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Describes the solution of implicitly discretized fluid flow equations, for turbulent swirling flows, by means of a new iterative method, based on the PISO algorithm. The technique is based on the splitting of the solution process into a series of steps, where, at each step, pressure operations are dissociated from those on velocities. The split sets of equations are solvable by standard numerical techniques. However, in this work, the influence of turbulent quantities and tangential velocity on the momentum equations is taken into account in the splitting process, through the source terms of the discretized equations. Does this by embedding a predictor and a corrector step for the turbulent quantities and for the tangential velocity into the PISO algorithm. This improvement to the standard PISO algorithm leads to a considerable reduction of the computational effort in achieving the same numerically converged solution. Applies the algorithm, in conjunction with a finite‐volume technique, to simulate two different geometries for two‐dimensional (axisymmetric) isothermal turbulent steady‐flows, with and without swirl. Compares the results with predictions of the same flows obtained other iterative methods (SIMPLE) and (PISO). Shows that the algorithm presented herein always exhibits a better efficiency in getting exactly the same final predictions, as far as the number of iterations for convergence and the required central processing unit time are concerned.

This paper aims to clarify the necessity of taking into account the commonly neglected radiation in built environments. Ignoring radiation within acclimatized spaces with moist air, which is a participating medium, can yield inaccurate values of the relevant variables, endangering the Heating, ventilation, and air conditioning design accuracy and leading to energy inefficiencies and discomfort.

The paper uses computational fluid dynamics to predict non-isothermal flows with radiation, for both mixing and displacement ventilation strategies. The tool is applied to a lab-scale model (scale 1:30), and the results are compared with experimental data and predictions without radiation. Furthermore, the radiation influence is also assessed at real-scale level, including a parametric study on the effect of the air relative humidity on radiation.

The paper demonstrates the unequivocal impact of radiation on the flows thermal-kinematics at real-scale: ignoring radiation yields average air temperature differences of 2ºC. This becomes more evident for larger air optical thicknesses (larger relative humidity): changing it from 20 per cent to 50 per cent and 70 per cent yields maximum relative differences of 100 per cent for the velocity components and 0.4ºC for the air temperature. Nevertheless, the results for the lab-scale case are not so conclusive about the effect of moist air radiation on the thermal flow characteristics, but they evidence its impact on the flow kinematics (maximum relative differences of velocity components of 35 per cent).

The paper fulfills an identified need to clarify the relevant effects of air moisture on radiation and on the flow turbulence and thermal-kinematic characteristics for forced convective flows inside built environments.

This study aims to feature the application of the artificial compressibility method (ACM) for the numerical prediction of two-dimensional (2D) axisymmetric swirling flows.

The respective academic numerical solver, named IGal2D, is based on the axisymmetric Reynolds-averaged Navier–Stokes (RANS) equations, arranged in a pseudo-Cartesian form, enhanced by the addition of the circumferential momentum equation. Discretization of spatial derivative terms within the governing equations is performed via unstructured 2D grid layouts, with a node-centered finite-volume scheme. For the evaluation of inviscid fluxes, the upwind Roe’s approximate Riemann solver is applied, coupled with a higher-order accurate spatial reconstruction, whereas an element-based approach is used for the calculation of gradients required for the viscous ones. Time integration is succeeded through a second-order accurate four-stage Runge-Kutta method, adopting additionally a local time-stepping technique. Further acceleration, in terms of computational time, is achieved by using an agglomeration multigrid scheme, incorporating the full approximation scheme in a V-cycle process, within an efficient edge-based data structure.

A detailed validation of the proposed numerical methodology is performed by encountering both inviscid and viscous (laminar and turbulent) swirling flows with axial symmetry. IGal2D is compared against the commercial software ANSYS fluent – by using appropriate metrics and characteristic flow quantities – but also against experimental measurements, confirming the proposed methodology’s potential to predict such flows in terms of accuracy.

This study provides a robust methodology for the accurate prediction of swirling flows by combining the axisymmetric RANS equations with ACM. In addition, a detailed description of the convective flux Jacobian is provided, filling a respective gap in research literature.

The purpose of this paper is to develop a combined method for three-dimensional incompressible flow and heat transfer by the spectral collocation method (SCM) and the artificial compressibility method (ACM), and further to study the performance of the combined method SCM-ACM for three-dimensional incompressible flow and heat transfer.

The partial differentials in space are discretized by the SCM with Chebyshev polynomial and Chebyshev–Gauss–Lobbatto collocation points. The unsteady artificial compressibility equations are solved to obtain the steady results by the ACM. Three-dimensional exact solutions with trigonometric function form and exponential function form are constructed to test the accuracy of the combined method.

The SCM-ACM is developed successfully for three-dimensional incompressible flow and heat transfer with high accuracy that the minimum value of variance can reach. The accuracy increases exponentially along with time marching steps. The accuracy is also improved exponentially with the increasing of nodes before stable accuracy is achieved, while it keeps stably with the increasing of the time step. The central processing unit time increases exponentially with the increasing of nodes and decreasing of the time step.

It is difficult for the implementation of the implicit scheme by the developed SCM-ACM. The SCM-ACM can be used for solving unsteady impressible fluid flow and heat transfer.

The SCM-ACM is applied for two classic cases of lid-driven cavity flow and natural convection in cubic cavities. The present results show good agreement with the published results with much fewer nodes.

The combined method SCM-ACM is developed, firstly, for solving three-dimensional incompressible fluid flow and heat transfer by the SCM and ACM. The performance of SCM-ACM is investigated. This combined method provides a new choice for solving three-dimensional fluid flow and heat transfer with high accuracy.

The purpose of this paper is to compare two different ventilation strategies, displacement and mixing, in heat, ventilating and air conditioning (HVAC) systems with recourse to computational fluid dynamics (CFD).

The flow and the heat and mass transfer are numerically predicted inside an air‐conditioned room with a desk and an occupant for the cooling and heating periods in moderate climate regions, like Mediterranean countries. Focus is placed on energy efficiency, thermal comfort and internal air quality (IAQ), evaluated from the simulations of the three‐dimensional, turbulent, non‐isothermal and buoyant flow of moist air.

For the cooling period, displacement exhibits higher energy and ventilation efficiencies promoting simultaneously better comfort for the occupant. For the heating period, mixing performs better due to the short‐circuit phenomenon occurring with the displacement flow. Overall, mixing behaves better for air‐conditioning of typical office rooms in Mediterranean‐climate countries, where heating and cooling climatization modes have to be alternated according to the season.

Room, desk and occupant are designed as parallelepipeds. No experimental work is performed but models used are previously validated by other authors against experimental data.

The results indicate a short‐circuit flow phenomenon that must be avoided when designing HVAC systems.

Use of grilles layout typical for the cooling period to study the air‐conditioning of a typical office room during the heating period, incorporating in the model a transport equation for the moisture. IAQ is simulated together with the flow, the heat and the comfort conditions: velocities, temperature, predicted mean vote (PMV), predicted percentage of dissatisfied (PPD), draught rating (DR), PPD due to air quality (PDQ) and air moisture content are calculated simultaneously.

The high costs of collection and transportation of municipal solid waste (MSW) on the overall waste management budget (sometimes more than 75 per cent) makes it an issue to be urgently addressed for improvement. The paper aims to focus on the optimisation of routing networks for waste collection/transportation.

The paper proposes herein the application of geographic information system (GIS) 3D route modelling for waste collection/transportation to optimise the route according to the minimum fuel consumption criterion to different municipalities of the island of Santo Antao of Cape Verde.

The optimisation for the lowest fuel consumption yields 52 per cent savings in fuel, when compared to that for the shortest distance, even travelling a 34 percent longer distance, which shows the importance of considering simultaneously the relief of the territory and the lowest fuel consumption criterion when optimising vehicle routes.

With such a supporting decision tool savings in fuel are huge, the efficiency of management systems is improved and the environmental impact during daily operation is reduced. The GIS 3D route modelling takes into account the effects of both the road inclination and the vehicle load.

The originality of the work lies in the chosen approach. To optimise vehicle routes the criterion of minimum fuel consumption rather than the commonly used shortest distance is used, since fuel consumption is the factor reflecting actual costs relative to MSW management.

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this study is to design a new model for municipal waste collection vehicle routing problems with time windows and energy generating from waste. To this purpose, a bi-objective model is presented with the objectives of increasing the income of waste recycles and energy generation from waste and reducing emissions from environmental pollutants.

A bi-objective model is presented with the objectives of increasing income of recycles trade and energy generation and reducing emissions from environmental pollutants. Concerning the complexity of the model and its inability to solve large-scale problems, non-dominated sorting genetic algorithms and multi-objective particle swarm optimization algorithms are applied.

In this research, an integrated approach to urban waste collection modeling that coordinates the various activities of waste management in the city of Kermanshah and energy generation from waste are provided. Besides, this study calculates the criteria that show the environmental effects of municipal waste. The proposed model helps to collect municipal wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy production.

The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

The purpose of this paper is to analyse the thermal environment of two engineering testing centres cooled via different means using computational fluid dynamics (CFD), focussing on the indoor temperature and air movement. This computational technique has been used in the analysis of thermal environment in buildings where the profiles of thermal comfort parameters, such as air temperature and velocity, are studied.

A pilot survey was conducted at two engineering testing centres – a passively cooled workshop and an air-conditioned laboratory. Electronic sensors were used in addition to building design documentation to collect the required information for the CFD model–based prediction of air temperature and velocity distribution patterns for the laboratory and workshop. In the models, both laboratory and workshop were presumed to be fully occupied. The predictions were then compared to empirical data that were obtained from field measurements. Operative temperature and predicted mean vote (PMV)–predicted percentage dissatisfied (PPD) indices were calculated in each case in order to predict thermal comfort levels.

The simulated results indicated that the mean air temperatures of 21.5°C and 32.4°C in the laboratory and workshop, respectively, were in excess of the recommended thermal comfort ranges specified in MS1525, a local energy efficiency guideline for non-residential buildings. However, air velocities above 0.3 m/s were predicted in the two testing facilities, which would be acceptable to most occupants. Based on the calculated PMV derived from the CFD predictions, the thermal sensation of users of the air-conditioned laboratory was predicted as −1.7 where a “slightly cool” thermal experience would prevail, but machinery operators in the workshop would find their thermal environment too warm with an overall sensation score of 2.4. A comparison of the simulated and empirical results showed that the air temperatures were in good agreement with a percentage of difference below 2%. However, the level of correlation was not replicated for the air velocity results, owing to uncertainties in the selected boundary conditions, which was due to limitations in the measuring instrumentation used.

Due to the varying designs, the simulated results of this study are only applicable to laboratory and workshop facilities located in the tropics.

The results of this study will enable building services and air-conditioning engineers, especially those who are in charge of the air-conditioning and mechanical ventilation (ACMV) system design and maintenance to have a better understanding of the thermal environment and comfort conditions in the testing facilities, leading to a more effective technical and managerial planning for an optimised thermal comfort management. The method of this work can be extended to the development of CFD models for other testing facilities in educational institutions.

The findings of this work are particularly useful for both industry and academia as the indoor environment of real engineering testing facilities were simulated and analysed. Students and staff in the higher educational institutions would benefit from the improved thermal comfort conditions in these facilities.

For the time being, CFD studies have been carried out to evaluate thermal comfort conditions in various building spaces. However, the information of thermal comfort in the engineering testing centres, of particular those in the hot–humid region are scantily available. The outcomes of this simulation work showed the usefulness of CFD in assisting the management of such facilities not only in the design of efficient ACMV systems but also in enhancing indoor thermal comfort.