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RISS 인기검색어
- 검색키워드
- 저자 : Khalifa S. Al-Jabri (검색결과 4 건)
- 무료
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Predicting the Behaviour of Semi-rigid Joints in Fire Using an Artificial Neural Network
Khalifa S. Al-Jabri,Saleh M. Al-Alawi 한국강구조학회 2007 International Journal of Steel Structures Vol.7 No.3
In this paper, we describe an artificial neural networking (ANN) model developed to predict the moment-rotation responseof semi-rigid beam-to-column joints at elevated temperature. Five types of beam-to-column joints, which represent typicaljoints used in construction, were modelled. Three flush end-plate bare-steel joints, one flexible end-plate bare-stel joint andtwo flexible end-plate composite joints were considered. The aplied moment and joint’s temperatures were used as inputeused for training and testing and validating the neural network models. The model’s predicted values were compared with actualtest results. The results indicate that the models can predict the momentrotationtemperature behaviour of semi-rigid beam-to-column joints with very high accuracy. The developed model can be modified easily to investigate other parameters thatinfluence the performance of joints in fire.
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Behavior of Steel-framed Buildings in a Fire
Khalifa S. Al-Jabri 한국강구조학회 2007 International Journal of Steel Structures Vol.7 No.3
The rules presented in the current codes of practice for the design of steel-framed buildings in fire conditions are based ontingconditions were obviously diferent from the real situation wherein the structure is subjected to natural fires. It has been knownfor many years, from observations of acidental fires, that structural members behave beter in fire when they constitute partof a structural arrangement than when they are tested in isolation. These observations have been confirmed by results fromform part of the structure can withstand much higher temperatures than those tested singly. This has raised doubts concerningthe conservative design aproaches provided by current fire enginering design codes. The atack on the twin towers of theWorld Trade Centre in New York on 11 September 201 has prompted close examination of the way in which buildings canfail in fires and has brought into the public eye the hazards that fires can pose to major building structures. This paper examinesmay allow for the construction of safer buildings in the future.
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Khalifa S. Al-Jabri,M. Al-Alawi2 한국강구조학회 2010 International Journal of Steel Structures Vol.10 No.4
This paper describes an artificial neural networking (ANN) model developed to predict the behaviour of semi-rigid composite joints at elevated temperature. Three different semi-rigid composite joints were selected, two flexible end-plates and one flush end-plate. Seventeen different parameters were selected as input parameters representing the geometrical and mechanical properties of the joints as well as the joint’s temperature and the applied loading, and used to model the rotational capacity of the joints with increasing temperatures. Data from experimental fire tests were used for training and testing the ANN model. Results from nine experimental fire tests were evaluated with a total of 280 experimental cases. The results showed that the R2 value for the training and testing sets were 0.998 and 0.97, respectively. This indicates that results from the ANN model compared well with the experimental results demonstrating the capability of the ANN simulation techniques in predicting the behaviour of semi-rigid composite joints in fire. The described model can be modified to study other important parameters that can have considerable effect on the behaviour of joints at elevated temperatures such as temperature gradient, axial restraints,etc.
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Sabah A. Abdul-Wahab,Edris M. Hassan,Khalifa S. Al-Jabri,Kaan Yetilmezsoy 대한환경공학회 2019 Environmental Engineering Research Vol.24 No.2
This study was conducted to explore the optimum proportion of zeolite and zeolite-kaolin as additives to cement clinker and gypsum samples, while maintaining the strength properties of produced environmentally sustainable cements. According to the British standard method, zeolite was added to cement clinker in proportions of 5-12% and 10-12% by weight, respectively, in the preparation of samples of zeolite-containing cement and zeolite-kaolin-based cement. Kaolin was used as a second additive as 10-20% of the total weight. The compressive strength tests were performed on base cement samples according to a standard procedure given in ASTM C109 Compressive Strength of Hydraulic Cement. These values were compared with those of the reference sample and the Omani allowable limits. The results indicated that the best compressive strength values were obtained with 88% cement clinker, 5% gypsum, and 7% zeolite for the zeolite-containing cement. Quantities of 70% cement clinker, 5% gypsum, 10% zeolite, and 15% kaolin gave the best results for zeolite-kaolin-based cement, resulting in a substitution of than 25% cement clinker. The study concluded that the partial cement clinker replacement using zeolite/kaolin combination may have a great influence on the reduction of CO₂ emission and energy saving in cement manufacturing.
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