CFD Calculations Research Articles

A computational method to predict cerebral perfusion flow after endovascular treatment based on invasive pressure and resistance

Background and objectivePredicting post-operative flow is essential for assessing the risk of adverse events in cerebrovascular stenosis patients following endovascular treatment (EVT). This study aimed to evaluate the accuracy of the CFD simulation model in predicting post-operative velocity, flow and pressure distal to a stenosis, based on cerebrovascular microcirculatory resistance. MethodsThe patient-specific models of the extracranial and intracranial arteries were reconstructed. The cerebrovascular microcirculatory resistance was applied to estimate post-operative blood velocity and flow rates. Pearson correlation and Bland-Altman analyses were used to evaluate the correlation and agreement between CFD calculations and transcranial Doppler (TCD) measurements. ResultsThere was a strong correlation between CFD- and TCD-based mean velocities (r=0.7733; P=0.0002), with volume flow measured by both methods also showing robust correlation (r=0.8621; P<0.0001). Additionally, agreement was found between mean velocities determined by CFD simulation and those estimated by TCD (P=0.2446, mean difference −4.2089; limits of agreement -11.5764 to 3.1586). However, agreement between volume flow from CFD simulations and TCD was less consistent (P=0.0387, mean difference -0.3272, limits of agreement -0.9276 to 0.2731). ConclusionsThe computational method used in this study enables the prediction of hemodynamic changes and offers valuable support in tailoring treatment strategies for cerebrovascular stenosis lesions.

Unsteady aerodynamic modeling and flight trajectory simulation of dual-spin projectile based on DNN and transfer-learning

To evaluate flight performance and aerodynamic characteristics of a dual-spin projectile, the coupled computational fluid dynamics and rigid body dynamics (CFD/RBD) method is commonly used, which can simultaneously solve the flight mechanics and flow field. However, the efficiency is compromised by the large number of CFD calculations required. This paper develops an unsteady aerodynamic modeling method that combines deep neural networks and transfer learning, which can accurately predict unsteady aerodynamics of dual-spin projectiles under varying initial conditions. Considering the influence of flight state and aerodynamic data from short-term historical moments, we integrate them as input features of the aerodynamic model to reduce the impact of long-term historical data. To enhance the model generalization under varying initial conditions, we fine-tune the built aerodynamic model using small amounts of data under new conditions by transfer learning. The proposed method is validated through interpolated and extrapolated prediction cases, respectively. The results indicate that the proposed method can achieve better accuracy and generalizability than long short-term memory neural networks and autoregressive moving average method in unsteady aerodynamic modeling of the dual-spin projectile. By coupling the flight dynamics equations with the aerodynamic model in the time domain, the flight simulation only takes a few seconds, which can reduce computing time by three orders of magnitude compared to the coupled CFD/RBD method.

Preliminary Implementation of High-Resolution Multi-Scale coupling calculations for the entire pressure vessel based on OpenFOAM

Significant coupling effects exist among system components in nuclear pressure vessel. Due to the complex geometric structures, the nuclear industry primarily relies on system codes or sub-channel methods for core safety analysis. However, these methods suffer from low model accuracy and insufficient coupling capabilities. Additionally, the differences in model scales impede direct coupling analysis with the CFD calculations of the plenum system. To address these issues, this paper proposes a multi −scale coupling calculation method for the entire pressure vessel: For the plenum system, detailed CFD modeling is employed, while the core calculations are conducted using CorTAF, a high-resolution core Multiphysics-coupling analysis method developed by our team. A cross-resolution coupling model is utilized to integrate the two, achieving cross-resolution coupling simulations for the entire pressure vessel, encompassing both the plenum and core system. The above method was applied to the coupling calculations of a typical pressurized water reactor’s lower plenum and core, revealing detailed thermal–hydraulic phenomena under precise core flow inlet distribution conditions. The lateral flow at the core inlet exceeds 1 m/s, with the maximum and minimum fluid velocities in the subchannels deviating by up to 70 % from the average velocity of 2.42 m/s. The flow distribution only begins to stabilize after a height of 1.2 m in the core. The paper also includes inlet asymmetric flow reduction calculations. Overall, the method enables multi-scale and multi-physics coupling calculations, which provide significant reference value for improving the accuracy of current core safety analyses.

Design of Input Signal for System Identification of a Generic Fighter Configuration

This article investigates the design of time-accurate input signals in the angle-of-attack and pitch rate space to identify the aerodynamic characteristics of a generic triple-delta wing configuration at subsonic speeds. Regression models were created from the time history of signal simulations in DoD HPCMP CREATETM-AV/Kestrel software. The input signals included chirp, Schroeder, pseudorandom binary sequence (PRBS), random, and sinusoidal signals. Although similar in structure, the coefficients of these regression models were estimated based on the specific input signals. The signals covered a wide range of angle-of-attack and pitch rate space, resulting in varying regression coefficients for each signal. After creating and validating the models, they were used to predict static aerodynamic data at a wide range of angles of attack but with zero pitch rate. Next, slope coefficients and dynamic derivatives in the pitch direction were estimated from each signal. These predictions were compared with each other as well as with the ONERA wind tunnel data and some CFD calculations from the DLR TAU code provided by the NATO Science and Technology Organization research task group AVT-351. Subsequently, the models were used to predict different pitch oscillations at various mean angles of attack with given amplitudes and frequencies. Again, the model predictions were compared with wind tunnel data. Final predictions involved responses to new signals from different models. A feed-forward neural network was then used to model pressure coefficients on the upper surface of the vehicle at different spanwise sections for each signal and the validated models were used to predict pressure data at different angles of attack. Overall, the models predict similar integrated forces and moments, with the main discrepancies appearing at higher angles of attack. All models failed to predict the stall behavior observed in the measurements and CFD data. Regarding the pressure data, the PRBS signal provided the best accuracy among all the models.

Pollutant Dispersion of Aircraft Exhaust Gas during the Landing and Takeoff Cycle with Improved Gaussian Diffusion Model

Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To assess the pollutant emissions and dispersion of aircraft during the landing and takeoff (LTO) cycle, and address air pollution surrounding the airport resulting from flight operations, this study evaluated emissions throughout the LTO phase based on Quick Access Recorder (QAR) data in conjunction with the first-order approximation method. An improved Gaussian diffusion model for mobile point sources was employed to examine the diffusion characteristics of contaminants. Additionally, CFD calculation outcomes for various exhaust velocities and wind speeds were utilized to validate the trustworthiness of the improved Gaussian model. The discussion also encompasses the influence of diffusion time, wind direction, wind speed, temperature gradient, and particle deposition on the concentration distribution of contaminants. The findings indicated that the Gaussian diffusion model aligned with the results of the CFD calculations. The diffusion distribution of contaminants around airports varies over time and is significantly influenced by atmospheric environmental factors, including wind direction, wind speed, and atmospheric stability. Specifically, a change in wind direction from 0° to 45° caused a shift of approximately 1000 m in the contaminant’s center. An increase in wind speed from 3 m/s to 5 m/s led to a decrease in concentration by about 15%. Furthermore, a transition in atmospheric stability from category ‘a’ (very unstable) to ‘f’ (very stable) resulted in a two-order-of-magnitude increase in contaminant concentrations.

The reflection in CFD calculations of influence of mass loading on the separation efficiency in a centrifugal separator

The reflection in CFD calculations of influence of mass loading on the separation efficiency in a centrifugal separator

A fast quadrupole-based analytical model for solving transient heat transfer in ventilated double-skin walls and assessing their energy saving potential

This research proposes a fast and accurate method for modeling transient heat transfer in ventilated double-skin façades (VDFs) with forced ventilation to predict their energy-saving potential. Using the thermal quadrupole formalism, the method solves the VDF problem in the Laplace domain while considering the full transient nature of the heat transfer; the only approximation is in space. The solution involves obtaining a general transfer function that predicts heat transfer rates or air temperatures at ventilated cavity's exit. The quadrupole method is validated against computational fluid dynamic numerical simulations conducted under similar meteorological, design and boundary conditions. A very good agreement was found (less than 3 % average deviation) with a significant reduction in computation time (less than 3s against 6h for CFD calculations). The model is computationally efficient and can consider important factors such as the opacity of the walls, construction materials, and air cavity design parameters. Finally, the model allows the assessment of the energy-saving potential of VDFs under various scenarios compared to conventional systems, which helps contributing to more sustainable building design practices. The energy efficiency of a VDF configuration was compared against a conventional wall system. Energy savings of 8.4 and 5.2 % were obtained, in cold and hot climates respectively.

Multi-fidelity data mining-based design optimization framework for scramjet-based aircraft

Aircraft design faces complex multidisciplinary problems and often involves numerous design variables, making direct optimization a time-consuming task. With the development of big data and machine learning technologies, using data mining methods to assist optimization has become key to addressing the inefficiency in multidisciplinary design optimization (MDO). To address the high cost of data acquisition in current data mining, this paper proposes an aircraft design optimization framework based on multi-fidelity data mining, using a large amount of inexpensive cursory estimation data to execute the MDO process and form a multidisciplinary optimization database. Then, data mining methods are used to decouple disciplinary relationships, transforming multidisciplinary coupling problems into simpler multi-objective problems. Subsequently, under viscous CFD computation conditions, the EDGE-p-BFFD deformation method is used to fine-tune the obtained configurations, further enhancing multidisciplinary performance. Before both optimizations, data mining methods were used to analyze the impact of design variables on objective functions, forming design knowledge and completing variable selection. In the multidisciplinary optimization practice of airbreathing aircraft, it can be found that the proposed framework effectively achieves disciplinary decoupling and explores the relationship between shape and performance. In the multidisciplinary optimization of the waverider based on cursory estimations, particle swarm optimization increased the aircraft's cruising range by 8.74 %. In the multi-objective optimization of the lifting body based on viscous CFD calculations, data mining was used to transform the problem into several key objectives. The MOEA/D algorithm increased the range by 2.9 %, validating the effectiveness of the data mining-based MDO framework proposed in this paper.

New guidelines for ISO 9053 based on CFD simulations of the static airflow resistivity of a perforated solid

The acoustic absorption coefficient of the acoustic absorbers is directly impacted by the airflow resistivity. The ISO 9053 explains the measurement procedure and specify the size and mounting of specimens, and the flow velocities. The main constraint of the standard is to maintain a stable linear flow so that the resistance is independent of the velocity. Additionally, it suggests a straight cylindrical pores specimen whose airflow resistivity value can be calculated theoretically. Any other specifications about the calibration specimen design are given. As the flow dynamics inside the perforated low porosity solid behave nonlinearly, it is important to integrate further guidelines in the design of the calibration specimens and measurements. This work presents CFD calculations results using OpenFoam, on the flow resistivity of a cylindrical solid containing a single perforation. The airflow velocity was determined based on the Reynolds number at the pore, which was varied between 0.33 to 2000. Different calibration specimens were tested by varying the length and the perforation diameter. An excellent agreement was observed between CFD and experimental data with an error of 5 %. The results show that the second-order extrapolation of specific resistance should be limited to Reynolds numbers equal to 500.

KATANA - water activation facility at JSI TRIGA, Part I: Final design and activity calculations

Water as a primary coolant will play an important role in the performance of fusion reactors, as it causes an ionising radiation field throughout the facility after its irradiation and activation and requires improved shielding for instruments and personnel. To support ITER, the KATANA irradiation facility, which utilises a closed-water activation loop, was built, licenced and commissioned in early 2024 at the TRIGA research reactor at the Jožef Stefan Institute in Slovenia.A comprehensive overview of the KATANA irradiation facility, which serves as a well-defined and stable high-energy γ and neutron source, is given, including the final design, experimental set-up, detector systems and overall timeline. The physical characteristics of KATANA were assessed by analyses of neutron transport simulations leading to activity calculations in connection with a conventional analytical approach, without using CFD calculations. The KATANA facility demonstrated the desired operational characteristics in terms of high and stable water flow rates, leading to high activity values of the observed isotopes 16N, 17N and 19O, which is essential for minimising experimental uncertainties.The preliminary calculations provided in-depth operational knowledge and important data for the KATANA facility, forming a basis for more advanced future experiments.

High-speed multi-stage gas-steam turbine with flow bleeding in a novel thermodynamic cycle for decarbonizing power generation

In the global pursuit of sustainable energy and reduced carbon footprints, advances in power generation techniques play a crucial role, not only in meeting the ever-increasing energy demands but also in ensuring that environmental standards are maintained and that the health of our planet is prioritized for future generations.In the ongoing quest for sustainable energy solutions, novel high-speed multi-stage gas-steam turbine models were designed to address the challenge of decarbonized power production. The thermodynamic parameters were adopted on the basis of the negative carbon dioxide gas power plant cycle relying on the following main devices, namely: wet combustion chamber, spray-ejector condenser, sewage sludge gasifier and gas-steam turbine. The peculiarities of the present system make the turbine the link of three important devices and its parameters affect the entire thermodynamic cycle. Therefore, it is reasonable to carry out dedicated novel in literature CFD calculations that also take into account the bleeding of the medium for the gasification process.Two distinct turbine models were introduced: a two-stage turbine achieving speeds of 95 000 rpm with an efficiency of more than 80%, and a five-stage turbine reaching 40 000 rpm with an efficiency of less than 70%. A design assumption of a bleed pressure of 100 kPa and a mass flow rate of 0.1 kg/s was adopted for both models. Computational simulations were utilized, and the turbine stages were selected with the aim of reducing energy losses. Through this work, a significant step towards a carbon-negative future using high-speed turbine technologies was demonstrated, laying the groundwork for further advancements in the field.

Fluid-Solid Coupling Analysis of the Propeller and Optimization of Boss Cap Fin Parameters

In order to ensure the accuracy of propeller modelling and hydrodynamic performance prediction, first of all, compared with atlas modelling and OpenProp modelling, it is pointed out that the characteristics of the blade model established by PropCad are more complete. Secondly, through the analysis and discussion of the computational domain distribution, grid independence verification and turbulence model, the CFD calculation model is established systematically. Thirdly, the hydrodynamic analysis of AU5-80 propeller is carried out under different advance ratios, and the simulation results are in good agreement with the open water test data. The accuracy of CFD calculation model is proved. Then, the fluid-solid coupling analysis of the propeller is performed, and it is verified that the stress field of the propeller meets the material strength requirement. It provides support for the further optimization design of propeller structure. Finally, through the design and analysis of the PBCF propeller, some optimization parameters of the PBCF are obtained. Because the PBCF can diffuse and weaken the hub vortex, the propeller thrust, and efficiency are improved.

New characterization models for macroscopic chemical-hydrodynamic behavior of catalytic cracking riser-reactor with interactive patterns of severe operating conditions using CFD calculations

BackgroundFCC is the core of refining technologies for production of high-valued chemicals including, light olefins, and fuels. Global capacity of catalytic cracking unites is projected to grow from 14.4 to 15.8 million barrels per day from 2022 to 2026. Moreover, global production of 57 % ethylene, 42 % propylene and 69 % butylene is based on deep/fluid catalytic cracking. Therefore, optimization of catalytic cracking process is our indispensable industrial approach. MethodsThis study is optimization of industrial catalytic cracking unit for maximizing the yield of light gases, gasoline and gasoil conversion using CFD calculations. Hydrodynamic behavior and performance of the riser-reactor was investigated at severe operating conditions, including feed temperature, catalyst temperature and catalyst to oil ratio (CTO) in the range of 788–903 K, 813–1013 K and 6–18, respectively. New characterization models were proposed for macroscopic chemical-dynamic behavior of the process. Models validated with ANOVA analysis, RSM methodology. Significant findingsResults showed that the maximum products yield and gasoil conversion occur between 4 and 8 s. It was obtained that the maximum yield of nearly 12 wt% light gases, 38–39 wt% gasoline and 54 % conversion is possible for this geometry of industrial unit via optimization of operating conditions. Coefficients of obtained models and interactive patterns of operating conditions showed that CTO is the most influential parameter on riser-reactor performance.

Influence of Damping Plate Size on Pitch Motion Response of Floating Offshore Wind Turbine

For floating offshore wind turbines, a significant pitch and roll motion response of the platform can affect the acceleration and power generation of the nacelle. The damping plate is considered a type of attachment that can be used to reduce rotational motion, but research on its anti-rotational effect is limited. The objective of this work is to analyze the impact of installing damping plates and varying their sizes on the pitch motion response of semi-submersible platforms, while also proposing optimization strategies for damping plate design. Firstly, a comparison between numerical simulations and experimental measurements validates the accuracy of the CFD calculations. Subsequently, different sizes of damping plates are proposed for the platforms, followed by simulations under various conditions. Finally, comprehensive data analysis is conducted. The findings suggest that installing damping plates enhances both the platform’s added moment of inertia and damping coefficients while simultaneously amplifying its motion response in regular waves. Furthermore, increasing the size of damping plates leads to an increase in both the added moment of inertia and motion response for the platform, whereas the damping coefficient exhibits an initial increasing trend followed by a subsequent decrease. Ultimately, it is found that increasing the distance between damping plates and the free surface significantly reduces wave-induced loads on the platform.

Design and Principles Analysis of Hydrofoil Appendages for Reducing Resistance of High-Speed Ships

To reduce the resistance of high-speed displacement ships with Froude numbers (Fr) between 0.4 and 0.5, this paper proposes the installation of hydrofoils at the bow and stern of the ship. Firstly, starting from the bow wave, this paper proposes the installation of a flat plate appendage at the free surface of the ship’s bow to suppress the height of the bow wave and thus reduce the hull resistance. Taking the DTMB 5415 ship model as the research object, CFD calculation results show that installing a flat plate appendage at the free surface of the ship’s bow can effectively suppress the height of the bow wave, and the total resistance reduction ratio can reach 6.49% when Fr = 0.45. Then, the flat plate appendage was improved to a hydrofoil appendage, further reducing the hull resistance. As a result, the total resistance reduction rate can reach 9.15% at Fr = 0.45. Following this, hydrofoil appendages were installed simultaneously at the bow and stern. The drag reduction effect and mechanism were studied, and the results show that the hydrofoils at the bow and stern have a good drag reduction effect. Suppressing the bow and stern waves and improving the flow field are the main reasons for the drag reduction. Finally, the drag reduction effect of the hydrofoil appendages was verified through experiments, demonstrating its excellent drag reduction effect when Fr = 0.4–0.5 and a maximum total resistance reduction ratio of 14.552%.

Inundation correlation research on the simulation of two-phase flow and heat transfer in a condenser

Abstract The performance of the condenser is important to keep the high efficiency of the instrument that converts thermal energy to power through steam. On the shell side of the condenser, there is a complex gas-liquid two-phase flow with coupled turbulence, phase change, and multi-component effects. Meanwhile, heat transfer and fluid flow are mutually coupled and interact with each other. This study carefully investigates a significant factor affecting the accuracy of two-phase model simulations in condensers. It’s found that the correction of the thermal resistance of the condensate plays a key role in good production. Starting from more accurate CFD calculation results of the two-phase flow, a method is derived that utilizes the liquid phase volume fraction for the correction. The simulated results obtained using this method show promising improvements compared to the complex approaches used by previous researchers.

Nacelle optimisation through multi-fidelity neural networks

PurposeAerodynamic shape optimisation is a complex problem usually governed by transonic non-linear aerodynamics, a high dimensional design space and high computational cost. Consequently, the use of a numerical simulation approach can become prohibitive for some applications. This paper aims to propose a computationally efficient multi-fidelity method for the optimisation of two-dimensional axisymmetric aero-engine nacelles.Design/methodology/approachThe nacelle optimisation approach combines a gradient-free algorithm with a multi-fidelity surrogate model. Machine learning based on artificial neural networks (ANN) is used as the modelling technique because of its ability to handle non-linear behaviour. The multi-fidelity method combines Reynolds-averaged Navier Stokes and Euler CFD calculations as high- and low-fidelity, respectively.FindingsRatios of low- and high-fidelity training samples to degrees of freedom of nLF/nDOFs = 50 and nHF/nDOFs = 12.5 provided a surrogate model with a root mean squared error less than 5% and a similar convergence to the optimal design space when compared with the equivalent CFD-in-the-loop optimisation. Similar nacelle geometries and aerodynamic flow topologies were obtained for down-selected designs with a reduction of 92% in the computational cost. This highlights the potential benefits of this multi-fidelity approach for aerodynamic optimisation within a preliminary design stage.Originality/valueThe application of a multi-fidelity technique based on ANN to the aerodynamic shape optimisation problem of isolated nacelles is the key novelty of this work. The multi-fidelity aspect of the method advances current practices based on single-fidelity surrogate models and offers further reductions in computational cost to meet industrial design timescales. Additionally, guidelines in terms of low- and high-fidelity sample sizes relative to the number of design variables have been established.

Multifidelity & multi-objective Bayesian optimization of hydrogen-air injectors for aircraft propulsion

The use of hydrogen as a fuel is a promising way to reduce the emissions of civil aviation but it requires the development of wholly new injectors for the combustion chamber. Thanks to the increase in available computing power, the application of optimization techniques combined with CFD computations is now possible to develop these injectors. Among the optimization approaches, Bayesian optimization is particularly relevant when the objective functions and constraints of the optimization problem are expensive to evaluate which is the case in CFD-based optimization. Besides, the use of a multifidelity strategy allows to reduce the simulation cost of the Bayesian method. Therefore, this paper investigates the application of a multifidelity and multi-objective Bayesian approach to improve the performances of a laboratory swirl injector using hydrogen and operating in conditions close to industrial targets. This optimization study combines LES simulations as high-fidelity model with 2D RANS simulations as low-fidelity.

Comparison Of Full-Scale PIV Measurements With CFD Simulations Of A Ship Propeller Inflow

Flow around the ship's hull and specifically the inflow conditions of the propeller(s) critically influence the propeller efficiency and cavitation behaviour. In a typical single-propeller vessel, the hull of the ship creates a velocity deficit in the top part of the propeller disk. This creates suitable conditions for cavitation, which is the main source of noise and vibration both inside the vessel as well as in the marine environment. Recently, two measurement campaigns were performed using a novel full-scale stereo-PIV device built to measure flows around vessels sailing at sea. During the first campaign, performed in one of MARIN's basins, the device was commissioned. The second campaign was performed during a sea trial; it resulted in propeller inflow data that can be used for validating CFD codes. The uncertainty of the PIV measurements was assessed using both campaigns. In the basin, uncertainty bias could be determined by comparing the PIV results with the carriage speed. At sea, the random part of uncertainty was determined by quantifying the standard deviation of the mean velocity for all three velocity components in the wake peak area of the propeller inflow. Overall, the uncertainty was found to be acceptably small, given the scale of the measurement and the necessity to work with naturally occurring seeding particles in the sea. CFD calculations of the same full-scale flow were performed using an in-house flow solver. The CFD results predicted the propeller RPM and the delivered power measured during the full-scale trial well, which gives confidence in the ability of CFD to predict ship trial performance. The comparison of the flow fields was good, with the PIV results demonstrating that full-scale PIV can be done reliably, and that the CFD is able to capture the major features of the flow in the considered area. For a large part of the flow field, the CFD was within the measurement uncertainty band. The wake peak was slightly underpredicted, which may be related to roughness effects on the boundary layer thickness.

CFD Calculation of Natural Convection Heat Transmission in a Three-Dimensional Pool with Hemispherical Lower Head

The integrity of a pressure vessel (PRV) is affected by the decay heat of the molten pool in the lower head, so it is very important to study the natural convection heat transmission in the lower head. Scholars from all over the world have carried out a lot of experimental studies and calculations to determine the convection mechanism and heat transmission characteristics of the molten pool. Most of them were based on the empirical formula of convective heat transmission on the wall of a hemispherical molten pool based on two-dimensional slice experiments and simulation calculations. In this study, FLUENT 2021R1 software was used to simulate the three-dimensional convective heat transmission process of the hemispherical molten pool, and the temperature, velocity and wall heat transmission coefficients of the flow field were analyzed. The results were in good agreement with experimental data from UCLA (University of California, Los Angeles). Through research on the heat transmission of the lower head, the results showed that in the region where the wall angle was θ between approximately 72 and 90 degrees, heat transmission coefficients had larger fluctuations, and a more reasonable empirical relation was proposed. Comparing between the simulation results of CFD and the two-dimensional empirical formula, it was found that the latter one was smaller under the same θ angle condition. Finally, the convection phenomena of different external temperatures were simulated, and the main factors affecting the flow field by temperature were analyzed.