Pressure Coefficient Cp Research Articles

Wind-driven and buoyancy effects for modeling natural ventilation in buildings at urban scale

This work proposes a new model to evaluate the air changes per hour (ach) due to natural infiltrations in buildings. This modeling already exists at building scale, but the new model will implement the hourly ventilation load in a physical-based modeling for space heating and cooling in buildings at urban scale. The proposed improvement considers the wind and buoyancy effects in the calculation of hourly achs in a high-density urban context. A three-zone air flow lumped modeling is applied to describe the air flow in buildings; the air flow rate due to infiltrations is calculated depending only on leakages’ characteristics and pressure variations in various climate conditions. The non-linear equations system of mass and energy conservation is solved by an iterative procedure using the Newton-Raphson numerical method. Besides, two different methodologies are compared to evaluate the external dynamic and static pressure conditions on building façades: experimental values (pressure coefficients Cp) and CFD simulations. For the latter, the air flow field in the urban canyons is described by the windy conditions and by imposing a temperature gradient due to solar irradiation between the windward and leeward facades. This methodology is applied to three urban canyons in Turin, with typical aspect ratios and orientations for some local climate conditions considering both heating and cooling seasons. Comparing the results of hourly ach obtained from the Cp method, the CFD technique allows to modulate the ach considering the impact of the canyon dimension, wind and buoyancy effect of non-isothermal condition, in varying the wind speed on the façades of buildings for different scenarios. It also overcomes the limit of field of applications of Cp, especially in high-density built urban environments. The encouraging results of this work will lead to future developments of the three-zone lumped model and its numerical solution techniques.

Analysis of Unsteady Flow and Interstage Interference of Pressure Pulsation of Two-Stage Pump as Turbine Under Turbine Model

The process pump as turbine (PPAT) serves as a crucial component for recovering high-pressure energy from mediums used in chemical and refining processes. Ensuring the long-term safe and stable operation of PPAT in high-temperature and high-pressure environments is essential, with pressure pulsation being one of its most significant external characteristic indicators. This study investigates the evolution of vortex structure distribution and the generation and propagation mechanisms of pressure pulsation in a two-stage PPAT operating in turbine mode. Results indicate that the uniformity of the pressure coefficient (Cp) gradient distribution is poorer in the first stage runner compared to the second stage, with a larger distribution area of high-strength vortices. In the draft tube, vortex strength increases with rising flow rates, and the flow around the circular cylinder on one side gradually develops to both sides. In the two-stage diffusers, the primary source of pressure pulsation is the dynamic and static interference effect between the two impellers and the corresponding diffuser tongue. The interstage interference with a frequency of n*15fn is most pronounced in the inflow runner, gradually weakening along the flow direction, and ultimately disappearing in the draft tube. In addition, more low-frequency signals with a frequency of 0.5fn are captured in the draft tube under large flow conditions, which is mainly generated by the vortex band in the draft tube. The low-frequency pulsation energy is high and the attenuation is slow, which has a great destructive effect on the energy recovery system of the PPAT.

Position query-guided cross-modal flow field prediction model of a transonic compressor cascade

The gradient of flow parameters in a transonic compressor cascade flow field varies significantly, especially in the region of shock waves, which causes a significant challenge to its high-precision flow field prediction. In this study, the position query-guided cross-modal flow field prediction model (PGCM) is proposed to effectively predict the flow field parameter distribution of a transonic compressor cascade. The PGCM utilizes the self-attention mechanism for the global and deep geometric feature extraction of configurations, which contributes to an in-depth understanding of the spatial relationships between coordinate points within the flow field, accurately capturing and analyzing the structural complexity of a compressor cascade flow. In addition, the PGCM integrates the cross-attention mechanism that establishes correlations between different input sequences, which enhances the performance of the model in querying and interpreting flow parameters at specific coordinates. The flow field prediction models are developed to predict the flow parameter distributions of different cascade geometries at Mach numbers of 0.78 and 0.93, respectively. The validation results indicate that the PGCM performs significantly better than the existing convolutional neural network and vision transformer, especially in the prediction of the pressure coefficient Cp distribution. The PGCM is adaptable to the variation of flow conditions and geometrical configurations efficiently and accurate in predicting the flow field of a compressor cascade. This paper demonstrates the promising potential of conducting the multi-modal information fusion to enhance the capability of flow field prediction.

Machine Learning for Dynamic Pressure Coefficient Prediction in Vertical Water Jets

Vertical water jets present significant challenges for hydraulic structures due to their potential to cause erosion and structural damage. This study aimed to predict the dimensionless pressure coefficient (Cp) of vertical water jets by examining the relationships between experimental parameters, such as Froude number, slope, and the ratio of waterfall height over the product of the Froude number and diameter, referred to as α, using machine learning models. Two hundred forty controlled experiments were conducted, with pressure data collected. To address the problem’s non-linearity, six machine learning models were tested: linear regression, K-nearest neighbors, decision tree, support vector regression, random forest, and XGBoost. The XGBoost model outperformed others, achieving an R-squared of 0.953 and a Root Mean Squared Error (RMSE) of 0.191. Residual analysis validated its better performance, demonstrating that it delivered the most accurate predictions with minimal bias. Feature importance analysis revealed the Froude number was the most significant predictor, followed by slope and diameter. This study emphasizes the importance of the Froude number in predicting jet behavior and shows the efficacy of advanced machine learning models in capturing complex fluid dynamics, providing valuable insights for optimizing engineering applications such as water jet cutting and cooling systems.

Aerodynamic performance optimization of a UAV's airfoil at low-Reynolds number and transonic flow under the Martian carbon dioxide atmosphere

Unmanned aerial vehicles (UAV) on Mars operate in a thin atmosphere of carbon dioxide, where the flow Reynolds number and local sound velocity are significantly reduced compared to the Earth's atmosphere because of low gas density and temperature. Therefore, a Mars UAV with a rotary-wing design can operate in a state of low-Reynolds number (Re = 1-5 × 104) and transonic flow (Matip = 0.7–1.2), where flow separation and shock waves occur simultaneously. The interaction between flow separation and shock waves not only makes the entire flow field more complex but also seriously affects the aerodynamic performance of the airfoil, thereby reducing the payload of UAVs, which previous aircraft designs based on the thick atmospheric environment of the Earth have not considered. Therefore, in this study, a numerical simulation method is used to conduct airfoil optimization research on a characteristic airfoil under low-Reynolds number transonic flow (Re = 33200, Ma = 0.85) conditions to acquire additional insight, improve aerodynamic performance of the airfoil, and enhance the payload. The results were compared with the optimization results of subsonic flow (Re = 19500, Ma = 0.50). The Hicks-Henne bump functions method was selected for airfoil parameterization, and non-dominated sorting genetic algorithms (NSGA)-Ⅱ were used for optimization. Through an analysis of the pressure coefficient (Cp), surface friction coefficient (Cf), and density gradient, the number and intensity of oblique shock waves on the upper and lower surfaces were observed to significantly affect the aerodynamic performance of airfoils under low-Reynolds number flow. The changes in flow separation and transition positions do not directly affect the aerodynamic performance but weaken the oblique shock wave intensity induced by the separation point or directly transform strong shock waves into weaker compression waves because of the absence of flow separation. The optimization results for both subsonic and transonic flow point to a thinner overall shape with a flatter surface with the drag greatly reduced due to the disappearance of shock waves on the lower surface, which significantly improves aerodynamic performance. Compared with the original airfoil, at Ma = 0.85, this design can increase the lift coefficient (Cl) by at least 124 % and lift drag ratio (Cl/Cd) by 177 %.

Influence of solvent viscosity ratio on the creeping flow of viscoelastic fluid over a channel confined circular cylinder

In this study, the role of solvent viscosity ratio (β) on the creeping flow characteristics of Oldroyd-B fluid over a channel-confined circular cylinder has been explored numerically. The flow governing equations have been solved by RheoTool, an open-source toolbox based on OpenFOAM, employing the finite volume method for extensive ranges of Deborah number (De=0.025–1.5) and solvent viscosity ratio (β=0.1–0.9) at a fixed wall blockage (B = 0.5). The present investigation has undergone extensive validation, with available literature under specific limited conditions, before obtaining detailed results for the relevant flow phenomena, such as stream function, pressure and stress contour profiles, pressure coefficient (Cp), wall shear stress (τw), normal stress (τxx), first normal stress difference (N1), and drag coefficient (CD). The flow profiles have exhibited a distinctive behavior characterized by a loss of symmetry in the presence of pronounced viscoelastic effects. The results for low De notably align closely with those for Newtonian fluids, and the drag coefficient (CD) remains relatively constant regardless of β, as the viscoelastic influence is somewhat subdued. These observations indicate that at high De and low β, viscoelasticity causes asymmetry in creeping flow around a circular cylinder. With an increase in De, the maximum velocity in gap between cylinder and channel walls increases; however, the cylinder experiences significantly less drag force. Within this parameter range, the prevailing force governing the flow is the pressure drag force.

Physics-Informed Machine Learning Using Low-Fidelity Flowfields for Inverse Airfoil Shape Design

Physics-informed neural networks (PINNs) are a class of scientific machine learning that utilizes differential equations in loss formulations to model physical quantities. Despite recent developments, complex phenomena such as high-Reynolds-number (high-Re) flow remain a modeling challenge without the use of high-fidelity inputs. In this study, a low-fidelity-influenced physics-informed neural network (LF-PINN) is proposed as a surrogate aerodynamic analysis model for inverse airfoil shape design at Re=1.0×106. The LF-PINN is developed in a hybrid approach using low-fidelity flowfields approximated from a viscous-inviscid coupled airfoil analysis tool (mfoil) and physics residuals from the steady, incompressible, two-dimensional Navier–Stokes (NS) equations. The approach is designed to alleviate offline computational costs by avoiding high-fidelity simulations and sustain predicting accuracy using corrections by the physics residuals. The LF-PINN is able to correct the low-fidelity flowfield quantities toward the ground truth, with a mean improvement of about 19% in pressure and about 5% in total velocity based on Euclidean distance comparisons. Evaluation of the airfoil surface pressure coefficient Cp distributions shows corrections by the LF-PINN at the suction peak, which largely contributes to lifting forces. Inverse airfoil shape design is conducted using target Cp distributions in the objective function, whereby the LF-PINN can approach the expected target shapes while reducing online computational time by at least an order of magnitude compared to direct airfoil analysis tools.

Research on the air-infiltration rate shelter coefficient of building complexes based on building parameter clustering

The configuration of a building complex can significantly influence the air-infiltration rate, which subsequently affects the energy consumption for heating and cooling. Given the diversity of parameters associated with a building complex, it is challenging to study all combinations. This study proposed the k-means clustering method to identify representative building clusters, thereby facilitating the derivation of correction coefficient for the air-infiltration rate within a complex. Initially, data pertaining to district characteristics, such as the complex density, height, and building aspect ratio, were collected and clustered to obtain several representative groups of building clusters. Subsequently, a validated computational fluid dynamics program with the renormalization group (RNG) k–ε turbulence model was employed to investigate the spatial characteristics of the pressure coefficient (Cp) on building surfaces across various groups within the complex. Finally, the shelter coefficient (SAIR), which represents the ratio of an individual building to those in different groups, was determined to correct for the air-infiltration rate in diverse district types. The results show that SAIR varies considerably (from 0.15 to 0.53) owing to the different densities, heights, and layouts between buildings. The applicability of SAIR was further demonstrated and verified in a case study of a building in Dalian, China. The research results can provide a method for predicting the air-infiltration rate of building complex.

A Computational Investigation of the Influence of Seafloor Conditions on the Turbulent Flow Characteristics of an Autonomous Underwater Vehicle

The effect of the seabed on the hydrodynamics of three-dimensional autonomous underwater vehicles (AUVs) varies according to the physical conditions of the place where AUVs interact with the environmental conditions. This study examines the hydrodynamics of an AUV resembling a torpedo model while taking the influence of the seabed surface as a function of the dimensionless distances (G/D) between the torpedo and the seabed. Reynolds numbers, varying from 1 × 104 to 8 × 104, were considered. These Reynolds numbers were associated with various seabed distances falling within 0.25 ≤ G/D ≤ 1.5. To perform the simulations, governing equations were utilized and incorporated with the k–ω SST turbulence model. It has been observed that when AUVs or torpedo models operate in close proximity to the seabed surface, several key hydrodynamic parameters and flow characteristics are affected. These include the pressure coefficient (Cp), drag coefficient (CD), overall flow structures, maneuverability, and performance of the torpedo model. As the AUV or torpedo model approaches the seabed surface, the symmetrical flow pattern deteriorates. This deterioration is associated with changes in vortical flow structures under the influence of seabed surfaces. Additionally, the intensity of the shear stress (τ) near the seabed surface gradually increases as the AUV or torpedo model gets closer to it. In summary, the proximity of AUVs or torpedo models to the seabed surface causes disruptions in the flow patterns, increased shear stress, and alterations in key hydrodynamic parameters, ultimately affecting the system's performance and behavior.

On the effect of pressure coefficient source on the energy demand of an isolated cross-ventilated building

Natural ventilation is a simple and effective measure to both reduce the cooling demand of buildings and improve the indoor air quality. In the prediction of heating and cooling demands by means of building energy simulations (BES), the use of pressure coefficients (Cp) from databases as input for the airflow network model is the common approach. Cp values for the same building typology may differ according to the adopted database and are generally unavailable for buildings with complex geometry. Employed Cp values may lead to differences in BES results. This manuscript presents a comparison, for different wind directions, between the Cp distributions and mean values on the facades of a detached building obtained with full-scale CFD – Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) – simulations, from a database and from wind-tunnel experiments. The obtained pressure coefficients are used in the BES of a naturally ventilated building and the energy demand difference between the four approaches is quantified. Four climate zones (tropical, dry/desertic, temperate, continental) are considered. Although, in terms of accuracy of Cp prediction, LES outperforms RANS for all the wind directions considered, annual cooling energy demand is found to be relatively insensitive to the source of Cp for the current case study, while predicted peak cooling values differ up to 10.8%. On the other hand, the prediction of annual heating energy demand in cold climates varies up to 3% depending on the Cp source employed for BES simulations.

Numerical investigation on flow and heat transfer of the rotating spherical particle in a supercritical water crossflow environment

The supercritical water gasification reactor provides a green and efficient method for the utilization of organic resources such as coal and biomass. It is important to note that collision-induced particle rotation in the reactor will affect the flow and heat transfer characteristics between the particles and the fluid. At present, there is a lacking consideration of particle rotation in the supercritical water environment. The purpose of this paper is to investigate the effects of dimensionless rotation rate (Ω∗) and particle Reynolds number (Rep) on drag coefficient (Cd), lift coefficient (Cl) and average Nusselt number (Nu) for the single particle in a supercritical water crossflow under two rotation modes, with rotation axes parallel and perpendicular to the jet direction. The flow field, temperature field, boundary layer, and surface pressure coefficient (Cp) were analyzed to interpret the variation of the particle dimensionless coefficients (Cd, Cl and Nu). It was found that the value of ∣Cp∣ on the particle surface rose at different locations for the two rotation modes, leading to an increase in the pressure drag and dominating the total drag force. However, the two rotation modes produced different deviating effects on the average Nusselt number. Ultimately, new correlation formulas of Cd, Cl and Nu for a rotating spherical particle in a supercritical water environment were proposed based on the results of numerical simulations, with a maximum deviation of 8.52%.

Numerical Analysis of Aerodynamic and Shock Wave Characteristics of Biconvex and Double-Wedge Shape Airfoils for Supersonic Flow

This present study describes the aerodynamic characteristics of supersonic flow over biconvex and double wedge airfoils using a finite volume method-based commercial CFD code Ansys Fluent. A steady-state RANS approach is used with SST k-ω viscous modeling. A series of simulations are conducted to analyze the characteristics of shock and expansion waves formed around the airfoils for Mach numbers ranging from 1.4 to 3.4 with varying angles of attack (α) from 0° to 20°. It is observed that the lift and drag coefficients both increase with the angle of attack for a fixed Mach number and decrease with the Mach number for a fixed angle of attack. Double wedge airfoil generates about 5% more lift at a low Mach number and 1% more lift at a higher Mach number compared to the biconvex airfoil. However, the biconvex airfoil generates lesser drag than the double wedge airfoil. The maximum value of the pressure coefficient (Cp ) is found to be 1.7 for biconvex airfoil and 1.4 for double wedge airfoil. The maximum value of the lift-to-drag ratio for biconvex airfoil is 7.63, occurs at 1.4 Mach number and 3.46° angle of attack, whereas the value for double wedge airfoil is 5.19 at the same Mach number with 4.47° angle of attack, which suggest that biconvex airfoil has a higher lift-to-drag ratio and gives a better aerodynamics performance. The shock waves start to detach after an angle of attack of 5° and the shock wave is fully detached at a 15° angle of attack for biconvex airfoil for Mach number of 1.4. For the same Mach number, the double wedge airfoil, the shock wave starts to form the same as the biconvex airfoil but the waves are fully detached at a lower angle of attack of 10°. With the increasing Mach number, the shock waves remain attached to the airfoil.

Influence of wind pressure patterns on the buckling resistance of hyperboloid steel cooling towers

When multiple cooling towers are built in a power plant, the wind load acting on the tower shell is asymmetrical owing to interference between the cooling towers. However, studies on the buckling resistance of steel cooling towers under asymmetrical wind loads are scarce. In this study, a finite element model of a 160-m-high hyperboloid single-layer reticulated-shell steel cooling tower was established. Nonlinear buckling analyses of the cooling tower were performed by considering 243 symmetrical and 216 asymmetrical wind load patterns to study the influence of the characteristic parameters of the mean wind pressure coefficient (Cp) on the buckling resistance of the cooling tower. The results showed that the most adverse wind load pattern was the distribution with the largest stagnation pressure on the windward side, largest wind suction on the crosswind side, and smallest wind suction on the leeward side. The symmetry of the wind load was not a key factor affecting the buckling resistance of a steel cooling tower. In addition, the characteristic values of Cp have a greater influence on the buckling resistance than the characteristic angles. The effect of the stagnation pressure on the buckling resistance was approximately three times that of the largest wind suction on the crosswind side.

Assessment of urban ventilation in typical Egyptian housing layouts from four eras using a multi-directional CFD analysis

ABSTRACTAir pollution is globally rising, especially in low- and middle-income countries, due to rapid urbanization. In hot arid environments like Egypt, adequate outdoor ventilation is required to aid in the removal of heat and pollutants and provide healthy living environments. In this context, the current research analyses the urban ventilation of typical Egyptian housing layouts using a simulated multi-directional approach. It is significant because few studies on evaluating urban ventilation of housing prototypes were undertaken in Egypt, and the approaches used were employed in nearly no relevant research in the region. Linear parallel, clustered, dot, and clustered-shifted patterns were investigated. Eight wind directions were analyzed to assess five parameters: 1) wind velocity, 2) age of air (aoa), 3) airflow, 4) pressure coefficient (cp) and 5) comfort index. An automated toolkit that enables the simultaneous simulation of several wind directions was employed. It consists of Eddy3D, a validated Grasshopper tool that uses OpenFOAM’s RANS models. The results showed that best velocities were found in the linear-parallel-unaligned and clustered layouts, directions NNE and N. The latter exhibited favorable airflow within its courtyards. In addition, wind directions had little influence on aoa, as did the layout pattern. Uncomfortable wind was greater in the clustered layout and lowest in the clustered-shifted layout. Except for ENE direction, cp was in opposition with ventilation, since W and WNW directions witnessed the greatest cross-ventilation potential. While linear-parallel-unaligned and clustered layouts created optimum ventilation and allowed outdoor activities, they require more research to increase cp and reduce uncomfortable winds.

Flow structure analysis of nanofluid impingement on modified target surface under different design parameters

The flow structures of jet impingement dominate heat and mass transfer process, even the whole thermal performance. In this study, we have inspected the flow structures and mechanism of nanofluid jet impingement onto a dimpled target surface with different design parameters. Investigations are performed for the relative depth of dimple ([Formula: see text]), the jet-to-plate spacing ([Formula: see text]), nanoparticle volume concentration ([Formula: see text]), and Reynolds number (Re) ranging to explore the mechanism of flow structure variations. Results indicate that these parameters have a significant effect on the flow structure of nanofluid jet impingement near the dimpled target surface. The flow begins to separate after passing the edge of the dimple along with the curvature of a dimple. [Formula: see text] will affect the form and location of flow separation and reattachment, and [Formula: see text] will affect the intensity of separation flow. The length of the flow separation bubble varies in different [Formula: see text] cases. When [Formula: see text] increases, the impinging energy and the velocity near the dimple edge decreases. The different Re has little effect on the length of the flow separation bubble and the tendency of the pressure coefficient (Cp). These results can provide further mechanism inspiration for the design of the flow structure of nanofluid jet impingement.

Influence of Buoyancy and Inter-Surface Radiation on Confined Jet Impingement Cooling of a Semi-Cylindrical Concave Plate

Abstract In this article, the confined jet impingement cooling of a semicylindrical concave plate is analyzed numerically. The finite volume approach is applied to two-dimensional numerical simulations in the transient regime. Air is employed as the working fluid and is regarded as nonparticipant for radiation. The investigation is done for different jet Reynolds numbers (Rej) ranging from 100 to 1000, as the Richardson number (Ri) corresponding to this interval ranges between 0.1 and 10. For any Richardson number, the modified Grashof number (Gr*) is fixed at 105. When analyzing the impact of intersurface radiation between the target plate and confined surfaces on the overall cooling performance, three emissivity values (ε= 0.05, 0.5, and 0.95) are taken into consideration. Additionally, simulations are done for the pure convective heat transfer, ignoring intersurface radiation (ε= 0.0). The influence of surface emissivity and the Richardson number on velocity, temperature, and pressure distribution in the flow domain, local dimensionless temperature (θ) alterations on the target plate and confined walls, alterations in convective (Nuc), radiative (Nur), overall Nusselt numbers (Nuovr), pressure coefficient (Cp), and ratio of radiative Nusselt number to overall Nusselt number (Nur/Nuovr) on the target plate are highlighted. The findings demonstrate that surface emissivity has a significant influence on thermal and hydrodynamic boundary layer formation, buoyancy induced flow and heat transfer, and the proportion of intersurface radiation in overall heat transfer rises as the Richardson number and surface emissivity increase. At low Richardson numbers, the pressure in the stagnation region is greater than the atmospheric pressure. However, as the buoyancy effect increases, the pressure in the stagnation region falls below the atmospheric pressure and rises toward the exit.

Experimental study on the evolution of wind turbine wake under streamwise pressure gradients

Wind tunnel experiments were conducted to explore how streamwise pressure gradients, commonly encountered in complex terrains, influence the wake behavior of a small-scale horizontal-axis wind turbine. The study involved measuring the wake characteristics up to 8 rotor diameters downstream in three pressure gradient scenarios: adverse (APG), favourable (FPG), and zero (ZPG) pressure gradients, assessed using the pressure coefficient (Cp) and its spatial gradient (ΔCp/Δx). These experiments were conducted at a rotor diameter Reynolds number of 96,000 with an inflow velocity of 10 m/s. The results indicate that while the pressure gradients have a more substantial impact on the wake’s velocity deficit, they have a minor effect on its velocity distribution. Nevertheless, non-zero pressure gradients cause significant deformations in the wake’s shape and vertical displacement of its center. Specifically, the FPG case demonstrates enhanced wake velocity recovery, whereas the APG case exhibits slower recovery than the ZPG case. Turbulent kinetic energy decreases as the wake progresses downstream in all cases, with the APG case consistently showing higher values at all measurement locations. Moreover, a consistent pattern of axial vorticity is observed close to the rotor across different pressure gradient cases, with the FPG case displaying notable organisation and amplification of axial vorticity.

Numerical Study of Aerodynamic Characteristics of Airflow Around NACA 0012 and NACA 4412 Airfoils at Re = 170000

In this paper, a numerical study of the aerodynamic characteristics using the CFD method of the two-dimensional flow around NACA 0012 and NACA 4412 airfoils at -10 degrees to 25 degrees of angle of attack operating at Re 170000 is presented. The formation of flow patterns, pressure distribution, pressure coefficient (Cp), lift coefficient (Cl), drag coefficient (Cd), moment coefficient (Cm), and skin friction coefficient distribution along the chord The Y+ wall value curve is a validation that the mesh formation is in accordance with the requirements, i.e., a Y+ wall value below 10 for viscous dominant flows and for Spalart-Allmaras turbulent model viscous. The geometry of NACA 0012 and NACA 4412 airfoils is created using SolidWork, and CFD analysis is carried out using Ansys Workbench 2018. The results show that the stall condition at NACA 0012 is at 15 degrees of angle of attack, while at NACA 4412 it is at 16 degrees. Under stall conditions, Cl of NACA4412 is approximately 13 percent higher than NACA 0012, while the value of Cd shows almost the same value for both NACA 0012 and NACA 4412.

Shape optimization of a corner‐recessed square tall building to reduce mean wind pressure using a multi‐objective genetic algorithm

SummaryThe current study aims to determine how the corner recession affects tall buildings with square plans. A series of numerical simulations have been conducted to find the parametric models' wind pressure. Visualization tools, such as contour plots and streamlines, present the wind flow near the buildings. Numerical simulations are conducted using RANS k‐ℇ turbulence models considering a length scale of 1:300. Subsequently, a shape optimization study has been carried out to propose a suitable percentage of corner recession, which should minimize the wind pressure on different faces of the building. As design factors, the amount of corner recession (S) and the wind incidence angle (Ø) are taken, along with the mean pressure coefficients (Cp) on the various building faces. Due to the eight axes symmetry of the building configuration, the random sampling technique is used for the Design of Experiment while accounting for the 0°–45° wind angle of attack. The Response Surface Approximation (RSA) is used to construct surrogate models of the objective functions. The RSA models are validated with wind tunnel test results presented in previously published articles. The optimization study is carried out using the multi‐objective genetic algorithm technique.

Validation of Paras3d Rans Pressure Data with Flight Results Over a Wing-body Rlv Configuration at Supersonic High Angle of Attack Conditions

Winged Reusable Launch Vehicle - Technology Demonstrator (RLV-TD) was successfully flight tested by Indian Space Research Organisation (ISRO). One of the main objectives of this Hypersonic Experiment (HEX) mission is to validate the aerodynamic design and ground based aerodynamic data generation procedure. In this paper, comparison of flight data and CFD estimated pressure coefficient (Cp) over fuselage, wing, vertical tail and rudder are presented at supersonic Mach number and high angle of attack conditions. PARAS3D RANS solver is able to capture the trends as measured in flight. In general, PARAS3D CFD over predicted the compression on windward side and under predicted leeward expansion as compared to flight measurement. In general, CFD predicts Cp close to flight measured value, except over a port in the vertical tail.