RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제
      • 좁혀본 항목 보기순서

        • 원문유무
        • 원문제공처
        • 학술지명
          펼치기
        • 주제분류
        • 발행연도
        • 작성언어
        • 저자
          펼치기

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • Buckling of porosity-dependent bi-directional FG nanotube using numerical method

        Wang, Haiquan,Zandi, Yousef,Gholizadeh, Morteza,Issakhov, Alibek Techno-Press 2021 Advances in nano research Vol.10 No.5

        This article focused on studying the buckling behavior of two-dimensional functionally graded (2D-FG) nanosize tubes, including porosity based on first shear deformation and higher-order theory of tube. The nano-scale tube is simulated based on the nonlocal gradient strain theory, and the general equations and boundary conditions are derived using Hamilton's principle for the Zhang-Fu's tube model (as higher-order theory) and Timoshenko beam theory. Finally, the derived equations are solved using a numerical method for both simply-supported and clamped boundary conditions. The parametric study is performed to study the effects of different parameters such as axial and radial FG power indexes, porosity parameter, nonlocal gradient strain parameters on the buckling behavior of di-dimensional functionally graded porous tube.

      • Computer simulation for stability performance of sandwich annular system via adaptive tuned deep learning neural network optimization

        Ming, Yan,Zandi, Yousef,Gholizadeh, Morteza,Oslub, Khaled,Khadimallah, Mohamed Amine,Issakhov, Alibek Techno-Press 2021 Advances in nano research Vol.11 No.1

        In this article with the aid of adaptively tuned deep neural network (DNN), dynamic stability analysis of the sandwich structure has been investigated. Due to finding the design-points features, the numerical solution procedure called two-dimensional generalized differential quadrature technique has been applied to the ordinary differential equations of the current structure system acquired on the foundation of the kinematic theory with refined higher order terms. Also, the involved parameters with the optimum values in the fully-connected neural network mechanism are obtained via momentum-based optimizer. For modeling a moderately thick structure, higher order terms of shear deformation are chosen. For stability analysis of the current structure the design points considering the method of adaptive learning is presented. For analysis of the current structure 'accuracy (used for determining the design-points) is presented through than the published outcomes in the literature. The outcomes of accuracy section of the current research show that the DNN-based model in analysis of the sandwich structure has less error than other models. The results show that the current momentum-based optimizer can be good tool for future researches about stability analysis of the various structure due to its good accuracy.

      • The compressive strength of concrete retrofitted with wind ash and steel slag pozzolans with a water-cement based polymers

        Cai, Ting,Zandi, Yousef,Agdas, Alireza Sadighi,Selmi, Abdellatif,Issakhov, Alibek,Roco-Videla, Angel Techno-Press 2021 Advances in concrete construction Vol.11 No.6

        Freeze and thaw phenomena in cold regions are the main cause of severe damage to concrete structures. Alkali-activated slag repair mortars, which are introduced as a suitable material for the replacement of Portland cement, can be used as the protective coating for these damaged structures. The mechanical properties and durability of this coating layer should be studied. In this study, the mechanical properties and durability of alkali-activated slag repair mortars with silica fume (SF) participation as inorganic additives against freeze-thaw and salt scaling attacks have been investigated. In order to evaluate the effects of alkaline activators type, the ratio of these solutions to Pozzolan (Pozz), and the use of SF as a substitute base material, these three factors were considered as the main variables to produce 12 alkali-activated slag mortar mixtures. To investigate their mechanical properties, compressive strength, tensile adhesion strength, and drying shrinkage tests were conducted. Also, mortar specimen length change, compressive strength loss, weight loss, and dynamic elastic modulus were measured to evaluate the durability features against freeze-thaw and salt scaling attacks. According to the results, in addition to higher compressive strength and adhesion resistance of alkali-activated slag repair mortars, these mortars showed at least 30% better durability against freeze-thaw and salt scaling attacks than cement-based repair mortar. Also, alkali-activated slag mixtures containing potassium hydroxide, alkaline solution (AS) to Pozz ratio of 0.7, and SF had the best mechanical properties and frost resistance among all mixtures.

      • A review study of application of artificial intelligence in construction management and composite beams

        Yan Cao,Yousef Zandi,Alireza Sadighi Agdas,Qiangfeng Wang,Xueming Qian,Leijie Fu,Karzan Wakil,Abdellatif Selmi,Alibek Issakhov,Angel Roco-Videla 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.39 No.6

        This paper is aimed to review the use of artificial intelligence (AI) algorithms in diverse civil engineering applications such as predicting and evaluating the different parameters of composite beams and shear connectors and determining the compressive strength of concrete. Also, the application of AI methods especially artificial neural network (ANN) in construction engineering and management including prediction and estimation, decision-making, classification or selection, optimization and risk analysis and safety has been thoroughly discussed. Furthermore, the integration of Artificial Neural network (ANN) with other soft computing methods, such as Backpropagation (BP), imperialist competitive algorithm (ICA), support vector regression (SVR), back-propagation neural network (BPNN), Genetic Algorithms (GA) and Multilayer feed forward (MLFF) has been reviewed. It has been reported that the combination of ANN with other intelligence algorithms leads to providing more accurate results. Moreover, the performance of ANN with other soft computing techniques, such as BP, BPNN, SVR, GA, ICA, and MLFF in various fields has been compared and ANN in many cases had superiority over other models.

      • Economic construction management of composite beam using the head stud shear connector with encased cold-formed steel built-up fix beam via efficient computer simulation

        Yin, Jinzhao,Tong, Huizhi,Gholizadeh, Morteza,Zandi, Yousef,Selmi, Abdellatif,Roco-Videla, Angel,Issakhov, Alibek Techno-Press 2021 Advances in concrete construction Vol.11 No.5

        With regard to economic efficiency, composite fix beams are widely used to pass longitudinal shear forces across the interface. The current knowledge of the composite beam load-slip activity and shear capability are restricted to data from measurements of push-off. Modelling and analysis of the composite beams based on Euro-code 4 regarding to shear, bending, and deflection under differing loads were carried out using Finite Element through an efficient computer simulation and the final loading and sections capacity based on the failure modes was analysed. In bending, the section potential was increased by an improvement of the strength in both steel and concrete, but the flexural and compressive resistance growth is very weak (3.2% 3.1% and 3.0%), while the strength of the concrete has increased respectively from 25 N/mm<sup>2</sup> to 30, 35, and 40 N/mm<sup>2</sup> compared to the increment of steel strength by 27% and 21% when it was raised from 275 to 355 and 460 N/mm<sup>2</sup>, respectively. It was found that the final flexural load capacity of fix beams was declined with increase in the fix beam span for both three steel strength. The shear capacity of sections was remained unchanged at constant steel strength and different length, but raised with final yield strength increment of steel sections by 29%, and 67% when it was raised from 275 N/mm<sup>2</sup> to 355 N/mm<sup>2</sup> and 460 N/mm<sup>2</sup>, respectively.

      • Application of multi-hybrid metaheuristic algorithm on prediction of split-tensile strength of shear connectors

        Chao Liu,Yousef Zandi,Abouzar Rahimi,Yongli Peng,Genwang Ge,Mohamed Amine Khadimallah,Alibek Issakhov,Subbotina Tatyana Yu 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.2

        Shear connectors play a major role in the development of composite steel concrete systems. The behavior of shear connectors is usually calculated by push-out measurements. These experiments are expensive and take a lot of time. Soft Computation (SC) may be applied as an additional solution to remove the need for push-out testing. The objective of the research is to explore the implementation, as sub-branches of the SC approaches, of artificial intelligence (AI) techniques for the prediction of advanced C-shaped shear connectors. To this end, multiple push-out tests on these connectors will be carried out and the requisite data is obtained for the AI models. The Grey Wolf Optimizer algorithm (GWO) is built to define the parameters that influence the shear strength of angle connectors. Two regression metrics as determination coefficient (R2) and root mean square (RMSE) were used to measure the results of model. Furthermore, only four parameters in the predictive models are sufficient to provide an extremely precise prediction. It was found that GWO is a faster method and is able to achieve marginally higher output indices than in experiments.

      • The economic and management use of rhododendron petals in potas-sium-ion nano batteries anode via efficient computer simulation

        Dai, Wensheng,Zand, Yousef,Agdas, Alireza Sadighi,Selmi, Abdellatif,Roco-Videla, Angel,Wakil, Karzan,Issakhov, Alibek Techno-Press 2021 Advances in nano research Vol.10 No.6

        Nano batteries are manufactured batteries which use nanoscale technology, small particles measuring less than 100 nanometers or 10-7 meters. In addition, because of plentiful potassium supplies and less cost, potassium-ion batteries (PIBs) are taken as possible substitutes for lithium-ion batteries for massive energy storing systems. Our modern lifestyle could be totally different without rechargeable batteries. Regarding their economic and management usage, these batteries are applied in electric and hybrid vehicles, devices, and renewable power generation systems. Accordingly, regarding the huge K ion radius, it is a difficult process for identifying relevant materials with excellent cycling stability and capacity. At present, the production of suitable anode materials with high specific capacities, long cycle life and low costs for PIBs remains a major challenge. Also, the continuing improvement in defining future electors, the manufacture of PIBs has been complicated by multiple challenges, namely low reversible performance, insufficient cycling stability and poor energy density, all of which have created important doubts for the effective implications of PIBs. Nano-particles have shown various advantages for enhanced energy and power density, cyclability and safety when it comes to designing and producing electrode materials via efficient computer simulation. In combination with large volume expansion, slow reaction kinetics, and low electrical conductivity the main cause for the degradation of SnO<sub>2</sub> reaction reversibility and power decay observed are not as obvious as those of Lithium-ion batteries (LIBs) as anodes of sodium-ion batteries (SIBs), and potassium-ion batteries (KIBs).

      • Influence of crack on the permeability of plastic concrete

        Yongqiang He,Rayed Alyousef,Abdulaziz Alaskar,Hisham Alabduljabbar,Abdeliazim Mustafa Mohamed,Nelson Maureira-Carsalade,Angel Roco-Videla,Alibek Issakhov,Hamid Assilzadeh 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.5

        This study examined the relations between permeability of the concrete due to addition of new cracks. The different concrete types analyzed were standard concrete, reinforced steel fiber concrete, and reinforced concrete polypropylene fiber. In consideration of the improved polypropylene content of polypropylene fiber reinforced concrete, the crack diameter was decreased by 72-93% for up to 0.25% fiber and cracks were eliminated with 0.3% fiber inclusion. In terms of steel fiberreinforced concrete, the results showed that steel reinforcing macro fibers decrease the permeability of cracked concrete at wider crack widths. While the permeability of unreinforced concrete was the highest, 0.5% steel content resulted in lower permeability while a higher steel content concrete with 1% steel had the lowest permeability. Crack stitching phenomenon and the effect of multiple cracks may be attributed to the decrease in the permeability. With respect to normal concrete, the findings showed the crack opening displacement at the highest tension is less than 20 microns. At this loading stage, after unloading, around 80% of the displacement is restored and the residual crack opening is notably small, indicating the low impact of cracking on concrete permeability (CP) and showing that CP was increased with crack width. As a result, adding polypropylene aggregate to concrete could significantly reduce the width of crack, while adding steel fiber to concrete reduces the permeability of cracked concrete compared to normal concrete which may result in a minor crack on CP.

      • Optimization algorithms for composite beam as smart active control of structures using genetic algorithms

        Yan Cao,Yousef Zandi,Morteza Gholizadeh,Leijie Fu,Jiang Du,Xueming Qian,Zhijie Wang,Angel Roco-Videla,Abdellatif Selmi,Alibek Issakhov 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.6

        The principles of productive active and semi-active civil and infrastructure engineering structural control date back 40 years and significant progress has been recorded in those four decades. Smart structures typically have some control systems that enable them to deal with perturbations. The active vibration management techniques have been applied numerically and experimentally in order to reduce the vibrational levels of lightweight economic composite structures. Smart composite beams and plates have been produced and tested with surface-based piezoelectric sensors and actuators. It has been found that an effective model of smart composite plates can predict the dynamic characteristics. Utilizing Genetic Algorithm (GA) was designed and implemented. Two regression model as root mean square (RMSE) and determination coefficient (R<sup>2</sup>) were used. The first and second bending modes are operated effectively by a beam, and simultaneous vibration levels are significantly reduced for the conductive plates by the simultaneous operation of the bending and twisting modes. Vibration management is realized by using efficient control. GA could show better performance for managing linear feedback laws under given assumptions.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼