Real Flow Research Articles

Exploring the Relationship between Data Sample Size and Traffic Flow Prediction Accuracy

Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. The suitable size of data sample assumes paramount importance in fostering sustainable transportation development. This paper investigates the relationship between traffic flow prediction performance and data sample size, considering data sample missing rates, duration, and road segment coverage. Real traffic flow data from 13 road sections in Changsha, China, are analyzed using the Decision Tree, Support Vector Machine, Gaussian Process Regression and Artificial Neural Network models. Some key findings include: Lower data sample loss rates improve prediction accuracy by capturing traffic flow patterns effectively, while higher loss rates decrease accuracy; an optimal data sample duration of around 7 days balances prediction accuracy and data stability, with longer durations providing more historical data but risking complexity; Broader road segment coverage gives a more comprehensive traffic flow information, but excessive coverage introduces noise and impacts the improvement of prediction accuracy. The results highlight the significant impact of data sample size on prediction performance. Enhancing reliability can be achieved by reducing data loss, selecting suitable durations, and considering appropriate road segment coverage, supporting improved traffic management and route planning.

Modeling Cardiovascular Flow with Artificial Viscosity: Analyzing Navier-Stokes Solutions and Simulating Cardiovascular Diseases

In this paper, the numerical solutions of the Navier-Stokes equations (NSE) used for modeling the flow in the cardiovascular system are investigated using the Finite Element Method (FEM). A fully discrete solution scheme of the NSE and its stability and error analysis are presented. Artificial viscosity stabilization is added to the fully discrete scheme to better model the real flow structure and to remove non-physical oscillations. Numerical tests are also presented to demonstrate the effectiveness of the resulting scheme. Simulations analyzing the flow structure in the case of cardiovascular diseases such as atherosclerosis and brain aneurysm are presented in detail along with wall shear stress values.

Enhancing flexibility of smart bioresorbable vascular scaffolds through 3D printing using polycaprolactone and polylactic acid

With the growing use of stent implantations, the risk of in-stent restenosis represents a major concern for cardiovascular patients. Herein, we propose a hybrid bioresorbable vascular scaffold (H-BVS) integrated with a wireless sensor that could enable significant advances in cardiovascular therapeutics. The H-BVS was carefully manufactured using a state-of-the-art customized 3D printer equipped with dual nozzles to achieve a synergistic combination of polycaprolactone (PCL) and polylactic acid (PLA), both of which are known for their bioresorbable properties. This characteristic is particularly valuable in medical applications where the scaffold is gradually absorbed by the body, eliminating the need for a second procedure to remove it. Furthermore, the H-BVS was integrated with a wireless, battery-less LC-type pressure sensor for real-time monitoring of in-stent restenosis. This wireless sensor was meticulously connected with the H-BVS framework through engineered microstructures, which not only ensured a robust bond but also significantly enhanced the overall integrity and functionality of the device. Additionally, the combination of the H-BVS and sensor was optimized to exhibit superior bending flexibility and radial strength, which are key factors in ensuring effectiveness and patient safety. The feasibility of the smart H-BVS (SH-BVS) was verified through comprehensive testing within a phantom system designed to simulate real blood flow conditions. We believe that the SH-BVS system holds strong potential to significantly improve patient monitoring and treatment strategies within the cardiovascular healthcare domain.

Numerical investigation on the VIV response of the flexible cylindrical structures subjected to non-linearly varying shear flow

Vortex-induced vibration (VIV) of flexible cylinders is an important phenomenon in ocean structures, which may cause fatigue damage and structural failure of offshore structures. Much literature has extensively explored VIV of flexible cylinders under various flow conditions, such as uniform and linearly varying shear flow. However, real scenarios in most cases involve non-uniform, non-linearly varying shear flow profiles. Hence, it is important to investigate the VIV response of the flexible cylindrical structures subjected to non-linearly varying shear flow profiles. This study employs a wake oscillator model (WOM) that simulates the VIV response of the flexible cylinder under the action of non-linearly varying shear flow velocity profiles. The flexible cylinder subjected to linearly varying sheared flow velocity profiles not only overpredicts but also underpredicts the VIV responses compared to the non-linearly varying sheared flow profile, which represents the real scenario. The VIV mode number for the flexible cylinder subjected to non-linear shear flow was found to have a non-linear relationship with that of linear shear flow. The VIV response of the flexible cylinder subjected to a linearly varying shear flow profile exhibits more travelling wave behaviour compared to non-linear shear flow. The location of the maximum VIV response of the structure having the same aspect ratio (L/D) and shear parameter (β), was different for linear and non-linear flow profiles across the span. The time and frequency domain responses showed a shift in the frequency band. The results obtained from the numerical simulations give better insights into the vibrational behaviour of flexible cylinders in realistic flow environments.

Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling

Tensor clustering has become an important topic, specifically in spatiotemporal modeling, because of its ability to cluster spatial modes (e.g., stations or road segments) and temporal modes (e.g., time of day or day of the week). Our motivating example is from subway passenger flow modeling, where similarities between stations are commonly found. However, the challenges lie in the innate high-dimensionality of tensors and also the potential existence of anomalies. This is because the three tasks, that is, dimension reduction, clustering, and anomaly decomposition, are intercorrelated with each other, and treating them in a separate manner will render a suboptimal performance. Thus, in this work, we design a tensor-based subspace clustering and anomaly decomposition technique for simultaneous outlier-robust dimension reduction and clustering for high-dimensional tensors. To achieve this, a novel low-rank robust subspace clustering decomposition model is proposed by combining Tucker decomposition, sparse anomaly decomposition, and subspace clustering. An effective algorithm based on Block Coordinate Descent is proposed to update the parameters. Prudent experiments prove the effectiveness of the proposed framework via the simulation study, with a gain of +25% clustering accuracy over benchmark methods in a hard case. The interrelations of the three tasks are also analyzed via ablation studies, validating the interrelation assumption. Moreover, a case study in station clustering based on real passenger flow data is conducted, with quite valuable insights discovered. History: Bianca Maria Colosimo served as the senior editor for this article. Funding: Dr. Yan is partially funded by DOE [DE-EE0009354] and NSF [CMMI 2316654]. Dr. Fugee is partially funded with the RGC [GRF 16201718 and 16216119]. The authors appreciate the help from the Hong Kong MTR Co. research, marketing, and customer service teams. Data Ethics & Reproducibility Note: The code capsule is available on Code Ocean at https://codeocean.com/capsule/6536164/tree and in the e-Companion to this article (available at https://doi.org/10.1287/ijds.2022.0028 ).

Study on Wind Farm Flow Field Characteristics Based on Boundary Condition Optimization of Complex Mountain Numerical Simulation

The accurate prediction of the flow field characteristics of complex mountains is of great practical significance for the development and construction of wind farms, but it is not yet fully understood. The main purpose of this study is to propose a method for the study of flow field characteristics under complex mountain conditions, which can optimize the boundary conditions required for numerical simulation through the wind acceleration ratio and, at the same time, couple the numerical simulation and wind measurement data to reflect the real mountain flow field distribution. The results show that the proposed method has good applicability in complex mountain wind farms, can reproduce the real flow field distribution, and has a certain practical value. Wind speed distribution and turbulence intensity are greatly affected by boundary conditions such as wind speed and wind direction and are also affected by the shielding effect brought by terrain changes. The contrast between 120° and 150° wind direction is more obvious. When the incoming wind moves to the top of a mountain or the ridgeline, it will form a low-speed wake area behind it, resulting in reduced wind speed, increased turbulence intensity, and an unstable flow field.

Influence of rotating wheels on Reynolds number sensitivity of passenger vehicle drag

Rotating wheels are essential to replicate realistic forces and flow fields during aerodynamic testing of passenger vehicles. Previous studies have found that the drag coefficient typically reduces with increased speed under rotating wheel conditions but is stable with stationary wheels. This paper investigates this velocity sensitivity for two vehicles, the aerodynamic research vehicle DrivAer and a production vehicle. Experiments with the DrivAer indicate that the drag reduction with increased speed cannot be explained by pressure changes on the vehicle body; instead, the effect is attributed to local flow changes around the wheels. Using numerical simulations, it is found that the separation at the front wheels' outer tire shoulder increases for lower velocities, thus resulting in higher drag coefficient and causing Reynolds number sensitivity. The degree of drag reduction is less for the DrivAer squareback than for the notchback due to the separation over the notchback's rear window. No direct difference is measured between various tires and rims. To assess the generality of the findings with the DrivAer, the results are compared to experiments with a production vehicle. It is observed that the drag sensitivity is less and only occurs if the rear wheels are rotating. Pressure measurements in the wheelhouses and around the wheel drive units confirm the front wheel separation's dependence on velocity and highlight the complex interaction between the front wheel wakes and rear wheel rotational state.

Hidden turbulence in van Gogh's The Starry Night

Turbulent skies have often inspired artists, particularly in the iconic swirls of Vincent van Gogh's The Starry Night. For an extended period, debate has raged over whether the flow pattern in this masterpiece adheres to Kolmogorov's theory of turbulence. In contrast to previous studies that examined only part of this painting, all and only the whirls/eddies in the painting are taken into account in this work, following the Richardson–Kolmogorov's cascade picture of turbulence. Consequently, the luminance's Fourier power spectrum spontaneously exhibits a characteristic −5/3 Kolmogorov-like power-law. This result suggests that van Gogh had a very careful observation of real flows, so that not only the sizes of whirls/eddies in The Starry Night but also their relative distances and intensity follow the physical law that governs turbulent flows. Moreover, a “–1”-like power-law persists in the spectrum below the scales of the smallest whirls, hinting at Batchelor-type scalar turbulence with a high Schmidt number. Our study, thus, unveils the hidden turbulence captured within The Starry Night.

Study on the influence of typical turbulent flow field on the metering performance of cross four channel ultrasonic flowmeter

Abstract In this paper, influence of typical turbulent flow field on a multi-channel ultrasonic flowmeter was studied. Experimental sample of the cross four-channel ultrasonic flowmeter were designed and processed, and CFD simulation models of flowmeter and right-handed spoiler, gate valve and velocity profile spoiler were established. Through simulation, the turbulent flow field behind typical spoilers such as right-handed spoiler, gate valve and velocity profile spoiler, and the influence of turbulent flow field on the metering performance of the cross four-channel ultrasonic flowmeter were studied. On this basis, the CFD simulation results and the real flow experiment results were compared and analyzed, and the reliability of the CFD simulation analysis results was verified, which provides the research basis for improving flowmeter performance.

A vertically non-uniform temperature approach for the friction term computation in depth-averaged viscoplastic lava flows

Recently, depth-averaged shallow flow models have been adapted to modelling liquefied lava flows, generally characterized by a marked temperature-dependent non-Newtonian rheology. Modelling these complex flows requires to include the effects of the depth-averaged temperature gradients in the governing equations. The most significant term to correctly predict the lava mobility is the flow resistance term, which is widely estimated using the linear viscoplastic Bingham model. This non-Newtonian model allows to relate the bed shear stress to the depth-averaged lava flow features by means of a cubic equation with analytical solution when assuming a uniform temperature distribution along the vertical profile. Nevertheless, the lava temperature is non-uniform along the vertical due to the heat transfer at the bottom and the free surface, and hence the classical cubic Bingham model is not valid anymore. In this work, a depth-averaged shallow flow model is adapted for realistic lava flows considering influence of the non-uniform vertical temperature profile in the non-Newtonian resistance. This requires to modify the rheological viscoplastic models for ensuring the coupling between flow dynamics and temperature evolution. Three non-uniform temperature vertical distributions are considered: linear, piece-wise and diffusion profiles. Synthetic tests are used to show the influence of the temperature vertical profile on the numerical results. Furthermore, laboratory experimental data are used to validate this novel viscoplastic resistance formulation and to show that the calibration of its parameters is possible.

A new method to compute the blood flow equations using the physics-informed neural operator

Using the Navier-Stokes equation for real blood flow simulations in patients is a challenging task. Among many of the challenges, initial and boundary conditions are not directly measurable. Many parameters for the flow model are also not directly measurable and differ from patient to patient and over time. New machine learning techniques, like physics-informed neural networks (PINN), offer some new ways to handle these difficulties. In this work, we aim to learn the operator that maps some easily measurable physiological signals to the solution of the blood flow equation. We use our proposed model based on Navier-Stokes equation and PINN to fit real data on blood pressure. A Windkessel boundary condition is used to produce physically correct reflection waves. A time-periodic condition is used to capture the periodicity of blood flow and enables our model to simulate the blood flow without initial and boundary conditions. Furthermore, we allow the periods of each instance of solution to be different, which makes the training of neural operators computationally expensive, but more accuracy and physical correct towards real blood pressure data. Further more, we also propose an efficient implementation to incorporate the periodic condition into our model. Estimating the hyper-parameters in the Navier-Stokes equation is also difficult. We then introduce a hyper-parameter network to estimate these parameters during the training process as well. The blood flow data contains useful information for disease detection and diagnosis, but directly measuring the entire blood flow remains a significant challenge. We apply our proposed method to cuffless blood pressure estimation. More specifically, we aim to predict the blood pressure waveform (continuous blood pressure and velocity in both time and space) from Electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which can be easily measured using wearable devices. Compared to other methods, our method is the first one that can predict blood flow continuously, both with location and time which are valuable for cardio-vascular medical treatments and diagnoses.

A spring-mass-damper model based on separated phase flow mode for pulsating heat pipe with adjustive-structured channels

Pulsating heat pipe (PHP) is a kind of efficient passive phase-change cooling device. The pulsating behaviors of the two-phase flow inside PHP significantly affect the heat transfer performance for PHP, the investigation of which will greatly contribute to the optimal design of PHP for electronic heat dissipation in small space. In the present work, the heat transfer performance of PHP is optimized via structure analysis and modeling calculation. A new “spring-mass-damper” model in terms of separated phase flow mode is established, where the frictional pressure loss of the real two-phase flow pattern − slug flow in PHP is considered. Besides, a prototype of PHP with adjustive-structured channel (ASCPHP) is proposed. The heat transfer performance of ASCPHP is evaluated with the newly established model. With theoretical computation method, the frequency of ASCPHP the superiority of ASPHP is also confirmed by comparison with other types of PHPs.

Investigation of two-phase flow distribution in the vertical annular distribution header of a variable refrigerant flow heat pump system

The characteristics of two-phase flow distribution from a vertically installed annular refrigerant distribution header to multiple branch ports are investigated, with a specific focus on simulating a real variable refrigerant flow heat pump (VRF HP) system. A test section is fabricated to replicate an actual distribution header for empirical investigation, utilizing an air–water mixture as the working fluid. A series of experiments are conducted to examine distribution characteristics, involving variations in the location of the main inlet port, operational mode, total mass flow rate, and void fraction. The experimental results indicate that the two-phase mixture exhibits a relatively uniform liquid phase distribution to the branch ports when the main inlet port is positioned at the bottom side. However, maldistribution to branch ports is intensified as the inlet void fraction increases and the flow rate of the two-phase mixture decreases. Furthermore, a series of computational fluid dynamics analyses is performed to investigate the distribution characteristics of R410A, the actual working fluid utilized in VRF HP systems. These analyses are conducted under the operational conditions typical of VRF HP systems. Despite identical Reynolds numbers for the two-phase R410A flow and air–water mixture flow, the former exhibits a notably uneven distribution to branch ports owing to the distinct thermophysical properties, particularly density and viscosity. The findings from this investigation enhance the comprehension of two-phase flow distribution characteristics in a vertically installed refrigerant distribution header under real VRF HP system conditions, offering valuable insights into mitigating the maldistribution of refrigerant flow to branch ports.

Electric vehicle eco-driving strategy at signalized intersections based on optimal energy consumption

Electric vehicles (EVs), which are a great substitute for gasoline-powered vehicles, have the potential to achieve the goal of reducing energy consumption and emissions. However, the energy consumption of an EV is highly dependent on road contexts and driving behavior, especially at urban intersections. This paper proposes a novel ecological (eco) driving strategy (EDS) for EVs based on optimal energy consumption at an urban signalized intersection under moderate and dense traffic conditions. Firstly, we develop an energy consumption model for EVs considering several crucial factors such as road grade, curvature, rolling resistance, friction in bearing, aerodynamics resistance, motor ohmic loss, and regenerative braking. For better energy recovery at varying traffic speeds, we employ a sigmoid function to calculate the regenerative braking efficiency rather than a simple constant or linear function considered by many other studies. Secondly, we formulate an eco-driving optimal control problem subject to state constraints that minimize the energy consumption of EVs by finding a closed-form solution for acceleration/deceleration of vehicles over a time and distance horizon using Pontryagin’s minimum principle (PMP). Finally, we evaluate the efficacy of the proposed EDS using microscopic traffic simulations considering real traffic flow behavior at an urban signalized intersection and compare its performance to the (human-based) traditional driving strategy (TDS). The results demonstrate significant performance improvement in energy efficiency and waiting time for various traffic demands while ensuring driving safety and riding comfort. Our proposed strategy has a low computing cost and can be used as an advanced driver-assistance system (ADAS) in real-time.

Digital Twin-Driven Dynamic Scheduling of Flexible Manufacturing System in the Context of Smart Factory Producing Brass Accessories

This study aims to deal with a dynamic scheduling problem of a real Flow Shop follow-up of an assembly process considering the specific constraints and requirements of a brass accessories manufacturing (BAM) company. We basically set up a Digital Twin-driven dynamic scheduling approach for Industry 4.0 by addressing uncertainties of machine availability. In fact, the setup of this Digital Twin (DT) is the outcome of the combination of both optimization and simulation. For the first step, we have elaborated a Mixed Integer Linear Programming (MILP) scheduling model by taking into account the dedicated requisites of our case study. Concerning simulation, a 3D simulation platform of a workshop producing brass accessories controlled by a Cyber-Physical Production System (CPPS) has been developed, in our previous work, including constraints and stochastic aspects. The simulation constraints are difficult or impossible to be modeled in the MILP model. These designs are integrated with the real workshop to construct the Digital Twin. The proposed tool enables the rescheduling of production orders based on machine disturbances and unpredictability. Validation scenarios have been designed and conducted to highlight the efficacy of the Digital Twin approach utilizing the brass accessories case study. We are confident that this represents the initial endeavor addressing the optimization of production rescheduling in a flow shop follow-up of a mixed assembly system.

Temperature-Stress Coupling Fatigue Behavior of Film-Cooling Holes in Complex Temperature Fields.

This research investigates the complex temperature distribution and fatigue behavior of single film-cooling holes manufactured by lasers with different pulse widths in a real flow field. The aerodynamic and heat transfer characteristics of film-cooling holes manufactured using lasers with different pulse widths were analyzed through laser drilling experiments, conjugate heat transfer simulations, and crystal plasticity finite element methods. The study investigated the relationship between changes in the geometric accuracy of the film-cooling holes and the corresponding flow and temperature fields during the film-cooling process. Additionally, the effects of temperature and structural variations on the stress around the holes in a flat plate composed of the second-generation nickel-based single-crystal superalloy DD6 in real flow and temperature fields were studied. The coupling effect of the temperature and stress fields around the holes on the fatigue behavior of the film-cooling holes was examined, and the fatigue damage mechanism of film-cooling holes in complex temperature fields was analyzed. It was found that changes in the blowing ratio do not affect the temperature and stress distributions around the holes but only alter the temperature peak. An increase in the temperature peak results in a decrease in the stress peak. Additionally, the fatigue damage of single film-cooling holes is determined by both the structural defects of the holes and the changes in material behavior due to the temperature around the holes, with the structural influence being more significant.

A Knee-Guided Evolutionary Algorithm for Multi-Objective Air Traffic Flow Management

Air traffic flow management plays a crucial role in efficient aviation. Most existing studies assume the flight speed as constant throughout the trip, leading to ineffective fixed-speed schedules. To address this issue, we propose a new problem model, which allows variable speed control to improve the flexibility and maneuverability of the management. In addition, we consider two conflicting objectives, which are minimizing the total flight delays and conflicts between flights, where the conflicts depend on the flight 4D trajectories (3D position plus time). To solve this new challenging problem, we propose a novel multi-objective evolutionary algorithm with new problem-specific individual representation and search operators. Specifically, the multi-chromosomes encoding scheme is designed to adapt to different types of operations. Then, to search the huge search space effectively, we develop a hybrid crossover operator that recombines the parents based on their flight routes. Furthermore, to balance the exploration and exploitation, we develop a new mutation strategy to utilize the heterogeneous search potential of different individuals. For exploitation, the knee individual in the Pareto front is improved by a new time shift operator for exploitation, and other non-dominated solutions are mutated by fixed-route mutation. For exploration, the dominated solutions are mutated randomly. To verify the effectiveness, we compare it with the real air traffic flow management schedules and the state-of-the-art algorithms on a range of real-world air traffic datasets. Extensive results show that the proposed algorithm can significantly outperform the baselines in generating safe and efficient 4D trajectories.

Impact pressure coefficient and object mobilization length in mass flows

As the impact force of a flow overcomes the frictional resistance of an object, the object moves as long as the pressure exerted by the flow is greater than its shear resistance. With this concept, here, we develop simple analytical models for the mechanical description of the coefficient of impact pressure Cp0 and the mobilization length L when a mass flow impacts a movable object. We invented the obstacle mobilization number Cp0, a dimensionless number, which is expressed as the ratio of the obstacle shear resistance to the kinetic energy of the flow, per unit length. We also relate it to the obstacle Froude number Fr0. When the object moves through the length L against the basal friction, after consuming its kinetic energy, the object eventually stops. This balance between the kinetic energy and friction yields an analytical model for the mobilization length of the object. Equivalently, if the mobilization length is known, the impact velocity can be calculated. This is very important in estimating the flow velocity of any large-scale natural mass flows. Our model predicts that Cp0 decreases strongly to weakly non-linearly with the impact velocity, density ratio between the granular particle and the mobile object, and the area ratio between the grain covered area of the object and its base. Moreover, Cp0 increases linearly with the basal friction coefficient. However, the dynamic response of Cp0 to the shape of the object may vary immensely between objects of different shapes. Our model also predicts that the mobilization length L of the mobile object varies with the square of the impact velocity of flowing mass, but decreases with basal friction of the obstacle and the component of gravitational acceleration in the direction normal to the flow depth. We conduct several laboratory chute experiments with different native Nepalese complex fruit seeds and food grains to validate the physical significance and scope of Cp0 and L. Our simple analytical models very well describe the coefficient of impact pressure and the mobilization length of the mobile object impacted by the laboratory granular flows. We discuss the applicability of Cp0 and L to real flow situations in designing protective civil defense structures as well as mitigating from natural disasters, and industrial transports of complex granular flows.

The influence of membrane fiber arrangement on gas exchange in blood oxygenators: A combined numerical and experimental analysis

Oxygenators take over lung function in the event of severe lung injuries by exchanging gas into the blood stream using hollow fiber membrane mats. A central limitation of oxygenators is their large foreign surface area and priming volume, which cause blood damage.Thus, gas exchange efficiency needs to be improved through an understanding of the interaction between fiber arrangement and blood flow directions. This has only been investigated in two dimensional or simplified non-realistic fiber bundles. The aim of this study was to quantify gas exchange in realistic 3D fiber bundles.We performed three dimensional micro scale CFD simulations of different realistic fiber arrangements and flow directions that we validated in corresponding test oxygenators using porcine blood.Fiber-configurations influence gas transfer by factor 2, with highest transfer rates for blood flowing in circumferential direction, and lowest for longitudinal direction in wound oxygenators. The CFD model correlates with the experiments with an R2 = 0.88.For the first time, the configuration of realistic 3D fiber bundles was proven to strongly influence gas transfer in oxygenators, in simulations and experiments. The CFD model serves for investigation of further configurations and to derive transfer coefficients for full scale oxygenators.

Collateral flow and pulsatility during large vessel occlusions: insights from a quantitative in vitro study.

Acute ischemic stroke caused by large vessel occlusions is being increasingly treated with neurovascular interventions. The hemodynamics within the collateral system of the circle of Willis (CoW) hemodynamics play a fundamental role in therapy success. However, transient in vivo data on pathological collateral flow during large vessel occlusions are not available. Moreover, there are no flow models that accurately simulate the hemodynamic conditions in the CoW during large vessel occlusions. We used a circulatory loop to generate highly reproducible cerebrovascular-like flows and pressures and used non-invasive flow visualization and high-resolution flow and pressure measurements to acquire detailed, time-dependent hemodynamics inside an anatomical phantom of the CoW. After calibrating a physiological reference case, we induced occlusions in the 1. middle cerebral artery, 2. terminal carotid artery, and 3. basilar artery; and measured the left posterior communicating artery flow. Mean arterial pressure and pulse pressure remained unchanged in the different occlusion cases compared to the physiological reference case, while total cerebral flow decreased by up to 19%. In all three occlusion cases, reversed flow was found in the left posterior communicating artery compared to the reference case with different flow magnitudes and pulsatility index values. The experimental results were compared with clinical findings, demonstrating the capability of this realistic cerebrovascular flow setup. This novel cerebrovascular flow setup opens the possibility for investigating different topics of neurovascular interventions under various clinical conditions in controlled preclinical laboratory studies.