• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2004년도 춘계 학술발표대회 개요집
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• pp.39-41
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• 2004

This study is to optimize the condition of pulse parameters using the response surface method in micro pulse TIG welding of pleated type metallic filter. The input parameters used were pulse current, base current, pulse duty, frequency and welding speed and the hydraulic pressure was used as the output parameter. The central composite design was designed using second order regression model, As the results, the optimal welding condition to manufacture the pleated type metallic filter was obtained.

• Structural Engineering and Mechanics
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• 제68권5호
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• pp.563-573
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• 2018

Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

• Geomechanics and Engineering
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• 제31권1호
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• pp.113-127
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• 2022

The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R² greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R² and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

• 한국음향학회지
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• 제32권4호
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• pp.317-328
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• 2013

본 논문은 수중함에 부착되는 소나(sonar)에서 소음차단을 위하여 일반적으로 사용되는 다층구조의 설계 최적화를 수행하였다. 설계 목표로서는 자함 자체 기계가진 진동으로 인하여 음향센서에 유기되는 음압이 낮도록, 그리고 외부 표적 함정으로부터 방사되어오는 음에 기인한 소나의 수신 음압이 운용주파수 대역에서 높고 고른 음압을 갖도록 하는 두 가지 상반된 설계 목표를 고려하였다. 설계 변수로서는 다층구조 각층의 재료 물성치 선택에 따른 이산변수와 각 층의 두께 변수인 연속변수를 함께 고려하여, 각 변수의 최적화 과정에 따른 영향도를 분석 하였고, 최적화 방법으로서는 진화알고리즘을 적용하였다. 또한 최적화 과정으로서는 두 가지 목표를 각각 고려하는 경우와 동시에 두 가지 복합적인 목표를 고려하는 경우에 대한 설계 최적화를 수행하여, 각 경우에 대한 설계 목표치의 최대화 정도를 분석하였다.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• 한국안전학회지
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• 제27권5호
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• pp.148-157
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• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

• 대한기계학회논문집A
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• 제27권10호
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• pp.1793-1799
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• 2003

An optimal design of a multi-layered plate structure to endure high-velocity impact has been suggested by using size optimization after numerical simulations. The NET2D, a Lagrangian explicit time-integration finite element code for analyzing high-velocity impact, was used to find the parameters for the optimization. Three different materials such as mild steel, aluminum for a multi-layered plate structure and die steel for the pellet, were assumed. In order to consider the effects of strain rate hardening, strain hardening and thermal softening, Johnson-Cook model and Phenomenological Material Model were used as constitutive models for the simulation. It was carried out with several different gaps and thickness of layers to figure out the trend in terms of those parameters' changes under the constraint, which is against complete penetration. Also, the measuring domain has been shrunk with several elements to reduce the analyzing time. The response surface method based on the design of experiments was used as optimization algorithms. The optimized thickness of each layer in which perforation does not occur has been obtained at a constant velocity and a designated total thickness. The result is quite acceptable satisfying both the minimized deformation energy and the weight criteria. Furthermore, a conceptual idea for topology optimization was suggested for the future work.

• Korean Chemical Engineering Research
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• 제46권5호
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• pp.903-914
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• 2008

본 연구는 ethylene oxide로부터 monoethylene glycol을 주제품으로 생산하는 상용화된 실제 공정의 생산 능력 증가시에 필요한 공정 모사와 에너지 절감을 위한 최적화 연구로서, 공정에 관여하는 다성분계의 기/액 상평형 거동을 NRTL-RK식으로 나타내고, 필요한 총 91개의 2성분계쌍의 상호작용 파라미터 값들로는 8개의 2성분계쌍에 대해서는 Aspen $Plus^{TM}$ 상용 모사기(Ver. 2006)에 내장된 값, 28개의 쌍에 대해서는 상평형 데이터를 문헌에서 조사하여 회귀분석하고 나머지 2성분계에 대해서는 모사기 내의 추산 기능을 이용하여 구한 값을 사용하였으며, 공정 모사 결과와 실제 공정 데이터와의 비교를 통해 상평형 계산의 정확성을 확인한 후, 모사기에 내장된 민감도 분석 기능을 사용하여 전체 에너지 소모량에 대한 각 장치의 민감도를 조사하여 적절한 조절변수를 선정하고 모사기 내에 내장되어 있는 순차적 2차 계획법에 의한 최적화 기능을 이용하여 공정 전체의 에너지 절약을 위한 최적화 작업을 수행하였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.226-234
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• 2008

Grain design has always been a vital and integral part of Solid Rocket Motor(SRM) design. Basing on the design objectives set by the system designer, the SRM designer has many options available for selecting the Grain configuration. Many of the available configurations may fulfill the required parameters of volumetric loading fraction, web fraction & Length to diameter ratios and produce internal ballistic results that may be in accordance to the design objectives. However, for any given set of design objectives, it is deemed necessary that best possible configuration be selected, designed and optimized. Hence optimal results of all applicable configurations are vital to be attained in order to compare and finalize the design that will produce most efficient performance. Generally the engineers pay attention and have skills on a specific grain configuration. The designing methodologies and computer codes available usually focus on single grain configuration may it be Star, Wagon Wheel or slotted tube. Hardly one can find a software or a design methodology where all such configurations can be worked on jointly and not only adequate designs be found but optimal solutions reached by applying an optimization method to find final design best suited for any design objective. In the present work design requirements have been set, grain configurations have been selected and their designing has been conducted. The internal ballistic parameters have been calculated and after finding the preliminary design solutions, the optimal solutions have been found. In doing so, software has been developed comprising of computer programs for designing the 2D grains including Star, Wagon Wheel and Slotted Tube configurations. The optimization toolbox of Matlab Fmincon has been used for getting optimal solutions. The affects of all the independent geometric design variables on the optimized solutions have been analyzed. Based on results attained from Optimization Method, an in depth comparison of Grain Configurations and analysis of performance prediction outputs have been conducted to come to conclusion as to which grain configuration is ideal for the current design requirement under study.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.