Principles Of Fluid Dynamics Research Articles

Flow characteristics in a horizontal reactor for continuous preparation of carbon nanotubes

This study focuses on a sophisticated horizontal reactor designed to facilitate the continuous growth of carbon nanotubes (CNTs) through chemical vapor deposition (CVD). Experimental observations reveal that carbon production varies at different locations within the reactor, with higher yields typically found in the middle and rear zones. The flow dynamics within the reactor play a pivotal role in CNT growth, prompting a detailed simulation of the flow field using Computational Fluid Dynamics (CFD). This simulation leverages fluid dynamics principles to assess the impact of various parameters on the flow field, ultimately identifying the optimal operating conditions. Findings indicate that temperature-induced density contrasts create cyclic flow patterns that can negatively affect CNT growth rates. However, the gas flow inside the horizontal continuous preparation reactor can be improved and optimized by adjusting and controlling the preparation parameters. Appropriately lowering the heating temperature and the mole fraction of propylene in inlet 2, within the range of conditions suitable for the growth of CNTs, while minimizing the perturbation of the flow field by the shape of the carriers, can promote more favorable CNTs growth.

Essential Fluidics for a Flow Cytometer.

Flow cytometry is an inherently fluidic process that flows particles on a one-by-one basis through a sensing region to discretely measure their optical and physical properties. It can be used to analyze particles ranging in size from nanoparticles to whole organisms (e.g., zebrafish). It has particular value for blood analysis, and thus most instruments are fluidically optimized for particles that are comparable in size to a typical blood cell. The principles of fluid dynamics allow for particles of such size to be precisely positioned in flow as they pass through sensing regions that are tens of microns in length at linear velocities of meters per second. Such fluidic systems enable discrete analysis of cell-sized particles at rates approaching 100 kHz. For larger particles, the principles of fluidics greatly reduce the achievable rates, but such high rates of data acquisition for cell-sized particles allow rapid collection of information on many thousands to millions of cells and provides for research and clinical measurements of both rare and common cell populations with a high degree of statistical confidence. Additionally, flow cytometers can accurately count particles via the use of volumetric sample delivery and can be coupled with high-throughput sampling technologies to greatly increase the rate at which independent samples can be delivered to the system. Due to the combination of high analysis rates, sensitive multiparameter measurements, high-throughput sampling, and accurate counting, flow cytometry analysis is the gold standard for many critical applications in clinical, research, pharmaceutical, and environmental areas. Beyond the power of flow cytometry as an analytical technique, the fluidic pathway can be coupled with a sorting mechanism to collect particles based on desired properties. We present an overview of fluidic systems that enable flow cytometry-based analysis and sorting. We introduce historical approaches, explanations of commonly implemented fluidics, and brief discussions of potential future fluidics where appropriate. © 2024 Wiley Periodicals LLC.

Enhancing Anti-Blast Capabilities of Pipelines with High-Performance Composite CFRP Laminate: Computational Fluid Dynamics-Based Predictive Analysis

Abstract Recent explosions highlighted the need for a thorough investigation to understand the impact of these explosions on critical infrastructural systems and networks like pipelines. This paper provides an essential understanding for developing safety protocols and interventions, strengthening resilience, enhancing public safety, mitigating socio-economic consequences, and ensuring sustained progress. Shallow buried conduits, crucial for transporting water, oil, and gas over long distances, face explosion risks due to conflicts, sabotage, terrorism, corrosion, and accidental damage. Recent blast incidents in San Francisco and Lagos underscore the devastating effects of conduit malfunctions, necessitating rigorous safety measures and technological innovations. In this research, an empty pipeline measuring 26.20 mm in thickness and subjected to a detonation initiated upon its uppermost surface is emulated, utilising the sophisticated computational capabilities of Abaqus software, integrating principles of computational fluid dynamics. Following a meticulous validation process achieved via mesh refinement analysis, the study expands to scrutinise two additional detonation scenarios — positioned above and below the pipe’s surface — while adhering to a steadfast standoff distance of 25mm. The primary objective of this scholarly endeavour is to ameliorate the deleterious repercussions inflicted upon the conduit by explosive forces, envisioning a scenario where deformation occurs without immediate rupture. To this end, a 0.15 mm thick and 200mm wide laminate composed of composite CFRP with 0°/90° fibre orientation is strategically affixed onto the upper half segment of each pipe model at the impacted region, serving as a fortification measure aimed at bolstering areas of susceptibility and potentially diminishing the magnitude of ensuing blast-induced impairment. Comparative analysis of the pipe’s performance, both with and without the applied laminate, is meticulously conducted to discern the effectiveness of this intervention. The results demonstrate a significant reduction in plastic damage with the utilisation of laminate, with models integrating CFRP experiencing an average decrease of approximately 39.94% compared to those without it. It highlights the efficacy of CFRP in protecting pipeline structural integrity against blast events.

Effect of electrolyte level on performance and mass transfer of non-aqueous lithium-oxygen battery

To accurately reveal the effect of electrolyte content on mass transfer within lithium-oxygen batteries and their discharge performance, this study utilizes computed tomography(CT) scanning technology and digital reconstruction methods to construct a geometric model of the lithium-oxygen battery cathode that is equivalent to the actual one. Based on the fundamental principles of mass transfer, fluid dynamics, and electrochemistry, a two-dimensional model for the discharge process of lithium-oxygen batteries is established. This model facilitates analysis of various parameters and their influencing factors, including the distribution of reaction products, pore structure, oxygen concentration distribution, battery performance, and overpotential, within the lithium-oxygen battery cathode. The research findings indicate that the deposition of reaction products alters the cathode structure and material transport; lower discharge current density and higher electrolyte levels are conducive to the dispersed deposition of reaction products, thereby reducing the deposition's resistance to internal mass transfer in the cathode.

Overview of steam turbines and efficiency

Thermal power plants, which produce energy from the burning of fossil fuels that in turn generate turbine-turning steam, contribute a large proportion of energy in the world. Research on how we could apply fluid dynamic and thermodynamic principles in the design of turbines is crucial to improving their efficiency and fuel consumption. This paper mainly aims to explore and summarize how the power efficiency of turbines is maximized in thermal power plants and analyze the designs of turbines that increase proficiency. Literature and past paper review will be the primary method of this research. The main findings of this research are that efficiency in thermal turbines can be increased in three principal ways: a multi-stage expansion mechanism, the application of alternating blades, and in implementation of a reheating system. Using these methods, efficiency has been increased almost a million-fold in steam turbines. The purpose of this paper is to gain insights into how energy output in thermal power plant turbines is maximized and the specific designs of turbines that improve its efficiency.

A novel functional index, aortic-valve-coefficient, for assessing aortic-stenosis in patients undergoing TAVR: A prospective-pilot study

BackgroundEvaluating the severity of aortic stenosis (AS) can be challenging, particularly in patients with low-gradient (LG, Δp < 40 mmHg) AS. Objective: This study aims to improve the accuracy of assessing severity of AS using a novel functional index- Aortic Valve Coefficient (AVC). The AVC is defined as ratio of mean transvalvular pressure-drop (Δp) to the proximal dynamic pressure (1/2 × blood density × VLVOT2; VLVOT: left ventricular outflow tract peak velocity). Hypothesis: AVC, developed from fundamental fluid dynamic principles, is a better index for accessing AS severity as it incorporates square of VLVOT and downstream pressure recovery. MethodsThis pilot prospective study enrolled 47 patients undergoing TAVR for AS. Using cardiac-catheterization-measured Δp and echocardiography-Doppler-derived VLVOT, AVC was evaluated. Pre- and post-TAVR pressure-velocity measurements were obtained, resulting in a dataset with 78 data points, including 32 data points specifically linked to LG AS. Linear regression analysis was performed to correlate AVC with Δp, VLVOT and aortic-valve-area. Welch 2-sample t-test was carried out to compare the means of AVC against aortic-valve-area. ResultsModerate correlation (r = 0.85) was observed between AVC and aortic-valve-area indicating AVC could be a prospective index. However, correlation decreased (r = 0.75) in LG AS patients, indicating increased discordancy. Comparing AVC and aortic-valve-area in LG AS patients with left ventricular ejection fraction (LVEF) < 50 % and LVEF ≥50 %, t-test showed that AVC values are significantly different (p < 0.05) as compared to aortic-valve-area (p = 0.48). ConclusionAVC, a novel index, has the potential to improve assessment of AS severity and clinical decision making for treating patients with AS. Condensed abstractComplex hemodynamics, such as paradoxical “low-flow low-gradient (LG)” Aortic stenosis (AS) can be difficult to diagnose. Currently, mean transvalvular pressure-drop and flow-derived aortic-valve-area assess AS severity. Aortic valve coefficient (AVC) is a novel index which combines both pressure-drop and flow measurements to assess the severity of AS. A total of 47 patients (72 data points) were studied undergoing TAVR. In LG AS patients, t-test comparing left ventricular ejection fraction (LVEF) < 50 % and LVEF ≥50 % showed that AVC are significantly different (p < 0.05) as compared to aortic-valve-area (p = 0.48). Therefore, AVC could be a better index.

Fluid dynamics and venous hemodynamics in the lower extremities.

Chronic venous disease is a vascular disorder characterized by impaired venous return and a progressive dysfunction of the venous system. Pathological reflux can occur due to abnormal dilation and weakening of the vein wall. The circulatory system is a natural structure in which physical laws, such as the law of closed containers and gravity, operate. The malfunctions in the system also adhere to these laws of nature. This article explains how the principles of fluid dynamics apply to the flow of blood in the veins of the legs. I am discussing the principles of Pascal's law, Torricelli's law, Bernoulli's law, and Poiseuille's law, and how they are relating to the anatomy and physiology of the venous system.

Machine learning-assisted discovery of flow reactor designs

Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current approaches. Furthermore, existing parameterizations of reactor geometries are low dimensional with expensive optimization, limiting more complex solutions. To address this challenge, we have established a machine learning-assisted approach for the design of new chemical reactors, combining the application of high-dimensional parameterizations, computational fluid dynamics and multi-fidelity Bayesian optimization. We associate the development of mixing-enhancing vortical flow structures in coiled reactors with performance and used our approach to identify the key characteristics of optimal designs. By appealing to the principles of fluid dynamics, we rationalized the selection of design features that lead to experimental plug flow performance improvements of ~60% compared with conventional designs. Our results demonstrate that coupling advanced manufacturing techniques with ‘augmented intelligence’ approaches can give rise to reactor designs with enhanced performance.

Four-dimensional hemodynamic prediction of abdominal aortic aneurysms following endovascular aneurysm repair combining physics-informed PointNet and quadratic residual networks

Hemodynamic parameters can provide surveillance for the risk of complication of abdominal aortic aneurysms following endovascular aneurysm repair (EVAR). However, obtaining hemodynamic parameters through computational fluid dynamics (CFD) has disadvantages of complex operation and high computational costs. Recently proposed physics-informed neural networks offer novel solutions to solve these issues by leveraging fundamental physical conservation principles of fluid dynamics. Based on cardiovascular point datasets, we further propose an integration algorithm combining physics-informed PointNet and quadratic residual networks (PIPN-QN) that is capable of mapping sparse point clouds to four-dimensional hemodynamic parameters. The implemented workflow includes generating point cloud datasets through CFD simulation and dynamically reproducing the three-dimensional flow field in the spatial and temporal dimensions through deep learning. Compared with physics-informed PointNet (PIPN), the PIPN-QN reduces the mean square error of pressure and wall shear stress by around 32.1% and 33.1% and anticipates hemodynamic parameters in less than 2 s (14 400 times faster than CFD). To address the challenge of big data requirements, we quantify the universal flow field using a reduced number of supervision points, as opposed to the large number of point clouds generated from the CFD simulation. The PIPN-QN can meet the real-time hemodynamic parameters obtained from patients with abdominal aortic aneurysms following EVAR with higher accuracy, faster speed, and lower training costs.

Optimization on manifold injection in DI diesel engine fuelled with acetylene

Researchers demonstrated that implementing new combustion technology and optimising fuel quantity results in a significant reduction in traditional fossil fuel usage and emission levels. The Reactivity Controlled Compression Ignition (RCCI) combustion strategy is one of the low temperature combustion technologies, and it is used to reduce the overall combustion temperature while also providing better combustion control. This study looks into RCCI combustion technology, which uses conventional diesel fuel as the high reactivity fuel (HRF) injected through the injector and acetylene gas as the low reactivity fuel (LRF) injected into the cylinder via a modified inlet manifold alongside air. The modified engine setup was tested for performance, emissions, and combustion under various load conditions, as well as different mass flow rates of acetylene gas, a low reactivity fuel that is injected with air. The flow field of the low reactivity fuel at the inlet manifold is analysed using the Computational Fluid Dynamics principle, which is used to determine the best flow rate for improving combustion quality. According to the simulation results, the optimal acetylene flow rate is 3 Litres Per Minute (LPM), and experimentation shows that at 3 LPM acetylene injection, the brake thermal efficiency (BTE) improves by about 3.2%, and emissions such as carbon monoxide (CO), hydrocarbon (HC), smoke intensity, and oxides of nitrogen (NOx) are reduced by about 35%, 17%, 10%, and 21%, respectively.

A novel semi-flexible coaxial nozzle based on fluid dynamics effects and its self-centering performance study

Coaxial nozzles are widely used to produce fibers with core–shell structures. However, conventional coaxial nozzles cannot adjust the coaxiality of the inner and outer needles in real-time during the fiber production process, resulting in uneven fiber wall thickness and poor quality. Therefore, we proposed an innovative semi-flexible coaxial nozzle with a dynamic self-centering function. This new design addresses the challenge of ensuring the coaxiality of the inner and outer needles of the coaxial nozzle. First, based on the principles of fluid dynamics and fluid–structure interaction, a self-centering model for a coaxial nozzle is established. Second, the influence of external fluid velocity and inner needle elastic modulus on the centering time and coaxiality error is analyzed by finite element simulation. Finally, the self-centering performance of the coaxial nozzle is verified by observing the coaxial extrusion process online and measuring the wall thickness of the formed hollow fiber. The results showed that the coaxiality error increased with the increase of Young’s modulus E and decreased with the increase of flow velocity. The centering time required for the inner needle to achieve force balance decreases with the increase of Young's modulus (E\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E$$\\end{document}) and fluid velocity (vf\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${v}_{f}$$\\end{document}). The nozzle exhibits significant self-centering performance, dynamically reducing the initial coaxiality error from 380 to 60 μm within 26 s. Additionally, it can mitigate the coaxiality error caused by manufacturing and assembly precision, effectively controlling them within 8 μm. Our research provides valuable references and solutions for addressing issues such as uneven fiber wall thickness caused by coaxiality errors.

An improved prediction model for in-stream water wheel performance

As global efforts to decarbonise industries continue, there is increasing pressure to identify and proliferate sustainable methods of generating electricity, in-line with the United Nations’ Sustainable Development Goal 7. The in-stream water wheel is a pico-hydropower technology that generates electricity using only the kinetic energy in the fluid, rather than both potential and kinetic, like most forms of pico-hydropower. Current methods of estimating the power output of these turbines lack validation, robustness and proper justification for their assumptions. This study has developed a new method for predicting the power output of in-stream water wheels, based on fluid dynamics principles, and has been compared with a range of experimental results to confirm its robustness. The new model identifies novel characteristics of the power stroke of the turbine blade, including unsteady effects and negative torque production at certain blade angles. In addition, the model can be tuned to match experimental data, improving its accuracy in specific applications. The better prediction of power output aims to encourage the use of in-stream water wheels as part of the global decarbonisation strategy.

Theory of Everything

Our Theory of Everything is made possible by the discovery of a closed fluid dynamic principle, working in a closed fluid space-time system, (the universe). Through the principle of fluid space-time, almost all of the unexplained mysteries of the universe are revealed. How the universe came into being, with matter and the most basic force, Gravity. Newton’s law of gravity in particular, the inverse square law with distance. (the reason is for appearance of the inverse square law, simultaneously in gravitation and electromagnetism, not a coincidence). Special Relativity is an account of how space contracts, time dilates and mass increases, with velocity. General Relativity is an account of how space-time curves. According to Muhammad’s closed fluid dynamic principle, space actually consists of an extremely fluid substance which we call aether. It is therefore fitting that through the closed fluid dynamic principle, we can arrive at an explanation for one major thorn in the side of Special Relativity, the twin paradox. The problem is, it is the twin who accelerates that gets it wrong. Because his assessment of the age of his brother was done without consideration of the fact that when he turned around, made the return journey, he felt his acceleration but did not employ this in Einstein’s time dilation, which was based on inertial reference frames. The task we are confronted with in this paper is to find out how the time dilation addressed in special relativity comes into proceedings in an accelerated frame. We achieve this.

Integrating local and distant radiation-induced lung injury: Development and validation of a predictive model for ventilation loss.

Investigations on radiation-induced lung injury (RILI) have predominantly focused on local effects, primarily those associated with radiation damage to lung parenchyma. However, recent studies from our group and others have revealed that radiation-induced damage to branching serial structures such as airways and vessels may also have a substantial impact on post-radiotherapy (RT) lung function. Furthermore, recent results from multiple functional lung avoidance RT trials, although promising, have demonstrated only modest toxicity reduction, likely because they were primarily focused on dose avoidance to lung parenchyma. These observations emphasize the critical need for predictive dose-response models that effectively incorporate both local and distant RILI effects. We develop and validate a predictive model for ventilation loss after lung RT. This model, referred to as P+A, integrates local (parenchyma [P]) and distant (central and peripheral airways [A]) radiation-induced damage, modeling partial (narrowing) and complete (collapse) obstruction of airways. In an IRB-approved prospective study, pre-RT breath-hold CTs (BHCTs) and pre- and one-year post-RT 4DCTs were acquired from lung cancer patients treated with definitive RT. Up to 13 generations of airways were automatically segmented on the BHCTs using a research virtual bronchoscopy software. Ventilation maps derived from the 4DCT scans were utilized to quantify pre- and post-RT ventilation, serving, respectively, as input data and reference standard (RS) in model validation. To predict ventilation loss solely due to parenchymal damage (referred to as P model), we used a normal tissue complication probability (NTCP) model. Our model used this NTCP-based estimate and predicted additional loss due radiation-induced partial or complete occlusion of individual airways, applying fluid dynamics principles and a refined version of our previously developed airway radiosensitivity model. Predictions of post-RT ventilation were estimated in the sublobar volumes (SLVs) connected to the terminal airways. To validate the model, we conducted a k-fold cross-validation. Model parameters were optimized as the values that provided the lowest root mean square error (RMSE) between predicted post-RT ventilation and the RS for all SLVs in the training data. The performance of the P+A and the P models was evaluated by comparing their respective post-RT ventilation values with the RS predictions. Additional evaluation using various receiver operating characteristic (ROC) metrics was also performed. We extracted a dataset of 560 SLVs from four enrolled patients. Our results demonstrated that the P+A model consistently outperformed the P model, exhibiting RMSEs that were nearly half as low across all patients (13±3 percentile for the P+A model vs. 24±3 percentile for the P model on average). Notably, the P+A model aligned closely with the RS in ventilation loss distributions per lobe, particularly in regions exposed to doses ≥13.5Gy. The ROC analysis further supported the superior performance of the P+A model compared to the P model in sensitivity (0.98vs. 0.07), accuracy (0.87vs. 0.25), and balanced predictions. These early findings indicate that airway damage is a crucial factor in RILI that should be included in dose-response modeling to enhance predictions of post-RT lung function.

Optimization of Aircraft Fuel Systems Considering Fluid Dynamics Principles

The fuel system is the lifeline of any aircraft, pivotal for its operation and future advancements. This study delves into aircraft fuel system design methodologies, aiming to streamline development processes. Through optimization and matrix methods like the morphological matrix, Saab Aerospace pioneer’s conceptual designs. These methods automate development and deepen our understanding of how top-level requirements impact engineering details. Quantifying matrices opens doors to design optimization and probabilistic design. Furthermore, a systematic approach to simulation modeling minimizes development time, leveraging parallel development and collaborative engineering. With stakeholder expectations in mind, experience gleaned from projects like the Gripen fuel system shapes an overarching process for future endeavors. This journey promises to reshape aircraft fuel system design, ensuring each drop of fuel propels us towards boundless horizons. Key Words: Aerospace engineering, Fuel system, Optimization techniques, Matrix methods, Simulation models, Conceptual design, System integration, Aircraft performance, Fuel tank configurations, Operational flexibility, Gripen Fuel, DSM- Design Structure Matrix

A COMPARATIVE ANALYSIS OF HYPOTHESIS IN THE MODELING OF A HYBRID COMPRESSION REFRIGERATION CYCLE

This paper presents a comprehensive thermodynamic analysis of a hybrid refrigeration system that integrates an evacuated tube solar thermal collector into a vapor compression refrigeration cycle. The proposed analysis comprises two distinct approaches: an isovolumetric model and a compressible flow model. The former assumes a constant specific volume within the solar heat exchanger, while the latter applies principles of compressible fluid dynamics. The study compares these models with a reference work, emphasizing similarities and disparities. The investigation systematically varies key parameters, including evaporator and condenser temperatures, inlet and outlet temperatures of the heat exchanger, and heat load. By varying these parameters, the coefficient of performance (COP) and compressor work are evaluated, elucidating the impact of heat addition on the system's performance. Additionally, the influence of different working refrigerant fluids, such as R22 and R410A, is examined under various design point conditions. The results demonstrate the potential energy savings achievable by the hybrid system, with reductions in electrical power compared to the conventional compressor, as solar heat is introduced. While the isovolumetric analysis closely aligns with the reference work, the compressible flow modeling highlights sensitivity to inlet conditions. Although not directly comparable, the latter approach presents promising trends within specific design point ranges. Comparisons of performance curves for different refrigerant fluids further validate the models and assist in potential fluid selection. Overall, the outcomes indicate a promising avenue for energy-efficient refrigeration systems and provide valuable insights for engineering design and optimization.

Mechanics of blood flow through narrow artery using Prandtl viscoelastic model

BackgroundThe mechanics of blood flow via converging diverging conduits is an intriguing phenomenon that involves multiple fundamental principles of fluid dynamics. Blood arteries can diverge, which means they expand, or converge, which means they contract down. This specific structure is essential for controlling blood flow and preserving adequate circulation across the body. The theory of fluid mechanics is significant concept related to blood flow along converging/divergent channels. Elevated shear strains near the narrower artery throat can stimulate platelets, causing thrombosis that can completely or partially stop blood supply to the human brain or heart. This communication addresses the blood flow in convergent and diverging artery using fundamental concept of fluid mechanics. The Prandtl fluid model is considered as a blood, because of its viscoelastic nature. The influence of heat source, frictional dissipations and a chemical reaction are included. MethodsThe Jaffrey-Hamel flow in a converging and diverging conduits is generalized to Prandtl fluid model considering the purely radial flow through cylindrical pipe like artery with an arbitrary cross section. The governing equations are solved computationally using the Runge–Kutta-Fehlberg (RKF-4) method. Significant findingThe rheological parameters ε and δ of blood show opposite tendencies for blood circulation. The Brownian and thermophoresis parameters has a significant effect on heat and mass transport rate. The presence of slip (semi blockage) produces flow reversal and higher drag forces at the arterial wall. Significant flow dynamics and heat-mass transport was reveled for diverging (wider) artery β > 0. The non-uniform heat source show similar trends for thermal profile and heat transfer rate.

Study on the Mechanism of Water and Sand Leakage in a Foundation Pit Retaining Structure Based on the Computational Fluid Dynamics–Discrete Element Method

The existence of defects in the enclosure structure is the primary cause of water and sand leakage in foundation pits, as well as being a significant source of danger in pit construction, but current research lacks an in-depth investigation of the generation mechanism and gestation process. In this paper, which comprehensively considers the microscopic particles and macroscopic level, the development mechanism of a water and sand leakage disaster in a foundation pit with a water-rich sand layer was studied using the principle of computational fluid dynamics and discrete element method coupled analysis (CFD–DEM); moreover, based on the anisotropy of the particle force and fluid energy analysis, the deformation of the stratum and ground stress field were analyzed. The results show that the stress field will produce a plugging effect at a certain distance from the defect, and the strata exhibit a dominant displacement tendency in the vertical direction, resulting in the emergence of a gradually concave stress relaxation zone and an elliptical contour in the strata displacement map near the defect. The fluid energy describes the displacement of the sand layer very well, and it is separated into the sand layer’s centralized loss region and the major loss area based on the high and low levels of the fluid energy class. The impact of fluid at the defect reaches the maximum kinetic energy, which penetrates the structural weakness and causes the loss of sand particles, and the cross-section of the water influx near the defect gradually expands with the loss of particles, indicating that there is a danger of further expansion of the defect under the impact of water flow. These results have technical implications for the management of water and sand leakage disasters in foundation pit engineering.

Blood flow effects in a patient with a thoracic aortic endovascular prosthesis

This work analyzes hemodynamic phenomena within the aorta of two elderly patients and their impact on blood flow behavior, particularly affected by an endovascular prosthesis in one of them (Patient II). Computational Fluid Dynamics (CFD) was utilized for this study, involving measurements of velocity, pressure, and wall shear stress (WSS) at various time points during the third cardiac cycle, at specific positions within two cross sections of the thoracic aorta. The first cross-section (Cross-Section 1, CS1) is located before the initial fluid bifurcation, just before the right subclavian artery. The second cross-section (Cross-Section 2, CS2) is situated immediately after the left subclavian artery. The results reveal that, under regular aortic geometries, velocity and pressure magnitudes follow the principles of fluid dynamics, displaying variations. However, in Patient II, an endoprosthesis near the CS2 and the proximal border of the endoprosthesis significantly disrupts fluid behavior owing to the pulsatile flow. The cross-sectional areas of Patient I are smaller than those of Patient II, leading to higher flow magnitudes. Although in CS1 of Patient I, there is considerable variability in velocity magnitudes, they exhibit a more uniform and predictable transition. In contrast, CS2 of Patient II, where magnitude variation is also high, displays irregular fluid behavior due to the endoprosthesis presence. This cross-section coincides with the border of the fluid bifurcation. Additionally, the irregular geometry caused by endovascular aneurysm repair contributes to flow disruption as the endoprosthesis adjusts to the endothelium, reshaping itself to conform with the vessel wall. In this context, significant alterations in velocity values, pressure differentials fluctuating by up to 10%, and low wall shear stress indicate the pronounced influence of the endovascular prosthesis on blood flow behavior. These flow disturbances, when compounded by the heart rate, can potentially lead to changes in vascular anatomy and displacement, resulting in a disruption of the prosthesis-endothelium continuity and thereby causing clinical complications in the patient.

Nzubechukwu Chukwudum Ohalete

This paper delves into the critical role of Navier-Stokes equations in biomedical engineering, with a specific focus on their application in the development of medical devices across the United States and Africa. The study aims to elucidate the integration of fluid dynamics principles in medical device innovation, assess the influence of cultural and economic factors on device design, and explore the regulatory landscape shaping this domain. Employing a methodical approach, the study analyzes Navier-Stokes applications in diverse geographical contexts, utilizing case studies to underscore the relevance and methodological rigor in biomedical engineering. The findings reveal that Navier-Stokes equations are pivotal in modeling biological fluid flows, essential for the design and analysis of cardiovascular and respiratory devices. The advancement of computational fluid dynamics (CFD) has significantly enhanced these applications, enabling more precise and patient-specific analyses. However, challenges in computational resources and simulating physiological conditions are identified as key limitations. The study highlights the profound impact of cultural and economic considerations on medical device design and functionality. It emphasizes the necessity of creating devices that are not only innovative and effective but also culturally appropriate and economically viable. Additionally, the evolving regulatory frameworks, particularly in the wake of global health crises, are examined for their impact on device safety and efficacy. In conclusion, the study recommends continued research and development to address the identified challenges and limitations, advocating for a multidisciplinary approach that integrates engineering, computational modeling, and medical expertise. It also calls for the consideration of cultural, economic, and regulatory factors in the design and development of medical devices, ensuring their global applicability and effectiveness in improving healthcare outcomes.