Computational Fluid Dynamics Evaluation Research Articles

Computational Fluid Dynamics Evaluation of Nitrogen and Hydrogen for Enhanced Air Conditioning Efficiency

Computational Fluid Dynamics Evaluation of Nitrogen and Hydrogen for Enhanced Air Conditioning Efficiency

Pollutant cross-transmission in courtyard buildings: Wind tunnel experiments and computational fluid dynamics (CFD) evaluation

Courtyards, a historical architectural feature surrounded by buildings, are common in urban housing and residential complexes. These spaces, often open-air and with rooms facing them, are crucial for daylight and natural ventilation. While courtyards are essential for introducing fresh airflow into adjacent indoor areas, the effectiveness of natural ventilation may be compromised due to potentially poor air circulation from limited openings. This raises a significant concern: could the design of courtyards inadvertently facilitate pollutant cross-transmission? Despite a wealth of research focused on airflow within courtyards, the indoor spaces in proximity to these courtyards have often been neglected in previous works, particularly concerning the exchange of pollutants between the indoor and courtyard environment. This research investigates the dynamics of indoor-outdoor pollutant cross-transmission in courtyard buildings, assessing factors like external wind flow patterns and internal pollutant sources. Wind tunnel experiments were conducted to measure internal pressure and CO2 concentration and to validate a computational model of the courtyard with 12 rooms. The validated Computational Fluid Dynamics (CFD) models were used to simulate the dispersion of pollutants from internal rooms under different wind conditions. The results showed that the k-epsilon Realizable model accurately simulated internal surface pressure distribution and pollutant dispersion in the courtyard building. It was observed that when pollutants were released from the downwind east-facing ground floor room, CO2 concentrations in adjacent side rooms on the same floor were significantly higher, increasing from the baseline of 400 ppm and reaching up to 3211 ppm in the north-facing room at a wind speed of 4.51 m/s and wind direction of 0°. Conversely, when pollutants originated from north- and south-facing side rooms, pollutants were minimally dispersed to adjacent rooms. Furthermore, at a wind direction of 45°, pollutants from wind-exposed rooms predominantly dispersed to downwind rooms, with peak concentrations exceeding 2400 ppm in downwind rooms. These findings demonstrate that pollutant dispersion is highly dependent on wind direction and the location of the pollutant source. The study concludes that while courtyards enhance indoor environmental quality through natural ventilation, their design must be carefully considered to prevent unintended pollutant cross-transmission, particularly under varying wind conditions and pollutant source locations.

Multi-objective hull form optimization utilizing sequential sampling optimization method

With advancements in computer technology, Computational fluid dynamics (CFD) theory provides a numerical tool for evaluating the comprehensive hydrodynamic performance of ships. On this basis, the Simulation-based design (SBD) technology based on the static sampling method (SSM) which is termed as SBD-SSM in this paper is recognized as a hull form optimization method with significant advantages. However, in the SBD-SSM method, the excessive pursuit of the global accuracy of the surrogate model leads to the need for more CFD evaluations. Consequently, this demands the substantiality of computing resources and diminishes optimization efficiency. We apply a novel hull form optimization method based on the Sequential Sampling-based Optimization (SBO) method to address this challenge. Furthermore, to strike an appropriate balance between prediction value and uncertainty while finding optimal solutions, we employ the adaptive sampling method known as Pseudo Expected Improvement Matrix (PEIM). By integrating SBO with PEIM, we introduce the SBO-PEIM optimization method, initially applied through mathematical optimization functions to verify its feasibility in optimization. Subsequently, we apply this method to optimize the total resistance and wake performance of the KCS ship. Our findings demonstrate that the SBO-PEIM method achieves higher prediction accuracy in near-optimal solutions than the SBD-SSM method, enhancing optimization efficiency by at least 17.5%. It validates the efficacy of the SBO-PEIM approach in addressing real-world engineering optimization challenges.

Computational Fluid Dynamics Evaluations on New Designs of the Delta-Shaped Blade Darrieus Hydrokinetic Turbine

Computational Fluid Dynamics Evaluations on New Designs of the Delta-Shaped Blade Darrieus Hydrokinetic Turbine

Experimental and Computational Fluid Dynamics Analysis of Industrial Water Desalination with High Salinity by Adsorption Chlorine on Resin in a Packed Column

AbstractTo investigate chlorine adsorption from water onto resins, some batch adsorption tests were considered. The mechanisms and characteristic parameters of the adsorption process were analyzed using isotherm models which revealed the following order (based on the coefficient of determination): Flory–Huggins (0.99) > Fowler‐Guggenheim (0.98) >, and Langmuir (0.38).The experimental data were examined using two kinetic models, including first‐ and second‐order ones with R2 value of 0.88, 0.1 respectively. According to the adsorption isotherm study, the Flory–Huggins isotherm model better fit adsorption on the surface of resin, as compared to other models. Assessing the thermodynamic parameters found out that the adsorption of Cl onto resins became an exothermic and spontaneous process. The results were then obtained. Similarly, the results of the experiment were provided via the computational fluid dynamics evaluation. Moreover, the results obtained by computational fluid dynamics were compared with the experimental data, and their accuracy was proved. Subsequently, the effects of changing the design and operating parameters, including flow rate (3, 6, 10 L min−1) and bed height (10, 20, 40 cm) on the performance of this tower were studied. The results showed that by reducing the adsorbent, the adsorbed Cl increased and a longer bed was required for adsorption, which was not cost‐effective. The amount of adsorption decreased as the flow rate increased, indicating that there was little contact between the Cl and the adsorbent.

Aerodynamic characterization of a H-Darrieus wind turbine with a Drag-Disturbed Flow device installation

This study examines the impact of the Drag-Disturbed Flow device on the startup and operation of HDWT (H-Darrieus wind turbine). The device plays a crucial role in enhancing the startup performance of the HDWT and improving the overall wind energy utilization. This work presents a study where two-dimensional computational fluid dynamics (CFD) evaluations are performed on various D-DF (Drag-Disturbed) devices. The HDWT utilizes the NACA0018 airfoil type, while the D-DF device employs triangular, oval, and NACA0018 airfoil structures. The text explains the installation process and operational principles of the D-DF device. It also verifies the device's meshing and accuracy. Furthermore, this study conducts 2-D simulations to analyze the impact of various D-DF devices on the moment and wind energy consumption coefficients of the HDWT. Additionally, the process by which D-DF devices enhance the performance of the HDWT is explained by an analysis of the vortex cloud diagram. The results indicate that the HDWTs equipped with D-DF devices experience significant performance improvements during the wind turbine startup phase. Specifically, the Drag blade effectively enhances the moment coefficient of the HDWTs at low tip speed ratios by an average of approximately 41.74 %. Additionally, once the HDWTs are started and operating at high tip speed ratios, all D-DF devices, except for the DF-Tri, can be utilized within the λ = 1.2–2 range to enhance the torque coefficient of the HDWT by an average of about 7.53 %. This study aims to improve the operating performance of the current HDWT, lower the wind turbine cut-in wind speed, and enhance the wind energy consumption of the turbine.

Computational Fluid Dynamics Evaluation of an Oil-flooded Screw Compressor

The cost of energy is directly influenced by geopolitical, economic, and environmental factors. There is an international trend towards renewable resources, although the implementation pace and legislation in force have issues. Complete abolishment of fossil fuels is practically impossible. Evolution is only possible with the use of these fuels but with modern, efficient equipment to reduce the pollution resulting from the process of extracting, processing, and using fossil fuels. In this paper, a screw compressor with oil injection, used in oil extraction stations, is analyzed numerically. This analysis is useful in the process of modernizing and improving the efficiency of this type of compressor, which is capable of operating in extreme working regimes, highly contaminated with impurities. The numerical analysis presented certain challenges related to biphasic flow in extremely small spaces at high compression ratios. The results include the absolute pressure variation and the flow rate variation. Regarding future research, test series will be carried out to validate the numerical results on the test bench with a 1:1 scale prototype.

A Practical Approach for Biochemical Modeling in the CFD Evaluation of Novel Anaerobic Digester Concepts for Biogas Production

The detailed physics-based description of anaerobic digesters is characterized by their multiscale and multiphysics nature, with Computational Fluid Dynamics (CFD) simulations being the most comprehensive approach. In practice, difficulties in obtaining a detailed characterization of the involved biochemical reactions hinder its application in the design of novel reactor concepts, where all physics interplays in the reactor must be considered. To solve this limitation, a practical approach is introduced where a calibration step using actual process data was applied for the simplified biochemical reactions involved, allowing us to efficiently manage uncertainties arising when characterizing biochemical reactions with lab scale facilities. A complete CFD modeling approach is proposed for the anaerobic digestion of wastewater, including heat transfer and multiphasic flow. The proposed multiphase model was verified using reference data and, jointly with the biochemical modeling approach, applied to a lab-scale non-conventional anaerobic digester for winery wastewater treatment. The results showed qualitative improvement in predicting methane production when the diameter of the particles was reduced, since larger particles tend to move downwards. The biochemistry of the process could be simplified introducing a preexponential factor of 380 (kmol/m3)(1 – n)/s for each considered chemical reaction. In general, the proposed approach can be used to overcome limitations when using CFD to scale-up optimization of non-conventional reactors involving biochemical reactions.

Feasibility study of a compact and multi-gas supersonic plasma jet for nuclear astrophysics and space research

Supersonic plasma jet targets can improve the present knowledge on low energy nuclear reaction cross sections allowing to study electron screening effects. They could also be employed both in the preliminary tests of space vehicles thermal protection systems and in the validation of computational fluid dynamics (CFD) evaluations of hot exotic gases. This common interest between nuclear astrophysics and space research led to a joint effort between the European Recoil Separator for Nuclear Astrophysics collaboration of the Italian National Institute for Nuclear Physics and the Italian Aerospace Research Center (CIRA) to develop an innovative, compact and multi-gas supersonic plasma jet setup. In this work we present the characterization of a test supersonic cold jet target, performed with ion beam analysis techniques, as benchmark for the validation of the CFD code NExT developed by CIRA. Being NExT outputs in agreement within 5% with experimental data, we employed it together with the software CEA of the United States National Aeronautics and Space Administration to design setups to be employed in both nuclear astrophysics and space re-entry research fields. We finally provide an overview of the plasma technologies to be employed in the construction of this supersonic plasma jet, aiming for a good balance of costs and performances. A 200 kW plasma arch torch, being also commercially available, was found to be a good option for both nuclear astrophysics and space re-entry experiments in small laboratories: for the first, a 20% of ionization may be reached with still an adequate target thickness (∼1017nuclei/cm2), while for the latter the most energetic scenario could be reproduced.

CFD Evaluation of Thermal Conditioning in a House of Social Interest with a Solar Chimney Arrangement in Guanajuato, Mexico

The aim of using electromechanical air conditioning in buildings is to maintain thermal comfort for its occupants; however, this type of air conditioning represents 40% of the total energy consumption of a building, generating economic and environmental impacts, because fossil fuels are the main source of energy. To reduce the use of electromechanical conditioning, it is possible to take advantage of the climatic conditions of the region to improve its performance. Due to the small number of works that quantitatively support measures aimed at improving the thermal behavior of houses in an integral way and the growth of mass construction in Mexico, in the present work, a solar chimney is incorporated in a typical type of social interest housing in Guanajuato. The incorporation of the solar chimney was simulated by using computational fluid dynamics (CFD) using ANSYS and evaluated by ASHRAE Standard 55-2017. The selected arrangement induces air flow inside without the need for external flow and obtains speeds of 0.2 m/s; thus, it could be considered for rooms within comfort zones up to an operating temperature of 29 °C according to the ASHRAE Standard 55-2017, PMV method.

Neural network-based multi-point, multi-objective optimisation for transonic applications

In the context of aircraft applications, the overall design process can be challenging due to the different aerodynamic requirements at several operating conditions and the total associated computational overhead. For this reason, the use of low order models for the optimisation of complex non-linear problems is sometimes used. This paper addresses the challenge of transonic aerodynamic design optimisation through the integration of a set of neural networks for the prediction of integral values, the classification of flow features and the estimation of flow field characteristics. The design method improves the computational efficiency relative to an expensive design process driven by Computational Fluid Dynamics (CFD) evaluations. The approach is used for the multi-point, multi-objective optimisation of a compact aero-engine nacelle in which the design outcomes are validated using a CFD in-the-loop optimisation strategy. It is demonstrated that the method based on the neural network capability identifies similar nacelle designs at a 75% reduction in the overall computational cost, a drag uncertainty prediction within 2.8%, and a predictive accuracy for the classification metric of 98%. For downselected configurations, the main flow characteristics in terms of peak Mach number, pre-shock Mach number and shock location are well predicted by the neural network models compared with the CFD-based evaluations.

Evaluation of CFD and machine learning methods on predicting greenhouse microclimate parameters with the assessment of seasonality impact on machine learning performance

For cleaner and sustainable greenhouse crops production, it is essential to successfully manage the needs and resources. Thus the prediction of the greenhouse microclimate, especially the temperature and relative humidity is of great interest. The research done in this area is, however, still limited, and a number of machine learning techniques have not yet been sufficiently exploited. The objective of this paper is to evaluate two greenhouse modeling techniques (machine learning (Artificial Neural Networks (ANN), Support Vector Machine (SVM), Bagging trees (BG) and Boosting trees (BT)) and Computational Fluid Dynamics (CFD) methods and assess the impact of the seasonal changes on machine learning performances. The study was carried out in a commercial greenhouse located in Agadir, Morocco, and the experimental data were collected during October and March. Results show that all predictive models are capable of predicting the inside air temperature (Tin) and relative humidity (Rhin) of the greenhouse with a quite good precision (R>0.98, nRMSE<7%). However, the time required by machine learning models was much more less than the one required by CFD model. For this reason, machine learning models were selected for further analysis and assessment of seasonality impact on their performances. The analysis and assessment of seasonality impact on Machine learning models prove their efficiency in predicting Tin and Rhin with a good agreement. A “combined data” model, built from experimental data of the two months, is tested and proved its efficiency in predicting Tin and Rhin of March and October separately and at the same time (R>0.98, nRMSE <9%).

Numerical investigation and performance enhancement of an ammonia-water radial-outflow turbine through the flow-oriented optimization

The radial-outflow turbine has advantages due to its liquid-rich gas adaptability when applied in a Kalina ammonia-water cycle system for the utilization of geothermal energy and waste heat. However, the existing radial-outflow turbine shows relatively lower efficiency than the conventional radial-inflow turbines due to its distinct stage configuration and the lack of efficient design method. In the present study, numerical investigation has been conducted on a radial-outflow turbine adopted in Kalina cycle system, by which the turbine flow losses are analyzed. To enhance the turbine performance, a design optimization method has been developed, which includes the following features: the flexible geometry variations are realized to explore the optimization potentials, where the stator and rotor blades are optimized simultaneously; the flow-oriented objective function is established to drive the optimizer to suppress the flow losses in blade passages while adjust the flow matching. To solve the complex geometry optimization problem, adaptive optimization algorithm is imported to accelerate global searching and reduce the costly Computational Fluid Dynamics evaluations. The developed optimization method has been applied in the geometry optimization of a radial-outflow ammonia-water turbine. Benefitting from the fine-tuned blade geometries, the flow matching between stator and rotor is adjusted and the flow losses are mitigated. Thus, the turbine efficiency and shaft power are improved by 6.46% and 5.85%, respectively.

Multi-disciplinary optimization of a space re-entry vehicle using skeleton-based integral soft objects

In the present paper, a parametric procedure for the shape modelling and optimization of a next generation winged re-entry vehicle using Skeleton-Based Integral Soft Objects is presented. Detailed aerodynamic bodies are efficiently generated just “inflating” a parametric flat domain representing the aeroshape planform composed by discretized panels. Specifically, a potential field generated by a set of mathematical primitives and related field functions is used to alter nodal coordinates of the flat planform domain. In such mode, several geometrical features as canopy, cabin outline, dihedral angles, winglets, and vertical tails can be easily modelled, added, or suppressed. Specialized Skeleton-Based Integral Soft Objects operators are used to produce both smooth and sharp transitions between different sub-component surfaces as required. Consequently, huge geometrical variations of the aerodynamic shape can be then efficiently generated using a very limited number of high-sensitivity parameters. The suggested modelling procedure has been tested performing several multi-disciplinary shape optimizations driven by rapid engineering evaluators, for a minimum mass/maximum cross range design of a concept vehicle that re-enters from Low Earth Orbit, up to a controlled horizontal landing on runway. Additionally, Computational Fluid Dynamics evaluations have been performed on optimum design candidates to validate the real performance of the proposed aeroshape configurations. Results comparison has highlighted slight differences within the range 5-10%, thus confirming the reliability of the design of the aircraft aeroshape.

CFD evaluation of mean and turbulent wind characteristics around a high-rise building affected by its surroundings

This study comprehensively investigated the accuracy of computational fluid dynamics (CFD) simulations for predicting the mean and turbulent wind characteristics around a high-rise building surrounded by low-rise street canyons. The flow field was characterized based on the complicated interaction between a high-rise building and its surrounding buildings, which has rarely been examined in previous CFD studies. We obtained the CFD results using steady Reynolds averaged Navier-Stokes equation (RANS) models and large eddy simulations (LES), which were compared with the measurement results obtained via wind tunnel experiments. Furthermore, we quantitatively investigated the impact of the presence of a high-rise building on the prediction accuracy of pedestrian wind environments, including the gust wind velocity. The results showed that the performance of both LES and RANS decreased in the presence of a high-rise building, indicating that predicting the flow around a high-rise building is more challenging than predicting the flow of a simple street canyon. Additionally, the prediction accuracies of RANS and LES for the mean wind velocity at the pedestrian level were similar in regions with high wind velocity. However, the prediction accuracy of LES in the medium- and low-wind-velocity regions was significantly better than that of RANS, which is closely related to the superior prediction accuracy of turbulent kinetic energy in LES. Although LES can predict the gust wind velocity directly with higher accuracy than that of RANS by using a gust factor, RANS can be used to predict the gust wind velocity with a certain accuracy using a peak factor.

CARD25: Computational Fluid Dynamics Evaluation of Surface Modification to Improve Endothelial Retention on Blood-wetted Artificial Organs

CARD25: Computational Fluid Dynamics Evaluation of Surface Modification to Improve Endothelial Retention on Blood-wetted Artificial Organs

Deployment of wind turbine in between cement silos for small power generation

This study provides an overview of Building-Integrated Wind Turbines, focusing on cement silos as wind concentrators, along with determining the amount of power that could be connected without regard to wind direction. The motivation of this research is the intermittency issue of wind stream in an open environment and non-exploration of wind turbines between cement silos. Building-Augmented Wind Turbines provide 717 W of aerodynamic power at 16 m/s, whereas Standalone Wind Turbines produce 562 W. This is due to the wind speed acceleration between buildings, which causes a concentration effect. Meanwhile, using the simulation software ANSYS, the turbine geometry is developed utilising a Computational Fluid Dynamics evaluation.

Irrigant flow characteristics in the root canal with internal root resorption: a computational fluid dynamics evaluation.

Irrigation dynamics of syringe irrigation with different needle designs (side-vented, double side-vented, notched) and ultrasonic irrigation in the root canal with internal root resorption were evaluated using a computational fluid dynamics model. A micro-CT scanned mandibular premolar was used for modeling internal root resorption. The needles and the ultrasonic tip were positioned at 2, 4, and 5mm from the working length. The insertion depth and the irrigation model were found influential on the shear stress and the irrigant extension. The extension of the irrigant increased toward 2-5mm from the working length. Ultrasonic irrigation revealed the highest shear stress values regardless of the insertion depth. The shear stress distribution on the resorption cavity walls gradually increased when the needles were positioned coronally. The residence time of the irrigant in the canal was affected by the needle position relative to the internal root resorption cavity and the needle type.

Computational fluid dynamics evaluation of conditions before impact of particles in plasma spraying process

Plasma Spraying is one of the most sophisticated and versatile thermal spray techniques. In Plasma Spraying, powdered material is injected into a plasma jet, which is generated from a plasma torch. Upon contact with the plasma jet, the particles are melted and propelled forward onto a substrate to form an adherent coating which modifies the properties of the substrate. The modifications to the substrate can, for example, increase its resistance to other extreme operating conditions such as wear, abrasion, and corrosion. However, the phenomena governing the formation of the plasma jet inside the plasma torch and its subsequent interaction with injected particles are not fully understood. This paper provides a detailed report on steps taken for the development of a comprehensive numerical model to simulate plasma jet development inside a direct current plasma torch. The heat flow and mass exchange of ionized gas with injected solid particles were followed in three dimensions by using a Computational Fluid Dynamics (CFD) method. A cylindrical energy source term which was defined as an increasing linear function dependent on time as a variable, was included to reproduce the effects of an electric arc on the gas flow. For optimization purposes, it was sought to investigate the effects of the particles’ injection angle and inlet velocity, as well as the effects of particle size distribution on the particle temperature and velocity histories.

CFD Evaluation of Pressure Change Along Coolant Passages in Sodium-Cooled Fast Reactor with Nek5000

To support the design efforts of advanced sodium-cooled fast reactors (SFRs), a series of computational fluid dynamics (CFD) simulations are performed to investigate the pressure change along various flow passages in the proposed SFR system. The simulations are carried out with the state-of-the-art spectral element flow solver, Nek5000. Two specific case studies are presented in this paper: the flow exiting the axial neutron reflector channels and the flow entering the fuel pin bundle. Due to the high Reynolds numbers expected, a Reynolds-averaged Navier-Stokes (RANS) approach is necessary to model the turbulence. A newly developed regularized RANS model is adopted in the related CFD calculations. The first case study explores the effect of Reynolds number on the pressure change when flow exits the reflector channels. The pressure change in this case has two major contributors: the change due to wall friction and the Bernoulli effect. It is noted that the nondimensional pressure loss follows a log-linear trend up to Re = 105, and then the trend is flattened. In the second case study, the advanced NekNek coupling capability is tested where an integral domain can be divided into multiple subdomains with coupling interfaces, which would greatly ease the meshing process of complex engineering geometries and potentially save computational resources. The preliminary results obtained so far confirm the consistency between the NekNek results and those produced by regular Nek5000 simulation. The presented work demonstrates the readiness and flexibility of the related CFD techniques, which is part of the broader effort to leverage cutting-edge CFD to inform the advanced nuclear reactor designs.