Precipitation behavior of σ phase in fusion zone of dissimilar stainless steel welds during multi-pass GTAW process

The purpose of this study is to investigate the precipitation characteristics of σ phase in the fusion zone of stainless steel welds at various welding passes during a tungsten are welding (GTAW) process. The morphology, quantity, and chemical composition of the δ-ferrite and σ phase were analyzed using optical microscopy (OM), a ferritscope (FS), a X-ray diffractometer (XRD), scanning electron microscopy (SEM), an electron probe micro-analyzer (EPMA), and a wavelength dispersive spectrometer (WDS), respectively. Massive δ-ferrite was observed in the fusion zone of the first pass welds during welding of dissimilar stainless steels. The σ phase precipitated at the inner δ-ferrite particles and decreased δ-ferrite content during the third pass welding. The σ and δ phases can be stabilized by Si element, which promoted the phase transformation of σ→ϱ+λ₂ in the fusion zone of the third pass welds. It was found that the σ phase was a Fe−Cr−Si intermetallic compound found in the fusion zone of the third pass welds during multi-pass welding.     

A Survey on the Numerics and Computations for the Landau-Lifshitz Equation of Micromagnetism

The Landau-Lifshitz (LL)equation of micromagnetism governs rich variety of the evolution of magnetization patterns in ferromagnetic media. This is due to the complexity of physical quantities appearing in the LL equation. This complexity causes also an interesting mathematical properties of the LL equation: nonlocal character for some quantities,nonconvex side-constraints, strongly nonlinear terms. These effects influence also the numerical approximations. In this work, recent developments on the approximation of weak solutions, together with the overview of well-known methods for strong solutions,are addressed. Author is supported by the Fund for Scientific Research - Flanders FWO (Belgium).     

Intelligent copyright protection system using a matching video retrieval algorithm

Many video service sites headed by YouTube know what content requires copyright protection. However, they lack a copyright protection system that automatically distinguishes whether uploaded videos contain legal or illegal content. Existing protection techniques use content-based retrieval methods that compare the features of video. However, if the video encoding has changed in resolution, bit-rate or codec, these techniques do not perform well. Thus, this paper proposes a novel video matching algorithm even if the type of encoding has changed. We also suggest an intelligent copyright protection system using the proposed algorithm. This can serve to automatically prevent the uploading of illegal content. The proposed method has represented the accuracy of 97% with searching algorithm in video-matching experiments and 98.62% with automation algorithm in copyright-protection experiments. Therefore, this system could form a core technology that identifies illegal content and automatically excludes access to illegal content by many video service sites.     

A novel dynamic pricing scheme for contributing peers in the VoD system

In this paper we have proposed a dynamic pricing scheme for the contributing peers in the Video on Demand (VoD) system. The scheme provides an effective mechanism to maximize the profit through the residual resources of the contributing peers. A utilization function is executed for each contributing peer to estimate the utility factor based on the parameters such as initial setup cost, holding cost, chaining cost and salvage cost. In this paper, we urge an effective dynamic pricing algorithm that efficiently utilizes a range of parameters with a varying degree of complexity. The key findings of the algorithm are (i) each contributing peers are benefitted by the monetary based on its resource contributions to the VoD system and (ii) a high degree of social optimum is established by proficiently aggregating the contributing peer’s resources with the overall resources of the VoD system. We validate our claim by simulating the proposed dynamic pricing scheme with other standard pricing schemes such as altruism, cost model and game theory perspective. The result of our dynamic pricing scheme shows the best utility factor than other standard pricing schemes.     

Multidisciplinary optimization of gas-quenching process

Distortion as a result of the quenching process is predominantly due to the thermal gradient and phase transformations within the component. Compared with traditional liquid quenching, the thermal boundary conditions during gas quenching are relatively simple to control. By adjusting the gas-quenching furnace pressure, the flow speed, or the spray nozzle configuration, the heat-transfer coefficients can be designed in terms of both the component geometry and the quenching time. The purpose of this research is to apply the optimization methodology to design the gas-quenching process. The design objective is to minimize the distortion caused by quenching. Constraints on the average surface hardness, and its distribution and residual stress are imposed. The heat-transfer coefficients are used as design variables. DEFORM-HT is used to predict material response during quenching. The response surface method is used to obtain the analytical models of the objective function and constraints in terms of the design variables. Once the response surfaces of the objective and constraints are obtained, they are used to search for the optimum heat-transfer coefficients. This process is then used instead of the finite-element analysis. A one-gear blank case study is used to demonstrate the optimization scheme.     

Improved corrosion protection of aluminum alloys by electrodeposited silanes

Organofunctional silanes recently have emerged as outstanding, environmentally friendly corrosion protectors for metal substrates, compared with conventional chromate treatments. A simple immersion technique is typically used to coat the metal surface with silane films. However, the thickness and uniformity of the films are uncontrolled in this process. This paper proposes a new deposition technique for the silane films on the metal surface, i.e., by electrodeposition. Hydrolyzed silanes are water-soluble, ionized molecules, so they can be deposited on metals by electrodeposition. Various combinations of silane mixtures were tested at different voltages, pH values, bath concentrations, and exposure times on panels of alloy aluminum and mirror-polished ferro-plate. The surface structure was characterized by scanning electron microscopy (SEM) and ellipsometry. The resistance of the film to corrosion was investigated by direct current (DC) polarization and electrochemical impedance spectroscopy (EIS) techniques. Electrodeposition results in a more organized and uniform film with fewer pores, compared with immersed or dipped films. This paper was presented at the 2nd International Surface Engineering Congress sponsored by ASM International, on September 15–17, 2003, in Indianapolis, Indiana, and appears on pp. 320–26 of the Proceedings.     

The distribution of grain boundary planes in polycrystals

During the last ten years, techniques have been developed to measure the distribution of grain boundaries in polycrystals as a function of both lattice misorientation and grain boundary plane orientation. This paper presents a brief overview of the techniques used for these measurements and the principle findings of studies implementing these techniques. The most significant findings are that grain boundary plane distributions are anisotropic, that they are scale invariant during normal grain growth, that the most common grain boundary planes are those with low surface energies, that the grain boundary populations are inversely correlated with the grain boundary energy, and that the coincident site lattice number is a poor predictor of the grain boundary energy and population.     

Preparation of Protein-Stabilized β-Carotene Nanodispersions by Emulsification–Evaporation Method

This work was initiated to prepare protein-stabilized β-carotene nanodispersions using emulsification–evaporation. A pre-mix of the aqueous phase composed of a protein and hexane containing β-carotene was subjected to high-pressure homogenization using a microfluidizer. Hexane in the resulting emulsion was evaporated under reduced pressures, causing crystallization and precipitation of β-carotene inside the droplets and formation of β-carotene nanoparticles. Sodium caseinate (SC) was the most effective emulsifier among selected proteins in preparing the nanodispersion, with a monomodal β-carotene particle-size distribution and a 17-nm mean particle size. The results were confirmed by transmission-electron microscopy analysis. SC-stabilized nanodispersion also had considerably high ζ-potential (−27 mV at pH 7), suggesting that the nanodispersion was stable against particle aggregation. Increasing the SC concentration decreased the mean particle size and improved the polydispersity of the nanodispersions. Nanodispersions prepared with higher β-carotene concentrations and higher organic-phase ratios resulted in larger β-carotene particles. Although increased microfluidization pressure did not decrease particle size, it did improve the polydispersity of the nanodispersions. Repeating the microfluidization process at 140 MPa caused the nanodispersions to become polydisperse, indicating the loss of emulsifying capacity of SC due to protein denaturation.     

Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies.