Computational Fluid Dynamics Simulation Data Research Articles

Evaluation of Mixed-Mode Ventilation Thermal Performance and Energy Saving Potential from Retrofitting a Beijing Office Building

Mixed-mode cooling can effectively reduce the energy consumption of building cooling while satisfying the thermal comfort of occupancy and indoor air quality requirements. This paper predicted the thermal performance and energy-saving potential of an existing Beijing office building (in continental climates) operated in a mixed-mode from April to October. For the natural ventilation mode, the results predicted by simulation were validated with the results of experiments conducted in October 2021 and April 2022. Occupancy thermal comfort of the mixed-mode building was predicted using Predicted Mean Vote (PMV) and adaptive comfort models. The predictions demonstrated acceptable satisfactory thermal comfort for the occupancy. The results showed that the mixed-mode building’s annual cooling energy use is reduced by around 45% compared to the air-conditioned building. In addition, the building’s indoor temperature and velocity distributions were predicted using a Computational Fluid Dynamics (CFD) simulation. The validation showed a satisfactory agreement between CFD simulation and measurement data. It is found from CFD results that cross-ventilation can provide thermal comfort for the occupancy while improving fresh air requirements. The suggested that operational strategies of mixed-mode cooling can be used in office buildings in continental climates. Retrofitting the existing office building can bring a significant amount of energy saving.

Numerical Simulation of Combustion and Characteristics of Fly Ash and Slag in a “V-type” Waste Incinerator

This study is focused on a “V-type” waste incinerator for municipal solid waste (MSW) combustion. Computational fluid dynamics (CFD) methods are used to study the MSW combustion process. The characteristics of fly ash and slag are analyzed by using a laser particle analyzer, scanning electron microscope, X-ray fluorescence, and X-ray diffraction. The results show that the error between the CFD simulation data and measured data is less than 10%, and the changing trend of the combustion process is well-modeled. The fly ash mainly has an irregular spherical or ellipsoid structure, whereas the slag mainly has an irregular porous structure. The main constituents of the ash and slag are CaO and SiO2, along with heavy metal elements such as Cu, Pb, and Cr.

Onset of Nucleate Boiling Model for Rectangular Upward Narrow Channel: CFD Based Approach

Despite that mechanistic and accurate correlations predicting the Onset of Nucleate Boiling (ONB) for pool boiling are widely presented in the literature, models for forced convective boiling remain few. These models do not provide the desired quality, principally because they do not consider important features of convective boiling. In this work, numerical investigations of the ONB for water boiling flow at atmospheric pressure upward a narrow rectangular channel (3 mm × 100 mm × 400 mm) are carried out based on Computational Fluid Dynamics (CFD) simulations. The predictions of the CFD calculations are validated with the available experimental data. A new ONB model incorporating the convective boiling features is developed and proposed. This model is derived based on several CFD simulation data, covering wide operating conditions. The flow Reynolds number ranges from 959 to 13500, inlet subcooling from 2.5 to 30 K and applied heat flux from 5 to 90 kW/m2. The new model predictions have a standard deviation of 2.7% where its performance is better than ±0.3 K when compared with additional simulation data that are provided for validation.

Finding the best operating condition in a novel process for explosive waste incineration using fluidized bed reactors

Explosives are among one of the most important components of a military system, and old explosives must be disposed safely and cleanly. Several explosive waste disposal methods have been developed, especially rotary kilns. Although using rotary kilns is better than other methods, problems like NOx emissions still exist. Thus a need of new and more efficient type of incinerator is required. Since fluidized bed reactors are well known for effective heat transfer and well mixed conditions, they have been proposed as an advanced incinerator. In this study, fluidized bed was simulated in CFD (computational fluid dynamics) program. The objective was finding the conditions that produced the lowest NOx emissions. By the CFD simulation, it was found that the change in inlet gas affects hot spot generation, and hot spot temperature is closely related to NOx emissions. As a result, the model was optimized through these characteristics and CFD simulation data.

Systematic assessment of the anode flow field hydrodynamics in a new circular PEM water electrolyser

In this work, we investigated the key underlying flow characteristics of a circular unit cell proton exchange membrane (PEM) water electrolyser. In particular, we focused on investigating anode flow field design using computational fluid dynamics (CFD) tool. Transient, 3D single phase fluid flow simulation results were presented, and in-house experiments were conducted for validation against CFD simulation data identifying key performance parameters of the PEM water electrolyser: uniform water distribution, pressure drop and hydraulic retention time. The effects of the water flow rate, inlet and outlet sizing and different number of inlet and outlet configurations were considered. The main observation from the study was discussed to provide insight into the factors affecting the flow pattern. Among the studied flow field design cases, it was found that the average pressure drop decreased with increase in number of inlets, also flow profile can be grouped into different set, depending on number of inlets. The correlation between pressure drop and mean velocity profile for different inlet and outlet configurations provides a useful basis to properly design the high performance PEM water electrolyser.

An Assessment of Drag Models in Eulerian–Eulerian CFD Simulation of Gas–Solid Flow Hydrodynamics in Circulating Fluidized Bed Riser

Accurate prediction of the hydrodynamic profile is important for circulating fluidized bed (CFB) reactor design and scale-up. Multiphase computational fluid dynamics (CFD) simulation with interphase momentum exchange is key to accurately predict the gas-solid profile along the height of the riser. The present work deals with the assessment of six different drag model capability to accurately predict the riser section axial solid holdup distribution in bench scale circulating fluidized bed. The difference between six drag model predictions were validated against the experiment data. Two-dimensional geometry, transient solver and Eulerian–Eulerian multiphase models were used. Six drag model simulation predictions were discussed with respect to axial and radial profile. The comparison between CFD simulation and experimental data shows that the Syamlal-O’Brien, Gidaspow, Wen-Yu and Huilin-Gidaspow drag models were successfully able to predict the riser upper section solid holdup distribution with better accuracy, however unable to predict the solid holdup transition region. On the other hand, the Gibilaro model and Helland drag model were successfully able to predict the bottom dense region, but the upper section solid holdup distribution was overpredicted. The CFD simulation comparison of different drag model has clearly shown the limitation of the drag model to accurately predict overall axial heterogeneity with accuracy.

Numerical investigation of gas/liquid two-phase flow in nozzle holes considering the fuel compressibility

In this paper, a numerical study on the fuel flow in a nozzle hole considering the fuel compressibility was performed. The results indicated that the discharge coefficient Cd in the nozzle hole for the compressible fuel was greater than that for the incompressible fuel. The critical cavitation number Kcrt was not affected by the fuel compressibility; rather, it only depended on the structural parameters and pressure difference of the nozzle hole. The Kcrt of compressible and incompressible fuel increased with the injection pressure. The difference between the Cd for compressible and incompressible fuel increased sharply in the initial short period before cavitation occurred. Subsequently, the difference decreased with an increase in the pressure difference. After cavitation occurred in the nozzle hole, the difference gradually decreased. Until the cavitation rapidly developed into supercavitation, the effect of the compressibility on the Cd in the nozzle hole became weak. For incompressible fuel, Cd decreased significantly in the single-phase flow of the fuel as the injection pressure increased. After cavitation occurred, the degree of the decrease in Cd caused by the increase in the injection pressure became insignificant. For compressible fuel, the injection pressure had little effect on Cd before cavitation occurred. However, the increase in the injection pressure reduced Cd after cavitation occurred. A fitting formula for Cd with respect to K1/2 under different injection pressures was obtained using an optimization algorithm. The good agreement between the calculation results and computational fluid dynamics simulation data confirmed the accuracy of the formula.

Integrated analysis of CFD simulation data with K-means clustering algorithm for soot formation under varied combustion conditions

Computational fluid dynamics (CFD) modelling is a scientific tool to provide fluid dynamics and chemical simulation that facilitates understanding of the complex combustion phenomenon in engine studies. With the advance of Machine Learning (ML) technology, the big data from CFD results can be intelligently recognized and classified, thus ease the data post-processing. This study proposed an integrated analysis that uses CFD simulation results of scalar distributions and K-means clustering algorithm to optimally partition engine combustion chamber into different zones. Therefore, the space of combustion chamber was automatically divided into light soot zones and heavy soot zones based on the clustering results on local equivalence ratio (ER) and temperature. Consequently, the surveys of soot mitigation by Reactivity Controlled Compression Ignition (RCCI) engines combustion mode were carried out as well as corresponding sooting tendency by CFD numerical study. The localized soot depositions in each zone under varied combustion boundaries were compared, hence improving the development of control strategy with numerical modellings and machine learning techniques.

The BubbleTree toolset: CFD-integrated algorithm for Lagrangian tracking and rigorous statistical analysis of bubble motion and gas fluxes for application to 3D fluidized bed simulations

Bubbling dynamics and distribution of gas flow critically influence the performance of fluidized bed reactors and must be quantified accurately for their design and performance optimization. In this study, a new toolset called the BubbleTree toolset (BT) was developed using Python and the Visualization Tool Kit (VTK) for analyzing computational fluid dynamics simulation data and performing statistical analysis of bubbling dynamics such as their volume, location, and velocity. In addition, the BT toolset provides the capability to (a) track bubbles through coalescence and splitting events and (b) compute throughflow by integrating gas fluxes through the bubble surface. The toolkit was verified using the method of manufactured solutions as well as by comparing bubbling dynamics predictions in large-scale simulations with relevant open-source software. The BT toolset also incorporates tools for rigorous statistical analysis in selected regions of interest as well as the reactor in its entirety. The BT will be integrated with MFiX CFD simulations which will enable the fundamental investigation of gas-solids flow interaction in complex reacting particulate flows, in situ estimation of bubbling (and cluster) dynamics dependent sub-grid models and performance optimization of fluidized bed reactors using CFD-simulations.

Wafter design for totally enclosed electric machines

A computational fluid dynamics (CFD) model representing the effect of wafters in a totally enclosed electric machine is presented, introducing the most relevant theoretical assumptions and simplifications. The validation of the model is conducted through experimental measurements. From the CFD simulation data, a second-order response surface is developed using statistical tools, from which the wafters’ influence on the convective heat transfer from the stator end windings is predicted. Wafter design criteria are obtained from the response surface information. Finally, a specific case is analysed, showing through CFD simulations that temperatures in the machine are reduced by including wafters in the design.

Benchmarking Reynolds Averaged Navier–Stokes Turbulence Models in Internal Pin Fin Channels

The performance of gas turbine engines increases with higher turbine inlet temperatures. To enable operation at temperatures beyond material limitations, turbine blades are often cooled using internal pin fin channels, which are used at the trailing-edge region. This study validates the accuracy of various Reynolds-averaged Navier–Stokes turbulence models in predicting the heat transfer rates and pressure distributions on the surface of the pins by comparing computational fluid dynamics simulation data against a valid set of experimental data obtained from literature. Considering the problem from an industrial design perspective, several commercially available, computationally efficient Reynolds-averaged Navier–Stokes turbulence models are used to predict the cooling performance of the pin fin channel. Turbulence models investigated are Menter’s shear stress transport, realizable , and a quadratic formulation of the realizable model. The geometry investigated is a staggered eight-row pin fin channel. Results show that the quadratic realizable and shear stress transport models predict pin surface heat transfer rates with the highest accuracy, with a dependency on Reynolds number and location within the channel. Comparisons have also shown that depending on Reynolds number, the realizable and quadratic realizable models match the pressure coefficient on the surface of the pin to within 8%.

Temperature balancing in steam methane reforming furnace via an integrated CFD/data-based optimization approach

In this work, we introduce a furnace-balancing scheme that generates an optimal furnace-side feed distribution that has the potential to improve the thermal efficiency of a reformer. The furnace-balancing scheme is composed of four major components: data generation, model identification, a model-based furnace-balancing optimizer and a termination checker. Initially, a computational fluid dynamics (CFD) model of an industrial-scale reformer, developed in our previous work, is used for the data generation as the model has been confirmed to simulate the typical transport and chemical reaction phenomena observed during reformer operation, and the CFD simulation data is in good agreement with various sources in literature. Then, we propose a model identification process in which the algorithm is formulated based on the least squares regression method, basic knowledge of radiative heat transfer and the existing furnace-side flow pattern. Subsequently, we propose a model-based furnace-balancing optimizer that is formulated as an optimization problem within which the valve position distribution is the decision variable, and minimizing the sum of the weighted squared deviations of the outer reforming tube wall temperatures from a set-point value for all reforming tubes with a penalty term on the deviation of the valve positions from their fully open positions is the objective function. CFD simulation results provide evidence that the optimized furnace-side feed distribution created by the furnace-balancing scheme can reduce the severity of nonuniformity in the spatial distribution of furnace-side temperature in the combustion chamber even when the reformer is under the influence of common valve-related disturbances.

Lactation in the Human Breast From a Fluid Dynamics Point of View.

This study is a collaborative effort among lactation specialists and fluid dynamic engineers. The paper presents clinical results for suckling pressure pattern in lactating human breast as well as a 3D computational fluid dynamics (CFD) modeling of milk flow using these clinical inputs. The investigation starts with a careful, statistically representative measurement of suckling vacuum pressure, milk flow rate, and milk intake in a group of infants. The results from clinical data show that suckling action does not occur with constant suckling rate but changes in a rhythmic manner for infants. These pressure profiles are then used as the boundary condition for the CFD study using commercial ansys fluent software. For the geometric model of the ductal system of the human breast, this work takes advantage of a recent advance in the development of a validated phantom that has been produced as a ground truth for the imaging applications for the breast. The geometric model is introduced into CFD simulations with the aforementioned boundary conditions. The results for milk intake from the CFD simulation and clinical data were compared and cross validated. Also, the variation of milk intake versus suckling pressure are presented and analyzed. Both the clinical and CFD simulation show that the maximum milk flow rate is not related to the largest vacuum pressure or longest feeding duration indicating other factors influence the milk intake by infants.

Enhanced flow visualisation of complex aerodynamic phenomena using automatic stream surface seeding with application to the BLOODHOUND SSC Land Speed Record vehicle

ABSTRACTThis application paper describes a novel, cluster-based, semi-automatic, stream surface placement strategy for structured and unstructured computational fluid dynamics (CFD) data, tailored towards a specific application: The BLOODHOUND jet and rocket propelled land speed record vehicle. An existing automatic stream surface placement algorithm(8), is extensively modified to cater for large unstructured CFD simulation data. The existing algorithm uses hierarchical clustering of velocity and distance vectors to find potential stream surface seeding locations. This work replaces the hierarchical clustering algorithm, designed to work with small regular grids, with a K-means clustering approach suitable for large unstructured grids. Modifications are made to the seeding curve construction algorithm, improving the smoothness and distribution of the discretised curve in complex cases. A new distance function is described which allows the user to target particular characteristics of simulation data. The proposed algorithm reduces the required memory footprint and computational requirement compared to previous work(8). The performance and effectiveness of the proposed algorithm is demonstrated, and CFD domain expert evaluation is provided describing the value of this approach.

Reduced order modeling of a short-residence time gasifier

State-of-the-art gasifiers require rapid mixing of fuel, steam and oxygen to achieve high carbon conversion within a short residence time. This allows reduction of the gasifier’s volume and the associated capital costs. CanmetENERGY of Natural Resources Canada has a pilot-scale gasifier that can convert solid fuels to syngas in less than 1s. This study describes the development of a reduced order model (ROM) for CanmetENERGY’s entrained flow short-residence time gasifier. The model consists of a reactor network that represents the gasifier using a set of chemical reactors that are aimed to capture distinct flow zones of the system. The layout of chemical reactors proposed in this work is based on computational fluid dynamics (CFD) simulations of the gasifier that accounted for the detailed gas and particle flows. The ROM implements sub-models for the simulation of drying, devolatilization, chemical reactions, viscous fluid–solid interactions, pollutant formation and heat transfer through the wall of the reactor. The predictions obtained by the ROM are in reasonable agreement with the CFD simulation data for axial temperature, heat flux, conversion and composition. Having established the flow pattern for a given gasifier and range of operating conditions, the proposed ROM is computationally efficient since it only requires 2.5min to converge whereas CFD simulations require 7–10days. This attractive feature enables integration of the gasifier ROM to process simulators for further development of integrated gasification combined cycle power plants.

CFD Simulation of Scale Influence on the Hydrodynamics of an Internal Loop Airlift Reactor

In this work, the overall gas hold-up in the riser and down-comer of three internal airlift reactors with a working volume of 10.5, 32 and 200 l at the range of temperatures 18℃ - 21℃, under atmospheric pressure was simulated using Com-putational Fluid Dynamics (CFD). The range of superficial gas velocity was 0.5 - 3 cm/s. The three reactors geometrically were similar to each other. CFD simulation and experimental data showed that the gas hold-up in the riser and down-comer increased by increasing the reactor scale. It was concluded that the simulated data were in good agreement with the experimental ones obtained from the literature.

Flow Past a Porous Permeable Sphere: Hydrodynamics and Heat-Transfer Studies

Flow past a porous permeable sphere has been studied using standard computational fluid dynamics (CFD) software (FLUENT) for a wide range of Reynolds numbers. Brinkman’s extension of Darcy’s law in the inner region and Navier–Stokes equations in the outer region of the porous permeable sphere were employed to solve the fluid flow phenomena. The results are presented in terms of three dimensionless parameters, e.g., the particle Reynolds number, the permeability ratio, and the drag ratio. The computed drag ratio asymptotically approaches zero at high permeability ratios and unity at low permeability ratios. A peak in the drag ratio versus permeability ratio plot is observed at high particle Reynolds number and in the intermediate range of permeability ratio. The drag ratios obtained from CFD simulation show good agreement with the experimental data available in the literature at different Reynolds numbers and permeability ratios. The results of heat transfer from porous permeable sphere are presented in terms of four dimensionless parameters: the particle Reynolds number (Re), permeability ratio, the Prandtl number (Pr), and the Nusselt number (Nu). The correlation obtained from the CFD simulation data for heat transfer from a porous permeable sphere is useful in predicting Nu for a wide range of Re and Pr at different permeability ratios.

Validation of a loss of vacuum accident (LOVA) Computational Fluid Dynamics (CFD) model

Intense thermal loads in fusion devices occur during plasma disruptions, Edge Localized Modes (ELM) and Vertical Displacement Events (VDE). They will result in macroscopic erosion of the plasma facing materials and consequent accumulation of activated dust into the ITER Vacuum Vessel (VV). A recognized safety issue for future fusion reactors fueled with deuterium and tritium is the generation of sizeable quantities of dust. In case of LOVA, air inlet occurs due to the pressure difference between the atmospheric condition and the internal condition. It causes mobilization of the dust that can exit the VV threatening public safety because it may contain tritium, may be radioactive from activation products, and may be chemically reactive and/or toxic (Sharpe et al. [1]; Sharpe and Humrickhouse [2]). Several experiments have been conducted with STARDUST facility in order to reproduce a low pressurization rate (300 Pa/s) LOVA event in ITER due to a small air leakage for two different positions of the leak, at the equatorial port level and at the divertor port level, in order to evaluate the velocity magnitude in case of a LOVA that is strictly connected with dust mobilization phenomena. A two-dimensional (2D) modelling of STARDUST, made with the CFD commercial code FLUENT, has been carried out. The results of these simulations were compared against the experimental data for CFD code validation. For validation purposes, the CFD simulation data were extracted at the same locations as the experimental data were collected. In this paper, the authors present and discuss the computer-simulation data and compare them with data collected during the laboratory studies at the University of Rome “Tor Vergata” Quantum Electronics and Plasmas lab.

Loss of vacuum accident (LOVA): Comparison of computational fluid dynamics (CFD) flow velocities against experimental data for the model validation

A recognized safety issue for future fusion reactors fueled with deuterium and tritium is the generation of sizeable quantities of dust. Several mechanisms resulting from material response to plasma bombardment in normal and off-normal conditions are responsible for generating dust of micron and sub-micron length scales inside the VV (Vacuum Vessel) of experimental fusion facilities. The loss of coolant accidents (LOCA), loss of coolant flow accidents (LOFA) and loss of vacuum accidents (LOVA) are types of accidents, expected in experimental fusion reactors like ITER, that may jeopardize components and plasma vessel integrity and cause dust mobilization risky for workers and public. The air velocity is the driven parameter for dust resuspension and its characterization, in the very first phase of the accidents, is critical for the dust release. To study the air velocity trend a small facility, Small Tank for Aerosol Removal and Dust (STARDUST), was set up at the University of Rome “Tor Vergata”, in collaboration with ENEA Frascati laboratories. It simulates a low pressurization rate (300 Pa/s) LOVA event in ITER due to a small air inlet from two different positions of the leak: at the equatorial port level and at the divertor port level. The velocity magnitude in STARDUST was investigated in order to map the velocity field by means of a punctual capacitive transducer placed inside STARDUST without obstacles. FLUENT was used to simulate the flow behavior for the same LOVA scenarios used during the experimental tests. The results of these simulations were compared against the experimental data for CFD code validation. For validation purposes, the CFD simulation data were extracted at the same locations as the experimental data were collected for the first four seconds, because at the beginning of the experiments the maximum velocity values (that could cause the almost complete dust mobilization) have been measured. In this paper the authors present and discuss the computer-simulation data and compare them with data collected in STARDUST.

Asymmetric Tensor Analysis for Flow Visualization

The gradient of a velocity vector field is an asymmetric tensor field which can provide critical insight that is difficult to infer from traditional trajectory-based vector field visualization techniques. We describe the structures in the eigenvalue and eigenvector fields of the gradient tensor and how these structures can be used to infer the behaviors of the velocity field. To illustrate the structures in asymmetric tensor fields, we introduce the notions of eigenvalue and eigenvector manifolds. These concepts afford a number of theoretical results that clarify the connections between symmetric and antisymmetric components in tensor fields. In addition, these manifolds naturally lead to partitions of tensor fields, which we use to design effective visualization strategies. Both eigenvalue manifold and eigenvector manifold are supported by a tensor reparameterization with physical meaning. This allows us to relate our tensor analysis to physical quantities such as rotation, angular deformation, and dilation, which provide physical interpretation of our tensor-driven vector field analysis in the context of fluid mechanics. To demonstrate the utility of our approach, we have applied our visualization techniques and interpretation to the study of the Sullivan Vortex as well as computational fluid dynamics simulation data.