scholarly journals Model-Based Design and Optimization of Blood Oxygenators

2020 ◽  
Vol 14 (4) ◽  
Author(s):  
Ge He ◽  
Tao Zhang ◽  
Jiafeng Zhang ◽  
Bartley P. Griffith ◽  
Zhongjun J. Wu
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Fiber Bundle ◽  
Cfd Modeling ◽  
Design Parameters ◽  
Model Parameters ◽  
Transfer Rates ◽  
Design And Optimization ◽  
Model Based ◽  
Model Predictions

Abstract Blood oxygenators, also known as artificial lungs, are widely used in cardiopulmonary bypass surgery to maintain physiologic oxygen (O2) and carbon dioxide (CO2) levels in blood, and also serve as respiratory assist devices to support patients with lung failure. The time- and cost-consuming method of trial and error is initially used to optimize the oxygenator design, and this method is followed by the introduction of the computational fluid dynamics (CFD) that is employed to reduce the number of prototypes that must be built as the design is optimized. The CFD modeling method, while having progress in recent years, still requires complex three-dimensional (3D) modeling and experimental data to identify the model parameters and validate the model. In this study, we sought to develop an easily implemented mathematical models to predict and optimize the performance (oxygen partial pressure/saturation, oxygen/carbon dioxide transfer rates, and pressure loss) of hollow fiber membrane-based oxygenators and this model can be then used in conjunction with CFD to reduce the number of 3D CFD iteration for further oxygenator design and optimization. The model parameters are first identified by fitting the model predictions to the experimental data obtained from a mock flow loop experimental test on a mini fiber bundle. The models are then validated through comparing the theoretical results with the experimental data of seven full-size oxygenators. The comparative analysis show that the model predictions and experimental results are in good agreement. Based on the verified models, the design curves showing the effects of parameters on the performance of oxygenators and the guidelines detailing the optimization process are established to determine the optimal design parameters (fiber bundle dimensions and its porosity) under specific system design requirements (blood pressure drop, oxygen pressure/saturation, oxygen/carbon dioxide transfer rates, and priming volume). The results show that the model-based optimization method is promising to derive the optimal parameters in an efficient way and to serve as an intermediate modeling approach prior to complex CFD modeling.

Recycling and Extraction of Zinc Ions in Disc-Donut Column Considering Forward Mixing Mass Transfer, Chemical Reaction and Effects of Pulsed and non-Pulsed Condition

2021 ◽  
Author(s):  
Mehdi Asadollahzadeh ◽  
Rezvan Torkaman ◽  
Meisam Torab-Mostaedi ◽  
Mojtaba Saremi
Keyword(s):  
Experimental Data ◽  
Mass Transfer ◽  
Flow Rate ◽  
Positive Impact ◽  
Plug Flow ◽  
Model Parameters ◽  
Zinc Ions ◽  
Zinc Extraction ◽  
Balance Equations ◽  
Transfer Rates

Abstract The current study focuses on the recovery of zinc ions by solvent extraction in the pulsed contactor. The Zn(II) ions from chloride solution were extracted into the organic phase containing D2EHPA extractant. The resulting data were characterized for the relative amount of (a) pulsed and no-pulsed condition; and (b) flow rate of both phases. Based on the mass balance equations for the column performance description, numerical computations of mass transfer in a disc-donut column were conducted and validated the experimental data for zinc extraction. Four different models, such as plug flow, backflow, axial dispersion, and forward mixing were evaluated in this study. The results showed that the intensification of the process with the pulsed condition increased and achieved higher mass transfer rates. The forward mixing model findings based on the curve fitting approach validated well with the experimental data. The results showed that an increase in pulsation intensity, as well as the phase flow rates, have a positive impact on the performance of the extractor, whereas the enhancement of flow rate led to the reduction of the described model parameters for adverse phase.

scholarly journals Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data

2017 ◽  
Vol 473 (2201) ◽  
pp. 20170045 ◽  
Author(s):  
I. A. Kuznetsov ◽  
A. V. Kuznetsov
Keyword(s):  
Experimental Data ◽  
Confidence Intervals ◽  
Surrogate Data ◽  
Model Parameters ◽  
Model Predictions ◽  
Estimate Parameter ◽  
Minimum Number ◽  
Percentile Bootstrap ◽  
Parameter Values ◽  
Best Fit

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate ‘experimental’ data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

Design and optimization of an electromechanical actuator for the latch of a foldable vehicle seat

2020 ◽  
Vol 62 (7) ◽  
pp. 749-755
Author(s):  
Z. K. Kocabicak ◽  
U. Demir
Keyword(s):  
Neural Network ◽  
Design Parameters ◽  
Design Criteria ◽  
Model Parameters ◽  
The Finite Element Method ◽  
Electromechanical Actuator ◽  
Design And Optimization ◽  
Artificial Neural Network Ann ◽  
Critical Model ◽  
Vehicle Seat

Abstract This paper deals with the electromechanical actuator (EAct) design for a seat latch while maintaining required force and displacement according to the boundary conditions and design criteria for the finite element method (FEM) in an Ansys Maxwell environment. Before presenting the analysis studies, some EAct models are parameterized according to the Taguchi’s design of experiment (DoE) method. After that, analysis results are evaluated to define the critical model parameters of the EAct according to the DoE method. Furthermore, the DoE results and design parameters of the EAct are trained in some cases by an artificial neural network (ANN). The dynamic behavior of the models from the ANN and DoE results are analyzed and the results obtained are compared. Finally, the optimal EAct model is defined taking into account design criteria.

VLE Determination of Carbon Dioxide Loaded Aqueous Alkanolamine Mixtures Using Modified Kent Eisenberg Model

2017 ◽  
Vol 231 (11-12) ◽  
Author(s):  
Humbul Suleman ◽  
Abdulhalim Shah Maulud ◽  
Zakaria Man
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Model Parameters ◽  
Thermodynamic Models ◽  
Carbon Dioxide Absorption ◽  
Proposed Model ◽  
Wide Range ◽  
Experimental Values ◽  
Good Agreement

AbstractA computationally simple thermodynamic framework has been presented to correlate the vapour-liquid equilibria of carbon dioxide absorption in five representative types of alkanolamine mixtures. The proposed model is an extension of modified Kent Eisenberg model for the carbon dioxide loaded aqueous alkanolamine mixtures. The model parameters are regressed on a large experimental data pool of carbon dioxide solubility in aqueous alkanolamine mixtures. The model is applicable to a wide range of temperature (298–393 K), pressure (0.1–6000 kPa) and alkanolamine concentration (0.3–5 M). The correlated results are compared to the experimental values and found to be in good agreement with the average deviations ranging between 6% and 20%. The model results are comparable to other thermodynamic models.

scholarly journals CFD Modeling and Simulation of the Hydrodynamics Characteristics of Coarse Coal Particles in a 3D Liquid-Solid Fluidized Bed

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 569
Author(s):  
Jian Peng ◽  
Wei Sun ◽  
Haisheng Han ◽  
Le Xie
Keyword(s):  
Experimental Data ◽  
Fluidized Bed ◽  
Fine Particles ◽  
Particle Density ◽  
Cfd Modeling ◽  
Hydrodynamic Characteristics ◽  
Model Parameters ◽  
Low Density ◽  
Coal Particles ◽  
Simulation Results

In this study, a Eulerian-Eulerian liquid-solid two-phase flow model combined with kinetic theory of granular flow was established to study the hydrodynamic characteristics and fluidization behaviors of coarse coal particles in a 3D liquid-solid fluidized bed. First, grid independence analysis was conducted to select the appropriate grid model parameters. Then, the developed computational fluid dynamics (CFD) model was validated by comparing the experimental data and simulation results in terms of the expansion degree of low-density fine particles and high-density coarse particles at different superficial liquid velocities. The simulation results agreed well with the experimental data, thus validating the proposed CFD mathematical model. The effects of particle size and particle density on the homogeneous or heterogeneous fluidization behaviors were investigated. The simulation results indicate that low-density fine particles are easily fluidized, exhibiting a certain range of homogeneous expansion behaviors. For the large and heavy particles, inhomogeneity may occur throughout the bed, including water voids and velocity fluctuations.

A Model for Vortex Induced Oscillation of Structures

1974 ◽  
Vol 41 (3) ◽  
pp. 581-586 ◽  
Author(s):  
W. D. Iwan ◽  
R. D. Blevins
Keyword(s):  
Experimental Data ◽  
Circular Cylinder ◽  
Analytical Model ◽  
Vortex Shedding ◽  
Fluid Dynamic ◽  
Model Parameters ◽  
Structural Systems ◽  
Dynamic Effects ◽  
Hidden Variable ◽  
Model Predictions

A model is presented for the analysis of the response of structural systems excited by vortex shedding. The model is based on the introduction of a hidden variable to describe the fluid dynamic effects. Model parameters may be determined from experimental data for fixed and forced elements and the model used to predict the response of elastically mounted elements. Analytical model predictions are compared with experimental results for a circular cylinder.

scholarly journals Simulating intervertebral disc cell behaviour within 3D multifactorial environments

2020 ◽  
Author(s):  
L Baumgartner ◽  
J J Reagh ◽  
M A González Ballester ◽  
J Noailly
Keyword(s):  
Experimental Data ◽  
Intervertebral Disc ◽  
Cell Viability ◽  
Mrna Expression ◽  
Collagen Type ◽  
Supplementary Information ◽  
Model Parameters ◽  
Type I ◽  
Cell Behaviour ◽  
Model Predictions

Abstract Motivation Low back pain is responsible for more global disability than any other condition. Its incidence is closely related to intervertebral disc (IVD) failure, which is likely caused by an accumulation of microtrauma within the IVD. Crucial factors in microtrauma development are not entirely known yet, probably because their exploration in vivo or in vitro remains tremendously challenging. In silico modelling is, therefore, definitively appealing, and shall include approaches to integrate influences of multiple cell stimuli at the microscale. Accordingly, this study introduces a hybrid Agent-based (AB) model in IVD research and exploits network modelling solutions in systems biology to mimic the cellular behaviour of Nucleus Pulposus cells exposed to a 3D multifactorial biochemical environment, based on mathematical integrations of existing experimental knowledge. Cellular activity reflected by mRNA expression of Aggrecan, Collagen type I, Collagen type II, MMP-3 and ADAMTS were calculated for inflamed and non-inflamed cells. mRNA expression over long periods of time is additionally determined including cell viability estimations. Model predictions were eventually validated with independent experimental data. Results As it combines experimental data to simulate cell behaviour exposed to a multifactorial environment, the present methodology was able to reproduce cell death within 3 days under glucose deprivation and a 50% decrease in cell viability after 7 days in an acidic environment. Cellular mRNA expression under non-inflamed conditions simulated a quantifiable catabolic shift under an adverse cell environment, and model predictions of mRNA expression of inflamed cells provide new explanation possibilities for unexpected results achieved in experimental research. Availabilityand implementation The AB model as well as used mathematical functions were built with open source software. Final functions implemented in the AB model and complete AB model parameters are provided as Supplementary Material. Experimental input and validation data were provided through referenced, published papers. The code corresponding to the model can be shared upon request and shall be reused after proper training. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

An independent quark model study of weak leptonic decays of pseudoscalar mesons

2015 ◽  
Vol 30 (16) ◽  
pp. 1550092
Author(s):  
S. N. Jena ◽  
P. K. Nanda ◽  
S. Sahoo ◽  
S. Panda
Keyword(s):  
Experimental Data ◽  
Quark Model ◽  
Decay Constant ◽  
Model Parameters ◽  
Decay Modes ◽  
Leptonic Decays ◽  
Model Study ◽  
Pseudoscalar Mesons ◽  
Model Predictions ◽  
Decay Widths

An independent quark model with a relativistic power-law potential is used to study the weak leptonic decays of light and heavy pseudoscalar mesons. The partial decay width and the decay constant for the weak leptonic decay are derived from the quark–antiquark momentum distribution amplitude which is obtained from the bound quark eigenfunction with the assumption of a strong correlation existing between quark–antiquark momenta inside the decaying meson in its rest frame. The model parameters are first determined from the application of the model to study the ground state hyperfine splitting of ρ, K, D, Ds, B, Bs and Bc mesons. The same model with no adjustable parameters is then used to evaluate the decay constants fM and the decay widths of pseudoscalar mesons. The model predictions agree quite well with the available experimental data as well as with those of several other models. The decay constant for pion and kaon are obtained as fπ = 132 MeV and fk = 161 MeV which closely agree with experimental values. But in case of heavier mesons for which experimental data are not yet available, the present model gives its predictions as fBC > fBS > fB, fDS > fD, fD > fB and fπ > fB which are in conformity with most of other model predictions. The model predictions of the corresponding decay widths and the branching ratios for the [Formula: see text] and [Formula: see text] decay modes are in close agreement with the available experimental data.

scholarly journals Sensitivity analysis of timber-concrete composite structures

2018 ◽  
Vol 16 (1) ◽  
pp. 125-134
Author(s):  
Nikola Velimirovic ◽  
Dragoslav Stojic
Keyword(s):  
Sensitivity Analysis ◽  
Composite Structures ◽  
Rank Order ◽  
Equivalent Stress ◽  
Latin Hypercube Sampling ◽  
Simulation Method ◽  
Design Parameters ◽  
Model Parameters ◽  
Design And Optimization ◽  
Stochastic Sensitivity Analysis

The sensitivity analysis could be defined as a study of how the variability of the output parameter of the considered model can be distributed to its sources, actually, on the variability of the various input model parameters. It helps to identify the most important design parameters of a particular structure and to focus on them during the design and optimization process. This paper is focused on the application of stochastic sensitivity analysis of maximum equivalent stress and maximum mid-span deflection of timber-concrete composite beam. All input parameters were considered to be random variables. Latin Hypercube Sampling numerical simulation method was employed. The estimation of the sensitivity was derived from Spearman rank-order correlation coefficient.

Parameters Calibration for Medium Hydraulic Excavator Simulation Model Based on Experimental Data

2013 ◽  
Vol 706-708 ◽  
pp. 1483-1491 ◽  
Author(s):  
An Lin Wang ◽  
Shi Ning Shi ◽  
Jun Huang
Keyword(s):  
Experimental Data ◽  
Genetic Algorithm ◽  
Simulation Model ◽  
Response Surface ◽  
Model Simulation ◽  
Error Function ◽  
Model Parameters ◽  
Hydraulic Excavator ◽  
Unknown Parameters ◽  
Model Based

The authenticity and reasonability of the medium hydraulic excavator simulation model parameters was the foundation to ensure the effectiveness of the simulation model. Based on the bond graph theory, a dynamic simulation model of a medium excavator was established. By the comparison of experimental data and simulation data, the response surface of unknown parameters and the error function of the system model were built. Subsequently, the genetic algorithm was employed to optimize the response surface and obtained optimal value. And then the calibration of the unknown parameters was automatically completed. It was proved that the model simulation curve and with experimental curve fitted better when response surface-genetic algorithm method was used for automatic optimization and calibration of unknown parameters. Furthermore, this method could also function to reduce effectively the number of trials of parameter calibration.

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