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RISS 인기검색어
- 검색키워드
- 저자 : Sohaib 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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Waqas Ahmad Wattoo,Ghulam Sarwar Kaloi,Muhammad Yousif,Mazhar Hussain Baloch,Baqar Ali Zardar,Jehangir Arshad,Ghulam Farid,Talha Younas,Sohaib Tahir 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.1
The escalating energy demand across the globe has intensifed the electricity production. Owing to the unavailability of the reliable techniques for electricity storage for a long duration, it is consumed immediately after its production. Therefore, electricity markets can’t be handled like the conventional stock markets. Power companies are facing immense price and delivery risks owing to the increasing competition in the electricity markets. As a result, risk management is the fundamental concern to be addressed in order to achieve the optimum proft targets. Consequently, the power generation organizations need to allocate their generation in bilateral contracts and spot market. For this purpose, an optimal theory of portfolio selection is proposed in this study for electricity generation by forming a reliable prototype and applying the proposed scheme to obtain the suitable outcomes. The Paris Accord on environmental safety from carbon dioxide and NOx gases is especially considered during the modeling of the proposed technique. The credibility of the proposed scheme is validated by using the real-time market data from the PJM market. Various risk-return tradeofs are implemented, and their corresponding solutions are acquired for portfolio optimization as corroborated by the results. The suggested technique is found reliable and adequate for the carbon tax paying suppliers around the world for allocating their respective generation based on the demand of the consumers.
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Park, Seung Hee,Ahmad, Sohaib,Yun, Chung Bang,Roh, Yong Rae Trans Tech Publications, Ltd. 2006 Key Engineering Materials Vol.321 No.-
<P>This paper presents a feasibility study of an impedance-based damage detection technique using PZT (Lead-Zirconate-Titanate) patches for real-time health monitoring of concrete structures. The PZT patches are used to detect progressive surface damage on a plain concrete beam. Both experimental and analytical studies are carried out. For damage quantification, root-mean square deviations (RMSD) before and after damage are used as a damage indicator.</P>
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Optimization of Flame Retardancy & Mechanical Performance of Jute-glass/Epoxy Hybrid Composites
Muhammad Umair,Ayesha Shahbaz,Ahsan Ahmad,Sohaib Arif,Khubab Shaker,Madeha Jabbar,Yasir Nawab 한국섬유공학회 2022 Fibers and polymers Vol.23 No.10
One of the limiting factors of natural fiber composites is their lower flame retardancy (FR) and mechanicalstrength as compared to the glass and other synthetic fiber composites. In this research, FR and mechanical properties of thehybrid jute-glass/epoxy composites were optimized. In the first part, different percentages (1 %, 2 % & 3 %) of zirconiumphosphate (ZrP) particles were mixed in epoxy resin to optimize the flame retardancy and mechanical properties of jute/epoxy composites. 3 % ZrP loaded composite showed improved FR and mechanical (tensile and impact) properties followedby 2 % and 1 % respectively. In the second part, optimized percentage of ZrP particles (3 %) was used to fabricate two (02)jute-glass hybrid epoxy composites, and their mechanical (tensile, flexural and impact) and FR properties were evaluated. Hybrid (H1) samples showed better mechanical and FR properties due to presence of glass layer on the outer side ofcomposite with 3 % ZrP particles loading.
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