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This aim of this work is to investigate different modelling approaches for air-cooled data centres. The study employs three computational methods, which are based on finite element, finite volume and lattice Boltzmann methods and which are respectively implemented via commercial Multiphysics software, open-source computational fluid dynamics code and graphical processing unit-based code developed by the authors. The results focus on comparison of the three methods, all of which include models for turbulence, when applied to two rows of datacom racks with cool air supplied via an underfloor plenum.

This paper studies thermal airflows in a data centre by applying different numerical simulation techniques that are able to analyse the thermal airflow distribution for a simplified layout of datacom racks in the presence of a computer room air conditioner.

Good quantitative agreement between the three methods is seen in terms of the inlet temperatures to the datacom equipment. The computational methods are contrasted in terms of application to thermal management of data centres.

The work demonstrates how the different simulation techniques applied to thermal management of airflow in a data centre can provide valuable design and operational understanding. Basing the analysis on three very different computational approaches is new and would offer an informed understanding of their potential for a class of problems.

The purpose of this paper is to highlight the possibilities of a novel Lagrangian formulation in dealing with the solution of the incompressible Navier‐Stokes equations with very large time steps.

The design of the paper is based on introducing the origin of this novel numerical method, originally inspired on the Particle Finite Element Method (PFEM), summarizing the previously published theory in its moving mesh version. Afterwards its extension to fixed mesh version is introduced, showing some details about the implementation.

The authors have found that even though this method was originally designed to deal with heterogeneous or free‐surface flows, it can be competitive with Eulerian alternatives, even in their range of optimal application in terms of accuracy, with an interesting robustness allowing to use large time steps in a stable way.

With this objective in mind, the authors have chosen a number of benchmark examples and have proved that the proposed algorithm provides results which compare favourably, both in terms of solution time and accuracy achieved, with alternative approaches, implemented in in‐house and commercial codes.

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.

Standard fire resistance curves such as ASTM E119 have been used for so long in structural fire practice. The issue with use of these curves that they do not represent real fire scenarios. As a result, the alternatives have been to either conduct experiments or find other tools to represent a real fire scenario. Therefore, the purpose of this paper is to understand the temperature effects resulted from a designed fire on steel beams and whether the standard fire curves represent a designed fire scenario.

Computational fluid dynamics (CFD) models were developed to simulate a designed fire scenario and to understand the structural responses on the beams under elevated temperatures. Consequently, the results obtained from the CFD models were compared with the results of three-dimensional (3D) non-linear finite element (FE) models developed by other researchers. The developed FE models were executed using a standard fire curve (ASTM E119). A parametric study including two case studies was conducted.

Results obtained from performing this study showed the importance of considering fire parameters such as fuel type and flame height during the thermal analysis compared to the standard fire curves, and this might lead to a non-conservative design as compared to the designed fire scenario. The studied cases showed that the steel beams experienced more degradation in their fire resistance at higher load levels under designed fires. Additionally, the models used the standard fire curves underestimated the temperatures at the early stages.

This paper shows results obtained by performing a comparison study of models used ASTM E119 curve and a designed fire scenario. The value of this study is to show the variability of using different fire scenarios; thus, more studies are required to see how temperature history curves can be used to represent real fire scenarios.

The purpose of this paper is to propose a new approach of using additively manufactured parametric models in the wind tunnel test-based aerodynamic shape optimization (ASO) framework and to present its applicability test results obtained from a realistic aircraft design problem.

For aircraft shape optimization, the following three methodologies were used. First, as a validation study, the possibility of using rapid prototyping (RP) model in the wind tunnel test was verified. Second, through the wind tunnel test-based ASO, the application and feasibility of the real fighter aircraft shape optimization were verified. A generic fighter configuration is parameterized to generate various test models using additive manufacturing. Wind tunnel tests are conducted to measure their stability criteria in high angle of attack (AOA). Finally, a computational fluid dynamics (CFD) study was performed and analysis procedures, costs and results compared to the wind tunnel test were compared and reviewed.

RP technology can significantly reduce the time and cost of generating parametric wind tunnel models and can open up new possibilities for wind tunnel tests to be used in the rigorous aerodynamic design loop. There was a slight difference between the results of the RP model and the metallic model because of rigidity and surface roughness. However, the tendency of the aerodynamic characteristics was very similarly predictable. Although there are limitations to obtaining precise aerodynamic data, it is a suitable method to be applied to comparative studies on various shapes with large geo-metric changes in the early phase of design. The CFD analysis indicates that the wind tunnel-based ASO using the RP model shows the efficiency corresponding to the CFD shape optimization.

The RP parametric models may have various assembly error sources and rigidity problems. The proposed methodology may not be suitable for collecting the accurate aerodynamic database of a final design; rather, the methodology is more suitable to screen out many configurations having fairly large shape variation in the early stage of the design process.

The wind tunnel test-based ASO can replace or supplement CFD-based ASO. In areas where CFD accuracy is low, such as high AOA flight characteristics, RP model wind tunnel-based ASO can be a research method that can secure both efficiency and accuracy advantages, providing ten times more effective in terms of cost and time. The wind tunnel test is used to obtain aerodynamic data at the final stage of shape design. It can be extended to a comparative study of several shapes in the early design phase. This procedure can be applied for both industrial level and educational aircraft design activities.

This study is the application to be applied as a parametric study on the whole aircraft, rather than using the RP model applying a simple partial control surface or configuration change of a part of the wing. The possibility of using the RP model was confirmed by comparing and verifying each other in a medium-sized wind tunnel using a relatively large RP model and a metallic model. It was verified that it can be applied in the shape design process, not the shape verification in the traditional design procedure, and a comparison with the CFD method was also performed. With further development and validation efforts, the new design framework may become an industrial standard for future aircraft development.

Data quality is a major challenge in data management. For organizations, the cleanliness of data is a significant problem that affects many business activities. Errors in data occur for different reasons, such as violation of business rules. However, because of the huge amount of data, manual cleaning alone is infeasible. Methods are required to repair and clean the dirty data through automatic detection, which are data quality issues to address. The purpose of this work is to extend the density-based data cleaning approach using conditional functional dependencies to achieve better data repair.

A set of conditional functional dependencies is introduced as an input to the density-based data cleaning algorithm. The algorithm repairs inconsistent data using this set.

This new approach was evaluated through experiments on real-world as well as synthetic datasets. The repair quality was determined using the F-measure. The results showed that the quality and scalability of the density-based data cleaning approach improved when conditional functional dependencies were introduced.

Conditional functional dependencies capture semantic errors among data values. This work demonstrates that the density-based data cleaning approach can be improved in terms of repairing inconsistent data by using conditional functional dependencies.

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 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 openings on aircraft structures can be modeled from an aerodynamical point of view as lid-driven cavities (LDC). This paper aims to show the primary verification and validation (V&V) process in computational fluid dynamics (CFD, and to investigate the influences of numerical settings on the efficiency and accuracy for solving the LDC problem.

To dig into the details of CFD approaches, this paper outlines the design, implementation, V&V and results of an efficient explicit algorithm. The parametric study is performed thoroughly focusing on various iteration methods, grid density discretization terms and Reynolds number effects.

This study parameterized the numerical implementation which provides empirical insights into how computational accuracy and efficiency are affected by changing numerical settings. At a low Reynolds number (not over 1,000), the time-derivative preconditioning is necessary, and k = 0.1 can be the optimal value to guarantee the efficiency, as well as the stability. A larger artificial viscosity (c = 1/16) would relieve the calculating oscillation issue but proportionally increase the discretization error. Furthermore, the iteration method and the mesh quality are two key factors that affect the convergence efficiency, thus need to be selected “wisely”.

The study shows how numerical implementation can enhance an accurate and efficient solution. This workflow can be used to determine the best parameter settings whenever CFD researchers applying this LDC problem as a complementary design tool for testing newly developed solvers.

The studied LDC problem is representative of CFD analysis in real aircraft structures. These numerical simulations provide a cost-effective and convenient tool to understand the parameter sensitivity, solution receptivity and physics of the CFD process.

Cloth fell distance is an effective parameter on controlling pick density during weaving process. The purpose of this study is developing a novel, simple and economic system to measure the cloth fell distance from the front position of the reed in each cycle of weaving process dynamically.

This novel system consists of optical sensors used to measure difference between time the reed reaches the cloth fell and time the reed reaches the front. To interpret this time difference to cloth fell distance, reed motion equation has been used. The reed motion curve in terms of angular position of the crankshaft can be calculated by mathematical analysis.

This method combining the electronic components and mechanical mechanism of reed motion measures the cloth fell distance online.

This simple and economic method can be used in all types of weaving machine. High accuracy and high speed processing in comparison to previous reported methods are the most advantages of this new real‐time system.