• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.334-340
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• 2013

This paper deals with the optimization of blade stiffened composite panels. The main objective of the research is to make response surfaces for the constraints. The response surface for warping thermal deformation was previously made for a fixed dimension composite structure. In this study, the dimensions of the blade stiffener were treated as design variables. This meant that a new response surface technique was required for the constraints. For the response surfaces, the lamination parameters, linear thermal expansions and dimensions of the structures were used as variables. A genetic algorithm was adopted as an optimizer, and an optimal result, which satisfied two constraints, was obtained. As a result, a new response surface was obtained, for predicting warping thermal deformation.

• 한국광학회:학술대회논문집
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• 한국광학회 1989년도 제4회 파동 및 레이저 학술발표회 4th Conference on Waves and lasers 논문집 - 한국광학회
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• pp.85-88
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• 1989

Introducing and optimizing it-significance to the Hopfield model, ten highly correlated binary images, i.e., numbers "0" to "9", are successfully stored and retrieved in a 6x8 node system. Unlike many other neural networks models, this model has stronger error correction capability for correlated images such as "6", "8", "3", and "9". the bit-significance optimization is regarded as an adaptive learning process based on least-mean-square error algorithm, and may be implemented with another neural nets optimizer. A design for electro-optic implementation including the adaptive optimization networks is also introduced.uding the adaptive optimization networks is also introduced.

• Steel and Composite Structures
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• 제47권4호
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• pp.513-521
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• 2023

The goal of this work is to create a new and improved GWO (Grey Wolf Optimizer), the so-called Robot GWO (RGWO), for dynamic and static target tracking involving multiple robots in unknown environmental conditions. From applying ourselves with the Gray Wolf Optimization Algorithm (GWO) and how it works, as the name suggests, it is a nature-inspired metaheuristic based on the behavior of wolf packs. Like other nature-inspired metaheuristics such as genetic algorithms and firefly algorithms, we explore the search space to find the optimal solution. The results also show that the improved optimal control method can provide superior power characteristics even when operating conditions and design parameters are changed.

• 한국의학물리학회지:의학물리
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• 제30권4호
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• pp.150-154
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• 2019

The objective of this study is to monitor the radiation doses delivered to a cardiac implantable electronic device (CIED) by comparing the absorbed doses calculated by a commercial treatment planning system (TPS) to those measured by an in vivo dosimeter. Accurate monitoring of the radiation absorbed by a CIED during radiotherapy is necessary to prevent damage to the device. We conducted this study on three patients, who had the CIED inserted and were to be treated with radiotherapy. Treatment plans were generated using the Eclipse system, with a progressive resolution photon optimizer algorithm and the Acuros XB dose calculation algorithm. Measurements were performed on the patients using optically stimulated luminescence detectors placed on the skin, near the CIED. The results showed that the calculated doses from the TPS were up to 5 times lower than the measured doses. Therefore, it is recommended that in vivo dosimetry be conducted during radiotherapy for CIED patients to prevent damage to the CIED.

• 대한조선학회논문집
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• 제48권4호
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• pp.325-329
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• 2011

Floating, production, storage and offloading (FPSO) is a production facility that refines and saves the drilled crude oil from a drilling facility in the ocean. The flare system in the FPSO is a major part of the pressure relieving system for hydrocarbon processing plants. The flare system consists of a number of pipes and complicated connection systems. Decision of pipe support types is important since the load on the support and the stress in the pipe are influenced by the pipe support type. In this study, we optimally determined the pipe support types that minimized the support cost while satisfying the design constraints on maximum support load, maximum nozzle load and maximum pipe stress ratio. Performance indices included in the design constraints for a specified design were evaluated by pipe structural analysis using CAESAR II. Since pipe support types were all discrete design variables, an evolutionary algorithm (EA) was used as an optimizer. We successfully obtained the optimal solution that reduced the support cost by 27.2% compared to the initial support cost while all the design requirements were satisfied.

• Structural Engineering and Mechanics
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• 제87권6호
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Steel and Composite Structures
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• 제49권1호
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• pp.91-107
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• 2023

An effective approach to promoting sustainability within the construction industry is the use of recycled aggregate concrete (RAC) as a substitute for natural aggregates. Ensuring the frost resilience of RAC technologies is crucial to facilitate their adoption in regions characterized by cold temperatures. The main aim of this study was to use the Random Forests (RF) approach to forecast the frost durability of RAC in cold locations, with a focus on the durability factor (DF) value. Herein, three optimization algorithms named Sine-cosine optimization algorithm (SCA), Black widow optimization algorithm (BWOA), and Equilibrium optimizer (EO) were considered for determing optimal values of RF hyperparameters. The findings show that all developed systems faithfully represented the DF, with an R² for the train and test data phases of better than 0.9539 and 0.9777, respectively. In two assessment and learning stages, EO - RF is found to be superior than BWOA - RF and SCA - RF. The outperformed model's performance (EO - RF) was superior to that of ANN (from literature) by raising the values of R² and reducing the RMSE values. Considering the justifications, as well as the comparisons from metrics and Taylor diagram's findings, it could be found out that, although other RF models were equally reliable in predicting the the frost durability of RAC based on the durability factor (DF) value in cold climates, the developed EO - RF strategy excelled them all.

• 한국강구조학회 논문집
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• 제17권6호통권79호
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• pp.661-672
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• 2005

본 연구에서는 많은 양의 함수 계산을 요구하는 확률론적 최적화 기법을 보다 효과적으로 강구조물에 적용하여 수행하고자 한다. 다양한 과학, 응용공학 분야에서 많은 시간이 소요되는 과정을 대체하는데 효과적인 도구로 출현한 인공신경망을 최적화 과정 중 많은 수의 유한요소 해석이 요구되는 재해석 문제에 적용함으로서 유한요소법의 평형방정식의 해의 근사해를 추정하여 재해석과정을 보다 간단하고 용이하게 수행하고자 한다. 또한 이용된 인공신경망의 학습효과의 개선을 위해 유전알고리즘을 적용한다. 확률론적 구조최적화 기법으로는 진화론적 방법에 기초한 알고리즘을 사용한다. 수치 예로써 전형적인 체적(중량)문제와 실 경비함수를 목적함수로 갖는 강구조물 모형에 본 연구의 알고리즘을 적용하여 본 알고리즘의 적용성과 타당성을 증명하였다.

• 한국기계가공학회지
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• 제19권7호
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• pp.7-15
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• 2020

Recently, the fourth industrial revolution has been presented as a new paradigm and additive manufacturing (AM) has become one of the most important topics. For this reason, process monitoring for each cross-sectional layer of additive metal manufacturing is important. Particularly, deep learning can train a machine to analyze, optimize, and repair defects. In this paper, image classification is proposed by learning images of defects in the metal cross sections using the convolution neural network (CNN) image labeling algorithm. Defects were classified into three categories: crack, porosity, and hole. To overcome a lack-of-data problem, the amount of learning data was augmented using a data augmentation algorithm. This augmentation algorithm can transform an image to 180 images, increasing the learning accuracy. The number of training and validation images was 25,920 (80 %) and 6,480 (20 %), respectively. An optimized case with a combination of fully connected layers, an optimizer, and a loss function, showed that the model accuracy was 99.7 % and had a success rate of 97.8 % for 180 test images. In conclusion, image labeling was successfully performed and it is expected to be applied to automated AM process inspection and repair systems in the future.

• Composites Research
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• 제35권1호
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• pp.31-37
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• 2022

본 연구에서는 복합재료 블레이드의 최적 구조설계 프레임워크를 개발하고 이를 헬리콥터 블레이드에 적용하여 구조설계를 수행하였다. 개발된 최적 설계 프레임워크는 유전자 알고리즘과 입자 군집 최적화 알고리즘을 결합한 PSGA를 활용해 구성하였다. 이는 블레이드 단면에 대한 유한요소 모델 생성, 2차원 단면 유한요소 해석, 그리고 1차원 회전 보 해석의 단계를 거쳐 최적화 결과를 도출해낸다. 설계 과정에서 각 단면들은 B-spline으로 구성되며, 유한요소 생성 프로그램인 Gmsh를 활용해 모델링 된다. 이를 활용하여 최적화 과정에서 각 변수마다 대응되는 2차원 유한요소모델을 생성해 블레이드의 구조해석을 수행했다. 본 연구에서 제안한 프레임워크를 HART II 블레이드에 적용하여 최적 구조 설계를 수행했다. 최적 설계 결과 회전익 로터에서 요구하는 구조적 특징을 유지하면서, 공진회피와 질량 등의 조건이 개선된 블레이드 형상을 도출하였다.