Complex Flow Research Articles

Investigating the role of thrombosis and false lumen orbital orientation in the hemodynamics of Type B aortic dissection

While much about the fundamental mechanisms behind the initiation and progression of Type B aortic dissection (TBAD) is still unknown, predictive models based on patient-specific fluid-structure interaction (FSI) simulations can help in risk stratification and optimal clinical decision-making. Aiming at the development of personalized treatment, FSI models can be leveraged to investigate the interplay between complex aortic flow patterns and anatomical features, while considering the deformation of the arterial wall and the dissection flap. In this study, the hemodynamics of false lumen thrombosis, a large fenestration, and the orbital orientation of the false lumen is studied through image-based FSI simulations on three TBAD patient-specific geometries. A new pipeline is developed leveraging the open-source software SimVascular and ParaView to analyze multiple patients simultaneously and to achieve large-scale parallelization in FSI results based on patients’ computed tomography (CT) images. The results of this study suggest that the internal orbital orientation of the false lumen contributes to maintaining a positive luminal pressure difference ΔPTL-FL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta P_{TL-FL}$$\\end{document} = PTL-PFL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P_{TL}-P_{FL}$$\\end{document} between the true lumen (TL) and the false lumen (FL), despite an impingement area in the false lumen near the entry tear. A positive and high luminal pressure difference is thought to promote TL expansion and FL compression. Moreover, it was also found that FL thrombosis at the entry tear region reduce the magnitude of the negative luminal pressure difference, which in turn may reduce FL expansion and the risk of unstable aortic growth. Finally, this FSI study suggests that the aortic wall and dissection flap stiffness determines the effects of a large fenestration in the descending thoracic aorta on the luminal pressure difference.

Relativistic BEC extracted from a complex FRG flow equation

Abstract Based on the functional renormalization group (FRG) under the local potential approximation, we analyze the Bose-Einstein condensation (BEC) in the relativistic complex scalar theory. This framework leads to a complex flow equation of the effective potential, even with the well-known Litim regulator. In order to evaluate the condensate from such a complex effective potential, we impose a condition between chemical potential and mass, analogously to those in the free theory or the mean field theory. We elucidate that for the strongly (weakly) coupled theory, the phase diagrams computed from the FRG are more (less) deviated from that under the mean field approximation. This result implies that quantum fluctuations strongly affect the nonperturbative formation of the BEC.

Heterogeneous Online Computational Platform for GEM-Based Plasma Impurity Monitoring Systems

The fusion energy research field presents many intricate challenges that require resolution. Many diagnostic systems employed in experiments are approaching the limits of current technology. Implementing efficient measurements requires using an appropriate set of tools to facilitate the optimal utilization of hardware. Fusion energy measurements must provide low latency processing with the capacity for future improvements and the ability to handle complex data flows efficiently. The presented work addresses these requirements and describes the implementation of a high-performance, low-latency software platform with convenient development for soft X-ray (SXR) plasma impurities emission tracing—the Asynchronous Complex Computation Platform (AC2P). This article presents the architectural design, implementation details, and performance and latency measurements based on the raw data acquired from the WEST tokamak and laboratory tests. AC2P provides the tools to develop low-latency, multi-core, multi-device complex data flow graph scale-up solutions for measuring impurities in hot plasmas. The system has been designed to operate online during experiments, calculate the energy distribution, position and occurrence time of SXR photons, monitor the data stream’s quality and archive any abnormalities for subsequent offline verification and algorithm improvement. This article presents AC2P, which operates as part of the SXR measurement system on the WEST tokamak.

Qualitative Analysis of the Heat Transfer in a Package of Square Steel Sections

During the heat treatment of square or rectangular steel sections, a heated charge, arranged in regular packages, is placed inside a furnace. This type of charge forms a porous medium through which a complex heat flow occurs during heating. Several heat transfer mechanisms act simultaneously within this medium: conduction through the section walls, conduction and natural convection within the gas, thermal radiation between the section walls, and complex heat transfer (mainly contact conduction) at the joints between the adjacent sections. This article presents a qualitative analysis of heat transfer, aiming to determine the contribution of individual heat transfer mechanisms to the overall process. For this purpose, an analytical model of complex heat transfer within the package was employed, based on the thermo-electric analogy. The results from experimental studies were used to calculate the natural convection and heat transfer at the joints. It was assumed that the material of the sections was low-carbon steel, and the gas was air. Calculations were performed for the temperature range of 25 °C to 700 °C, considering three different geometrical configurations of the sections. It was shown that the effective thermal conductivity (ETC) of the package for the considered geometrical cases varies between 2.2 and 10.6 W/(m·K), which is an order of magnitude lower than the thermal conductivity of the individual sections. This parameter increased dynamically with the temperature. Moreover, the heat transfer intensity within the package of sections was nearly an order of magnitude lower than the heat conduction observed in a solid steel charge. Additionally, it was shown that the primary heat transfer mechanisms governing the heating process were thermal conduction (in the lower temperature range—up to approximately 350 °C) and thermal radiation (in the higher temperature range—above 350 °C). The gas convection inside the sections had a minimal impact on the heating process of the package. The primary parameters influencing the quality of the results were the joint resistance between the adjacent sections and the emissivity of the sections. The presented model can be used for the optimization of heat treatment processes for the considered charge.

Effect of soft magnetic particles content on multi-physics field of magnetorheological composite gel clutch with complex flow channel excited by Halbach array arrangement

In this paper we investigate the influence of soft magnetic particle mass fraction on the multi-physics field of proposed magnetorheological (MR) gel clutch. A novel MR gel clutch with complex cup-shaped gap is described, whose performance is based on the relative placement between Halbach array arrangement and MR gel. Smart MR gel with 40 wt%, 50 wt%, 60 wt%, 70 wt% and 80 wt% of soft magnetic particles used as the transfer medium and Halbach array is adopted as magnetic excitation system. Its magnetic/mechanical analysis is carried out based on Bingham-plastics model using COMSOL Multiphysics software, which takes into account the variation of dynamic viscosity with magnetic flux density. The distribution of the magnetic flux density, shear yield stress, post-yield viscosity, shear stress and torque in the four flow channels during the transition from engagement state to disengagement state are obtained and analyzed in detail. Multi-physics field characteristics of proposed MR gel clutch with five kinds of MR gels are studied and compared in order to give some useful suggestions in the design phase. Finally, the dynamic torque of the MR clutch with different MR gel is experimentally evaluated.

Numerical investigation of spindle position effects on steam ejector performance with a nonequilibrium condensation model

AbstractThis research studied the performance of a spindle‐controlled steam ejector using models such as ideal gas and wet steam under various operating conditions based on computational fluid dynamics (CFD). A wet steam model incorporating nonequilibrium condensation was employed to simulate the complex flow phenomena within the ejector. The structure of the flow, entrainment ratio (Er), and shock wave characteristics of the steam ejector were examined in two different models. Results indicate that the spindle position has a substantial impact on steam ejector performance. For the ideal gas and wet steam models, the optimal spindle position (SP‐5) at a .1 MPa motive pressure achieves the highest entrainment ratios (Er) of 1.01 and 1.042, respectively. However, an ejector with a fixed geometry achieves Er values of only .517 and .549 for the ideal gas and wet steam models, under identical working conditions. This represents a substantial improvement of 89.8% over the fixed‐geometry ejector. The wet steam model consistently predicts 2%–4% higher Er values compared with the ideal gas model across all spindle positions. The study also reveals that increasing the motive pressure from .1 to .3 MPa reduces Er by up to 45.8% at the optimal spindle position, with the shock train length extending to 35% of the mixing chamber at .3 MPa. These findings offer insights for improving the design and optimization of variable‐geometry steam ejectors, potentially increasing efficiency in industrial applications.

The Potential of Sound Analysis to Reveal Hemodynamic Conditions of Arteriovenous Fistulae for Hemodialysis.

Arteriovenous fistula (AVF), the preferred vascular access for hemodialysis, is associated with high failure rate. The aim of this study was to investigate the potential of AVF sound auscultation in providing quantitative information on AVF hemodynamic conditions. This single-center prospective study involved six patients with native radio-cephalic AVFs who underwent multiple follow-up visits. Doppler Ultrasound blood flow volume (BFV) assessment and electronic stethoscope-based sound recordings were performed during each visit, whereas MRIs were acquired 3days, 3weeks and 1year after surgery. Computational fluid dynamic (CFD) simulations were performed on patient-specific MRI-derived geometrical models. Higher values of median peak amplitudes ratios (high-low peak ratio-HLPR) were found to be associated with complex blood flow and velocity streamlines recirculation at systolic peak, and corresponding extended regions of high oscillatory shear index (OSI). On the contrary, lower values of HLPR were associated with laminar flow pattern and low values of OSI. Significant differences were observed in HLPR between subgroups with extended or limited areas with OSI > 0.1 (0.67 vs 0.31, respectively). Significant relationships were found between AVF sound intensity and brachial BFV (slope = 0.103, p < 0.01) as well as between longitudinal changes in brachial BFV and HLPR (slope = - 0.001, p < 0.01). Our results show that AVF sound can be exploited to extract fundamental information on AVF hemodynamic conditions, providing indication of the presence of complex hemodynamic and adequate BFV to perform hemodialysis. Sound analysis has therefore the potential to improve clinical AVF surveillanceand to ameliorate outcome.

A study on the internal vortex structure within a single-blade pump via numerical methods and particle image velocimetry experiments

This study investigates the performance and internal flow characteristics of a single-blade centrifugal pump through a comprehensive analysis integrating performance tests, Particle Image Velocimetry (PIV) tests, and numerical simulations. Across the operational speed range of 1470–2940 rpm, the predicted pump (head-flow rate curve)performance error between the numerical simulation results and the test results of the pump underrated flow conditions is found to be only 3.4%, demonstrating the high accuracy of the selected numerical method in predicting both performance metrics and internal flow structures. Key findings highlight the presence of significant circumferential and axial secondary flows in the region where the blade wraps back, resulting in the formation of high-intensity vortex structures and subsequent energy dissipation. The interaction of the blade's trailing jet with the volute casing's tongue induces periodic changes in the intensity and spatial size of these vortex structures. Furthermore, pronounced reverse vortex pairs are identified within the volute casing, attributed to axial non-uniformity in impeller outflow. These vortex pairs are associated with the preferential accumulation of solid particles, potentially contributing to wear in the volute casing of single-blade centrifugal pumps. The revelation of the evolution characteristics of vortex structure in single-blade centrifugal pumps provides theoretical support for reducing pressure pulsation and radial force of single-blade centrifugal and provides a potential solution to the technical difficulties of low efficiency and poor stability of single-blade centrifugal pumps. Overall, this study provides valuable insights into optimizing the design and operational efficiency of single-blade centrifugal pumps by elucidating their complex flow dynamics and performance characteristics under varying operational conditions.

Study on characteristics and prediction of the pressure drag of the swept strut under supersonic wide-range conditions

In this paper, the numerical simulation of the swept strut ramjet combustor was carried out under wide-range conditions (Ma3 = 1.8 ∼ 5.0), and the pressure drag characteristics of the swept strut were discussed. The results show that the pressure drag characteristics of the swept strut are related to the Mach number of the combustor inlet and the swept angle of the strut. The decreased boundary of the strut pressure drag coefficient gradually advances with the decrease of the Mach number of the combustor inlet. When Ma3 = 1.8 ∼ 2.0, the pressure drag reduction boundary is α = 15°. When Ma3 = 2.2 ∼ 2.8, the pressure drag reduction boundary is α = 45°. When Ma3 = 3.0 ∼ 4.0, the pressure drag reduction boundary is α = 60°. When Ma3 = 5.0, the pressure drag reduction boundary is α = 65°. In addition, with the decrease of the Mach number of the combustor inlet, the pressure drag reduction performance benefit brought by increasing the swept angle of the strut will gradually increase. Furthermore, a pressure drag coefficient prediction model suitable for wide-range conditions and multiple configurations of swept struts was proposed based on deep learning. The prediction model consists of two parts in series, which includes the prediction model of the surface pressure coefficient of the swept strut based on multilayer perceptron (MLP) and the prediction model of the pressure drag coefficient of the swept strut based on convolutional neural network (CNN). To improve the prediction accuracy of the MLP model, new training samples were added based on the ensemble-based uncertainty quantification, and the improved MLP model was obtained by retraining. The results show that both the two prediction models have high prediction accuracy under the effect of multiple complex flow characteristics on the strut. The results of this study are helpful to provide a reference for the aerodynamic drag reduction design of the strut in the wide-speed supersonic combustor.

Enhancing high-resolution reconstruction of flow fields using physics-informed diffusion model with probability flow sampling

The application of artificial intelligence (AI) technology in fluid dynamics is becoming increasingly prevalent, particularly in accelerating the solution of partial differential equations and predicting complex flow fields. Researchers have extensively explored deep learning algorithms for flow field super-resolution reconstruction. However, purely data-driven deep learning models in this domain face numerous challenges. These include susceptibility to variations in data distribution during model training and a lack of physical and mathematical interpretability in the predictions. These issues significantly impact the effectiveness of the models in practical applications, especially when input data exhibit irregular distributions and noise. In recent years, the rapid development of generative artificial intelligence and physics-informed deep learning algorithms has created significant opportunities for complex physical simulations. This paper proposes a novel approach that combines diffusion models with physical constraint information. By integrating physical equation constraints into the training process of diffusion models, this method achieves high-fidelity flow field reconstruction from low-resolution inputs. Thus, it not only leverages the advantages of diffusion models but also enhances the interpretability of the models. Experimental results demonstrate that, compared to traditional methods, our approach excels in generating high-resolution flow fields with enhanced detail and physical consistency. This advancement provides new insights into developing more accurate and generalized flow field reconstruction models.

An algorithm for the incorporation of relevant FVM boundary conditions in the Eulerian SPH framework

The finite volume method (FVM) is widely recognized as a computationally efficient and accurate mesh-based technique. However, it has notable limitations, particularly in mesh generation and handling complex boundary interfaces or conditions. In contrast, the smoothed particle hydrodynamics (SPH) method, a popular meshless alternative, inherently circumvents the challenges of mesh generation and yields smoother numerical outcomes. Nevertheless, this approach comes at the cost of reduced computational efficiency. Consequently, researchers have strategically combined the strengths of both methods to investigate complex flow phenomena, producing precise and computationally efficient outcomes. However, algorithms involving the weak coupling of these two methods tend to be intricate and face challenges regarding versatility, implementation, and mutual adaptation to hardware and coding structures. Thus, achieving a robust and strong coupling of FVM and SPH within a unified framework is essential. A mesh-based FVM has recently been integrated into the SPH-based library SPHinXsys. However, due to the differing boundary algorithms between these methods, the crucial step for establishing a strong coupling of both methods within a unified SPH framework is to incorporate the FVM boundary algorithm into the Eulerian SPH method. In this paper, we propose a straightforward algorithm within the Eulerian SPH method, which is algorithmically equivalent to that in FVM and based on the principle of zero-order consistency. Moreover, several numerical examples, including compressible and incompressible flows with various boundary conditions in the Eulerian SPH method, demonstrate the stability and accuracy of the proposed algorithm.

Benchmark Simulation of Laminar Reactive Micromixing Using Lattice Boltzmann Methods

Micromixers are chemical processing devices with complex flow patterns applied for both mixing and reaction of chemical species. In current research, laminar reacting multicomponent flows are considered. Despite the laminar streaming regime (e.g., Re = 186), there exist secondary flow microstructures. For this setup, accurate predictions of those structures are possible with a large-eddy simulation on a fine mesh resolving till the Batchelor microscales. Utilizing the open-source lattice Boltzmann method (LBM) framework, OpenLB, a benchmark simulation of the reacting micromixer, is re-established with new, more precise computation results. In this context, a Schmidt-number-based stabilization method for LBM-discretized reactive advection–diffusion equations by laminar secondary flow structures is used. A convergence study is performed, which is also a novelty. All computations have been performed on the high-performance computing cluster HoreKa using up to 160 NVIDIA A100 graphics processing units.

An entropy measure-based study on flow pattern of gas-liquid two-phase flow in a U-Tube

U-tubes are widely applied in gas-liquid two-phase transportation in chemical engineering. The diverse flow patterns within these tubes significantly affect the pressure loss, heat transfer efficiency, and even the fluid-induced vibration amplitude of the tubes. This study explores the complex flow pattern features in a U-tube in a vertical plane and focuses on recognizing them. For the acquisition and classification of flow patterns, a Computational Fluid Dynamics (CFD) model for gas-liquid two-phase flow is first established, and its quantitative calculation error is ensured to be less than 5%. Then, the spatiotemporal evolution characteristics of flow patterns is analyzed. The real-time pressure drop response is chosen as the representation signal, and its nonlinear features in the time and frequency domain under different flow patterns are explored. A nonlinear time series is constructed by extracting a segment from the real-time pressure drop data, and six entropy measures are applied to analyze and identify them. Finally, the sensitivity of entropy measures to both the time series lengths and the tested sections are evaluated. Results show that there are six typical flow patterns in a U-tube. According to most entropy measures, the bubble flow has the highest complexity; however, the plug flow presents the lowest complexity. In the U-bend, pressure drop signals for the bubble and annular flows show random fluctuations within a specific range, in contrast to the marked periodicity in plug flow signals, while wavy and slug flows exhibit intermittent peak values. Including the upstream and downstream straight pipes in the analysis, rather than focusing solely on the U-bend, significantly increases the complexity of the stratified, plug, and slug flows. Fuzzy entropy is an effective tool for identifying the six flow patterns, demonstrating good resilience to variations in the length of the data series. This characteristic makes it highly useful for real-time identification of flow patterns in the U-bend sections of non-transparent U-tubes, offering considerable potential in chemical equipment.

Preventing scour of monopile foundations using a vertical rotation device

Scour around monopile foundations is a major cause of offshore wind turbine failures, necessitating effective scour prevention measures to ensure the reliability of monopiles. This study investigates a new scour prevention strategy utilizing a vertical turbine rotor. This measure can not only effectively reduce scour around monopile foundations in complex flow field environments but also generate clean electricity, adding value. The effectiveness of the device in mitigating scour is evaluated through experiments. Subsequently, the impact of the flow field around the pile foundation and the seabed shear stress are examined using numerical simulations. The influence of the device’s installation position on seabed shear stress is also discussed. The results indicate that the vertical rotating device significantly reduce scour around the pile foundation, thereby enhancing the reliability of monopile foundations.

Comprehensive Experimental Assessment Of Unsteady Pressure And Heat Flux In A Small-Core Turbine Over-Tip Shroud

Abstract For novel high-speed small core turbines, with tip clearance below 0.5mm, even small blade-to-blade tip clearance variation is significant. The assessment of these complex flows is pertinent to the design of the next generation of small-core turbines. This manuscript provides a thorough experimental analysis of the shroud?s unsteady heat flux and static pressure in a small-core squealer-tip blade turbine. Atomic Layer Thermopile sensors and fast response pressure transducers were used to perform high-frequency acquisition at 2MHz around the 51% axial blade chord on the shroud. Measurements were taken at engine-representative conditions at several operational conditions and tip clearances. The signals were phase-locked averaged over the revolution period and synchronized to identify individual blade and row signatures. The linear relationship between the rotational tip Reynolds and the static pressure ratio across the blade tip reveals the transition point to reverse over-tip flows. Total heat flux is decomposed into different steady and unsteady heat flux contributions. It is demonstrated that the adiabatic wall temperature governs the unsteady heat flux and contributes to one third of the total surface heat flux. A linear trend was observed between the unsteady heat flux and the tip clearance measured at the pressure and suction side rims. Similar trends were observed between the local heat flux and the pressure ratio across the tip. A comparison with CFD predictions highlights some limitations on resolving the detached and secondary flows, evidencing the necessity of complementary experimental data.

Comparative Study on the Application Efficacy of Small Disturbance Equation versus One-Dimensional Euler Equation in Nozzle Flow Analysis

This paper presents a numerical simulation study of subsonic and supersonic nozzle flow regimes utilizing the Small Disturbance Equation (SDE), implemented through Python to analyze flow stability under various boundary conditions. The SDE, extensively applied in aerospace, meteorology, and fluid mechanics, offers a critical framework for examining aircraft stability and maneuverability, essential for ensuring flight safety. Additionally, its application extends to spacecraft stability and control in aerospace science. The findings from this study reveal that subsonic flows, characterized by their stability and smoothness, respond more predictably under varying boundary conditions compared to their supersonic counterparts. Conversely, supersonic flows demonstrate increased sensitivity to changes in boundary conditions, resulting in more complex flow patterns. This sensitivity underscores the need for precise control mechanisms in supersonic applications to maintain flow stability and ensure the safety and efficiency of aerospace operations. The simulations underscore the practical importance of the SDE in advancing the understanding of dynamic flow problems across different scientific and engineering disciplines.

Advanced Numerical Techniques for Supersonic Flow Analysis: From Euler Equations to Practical Applications in Aerospace and Turbomachinery Engineering

This paper explores advanced numerical techniques for analyzing supersonic flow, with a particular focus on the application of Euler equations in aerospace and turbomachinery engineering. Theoretical foundations such as boundary conditions, error evaluation, grid partitioning, and the Successive Over-Relaxation (SOR) method are thoroughly examined. Rigorous numerical simulations are conducted to investigate the final velocity field distribution and convergence characteristics under various conditions. The research underscores the precision and efficiency of these numerical methods, highlighting their practical applications in the aerodynamic design of aircraft and potential use in turbomachinery design. The findings contribute significantly to the advancement of computational fluid dynamics in supersonic flow regimes, providing valuable insights for engineers and researchers engaged in this specialized area. The study not only enhances understanding of complex flow dynamics but also supports the development of more effective engineering solutions in high-speed applications.

FlawCheck: Detecting Smart Contract Vulnerabilities Based on Symbolic Execution

ABSTRACTSmart contracts are turing‐complete computer programs running on blockchains. Like traditional programs, smart contracts are also vulnerable. However, unlike traditional programs, it is very difficult to modify smart contracts once they are deployed on the blockchain. Therefore, reducing potential vulnerabilities in contracts before deployment to the blockchain is very important. The existing smart contract detection tools mostly fail to fully consider the complex control flow relationships within smart contracts, leading to false positives and false negatives. To address these problems, we propose FlawCheck, a vulnerability detection tool based on symbolic execution. First, it compiles smart contract source code into bytecode. Then, it disassembles bytecode into an opcode sequence, building the dependencies of contract control flow. Next, it performs preliminary analysis on the information generated during the simulated execution on the Ethereum virtual machine to identify suspicious vulnerability paths. Finally, it detects these suspicious paths by using symbolic execution. We verified that FlawCheck can detect five types of smart contract vulnerabilities. Experimental results on a dataset of 13016 real contracts shows that FlawCheck has higher accuracy than other tools.

Particle image velocimetry study of the flow control effects of singular and multiple curved serration models

This paper reports on preliminary observations of an investigation of flows associated with models that mimic serrations on the leading edge of barn owl feathers. The objective was to use particle image velocimetry measurements to determine the capacity of singular and multiple curved (three-dimensional) serration models to modify the noise-reducing indicators of a narrow-channeled flow past a cylinder. Four models were tested: 3 singular serration models of respective angles of inclination, α = 24°, 27.5° and 31°, and a model consisting of an array of 3 serrations of α = 24°, 27.5° and 31°. Each case was subjected to flow of Reynolds number (based on the serration height and maximum velocity of the flow) of ∼2,000, simulating the flow regime of local flow around barbs of real barn owl flights. A planar particle image velocimetry technique was used to capture the midspan plane velocities to determine the effects of each model. The results show that using singular serration models of inclination angles than 30° may lead to disorganized spatial structures and enhanced turbulence levels. On the other hand, an array of only 3 curved serrations of different geometries can modify the spatial flow structure into a well-ordered one, resulting in a 50% reduction in turbulence intensities. These initial results suggest that under complex flow conditions, the insertion of single and multiple curved serrations can lead to significant flow changes that may result in potential noise modifications.

Capillary Orientation and Morphology Dictated Oscillatory Electro-magneto-imbibition of Viscoelastic Electrolytes.

We explore the intricate dynamics of imbibition by a viscoelastic electrolyte within an arbitrarily oriented, nonuniform microcapillary, while under the stimulus of external electromagnetic fields and internal electroviscous forces stemming from streaming potential. The microcapillary walls are envisaged to be tapered relative to each other, with the entire system inclined with respect to the horizontal plane. The rheological behavior of the electrolyte is characterized using the Phan-Thien-Tanner (PTT) model. To manipulate the imbibition dynamics, external transverse magnetic and electric fields are imposed. Incorporating all contributing forces, we obtain semianalytical formulations for the velocity and shear stress distributions. We identify distinct stages during the imbibition process: (i) initial, (ii) filling, (iii) oscillatory, and (iv) stagnation stages. Moreover, we scrutinize the impact of four pivotal parameters, namely, the Weissenberg number (Wi), the Hartmann number (Ha), the transverse electric to viscous force (EVF) number (S), and the electric Reynolds number (Ree), on the imbibition dynamics across different inclinations and taper angles. We also delineate the parameter space for these four parameters, identifying where the onset of oscillations occurs. Finally, through scaling analysis, we establish the existence of four distinct regimes corresponding to the aforementioned stages: (i) the linear regime, (ii) the Washburn regime, (iii) the oscillatory regime, and (iv) the equilibrium regime. Our findings are anticipated to enhance the understanding of capillary imbibition under such complex flow conditions and contribute significantly to the advancement of capillarity-driven microfluidic devices.