Performance evaluation of structural concrete using controlled quality coarse and fine recycled concrete aggregate

This paper presents the fresh, mechanical, and durability performance, of a structural concrete mix classified as C-1, by the Canadian Standards Association (CSA) made with controlled quality Recycled Concrete Aggregate (RCA). Five mixes with water-to-cementing material (w/cm) ratio of 0.40 were produced with various RCA contents and tested against two 0% RCA control mixes made with General Use (GU) cement, and General Use Limestone cement (GUL). The RCA contents in the mixes were 10%, 20%, and 30% by coarse aggregate volume replacement, as well as 10% and 20% fine and coarse (granular) aggregate volume replacement. All evaluated mixes met the specifications from the CSA for fresh, mechanical, and durability properties. The coarse RCA mixes performed better than the granular RCA mixes in terms of flexural and splitting tensile strengths, linear drying shrinkage, water sorptivity, and rapid chloride-ion permeability, where the test results were significantly affected by the ultra fines present in the granular RCA.     

Integrated circuit and system design for renewable energy inverters

This study proposes that a novel integrated circuit (IC) and system design for renewable energy inverters can harvest renewable energy to power direct current (DC) and alternating current (AC) loads. In addition, an intelligent synthesis and management tool is developed to design the proposed system and to judge the system’s operational maintenance decisions. Finally, a renewable energy inverter’s information is posted to an online system. Users can obtain the proposed system’s information at any time and place. The accurate and superior performance of the proposed IC and system is confirmed by computer simulations and experimental results.     

Mechanical properties of a self-healing fibre reinforced epoxy composites

Inspired by biological systems in which damage triggers an autonomic healing response, a polymer composite material that can heal itself when cracked has been developed. In this work, compression and tensile properties of a self-healed fibre reinforced epoxy composites were investigated. Microencapsulated epoxy and mercaptan healing agents were incorporated into a glass fibre reinforced epoxy matrix to produce a polymer composite capable of self-healing. The self-repair microcapsules in the epoxy resin would break as a result of microcrack expansion in the matrix, and letting out the strong repair agent to recover the mechanical strength with a relative healing efficiency of up to 140% which is a ratio of healed property value to initial property value or healing efficiency up to 119% if using the healed strength with the damaged strength.     

Influence of pores arrangement on stability of photonic structures during sintering

Discrete Element Method (DEM) has been used for numerical investigation of sintering-induced structural deformations occurring in inverse opal photonic structures. The influence of the initial arrangement of template particles on the stability of highly porous inverse opal α-Al₂O₃ structures has been analyzed. The material transport, densification, as well as formation of defects and cracks have been compared for various case studies. Three different stages of defects formation have been distinguished starting with local defects ending with intrapore cracks. The results show that the packing of the template particles defined during the template self-assembly process play a crucial role in the later structural deformation upon thermal exposure. The simulation results are in very good agreement with experimental data obtained from SEM images and previous studies by ptychographic X-ray tomography.     

Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC

This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets.     

Investigations on grinding process of woven ceramic matrix composite based on reinforced fiber orientations

Fiber orientations play the decisive role in grinding process of woven ceramic matrix composites, but the influence of woven fibers in grinding process is not clear. This paper studies the surface quality and grinding force by comparing different woven surfaces. Through a series of experiments in optimized sampling conditions, we analyze characteristics of the material surface topography height, wave distribution and surface support properties in details. And we find some outstanding characteristics of the surface microstructure. We also study the influence of grinding processing parameters on surface microstructure. The results show that machining surface which contains more parallel fibers is rougher and more keenness than gauss surface. Grinding wheel speed and depth of cut have great influence on surface topography and surface support properties. And it is discovered that grinding forces are also highly dependent on fiber orientations. The mechanism of the grinding phenomena is also analyzed in this paper according to knowledge of fracture mechanics and mechanical damage phenomenology. The research obtained will be an important technical support on improving the processing quality of woven ceramic matrix composites.     

A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.     

A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.     

New nanocomposite based on poly(lactic-co-glycolic acid) copolymer and magnetite. Synthesis and characterization

The study presents the preparation of the new magnetic nanocomposite based on PLGA and magnetite. The PLGA used to obtain the magnetic nanocomposites was synthesized by the copolymerization of lactic acid with glycolic acid, in the presence of tin octanoate [Sn(Oct)₂] as catalyst, by polycondensation procedure. Magnetite was obtained by co-precipitation from aqueous salt solutions FeCl₂/FeCl₃. The particles size of magnetite was 420 nm, and the saturation magnetization 62.78 emu/g, while the PLGA/magnetite nanocomposite size was 864 nm and the saturation magnetization 39.44 emu/g. The magnetic nanocomposites were characterized by FT-IR, DLS technique, SEM, VSM and simultaneous thermal analyses (TG–FTIR–MS). The polymer matrix PLGA acts as a shell and carrier for the active component, while magnetite is the component which makes targeting possible by external magnetic field manipulation. Based on the gases resulted by thermal degradation of PLGA copolymer, using the simultaneous analysis TG–FTIR–MS, a possible degradation mechanism was proposed.     

Characteristics and formation mechanism of porosities in CFRP during laser joining of CFRP and steel

An experimental investigation on the mechanism of porosity formation during the laser joining of carbon fiber reinforced polymer (CFRP) and steel is presented. The porosity morphology and distribution were characterized by optical and scanning electron microscopy, and the thermal pyrolysis behaviors were investigated by thermal analysis and designed back-side cooling experiments. The results show that there are two types of porosities in CFRP. Porosity I only appears when the heat input is more than 77.8 J/mm. It has a smooth inner wall and distributes near the bonding interface between CFRP and steel at the central area of melted zone, which is caused by gaseous products such as CO₂, NH₃, H₂O, and hydrocarbons produced by the pyrolysis of CFRP. Porosity II can be seen under all joining conditions. It has a rough inner wall and distributes far away from the bonding interface, concentrating at the final solidification locations. Porosity II is caused by the shrinkage of melted CFRP during solidification stage.