• Steel and Composite Structures
• /
• 제6권3호
• /
• pp.203-219
• /
• 2006

One of the most promising ways through which a steel moment frame may attain high energy dissipating capability is to trim off a portion of the beam flanges near the column face. This type of moment connection, known as Reduced Beam Section (RBS) connection, has notable superiority in comparison with other moment connection types. As the result of the advantages of RBS moment connection, it has widely being used in practice. In spite of the good hysteretic behaviour, an RBS beam suffers from an undesirable drawback, which is local and lateral instability of the beam. The instability in the RBS beam reduces beam load-carrying capacity. This paper aims to investigate key issues influencing cyclic behaviour of RBS beams. To this end, a numerical analysis was conducted on a series of steel subassemblies with various geometric properties. The obtained results together with the existing experimental data are used to study the instability of RBS beams. A new slenderness concept is presented to control an RBS beam for combined local and lateral instability. This concept is in good agreement with the numerical and experimental results. Finally, a model is developed for the prediction of the magnitude of moment degradation owing to the instability of an RBS beam.

• Structural Engineering and Mechanics
• /
• 제37권1호
• /
• pp.39-59
• /
• 2011

Results of an experimental investigation on the behavior and ultimate shear capacity of 27 reinforced concrete Transfer (deep) beams are summarized. The main variables were percent longitudinal(tension) steel (0.28 to 0.60%), percent horizontal web steel (0.60 to 2.40%), percent vertical steel (0.50to 2.25%), percent orthogonal web steel, shear span-to-depth ratio (1.10 to 3.20) and cube concrete compressive strength (32 MPa to 48 MPa).The span of the beam has been kept constant at 1000 mm with100 mm overhang on either side of the supports. The result of this study shows that the load transfer capacity of transfer (deep) beam with distributed longitudinal reinforcement is increased significantly. Also, the vertical shear reinforcement is more effective than the horizontal reinforcement in increasing the shear capacity as well as to transform the brittle mode of failure in to the ductile mode of failure. It has been observed that the orthogonal web reinforcement is highly influencing parameter to generate the shear capacity of transfer beams as well as its failure modes. Moreover, the results from the experiments have been processed suitably and presented an analytical model for design of transfer beams in high-rise buildings for estimating the shear capacity of beams.

• Computers and Concrete
• /
• 제20권6호
• /
• pp.627-634
• /
• 2017

Predicting the compressive strength of concrete is important to assess the load-carrying capacity of a structure. However, the use of blended cements to accrue the technical, economic and environmental benefits has increased the complexity of prediction models. Artificial Neural Networks (ANNs) have been used for predicting the compressive strength of ordinary Portland cement concrete, i.e., concrete produced without the addition of supplementary cementing materials. In this study, models to predict the compressive strength of blended cement concrete prepared with a natural pozzolan were developed using regression models and single- and 2-phase learning ANNs. Back-propagation (BP), Levenberg-Marquardt (LM) and Conjugate Gradient Descent (CGD) methods were used for training the ANNs. A 2-phase learning algorithm is proposed for the first time in this study for predictive modeling of the compressive strength of blended cement concrete. The output of these predictive models indicates that the use of a 2-phase learning algorithm will provide better results than the linear regression model or the traditional single-phase ANN models.

• Structural Engineering and Mechanics
• /
• 제83권2호
• /
• pp.245-257
• /
• 2022

As the main lateral load resisting system in high-rise reinforced concrete structures, the mechanical performance of shear wall has a significant impact on the structure, especially for high-rise buildings. Steel corrosion has been recognized as an important factor affecting the mechanical performance and durability of the reinforced concrete structures. To investigate the effect on the seismic behaviour of corroded reinforced concrete shear wall induced by corrosion, analytical investigations and simulations were done to observe the effect of corrosion on the ultimate seismic capacity and drift capacity of shear walls. To ensure the accuracy of the simulation software, several validations were made using both non-corroded and corroded reinforced concrete shear walls based on some test results in previous literature. Thereafter, a parametric study, including 200 FE models, was done to study the influence of some critical parameters on corroded structural shear walls with boundary element. These parameters include corrosion levels, axial force ratio, aspect ratio, and concrete compressive strength. The results obtained would then be used to propose equations to predict the seismic resistance and drift capacity of shear walls with various corrosion levels.

• Nuclear Engineering and Technology
• /
• 제54권3호
• /
• pp.1071-1084
• /
• 2022

The present study aims to investigate the dynamic properties of a novel isolation system composed of separate rubber and wire isolators. The testing program comprised pure compressive, pure-shear, compressive-stress dependence, and shear-strain dependence tests that used full-scale test specimens according to ISO 22762-1. A total of 22 test specimens were fabricated and investigated. Among the tests, the pure compressive test was a destructive test that reached up to the failure stage, whereas the others were nondestructive tests before the failure stage. Similar to the pure-shear test, at each compressive-stress level in the compressive dependence test or at each shear-strain level in the shear-strain dependence test, the cyclic loading was conducted for three cycles. In the nondestructive tests, examination of the dynamic shear properties in the X-direction was independent of the Y-direction. The test results revealed that the increase in the shear strain increased the energy dissipation but decreased the damping ratio, whereas the increase in the compressive stress increased the damping ratio. In addition, a macro model was developed to simulate the load-displacement response of the isolation systems, and the prediction results were consistent with the experimental results.

• Steel and Composite Structures
• /
• 제44권2호
• /
• pp.225-240
• /
• 2022

Local responses of steel plate-concrete composite (SC) walls under impact loads are typically evaluated using design equations available in the AISC N690s1-15. These equations enable design of impact-resistant SC walls, but some essential parts such as the effects of wall size and shear reinforcement ratio have not been addressed. Also, since they were developed for design basis events, improved equations are required for accurate prediction of the impact behaviors of SC walls for beyond design basis impact evaluation. This paper presents a numerical study to construct a robust numerical model of SC walls subjected to impact loads to reasonably predict the SC-wall impact behavior, to evaluate the findings observed from the impact tests including the effects of the key design parameters, and to assess the actual responses of full-scale SC walls. The numerical calculations are validated using intermediate-scale impact tests performed previously. The influences of the fracture energy of concrete and the conservative aspects of the current design equations are discussed carefully. Recommendations are made for design practice.

• 반도체디스플레이기술학회지
• /
• 제22권3호
• /
• pp.41-45
• /
• 2023

Currently, the method of loading items in the warehouse, the worker directly decides the loading location, and the most used method is to load the product at the location closest to the entrance. This can be effective when there is no difference in the required amount for goods, but when there is a difference in the required amount for goods, it is inefficient because items with a small required amount are loaded near the entrance and occupy the corresponding space for a long time. Therefore, in order to minimize the release time of goods, it is essential to select an appropriate location when loading goods. In this study, a method for determining the loading location by predicting the required amount of goods was studied to select the optimal loading location. Deep learning based bidirectional long-term memory networks (Bi-LSTM) was used to predict the required amount for goods. This study compares and analyzes the release time of goods in the conventional method of loading close to the entrance and in the loading method using the required amount for goods using the Bi-LSTM model.

• Nuclear Engineering and Technology
• /
• 제56권3호
• /
• pp.1052-1065
• /
• 2024

Advanced Pressurized Water Reactors (APWRs) and Boiling Water Reactors (BWRs) employ a suppression pool as a heat sink to prevent containment overpressure. Steam can be discharged into the pool through multi-hole spargers or blowdown pipes in both normal and accident conditions. Direct Contact Condensation (DCC) creates sources of momentum and heat. The competition between these two sources determines the development of thermal stratification or mixing of the pool. Thermal stratification is of safety concern as it reduces the cooling capability compared to a completely mixed pool condition. In this work we develop a scaling approach to prediction of the thermal stratification in a water pool induced by steam injection through spargers. Experimental data obtained from large-scale pool tests conducted in the PPOOLEX and PANDA facilities, as well as simulation results obtained using validated codes are used to develop the scaling. Two injection orientations, namely radial injection through multi-hole Sparger Head (SH) and vertical injection through Load Reduction Ring (LRR), are considered. We show that the erosion rate of the cold layer can be estimated using the Richardson number. In this work, scaling laws are proposed to estimate both the (i) transient erosion velocity and (ii) the stable position of the thermocline. These scaling laws are then implemented into a 1D model to simulate the thermal behavior of the pool during steam injection through the sparger.

• 한국지반공학회논문집
• /
• 제22권6호
• /
• pp.15-26
• /
• 2006

말뚝의 지지력과 거동을 예측하기 위하여 다양한 연구들이 수행되었음에도 불구하고, 메커니즘에 대한 전반적인 이해가 아직까지 미흡한 실정이다. 이는 많은 인자들이 서로 복잡한 연관성을 맺으며 말뚝의 거동에 영향을 미치기 때문이다. 따라서 지반조건과 말뚝조건 및 항타조건 등 과 관련된 많은 인자들 가운데 지지력에 중요한 영향을 미치는 인자들을 도출하기 어려우며, 또한 인자들 간의 복잡한 연관성을 지지력 공식에 적합하게 고려하기란 매우 어렵다. 본 연구에서는 항타말뚝들에 대한 동재하시험으로부터 선단 및 주면 지지력을 포함한 지지력을 예측하기 위하여 인공신경망이 적용되었다. 첫째로, 신경망 모델링에 근거한 민감도 분석를 통하여 지지력에 대한 각 영향인자들의 영향이 검토되었다. 둘째로, 지지력 예측을 위한 최적의 인공신경망 모델을 도출하기 위하여 인공신경망과 유전자 알고리즘으로 구성된 설계기법이 적용되었다. 이를 통해 토사지반에 관입된 항타말뚝의 지지력을 산정할 수 있는 최적의 인공신경망 모델을 제안하고자 하였다. 사용된 설계기법을 통하여 적합한 입력층 조합, 은닉층 노드수과 각 층 사이의 연결구조를 도출하였다. 도출된 인공신경망 모델을 적용함으로써 항타말뚝의 지지력을 간단하며 신뢰성 있게 예측할 수 있음을 알 수 있다.

• Steel and Composite Structures
• /
• 제50권6호
• /
• pp.705-720
• /
• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.