Critical aspects of sinter-hardening of prealloyed Cr–Mo steel

In recent years, growing demand for greater mechanical properties of PM steel components with competitive fabrication cost has led to significant innovations in different fields of powder metallurgy. Recent research has been focused on reaching higher performance with lower cost. To this end, the possibility of combining the conventional sintering and post-sintering processes for a particular powder composition has been introduced. Sinter-hardening is a result of the research conducted along this line. Elimination of any secondary operation such as quench-hardening by incorporating it in the sintering process (i.e. sinter-hardening) is of great interest, as it will lead to lower processing costs and equal, if not higher mechanical performance. However, to ensure the desired mechanical properties of the final component and robustness of the performance, critical aspects of the sinter-hardening process should be rigorously studied.Hence with specific attention to a Cr–Mo steel powder (FL-5305), this study deals with the influence of density on cooling rate, the effect of different sintering temperatures (e.g. 1120 °C and 1250 °C) on austenite grain size and consequently, hardenability. The microstructure development in sinter-hardened FL-5305 material has been analyzed and predicted by means of the available literature for solid steel and also using the commercial software (JMatPro 5.0) for materials assessment based on thermodynamic and kinetics modeling. Finally, inaccurate carbon control and its adverse impact on excessive formation of cementite have been addressed.     

Near critical carbon dioxide extraction of Anise (Pimpinella Anisum L.) seed: Mathematical and artificial neural network modeling

In the current study, two models for estimating essential oil extraction yield from Anise, at high pressure condition, were used: mathematical modeling and artificial neural network (ANN) modeling. The extractor modeled mathematically using material balance in both fluid and solid phases. The model was solved numerically and validated with experimental data. Since the potential of near critical extraction is of consider able economic significance, a multi-layer feed forward ANN has been presented for accurate prediction of the mass of extract at this region of extraction. According to the network's training, validation and testing results, a three layer neural network with fifteen neurons in the hidden layer is selected as the best architecture for accurate prediction of mass of extract from Anise seed. Finally, the influence of pressure and solvent flow rate on the extraction kinetics was studied using ANN model and the optimum pressure range has been determined.     

Tung oil: An autonomous repairing agent for self-healing epoxy coatings

The capability of the encapsulated Tung oil was investigated as a scratch healing agent for self-healing coatings. Encapsulation of Tung oil with urea–formaldehyde shell was carried out by in situ polymerization. Before the mechanical agitation of microcapsules into epoxy resin, their characteristics were evaluated by scanning electron microscope (SEM) and Fourier transform infrared spectroscopy (FTIR). Released Tung oil from ruptured microcapsules healed the artificial scratch in the coating matrix successfully. Corrosion resistance of healed area was evaluated by electrochemical impedance spectroscopy (EIS) and immersion test; and the results were compared with neat epoxy coating.     

Effect of fiber angle on LYP steel shear walls behavior简

Steel shear wall（SSW） was properly determined using numerical and experimental approaches.The properties of SSW and LYP（low yield point） steel shear wall（LSSW） were measured.It is revealed that LSSW exhibits higher properties compared to SSW in both elastic and inelastic zones.It is also concluded that the addition of CFRP（carbon fiber reinforced polymers） enhances the seismic parameters of LSSW（stiffness,energy absorption,shear capacity,over strength values）.Also,stress values applied to boundary frames are lower due to post buckling forces.The effect of fiber angle was also studied and presented as a mathematical equation.     

A model for stress-dependence of apparent permeability in nanopores of shale gas reservoirs

Predicting long-term production from gas shale reservoirs is a challenging task due to changes in effective stress and permeability during gas production. Unlike coal, the variation of sorbing gas permeability with pore pressure in shale does not always feature a biphasic trend under a constant confining pressure. The present contribution demonstrates that the biphasic dependence of permeability on pore pressure depends on a number of physical and geometrical factors, each with a distinct impact on gas permeability. This includes pore size, adsorption isotherm, and the variation of gas viscosity with pore pressure. A single-capillary model is proposed for the apparent permeability of real gas in shale. Results indicate that the biphasic relation between apparent permeability and pore pressure is prevalent when the sorbing gas flows in sufficiently small pores. In addition, the effects of sorption isotherm and internal resistance of nonideal gas to flow cannot be ignored.     

Thinned-ECOC ensemble based on sequential code shrinking

Error-correcting output coding (ECOC) is a strategy to create classifier ensembles which reduces a multi-class problem into some binary sub-problems. A key issue in designing any ECOC classifier refers to defining optimal codematrix having maximum discrimination power and minimum number of columns. This paper proposes a heuristic method for application-dependent design of optimal ECOC matrix based on a thinning algorithm. The main idea of the proposed Thinned-ECOC method is to successively remove some redundant and unnecessary columns of any initial codematrix based on a metric defined for each column. As a result, computational cost of the ensemble is reduced while preserving its accuracy. Proposed method has been validated using the UCI machine learning database and further applied to a couple of real-world pattern recognition problems (the face recognition and gene expression based cancer classification). Experimental results emphasize the robustness of Thinned-ECOC in comparison with existing state-of-the-art code generation methods.     

A biased‐randomized iterated local search for the distributed assembly permutation flow‐shop problem

Modern production systems require multiple manufacturing centers—usually distributed among different locations—where the outcomes of each center need to be assembled to generate the final product. This paper discusses the distributed assembly permutation flow‐shop scheduling problem, which consists of two stages: the first stage is composed of several production factories, each of them with a flow‐shop configuration; in the second stage, the outcomes of each flow‐shop are assembled into a final product. The goal here is to minimize the makespan of the entire manufacturing process. With this objective in mind, we present an efficient and parameter‐less algorithm that makes use of a biased‐randomized iterated local search metaheuristic. The efficiency of the proposed method is evaluated through the analysis of an extensive set of computational experiments. The results show that our algorithm offers excellent performance when compared with other state‐of‐the‐art approaches, obtaining several new best solutions.     

Low-power high-speed interconnection networks in NOC using multi-valued current-mode techniques

With the fast developments and growth of electronic applications and a great demand for increasing the speed of processors, VLSI circuits and on-chip interconnections the ＂Networks-On-Chip＂ （NOC） is the best solution for ＂System-On-Chip＂ （SOC）. The most fundamental part of networks On-Chip is the On-Chip interconnection. The model presented in this article describes the method of sending data on On-Chip interconnection by using a current-mode multi-valued logic instead of voltage-mode in order to increase speed and reduce the number of interconnection wires.     

Perspectives on management theory’s application in the internet of things research

Information Systems and e-Business Management - The growing use of the internet of things (IoT) has provided businesses with a new opportunity. This study performed a systematic literature review...     

An efficient and stable method to cluster software modules using ant colony optimization algorithm

The Journal of Supercomputing - Software evolution is a natural phenomenon due to the changing requirements. Understanding the program structure is a significant and complicated factor in...