Effect of the Porous Skeletal Iron Structure on the Infiltration of Aluminum Melts

Powder Metallurgy and Metal Ceramics - The infiltration of aluminum melts into porous metal skeletons produced by powder metallurgy methods, including 3D printing, under a pressure gradient was...     

A Method of Transferring the Unit of Power of High-Intensity Laser Radiation

Measurement Techniques - A method is proposed for transferring the unit of mean power of laser radiation by means of measuring high-intensity power (kilowatts), with the possibility of constant...     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Pixel clustering for color image segmentation

Programming and Computer Software - Image segmentation using a hierarchical sequence of piecewise constant approximations that minimally differ from the original image in terms of the total squared...     

Modeling of diffusional limitations in styrene acrylonitrile random bulk copolymerization

Diffusional limitations (the gel, glass, and cage effects) are manifested in several bulk free radical homopolymerizations as well as in random copolymerizations. These are associated with decreases of several orders of magnitude of the rate constants of termination, propagation, and initiation (the initiator efficiency), respectively. These phenomena have been modeled earlier using the free volume theory for the diffusivities of primary radicals, macro‐radicals, and monomer molecules, and have been applied to homopolymerizations. In this study, a similar model is developed for random bulk copolymerizations. The parameters of the model are fitted using isothermal data on styrene acrylonitrile random copolymerization carried out in small ampoules. Thereafter, best‐fit global correlations have been developed for this system. This enables the model to be used for studying non‐isothermal copolymerizations, as well as for carrying out optimization of industrial reactors, where non‐isothermal conditions are a norm. POLYM. ENG. SCI., 55:2098–2110, 2015. © 2014 Society of Plastics Engineers