Prediction of deflection of reinforced concrete shear walls

Reinforced concrete shear walls are used in tall buildings for efficiently resisting lateral loads. Due to the low tensile strength of concrete, reinforced concrete shear walls tend to behave in a nonlinear manner with a significant reduction in stiffness, even under service loads. To accurately assess the lateral deflection of shear walls, the prediction of flexural and shear stiffness of these members after cracking becomes important. In the present study, an iterative analytical procedure which considers the cracking in the reinforced concrete shear walls has been presented. The effect of concrete cracking on the stiffness and deflection of shear walls have also been investigated by the developed computer program based on the iterative procedure. In the program, the variation of the flexural stiffness of a cracked member has been evaluated by ACI and probability-based effective stiffness model. In the analysis, shear deformation which can be large and significant after development of cracks is also taken into account and the variation of shear stiffness in the cracked regions of members has been considered by using effective shear stiffness model available in the literature. Verification of the proposed procedure has been confirmed from series of reinforced concrete shear wall tests available in the literature. Comparison between the analytical and experimental results shows that the proposed analytical procedure can provide an accurate and efficient prediction of both the deflection and flexural stiffness reduction of shear walls with different height to width ratio and vertical load. The results of the analytical procedure also indicate that the percentage of shear deflection in the total deflection increases with decreasing height to width ratio of the shear wall.     

An integrated approach to concept evaluation in a new product development

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.     

Visualization of fibrous and thread-like data

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU. We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.     

Assessment of Water Quality Management in Turkey

Abstract

There has been a noticeable increase in the amount of pollution in water resources in Turkey in recent years. Negative environmental developments, such as industrialization, increasing urbanization, improper pesticide and fertilizer applications in agricultural lands, and the drainage of domestic and industrial wastewater into water resources without any waste treatment applications, cause rapid pollution of both surface and groundwater resources. Therefore, it is necessary to allocate more attention to water resources monitoring and evaluation studies to prevent the pollution of water resources, and to reclaim these resources.     

Vibration analysis of rolling element bearings with various defects under the action of an unbalanced force

In this paper, a method based on the finite element vibration analysis is presented for defect detection in rolling element bearings with single or multiple defects on different components of the bearing structure using the time and frequency domain parameters. A dynamic loading model is proposed in order to create the nodal excitation functions used in the finite element vibration analysis as external loading. A computer code written in Visual Basic programming language with a graphical user interface is developed to create the nodal excitations for different cases including the outer ring, inner ring or rolling element defects. Forced vibration analysis of a bearing structure is performed using the commercial finite element package I-DEAS under the action of an unbalanced force transferred to the structure via a ball bearing. Time and frequency domain parameters such as rms, crest factor, kurtosis and band energy ratio for the frequency spectrum of the enveloped signals are used to analyse the effect of the defect location and the number of defects on the time and frequency domain parameters. The role of the receiving point for vibration measurements is also investigated. The vibration data for various defect cases including the housing structure effect can be obtained using the finite element vibration analysis in order to develop an optimum monitoring method in condition monitoring studies.     

Biodiversity and technological properties of yeasts from Turkish sourdough

Food Science and Biotechnology - In this study, yeasts were isolated and characterized from twelve traditional sourdough samples which belongs to Black Sea and Aegean regions of Turkey. Twenty six...     

PSW statistical LSB image steganalysis

Multimedia Tools and Applications - Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art...     

A polyurethane‐based nanocomposite biocompatible bone adhesive

A novel polyurethane‐based foam‐like adhesive reinforced with nanosized hydroxyapatite (HA) particles was developed and investigated for bone‐to‐bone bonding applications in terms of mechanical adhesion and biocompatibility. The adhesive has a hierarchical structure with HA particles at the nanoscale level and pores at the micro‐scale level. This adhesive was tested mechanically in the three principal loading modes anticipated: shear, tension, and compression. Standard testing procedures were used when available. Tensile strength of primed adhesive showed a four‐fold increase in adhesion on unmodified bone and a nearly two‐fold increase in adhesion to primed bone as compared with the conventional bone cement. Biocompatibility was initially assessed in vitro using cell culture tests, which showed positive interaction with the adhesive. Then, a second biocompatibility test was performed using Xenopus laevis limbs to assess an in vivo response. The results indicated that the adhesive material produces a normal response consistent with control specimens. However, long‐term observations and tests with additional species are needed to demonstrate full biocompatibility. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2013     

Evaluating of traumatic brain injuries using artificial neural networks

The purpose of this study is to develop a diagnostic system to detect the severity of traumatic brain injuries using artificial neural networks. Three layered back propagation neural network with an input layer of 10 nodes whose output providing the inputs to a hidden layer was used. Thirty-two patients with traumatic brain injuries in different age and gender were taken in the study. Electroencephalography, Trauma and Glasgow coma scores were used for evaluating the data. The results obtained from the system were compared with the findings of neurologists. We found a significant relationship between the findings of neurologists and systems output for normal, mild, moderate and severe electroencephalography tracing data. Getting this system in routine use will lead to make a rapid decision for the degree of trauma with electroencephalography and revised trauma score.     

An integrated decision aid extension to material selection problem

Choice of an adequate material in design process is one of the critical tasks for the relevant decision-makers. At this insight, the consistency of the decisions is extremely depending on the relevance of adapted techniques to the nature of different problem cases. This paper proposed an integrated decision aid (IDEA) to match the suitable techniques with different problem cases based on the following six dimensions: (i) the type of the decision problem, (ii) the size of the problem, (iii) selection of the preference techniques by decision-makers, (iv) decision-makers’ preference structure, (v) the necessity for the use of relative importance, (vi) the nature of performance values. Furthermore, the implementation procedure of the proposed IDEA for a material selection problem is demonstrated with the previously cited applications from material science literature. Hereafter, it is expected that the IDEA provides great advantages and encouragements to researchers/practitioners in order to prevent excessive time consuming, probable misapplications, and the other challenging issues in multiple criteria analysis of material selection problems.