Fluidized bed heat treatment of cast Al-Si-Cu-Mg alloys

The effects of fluidized bed heat treatment on the microstructural and mechanical properties of Al-Si-Cu-Mg cast alloys, namely, 354 and 319, were studied. The heating rate in fluidized beds (FBs) is greatervis-à-vis conventional electrical resistance furnaces (CFs). The high heating rate in FBs increases the kinetics of metallurgical phenomena such as Si fragmentation and spherodization during solution heat treatment, as well as the precipitation rate of phases such as Al₅Cu₂Mg₈Si₆ and Al₂Cu during aging. It is observed that the dissolution rate of phases such as Mg₂Si and Al₅Cu₂Mg₈Si₆ takes place very rapidly. The solution heat treatment of 319 alloy using FB results in complete dissolution of Mg₂Si and Al₅Cu₂Mg₈Si₆ particles within 45 minutes. However, for phases such as Al₂Cu and Ferich intermetallics, the dissolution rate is relatively slow. Even on prolonged solution heat treatment for 6 hours, these phases do not dissolve completely. It is observed that incomplete dissolution of the Al₂Cu phase does not significantly affect tensile properties of T4-treated alloys. The optimum solution heat-treatment time in FB for both 354 and 319 alloys is 45 minutes at 527 °C and 493 °C, respectively. Thermal analysis shows an exothermic peak owing to recrystallization and coarsening of eutectic grains during solution heat treatment. The high heating rate in FB causes this transformation to take place at a lower temperature than in CF. It is observed that the nucleation rate of Al₅Cu₂Mg₈Si₆ during aging in FB is greater than using CF. Thermal analysis of samples during the ramp-up stage while aging using FB did not show any phase transformation, while those using CF show two endothermic transformations, which are most likely due to the dissolution of GP zones or the co-cluster of solutes. Aging at 200 °C results in a greater number density of precipitates than those at 240 °C. The tensile strength of samples aged at 200 °C is greater than those aged at 240 °C, because the amount of precipitates formed at 200 °C is greater than that at 240 °C. The total heat-treatment time for T6 temper is less than 2 hours in FBs, which is a significant reduction in heat-treatment time, as well as energy consumption.     

Multiple exemplar-based facial image retrieval using independent component analysis.

In this paper, we design a content-based image retrieval system where multiple query examples can be used to indicate the need to retrieve not only images similar to the individual examples, but also those images which actually represent a combination of the content of query images. We propose a scheme for representing content of an image as a combination of features from multiple examples. This scheme is exploited for developing a multiple example-based retrieval engine. We have explored the use of machine learning techniques for generating the most appropriate feature combination scheme for a given class of images. The combination scheme can be used for developing purposive query engines for specialized image databases. Here, we have considered facial image databases. The effectiveness of the image retrieval system is experimentally demonstrated on different databases.     

Soft and Hard Adhesion

The force needed to pull a cylindrical stud from a soft elastomeric film depends on their elastic and geometric properties. For a rigid stud and a thick elastomeric film, the pull-off stress (σ) depends on the elastic modulus (E) of the film and the radius (a) of the stud as σ ∼ (E/a)^1/2 (soft adhesion). However, when the film is very thin, the pull-off stress is significantly higher than the case with thick films, and its value depends on the elastic modulus and the thickness (h) of the film as σ ∼ (E/h)^1/2 (hard adhesion). Here, we study the pull-off behavior of a soft cylindrical stud, one flat end of which is coated with a high modulus thin baseplate. As the flexural rigidity of this baseplate is varied, we observe the transition between the two types of adhesion. We present a simple physical interpretation of the problem, which could be of value in understanding various biofouling and adhesive situations.     

Social media assimilation in firms: Investigating the roles of absorptive capacity and institutional pressures

Firms are increasingly employing social media to manage relationships with partner organizations, yet the role of institutional pressures in social media assimilation has not been studied. We investigate social media assimilation in firms using a model that combines the two theoretical streams of IT adoption: organizational innovation and institutional theory. The study uses a composite view of absorptive capacity that includes both previous experience with similar technology and the general ability to learn and exploit new technologies. We find that institutional pressures are an important antecedent to absorptive capacity, an important measure of organizational learning capability. The paper augments theory in finding the role and limits of institutional pressures. Institutional pressures are found to have no direct effect on social media assimilation but to impact absorptive capacity, which mediates its influence on assimilation.     

Reconstruction Based Recognition of Scenes with Multiple Repeated Components

This paper proposes an invariance based recognition scheme for scenes with multiple repeated components. The scheme considers three component subsets which characterize the scene completely. Each such three component subset is reconstructed using single image based information. We have developed a mathematical framework for the projective reconstruction based on relative affine structure of each such three component building block. This is extended to the case when each of the components is a quadric. A set of projective invariants of three quadrics has also been obtained by us. Although the reconstruction scheme is general and applicable to all multiple repeated components, it requires the computation of infinite homography. The infinite homography and hence the reconstruction scheme are only image computable with the given information in the case of translational repetition. We therefore develop a recognition strategy for the specific case of translationally repeated quadrics. As a recognition strategy for scenes with multiple translationally repeated quadric components, we propose to compute and store invariant values for each such three component subsets. Experiments on real data have shown the applicability of this approach for recognition of aerial images of power plants. The discriminatory power of the invariants and the stability of the recognition results have also been experimentally demonstrated.     

Reconstruction-based recognition of scenes with translationallyrepeated quadrics

This paper addresses the problem of invariant-based recognition of quadric configurations from a single image. These configurations consist of a pair of rigidly connected translationally repeated quadric surfaces. This problem is approached via a reconstruction framework. A new mathematical framework, using relative affine structure, on the lines of Luong and Vieville (1996), has been proposed. Using this mathematical framework, translationally repeated objects have been projectively reconstructed, from a single image, with four image point correspondences of the distinguished points on the object and its translate. This has been used to obtain a reconstruction of a pair of translationally repeated quadrics. We have proposed joint projective invariants of a pair of proper quadrics. For the purpose of recognition of quadric configurations, we compute these invariants for the pair of reconstructed quadrics. Experimental results on synthetic and real images, establish the discriminatory power and stability of the proposed invariant-based recognition strategy. As a specific example, we have applied this technique for discriminating images of monuments which are characterized by translationally repeated domes modeled as quadrics     

Laser micro-welding of aluminum and copper with and without tin foil alloy

In this paper continuous laser welding of two dissimilar materials, aluminum and copper, was investigated. The aluminum and the copper utilized were Al3003-H14 and Cu110-H00, respectively. Two different sets of samples were laser welded; one in which a filler material, tin foil alloy (S-bond 220), was sandwiched between the aluminum and the copper and another set in which the aluminum and copper were directly welded without any filler. The foil alloy was utilized to enhance the compatibility of the two metals; aluminum and copper, reducing the brittleness of the intermetallic compound that may form and, subsequently, enhance the mechanical properties. The welding was carried out using an IPG 500 SM fiber laser. The length of the laser joint produced was 20 mm and the width was about 200 μm. The strength of the joint was evaluated by conducting the lap shear stress test. Samples in which filler foil was used exhibited a better performance in the lap shear stress test (an average of 780 N) than the samples without tin foil (an average of 650 N). The improvement in the lap shear test could be attributed to the positive effects of the filler on enhancing the compatibility of the intermetallic compound formed via diffusion. The fracture surface of both types of joints (with and without filler) was characterized using scanning electron microscope equipped with energy-dispersive X-ray (EDAX). To understand the failure initiation and propagation of the samples under tension, a finite element (FE) model was developed for the samples created with no filler material. The failure mechanism predicted from the FE model matches reasonably well with the experimental observations from EDAX analysis.     

Effect of Heat Treatment, Pre-stress and Surface Hardening on Fracture Toughness of Micro-Alloyed Steel

Micro-alloyed steels are being increasingly accepted by industry in various fields of application and are available with a wide variety of microstructures. Extensive literature is available on their microstructure-property relationships. The superior mechanical properties of micro-alloyed steels are caused by fine-grained microstructures and precipitation of micro-alloying elements such as V, Ti and Nb that led to an improvement in yield strength, in the product of tensile strength and total elongation and in Charpy V-notch impact energy as well. The microstructural changes caused by heat treatment or residual stress state caused by surface hardening or mechanical means may influence the fracture toughness of these micro-alloyed steels. It is in this context that the present work begins with experimental determination of quasi-static initiation fracture toughness (J _1c) of low carbon (0.19%) micro-alloyed steel in as-rolled condition without any heat treatment. The study further explores the effect of normalizing, shot-peening and cyaniding followed by shot-peening on fracture toughness of as-rolled steel under study. The normalizing heat treatment, shot-peening and cyaniding followed by shot-peening—each indicates a positive influence on initiation fracture toughness. Results, when compared, show that cyaniding followed by shot-peening have led to a 2.7 times increase in J _1c. Cyaniding followed by shot-peening may therefore be considered as having the most positive influence on initiation fracture toughness in as-rolled condition for the type of micro-alloyed steel under study. Although initiation fracture toughness is in general known to decrease with increase in yield strength in LEFM arena, the micro-alloyed steel under study when normalized displayed simultaneous improvement in yield strength and J _1c. All these observed effects of normalizing, shot-peening and cyaniding on initiation fracture toughness (elastic-plastic fracture mechanics) were explained on the basis of microstructural study and stress depth profiles.     

Evolution of particle metrics in a buoyant aerosol cloud from explosive releases

Abstract

The detonation of high explosive (HE) material generates a cloud containing a high concentration of detonation products in the form of aerosol particles and gases. Modeling and simulation of aerosol metrics in an explosive cloud is a complex problem as it involves various processes such as chemical reaction, nucleation, volume expansion, and coagulation. Several models have been developed to study the atmospheric dispersion of these detonation products, but very few or no model is available to study the evolution of aerosol metrics at the early stage. In this work, we present a numerical model to simulate the temporal evolution of aerosol metrics in an expanding cloud by coupling transient thermodynamic properties with important microphysical processes. To illustrate the application, the numerical model is applied to a typical HE, and the aerosol particle properties such as size distribution, number concentration, and average size are estimated from the numerical results. These results will provide the essential input conditions for atmospheric dispersion models to estimate the atmospheric concentration and deposition of aerosol particles.

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