This study numerically compares optimum solutions generated by element- and node-wise topology optimization designs for free vibration structures, where element-and node-wise denote the use of element and nodal densities as design parameters, respectively. For static problems optimal solution comparisons of the two types for topology optimization designs have already been introduced by the author and many other researchers, and the static structural design is very common. In dynamic topology optimization problems the objective is in general related to maximum Eigenfrequency optimization subject to a given material limit since structures with a high fundamental frequency tend to be reasonable stiff for static loads. Numerical applications topologically maximizing the first natural Eigenfrequency verify the difference of solutions between element-and node-wise topology optimum designs.

본 논문에서는 컨테이너선의 선형 최적 설계 자동화와 관련하여 연구한 내용과 결과를 정리하였다. 컨테이너선은 일반적으로 프루우드 수 0.26 근처에서 운항하는 선박으로 이 속도에서 운항하는 선박 전용 선형 최적 설계 자동화를 구현하기 위하여 최적화 알고리 즘, 선형 변경 알고리즘, 선박 성능 예측 알고리즘, 자동화 알고리즘 그리고 반복적 계산 기법을 적용하여 컨테이너선의 선형 최적 설계 자동화가 가능한 수치해석 컴퓨터 프로그램을 개발하였으며, HOTCONTAINER라고 명명하였다. 본 연구에서는 선형 최적 설계를 위한 설 계 변수의 적절한 선정을 위하여 민감도 분석 알고리즘을 개발하여 적용하였다. 개발된 선형 최적 설계 자동화 알고리즘의 신뢰성과 실 선 적용성을 파악하기 위하여 세계적으로 다양한 연구가 진행된 컨테이너 선박인 KCS 선박을 대상 선박으로 하여 선형 최적 설계 자동 화 수치해석을 수행하여 그 결과물로써 최적 선박을 도출하고, 대상 선박과 최적 선박의 조파저항과 파계 그리고 파고를 비교하였다. 결 론적으로 최적 선박이 대상 선박과 비교하여 조파저항이 47.63% 감소한 것을 볼 수 있었으며, 배수량과 접수 표면적은 각각 0.50%, 0.39% 감소한 것을 볼 수 있었다.

This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS’s rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment. K

OWEC(Overtopping Wave Energy Converter)는 월파된 파도를 이용한 파력발전시스템이라한다. OWEC의 성능 및 안전성은 파고, 주기 등 파도의 특성에 의해 영향을 받는다. 따라서 해역 특성에 따른 OWEC의 최적 형상과 구조안전성에 관한 연구가 필요하다. 본 연구 에서는 울릉읍 연안 해양 환경 데이터를 이용하였으며, SPH(Smoothed Particle Hydrodynamics) 입자법 해석을 통해 기존 케이슨 하부 구조에 변화를 준 모델 4개를 비교하여 월파 효율을 분석하였다. 그 결과, 하부 구조의 변경 및 경량화가 가능함을 확인하였다. 최적화 해석을 통 해 설계 하중에 내하력을 가지는 하부 구조인 새로운 트러스형 구조를 제안하였다. 이후 부재 직경 및 두께를 설계변수로 하는 사례 연구 를 통해 허용응력조건 하에서 구조 안전성의 확보를 확인하였다. 주기적인 파랑 하중을 받기 때문에 제안하는 구조의 고유 진동수와 해 당 해역의 파주기를 비교하였으며, 1년 재현 주기의 파랑을 하중으로 한 조화응답해석을 수행하였다. 제안하는 하부 구조는 동일 가진력 에서 기존 설계 대비 응답의 크기가 감소하였으며, 기존 대비 32% 이상의 중량 절감을 수행하였다.

Reinforcement learning (RL) is widely applied to various engineering fields. Especially, RL has shown successful performance for control problems, such as vehicles, robotics, and active structural control system. However, little research on application of RL to optimal structural design has conducted to date. In this study, the possibility of application of RL to structural design of reinforced concrete (RC) beam was investigated. The example of RC beam structural design problem introduced in previous study was used for comparative study. Deep q-network (DQN) is a famous RL algorithm presenting good performance in the discrete action space and thus it was used in this study. The action of DQN agent is required to represent design variables of RC beam. However, the number of design variables of RC beam is too many to represent by the action of conventional DQN. To solve this problem, multi-agent DQN was used in this study. For more effective reinforcement learning process, DDQN (Double Q-Learning) that is an advanced version of a conventional DQN was employed. The multi-agent of DDQN was trained for optimal structural design of RC beam to satisfy American Concrete Institute (318) without any hand-labeled dataset. Five agents of DDQN provides actions for beam with, beam depth, main rebar size, number of main rebar, and shear stirrup size, respectively. Five agents of DDQN were trained for 10,000 episodes and the performance of the multi-agent of DDQN was evaluated with 100 test design cases. This study shows that the multi-agent DDQN algorithm can provide successfully structural design results of RC beam.

The Ti-6Al-4V lattice structure is widely used in the aerospace industry owing to its high specific strength, specific stiffness, and energy absorption. The quality, performance, and surface roughness of the additively manufactured parts are significantly dependent on various process parameters. Therefore, it is important to study process parameter optimization for relative density and surface roughness control. Here, the part density and surface roughness are examined according to the hatching space, laser power, and scan rotation during laser-powder bed fusion (LPBF), and the optimal process parameters for LPBF are investigated. It has high density and low surface roughness in the specific process parameter ranges of hatching space (0.06–0.12 mm), laser power (225–325 W), and scan rotation (15°). In addition, to investigate the compressive behavior of the lattice structure, a finite element analysis is performed based on the homogenization method. Finite element analysis using the homogenization method indicates that the number of elements decreases from 437,710 to 27 and the analysis time decreases from 3,360 to 9 s. In addition, to verify the reliability of this method, stress–strain data from the compression test and analysis are compared.

In this study, it was investigated about optical simulation in high brightness and high uniformity direct-type backlight design for medical application. Direct-type backlight has been used high-brightness backlight such as Medical LCD application. The key parameter in designing direct-type backlight was consists of three geometrical dimension such as the distance of two lamps, the gap of lamp and reflection plate and the number of lamps. It has many of variations in optical design and it causes the different properties in backlight system. It shows the best values of above parameters; 26mm of the distance of two lamps, 4.5mm of the gap of lamp and reflection plate and 16 lamps. And we produced the specimen as above condition, and acquired good result in backlight such as the value of the brightness is 6423 nit in center of emission area and less than 5% in brightness uniformity. It shows the effective ways of designing backlight system using optical simulation method for medical LCD application.

최근 토목공학 분야 내 현장조건을 구현할 수 있는 스마트 건설 기술의 요소기술로서 3D 프린팅 기술의 적용 분야 가 확대되고 있다. 센서기술의 보조도구, 모듈러 시공상 적용 등으로 다양하게 활용되고 있는 가운데 3D 프린팅 기술을 단순 부재 제작이 아닌 각각의 부재들이 최대 성능을 발휘할 수 있는 최적설계 도출 방안으로 활용하고자 한다. 이를 위해 3D 프린 팅 재질인 필라멘트를 활용하더라도 신뢰성 있는 최적설계가 도출이 가능한지에 대한 연구가 선행되어야 하며, 이에 본 연구에 서는 지반보강재 중 하나인 지오셀 관련 선행연구 결과와 필라멘트의 물성치가 적용된 해석 결과와의 비교를 통해 재료적 신뢰 성을 검증하고자 한다. 해석 결과, 지오셀 구성요소에 따른 보강성능의 경향이 기존 선행연구 결과와 일치함을 확인하였기에 필 라멘트를 활용하더라고 충분히 신뢰성 있는 최적설계가 도출이 가능할 것이라 판단된다.

대기오염물질과 온실가스 배출량을 저감 시키기 위한 배기 후처리 장치에 대한 연구는 활발히 진행 중이지만 그 중 선박용 입 자상물질/질소산화물(PM/NOx) 동시저감 장치에서는 엔진에 미치는 배압 및 필터 담체 교체에 대한 문제가 발생하고 있다. 본 연구에서는 PM/NOx를 동시저감 할 수 있는 일체형 장치의 최적 설계를 위해 장치 내부 유동과 입·출구 압력을 통한 배압의 변화를 연구하여 적절한 기준을 제시하였다. Ansys Fluent를 활용하여 디젤미립자필터(DPF) 및 선택적촉매환원법(SCR)에 다공성 매체 조건을 적용하였고 공극률은 30 %, 40 %, 50 %, 60 % 및 70 %로 설정하였다. 또한, 엔진 부하에 따른 Inlet 속도를 경계 조건으로 7.4 m/s, 10.3 m/s, 13.1 m/s 및 26.2 m/s로 적 용하여 배압에 미치는 영향을 분석하였다. CFD 분석 결과, 장치의 입구 온도 보다 입구 속도에 따른 배압의 변화율이 크고 최대 변화율은 27.4 mbar였다. 그리고 모든 경계 조건에서의 배압이 선급 기준인 68 mbar를 초과하지 않았기 때문에 1800 kW 선박에 적합한 장치로 평가 되었다.

Screws are the closest and most familiar mechanical elements of everyday life, and are generally used so widely that there is no machine without screws. Screws are used to make it easier to combine objects with objects, and are also used to transfer large forces from machines. The most influential factor in the coupling of these screws is the effective diameter. If the effective diameter is not accurate, the support cannot be finished or endured, leading to a major accident. The importance of these screws cannot be ignored, so in this study, the effective diameter was measured using the three-wire method, the screw micrometer method, and the projector method, and the one-way factor design method was applied to determine the exact method compared to the KS standard.

Korea Radioactive Waste Agency (KORAD), regulatory body and civic groups are calling for an infrastructure system that can more systematically and safely manage data on the results of radioactive waste sampling and nuclide analysis in accordance with radioactive waste disposal standards. To solve this problem, a study has been conducted on the analysis of the nuclide pattern of radioactive waste on the nuclide data contained in low-and intermediate-level radioactive waste. This paper will explain the optimal repackaged algorithm for reducing radioactive waste based on previous research results. The optimal repackaged algorithm for radioactive waste reduction is comprised based on nuclide pattern association indicators, classification by nuclide level of small-packaged waste, and nuclide concentration. Optimization simulation is carried out in the order of deriving nuclide concentration by small-packaged, normalizing drum minimization as a function of purpose, normalizing constraints, and optimization. Two scenarios were applied to the simulation. In Scenario 1 (generating facilities and repackaged by medium classification without optimization), it was assumed that there are 886 low-level drums and 52 very low-level drums. In Scenario 2 (generating facilities and repackaged by medium classification with optimization), 708 and 230 drums were assigned to the low-level and very low-level drums, respectively. As a result of the simulation, when repackaged in consideration of the nuclide concentration and constraints according to the generating facility cluster & middle classification by small package (Scenario 2) the low-level drum had the effect of reducing 178 drums from the baseline value of 886 drums to 708 drums. It was found that the reduced packages were moved to the very low-level drum. The system that manages the full life-cycle of radioactive waste can be operated effectively only when the function of predicting or tracking the occurrence of radioactive waste drums from the source of radioactive waste to the disposal site is secured. If the main factors affecting the concentration and pattern of nuclides are systematically managed through these systems, the system will be used as a useful tool for policy decisions that can prevent human error and drastically reduce the generation of disposable drums.

Most of automobile steering parts are manufactured through the multi-stage cold forging process using round-bar drawn materials. The same process is applied to the ball stud parts of the outer ball joint, and various research activities are being carried out to reduce the extreme manufacturing cost in order to survive in the limitless competition. In this paper, we present a quantitative prediction method for the limiting life of the die as a method for cost reduction in the multi-stage cold forging process. The load on the die was minimized by distributing the forming load based on process optimization through finite element analysis. In addition, based on the quantitative prediction algorithm of the limiting life of the die, the application of the split die and the optimization of the phosphate treatment of the material surface are presented as a conclusion as a method to improve the limiting life of the die.

본 논문에서는 1차원 오일러 보 요소(Euler-Bernoulli Beam Element)를 이용한 회전익기 축계에 대한 중량 최적설계를 수행하였다. 회전 축계의 특성을 고려해 비틀림(Torsion)과 베어링과 같은 축지지 강성 및 플랜지(Flange) 질량을 모두 고려하였고, 동적 안전성 확 보를 위해 고유치 해석을 수행하여 임계속도(Critical Speed)와 기어박스로부터 오는 치 변형 가진을 회피할 수 있도록 하였다. 축의 길 이는 고정된 상태에서 두께와 반경을 조절하여 중량 최적화를 수행하였으며, 최적화 과정은 2단계로 나누어 진행하였다. 1단계에서 는 비틀림 강도를 제약조건으로 하여 중량을 최적화한 후 2단계에서는 축계 안정성 확보 기준(Headquarters, U.S. Army Material Command, 1974)에 따라 축의 비틀림 강도에 대한 제약조건을 만족시키며, 축의 1차 모드가 임계속도를 회피할 수 있도록 축 1차모드 와 임계속도의 차이가 최대가 되도록 최적화를 진행하였다. 주어진 1차원 보 요소를 이용하여 최적설계를 한 결과를 3차원 유한요소 모델과 실제 제작된 축게의 시험결과와 비교하여 제안된 방법을 검증하였다.

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.

현재 국내외적으로 다양한 강재 댐퍼의 형상에 대한 연구가 이뤄지고 있다. 강재 댐퍼는 제진장치 중 하나로 항복을 통해 지진에너지를 흡수 및 소산하여 본 구조물을 보호한다. 최근 적용되고 있는 면내 전단 변형에 의해 작동하는 댐퍼는 응력이 특정 부위에 집중되어 재료의 대부분이 본래의 역량을 발휘하지 못하는 한계가 있었다. 따라서, 본 연구에서는 이 한계를 극 복하고자 전역 최적화 기법 중 하나인 뻐꾸기 탐색을 적용해 최적 형상을 설계하였다. 탐색된 최적 형상을 토대로 수치해석과 실제 실험을 통한 성능검증을 수행했다. 최적 형상으로 설계된 댐퍼는 안정적인 이력거동을 보이고, 높은 에너지 소산능력을 확 보하는 것으로 나타났다. 본 연구에서는 전역 최적화 기법을 적용한 최적 설계 방법을 제시하고 그 결과를 검증함으로써, 다양한 형태의 공학적 문제 해결에 대한 적용 가능성을 제시하였다.

The purpose of this study was to develop an optimized hull-form of a coastal fishing vessel operating at high speed. In order to achieve the purpose of the study, HOTBOAT, that can perform an automatic hull-form optimal design of a coastal fishing vessel, was developed. HOTBOAT was composed of an objective function estimation algorithm and an optimization algorithm and a hull-form modification algorithm. In this study, the wave-making resistance was selected as an objective function and the potential-based panel method was applied to predict the objective function. SQP(sequential quadratic programming) method were adopted to predict the optimal direction and answer. Bell-shaped hull-form modification function method and NURBS(non-uniform rational B-spline) geometry modeling method were applied to modify the hull-form during the whole optimization process. HOTBOAT was applied to develop the optimal hull-form of a coastal fishing vessel with minimum wave resistance. The initial hull-form of the coastal fishing vessel was compared with the optimal hull-form. As a result of hull-form optimization, a coastal fishing vessel with a reduction of about 30% was developed compared with the initial hull-form and the displacement and the wetted surface area of the optimal hull-form was decreased to less than about 1% in comparison with the initial hull-form.