Numerical Analysis of the Spontaneous Combustion Accidents of Oil Storage Tanks Containing Sulfur

In order to study various influencing factors of spontaneous combustion accidents of sulfur-containing oil storage tanks, this paper constructed a two-dimensional model of the storage tank wall by COMSOL Multiphysics software. The proposed model takes temperature change trend as an observation index to explore the heat transfer process of the tank wall. By fitting the function curve of heat release with oxidation reaction temperature of sulfur corrosion products and comparing with constant heat sources, it is found that heat source intensity will affect the temperature growth trend of tank spontaneous combustion. In addition, the air convection heat transfer coefficient represents the interference degree of external environment to the spontaneous combustion heating process, and the wall heating rate decreases with the increase of air convection heat transfer coefficient. The different heat release rates in varying oxidation stages will lead to distinct temperature growth trends. The larger the air convection heat transfer coefficient, the greater the temperature difference between the inner and outer walls of the tank, which is not conducive to the detection of the abnormal temperature of the heat source. The difference of thermal insulation and thermal conductivity of tank materials also affects the wall heat transfer, so the material properties should be considered comprehensively in actual production. The research results can provide a research basis and a theoretical basis for monitoring, prevention, and control of spontaneous combustion of sour oil storage tanks.

Experimental and Theoretical Investigation of the Natural Convection Heat Transfer Coefficient in Phase Change Material (PCM) Based Fin-and-Tube Heat Exchanger

Latent heat thermal energy storage systems allow storing large amounts of energy in relatively small volumes. Phase change materials (PCMs) are used as a latent heat storage medium. However, low thermal conductivity of most PCMs results in long melting (charging) and solidification (discharging) processes. This study focuses on the PCM melting process in a fin-and-tube type copper heat exchanger. The aim of this study is to define analytically natural convection heat transfer coefficient and compare the results with experimental data. The study shows how the local heat transfer coefficient changes in different areas of the heat exchanger and how it is affected by the choice of characteristic length and boundary conditions. It has been determined that applying the calculation method of the natural convection occurring in the channel leads to results that are closer to the experiment. Using this method, the average values of the heat transfer coefficient (have) during the entire charging process was obtained 68 W/m2K, compared to the experimental result have = 61 W/m2K. This is beneficial in the predesign stage of PCM-based thermal energy storage units.

Application of support vector machines for accurate prediction of convection heat transfer coefficient of nanofluids through circular pipes

Purpose Convection is one of the main heat transfer mechanisms in both high to low temperature media. The accurate convection heat transfer coefficient (HTC) value is required for exact prediction of heat transfer. As convection HTC depends on many variables including fluid properties, flow hydrodynamics, surface geometry and operating and boundary conditions, among others, its accurate estimation is often too hard. Homogeneous dispersion of nanoparticles in a base fluid (nanofluids) that found high popularities during the past two decades has also increased the level of this complexity. Therefore, this study aims to show the application of least-square support vector machines (LS-SVM) for prediction of convection heat transfer coefficient of nanofluids through circular pipes as an accurate alternative way and draw a clear path for future researches in the field. Design/methodology/approach The proposed LS-SVM model is developed using a relatively huge databank, including 253 experimental data sets. The predictive performance of this intelligent approach is validated using both experimental data and empirical correlations in the literature. Findings The results show that the LS-SVM paradigm with a radial basis kernel outperforms all other considered approaches. It presents an absolute average relative deviation of 2.47% and the regression coefficient (R2) of 0.99935 for the estimation of the experimental databank. The proposed smart paradigm expedites the procedure of estimation of convection HTC of nanofluid flow inside circular pipes. Originality/value Therefore, the focus of the current study is concentrated on the estimation of convection HTC of nanofluid flow through circular pipes using the LS-SVM. Indeed, this estimation is done using operating conditions and some simply measured characteristics of nanoparticle, base fluid and nanofluid.

Fluid Convection Models for Low-Temperature Grinding and Effect of Fluid Warming

The paper considers fluid convection in low-temperature grinding. Fluid cooling often predominates over all other forms of heat dispersion in the grinding zone particularly in low-temperature grinding. Experimental values of convection heat transfer coefficient (CHTC) up to and in excess of 200,000 W/m2K have been found by various researchers both for water-based emulsions and in one case for mineral oils employed in high wheel-speed grinding. Several convection models have been developed in recent years for the prediction of CHTCs in low-temperature grinding. This paper reviews advances in convection modeling and reconsiders the basic assumptions implied. A proposal is made for improved estimation for highly churned flow assuming a degree of fluid warming. Predicted coefficients are compared with measured values.