Optimal design of laser solid freeform fabrication system and real-time prediction of melt pool geometry using intelligent evolutionary algorithms

With the rapid growth of laser applications and the introduction of high efficiency lasers (e.g. fiber lasers), laser material processing has gained increasing importance in a variety of industries. Among the applications of laser technology, laser cladding has received significant attention due to its high potential for material processing such as metallic coating, high value component repair, prototyping, and even low-volume manufacturing. In this paper, two optimization methods have been applied to obtain optimal operating parameters of Laser Solid Freeform Fabrication Process (LSFF) as a real world engineering problem. First, Particle Swarm Optimization (PSO) algorithm was implemented for real-time prediction of melt pool geometry. Then, a hybrid evolutionary algorithm called Self-organizing Pareto based Evolutionary Algorithm (SOPEA) was proposed to find the optimal process parameters. For further assurance on the performance of the proposed optimization technique, it was compared to some well-known vector optimization algorithms such as Non-dominated Sorting Genetic Algorithm (NSGA-II) and Strength Pareto Evolutionary Algorithm (SPEA 2). Thereafter, it was applied for simultaneous optimization of clad height and melt pool depth in LSFF process. Since there is no exact mathematical model for the clad height (deposited layer thickness) and the melt pool depth, the authors developed two Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to estimate these two process parameters. Optimization procedure being done, the archived non-dominated solutions were surveyed to find the appropriate ranges of process parameters with acceptable dilutions. Finally, the selected optimal ranges were used to find a case with the minimum rapid prototyping time. The results indicate the acceptable potential of evolutionary strategies for controlling and optimization of LSFF process as a complicated engineering problem.     

A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models.     

Hybrid cascode compensation with feedforward stage for high-speed area-efficient three-stage CMOS amplifiers

Hybrid cascode feedforward compensation (HCFC) is proposed for low-power area-efficient three stage amplifiers driving large capacitive loads. With no overhead in power or area, the total compensation capacitor is divided and shared between two internal high-speed loops instead of solely one loop as is common in prior art. Detailed analysis of HCFC shows significant improvement in terms of stability and bandwidth. This is verified for a 1.2-V amplifier driving a 500-pF capacitive load in 90-nm CMOS technology, where HCFC reduces the total capacitor size and improves the gain-bandwidth by at least 30 and 40 %, respectively, compared to the prevailing schemes.     

Dendrigraft with citric acid on acrylonitrile/acrylic acid copolymer electrospun fibres

Acrylonitrile/acrylic acid copolymers were synthesized with different mole fractions (1, 2, 5 and 10 mol%) of acrylic acid (AA) in the feed by aqueous suspension polymerization, and bead‐free fibres (295–375 nm in diameter) were made from the copolymers in dimethylformamide solutions by electrospinning. In a heterogeneous system containing electrospun fibre mats, dendritic molecules were grown by reaction between carboxylic acid of AA and –OH groups of citric acid activated by dicyclohexylcarbodiimide. The products were analysed using ¹H NMR, ¹³C NMR and Fourier transform infrared spectroscopies, density determination, scanning electron microscopy, optical microscopy, differential scanning calorimetry and pH response properties. With decreasing AA content, the isotacticity of the copolymers decreases with a more random distribution of the co‐monomers which leads to higher percentage conversions of dendrigraft due to reduced steric hindrance. On the formation of dendrigraft, the percentage conversion of the reactions decreases with an increase of generation number and AA content. A reduction of density for the first generation and then an increase with increasing generation are observed. During oxidation stabilization of fibres with a decrease of AA content and an increase in generation number, the amount of liberated heat increases. Fibres containing more carboxylic groups show significantly greater amounts of swelling/de‐swelling in basic and acidic media, respectively. To be used as nanocarbon fibre precursors, or as active particles for loading with guest molecules, or as pH actuators, the first generation of dendrigrafted fibres are expected to have the greatest potential among the various samples examined. © 2013 Society of Chemical Industry     

SOLUTION OF POPULATION BALANCE EQUATIONS IN EMULSION POLYMERIZATION USING METHOD OF MOMENTS

In this work, the method of moments is used for solution of population balance equations appearing in modeling of emulsion polymerization (EP). The zero-one model without coagulation effect and the pseudo-bulk model including coagulation effect are investigated as two common approaches for modeling EP processes. The fixed quadrature method is used to close the set of moment equations, and the maximum entropy approach is applied to reconstruct the particle size distribution from a finite number of its moments. Comparing the results with those obtained by the high-precision finite volume technique indicates that, despite the low computational load of the moment method, it has an acceptable accuracy. These features support use of the moment technique for other applications such as on-line control or optimization in particulate processes.     

Iron oxide/gold nanoparticles‐decorated reduced graphene oxide nanohybrid as the thermo‐radiotherapy agent

The main focus of the current study is the fabrication of a multifunctional nanohybrid based on graphene oxide (GO)/iron oxide/gold nanoparticles (NPs) as the combinatorial cancer treatment agent. Gold and iron oxide NPs formed on the GONPs via the in situ synthesis approach. The characterisations showed that gold and iron oxide NPs formed onto the GO. Cell toxicity assessment revealed that the fabricated nanohybrid exhibited negligible toxicity against MCF‐7 cells in low doses (<50 ppm). Temperature measurement showed a time and dose‐dependent heat elevation under the interaction of the nanohybrid with the radio frequency (RF) wave. The highest temperature was recorded using 200 ppm concentration nanohybrid during 40 min exposure. The combinatorial treatments demonstrated that the maximum cell death (average of 53%) was induced with the combination of the nanohybrid with RF waves and radiotherapy (RT). The mechanistic study using the flow cytometry technique illustrated that early apoptosis was the main underlying cell death. Moreover, the dose enhancement factor of 1.63 and 2.63 were obtained from RT and RF, respectively. To sum up, the authors’ findings indicated that the prepared nanohybrid could be considered as multifunctional and combinatorial cancer therapy agents.Inspec keywords: radiation therapy, toxicology, gold, biomedical materials, nanofabrication, nanoparticles, iron compounds, cancer, nanomedicine, cellular biophysics, tumours, graphene compounds, biothermicsOther keywords: graphene oxide nanohybrid, combinatorial cancer treatment agent, cell toxicity assessment, MCF‐7 cells, dose‐dependent heat elevation, multifunctional cancer therapy agents, thermoradiotherapy agent, graphene oxide‐iron oxide‐gold nanoparticles, temperature measurement, radiofrequency wave, flow cytometry, time 40.0 min, CO‐FeO‐Au     

Constructing a block layout by face area

Solving the facility layout problems by graph theory consists of two stages. In the first stage, a planar graph that specifies desired adjacencies is obtained and in the second stage, a block layout is achieved from the planar graph. In this paper, we introduce face area as a new concept for constructing a block layout. Based on this idea, we present a new algorithm for constructing block layout from a maximal planar graph (MPG). This MPG must be generated from deltahedron heuristic. Constructed block layout by this algorithm satisfies all of adjacency and area requirements.     

A game equilibrium model of a retail electricity market with high penetration of small and mid-size renewable suppliers

Game theory has provided a practical tool to model players' strategic behavior in electricity markets, particularly as the world moves towards a more competitive market. A game theoretic approach can be used to find the clearing electricity price in a retail electricity market with a high penetration of small and mid-size renewable suppliers.     

A Novel Evolutionary-Based Cooperative Spectrum Sensing Mechanism for Cognitive Radio Networks

Cognitive radio (CR) is considered as a feasible intelligent technology for 4G wireless networks or self-organization networks and envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, one of the main concerns is to reliably sense the presence of primary users, to attain protection against harmful interference caused by the potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, genetic algorithm (GA) and particle swarm optimization (PSO) are investigated. An imperialistic competitive algorithm (ICA) is proposed to minimize error detection at the common soft data fusion (SDF) center for structurally centralized cognitive radio network (CRN). By using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed method is compared with other evolutionary algorithms, as well as other conventional deterministic, such as maximal ratio combining- (MRC-), modified deflection coefficient- (MDC-), normal deflection coefficient- (NDC-) based SDF schemes and OR-rule HDF based. MATLAB simulations confirm the superiority of the ICA-based scheme over the PSO-, GA-based and other conventional schemes in terms of detection performance. In addition, the ICA-based scheme also shows promising convergence and time running performance as compared to other iterative-based schemes. This makes ICA an adequate solution to meet real-time requirements.     

Outage Probability Based Robust Distributed Beam-Forming in Multi-User Cooperative Networks with Imperfect CSI

In this paper, a new robust problem is proposed for relay beamforming in relay system with stochastic perturbation on channels of multi user and relay network. The robust problem aims to minimize the transmission power of relay nodes while the imperfect channel information (CSI) injects stochastic channel uncertainties to the parameters of optimization problem. In the power minimization framework, the relays amplification weights and phases are optimized assuming the availability of Gaussian channel distribution. The power sum of all relays is minimized while the outage probability of the instantaneous capacity (or SINR) at each link is above the outage capacity (or SINR) for each user. The robust problem is a nonconvex SDP problem with Rank constraint. Due to the nonconvexity of the original problem, three suboptimal problems are proposed. Simulation and numerical results are presented to compare the performance of the three proposed solutions with the existing worst case robust method.