Currently, the construction trend of high-rise structures is changing from a cube-shaped box to a free-form. In the case of free-form structures, it is difficult to predict the behavior of the structure because it induces torsional deformation due to inclined columns and the eccentricity of the structure by the horizontal load. For this reason, it is essential to review the stability by considering the design variables at the design stage. In this paper, the position of the weak vertical member was analyzed by analyzing the behavior of the structure according to the change in the core position of the twisted high-rise structures. In the case of the shear wall, the shear force was found to be high in the order of proximity to the center of gravity of each floor of the structure. In the case of the column, the component force was generated by the axial force of the outermost beam, so the bending moment was concentrated on the inner column with no inclination.

Asphalt concrete(Ascon) is used to repair potholes and cracks. Special truck-mounted cargo boxes transport 200℃ asphalt concrete to repair potholes and cracks. However, long working and transportation hours to repair wide roads decrease the temperature of the asphalt concrete inside the cargo boxes. If the asphalt concrete temperature drops below 170℃, the adhesion with roads that need repair decreases. Therefore, the temperature of the asphalt concrete needs to be maintained for a long time. Conventional asphalt concrete cargo boxes are mostly burner-type models using hot air to prevent the temperature of the asphalt concrete from dropping. However, there are significant temperature differences between the asphalt concrete near and far away from the hot air, so the temperature decreases over time and leads to the disposal of large amounts of asphalt concrete. This causes waste of resources and environmental pollution. Therefore, this study proposed a heat dissipation cut-off type cargo box model to solve this problem and demonstrated its performance over conventional burner-type models through tests and analysis.

A mid-story isolation system was proposed for seismic response reduction of high-rise buildings and presented good control performance. Control performance of a mid-story isolation system was enhanced by introducing semi-active control devices into isolation systems. Seismic response reduction capacity of a semi-active mid-story isolation system mainly depends on effect of control algorithm. AI(Artificial Intelligence)-based control algorithm was developed for control of a semi-active mid-story isolation system in this study. For this research, an practical structure of Shiodome Sumitomo building in Japan which has a mid-story isolation system was used as an example structure. An MR (magnetorheological) damper was used to make a semi-active mid-story isolation system in example model. In numerical simulation, seismic response prediction model was generated by one of supervised learning model, i.e. an RNN (Recurrent Neural Network). Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm The numerical simulation results presented that the DQN algorithm can effectively control a semi-active mid-story isolation system resulting in successful reduction of seismic responses.

In this paper, a twisted shape structure with an elevation form favorable to the resistance of vibration caused by wind loads is selected from among the forms of high-rise buildings. The analytical model is a square, triangular, and hexagonal plane with a plane rotation angle of one degree from 0 to 3 degrees per each story. As a result of the analysis, as the twist angle increased, story drift ratio is increased. Responses with different eccentricity rates were shown by analytical models. Therefore planar shapes designed symmetrically to the horizontal axis of X and Y are considered advantageous for eccentricity and torsion deformation. In the case of the bending moment of the column, the response was amplified in the column supporting the base floor, the roof floor, the floor in which the cross-section of the vertical member changes, and the floor having the same number of nodes as the base floor. Finally, the axial force response of the column is determined to be absolutely affected by the gravity load compared to the lateral load.

A tilted tall building is actively constructed as landmark structures around world to date. Because lateral displacement responses of a tilted tall building occurs even by its self-weight, reduction of seismic responses is very important to ensure structural safety. In this study, a smart tuned mass damper (STMD) was applied to the example tilted tall building and its seismic response control performance was investigated. The STMD was composed of magnetorheological (MR) damper and it was installed on the top floor of the example building. Control performance of the STMD mainly depends on the control algorithn. Fuzzy logic controller (FLC) was selected as a control algorithm for the STMD. Because composing fuzzy rules and tuning membership functions of FLC are difficult task, evolutionary optimization algorithm (EOA) was used to develop the FLC. After numerical simulations, it has been seen that the STMD controlled by the EOA-optimized FLC can effectively reduce seismic responses fo the tilted tall building.

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

In this paper, the dynamic response was analyzed by performing linear dynamic analysis using historic earthquake loads on twisted-shaped structures and fixed structure among free-form high-rise structures with atypical elevation shape following prior studies. In addition, the dynamic characteristics of the analysis models according to the plane rotation angle of the twisted structure were compared and analyzed. As a result of the analysis, as the plane rotation angle of the twisted structure increased, the interlayer deformation rate increased in the high-rise part of 50th floors or more. The story shear force and the story absolute acceleration were similar in the entire structure. In the case of the story shear force, the response of the twisted shape model was rather reduced in the middle part. As a result of analyzing the dynamic response, the vulnerable layer where the response amplification of the twisted structure occurs was found to be 31st story.

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

In this study, experiments and simulations were performed for fillet joint friction stir welding according to tool shape and welding conditions. Conventional butt friction stir welding has good weldability because heat is generated by friction with the bottom of the tool shoulder. However, in the case of fillet friction stir welding, the frictional heat is not sufficiently generated at the bottom of the tool shoulder due to the shape of the tool and the shape of the joint. Therefore, it is important to sufficiently generate frictional heat by slowing the welding speed as compared to butt welding. In this study, experiments and simulations were carried out on an aluminum battery housing made by friction stir welding an extruded material with a fillet joint. The temperature of the structure was measured using a thermocouple during welding, and the heat source was calculated through correlation analysis. Thermal elasto-plastic analysis of the structure was carried out using the calculated heat source and geometric boundary conditions. It is confirmed that the experimental results and the simulation results are well matched. Based on the results of the study, the deformation of the structure can be calculated through simulation even if the tool shape and welding process conditions change.

In this study, structural characteristics were analyzed by combining gravity load and lateral loads such as seismic loads through static analysis of example structures, and the static characteristics of the twisted structure according to the plane rotation angle were also analyzed. Example structures were selected as regular structure, and twisted structures; 1.0, 2.0, and 3.0 degree angle of rotation per story, and static analysis was performed by the load combination case 1 and case 2. As a result the story drift ratio of the twisted-shaped structure also increased as the plane rotation angle per story increased. The eccentricity according to the load combination was the highest in the lower stories of all analysis models, and the eccentricity was found to be larger as the rotation angle decreased. The twisted-shaped structure was more responsible for the bending moment of the column than the regular structure, and the vertical member axial force of all analysis models was almost similar.

In this study, a tuned mass damper(TMD) was installed to control the displacement response to earthquakes by generalizing to six analysis models according to the shape of the upper structure based on the case of various large spatial structures around the world. The six analysis models are ribbed type, latticed type, elliptical type, gable type, barrel type, and stadium type composed of 3D arch trusses. In this paper, ribbed type, latticed type and elliptical type were analyzed. The mass of each TMD was set to 1% of the total structural mass. Result of analyzing the optimal number and position of the analysis model, the displacement response control was the most excellent in the model with 6 and 8 TMDs, and the displacement response decreased in most cases. The displacement response control was better with installing the TMD at the edge point than focusing the TMD at the center of the analysis model. However, when 10 or more TMDs are installed or concentrated in the center, large loads intensively act on the structure, resulting in increased displacement. Therefore, although it is slightly different depending on the shape, it is judged that the displacement response control is the best to install 6 and 8 TMDs at the close to the edge point.

In this study, a tuned mass damper(TMD) was installed to control the displacement response to earthquakes by generalizing to six analysis models according to the shape of the upper structure based on the case of various large spatial structures around the world. The six analysis models are ribbed type, latticed type, elliptical type, gable type, barrel type, and stadium type composed of 3D arch trusses. In this paper, ribbed type, latticed type and elliptical type were analyzed. The mass of each TMD was set to 1% of the total structural mass. Result of analyzing the optimal number and position of the analysis model, the displacement response control was the most excellent in the model with 6 and 8 TMDs, and the displacement response decreased in most cases. The displacement response control was better with installing the TMD at the edge point than focusing the TMD at the center of the analysis model. However, when 10 or more TMDs are installed or concentrated in the center, large loads intensively act on the structure, resulting in increased displacement. Therefore, although it is slightly different depending on the shape, it is judged that the displacement response control is the best to install 6 and 8 TMDs at the close to the edge point.

In this paper, the displacement response to seismic loads was analyzed after installing TMD in spatial structures and high-rise buildings. In the case of a spatial structures, since it exhibits complex dynamic behavior under the influence of various vibration modes, it is not possible to effectively control the seismic response by installing only one TMD, unlike ordinary structures. Therefore, after installing eight TMDs in the structure, the correlation between displacement response and mass ratio was examined while changing the mass. The TMD must be designed to have the same frequency as the structure frequency so that the maximum response reduction effect can be exhibited. It can be confirmed that the most important variable is to select the optimal TMD mass in order to install the TMD on the structure and secure excellent control performance against the earthquake load. As a result of analyzing the TMD mass ratio, in the case of high-rise buildings, a mass ratio of 0.4% to 0.6% is preferable. In spatial structures, it is desirable to select a mass ratio of 0.1% to 0.2%. Because this study is based on the theoretical study based on numerical analysis, in order to design a TMD for a real structure, it is necessary to select within a range that does not affect the safety of the structure.

The cast iron pipe protection of submarine cables has a bump in the connection, so the guide device for checking the position and location of the submarine cable must pass through the curved surface. Since the connection is present at a regular intervals, impact loads are periodically applied, affecting the durability of the guide device. In this study, the design was changed to improve the durability of guide device links. And for the analysis of the durability for link of guide device, the flexible dynamic analysis of the guide device was performed using MSC.Adams, and the dynamic stress acting on the link was calculated using MSR(Modal Stress Recovery) method. As a result, the dynamic stress is reduced by 17.9%~31.1%. In addition, durability was calculated for the initial model and the improved model. As a result, the durability of the new model was improved more than 200 % better than to the initial model.