Mohamed S. Hamed

Experimental investigation of propagation of wetting front on curved surfaces exposed to an impinging water jet

The wetting phenomenon during the cooling of a hot cylindrical specimen exposed to an impinging water jet has been studied experimentally. The Speed of Propagation of Wetting Front (SPWF) and regions of boiling heat that transfer outwards from the jet stagnation point have been investigated using high-speed video images. The effect of various jet parameters (velocity, diameter, water temperature) and the effect of the surface temperature on SPWF have been considered. Experiments were conducted under transient conditions considering initial specimen surface temperatures of 250°C, 500°C and 800°C, water temperatures in the range between 20°C and 80°C, jet velocities of 5 m/s and 7.75 m/s and jet diameters of 3 mm and 4 mm. For all of the jet and surface parameters considered in the study, SPWF was found to correlate well with power functions of time (i.e., instantaneous wetting front radius R=a(t)n)). Within the considered range of parameters, the results indicate that SPWF is mostly affected by the initial surface temperature, water temperature and jet velocity. Since control of the product microstructure is the key in determining its mechanical properties, the results of the investigation of the SPWF are used to quench carbon steel (1045) cylinders using different combinations of jet parameters. The results show a great flexibility in achieving various cooling rates, as indicated by the change in the final microstructure of the quenched samples.

A nonlinear numerical model for sloshing motion in tuned liquid dampers

Purpose – This paper presents a new numerical model that, unlike most existing ones, can solve the whole liquid sloshing, nonlinear, moving boundary problem with free surface undergoing small to very large deformations without imposing any linearization assumptions.Design/methodology/approach – The time‐dependent, unknown, irregular physical domain is mapped onto a rectangular computational domain. The explicit form of the mapping function is unknown and is determined as part of the solution. Temporal discretization is based on one‐step implicit method. Second‐order, finite‐difference approximations are used for spatial discretizations.Findings – The performance of the algorithm has been verified through convergence tests. Comparison between numerical and experimental results has indicated that the algorithm can accurately predict the sloshing motion of the liquid undergoing large interfacial deformations.Originality/value – The ability to model liquid sloshing motion under conditions leading to large int...

Effects of Acidity and Method of Preparation on Nucleate Pool Boiling of Nanofluids

Past research has shown contradicting trends in the rate of heat transfer during pool boiling of nanofluids, which could be attributed either to their stability or to their method of preparation or to both. An experimental study has been conducted to investigate the effects of electrostatic stabilization and preparation method of nanofluids on their pool boiling rate of heat transfer. Nanofluids made from water and alumina nanoparticles at 0.1 vol% concentration were used. The effect of electrostatic stabilization was investigated by changing the pH value from 6.5, neutral, to 5, acidic. The effect of preparation method has been investigated by using nanofluids prepared from dry particles and from ready-made suspensions. Compared with water, all nanofluids investigated resulted in deterioration in the rate of heat transfer during pool boiling. Neutral nanofluids made from ready-made suspensions and from dry particles resulted into almost the same deterioration in the rate of heat transfer of 49% and 45%, respectively, with respect to that of pure water. The most significant effect of electrostatic stabilization was found in the case of acidic nanofluids made from dry particles, which resulted in deterioration in the rate of heat transfer of 31%. However, acidic nanofluids made from ready-made suspensions resulted in a deterioration of 46%, which is almost the same as that of suspension-made and dry particles-made nanofluids. These results indicate that electrostatic stabilization using acid addition is most effective with nanofluids made from dry particles.

Turbulence Modeling of Forced Convection Heat Transfer in Two-Dimensional Ribbed Channels

Although the problem of 2D ribbed channels has been studied heavily in the literature as a benchmark or basic case for cooling of electronic packing, there is still a contradiction in the literature about the suitable turbulence model that should be used in such a problem. The accuracy of the computational predictions of heat transfer rates depends mostly on the choice of the proper turbulence model that is capable of capturing the physics of the problem, and on the corresponding wall treatment. The main objective of this work is to identify the proper turbulence model to be used in thermal analysis of electronic systems. A number of available turbulence models, namely, the standard k-e, the renormalization group k-e, the shear stress transport (SST), the k-ω, and the Reynolds stress models, have been investigated. The selection of the most appropriate turbulence model has been based upon comparisons with both direct numerical simulations (DNSs) and experimental results of other works. Based on such comparisons, the SST turbulence model has been found to produce results in very good agreement with the DNS and experimental results and hence it is recommended as an appropriate turbulence model for thermal analysis of electronic packaging.

An Efficient Numerical Algorithm for the Prediction of Thermal and Microstructure Fields during Quenching of Steel Rods

This paper presents a new, more efficient numerical algorithm that has been developed to predict thermal and microstructure fields during quenching of steel rods. The present algorithm solves the full nonlinear heat conduction equation using a central finite-difference scheme coupled with a fourth-order Runge-Kutta nonlinear solver. Numerical results, obtained using the present algorithm, have been validated using experimental data and numerical results available in the literature. In addition to its accurate predictions, the present algorithm does not require iteration; hence, it is computationally more efficient than previous numerical algorithms.

Optimization of Energy Utilization and Productivity of Heat Treating Batch-Type Furnaces

Due to the energy-intensive nature of the heat treating industry and the recent substantial increase of energy prices, the availability of predictive tools that can be used to optimize heat treatment processes has become a very pressing must. Load configuration (size and arrangement) during batch-type heat treating operations is the main factor that controls the rate of heat transfer between the furnace and the load, and hence it affects energy utilization and productivity of such operations. The main objective of this work is to develop a numerical model that can be used as a predictive tool for determining optimum loading of batch-type furnaces in order to achieve maximum productivity (mass treated per unit time) and minimum energy consumption per unit mass. A numerical model has been developed to simulate heat treatment processes in batch-type furnaces. The model has been validated by comparing numerical results with experimental data collected under laboratory and real-life conditions. Experiments have been carried out at the research facility at TPL as well as at different industrial sites. The paper presents the development and validation of the model as well as case studies of batch heat treatment cycles where best load configurations have been investigated.

Modeling of Heat Treatment of Randomly Distributed Loads in Multi-Zone Continuous Furnaces

A model for the heat treatment of randomly distributed metal parts processed in multi-zone continuous mesh-belt furnaces has been developed. The model accounts for the heat transfer by convection and radiation to the load and the belt. The effect of gas radiation due to the presence of CO2 and/or H2O gases in the furnace atmosphere has been accounted for. The effect of conduction, convection, and radiation within the parts has been considered. The effective thermal properties of the load have been calculated using a new model developed for randomly distributed parts. The effective thermal properties model has been developed using experimental data obtained from transient experiments carried out at the Thermal Processing Laboratory (TPL) of McMaster University. The continuous furnace model is capable of predicting temperature distribution within the load and the belt. It has been validated using real-life data obtained from test runs carried out at two heat treatment facilities in Ontario, Canada. The effects of load density, load emissivity and belt speed on furnace productivity have been investigated using the present continuous furnace model.

A Modified Online Input Estimation Algorithm for Inverse Modeling of Steel Quenching

The surface temperatures and surface heat flux of a 1080 steel cylinder during the quenching process are estimated by the application of inverse heat transfer analysis. The conventional online input estimation algorithm is modified and used for the first time to handle this coupled nonlinear problem. The nonlinearity of the problem is treated explicitly, which results in a noniterative algorithm suitable for real-time control of the steel quenching process. The results obtained are validated using experimental data and numerical results obtained by solving the direct problem. Results show that the algorithm can estimate the convective heat transfer coefficient efficiently.

Numerical study of the modeling error in the online input estimation algorithm used for inverse heat conduction problems (IHCPs)

A numerical investigation has been conducted to study the effect of modeling error in the state equation on the performance of the online input estimation algorithm in its application to the inverse heat conduction problems. This modeling error is used as a tuning parameter known as the stabilizing parameter in the online input estimation algorithm of the inverse heat conduction problems. Three different cases which cover most forms of the boundary heat flux functions have been considered. These cases are: square wave, triangular wave and mixed wave heat fluxes. The investigation has been carried for a one dimensional inverse heat conduction problem. Temperature measurements required for the inverse algorithm was generated by using a numerical solution of the direct heat conduction problem employing the three boundary heat flux functions. The most important finding of this investigation is that a robust range of the stabilizing parameter has been found which achieves the desired trade-off between the filter tracking ability and its sensitivity to measurement errors. For all three considered cases, it has been found that there is a common optimal value of the stabilizing parameter at which the estimate bias is minimal. This finding is very important for practical applications since this parameter is unknown practically and this study provides a needed guidance for assuming this parameter. The effect of changing other important parameters in the online input estimation algorithm on its performance has also been studied in this investigation.

Interaction between primary dendrite arm spacing and velocity of fluid flow during solidification of Al–Si binary alloys

A new and more efficient numerical algorithm to simulate the solidification of binary metallic alloys, wherein for the first time, the undercooling of the liquidus temperature prior to solidification event and optimized thermo-physical properties was incorporated, has been recently developed and validated by various experiments. Subsequently, experiments were carried out to evaluate the validity of various theoretical models in the literature used to predict the dendrite arm spacing (DAS) and quantify the critical interaction between fluid flow and transient DAS during unsteady state solidification. Typically, models of solidification processes such as casting, welding and galvanizing assume a constant value of fluid flow to predict the DAS and in many cases unable to obtain validation. This practice is erroneous and the transient fluid flow developed during solidification has a significant effect on the transient DAS, thermal gradient (G), solidification velocity (R) and morphology of the mushy zone. The Bouchard–Kirkaldy model (DAS prediction) coupled with the Lehmann model to incorporate fluid flow velocity was the only valid theoretical model in binary alloy solidification.