation is 4.5% or 8.0% depending on method. The liquid-dominated study showed that the liquid-wall friction factor and the slug bubble velocity are the closure laws with the greatest impact. Moreover, the estimated relative standard deviation in the liquid-wall friction factor is 5%, and the deviation in the slug bubble velocity is 4%. We used direct measurements of the slug bubble velocity to validate the estimated uncertainty

Repeatability in a multiphase pipe flow case study

A high degree of repeatability is most often an underlying assumption for research and development based on multiphase flow experiments. In this paper repeatability in multiphase flow experiments are studied through an experimental campaign with 28 replicates for 11 unique settings. The experiments were conducted in a flow loop with multiple injections of oil, water and air. A high degree of repeatability was found, with relative replicate deviations in volume flow rates and pressure drops of 0.1% in magnitude. Further, several potential causes of replicate deviations were studied, and firmer control of temperature of the inflow fluids is proposed as a means to improve repeatability in volume flow rates and pressure. We conclude that for practical use, the presented category of multiphase experiments sufficiently meets underlying repeatability assumptions