Localized Recrystallization in Cast Al-Si-Mg Alloy during Solution Heat Treatment: Dilatometric and Calorimetric Studies

During heat treatment, the work piece experiences a range of heating rates depending upon the sizes and types of furnace. When the Al-Si-Mg cast alloy is heated to the solutionizing temperature, recrystallization takes place during the ramp-up stage. The effect of heating rate on recrystallization in the A356 (Al-Si-Mg) alloy was studied using dilatometric and calorimetric methods. Recrystallization in as-cast Al-Si alloys is a localized event and is confined to the elasto-plastic zone surrounding the eutectic Si phase; there is no evidence of recrystallization in the center of the primary Al dendritic region. The size of the elasto-plastic zone is of the same order of magnitude as the Si particles, and recrystallized grains are observed in the elasto-plastic region near the Si particles. The coefficient of thermal expansion of Al is an order of magnitude greater than Si, and thermal stresses are generated due to the thermal mismatch between the Al phase and Si particles providing the driving force for recrystallization. In contrast, recrystallization in Al wrought alloy (7075) occurs uniformly throughout the matrix, stored energy due to cold work being the driving force for recrystallization in wrought alloys. The activation energy for recrystallization in as-cast A356 alloy is 127 KJ/mole. At a slow heating rate of 4.3 K/min, creep occurs during the heating stage of solution heat treatment. However, creep does not occur in samples heated at higher heating rates, namely, 520, 130, and 17.3 K/min.     

Context-based prefetch – an optimization for implementing objects on relations

When implementing persistent objects on a relational database, a major performance issue is prefetching data to minimize the number of round-trips to the database. This is especially hard with navigational applications, since future accesses are unpredictable. We propose the use of the context in which an object is loaded as a predictor of future accesses, where a context can be a stored collection of relationships, a query result, or a complex object. When an object O's state is loaded, similar state for other objects in O's context is prefetched. We present a design for maintaining context and for using it to guide prefetch. We give performance measurements of its implementation in Microsoft Repository, showing up to a 70% reduction in running time. We describe several variations of the optimization: selectively applying the technique based on application and database characteristics, using application-supplied performance hints, using concurrent database queries to support asynchronous prefetch, prefetching across relationship paths, and delayed prefetch to save database round-trips. Received May 3, 2000 / Accepted October 26, 2000     

Effect of Heat Input on Microstructural Changes and Corrosion Behavior of Commercially Pure Titanium Welds in Nitric Acid Medium

Commercially pure titanium (Ti) has been selected for the fabrication of dissolver for the proposed fast reactor fuel reprocessing plant at Kalpakkam, India. In the present investigation, microstructural changes and corrosion behavior of tungsten inert gas (TIG) welds of Ti grade-1 and grade-2 with different heat inputs were carried out. A wider heat affected zone was observed with higher heat inputs and coarse grains were observed from base metal toward the weld zone with increasing heat input. Fine and more equiaxed prior β grains were observed at lower heat input and the grain size increased toward fusion zone. The results indicated that Ti grade-1 and grade-2 with different heat inputs and different microstructures were insensitive to corrosion in liquid, vapor, and condensate phases of 11.5 M nitric acid tested up to 240 h. The corrosion rate in boiling liquid phase (0.60-0.76 mm/year) was higher than that in vapor (0.012-0.039 mm/year) and condensate phases (0.04-0.12 mm/year) of nitric acid for Ti grade-1 and grade-2, as well as for base metal for all heat inputs. Potentiodynamic polarization experiment carried out at room temperature indicated higher current densities and better passivation in 11.5 M nitric acid. SEM examination of Ti grade-1 welds for all heat inputs exposed to liquid phase after 240 h showed corrosion attack on the surface, exposing Widmanstatten microstructure containing acicular alpha. The continuous dissolution of the liquid-exposed samples was attributed to the heterogeneous microstructure and non-protective passive film formation.     

Optimal synthesis of refrigeration cycles and selection of refrigerants

The optimal synthesis of the refrigeration configuration and the selection of the best refrigerants that satisfy a set of process cooling duties at different temperatures is addressed. This approach simultaneously selects refrigerants and synthesizes refrigeration structures by minimizing a weighted sum of investment and operating costs. A superstructure representation considers the majority of refrigeration cycle features encountered in real complex multistage refrigeration cycles such as economizers, multiple refrigerants, and heat integration. A novel theoretical treatment of modeling representations and algorithmic improvements is introduced. Results, for example, involving multiple refrigerants, cooling loads, and heat sinks are obtained. Complex, nonintuitive topologies typically emerge as the optimal refrigeration configurations that are better than those obtained when refrigeration synthesis is performed after refrigerant selection.     

A multi-objective genetic algorithm approach to the design of cellular manufacturing systems

In this paper, a multi-objective integer programming model is constructed for the design of cellular manufacturing systems with independent cells. A genetic algorithm with multiple fitness functions is proposed to solve the formulated problem. The proposed algorithm finds multiple solutions along the Pareto optimal frontier. There are some features that make the proposed algorithm different from other algorithms used in the design of cellular manufacturing systems. These include: (1) a systematic uniform design-based technique, used to determine the search directions, and (2) searching the solution space in multiple directions instead of single direction. Four problems are selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method in designing the manufacturing cells.     

Non-Newtonian electromagnetic fluid flow through a slanted parabolic started Riga surface with ramped energy

The present study deals with the implications of non-Newtonian fluid via a slanted parabolic started surface with ramped energy. In addition, the characteristics of electrically conducting viscoelastic liquid moving across the Riga surface are investigated systematically, emphasized within the time-dependent concentration and temperature variations. The mathematical model is made possible by enforcing momentum and heat conservation principles in the format of partial differential equations (PDEs). Heat considerations are emphasized with respect to radiant heat influx. Similarity characteristics are leveraged to convert PDEs to ordinary differential equations. The Laplace transform method is used to find the exact solutions for the obtained differential configuration. The effect of flow on associated patterns is depicted graphically and with tables. Furthermore, fluctuation in relevant engineering parameters such as wall shear stress, temperature, and mass variability on the surface is measured. The range of parameters selected is as follows: $\psi [0.1-1]$, $Pr[0.71-10]$, $Sc[0.16-2.01]$, $Gr=Gc[5-20]$, $E[1-5]$, and $R[2-10]$. The analytical and numerical solutions are validated and in good agreement. It is worth reporting that the improved Hartmann number and thermal radiation values boost velocity dispersion and skin friction. As expected, respectively, energy and mass transfer rates are escalated with large values of Prandtl number and Schmidt number.     

Optimal design and development of a 2-DOF PKM-based machine tool

This paper presents multiobjective optimization of a typical 2-degree-of-freedom (DOF) parallel kinematic machine (PKM) tool that has only single DOF joints. Nondimensional indices, namely global stiffness index (GSI), global conditioning index (GCI), and workspace index, are considered as the objectives for optimization. The indices GSI and GCI depict the variation of stiffness and dexterity of PKM within the workspace. The leg length and distance between two rails on which actuators slide are treated as design variables as these greatly influence the characteristics of PKM. A multiobjective genetic algorithm (MOGA) approach is implemented in MATLAB to find an efficient solution to this complex optimization problem. Fitness function includes inverse kinematics equations, Jacobian and stiffness matrices to compute and optimize the nondimensional indices. First, the optimal value of each index is obtained by single-objective GA. To further improve the results, a hybrid function PATTERNSEARCH is used. This helps to select appropriate boundary conditions for MOGA. To obtain the optimal values of all the three indices, a multiobjective GA is carried out. The results are compared with a conventional exhaustive search method of optimization. The obtained results show that the use of MOGA enhances the quality of the optimization outcome. Secondly, a prototype has been designed and developed with the optimal dimensions. The actual workspace of the PKM and influence of leg collision on the workspace are studied. Finally, a preliminary experimentation was carried out. A comparison between PKM and the three-axis serial kinematic machine tool is presented.     

Selection of the optimal electrochemical machining process parameters using biogeography-based optimization algorithm

Electrochemical machining (ECM) has become one of the most potential and useful non-traditional machining processes because of its capability of machining complex and intricate shapes in high-strength and heat-resistant materials. For effective utilization of the ECM process, it is often required to set its different machining parameters at their optimal levels. Various mathematical techniques have already been proposed by past researchers to determine the optimal combinations of the different machining parameters of the ECM process. In this paper, the machining parameters of an ECM process and a wire electrochemical turning process are optimized using the biogeography-based optimization (BBO) algorithm. Both the single- and multi-response optimization models are considered. The optimization performance of the BBO algorithm is also compared with that of other population-based algorithms, e.g., genetic algorithm and artificial bee colony algorithm. It is observed that the BBO algorithm outperforms the others with respect to the optimal values of different process responses and computation time.