One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried out using the APDL scripting language (ANSYS Parametric Design Language) that is provided by the commercial code ANSYS. Infrared (IR) thermography technique was used to explore the workpiece surface and to validate the obtained results. The work takes into account the effect of different speeds of the laser beam and pulses overlap on the temperature pattern of the material surface and depth.
Background: Polymethylmethacrylate (PMMA) is the most ‎commonly used mâ€aterial in denture construction. This material is ‎far from ideal in fulfilling the‎ mechanical requirements, like low impact and transverse strength and poor thermal conductivity are present in this material. The purpose of this study was to study the effect of addition a composite which include 1%wt silanized silicone dioxide nano fillers (SiO2) and 1wt% oxygen plasma treated polypropylene fiber (PP) on some properties of heat cured acrylic resin denture base material (PMMA). Materials and methods: One hundâ€red (100) prepared specimens were divided into five groups according to the tests, each group consisted of 20 specimens and t
A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro
... Show MoreMethods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and
... Show MoreThis research reports an error analysis of close-range measurements from a Stonex X300 laser scanner in order to address range uncertainty behavior based on indoor experiments under fixed environmental conditions. The analysis includes procedures for estimating the precision and accuracy of the observational errors estimated from the Stonex X300 observations and conducted at intervals of 5 m within a range of 5 to 30 m. The laser 3D point cloud data of the individual scans is analyzed following a roughness analysis prior to the implementation of a Levenberg–Marquardt iterative closest points (LM-ICP) registration. This leads to identifying the level of roughness that was encountered due to the range-finder’s limitations in close
... Show MoreDairy wastewater generally contains fats, lactose, whey proteins, and nutrients. Casein precipitation causes the effluent to decompose into a dark, strong-smelling sludge. Fluid waste contains soluble organic matter, suspended solids, and gaseous organic matter, which cause undesirable taste and smell, grant tone and turbidity, and advance eutrophication, which plays an essential role in increasing biological oxygen demand (BOD) in water. It also contains detergents and disinfecting agents from the rinses and washing processes, which increase the need for chemical oxygen (COD). One of the characteristics of dairy effluents is their relatively high temperature, high organic contents, and wide pH range, so the discharge of wastewater into
... Show MoreThe solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, i
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