Fracture Analysis of a Special Cracked Lap Shear (CLS) Specimen with Utilization of Virtual Crack Closure Technique (VCCT) by Finite Element Methods

Some of the most important characteristics due to a fracture investigation of a special specimen are taken into account. Debonding considerations for a composite/steel cracked lap shear (CLS) specimen by utilization of finite element methods (FEM) as well as a virtual crack closure technique (VCCT) approach have been investigated. Strain energy release rate, delamination load case and direct cycle fatigue analysis have taken into consideration in this study, and the corresponding simulations have been done by ABAQUS/Standard. Linear elastic fracture criteria are used for validation of numerical results from the simulation. For comparison of three different categories of analysis, some special characteristics such as effective energy release rate ratio, bond state, time at bond failure and opening behind crack tip at bond failure have been illustrated. In this work, a detailed analysis of a special CLS specimen debonding by using VCCT and FEM is presented and varied results for validation of this kind of combination are obtained and have been discussed.     

Variety and volume dynamic management for value creation in changeable manufacturing systems

In today’s uncertain market and continuously evolving technology, managing manufacturing systems are more complex than ever. This paper studies the dynamics of managing variety and volume to enhance value creation in manufacturers implementing system-level advanced and automated manufacturing technology (AAMT). The demand is composed of heterogeneous customers who make purchasing decisions depending on the variety levels and lead times of the firm’s product offerings. The cost structure adopted calculates profit as the difference between customer value creation rate (VCR) and costs associated with the process of creating this value. Reported results contribute to the variety and volume management literature by offering analytical clarity of factors affecting product platforms and capacity scalability management for systems with AAMT. In addition, insightful answers to the trade-offs between profit maximising market coverage and investments, smoothing demand policies and system stability for this type of environment are presented. Furthermore, the value of market information in deciding the industrial technology investment and also the impact of product life cycle on the same investment is captured.     

A receiver aware H.264/AVC encoder for decoder complexity control in mobile applications

Due to the power limitations of mobile devices, high-quality video decoding is still a main concern, because it quickly drains battery. In this paper, an H.264/AVC receiver aware encoder has been designed that (1) takes into account all of the decoder modules of a receiver, unlike existing RAEs that only consider some of these modules and are therefore sub optimal, and (2) is independent of decoder implementations and platforms. Furthermore, a decoder complexity controller has been proposed that reduces the complexity of different decoder modules, while minimum distortion is achieved. Finally, we formulate and solve a generic RAE optimization problem, and apply this solution to control the computational resource allocation at the macroblock level of a RAE. Our experiments indicate that the proposed approach can reduce the complexity of different modules by up to 10 % with no quality degradation. In addition, the average error of the proposed complexity controller is 0.8 %, making the accuracy of the system very close to 1.     

Development and validation of spectrophotometric and HPTLC methods for simultaneous determination of rosiglitazone maleate and metformin hydrochloride in the presence of interfering matrix excipients

Two simple methods have been developed and validated for the simultaneous determination of rosiglitazone maleate (ROS) and metformin hydrochloride (MET) in synthetic mixtures and coated tablets in a ratio of 1:250 (ROS:MET). The first method was a spectrophotometric one. The minor component, ROS was determined by measuring the values of absorbance at λ_max 312?nm and the D₁ amplitudes at 331?nm where MET shows no absorption contribution. However, absorbance interferences from tablet excipients were successfully corrected by D₁ at 331?nm zero-crossing technique. Study of spectral interference from tablet excipients was included in the text. Standard curves for A_max and D₁ methods were in the concentration range 20.0–80.0?μg?mL^?1. The major component, MET was determined both in binary mixtures and tablets by measuring its A_max at 236?nm. Extensive dilution eliminated any absorption contribution from the coexisting ROS or tablet matrix. Standard curves showed linearity in the concentration range 4.0–12.8?μg?mL^?1. The second method was based on high performance thin layer chromatography (HPTLC) separation of the two drugs followed by densitometric measurements of their spots at 230?nm. The separation was carried out on Merck HPTLC aluminium sheets of silica gel 60 F254 using methanol:water:NH₄Cl 1% w/v (5:4:1 v/v/v) as the mobile phase. Linear calibration graphs of peak area values were obtained versus concentrations in the range of 0.4–2.0?μg?band^?1 and 20.0–100.0?μg?band^?1 for ROS and MET, respectively. According to International Conference on Harmonisation (ICH) guidelines, different validation parameters were verified for the two methods and presented.     

An Experimental Insight into the Structural and Electronic Characteristics of Strontium‐Doped Titanium Dioxide Nanotube Arrays

The possibility of in situ doping during electrochemical anodization of titania nanotube arrays is demonstrated and the mechanism and variations in structural and electronic characteristics of the nanotube arrays as after doping is systematically explored. In the presence of strontium as the dopant, bulk analysis shows strontium mainly incorporated into the lattice of TiO₂. Surface analysis, however, reveals phase segregation of SrO in the TiO₂ matrix at high Sr doping levels. The near edge X‐ray absorption fine structure (NEXAFS) spectroscopy analysis reveals that Sr²⁺ doping only alters the Ti and O ions interaction in the TiO₂ lattice on the surface with no effect on their individual charge states. An in‐depth understanding of the dopant incorporation mechanism and distribution into TiO₂ nanotube arrays is achieved using high resolution transmission electron microscopy (HRTEM) and the high angle annular dark‐field scanning transmission electron microscopy (HAADF‐STEM) coupled with the electron energy loss spectroscopy (EELS) measurements on the surface and bulk of the nanotubes. Upon their use to photoelectrochemically split water, the Sr‐doped TiO₂ nanotube film shows incident photon conversion efficiencies (IPCE) as high as 65%. The enhanced light activity in conjunction with the ordered one‐dimensional morphology makes the fabricated films promising candidates for water photoelectrolysis.     

Rule extraction for fatty liver detection using neural networks

Neural Computing and Applications - Non-alcoholic fatty liver disease (NAFLD) is one of the most common diseases in the world. Recently the FibroScan device is used as a noninvasive, yet costly...     

Developing a New Integrated Bi-Objective Model for Buffer and Process Time Optimization Problem using Optimization via Simulation Approach

The cost of semi-finished products storage and processing time are two issues affecting the rate of manufacturing in all production systems. The acceleration in production time is usually associated with the increase of costs and lack of appropriate allocation of the production line buffers imposing production costs and increase in delivery time and decrease in productivity. Many previous studies have focused on deterministic production systems using mathematical programming models. Moreover, the optimization of buffers and processing times with stochastic events has not been considered simultaneously. In this study, a new simulation-based optimization model has been proposed to address the modeling and solving of buffer and processing time optimization problem in a stochastic environment. The real world problem has been modeled by using the simulation technique and the model replicated by a design of experiment method. The results were used to build a meta-model of regression for the objective functions and finally, a new mathematical model was solved by a multiobjective Genetic Algorithm. The results of this research show that the proposed approach has efficient solutions and could be easily applied to real world problems.