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This paper aims to present the assumptions and the issues that arise when developing an integrated modelling methodology between a computational fluid dynamics (CFD) software applied to compartment fires and a finite element (FE) software applied to structural systems.

Particular emphasis is given to the weak coupling approach developed between the CFD code fire dynamics simulator (FDS) and the FE software SAFIR. Then, to show the potential benefits of such a methodology, a multi-storey steel-concrete composite open car park was considered.

Results show that the FDS–SAFIR coupling allows overcoming shortcomings of simplified models by performing the thermal analysis in the structural elements based on a more advanced modelling of the fire development, whereas it appears that the Hasemi model is more conservative in terms of thermal action.

A typical design approach using the Hasemi model is compared with a more advanced analysis that relies on the proposed FDS–SAFIR coupling.

Computational fluid dynamics (CFD)/computational structural dynamics (CSD) coupling analysis is an important method in the research of helicopter aeroelasticity due to its high precision. However, this method still suffers from some problems, such as wake dissipation and large computational cost. In this study, a new coupling method and a new air load correction method that combine the free wake model with the CFD/CSD method are proposed to maintain computational efficiency whilst solving the wake dissipation problem of the prior coupling methods.

A new coupling method and a new air load correction method that combine the free wake model with the CFD/CSD method are proposed. With the introduction of the free wake model, the CFD solver can adopt two-order accuracy schemes and fewer aerodynamic grids, thus maintaining computational efficiency whilst solving the wake dissipation problem of the prior coupling methods.

Compared with the predictions of the prior methods and flight test data, those of the proposed method are more accurate and closer to the test data. The difference between the two methods in high-speed forward flight is minimal.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed method further.

In this paper, a CFD/CSD/free wake coupling method is proposed to improve the computational accuracy of the traditional CFD/CSD coupled method and ensure the computational efficiency.

The purpose of this paper is to show the superior turbulence method in CFD analysis of radial turbo machines and to introduce the best way to choose turbulence parameters whenever FLUENT user applies this software as a complementary design tool for high‐speed turbo machinery components.

One of the most important issues in CFD is analysis of flow field in turbo machines. Flow in high‐speed radial turbo machinery is a 3D, turbulent and unsteady behavior so needs suitable method for converging. It is clear that the turbulence model has an extraordinary effect on investigation of 3D flows in high‐speed turbo machinery. A centrifugal compressor of micro and radial turbines have been designed and simulated 3D using the commercial CFD‐code FLUENT 6. Three turbulence models k‐ε/standard, renormalization‐group (RNG) and RSM were considered and results of three models were compared with experimental and 1D design results.

The study showed numerical results are compatible with experimental performance data. It determined that RNG method in CFD analysis of radial turbo machines has provided better results than the standard k‐ε method. In addition, when using the RNG method, the phenomena of flow field were more visible than other methods.

This paper offers use of the RNG method as a superior turbulence method in CFD analysis of radial turbo machines.

Wind 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.

A 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.

The 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.

The 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.

The purpose of this paper is to review the applications of the chemical reactor network (CRN) approach for modeling the combustion in gas turbine combustors and classify the CRN construction methods that have been frequently used by researchers.

This paper initiates with introducing the CRN approach as a practical tool for precisely predicting the species concentrations in the combustion process with lower computational costs. The structure of the CRN and its elements as the ideal reactors are reviewed in recent studies. Flow field modeling has been identified as the most important input for constructing the CRNs; thus, the flow field modeling methods have been extensively reviewed in previous studies. Network approach, component modeling approach and computational fluid dynamics (CFD), as the main flow field modeling methods, are investigated with a focus on the CRN applications. Then, the CRN construction approaches are reviewed and categorized based on extracting the flow field required data. Finally, the most used kinetics and CRN solvers are reviewed and reported in this paper.

It is concluded that the CRN approach can be a useful tool in the entire process of combustion chamber design. One-dimensional and quasi-dimensional methods of flow field modeling are used in the construction of the simple CRNs without detailed geometry data. This approach requires fewer requirements and is used in the initial combustor designing process. In recent years, using the CFD approach in the construction of CRNs has been increased. The flow field results of the CFD codes processed to create the homogeneous regions based on construction criteria. Over the past years, several practical algorithms have been proposed to automatically extract reactor networks from CFD results. These algorithms have been developed to identify homogeneous regions with a high resolution based on the splitting criteria.

This paper reviews the various flow modeling methods used in the construction of the CRNs, along with an overview of the studies carried out in this field. Also, the usual approaches for creating a CRN and the most significant achievements in this field are addressed in detail.

The development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them.

A three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods.

Although the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively.

The model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs.

The Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

This paper aims to present a fast and effective approach to tackle complex fluid structure interaction problems that are relevant for the aeronautical design.

High fidelity computer-aided engineering models (computational fluid dynamics [CFD] and computational structural mechanics) are coupled by embedding modal shapes into the CFD solver using RBF mesh morphing.

The theoretical framework is first explained and its use is then demonstrated with a review of applications including both steady and unsteady cases. Different flow and structural solvers are considered to showcase the portability of the concept.

The method is flexible and can be used for the simulation of complex scenarios, including components vibrations induced by external devices, as in the case of flapping wings.

The computation mesh of the CFD model becomes parametric with respect to the modal shape and, so, capable to self-adapt to the loads exerted by the surrounding fluid both for steady and transient numerical studies.

Biocontaminants represent higher risks to occupants' health in shared spaces. Natural ventilation is an effective strategy against indoor air biocontamination. However, the relationship between natural ventilation and indoor air contamination requires an in-depth investigation of the behavior of airborne infectious diseases, particularly concerning the contaminant's viral and aerodynamic characteristics. This research investigates the effectiveness of natural ventilation in preventing infection risks for coronavirus disease (COVID-19) through indoor air contamination of a free-running, naturally-ventilated room (where no space conditioning is used) that contains a person having COVID-19 through building-related parameters.

This research adopts a case study strategy involving a simulation-based approach. A simulation pipeline is implemented through a number of design scenarios for an open office. The simulation pipeline performs integrated contamination analysis, coupling a parametric 3D design environment, computational fluid dynamics (CFD) and energy simulations. The results of the implemented pipeline for COVID-19 are evaluated for building and environment-related parameters. Study metrics are identified as indoor air contamination levels, discharge period and the time of infection.

According to the simulation results, higher indoor air temperatures help to reduce the infection risk. Free-running spring and fall seasons can pose higher infection risk as compared to summer. Higher opening-to-wall ratios have higher potential to reduce infection risk. Adjacent window configuration has an advantage over opposite window configuration. As a design strategy, increasing opening-to-wall ratio has a higher impact on reducing the infection risk as compared to changing the opening configuration from opposite to adjacent. However, each building setup is a unique case that requires a systematic investigation to reliably understand the complex airflow and contaminant dispersion behavior. Metrics, strategies and actions to minimize indoor contamination risks should be addressed in future building standards. The simulation pipeline developed in this study has the potential to support decision-making during the adaptation of existing buildings to pandemic conditions and the design of new buildings.

The addressed need of investigation is especially crucial for the COVID-19 that is contagious and hazardous in shared indoors due to its aerodynamic behavior, faster transmission rates and high viral replicability. This research contributes to the current literature by presenting the simulation-based results for COVID-19 as investigated through building-related and environment-related parameters against contaminant concentration levels, the discharge period and the time of infection. Accordingly, this research presents results to provide a basis for a broader understanding of the correlation between the built environment and the aerodynamic behavior of COVID-19.

The purpose of this work is to present a procedure for determining the wind drift factor through two-dimensional computational fluid dynamics (CFD) simulations of the wind acting on a wavy sea surface, such that the subjectivity of its estimation is reduced.

The wind drift factor was determined by two-dimensional CFD analyses with open-channel condition. The characteristic wave was determined by the Sverdrup–Munk–Bretschneider (SMB) method. The uncertainty analysis is based on convergence studies using a single parameter refinement (grid and time step).

This procedure allows the estimation of the wind drift factor in a fetch-limited domain. The domain's value in the analyzed region is 0.0519 ± 4.92% which is consistent with the upper values of the wind drift factors reported in the literature.

The use of a three-dimensional domain was impractical with the available computational resources because of the fine mesh required for wave modeling. The uncertainty analysis consisted only of a verification procedure. Validation against real data was not possible because of the lack of measured data in the analyzed region.

The wind drift factor is usually estimated based on either experience or random sampling. The original contribution of this work is the presentation of a CFD procedure for estimating the wind drift factor, in which the domain inlet is subjected to a wave boundary condition and to a wind velocity.

The purpose of this paper is to examine the aerodynamic effects of rear spoiler geometry on a sports car. Today, due to economical, safety and even environmental concerns, vehicle aerodynamics play a much more significant role in design considerations and rear spoilers play a major role in this area.

A 2-D vehicle geometry of a race car is created and solved using the computational fluid dynamics (CFD) solver FLUENT version 6.3. The aerodynamic effects are analyzed under various vehicle speeds with and without a rear spoiler. The main results are compared to a wind tunnel experiment conducted with 1/18 replica of a Nascar.

By the CFD analysis, the drag coefficient without the spoiler is calculated to be 0.31. When the spoiler is added to the geometry, the drag coefficient increases to 0.36. The computational results with the spoiler are compared with the experimental data, and a good agreement is obtained within a 5.8 percent error band. The uncertainty associated with the experimental results of the drag coefficient is calculated to be 6.1 percent for the wind tunnel testing. The sources of discrepancies between the experimental and numerical results are identified and potential improvements on the model and experiments are provided in the paper. Furthermore, in the CFD model, it is found that the addition of the spoiler caused a decrease in the lift coefficient from 0.26 to 0.05.

This paper examines the effects of rear spoiler geometry on vehicle aerodynamic drag by comparing the CFD analysis with wind tunnel experimentation and conducting an uncertainty analysis to assess the reliability of the obtained results.