• 한국추진공학회지
• /
• 제18권6호
• /
• pp.59-67
• /
• 2014

1 N급 단일추진제 하이드라진 추력기 개발모델에 대한 인수수준 랜덤 진동시험과 장기수명 연소시험이 수행되었다. 랜덤 진동시험 결과로부터 1 N급 추력기 개발모델로 구성된 이중추력기모듈의 고유 진동수는 부품수준 요구조건(100 Hz)을 상회하였으며, 구조적으로 강건함을 확인하였다. 또한 20 kg 이상의 추진제가 사용된 장기수명 연소시험 결과 연속모드 추력 감소는 약 7% 이하, 추력 불안정 현상은 ${\pm}5%$ 이내로 나타났다. 컴퓨터단층촬영을 이용해 추력기 내부의 촉매를 촬영한 결과 촉매의 손실은 약 7% 이하로 추력기 개발모델의 설계가 적절함을 보여주었다.

• Structural Engineering and Mechanics
• /
• 제29권5호
• /
• pp.505-530
• /
• 2008

This paper proposes the application of active multiple tuned mass dampers (AMTMD) for translational and torsional response control of a simplified two-degree-of-freedom (2DOF) structure, able to represent the dynamic characteristics of general asymmetric structures, under the ground acceleration. This 2DOF structure is a generalized 2DOF system of an asymmetric structure with predominant translational and torsional responses under earthquake excitations using the mode reduced-order method. Depending on the ratio of the torsional to the translational eigenfrequency, i.e. the torsional to translational frequency ratio (TTFR), of asymmetric structures, the following three cases can be distinguished: (1) torsionally flexible structures (TTFR < 1.0), (2) torsionally intermediate stiff structures (TTFR = 1.0), and (3) torsionally stiff structures (TTFR > 1.0). The even distribution of the AMTMD within the whole width and half width of the asymmetric structure, thus leading to three cases of installing the AMTMD (referred to as the AMTMD of case 1, AMTMD of case 2, AMTMD of case 3, respectively), is taken into account. In the present study, the criterion for searching the optimum parameters of the AMTMD is defined as the minimization of the minimum values of the maximum translational and torsional displacement dynamic magnification factors (DMF) of an asymmetric structure with the AMTMD. The criterion used for assessing the effectiveness of the AMTMD is selected as the ratio of the minimization of the minimum values of the maximum translational and torsional displacement DMF of the asymmetric structure with the AMTMD to the maximum translational and torsional displacement DMF of the asymmetric structure without the AMTMD. By resorting to these two criteria, a careful examination of the effects of the normalized eccentricity ratio (NER) on the effectiveness and robustness of the AMTMD are carried out in the mitigation of both the translational and torsional responses of the asymmetric structure. Likewise, the effectiveness of a single ATMD with the optimum positions is presented and compared with that of the AMTMD.

• Structural Engineering and Mechanics
• /
• 제55권6호
• /
• pp.1261-1278
• /
• 2015

Due to their low intrinsic damping, stay cables in cable-stayed bridges have often exhibited unanticipated and excessive vibrations which result in increasing maintenance frequency and disruption to normal operations of the entire bridges. Mitigation of undesired cable vibration can be achieved by attaching an external damping device near the anchorage. High Damping Rubber (HDR) dampers have many advantages such as compact size, better aesthetics, easy maintenance, temperature stability, and cost benefits; therefore, they have been widely used to increase cable damping. Although a single damper has been shown to reduce cable vibrations, it is not the most effective method due to geometric constraints. This paper proposes the use of two HDR dampers to improve effectiveness and robustness in suppressing cable vibration. Oscillation parameters of the cable-dampers system were investigated in detail by modeling the stay cable as a taut string and each HDR damper as complex-valued impedance and by using an analytical formulation of the complex eigenvalue problem. The problem of two HDR dampers arbitrarily located along a cable is solved and the solution is discussed. Asymptotic formulas to calculate the damping ratios of the cable with two HDR dampers installed near the anchorage(s) are proposed and compared with the exact solutions. Further, a design example is presented in order to justify the methodology. The results of this study show that when the two HDR dampers are installed close to each other on the same end of the cable, some interaction between the dampers leads to reduced damping ratio. When the dampers are on the opposite ends of the cable, they are effective in increasing damping ratio and can provide better vibration reduction to multiple modes.

• Smart Structures and Systems
• /
• 제24권1호
• /
• pp.53-65
• /
• 2019

Misaligned wind-wave and seismic loading render offshore wind turbines suffering from excessive bi-directional vibration. However, most of existing research in this field focused on unidirectional vibration mitigation, which is insufficient for research and real application. Based on the authors' previous work (Sun and Jahangiri 2018), the present study uses a three dimensional pendulum tuned mass damper (3d-PTMD) to mitigate the nacelle structural response in the fore-aft and side-side directions under wind, wave and near-fault ground motions. An analytical model of the offshore wind turbine coupled with the 3d-PTMD is established wherein the interaction between the blades and the tower is modelled. Aerodynamic loading is computed using the Blade Element Momentum (BEM) method where the Prandtl's tip loss factor and the Glauert correction are considered. Wave loading is computed using Morison equation in collaboration with the strip theory. Performance of the 3d-PTMD is examined on a National Renewable Energy Lab (NREL) monopile 5 MW baseline wind turbine under misaligned wind-wave and near-fault ground motions. The robustness of the mitigation performance of the 3d-PTMD under system variations is studied. Dual linear TMDs are used for comparison. Research results show that the 3d-PTMD responds more rapidly and provides better mitigation of the bi-directional response caused by misaligned wind, wave and near-fault ground motions. Under system variations, the 3d-PTMD is found to be more robust than the dual linear TMDs to overcome the detuning effect. Moreover, the 3d-PTMD with a mass ratio of 2% can mitigate the short-term fatigue damage of the offshore wind turbine tower by up to 90%.

• 지식경영연구
• /
• 제22권1호
• /
• pp.139-154
• /
• 2021

기업 경영에 있어 환경적 위험이 증대되면서, 외부 충격 이후에 빠르게 일상 운영수준으로 복귀하는 능력인 회복역량에 대한 관심이 증대되고 있다. 이에 본 논문에서는 기업의 회복역량에 대한 개념적 모형을 제시하고, 이를 실증적으로 검증하고자 한다. 기존 연구를 기반으로 회복역량의 하위 구성개념을 강건성, 대체성, 자원동원성 및 신속성으로 구분하였으며, 선행요인으로 기업의 지식경영활동을 제시하였다. 회복역량을 매개변인으로 고려하면서, 기업의 성과에 영향을 미칠 것으로 가정하였다. 지식경영활동, 회복역량 및 성과로 이어지는 구조모형을 검증하기 위하여, 체계적으로 기업 대상 설문을 설계하여 조사를 시행하였다. 지식경영활동 외에 개별 기업의 회복역량을 높일 수 있는 독립변수들에 대한 탐색적 연구가 필요함과 성과에 대한 세분화된 검증이 필요함을 향후 연구방향으로 제시하였다.

• 시스템엔지니어링학술지
• /
• 제16권2호
• /
• pp.27-37
• /
• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Smart Structures and Systems
• /
• 제31권1호
• /
• pp.57-68
• /
• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• Smart Structures and Systems
• /
• 제31권3호
• /
• pp.259-273
• /
• 2023

Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affecting the accuracy and stability of RTHS. To this end, the authors have proposed a model-based adaptive control strategy with a Kalman filter (MAC-KF). In the proposed method, the time delay is mainly mitigated by a parameterized feedforward controller, which is designed using the discrete inverse model of the control plant and adjusted using the KF based on the displacement command and measurement. A feedback controller is employed to improve the robustness of the controller. The objective of this study is to further validate the power of dealing with a nonlinear control plant and to investigate the potential challenges of the proposed method through actual experiments. In particular, the effect of the order of the feedforward controller on tracking performance was numerically investigated using a nonlinear control plant; a series of actual RTHS of a frame structure equipped with a magnetorheological damper was performed using the proposed method. The findings reveal significant improvement in tracking accuracy, demonstrating that the proposed method effectively suppresses the time delay in RTHS. In addition, the parameters of the control plant are timely updated, indicating that it is feasible to estimate the control plant parameter by KF. The order of the feedforward controller has a limited effect on the control performance of the MAC-KF method, and the feedback controller is beneficial to promote the accuracy of RTHS.

• Structural Engineering and Mechanics
• /
• 제84권2호
• /
• pp.143-154
• /
• 2022

Corrosion of steel reinforcement is considered as the main cause of concrete structures deterioration, especially those under humid environmental conditions. Hence, fiber reinforced polymer (FRP) bars are being increasingly used as a replacement for conventional steel owing to their non-corrodible characteristics. However, predicting the shear strength of beams reinforced with FRP bars still challenging due to the lack of robust shear theory. Thus, this paper aims to develop an explicit data driven based model to predict the shear strength of FRP reinforced beams using multi-objective evolutionary polynomial regression analysis (MOGA-EPR) as data driven models learn the behavior from the input data without the need to employee a theory that aid the derivation, and thus they have an enhanced accuracy. This study also evaluates the accuracy of predictive models of shear strength of FRP reinforced concrete beams employed by different design codes by calculating and comparing the values of the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²), and percentage of prediction within error range of ±20% (a20-index). Experimental database has been developed and employed in the model learning, validation, and accuracy examination. The statistical analysis illustrated the robustness of the developed model with MAE, RMSE, 𝜇, 𝜎, R², and a20-index of 14.6, 20.8, 1.05, 0.27, 0.85, and 0.61, respectively for training data and 10.4, 14.1, 0.98, 0.25, 0.94, and 0.60, respectively for validation data. Furthermore, the developed model achieved much better predictions than the standard predictive models as it scored lower MAE, RMSE, and 𝜎, and higher R² and a20-index. The new model can be used in future with confidence in optimized designs as its accuracy is higher than standard predictive models.

• Smart Structures and Systems
• /
• 제32권5호
• /
• pp.319-338
• /
• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.