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- 저자 : Rafi Ahmad (검색결과 4 건)
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Bond strength prediction of steel bars in low strength concrete by using ANN
Sohaib Ahmad,Kypros Pilakoutas,Muhammad M. Rafi,Qaiser U. Zaman 사단법인 한국계산역학회 2018 Computers and Concrete, An International Journal Vol.22 No.2
This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi- Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.
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Makingu Mondi,Peter Woods,Ahmad Rafi 서울대학교 교육연구소 2007 Asia Pacific Education Review Vol.8 No.3
This paper presents the systematic development of a ‘Uses and Gratification Expectancy’ (UGE) conceptual framework which is able to predict students’ ‘Perceived e-Learning Experience.’ It is argued that students’ UGE as regards e-learning resources cannot be implicitly or explicitly explored without first examining underlying communication theories and learning perspectives. As such, the theoretical framework is grounded in the confluence of theories from communication theories and learning perspectives. The integration of Expectancy-value Theory, and the Uses and Gratification Theory serves to accommodate the suggestion that elearning resources offer gratifications that are expected and valued by students. The key theoretical and practical assumptions of the UGE approach are highlighted and consistently implemented in the conceptual edifice.
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Hege Lynum Pedersen,Rafi Ahmad,Ellen Kristin Riise,Hanna-Kirsti Schrøder Leiros,Stefan Hauglid,Sigrun Espelid,Bjørn Olav Brandsdal,Ingar Leiros,Nils-Peder Willassen,Peik Haugen 한국미생물학회 2010 The journal of microbiology Vol.48 No.2
The Ferric uptake regulator (Fur) is a global transcription factor that affects expression of bacterial genes in an iron-dependent fashion. Although the Fur protein and its iron-responsive regulon are well studied, there are still important questions that remain to be answered. For example, the consensus Fur binding site also known as the “Fur box” is under debate, and it is still unclear which Fur residues directly interact with the DNA. Our long-term goal is to dissect the biological roles of Fur in the development of the disease cold-water vibriosis, which is caused by the psychrophilic bacteria Aliivibrio salmonicida (also known as Vibrio salmonicida). Here, we have used experimental and computational methods to characterise the Fur protein from A. salmonicida (AS-Fur). Electrophoretic mobility shift assays show that AS-Fur binds to the recently proposed vibrio Fur box consensus in addition to nine promoter regions that contain Fur boxes. Binding appears to be dependent on the number of Fur boxes, and the predicted “strength” of Fur boxes. Finally,structure modeling and molecular dynamics simulations provide new insights into potential AS-Fur–DNA interactions.
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Fire performance curves for unprotected HSS steel column
M. Shahria Alam,A.H.M. Muntasir Billah,Shahriar Quayyum,Mahmud Ashraf,A.N.M. Rafi,Ahmad Rteil 국제구조공학회 2013 Steel and Composite Structures, An International J Vol.15 No.6
The behaviour of steel column at elevated temperature is significantly different than that atambient temperature due to its changes in the mechanical properties with temperature. Reported literaturesuggests that steel column may become vulnerable when exposed to fire condition, since its strength andcapacity decrease rapidly with temperature. The present study aims at investigating the lateral load resistanceof non-insulated steel columns under fire exposure through finite element analysis. The studied parametersinclude moment-rotation behaviour, lateral load-deflection behaviour, stiffness and ductility of columns atdifferent axial load levels. It was observed that when the temperature of the column was increased, there wasa significant reduction in the lateral load and moment capacity of the non-insulated steel columns. Moreover,it was noted that the stiffness and ductility of steel columns decreased sharply with the increase intemperature, especially for temperatures above 400°C. In addition, the lateral load capacity and the momentcapacity of columns were plotted against fire exposure time, which revealed that in fire conditions, thenon-insulated steel columns experience substantial reduction in lateral load resistance within 15 minutes offire exposure.
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