Optoelectronic devices informatics: optimizing DSSC performance using random-forest machine learning algorithm

This paper provides an attempt to utilize machine learning algorithm, explicitly random-forest algorithm, to optimize the performance of dye sensitized solar cells (DSSCs) in terms of conversion efficiency. The optimization is implemented with respect to both the mesoporous TiO2 active layer thickness and porosity. Herein, the porosity impact is reflected to the model as a variation in the effective refractive index and dye absorption. Database set has been established using our data in the literature as well as numerical data extracted from our numerical model. The random-forest model is used for model regression, prediction, and optimization, reaching 99.87% accuracy. Perfect agreement with experimental data was observed, with 4.17% conversion efficiency.     

Finite‐time stability of linear fractional‐order time‐delay systems

In this paper, a finite‐time stability results of linear delay fractional‐order systems is investigated based on the generalized Gronwall inequality and the Caputo fractional derivative. Sufficient conditions are proposed to the finite‐time stability of the system with the fractional order. Numerical results are given and compared with other published data in the literature to demonstrate the validity of the proposed theoretical results.     

Finite-Time Stability for Caputo–Katugampola Fractional-Order Time-Delayed Neural Networks

Neural Processing Letters - In this paper, an original scheme is presented, in order to study the finite-time stability of the equilibrium point, and to prove its existence and uniqueness, for...     

Solid State Rheological Properties of Ultra‐High Molecular Weight Polyethylene Foams

The rheological properties of ultra‐high‐molecular‐weight polyethylene (UHMWPE) foams were studied using solid state rheometry. Frequency and temperature sweeps were performed in the linear viscoelastic regime. For comparison purposes, low‐density polyethylene (LDPE) and high density polyethylene (HDPE) foams were also studied. For the range of densities under consideration (200‐700 kg/m³), several models for prediction of elastic moduli were compared. It was found that none of the models succeeded in representing completely the mechanical behavior of foams. Further refinements must be made in order to take into account parameters relating the morphology of the foam to its mechanical properties.     

Model‐free kinetics: Curing behavior of phenol formaldehyde resins by differential scanning calorimetry

Isoconversional analysis was used to treat nonisothermal DSC data and yield the dependence of activation energy on conversion during the curing process of PF resins. The shape of the dependence revealed that the curing process of PF resins displayed a change in the reaction mechanism from a kinetic to a diffusion regime. In the kinetic regime a comparative DSC experimental analysis between monomer mixtures and PF resins showed that the addition reactions between phenol and formaldehyde had been mostly completed during the synthesis of PF resins and that the main kinetic reactions contained parallel condensations in the curing process. For the diffusion regime a modified equation for the diffusion rate constant, k_D = D₀ exp(?E_D /RT + K₁α + K₂α²), is proposed. This equation is in good agreement with the experimental dependence of E_α on α in the diffusion regime, which shows the effect of both temperature and conversion on diffusion. A prediction of the conversion advancement with the reaction time under isothermal condition for PF resin has been made. This prediction can be useful in practical applications for evaluating isothermal behavior of thermosetting systems from nonisothermal experimental data. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 433–440, 2003     

A hybrid differential evolution algorithm based on particle swarm optimization for nonconvex economic dispatch problems

This paper presents the design and application of an efficient hybrid heuristic search method to solve the practical economic dispatch problem considering many nonlinear characteristics of power generators, and their operational constraints, such as transmission losses, valve-point effects, multi-fuel options, prohibited operating zones, ramp rate limits and spinning reserve. These practical operation constraints which can usually be found at the same time in realistic power system operations make the economic load dispatch problem a nonsmooth optimization problem having complex and nonconvex features with heavy equality and inequality constraints.The proposed approach combines in the most effective way the properties of two of the most popular evolutionary optimization techniques now in use for power system optimization, the Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. To improve the global optimization property of DE, the PSO procedure is integrated as additional mutation operator.The effectiveness of the proposed algorithm (termed DEPSO) is demonstrated by solving four kinds of ELD problems with nonsmooth and nonconvex solution spaces. The comparative results with some of the most recently published methods confirm the effectiveness of the proposed strategy to find accurate and feasible optimal solutions for practical ELD problems.     

Real time implementation of backstepping-multiscalar control to induction motor fed by voltage source inverter

A novel version of nonlinear induction motors (IM) control algorithm based on the backstepping approach has been proposed in this work. For that, the conventional mathematical model of IM is replaced by the multiscalar one, which is more suitable for application of the backstepping design. By using such combination, the system has fast dynamic response, better load disturbance rejection capability, less parameters sensitivity and better tracking performance of rotor speed and rotor flux magnitude. The effectiveness of the proposed control structure is validated by simulation as well by experiment under critical disturbance conditions.     

Poly(arylene ether)s carrying pendant (3‐sulfonated) phenylsulfonyl groups

A series of poly(arylene ether)s with biphenyl units and pendant sulfonated phenylsulfonyl groups was prepared via nucleophilic aromatic substitution reactions of varying ratios of 3,5‐difluoro‐3′‐sulfonated diphenylsulfone and 4,4′‐difluorodiphenylsulfone with 4,4′‐biphenol. As such, the sulfonic acid moieties reside in the meta position of a pendant, electron‐poor phenylsulfonyl group. Mechanically robust proton‐exchange membranes with ion‐exchange capacities (IEC) ranging from 0.91 to 2.05 meq g^?1 were cast from dimethylacetamide. The thermal stability of the membranes was evaluated via thermogravimetric analysis and the 5% weight losses were found to be in excess of 330 °C in air. The glass transition temperatures were determined, via differential scanning calorimetry, to range from a low of 148 to a high of 209 °C at IEC values of 0.91 and 1.79 meq g^?1, respectively. The copolymer membranes reached proton conductivities as high as 142 mS cm^?1 under 100% relative humidity, with relatively low water uptake values (8–32 wt%). Copyright © 2012 Society of Chemical Industry     

Polymerization compounding composites of nylon‐6,6/short glass fiber

Nylon‐6,6 was grafted onto the surface of short glass fibers through the sequential reaction of adipoyl chloride and hexamethylenediamine onto the fiber surface. Grafted and unsized short glass fibers (USGF) were used to prepare composites with nylon‐6,6 via melt blending. The glass fibers were found to act as nucleating agents for the nylon‐6,6 matrix. Grafted glass fiber composites have higher crystallization temperatures than USGF composites, indicating that grafted nylon‐6,6 molecules further increase crystallization rate of composites. Grafted glass fiber composites were also found to have higher tensile strength, tensile modulus, dynamic storage modulus, and melt viscosity than USGF composites. Property enhancement is attributed to improved wetting and interactions between the nylon‐6,6 matrix and the modified surface of glass fibers, which is supported by scanning electron microscopy (SEM) analysis. The glass transition (tan δ) temperatures extracted from dynamic mechanical analysis (DMA) are found to be unchanged for USGF, while in the case of grafted glass fiber, tan δ increases with increasing glass fiber contents. Moreover, the peak values (i.e., intensity) of tan δ are slightly lower for grafted glass fiber composites than for USGF composites, further indicating improved interactions between the grafted glass fibers and nylon‐6,6 matrix. The Halpin‐Tsai and modified Kelly‐Tyson models were used to predict the tensile modulus and tensile strength, respectively.     

Takagi–Sugeno fuzzy modeling for three-phase micro hydropower plant prototype

Micro hydropower plants (MHPP) are widely set up in off-grid sites to provide electrical power. The power quality in such site is a challenge and requires an accurate model for MHPP. The model has to be available for large operating points. Moreover, the model must take into consideration the non-linear character of the system. For these reasons, the present paper proposes a Takagi–Sugeno (T.S) fuzzy model approach for modeling the overall behavior of a three-phase MHPP prototype. This modeling is based on the identification of simple approximations by first and second order systems around several operating points of the system. These operating points depend on different water flows and electric load variations. The developed T.S fuzzy models were experimentally validated taking into consideration various working conditions. The results show that the approximation by the second order system has better accordance with the real system responses. Therefore, this approximation devotes more opportunities to synthesize suitable and robust controllers for MHPP compared to the first order one.