GA and ICA approaches to job rotation scheduling problem: considering employee’s boredom

This paper presents a new model dealing with the job rotation scheduling problem, which is less studied, focusing on human characteristics such as boredom. Existing literature on conceptualizing boredom shows that researchers evaluate boredom in terms of exposure to the same tasks. We developed it to “exposure to similar tasks” and defined its functionality based on the need of assigning jobs with more similarity to each worker in the smallest period of planning which lowers the external interruption effect on worker’s concentration. To address the imbalance between number of jobs and that of workers in many industrial settings, we developed a multi-period imbalance assignment model. The proposed model is to rotate workers during a given planning horizon such that the total cost including assignment and boring cost will be minimized. The applicability of the model is described by presenting some real cases and validated through solving several randomly produced test problems by using Lingo software. Two search algorithms, genetic algorithm (GA) and imperialist competitive algorithm (ICA), designed to conquer the algorithmic complexity of model and their parameters adjusted using Taguchi’s method were used. The efficiency of algorithms is shown, comparing it with Lingo computation times, and it is shown that ICA solutions have better quality than GA solutions as well.     

Ionic Liquid-Mediated Biopolymer Extraction from Coffee Fruit

Ionic liquids (ILs) are effective solvents for biomass. Refined cellulose is commonly used; however, recent interest has grown to consider woody and herbaceous biomass and industrial crop residues like fruit peels. Here, the authors report results on the dissolution and shaping of cotton and coffee fruit (cascara) in 1,8-diazabicyclo[5.4.0]undec-7-inium acetate ([DBUH][OAc]). Cascara is a high-volume, low-value crop residue that poses an environmental and economic burden in producer countries leading to a high-value proposition if recoverable. Fruit/ionic liquid solutions (0–15% w/w dissolved at 60 °C) were characterized with respect to biomass concentration and shaped into fibers and films coagulated in DI water and methanol. Rheology was assessed using parallel plate rheometry. Cotton/IL mixtures formed better fibers compared to cascara-based solutions, which required 2.6× more biomass in solution for viable fiber formation. At 10% loading, fibers could be produced from untreated coffee fruit with diameters ranging from 18–100 microns. Coffee fruit residues and their precipitated films show that both cellulose and lignin dissolve in pure [DBUH][OAc]. Chemical characterization of cascara and cascara films demonstrates the conveyance of high concentrations of lignin and extracts that result in weaker mechanical properties. Further purification of cascara is required for effective use in structural applications.     

Novel Linear Piezo-resistive Auxetic Meta-Sensors with Low Young's Modulus by a Core–Shell Conceptual Design and Electromechanical Modelling

Production of piezo-resistive auxetic sensors is usually carried out through mixing and coating methods. Although these methods are beneficial, Young's modulus of mixed sensors becomes high because of using a high percentage of sensing elements while the durability of coated sensors gets low due to the separation of sensing elements from the sensor surface. This article presents a new core–shell metamaterial model to address the mentioned problems. The shell and the core are produced of polydimethylsiloxane (PDMS) rubber and a mixture of PDMS/graphite powders (73.45 wt% graphite powders), respectively. A finite element model is developed via COMSOL software to predict the electromechanical behaviors of the created sensor and verified by an experimental study. Scanning electron microscope imaging is conducted to detect the separations of the graphite particles. The main important feature of this meta-sensor is to possess a linear sensitivity due to having zero Poisson's ratio. The advantage of this method is that Young's modulus of the sensor does not decrease (unlike the mixing method), and the sensor-coated particles do not separate from the sensor after a while (unlike the coating method). The introduced model has advantages that promote potential applications such as using sensory gloves to detect, for instance, human hand movements.     

Thermally Activated Aromatic Ionic Dopants (TA-AIDs) Enabling Stable Doping,Orthogonal Processing and Direct Patterning

Doping plays a critical role in organic electronics, and dopant design has been central in the development of functional and stable doping. In this study, there is departure from conventional molecular dopants and a new class of dopants are reported – aromatic ionic dopants (AIDs). AIDs consist of a pair of aromatic cation and anion that are responsible for molecular doping reaction and charge balancing separately. It is shown that the first AID made from cycloheptatrienyl (tropylium) cation and pentacyanocyclopentadienide anion (PCCp), abbreviated as T-PCCp, can function as an effective p-type dopant to dope polydioxythiophenes. Here, tropylium cation induces the doping reaction while the PCCp anion stabilizes the generated polarons and bipolarons. With T-PCCp, a highly doped (≈120 S/cm) and stable system is achieved up to 150 °C, an orthogonal (sequential)solution processing resulting from the immiscibility of the dopant and the polymer host, and a high-resolution direct micropatterning with laser writing resulted from a thermally activated doping process.     

Study on forcing schemes in the thermal lattice Boltzmann method for simulation of natural convection flow problems

The present study addresses the effect of various schemes for applying an external force term on the accuracy and performance of the thermal lattice Boltzmann method (LBM) for simulation of free convection problems. Herein, the forcing schemes of Luo, shifted velocity method, Guo, and exact difference method are applied by considering three velocity discrete models of D2Q4, D2Q5, and D2Q9. The accuracy and performance of these schemes are evaluated with the simulation of three natural convection problems, namely, free convection in a closed cavity, in a square enclosure with a hot obstacle inside, and the Rayleigh-Benard problem. The obtained results based on the present thermal LBM with different forcing schemes and velocity discrete models are compared with the existing experimental and numerical data in the literature. This comparison study indicates that imposing all employed forcing schemes leads to similar performance for the simulation of free convection problems studied at the middle range of Rayleigh numbers. It is found that the Luo forcing scheme is simple for implementation in comparison with the other three forcing schemes and provides the results with acceptable accuracy at moderate Rayleigh numbers. At higher Rayleigh numbers, however, the Guo scheme is not only numerically stable but a more precise forcing scheme in comparison with the other three methods. It is illustrated that employing the discrete velocity model of D2Q4 has more appropriate numerical stability along with less computational cost in comparison with two other discrete velocity models for simulation of natural convection heat transfer.     

Modification and optimization of benzene alkylation process for production of ethylbenzene

In this paper, an industrial ethylbenzene production unit has been simulated and the results are compared against five-day experimental data. According to prevailing unit condition, i.e. recycled ratio of benzene, benzene selectivity, and energy consumption, the unit is not working under its optimum conditions for minimum cost of ethylbenzene production. In the current design, high amount of benzene recycle (6:1) causes to have an additional cost due to fractionation of ethylbenzene from benzene. A new approach is proposed to modify the benzene alkylation process and reduce the unit's energy consumption. In the newly designed scheme, two double-bed alkylation reactors converted into four single-bed reactors. The amount of injected ethylene, alkylation reactors temperature, and recycled stream are regulated as adjustable parameters for the optimization of the process. In the modified process, the reflux ratio reduced to 1.87 and the benzene selectivity increased. The optimized process shows a considerable decrease in the unit's energy consumption in compare to the current process. Also, the mass fraction of ethylbenzene would reach to 99.12% of purity before entering to the transalkylation reactor for further purification. Therefore, if the presented purity is acceptable for the final application, the transalkylation reactor could be eliminated from the new design.     

Preparation of low-platinum-loading electrocatalysts using electroless deposition method for proton exchange membrane fuel cell systems

One promising preparative method that offers the potential for improved platinum (Pt) dispersion of electrocatalysts is electroless deposition (ED). In this study, the effects of multiwalled carbon nanotubes (MWCNTs) pretreatment and synthesis procedure on properties of the four catalysts, synthesized by ED method, have been considered. The results of energy-dispersive X-ray spectroscopy (EDS), X-ray dot-mapping, X-ray fluorescence (XRF) and cyclic voltammetry (CV) analyses showed that using palladium (Pd) precursor during two-step sensitization-activation coating procedure gives uniform Pt particles distribution on MWCNTs with low aggregation and high specific surface area (∼80 m² g⁻¹). In addition, to investigate the performance of the synthesized catalysts in experimental fuel cell system, thin-film method was used to fabricate the membrane electrode assemblies (MEAs). Obtaining the polarization curves for the fabricated MEAs (Pt loading ∼0.4 mg cm⁻²) and a commercial MEA (ElectroChem, Pt loading ∼1 mg cm⁻²) demonstrated that the catalyst prepared by two-step sensitization-activation coating procedure possesses a good performance despite of its lower Pt content.     

Biomass and lipid productivities of marine microalgae isolated from the Persian Gulf and the Qeshm Island

In this work, the screening of 147 microalgal strains from the Persian Gulf and the Qeshm Island (Iran) were done in order to choose the best ones, in terms of growth (biomass) rate and lipid content for biodiesel production. A methodology, combining experiments in lab-scale and pilot plant (open pond) used to produce and evaluate biomass and lipid productivity is presented for the systematic investigation of the potential of different microalgae species. The culture conditions, including photo flux (180 ??E m⁻² s⁻¹), photoperiod (12 h light/dark), temperature (25 °C), pH (≈8), air (carbon dioxide) and growth medium, were kept constant for all experiments. Microalgae were screened in two stages using optical density (for evaluation of biomass concentration) and Nile red and gas chromatography (for determination of lipid content and fatty acid fractions). In general, maximum specific growth rate and the maximum biomass productivity were obtained after 8-12-day culture. Nannochloropsis sp. and Neochloris sp. were selected from the marine microalgal culture collection, due to their high biomass (50 and 21.7 g L⁻¹, respectively) and oil content (52% and 46%, respectively). If the purpose is to produce biodiesel only from one species, Nannochloropsis sp. presented the most adequate fatty acid profile, namely linolenic and other polyunsaturated fatty acids. However, the microalgae Chlorella sp. can also be used if associated with other microalgal oils. In addition, selected strains could be potent candidates for commercial production in the open pond culture.     

On the self-scheduling of a power producer in uncertain trading environments

This work presents a scenario-based approach to the self-scheduling problem of a price taker power producer in a DA market. It concentrates on three categories of uncertainty including price, forced outage and generation reallocation and analyses their effects on the producer revenue. To tackle the uncertainties a set of price scenarios are so generated that their means and covariance matrix are the same as the base-case scenario. Forced outage and generation reallocation of generator for each price scenario are appropriately modeled through a probabilistic methodology. In this work Downside Risk (DR) is employed as the risk measure which quantifies the downside violations from a specified target. A risk-constrained self-scheduling problem is therefore formulated and solved as a mixed integer linear programming problem. Numerical results for a case study are discussed.     

Drivetrains on floating offshore wind turbines: lessons learned over the last 10 years

This paper presents lessons learned from own research studies and field experiments with drivetrains on floating wind turbines over the last ten years. Drivetrains on floating support structures are exposed to wave-induced motions in addition to wind loading and motions. This study investigates the drivetrain-floater interactions from two different viewpoints: how drivetrain impacts the sub-structure design; and how drivetrain responses and life are affected by the floater and support structure motion. The first one is linked to the drivetrain technology and layout, while the second question addresses the influence of the wave-induced motion. The results for both perspectives are presented and discussed. Notably, it is highlighted that the effect of wave induced motions may not be as significant as the wind loading on the drivetrain responses particularly in larger turbines. Given the limited experience with floating wind turbines, however, more research is needed. The main aim with this article is to synthesize and share own research findings on the subject in the period since 2009, the year that the first full-scale floating wind turbine, Hywind Demo, entered operation in Norway.