Synthesis and characterization of poly (linoleic acid)-g-poly(methyl methacrylate) graft copolymer with applying in Au/PLiMMA/n-Si diode

Poly (linoleic acid)-g-poly(methyl methacrylate) (PLiMMA) graft copolymer was synthesized and characterized. PLiMMA graft copolymer was synthesized from polymeric linoleic acid peroxide (PLina) possessing peroxide groups in the main chain by free radical polymerization of methyl methacrylate. Later, PLiMMA was characterized by proton nuclear magnetic resonance (¹H NMR), gel permeation chromatography (GPC), thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC) techniques. Furthermore, Au/PLiMMA/n-Si diode was fabricated for the purpose of investigating PLiMMA׳s conformity in diodes. The main electrical characteristics of this diode were investigated using experimental current–voltage (I–V) measurements in dark and at room temperature. Obtained results, such as sufficiently high rectifying ratio of 4.5×10⁴, indicate that PLiMMA is a promising organic material for electronic device applications.     

Evaluation of standard and real fire exposures on thermal response of rail car floor assembly

This work developed a computational methodology to evaluate and compare standard fire exposures such as those outlined in ASTM E119 with real fire exposures and determine the difference in the temperature rise of a rail car floor assembly. The real fire exposures simulated in this work were identified in a review of incidents and consisted of a constantly-fed diesel fuel spill, a localized trash fire, and a gasoline spill simulated from a collision of the railcar with an automobile. These realistic fire exposures were applied to a variety of exemplar rail cars representative of single-level and bi-level passenger cars. These floor assembly models exposed to realistic fires were simulated in Fire Dynamics Simulator (FDS). The thermal exposure at the underside of railcar provided by FDS was coupled with a thermal model in ABAQUS, which provided the evolution of temperature in different components of the floor assembly. The standard scenarios were simulated for 2 hours instead of the typical 30 minutes to identify the appropriate exposure duration in ASTM E119, which can better represent a real fire scenario. The average and maximum temperatures predicted at the unexposed surface for both scenarios were compared with the threshold values given in NFPA 130.     

High‐intensity sweeteners in espresso coffee: ideal and equivalent sweetness and time–intensity analysis

The efficient substitution of sucrose by a sweetener in beverages requires the application of some sensory techniques. First, one must determine the concentrations of the sweeteners under study, equivalent in sweetness to the ideal sucrose concentration. In addition, it is fundamental to determine which is most similar to sucrose. The objectives of this study were to determine the ideal sweetness for espresso coffee and the equivalent concentrations in sweetness of different sweeteners, as well as characterise the time–intensity profile of each sweetener in relation to sweetness. The sweeteners evaluated were sucralose, aspartame, neotame, a cyclamate/saccharin mixture (2:1) and stevia. The sucrose concentration considered ideal by consumers was 12.5% (w/v), and the equivalent concentrations of the sweeteners were 0.0159% for sucralose, 0.0549% for aspartame, 0.0016% for neotame, 0.0359% for the cyclamate/saccharin mixture and 0.0998% for stevia. The time–intensity analysis indicated that possibly the sweeteners neotame, aspartame and sucralose would be the best substitutes for sucrose.     

Homogenization with uncertainty in Poisson ratio for polymers with rubber particles

The main aim of this work is dual computer analysis of probabilistic coefficients for the homogenized tensor of the polymer filled with the rubber particles having randomized Poisson ratios of both constituents. The major issue is to verify an influence of a randomness in rubber Poisson ratio close to the compressibility limit on the uncertainty of the effective tensor probabilistic characteristics. Probabilistic analysis presented here is carried out using mainly the stochastic perturbation technique provided by the common application of the traditional FEM commercial code ABAQUS and the symbolic computations package MAPLE. This FEM-based technique employs polynomial response function of the optimum order recovered from the weighted least squares method and following a set of deterministic solutions obtained for various values of the randomized input parameter. Optimization procedure is released entirely into a symbolic environment, where maximization of the correlation factor together with minimization of the fitting variance and approximation error are applied. Homogenization technique consists in equating of deformation energies for the real composite and the artificial one characterized by the effective elasticity tensor with uncertainty.     

Technical and economic analysis of solvent-based lithium-ion electrode drying with water and NMP

Processing lithium-ion battery (LIB) electrode dispersions with water as the solvent during primary drying offers many advantages over N-methylpyrrolidone (NMP). An in-depth analysis of the comparative drying costs of LIB electrodes is discussed for both NMP- and water-based dispersion processing in terms of battery pack $/kWh. Electrode coating manufacturing and capital equipment cost savings are compared for water vs. conventional NMP organic solvent processing. A major finding of this work is that the total electrode manufacturing costs, whether water- or NMP-based, contribute about 8–9% of the total pack cost. However, it was found that up to a 2?×?reduction in electrode processing (drying and solvent recovery) cost can be expected along with a $3–6?M savings in associated plant capital equipment (for a plant producing 100,000 10-kWh Plug-in Hybrid Electric Vehicle (PHEV) batteries) using water as the electrode solvent. This paper shows a different perspective in that the most important benefits of aqueous electrode processing actually revolve around capital equipment savings and environmental stewardship and not processing cost savings.     

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength and stress have an odd or an even set size. The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa. The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study. The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample. In general, the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.     

Thermal Bending Analysis of Doubly Curved Composite Laminated Shell Panels with General Boundary Conditions and Laminations

Thermal bending analysis of doubly curved laminated shell panels with general boundary conditions and laminations is presented. The equations of equilibrium are derived in the form of two coupled sets of ordinary differential equations based on a general shell theory and solved through the state-space approach in a repeated manner. It is depicted that the results of the present method are in great agreement with analytical solutions. Cylindrical shell panels with general boundary conditions and laminations, where no analytical solution is available, are solved. It is found that the present method exhibits a high convergence rate as well as presenting accurate results in all cases.     

Bearing Failure Optimization of Composite Double-Lap Bolted Joints Based on a Three-Step Strategy Marked By Feasible Region Reduction and Model Decoupling

To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction, optimization model decoupling and optimization was presented. In feasible region reduction, the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses, and the feasible regions of variables were reduced by influence mechanism analyses. In model decoupling, the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis. In the third step, the optimization sub-models were solved one by one using a genetic algorithm, and the modified characteristic curve method was adopted as the failure prediction method. Based on the proposed optimization method, optimization of a double-lap single-bolt joint was performed using the ANSYS^® code. The results show that the bearing failure load increased by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of the joint, which validated the effectiveness of the three-step optimization strategy.