• Smart Structures and Systems
• /
• 제16권1호
• /
• pp.47-65
• /
• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• Earthquakes and Structures
• /
• 제16권5호
• /
• pp.523-532
• /
• 2019

Different types of gas reservoir such as Liquid Natural Gas (LNG) are among the strategic infrastructures, and have great importance for any government or their private owners. To keep the tank and its contents safe during earthquakes especially if the contents are of hazardous or flammable materials; using seismic protection systems such as base isolator can be considered as an effective solution. However, the major deficiency of this system can be the large deformation in the isolation level which may lead to the failure of bearing system. In this paper, as a solution, the efficacy of an optimally designed combined vibration control system, the combined laminated rubber isolator and rotational friction damper, is investigated to evaluate the enhancement of an existing metal tank response under both far- and near-field earthquakes. Responses like impulsive and convective accelerations, base shear, and sloshing height are studied herein. The probabilistic framework is used to consider the uncertainties in the structural modeling, as well as record-to-record variability. Due to the high calculation cost of probabilistic methods, a simplified structural model is used. By using the Mont-Carlo simulation approach, it is revealed that this combined isolation system is a highly reliable system which provides considerable enhancement in the performance of reservoir, not only leads to the reduction of probability of catastrophic failure of the tank but also decrease the reservoir damage during the earthquake. Moreover, the relative displacement of the isolation level is controlled very well by this combined system.

• 한국구조물진단유지관리공학회 논문집
• /
• 제26권1호
• /
• pp.10-18
• /
• 2022

국내 발생 지진파형을 분석하여 중진지역 특성을 고려하고 내진설계기준에 부합하는 한국형 인공지진파를 생성하였으며, 획일적이고 미관을 손상시키는 일본식 내진보강 공법을 지양하고 한국형 중진지역의 특징을 반영하여 지진의 빈도가 적고 강도가 비교적 강하지 않은 국내 실정에 적합한 학교 건물의 내진보강 공법을 개발하였다. 이를 바탕으로 현재 과다 설계되어 있는 학교 내진보강 시설물을 중진지역 특성에 맞게 최적화하여 내진 안전성 평가를 수행하였으며, 기존 학교건물의 내진성능평가에 비해 미적인 요소를 고려하고 효율성 있는 구조기법을 적용한 합리적 보강 기법을 제안하였다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제55권2호
• /
• pp.45-51
• /
• 2006

In this paper, we propose a new architecture of Information Granulation based genetically optimized Self-Organizing Fuzzy Polynomial Neural Networks (IG_gSOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially information granulation and genetic algorithms. The proposed IG_gSOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). To evaluate the performance of the IG_gSOFPNN, the model is experimented with using two time series data(gas furnace process and NOx process data).

• Structural Monitoring and Maintenance
• /
• 제6권4호
• /
• pp.317-346
• /
• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권8호
• /
• pp.561-570
• /
• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• 한국시뮬레이션학회논문지
• /
• 제29권3호
• /
• pp.49-55
• /
• 2020

발사체의 사거리 증대는 중요한 성능개선 목표 중 하나이다. 일반적으로 발사체 비행탄두의 형상은 공기역학 및 구조적인 요소를 복합적으로 고려하여 선정한다. 몸체, 탄두부 및 탄미부 형상의 선정은 공기역학적 설계에 중요한 영향을 미친다. 발사체 비행탄두 형상의 주요 설계 요소는 공기역학적 항력이다. 공기역학적 항력은 발사체의 운동과 반대 방향으로 작용하는 공기역학적 힘이다. 준실험적 기법을 이용하여 탄두부, 탄미부 및 몸체 형상이 발사체의 공기역학적 특성에 미치는 영향을 분석하기 위한 연구를 수행하였다. 여러 가지 비행탄두 형상 변수에 대한 연구를 수행하였으며, 최대 사거리 성능 분석에는 탄도 모사분석 모델을 사용하였다. 발사체 비행탄두 형상 최적화를 이용한 사거리 증대 가능성을 분석하고, 형상 변수 최적화에 의한 사거리 증대 효과를 확인하였다.

• Computers and Concrete
• /
• 제29권 6호
• /
• pp.375-391
• /
• 2022

This paper examined the impact of the cross-sectional structure on the structural results under different loading conditions of reinforced concrete (RC) members' management limited in Carbon Fiber Reinforced Polymers (CFRP). The mechanical properties of CFRC was investigated, then, totally 32 samples were examined. Test parameters included the cross-sectional shape as square, rectangular and circular with two various aspect rates and loading statues. The loading involved concentrated loading, eccentric loading with a ratio of 0.46 to 0.6 and pure bending. The results of the test revealed that the CFRP increased ductility and load during concentrated processing. A cross sectional shape from 23 to 44 percent was increased in load capacity and from 250 to 350 percent increase in axial deformation in rectangular and circular sections respectively, affecting greatly the accomplishment of load capacity and ductility of the concentrated members. Two Artificial Intelligence Models as Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) were used to estimating the tensile and flexural strength of specimen. On the basis of the performance from RMSE and RSQR, C-Shape CFRC was greater tensile and flexural strength than any other FRP composite design. Because of the mechanical anchorage into the matrix, C-shaped CFRCC was noted to have greater fiber-matrix interfacial adhesive strength. However, with the increase of the aspect ratio and fiber volume fraction, the compressive strength of CFRCC was reduced. This possibly was due to the fact that during the blending of each fiber, the volume of air input was increased. In addition, by adding silica fumed to composites, the tensile and flexural strength of CFRCC is greatly improved.

• 항공우주시스템공학회지
• /
• 제12권3호
• /
• pp.70-78
• /
• 2018

탄소섬유 복합재료를 적용하는 일체형 접이식 날개 개발에 대한 연구를 수행하였다. 설계 요구조건을 검토하고 상용 소프트웨어를 적용한 최적설계기법을 통해 복합재료 날개 설계를 실시하였다. 복합재료 제조공정인 핫프레스, 펄트루전, 오토클레이브를 평가하고 성능과 비용을 고려하여 일체형 날개제작에 가장 적합한 다중공정을 결정하였다. 설계개념 확정을 위해 두 차례의 설계개발시험으로 제작공정을 검증하고 구조해석을 통해 복합재료 날개의 강성과 강도를 예측하였다. 시험하중을 먼저 산출하고 양쪽 날개를 대상으로 설계제한하중과 설계극한하중에 대한 정하중 구조시험을 수행하였다. 그 결과, 시험의 각 평가기준을 만족하였으며 일련의 구조해석과 시험을 통해 구조안전성을 검증하였다.

• 한국전산구조공학회논문집
• /
• 제27권4호
• /
• pp.231-238
• /
• 2014

건물의 경우, 용도 변경에 따른 중력하중 변화, 시공 단계에 따라 중력하중 변화 등이 구조물 시스템에 영향을 미친다. 따라서, 본 연구에서는 시스템 식별 변수 설정에 있어 기존에 강성만을 변수로 설정한 방법에 추가적으로 질량을 변수로 설정하여 시스템을 식별하는 기법을 제안한다. 계측한 동특성과 FE모델에서 추출한 동특성 간의 차이를 최소화하여 변수를 탐색하게 된다. 최소화 기법으로 변형 유전 알고리즘을 적용하였다. 보다 전역적 해탐색을 위해 변형 유전 알고리즘은 더 넓은 해 탐색 공간에서 해를 찾는다. 철골 보 구조물의 시뮬레이션을 통해 본 연구가 제시한 기법을 검증하였고 변형 유전 알고리즘과 기존의 단순 유전 알고리즘의 성능을 비교하였다. 또한, 강성 식별만을 수행한 기존 연구의 방법과 본 연구가 제시한 기법간의 차이를 비교하였다.