• Journal of Contemporary Eastern Asia
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• 제12권1호
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• pp.49-63
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• 2013

This work identifies the key factors influencing the success of multidisciplinary, interdisciplinary, and trans-disciplinary R&D projects in transition economies by integrating knowledge management, organizational, inter/intra-collaboration (open-innovation), and leadership perspectives, while also addressing the perspective of the science of team science, which is an integrative approach to R&D. This is followed by providing the major sub-constructs of team science and policy implications to better facilitate multidisciplinary, interdisciplinary, and transdisciplinary R&D projects in knowledge-based transition economies.

• 공학교육연구
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• 제9권4호
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• pp.10-18
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• 2006

오늘날 공학도에게는 타 전공자들과 한 팀을 이루어 공동의 프로젝트를 효과적으로 진행해 나갈 수 있는 능력이 절실히 요구되고 있다. 대학에서는 이러한 요구를 충족시키기 위한 방안으로 복합학제 설계교육의 중요성이 커지고 있다. 본 논문에서는 동국대학교에서 수행하였던 복합학제 설계교육의 사례를 통해 그 효과를 정량적으로 측정하고 분석하여 보았다. 단일전공자로 구성된 팀들과 복합전공자로 구성된 팀들간의 학업성취도를 비교분석한 결과 복합팀의 학업성취도가 높은 것으로 나타났다. 또한 설문조사를 통해 학생들은 팀의 의사소통이 프로젝트를 진행하는데 중요한 요소라고 생각하였으며 이러한 결과는 복합학제 설계교육이 더욱 확대될 필요가 있으며 이를 통해 학생들이 사회에 나가기 전 수업을 통해 꾸준히 연습되어야 함을 보여준다.

• 한국CDE학회논문집
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• 제5권3호
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• pp.263-275
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• 2000

Multidisciplinary design optimization(MDO) can yield optimal design considering all the disciplinary requirements concurrently. A method to implement the collaborative optimization(CO) approach, one of the MDO methodologies, is developed using a pre-compiler “EzpreCompiler”, a design optimization library “EzOptimizer”, and a common object request broker architecture(CORBA) in distributed computing environment. The CO approach is applied to a mathematical example to show its applicability and equivalence to standard optimization(SO) formulation. In a realistic engineering problem such as optimal design of a two-member hub frame, optimal design of a speed reducer and initial design of a bulk carrier, the CO yields better results than the SO. Furthermore, the CO allows the distributed processing using the CORBA, which leads to reduction of overall computation time.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.170-175
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• 2001

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multiple objective genetic algorithm (MOGA), and a sample test case is presented to show the effects of optimizing the sequence with MOGA.

• Computers and Concrete
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• 제32권3호
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• 한국신뢰성학회지:신뢰성응용연구
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• 제15권1호
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• pp.33-43
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• 2015

The importance of reliability engineering has increased in recent years. Many studies have been carried out into reliability in a variety of research domains, largely focused on industrial engineering, mechanical engineering, electronics engineering, materials engineering and statistical science. However, most of these studies were carried out without collaboration between different areas of study. Here, we analyze research papers and patents regarding reliability that were published during the past five years, and describe core trends in the development of reliability technology from a multidisciplinary perspective.

• 한국CDE학회논문집
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• 제5권2호
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• pp.184-195
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• 2000

MDO (Multidisciplinary Design Optimization) methodology is an emerging new technology to solve a complicate structural analysis and design problem with a large number of design variables and constraints. In this paper MDO methodology is adopted through the use of computer aided systems such as Geometric Solid Modeller, Mesh Generator, CAD system and CAE system. And this paper introduces MDO methodology as a new method for structural analysis and design through the application to the structural design of flap drive system. In a MDO methodology application to the structural design of flap drive system, kinetodynamic analysis is done using a simple aerodynamic analysis model for the air flow over the flap surface instead of difficult aerodynamic analysis. Simultaneously the structural static analysis is done to obtain the optimum structural condition. And the structural buckling analysis for push pull rod is also done to confirm the optimum structural condition (optimum cross section shape of push pull rod).

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.429-432
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• 2004

Multidisciplinary design optimization technique is applied to drum type washer in order to minimize the vibration of the cabinet. Dynamic analysis and structural analysis are carried out by using commercial programs to obtain the reliable responses. Analysis models are compared to the experimental responses and finally validated for further design. Two commercial programs are integrated by the design framework EMDIOS that provides interfaces to conveniently link between analyzers and performs design optimization. In this research we could obtain an optimum design that reduces the magnitude of amplitude by about 33% compared with the original design.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.695-700
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• 2008

Artificial neural network (ANN) has been extensively used in areas of nonlinear system modeling, analysis and design applications. Basically, ANN has its distinct capabilities of implementing system identification and/or function approximation using a number of input/output patterns that can be obtained via numerical and/or experimental manners. The paper describes a role of ANN, especially a back-propagation neural network (BPN) in the context of engineering analysis, design and optimization. Fundamental mechanism of BPN is briefly summarized in terms of training procedure and function approximation. The BPN based causality analysis (CA) is further discussed to realize the problem decomposition in the context of multidisciplinary design optimization. Such CA is also applied to quantitatively evaluate the uncoupled or decoupled design matrix in the context of axiomatic design with the independence axiom.

• Advances in aircraft and spacecraft science
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• 제4권3호
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.