The sizing of the cooling system is one of the most crucial parts of the design of power electronics since it has a high impact on the overall performance of the packages as well as the lifetime of the chips. The high temperature causes irreversible damage and increases the cost for maintenances and substitutions. However, during the design of the package, some geometric constraints can occur, such as maximum height or width. Moreover, limitations about volume rate and fluid temperature must be taken into account. This work aims to create a tool that can automatize the design of the heat sink cooling system with geometric constraints. The analytical model can consider in-line and staggered configurations. In this study, a genetic algorithm is applied as the optimization algorithm in order to find a solution which respects the boundary and fluid constraints and minimize the heat sink volume. Numerical simulations for the resulted geometries have been performed to validate the tool. The results of the numerical simulations show an error between the numerical and the expected maximum temperature of the plate lower than 2% and 3% for in-line and staggered configuration, respectively. The model can be applied over a wide range of application, and it can be easily adapted to different material and different cooling liquid.

In this paper we describe an adaptive and multi-scale algorithm for the parsimonious fit of the corneal surface data that allows to adapt the number of functions used in the reconstruction to the conditions of each cornea. The method implements also a dynamical selection of the parameters and the management of noise. It can be used for the real-time reconstruction

The demand for raw materials to manufacture any product always seems to be highly dynamic and unpredictable in their market. Copious number of suppliers supplies the different amount of raw materials at different instants of time. The suppliers may/may not supply the required amount of raw materials to meet the demand at the demanded period. It is a difficult process to identify a supplier for every raw material who can satisfy the demand. Moreover, to keep every unit of raw material in the factory's warehouse, there is holding cost. So, an optimal instant of period has to be identified to purchase the raw material so that the holding cost can be minimized. These issues increase the complexity for the manufacturer in identifying the optimal suppliers and the optimal periods to purchase the raw materials. In this paper, an effective methodology based on Genetic Algorithm is proposed to identify the optimal suppliers as well as the periods to purchase the raw materials. The proposed methodology selects an optimal supplier for every raw material from a huge collection of suppliers and also it identifies the optimal periods from all the possible periods the supplier can supply. The proposed methodology is tested using a simulated dataset and the results are validated by comparing the holding cost and mean holding cost that are obtained when the optimal suppliers and the rest of the suppliers are selected, respectively. The results show that with the aid of the proposed methodology, the manufacturer can fulfill the demand of all the raw materials with minimum holding cost.

Typical steel deck-concrete slab floor systems used in multi-story steel construction require intermediate filler or support beams (14 in. or deeper) and are limited to span of 8-12 ft depending on deck depth. The goal of the research was to develop and validate innovative long span floor systems capable of spanning up to 30 ft with total depths up to 12 in. or less. Several long-span floor systems were conceived and considered. These floor systems were evaluated based on their ability to achieve certain performance objectives. To accomplish these objectives, the project has been conducted in four tasks. The first task focused on conducting a literature review and survey of existing long-span slab systems. This task was conducted to determine the state-of-art for existing floor systems in steel construction. It helped in identifying existing solutions that have been proposed or implemented in steel construction. The second task of the research focused on conceptual development and design of long span floor systems. A suite of different floor system types were developed and proposed. The systems were ranked by the researchers and an oversight committee based on their technical merit and potential to achieve the prescribed performance objectives. The systems were analyzed and designed using analytical tools and methods including the finite element method (FEM), numerical analysis, and existing design codes. Based on the rankings, floor systems were selected for further development and experimental validation. The third task for the research project focused on the experimental validation of the floor system candidates. The testing focused on three different aspects for the floor systems. The aspects included strength and serviceability characteristics at ambient temperature levels, the fundamental heat transfer of certain specimens, and the effects of combined mechanical and thermal loading. The fourth task focused on numerical investigations and analytical parametric studies of the long-span floor system candidates. Analysis methods were developed and used for structural evaluation and evaluation for floor vibrations. Three different systems were found to present merit as potential long span systems. Two used 7.5 in. deep steel decks acting composite with either a 2.5 in. or 3.5 in. concrete slab on top to achieve 30 ft spans with a 10 or 11 in. depth. The other modified existing steel deck-concrete slab systems with new type of self-shoring system to achieve 30 ft spans with a 12.5 in. depth.