Computational Fluid Dynamics And Heat Transfer Research Articles

Analysis of flow boiling incipience models in computational fluid dynamics

Recent advances in the computational fluid dynamics and heat transfer (CFD/HT) modeling of flow boiling have enabled a more detailed analysis and understanding of thermal management in relatively complex microsystems. Most advanced modeling approaches allow the transient analysis of two-phase flow and phase-change processes, providing the capability to post-process in detail the temperature, phase and pressure distributions in microscale applications with the use of moderate computational resources. Although these models have significantly evolved in recent years, there are still several idealizations and assumptions that have yet to be improved or better justified, the boiling incipience treatment being a commonly questioned topic. In the present investigation, a boiling incipience model is incorporated into an existing CFD/HT model for the analysis of flow boiling mechanisms, where the superheat temperature is derived from fundamental thermodynamic relations and compared to the original CFD/HT model that does not account for such effects. Results are compared using a non-trivial case of a silicon micro-cooling layer with variable density of pin fins that has been demonstrated to be an efficient thermal control device in high-power applications. The dielectric fluid HFE-7200 is used as the coolant in flow boiling conditions. The two-phase flow regimes and heat transfer results for both models are compared.

Reconstruction and fast prediction of 3D heat and mass transfer based on a variational autoencoder

Reconstruction and fast prediction of heat and mass transfer are important for the improvement of data center operations and energy savings. In this study, an artificial neural network (ANN) and variational autoencoder (VAE) composite model is proposed for the reconstruction and prediction of 3D flowfields with high accuracy and efficiency. The VAE model is trained to extract features of the problem and to realize 3D physical field reconstruction. The ANN is employed to achieve the constructability of the extracted features. A dataset of steady temperature/velocity fields is acquired by computational fluid dynamics and heat transfer (CFD/HT) and fed to train the deep learning model. The proposed ANN-VAE model is experimentally proven to achieve promising field prediction accuracy with a significantly reduced computational cost. CFD/HT method is often incapable of occasions that require instant knowledge of heat and mass transfer. The proposed ANN-VAE method convert the time-consuming simulations into the training stage. Driven by large amount of simulation data, the trained ANN-VAE model is capable of field prediction. Compared to the CFD/HT method, the ANN-VAE method speeds up the physical field prediction by approximately 380,000 times, with mean accuracies of 97.3% for temperature field prediction and 97.9% for velocity field prediction, making it feasible for real-time prediction of heat and mass transfer.

Optimisation of design parameters of the finned tube heat exchanger by numerical simulations and artificial neural networks for the condensing wall hang boilers

This research investigates the use of computational fluid dynamics (CFD) and artificial neural networks (ANNs) to optimise the design of finned tube heat exchangers for use in condensing wall-mounted boilers (WHBcs). Fin height, thickness, and distance are selected as the input design parameters, and the internal volume of the heat engine is modelled using the CFDHT (CFD and heat transfer) method. Different ANN structures are trained and tested on the resulting data to identify the optimal training process. The trained ANN is then used to predict various output parameters, including total heat transfer on the inner surface of the tube, maximum temperature on the fins, total heat transfer per unit volume of the heat exchanger, and pressure drop between the inlet and outlet of the internal volume. The optimal design scenarios are evaluated based on design criteria, and the ANN is found to have good statistical performance, with an average accuracy of 1.00018 and a maximum relative error of 9.16%. The ANN is able to accurately estimate the optimal design case.

Flow boiling in geometrically modified microchannels

Microchannels are a promising solution for high-heat-flux thermal management scenarios, including high-performance microelectronics cooling and power electronics cooling. However, thermohydraulic instabilities result from the rapid vapor bubble formation. The prior literature has examined several methods, including constricted inlet microchannels, expanding microchannels, and auxiliary jetting microchannels, to mitigate the effect of these instabilities. Computational fluid dynamics and heat transfer (CFD/HT) modeling of the flow boiling phenomena in these microchannel configurations has seen limited examination, and one-to-one numerical comparisons of the different mitigation strategies have not been performed. In the present investigation, CFD/HT analyses using a three-dimensional (3D) volume of fluid model coupled with a phase-change model for the interfacial heat and mass transfer were performed for multiple microchannel configurations (constricted inlet, expanding, and auxiliary jetting microchannels). A benchmark case of a rectangular microchannel was examined to quantify baseline thermohydraulic performance. Results demonstrated slight to significant thermal performance improvements for all cases, and significant pressure benefits for the expanding and jetting cases, consistent with experimental results in the literature. Bubble dynamics and visualization for the baseline and alternative configurations are provided to give insight into their underlying physics, and the differences in performance were investigated and compared with available literature.

Development and Validation of a Model for Efficient Simulation of Freezing of Water in Large Tanks

Abstract Liquid water–urea mixtures are used in diesel vehicles for exhaust after treatment. In cold weather, the entire liquid may freeze and the process may span over a day. Traditional computational fluid dynamics and heat transfer (CFD/CHT) methodologies are impractical for modeling such freezing processes because of restrictions in the time-step size—typically milliseconds—posed by numerical stability and physical timescale considerations. Preliminary investigations revealed that the primary constraint for using small time-steps is the fine-scale motion generated by natural convection in both the liquid and the gas. A new model is proposed and demonstrated for efficient prediction of the propagation of the solidification front. In this model, heat transfer due to natural convection is modeled as a diffusive process analogous to how turbulent transport is modeled using an eddy diffusivity. The model enables the use of large time-steps since the fine-scale motions due to natural convection are not resolved. It was validated against experimental data for pure water, which were also collected as part of the study. Each experiment collected data at intervals of 6 s for a total duration of about 24 h. Several different tank fill levels were considered, and a good agreement with experimental data was noted, especially for shallow fill levels. Large-scale parallel three-dimensional calculations were conducted for the freezing of pure water in a few days of computational time as opposed to a year (projected) of computational time using traditional CFD/CHT models and the same computational resources.

Thermal Modeling of Outdoor Digital Displays Under Different Brightness Outputs

The thermal design process for electronic products often minimizes the use of computational fluid dynamics and heat transfer (CFD/HT) software in favor of quick prototyping and testing to determine the thermal characteristics of the product. For large-scale products with many thermal challenges, such a strategy can be impractical due to the high cost of prototyping cycles, time constraints, and inevitable iterations involved. In such cases, thorough CFD/HT models developed early in the design process are valuable for driving the product design. Based on this idea, the study examines thermal performance of 55” outdoor digital displays using CFD/HT tools and a prediction under hazardous outdoor condition is made for two different brightness outputs. The prediction is extrapolated and validated through the outdoor testing and simulation comparisons. It is shown that CFD/HT software can be used as a means of making conservative design choices.

Reduced order modeling of a data center model with multi-Parameters

Although full-field simulations using computational fluid dynamics and heat transfer (CFD/HT) tools can be applied to predict the flow and temperature fields inside data centers, their running time remain the biggest challenge to most modelers. In this paper, a reduced order modeling method is used to drastically reduce the running time (up to 600 times faster) while still acceptably preserving the accuracy of the model. The results obtained from Proper Orthogonal Decomposition (POD) method are in good agreement with the results obtained from CFD/HT model simulation. The sensitivity analysis of some of the design parameters in the POD model is evaluated. In addition, a 3-D temperature profile of the data center model constructed from 2D slices are generated with a linear interpolation technique. Tradeoff between accuracy and running time is observed and discussed.

Coupled inviscid-viscous solution method for bounded domains: Application to data-center thermal management

Computational fluid dynamics and heat transfer (CFD/HT) models have been employed as the dominant technique for the design and optimization of both new and existing data-centers. Inviscid modeling has shown great speed advantages over the full Navier–Stokes CFD/HT models (over 20 times faster), but is incapable of capturing the physics in the viscous regions of the domain. A coupled inviscid-viscous solution method (CIVSM) for bounded domains has been developed in order to increase both the solution speed and accuracy of CFD/HT models. The methodology consists of an iterative solution technique that divides the full domain into multiple regions consisting of at least one set of viscous, inviscid, and interface regions. The full steady, Reynolds averaged Navier–Stokes equations with turbulence modeling are used to solve the viscous domain, while the inviscid domain is solved using the Euler equations. By combining the increased speed of the inviscid solver in the inviscid regions, along with the viscous solver’s ability to capture the turbulent flow physics in the viscous regions, a faster and potentially more accurate solution can be obtained for bounded domains that contain large inviscid regions, such as data-centers.

Inviscid and Viscous Numerical Models Compared to Experimental Data in a Small Data Center Test Cell

Both localized power densities and overall power consumption within the data center continue to rise, following the same upward trend as the information technology (IT) equipment stored within the data center. Air cooling this increasing power has proved a significant challenge at both the IT equipment and data center level. In order to combat this challenge, computational fluid dynamics and heat transfer (CFD/HT) models have been employed as the dominant technique for the design and optimization of both new and existing data centers. This study is a continuation of earlier comparisons of CFD/HT models to experimentally measured temperature and flow fields in a small data center test cell. It compares an inviscid model, a laminar flow model, and three turbulence models to six sets of experimentally collected data. The six sets of data are from two different IT equipment rack power dissipations using three different layouts of perforated tiles. Insight into the location of the deviation between the different CFD/HT models and experimental data are discussed, along with the computational effort involved in running the models. A new grid analysis was performed on the different CFD/HT models in order to try to minimize computational effort. The inviscid model was able to run with a smaller grid size than the viscous models and even for the same size grid was found to run 30% faster than the fastest viscous model. Due to both the reduced grid size and computational effort (due to the simpler equation set), the inviscid model ran over thirty times faster than the next fastest model. The fact that the inviscid model ran the fastest is not surprising, however what was not expected is that the inviscid model was also found to have the smallest deviations from the experimental data for all six of the cases. This is most likely due to the arrangement of the data center test cell with the relatively few high velocity air jets and large open space around the IT equipment. More tightly packed data centers with higher air velocities and turbulent mixing conditions will certainly produce different results than those found in this study.

Investigation of design parameters of a domestic refrigerator by artificial neural networks and numerical simulations

This study presents an application of artificial neural networks (ANNs) to predict the design parameter's values of the static type domestic refrigerator. The interior air volume of refrigerator was modeled using computational fluid dynamics and heat transfer (CFDHT) method and analyses were made. The numerical results were validated by comparing with the experimental results and then inner design parameters were determined. Data sets for training and testing ANN model were acquired by numerical results. The ANN was used for predicting design parameters' values, namely the gap between evaporator surface and glass shelf, evaporator height and surface temperature. ANN predictions demonstrate us a good statistical performance with the average correlation coefficients of 1.00453 and maximum relative error of 2.32%. It is suggested that ANNs model is a successful method for the designers and engineers to obtain preliminary assessment quickly for design parameter modifications of the static type domestic refrigerators.