Evaluation of Process Capability in Gas Carburizing Process to Achieve Quality through Limit Design Concept

NUMEROUS INDUSTRIAL APPLICATIONS requirea hard wear-resistant surface called the case,and arelatively soft,tough inside called the core.There arefive principal methods of case hardening:?Carburizing?Nitriding?Cyaniding or carbonitriding?Flame hardening?Induction hardeningThe first three methods change the chemicalcomposition,carburizing by the addition of carbon,nitriding by the addition of nitrogen and cyaniding bythe addition of both carbon and nitrogen.The last twomethods do n…     

Analysis on Phase Transformation (ATP) Using Computational Thermal Principles (CTP)

COMPUTER ANALYSIS is a method of computerapplication that is expected by heat treaters to yieldbetter results.Quenching is an integral part of industrialheat treatment processes for steels and provides ameans by which the mechanical properties of steel canbe controlled.During quenching,the steel is typicallycooled from above the austenizing temperature anddepending upon the temperature field developed withinthe material,different types of phase transformationsoccur which result in variet…     

Supervised learning of large perceptual organization: graphspectral partitioning and learning automata

Perceptual organization offers an elegant framework to group low-level features that are likely to come from a single object. We offer a novel strategy to adapt this grouping process to objects in a domain. Given a set of training images of objects in context, the associated learning process decides on the relative importance of the basic salient relationships such as proximity, parallelness, continuity, junctions, and common region toward segregating the objects from the background. The parameters of the grouping process are cast as probabilistic specifications of Bayesian networks that need to be learned. This learning is accomplished using a team of stochastic automata in an N-player cooperative game framework. The grouping process, which is based on graph partitioning is able to form large groups from relationships defined over a small set of primitives and is fast. We statistically demonstrate the robust performance of the grouping and the learning frameworks on a variety of real images. Among the interesting conclusions is the significant role of photometric attributes in grouping and the ability to form large salient groups from a set of local relations, each defined over a small number of primitives     

Thermo-mechanical model with adaptive boundary conditions for friction stir welding of Al 6061

Thermo-mechanical simulation of friction stir welding can predict the transient temperature field, active stresses developed, forces in all the three dimensions and may be extended to determine the residual stress. The thermal stresses constitute a major portion of the total stress developed during the process. Boundary conditions in the thermal modeling of process play a vital role in the final temperature profile. The heating and cooling rates with the peak temperature attained by the workpiece determine the thermal stress. Also, predicting realistic peak temperature becomes important as the operating temperature at the interface of tool-workpiece is very close to the solidus temperature of the aluminum workpiece.The convection heat-transfer coefficients of the surfaces exposed to air can be theoretically determined using Newton's law of cooling. Contact conductance depends on the pressure at the interface and has a non-uniform variation. The actual pressure distribution along the interface is dependent on the thermal stress from local temperature and non-linear stress–strain state. Therefore, applying an adaptive contact conductance can make the model more robust for process parameter variations.A finite element thermo-mechanical model with mechanical tool loading was developed considering a uniform value for contact conductance and used for predicting the stress at the workpiece and backplate interface. This pressure distribution contours are used for defining the non-uniform adaptive contact conductance used in the thermal model for predicting the thermal history in the workpiece. The thermo-mechanical model was then used in predict stress development in friction stir welding.     

Study of defect levels in CdTe using thermoelectric effect spectroscopy

We have studied the defect levels in as grown and post growth processed cadmium telluride (CdTe) using thermoelectric effect spectroscopy (TEES) and thermally stimulated current (TSC) techniques. We have extracted the thermal energy (E_th) and trapping cross section (σ_th) for the defect levels using the initial rise and variable heating rate methods. We have identified 10 different defect levels in the crystals. Thermal ionization energy values obtained experimentally were compared to theoretical values of the transition-energy levels of intrinsic and extrinsic defects and defect complexes in CdTe determined by first-principles band-structure calculations. On the basis of this comparison, we have associated the observed ionization levels with various native defects and impurity complexes.     

Isomerization and Decomposition of Chloromethylacetylene

The isomerization and thermal decomposition of chloromethylacetylene (CMA) has been studied with two shock tube techniques. The first experiment (Jerusalem) utilizes single-pulse shock tube methods to measure the isomerization rate of CMA to chloroallene. In addition, equilibrium constants can be estimated at ∼1200 K. The second experiment (Argonne) monitors Cl-atom formation at temperatures above ∼1150 K. Absolute yield measurements have been performed over the 1200–1700 K range and indicate that two decomposition channels contribute to CMA destruction, namely, Cl fission and HCl elimination. The results show that the branching fraction between processes is temperature dependent. Therefore, direct Cl-atom fission is accompanied by molecular elimination, undoubtedly giving HCl and one or more isomers of C₃H₂. MP2 6–31G(d,p) ab initio electronic structure calculations have been used to determine vibration frequencies and moments of inertia for three C₃H₃Cl isomers. Using these quantities, the experimental equilibrium constants required that ΔH⁰₀(CH₂Cl–C≡CH ⇌ CHCl=C=CH₂) = −;0.24 kcal mole⁻¹. A potential energy surface pertinent to the present system has been constructed, and RRKM calculations have been carried out in order to explain the isomerization rates. The isomerization data can be explained with E₀ = 52.3 kcal mole⁻¹ and 〈ΔE_down〉 = 225 cm⁻¹. Subsequent semi-empirical Troe and RRKM-Gorin modeling of the Cl atom rate data require E₀ = (67.5 ± 0.5) kcal mole⁻¹ with a 〈ΔE_down〉 = (365 ± 90) cm⁻¹. This suggests a heat of formation for propargyl radicals of (79.0 ± 2.5) kcal mole⁻¹.     

A proof system for distributed processes

Summary A partial correctness proof system for Brinch Hansen’s Distributed Processes (DP) is presented. Two important aspects of the system are: Proofs of individual processes of a DP program are completely isolated from each other; in particular, no assumptions are allowed in the proof of one process about the behavior of the other processes. Secondly a process is characterized by its externally visible behavior, i.e. the sequence of interactions between this process and the other processes of the program. An example demonstrates the use of the system. This paper is an extended version of a paper presented at the Workshop on Logics of Programs, Brooklyn, New York, June 17–19, 1985 and was supported in part by the National Science Foundation under grant ECS-8404725.     

A proof system for distributed processes

Summary A partial correctness proof system for Brinch Hansen's Distributed Processes (DP) is presented. Two important aspects of the system are: Proofs of individual processes of a DP program are completely isolated from each other; in particular, no assumptions are allowed in the proof of one process about the behavior of the other processes. Secondly a process is characterized by its externally visible behavior, i.e. the sequence of interactions between this process and the other processes of the program. An example demonstrates the use of the system.This paper is an extended version of a paper presented at the Workshop on Logics of Programs, Brooklyn, New York, June 17–19, 1985 and was supported in part by the National Science Foundation under grant ECS-8404725