Comparing flow-based and anatomy-based features in the data-driven study of nasal pathologies

Introduction: We examined the viability of pairing wire-obtained flow pressure data with computational fluid dynamic (CFD) analysis for accurate patient-specific 3D reconstruction of flow through cerebral vessels—an approach that provides comprehensive velocity data and other flow parameters to assist the preventative diagnosis of cerebral stenosis. Methods: Two physical phantom models of a cerebral stenosis—differing in regard to vascular morphology at and around the stenosis—were prepared, filled with physiological saline and connected individually to a flow pump (Vascular Simulations LLC Left Heart Replicator) applying pulsatile flow. Pressure measurements were taken upstream of the stenosis by microcatheter-guided wires to define an inlet boundary condition for CFD analysis. Pressure and velocity at 2 cm proximal to stenosis, the stenosis inlet, the stenosis outlet, and 2 cm distal to stenosis were measured to validate the CFD simulated flow. Results: Excellent agreement was observed between CFD and wire-measured time-dependent flow pressure, with the expected pulsatile behavior observed at each location. Between the two methods, differences in maximum systolic pressures ranged between |0.73±0.72|% and |3.90±0.74|%. Differences in minimum diastolic pressures ranged between |1.79±1.33|% and |9.08±1.42|%. Velocity data from wire measurements lacked pulsatile behavior and showed differences ranging between |2.93±5.20|% and |120.10±2.91|% from CFD-obtained measurements, which did show correct pulsatile behavior. Larger discrepancies were strongly associated with areas of higher CFD predicted velocities (r=0.86). Conclusion: Guidewire flow measurements provided CFD analysis with accurate inlet boundary conditions and validated CFD simulation results. CFD analysis allowed for detailed visualization of key flow parameters that may be difficult to physically measure—such as velocity—that are relevant for understanding risk factors associated with cerebral stenosis on a case-by-case basis.

QFA (quench factor analysis) method is widely used to predict the mechanical properties such as hardness and strength according to temperature of quenched material that has to be determined by experimental heat treatment. But, QFA coupled with CFD (computational fluid dynamics) analysis of this study can predict the mechanical properties without the experiment of heat treatment except the experiment to determine the material constants of QFA. First of all, Jominy test and FPS (flexible polyhedron search) are performed to determine the material constants of QFA. The CFD analysis is applied to predict the cooling temperature of Al6061 cylinder cooled by water of 25°C during quenching of solid solution heat treatment. Hardnesses of T6 heat treated Al6061 cylinder is predicted by the QFA coupled with CFD analysis without experiment of heat treatment and then the predicted hardnesses are compared with experimentally measured hardnesses according to positions of cylinder. The predicted hardnesses of cylinder are in good agreement with the measured ones within a maximum error of 8.45%.

Computational Fluid Dynamics (CFD) analysis results and experimental data are presented for the Pennsylvania State University's (PSU) Propulsion Engineering Research Center (PERC) rocket based combined cycle (RBCC) rocket-ejector experiments. The PERC RBCC experimental hardware was tested in direct-connec t configuration operating in diffusion and afterburning (DAB) combustion. Two of the test points had similar experimental hardware but significantly different rocket and air flow rates resulting in significantly different plume-to-air mixing characteristics. At the design point mass flow rates the plume-to-air mixing was diffusion dominated. At a test point with mass flow rate below the design point, the mixing rate was enhanced due to recirculation of plume gases. The objective of this paper is to provide insight into the fluid dynamics responsible for this change in ejector mode mixing characteristics of the RBCC. The plume-to-air mixing of the two test points is measured experimentally with Raman Spectroscopy specie distribution. CFD analysis is used to interpret the experimental data and illustrate the fluid dynamics of the two different mixing processes. Experimental data and CFD analysis of intermediate mass flow rates are used to illustrate the transition from diffusion dominated mixing to recirculation dominated mixing. Nomenclature AR = area ratio d = duct height, 12.7 cm (5 in.) h = horizontal position PC = chamber pressure x = axial position

Passive cooling of the PBMR spent and used fuel tanks

Modeling and experimental analysis of packed column for SO2 emission control process

The objective of this paper is to present the performance comparison of 2D Computational Fluid Dynamics (CFD) analysis with experimental analysis of 0.6 m impulse turbine with fixed guide vanes for both 0.6 and 0.7 hub to tip ratio (H/T). Also the comparison of 2D CFD analysis of the said turbine with different values of H/T ranging from 0.5 to 0.7. A 2D-cascade model was used for CFD analysis while uni-directional steady flow was used for experimental analysis. The blade and guide vane geometries are based on 0.6 m rotor diameter, with optimum profile, and different H/T of 0.5, 0.6 and 0.7. It was concluded from 2D CFD analysis that 0.5 H/T ratio performances was higher than that of 0.6 and 0.7 H/T at peak efficiency and the operational flow range for 0.5 H/T was found to be wider than that of 0.6 and 0.7 H/T ratio.

Achieving minimum pressure loss and exit temperature pattern factors are the two important, but conflicting performance goals of a gas turbine combustor. In this study, Taguchi method was used to design CFD (Computational Fluid Dynamics) analysis based experiments in order to arrive at optimized liner hole sizes (primary and dilution) of an annular gas turbine combustor. The CFD experiments were steady & three-dimensional Reynolds Averaged Navier-Stokes (RANS) based analyses performed on a 20-degree sector combustor model. Nine CFD analyses were performed as per the Taguchi L-9 orthogonal array, based on which, an optimal hole configuration was arrived. An additional CFD run was carried out to verify the predicted result. The optimized hole size combination reduces the Circumferential Pattern Factor (CPF) by 28% and pressure loss by 0.06% (difference between absolute values of percentage pressure losses) in comparison to the baseline configuration.

PurposeWind loading calculations are currently performed according to the ASCE 7 standard. Values in this standard were estimated from simplified models that do not necessarily take into account relevant flow characteristics. Thus, the standard does not have provisions to handle the majority of rooftop photovoltaic (PV) systems. Accurate solutions for this problem can be produced using a full-fledged three-dimensional computational fluid dynamics (CFD) analysis. Unfortunately, CFD requires enormous computation times, and its use would be unsuitable for this application which requires real-time solutions. To this end, a real-time response framework based on the proper orthogonal decomposition (POD) method is proposed.Design/methodology/approachA real-time response framework based on the POD method was used. This framework used beforehand and off-line CFD solutions from an extensive data set developed using a predefined design space. Solutions were organized to form the basis snapshots of a POD matrix. The interpolation network using a radial-basis function (RBF) was used to predict the solution from the POD method given a set of values of the design variables. The results presented assume varying design variables for wind speed and direction on typical PV roof installations.FindingsThe trained POD–RBF interpolation network was tested and validated by performing the fast-algebraic interpolation to obtain the pressure distribution on the PV system surface and they were compared to actual grid-converged fully turbulent 3D CFD solutions at the specified values of the design variables. The POD network was validated and proved that large-scale CFD problems can be parametrized and simplified by using this framework.Originality/valueThe solar power industry, engineering design firms and the society as a whole could realize significant savings with the availability of a real-time in situ wind-load calculator that can prove essential for plug-and-play installation of PV systems. Additionally, this technology allows for automated parametric design optimization to arrive at the best fit for a set of given operating conditions. All these tasks are currently prohibited because of the massive computational resources and time required to address large-scale CFD analysis problems, all made possible by a simple but robust technology that can yield massive savings for the solar industry.

Background: Fractional flow reserve (FFR) is used to evaluate the need for percutaneous coronary intervention (PCI) in cases of moderate stenosis of the coronary artery. Recently, diagnostic imaging support with computational fluid dynamics (CFD) analysis has been garnering attention. This study defines the relationship between FFR conducted for cardiac catheterization and CFD analyses conducted using coronary computed tomography (CT) for moderate stenosis, in addition to considering whether wall pressure (WP) and wall shear stress (WSS) can be used to evaluate ischemia.Methods and Results: Cases in which FFR was measured via coronary CT and cardiac catheterization was performed within 3 months were collected retrospectively. In the CFD analysis, WP and WSS were calculated and compared with FFR. Three groups were created to compare results of CFD analysis and FFR values according to the location of the stenosis: the right coronary artery, the left anterior descending artery, and the left circumflex artery. There was a correlation between FFR and WSS according to CFD analysis for moderate stenosis of the coronary artery, with a cut-off value for treatment able to be calculated.Conclusions: The results of this study suggest that ischemia can be evaluated by conducting CFD analysis (WSS) using coronary CT.

The actual underlying mechanisms of acute type A aortic dissection (AAAD) are not well understood. The present study aimed to elucidate the mechanism of AAAD using computational fluid dynamics (CFD) analysis. We performed CFD analysis using patient-specific computed tomography imaging in 3 healthy control cases and 3 patients with AAAD. From computed tomography images, we made a healthy control model or pre-dissection model for CFD analysis. Pulsatile cardiac flow during one cardiac cycle was simulated, and a three-dimensional flow streamline was visualized to evaluate flow velocity, wall shear stress and oscillatory shear index (OSI). In healthy controls, the transvalvular aortic flow was parallel to the ascending aorta. There was no spotty high OSI area at the ascending aorta. In pre-dissection patients, accelerated transvalvular aortic flow was towards the posterolateral ascending aorta. The vortex flow was observed on the side of the lesser curvature in mid-systole and expanded throughout the entire ascending aorta during diastole. Systolic wall shear stress was high due to the accelerated aortic blood flow on the side of the greater curvature of the ascending aorta. On the side of the lesser curvature, high OSI areas were observed around the vortex flow. In all pre-dissection cases, a spotty high OSI area was in close proximity to the actual primary entry site of the future AAAD. The pre-onset high OSI area with vortex flow is closely associated with the future primary entry site. Therefore, we can elucidate the mechanism of AAAD with CFD analysis.

Mechanical Heating Ventilation and Air-Conditioning (HVAC) systems account for 60% of the total energy consumption of buildings. As a sector, buildings contributes about 40% of the total global energy demand. By using passive technology coupled with natural ventilation from wind towers, significant amounts of energy can be saved, reducing the emissions of greenhouse gases. In this study, the development of Computational Fluid Dynamics (CFD) analysis in aiding the development of wind towers was explored. Initial concepts of simple wind tower mechanics to detailed design of wind towers which integrate modifications specifically to improve the efficiency of wind towers were detailed. From this, using CFD analysis, heat transfer devices were integrated into a wind tower to provide cooling for incoming air, thus negating the reliance on mechanical HVAC systems. A commercial CFD code Fluent was used in this study to simulate the airflow inside the wind tower model with the heat transfer devices. Scaled wind tunnel testing was used to validate the computational model. The airflow supply velocity was measured and compared with the numerical results and good correlation was observed. Additionally, the spacing between the heat transfer devices was varied to optimise the performance. The technology presented here is subject to a patent application (PCT/GB2014/052263).

Inferior turbinate reduction (ITR) is a commonly performed procedure for the treatment of nasal obstruction. Which portion of the inferior turbinates should be surgically addressed to improve nasal airflow has yet to be determined. To use computational fluid dynamics (CFD) analysis to evaluate the airflow changes after reduction along different portions of the inferior turbinate. Computed tomographic scans of 5 patients were selected. Seven CFD models were created for each patient: 1 unaltered and 6 various ITRs, including 3 one-third ITRs (anterior, middle, and posterior one-third); 2 two-thirds ITRs (anterior and posterior two-thirds); and 1 full-length ITR model. Total airflow rate and nasal resistance was obtained through CFD analysis, and regression analysis was performed on the increased nasal volume, locations, and nasal resistance for all 5 patients. Total airflow rate and nasal resistance was obtained through CFD analysis, and regression analysis was performed on the increased nasal volume, locations, and nasal resistance for all 5 patients. Full ITR over the whole length was consistently most effective to improve nasal airflow and resistance for all 5 patients (2 men and 3 women), adjusted for the volume. Regression analysis showed a strong linear (R2≥0.79) relationship between nasal volume changes and nasal airflow. However, the most effective location of partial turbinate reduction was not consistent among patients. Surprisingly, for some patients, posterior ITRs were more effective than anterior ITRs. The site of most effective partial ITR differed from 1 side to the other even in the same individual. The effectiveness of partial ITR and target location likely depends on individual patient anatomy. The fact that full ITRs were consistently most effective and the linear regression between flow and nasal volume changes may indicate that the entire length of the IT has a functional impact on nasal airflow and resistance. NA.

<p>Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) analysis were performed in this work in order to obtain the best design for safety and aerodynamic performance of the bicycle cycling helmet. FEA analysis was computed on two different helmet designs to determine the critical area subjected to impact. A pressure load was applied on the helmets’ outer surface to simulate oblique loading. The critical areas of the helmets were then highlighted and identified, enabling design improvements to be made on both designs. CFD analysis was then executed in order to obtain the lowest drag coefficient number in reducing the air resistance induced by both of the helmet designs, inherently increasing cyclist performance and ensuring competition success.</p>

Port design is an integral part of a combustion system. For a spark-ignited engine, it impacts both in-cylinder charge motion and performance potential. While turbulence intensity and air-mixture quality affect dilution tolerance and fuel economy as a result, breathing ability affects wide open throttle performance. Traditional approaches deploy experimental techniques to reach a target balance between the charge motion and breathing capacity. Such techniques do not necessarily result in an optimized solution. Unrelenting development of Computational Fluid Dynamics (CFD) tools, Design of Experiment (DOE) and optimization techniques combined with increased computational power led to the development of new methodologies over the past decade. Such advancements have the potential to deliver optimized solutions. Recent releases of engineering CAD packages, like CATIA V5 and Pro-Engineer, enable both parametric modeling and associative design update. This paper demonstrates a coupling process between CFD analysis and engineering CAD software using process integration and design optimization software (PIDO). CATIA V5, ICEM-CFD meshing tool and FLUENT-UNS CFD code were integrated to run through many port designs using ISIGHT. The automatic coupling was aimed at optimizing the port layout for a certain cost function such as flow restriction or charge motion, subject to manufacturing and packaging constraints. Accomplishing this task necessitates running the executables of various software using macros and scripts. This integrating methodology utilized best design practices for an intake port, and numerous numerical experiments were attempted. This methodology was demonstrated on a V-engine intake port with geometric, manufacturing and packaging constraints. In order to prove the methodology described, two distinct designs were attempted, the first of which demonstrated high flow at the expense of charge motion, while the other targeted tumble charge motion to the detriment of flow. Both concepts were prototyped and evaluated on the flow bench. Good correlation between simulation and test results was demonstrated in this study. It was concluded that this process could be reliably adopted in a production environment with reasonable amount of turn around time.

CFD (Computational Fluid Dynamic) analysis is a modern technique to estimate and determine fluid characteristics. CFD uses the Navier-Stokes equation to solve complex fluid behavior along with turbulence models such as k-Ɛ which is well known for solving engineering and scientific problems. The objective of this paper is to determine the performance of an industrial component in the pipeline "Bermad Air Valve" where this valve plays a key role in releasing and intaking air volume in a pressurized system. The air valve has three different positions, fully open, partially closed, and fully closed. The procedure started with preparing the geometry, meshing, and boundary condition setup for a fully and 99% closed valve. The results were compared with the experimental air valve test along with CFD analysis done previously in an experimental article. The final data gathered from the valve outlet shows that CFD is an effective engineering tool to predict fluid behavior.