Flow-sensitive Analysis Research Articles

Sensitivity analysis of electroosmotic magnetohydrodynamics fluid flow through the curved stenosis artery with thrombosis by response surface optimization

The current numerical investigation focuses on the sensitivity analysis of the pertinent parameters of the electrically conducting fluid (blood) with the suspension of Al2O3 nanoparticles through the constricted arteries in the presence of stenosis, thrombosis and catheter. The mathematical model is developed to simulate the blood flow through the catheterized artery having irregular stenosis at the wall and thrombosis at the centre. The interactions of different physical phenomena like electroosmosis, radiation, Joule heating and a uniform radial magnetic field actuate the fluid flow. The nanoparticles shape effect is taken into account by considering the Crocine model. The governing equations are discretized by employing the Crank-Nicolson scheme, and the graphical portrayals for the impact of significant parameters on the flow characteristics have been devised and discussed. The statistical experiment is designed based on the parametric range of the parameter. The sensitivity analysis is performed on response surfaces after getting the best-fitted response surface relative to each response variable. The WSS profile negatively correlates with hematocrit parameter hm, Hartmann number M and positively related with Debye–Huckel parameter qe, while the reverse trend is observed for the impedance profile. The present work may be helpful in biomedical engineering, such as magnetic resonance angiography (MRA), which creates artery images. The integrated medical imaging and hemodynamic framework assist surgeons and researchers in better understanding the abnormalities caused by cardiovascular diseases and gaining a deeper grasp of the hemodynamic flow and other bodily fluids for surgical restoration.

Probabilistic Power Flow Based Renewable Energy Line Flow Sensitivity Analysis

Probabilistic Power Flow Based Renewable Energy Line Flow Sensitivity Analysis

Response surface optimization for the electromagnetohydrodynamic Cu-polyvinyl alcohol/water Jeffrey nanofluid flow with an exponential heat source

This article examines the sensitivity analysis of Jeffrey fluid flow in the presence of copper nanoparticles with polyvinyl alcohol water serving as the base fluid under the influence of source terms like Joule heating, viscous dissipation, exponential heat source, and Arrhenius activation energy via a non-linear vertically elongating surface of non-uniform thickness. Governing PDEs are first converted into ODEs using a suitable similarity transformation. The resulting coupled ODEs are converted into a system of first-order ODEs and then solved using the shooting iteration technique with the RK-4th order method. The remarkable impacts of numerous parameters like Deborah number, Hartmann number, electric field parameter, thermal and solutal Grashof number, Prandtl and Eckert numbers, exponential heat source parameter, Lewis number, chemical reaction parameter, and activation energy parameter associated with the flow properties are discussed graphically. The effects of various physical parameters and the dependence of the response factors on the input parameter are explored using an experimental design and sensitivity analysis based on Response Surface Methodology. Response Surface Methodology is utilized to determine the output response variables of model dependencies, such as the drag coefficient and Nusselt number on the independent input parameters, namely the electric field parameter and Deborah numbers for the drag coefficient, and electric field parameter, thermophoresis diffusion parameter, and exponential heat source parameter for the Nusselt number. Local Nusselt number enhances with increment in the electric field parameter and thermophoresis diffusion parameter values, whereas it decelerates with the rise in exponential heat source parameter. The non-Newtonian nanofluids have proven their great potential in thermal transportation which has a diverse range of applications in thermal energy technologies such as lubrication, natural gas networks, spray processes, and cooling of nuclear reactors, spinning of fibers, cryopreservation, drawing of copper wires, nano-drug delivery, electronics, and many more.

Sensitivity analysis for subcooled flow boiling using Eulerian CFD approach

This paper presents capability of Eulerian CFD (Computational Fluid Dynamics) approach using sensitivity-analysis-based model to predict subcooled boiling flows in the DEBORA experiment, the conditions corresponding to those in PWRs (Pressurized Water Reactors). The main feature of the developed model is a good estimation of the void fraction distribution in a cross section of a heated pipe, not only in the lower void regime but also in the high void regime (>0.5), which is achieved by modifying the lift force coefficients in the model developed by Baglietto’s group. In addition, the Sauter diameter profile is well predicted by employing the MUSIG population balance model, in which the coalescence and breakage factors are tuned to the experiments. A nucleation site density model recently proposed by Li is employed together with the Tolubinsky and Kostanchuk bubble departure diameter model, whose coefficient is again obtained via a sensitivity analysis. The model developed in this work, CTU-PSI model, is expected to be applied to boiling flow simulations in PWRs.

Parametrization of Eddy Mass Transport in the Arctic Seas Based on the Sensitivity Analysis of Large-Scale Flows

The characteristics of eddy mass transport are estimated depending on the values of the parameters of a large-scale flow that forms under the conditions of the shelf seas in the Arctic. For this, the results of numerical simulation of the Kara Sea with a horizontal resolution permitting the development of mesoscale eddies are used. The multiple realizations of eddy mass flux resulting from a numerical experiment are considered as a statistical sample and are analyzed using methods of sensitivity study and clustering of sample elements. Functional dependencies are obtained that are closest to the simulated distributions of quantities. These expressions make it possible, within the framework of large-scale models, to evaluate the characteristics of the cross-isobathic eddy mass transport in the diffusion approximation with a counter-gradient flux. Numerical experiments using the SibCIOM model showed that areas along the Fram branch of the Atlantic waters trajectory in the Arctic as well as the shelf of the East Siberian and Laptev seas with adjacent deep water areas are most sensitive to the proposed parametrization of eddy exchanges. Accounting for counter-gradient eddy fluxes turned out to be less important.

Sensitivity analysis of the nanofluid flow over a stretching flat surface

Sensitivity analysis of the nanofluid flow over a stretching flat surface

Analysis on pressure anomaly within PEMFC stack based on semi-empirical and flow network models

Flow distribution within proton exchange membrane fuel cell (PEMFC) stacks is an important factor in affecting cell performance. In the present study, a coupled stack model is developed based on a flow network model and a semi-empirical model. The frictional and local losses due to two-phase flow, reactant consumption, diverging, and converging are considered in the flow network model. The effectiveness of the coupled model is validated by the experimental polarization curve and pressure drop of a 30-cell PEMFC stack with the U-type configuration. Flow distribution, sensitivity analysis, and pressure anomaly within the stack are investigated through simulation results. The results show that the overall pressure drop of the stack is mainly affected by channel parameters of length, width, and height. Besides, the appearance of pressure anomaly leads to lower performance and larger pressure drop among cells. The pressure distribution among cells is almost unchanged although the voltage of anomalous cells is much lower than that of normal cells. In addition, the anomalous cells perform worse with the increase of anomaly extent. Nevertheless, the increase in the number of anomalous cells can enhance the voltage of the single anomalous cell by sharing the adverse influence aroused by pressure anomaly.

A sensitivity analysis of MHD nanofluid flow across an exponentially stretched surface with non-uniform heat flux by response surface methodology

The current study investigates the MHD flow of nanofluid across an elongating surface while taking into account non-uniform heat flux. For this, we have considered the flow of a boundary layer over a stretched sheet containing (water-based) Al2O3 nanoparticles. The convective boundary conditions for temperature have been invoked. The flow created by a surface that is exponentially expanding in the presence of a magnetic field and a non-uniform heat flux has been mathematically formulated by using laws of conservation. Transformed non-dimensional systems of governing equations have been analyzed numerically by using Adam’s Bashforth predictor corrector approach. The effects of emerging parameters on the fluid velocity and temperature profiles have been further described by plotting graphs. An experimental design and a sensitivity analysis based on Response Surface Methodology (RSM) are used to examine the effects of various physical factors and the dependence of the response factors of interest on the change of the input parameter. To establish the model dependencies of the output response variables, which include the skin friction coefficient and the local Nusselt number, on the independent input parameters, which include the magnetic field parameter, the nanoparticle volume fraction, and the heat transfer Biot number, RSM is used. On the basis of statistical measures such as Q - Q residual plots, adjusted and hypothesis testing using p values, it is observed that both of our models for Skin Friction Coefficient (SFC) and the Local Nusselt Number (LNN) are best fitted. Further, it is concluded that the sensitivity of the SFC, as well as the LNN through heat transfer Biot number, is greater than that of nanoparticle volume fraction and magnetic field parameter. The SFC is sensitive to all combinations of the input parameters. At high levels of heat transfer Biot number, the LNN displays negative sensitivity via magnetic field parameters.

Adjoint-based sensitivity analysis of viscoelastic fluids at a low deborah number

This work performs an adjoint-based sensitivity analysis of a viscoelastic fluid flow around a cylinder in a confined channel. The viscoelastic behavior of the fluid is modeled by the Oldroyd-B constitutive equation and the quantity of interest of the flow is set to the resistance of the cylinder. A set of continuous adjoint governing equations is formulated to quantify the local sensitivities of rheological model parameters on the drag of the cylinder. The adjoint equations are solved together with the original resistance prediction problem, at the Deborah number 0.5. Final outcomes are the field resistance-sensitivity maps for the Oldroyd-B model parameters that imply the local relative importance of different underlying physical mechanisms reflected in the model parameters. In particular, the sensitivity map of relaxation parameter distinguishes two opposing effects of fluid elasticity to resistance of the cylinder depending on the location. While the fluid elasticity near the top and bottom surfaces reduces the resistance, it works adversely near the front and back surfaces. The example illustrates how adjoint-based sensitivity analysis can be utilized for developing effective flow control strategies in many applications working with viscoelastic fluids.

Numerical study and sensitivity analysis of two-phase oil-water flow and heat transfer in different flowline orientations using OpenFOAM

Evaluating the oil-water temperatures in flowlines is demanding mostly in deep offshore applications where flow assurance issues and dramatic heat transfer are anticipated to occur. Consequently, a 3-D mathematical model of oil-water Newtonian flow under non-isothermal conditions is established to investigate the mechanisms of the two-phase oil-water transportation and heat transfer in horizontal and inclined flowlines. In this study, a non-isothermal two-phase flow model is first modified and then implemented in the InterFoam solver by introducing the energy equation using OpenFOAM® code. The Low Reynolds Number (LRN) k-ε turbulence model is employed to resolve the turbulence phenomena within the oil and water mixtures. The flow patterns, local heat transfer coefficients (HTC), and relative errors for two-phase oil-water flow at different flowline orientations (0o, +4o, +7o) are compared with the experimental literature results. The model was also employed to ascertain the effect of input water cuts and flowline inclinations on the flow regimes, and the results were validated in literature with a high accuracy level. Global sensitivity analysis is then conducted to determine the effect of the different parameters on the output temperature and pressure of the produced two-phase hydrocarbon systems. Subsequently, HTC and flow patterns for oil-water flows at different inclinations of −10o, -4o, and +10o can be predicted by the model. The velocity distribution, liquid holdup, pressure gradient, and temperature variation at the flowline cross-sections are simulated and analyzed extensively.

Experimental and modeling study of acetone combustion

The pyrolysis and oxidation of acetone were studied using three complementary experimental setups. Jet-stirred reactor experiments were performed at four equivalence ratios (ϕ = 0.5, 1, 2, and ∞), at pressure of 1.067 bar (800 Torr) and over the temperature range of 700–1200 K for pyrolysis and 600–1150 K for oxidation. The decomposition of acetone starts around 800 K with a conversion rate of 50% obtained around 1000 K in both pyrolysis and oxidation studies. The main stable products detected in both conditions are small hydrocarbons (methane, ethane, and ethylene), with also acetaldehyde, CO and CO2 for oxidation. Oscillation behavior was detected beyond 1000 K under oxidation conditions and the products were followed with on-line mass spectrometry. Ignition delay times were measured using a rapid compression machine at pressures of 20 and 40 bar under non-diluted stoichiometric conditions over the temperature range 850–1100 K. The ignition delay times measured in the present study, combined with shock tube data of literature, exhibit a slight inflexion to the Arrhenius behavior, but no negative temperature coefficient. Laminar burning velocities were measured using a flat flame burner at atmospheric pressure for three fresh gas temperatures: ambient temperature, 358 and 398 K. A detailed kinetic model of the combustion of acetone including 852 species and 3265 reactions was developed. This new kinetic mechanism predicts relatively well the experimental measurements of ignition delay times, the mole fraction of the products in the jet-stirred reactor including oscillations and laminar burning velocities. Related flow rate and sensitivity analysis are also presented providing new insights into the acetone reaction network.

Modelling of pore pressure evolution in a compressional tectonic setting: The Kuqa Depression, Tarim Basin, northwestern China

The Kuqa Depression is part of a Mesozoic-Cenozoic foreland basin located at the northern margin of the Tarim Basin. High fluid overpressures were reported in the Mesozoic section related to both the complex tectonic evolution and the sealing by the salt-bearing sequence within the Paleogene Kumugeliemu Group. The role of structural evolution and compressional shortening in the generation of overpressures is poorly understood and requires a model-based understanding of the basin structure for different time steps. Structurally restored geometries based on a present-day geological section interpreted from a 2D seismic line, has been used as input for a basin and petroleum system model to simulate pore pressure history through geological time. In this simulation, we demonstrate structural dependencies of pore pressure development, and examine the impact of disequilibrium compaction, tectonic compression, opening and closing of faults over time, as well as folding on overpressure evolution. The poroelastic model is used to quantitatively evaluate the contribution of horizontal shortening due to tectonic compression on overpressure. We found that the pressure increase caused by 12.5% shortening can account for a maximum of more than 60% of overpressure, depending on lithology and deformation strength. We also simulated the effect of salt content within the seal layer on overpressure and found that the increase in salt has promoted the onset time and magnitude of overpressure in the underlying strata, which favors porosity preservation. A heat flow sensitivity analysis was performed, suggesting that the pressure increase caused by extremely high heat flow is rather low.

Sensitivity analysis for Rabinowitsch fluid flow based on permeable artery constricted with multiple stenosis of various shapes

Sensitivity analysis for Rabinowitsch fluid flow based on permeable artery constricted with multiple stenosis of various shapes

Sensitivity analysis of a swirling flow to the GEKO model

Accurate numerical models for hydraulic turbine applications are highly coveted. They must be able to correctly capture the swirling flow found at off-design operating conditions in the turbine draft tube. The GEKO model is a relatively fast and flexible eddy viscosity turbulence model with adjustable coefficients to tune the model to different flow scenarios. In this study, the GEKO model is tested on a swirling flow inside a diffusor similar to the flow conditions found at part-load operation of a propeller turbine. The diffusor investigated corresponds to the Porjus U9 draft tube cone section, including the runner cone. Results showed that the near-wall coefficient, with a value of 2, increased the wall shear stress and moved the separation point from the runner cone further downstream. Moreover, with a value of 0.7, the separation coefficient increased the eddy viscosity, which also moved the separation point from the runner cone further downstream. Both coefficients gave velocity profiles closer to experimental values and increased the swirl number at the outlet of the diffusor by up to 36.9 % compared to the GEKO default model. Overall, the near-wall coefficient with a value of 2 gave the best results. The GEKO model provides an opportunity to tweak numerical models to swirling flow.

Receptivity and sensitivity analysis of Jeffery-Hamel flow

Receptivity and sensitivity analysis of Jeffery-Hamel flow

Water Balance Evaluation for Flood Risk Reduction in the Yala River Basin, Western Kenya

The Yala River Basin (YRB) in Western region of Kenya has in the past experienced climate and weather extreme events that include floods. Floods have triggered loss of lives, destruction of property, outbreak of water borne diseases and siltation of arable land. This study utilized the Nedbør-Afstrømnings-Model (NAM) hydrologic model (available in the NAM Module of the MIKE 11 hydrodynamic model) on the Yala River Basin (YRB) to generate flood flows for water balance evaluation. The study utilized satellite imagery data for the period 1984-2010 sourced from the Regional Centre for Mapping of Resources for Development, rainfall (1980-2012) and river discharge (1947-2012) data sets from the Kenya Meteorological Department (KMD) and the Water Resources Management Authority (WARMA), respectively. Data quality control was statistically checked before sensitivity analysis, calibration, validation, and simulation of the flood flows. Daily water balance estimates for the Yala River Basin (YRB) over the period 1980-2010 were developed using the NAM hydrologic model. The results indicate that the mapped flood area extent varied by a value of 34.23 km2 over the period 1980-2010. The Yala River Basin (YRB) indicated an estimated inflow value of 4,814.72 MCM and outflow value of 4,578.23 MCM, with a coefficient of determination of 0.867. The difference between the inflow and outflow values was 236.49 MCM, that formed the flood flow or the water balance. This study concluded that the water balance value of 236.49 MCM was responsible for the floods recorded in the Yala River Basin (YRB) for the period 1980-2010, and it should be taken care of through flood risk reduction initiatives.

Real-time and consistent sparse estimation of power system distribution factors using online adaptive elastic-net

Distribution factors (DFs) are vital for power system monitoring and secure operation. However, it is challenging to accurately estimate dominant DFs while promoting the sparsity of DFs in real time, especially in large-scale power systems with high-dimensional data. This paper proposes a novel Online Adaptive Elastic-net (AdaEnet) method to address this challenge, which allows the real-time and consistent sparse estimation of DFs in large-scale power systems. The problem is formulated as a sparse regression problem using data measured by phasor measurement units. The AdaEnet estimator is advocated to promote the sparsity of DFs, and a LARS-AdaEnet algorithm is developed for the real-time estimation of DFs. Thanks to the oracle properties and the grouping effect of the AdaEnet, the method yields unbiased dominant estimates with stability to collinear predictor variables, even for underdetermined systems. Moreover, due to the online updated adaptive weights and the early-stopping property of the LARS-AdaEnet, the method efficiently solves the estimator using only a few latest samples. Test results on the IEEE 300- and the Polish 3375-bus systems demonstrate that the proposed method achieves high estimation consistency and real-time adaptability in the presence of high-dimensional data (i.e., massive collinear predictor variables of small sample size). Hence this method promotes the data-driven, sparsity-aware, and computationally efficient sensitivity analysis of active power line flows in large-scale power systems. It can broadly facilitate real-time situational awareness and decision-making for improving power system security.

Uncertainty propagation and sensitivity analysis of three-phase flow in porous media using polynomial chaos expansion

In this study, polynomial chaos expansion (PCE) will be utilized to investigate propagation and evolution of uncertainty from uncertain model parameters to model outputs. Unknown PCE coefficients are calculated using probabilistic collocation method (PCM), which is a non-intrusive technique. The proposed approach is evaluated on a 2D reservoir under three-phase flow condition. By use of PCEs, dependent model outputs, such as well bottomhole pressure and production rates, are represented as functions of uncertain model parameters, including parameters defining the capillary pressure (Pc) and relative permeability (kr) curves. Accuracy, compatibility and efficiency of the proposed approach are compared with Monte Carlo (MC) method, which is considered as the reference case. Mean values, standard deviations and histograms for well bottomhole pressure and production rates estimated from the PCM-based PCE are closely matched to those obtained from MC method. This discloses the fact that the proposed approach can successfully restore the simulation model to represent propagation of uncertainty from uncertain model parameters toward model outputs and to perform sensitivity analysis (SA). Unlike the MC approach which requires an extremely large number of realizations to obtain accurate results, the PCM-based PCE requires to perform model evaluations only at the selected collocation points, thus the computational cost is significantly reduced. Subsequently, using the proposed PCE as the surrogate model of the reservoir, Sobol's sensitivity indices are calculated analytically. Results of SA reveal that those parameters defining Pc curves have negligible effect on the model outputs compared with those parameters defining kr curves, and thus may be ignored during history matching process. Moreover, it is observed that the effects caused by interactions between uncertain kr and Pc parameters have negligible contribution compared to the individual effect of each parameter.

A novel parametric coupled pressure and temperature inversion method for combined perforation and well test system

Combined perforation and well test system is commonly used in oil and gas fields, especially in reservoirs with low energy and transmissibility. For the conventional inversion method in a combined perforation and well test system, only the pressure data are used to perform the type curve matching, with the variation in temperature being neglected. This may complicate the matching procedure and result in errors in the inversion results. Thus, we proposed a new inversion method in this study, where the gas volume and flow rate terms substituted the pressure and pressure derivative terms to perform type curve matching. This was because the variation in gas volume coupled the variations in pressure and temperature. To make the type curve matching feasible, on the one hand, we need the type curves that depict dimensionless gas volume and flow rate; on the other hand, the field data of pressure and temperature should also be transformed into gas volume and flow rate data, which are the core contents of this paper. A corresponding mathematical model is established and the analytical solutions of gas volume and flow rate are derived with the Laplace transformation. Based on the solutions, the flow regimes analysis and sensitivity analysis on controlling parameters are conducted. Next, a workflow that can convert the pressure and temperature data into gas volume and flow rate data is proposed. Last, the application on a well from Puguang gas field is presented to show the feasibility of our method. Results show that our method successfully interpret the field data comparing to the conventional method that only uses the pressure data. Moreover, comparisons between the results of our method and other field data calibrate the reliability and accuracy of our method.

Sensitivity analysis of intercity public passenger flow based on prospect theory

The contradiction between traffic supply and demand in different periods of intercity transport corridor becomes increasingly prominent, and there is a large waste of transportation resources. In order to analyze the passenger flow sensitivity for different modes of transportation at different periods of time under the change of high-speed railway ticket price, a generalized travel prospect cost minimum assignment model is constructed. Then, the passenger flow of different travel modes in each period of the intercity passenger transport corridor is calculated, the passenger flow sensitivity model and the sensitivity rate model are also constructed. Taking Tianjin-Beijing intercity passenger transport corridor as a case study, the results show that when the ticket price reduces, the passenger flow sensitivity change rate of each mode in each period increases linearly. The increase of ticket price has little influence on all modes of transportation in each period. In the same range of ticket price fluctuation, the sensitivity of passenger flow of high-speed railway is the largest when the ticket price changes in the period of negative supply-demand balance, and the sensitivity of passenger flow corresponding to the reduction of ticket price is about twice that of passenger flow corresponding to the increase of ticket price. The research work provides a theoretical reference for optimizing the traffic structure of Tianjin-Beijing intercity passenger transport corridor.