다단 최적 설계 프레임워크를 활용한 전기추진 항공기 프로펠러 공력 최적 설계

권형일(Hyung-Il Kwon),이슬기(Seul-Gi Yi),최성임(Seongim Choi),김근배(Keunbae Kim) 한국항공우주학회 2013 韓國航空宇宙學會誌 Vol.41 No.3

본 연구에서는 프로펠러나 헬리콥터 로터와 같은 회전체의 공력 최적 설계를 위한 다단 최적 설계 프레임워크를 제안한다. 이 프레임워크는 플랜폼 설계와 단면의 형상 설계를 반복적으로 수행하는 설계 전략을 통해 회전체의 공력 성능 향상을 목표로 한다. 플랜폼 설계의 단계에서는 유전 알고리즘과 2차원 CFD 데이터베이스 기반의 깃 요소 모멘텀 이론을 이용하여 빠른 시간에 회전체의 공력 특성을 평가하여 최적점을 탐색하였다. 플랜폼 설계 후 단면에 유입되는 유동 조건을 예측하여 단면 형상 최적 설계를 수행하였다. 설계 과정에서 보다 면밀하게 유동 특성이 분석될 수 있도록 2차원 N-S 해석자와 민감도 기반의 최적화 알고리즘을 통해 최적해를 탐색하였다. 단면 형상이 설계된 후에 는 최적의 유동 조건을 산출할 수 있도록 플랜폼 설계를 반복적으로 수행하였다. 본 프레임워크를 1㎾급 전기추진용 항공기 프로펠러 설계에 적용하여 그 유효성을 3차 원 N-S 해석과 풍동 실험을 통해 검증하였다. 설계 후, 풍동 실험 결과를 기준으로 약 5%의 프로펠러 효율 증가를 얻을 수 있었다. A multi-level design optimization framework for aerodynamic design of rotary wing such as propeller and helicopter rotor blades is presented in this study. Strategy of the proposed framework is to enhance aerodynamic performance by sequentially applying the planform and sectional design optimization. In the first level of a planform design, we used a genetic algorithm and blade element momentum theory (BEMT) based on two-dimensional aerodynamic database to find optimal planform variables. After an initial planform design, local flow conditions of blade sections are analyzed using high-fidelity CFD methods. During the next level, a sectional design optimization is conducted using two dimensional Navier-Stokes analysis and a gradient based optimization algorithm. When optimal airfoil shape is determined at the several spanwise locations, a planform design is performed again. Through this iterative design process, not only an optimal flow condition but also an optimal shape of an EAV propeller blade is obtained. To validate the optimized propeller-blade design, it is tested in wind-tunnel facility with different flow conditions. An efficiency, which is slightly less than the expected improvement of 7% predicted by our proposed design framework but is still satisfactory to enhance the aerodynamic performance of EAV system.

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

박형욱,정준,이재우 한국항공우주학회 2016 International Journal of Aeronautical and Space Sc Vol.17 No.2

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

Possibility Based Small Aircraft Design Optimization Using Database Driven Uncertainty Approach

Hsu Myat Naing,Daniel Neufeld,Nguyen Nhu Van,Maxim Tyan,Jae-Woo Lee,Sangho Kim 한국항공우주학회 2013 한국항공우주학회 학술발표회 논문집 Vol.2013 No.4

Since deterministic optimization method without considering uncertainty lead to unreliable designs, it is required to consider design methods that take into account of the input uncertainty. In this study, uncertainties which are from the analysis methods that do not perfectly correspond to physical phenomenon are taken into account in optimization process. Possibility Base Design Optimization Design Optimization is one of the methods for accounting for uncertainties by modeling each source of uncertainty as a fuzzy number. Possibility Base Design Optimization with performance measure approach that improves numerical efficiency and stability is used in this design optimization. This paper describes a process that implements a design optimization using possibility theory to perform small aircraft conceptual design optimization in order to produce results that are more conservative but more trustworthy than conventional optimization approach.

Uncertainty-based MDO for aircraft conceptual design

Park, Hyeong-Uk,Lee, Jae-Woo,Chung, Joon,Behdinan, Kamran Emerald Group Publishing Limited 2015 Aircraft engineering and aerospace technology Vol.87 No.4

<P><B>Purpose</B></P> <P> – The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design optimization methods. Reliability-Based Design Optimization (RBDO), Possibility-Based Design Optimization (PBDO) and Robust Design Optimization (RDO) methods were developed to handle uncertainties of design optimization. The RBDO method is found suitable for uncertain parameters when sufficient information is available. On the other hand, the PBDO method is proposed when uncertain parameters have insufficient information. The RDO method can apply to both cases. The RBDO, PBDO and RDO methods were considered with the Multidisciplinary Design Optimization (MDO) method to generate conservative design results when low fidelity analysis tools are used. </P> <P><B>Design/methodology/approach</B></P> <P> – Methods combining MDO with RBDO, PBDO and RDO were developed and have been applied to a numerical analysis and an aircraft conceptual design. This research evaluates and compares the characteristics of each method in both cases. </P> <P><B>Findings</B></P> <P> – The RBDO result can be improved when the amount of data concerning uncertain parameters is increased. Conversely, increasing information regarding uncertain parameters does not improve the PBDO result. The PBDO provides a conservative result when less information about uncertain parameters is available. </P> <P><B>Research limitations/implications</B></P> <P> – The formulation of RDO is more complex than other methods. If the uncertainty information is increased in aircraft conceptual design case, the accuracy of RBDO will be enhanced. </P> <P><B>Practical implications</B></P> <P> – This research increases the probability of a feasible design when it considers the uncertainty. This result gives more practical optimization results on a conceptual design level for fabrication. </P> <P><B>Originality/value</B></P> <P> – It is RBDO, PBDO and RDO methods combined with MDO that satisfy the target probability when the uncertainties of low fidelity analysis models are considered.</P>

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

Park, Hyeong-Uk,Chung, Joon,Lee, Jae-Woo The Korean Society for Aeronautical and Space Scie 2016 International Journal of Aeronautical and Space Sc Vol.17 No.2

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

Hyeong-Uk Park,Joon Chung,Jae-Woo Lee 한국항공우주학회 2016 International Journal of Aeronautical and Space Sc Vol.17 No.2

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

Development of optimal water distribution system design and operation approach considering hydraulic and water quality criteria in many-objective optimization framework

Choi Young Hwan 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.2

Water distribution systems (WDSs) are major infrastructure, and it needs to consider economic, hydraulic stability, and water quality safety to optimal design and operation of WDSs. However, the previous studies related to WDS design and operation were focused on each field (i.e. design: optimal pipe diameter, pump sizing, and valve location; operation: optimal pump scheduling, etc.) even though the WDS design and operation have a correlation. Therefore, to achieve economic feasibility, hydraulic stability, and water quality safety under WDS design and operation process, this study develops an optimal WDS design and operation approach considering hydraulic and water quality criteria in the many-objective optimization framework. To consider design and operation, this study applies three objective functions to minimize the total design and operation cost (i.e. the pipe cost, pump construction, and pump operation cost), maximize system robustness, and minimize the amount of chlorine requisition simultaneously under the hydraulic and quality constraints. The proposed optimal WDS design and operation model was applied to the two-stage optimization procedures. The first process determined the optimal pipe diameter set. The second process determined the optimal pump construction and scheduling considering three objective functions such as the total pump cost, the system robustness, and the quantity of the required residual chlorine for determining optimally the available number of pumps, capacity, and scheduling. For the optimization, the self-adaptive multi-objective harmony search is used and a famous benchmark network for the optimal design and pump operation of WDSs is applied to verify the proposed approach. This study can provide a new perspective on WDS design and operation technique considering the essential design factors to the water utility.

다중목적 최적화 알고리즘을 활용한 주거복합커뮤니티공간 디자인 연구

김범승 ( Kim Beomseung ),이우형 ( Lee Woohyoung ) 한국공간디자인학회 2021 한국공간디자인학회논문집 Vol.16 No.8

(Background and Purpose) Recently, a residential complex community development that provides medium/high-density housing and living SOC using the blighted low-rise residential area in the downtown area is being developed. Architecturally, the high-density integration of complex programs is essential to simultaneously satisfying different requirement for environmental performance and each use. As the existing black box design method has a limit to its response, this design focuses on the design method using a multi objective optimization algorithm and considers the impact of the adjacent context including the own building within the site. We propose a design for a residential complex community space that reflects the optimal architectural composition that satisfies the different design conditions that conflict with each other. (Method) For design example, it is set as a residential complex community space including residential, commercial, and community facilities that respond to community problems for blighted area located on a slope site in the Jeongneung Redevelopment Area in Seoul. Based on the relationship between the adjacent context and the group of buildings on the site, the design is drawn based on the site plan and shape that simultaneously satisfy the environmental optimization based on insolation and the view and perception requirements for each use. To do this, it utilizes Octopus, a multi objective optimization add-on based on Rhino Grasshopper. The optimal solution that meets the complex requirements of the example is selected and applied to the final design through the review of performance and planning for multiple solution groups derived from Octopus. (Results) The derived design includes not only site plan and shape of the most importantly, but also urban and architectural aspects that respond to various requirements for the community. First, from an urban point of view, the social integration of the community was strengthened by providing functions required to respond to the physical and socio-economic problems of the community cut off from the surrounding. From the architectural point of view, through the calculation results derived from the optimization, a number of complex conditions including the environmental performance of complex including local facilities were satisfied. In addition, from a technical point of view, evidence-based design based on objectivity that goes beyond the limits of subjective arbitrariness inherent in the existing architectural design process was applied. (Conclusions) This design confirmed the applicability and potential use of an optimization genetic algorithm linked with a new digital tool in architectural design by deriving alternatives to the set examples. The effectiveness of multi objective optimization to overcome the limitations of traditional design was confirmed. Furthermore, it has meaning in expanding the versatility of practical grafting of advanced new technology and architectural design.

데이터 기반 설계를 활용한 최적 파빌리온 배치 및 적용 설계안

손상현 ( Son Sanghyun ) 한국공간디자인학회 2021 한국공간디자인학회논문집 Vol.16 No.1

(Background and Purpose) The recent remarkable development of digital technology is causing rapid change in our society. In architecture, there is increased interest in data-based design that supports decision-making through collecting, filtering, and evaluating building and urban-related data, as well as visualizing this in real-time. This design proposal set up an example with specific site conditions and evaluates the performance of the building, explores an optimal design that reflects the computation result derived from the optimization genetic algorithm based on the evaluation data. This can be a new way of making decisions as opposed to relying on the experience, intuition, and personal talent of the architect as it was in the past, and develop into a new design approach that combines design process with actual data. (Method) An open space in an urban environment can be selected as an example, and the design layout can be derived that maximizes visibility of the building, as well as minimizes total surface area. Based on this layout, a pavilion with various programs can be proposed on this open space. For this, the 3D modeling tool Rhino 3D, the parametric design tool Grasshopper, and the genetic algorithm-based Multi-Objective Optimization add-on Octopus were used. First, various parametric alternatives for the pavilion layout were considered and the visibility and total surface area of each alternative were analyzed. The optimized result data linked to each alternative was visualized in real-time to select the optimal layout. Then the final proposal was drawn from the selected layout and form. (Results) The final design is the result derived from the optimal layout and is an architectural design that considers a new way of utilizing open space in the developed city. First, the pavilion layout derived from the optimization genetic algorithm was propose on the open space that is adjacent to the main street in the city. Diverse programs and event spaces such as indoor and outdoor exhibition spaces, small exhibition spaces, shops, cafes, small gardens, lawns, and fountains were included in the pavilion with basic modules. In addition, this was connected to a modular street, proposing a new open space in the city that can respond to future program changes and be experienced continuously. (Conclusions) This design proposal evaluated building performance using computation, visualized and optimized the results, and proposed a final pavilion design reflecting this design process. Through this process, the limitations of the traditional architectural decision-making method which relied on the experience, intuition of the architect can be overcome. The proposal pursues objectivity based on quantitative data and presented the possibility of a new data-based architectural design which minimizes the time-consuming process of revising and reproducing alternatives in the early stage of design.

Multi-Optimal Designs for Second-Order Response Surface Models

Park, You-Jin The Korean Statistical Society 2009 Communications for statistical applications and me Vol.16 No.1

A conventional single design optimality criterion has been used to select an efficient experimental design. But, since an experimental design is constructed with respect to an optimality criterion pre specified by investigators, an experimental design obtained from one optimality criterion which is superior to other designs may perform poorly when the design is evaluated by another optimality criterion. In other words, none of these is entirely satisfactory and even there is no guarantee that a design which is constructed from using a certain design optimality criterion is also optimal to the other design optimality criteria. Thus, it is necessary to develop certain special types of experimental designs that satisfy multiple design optimality criteria simultaneously because these multi-optimal designs (MODs) reflect the needs of the experimenters more adequately. In this article, we present a heuristic approach to construct second-order response surface designs which are more flexible and potentially very useful than the designs generated from a single design optimality criterion in many real experimental situations when several competing design optimality criteria are of interest. In this paper, over cuboidal design region for $3\;{\leq}\;k\;{\leq}\;5$ variables, we construct multi-optimal designs (MODs) that might moderately satisfy two famous alphabetic design optimality criteria, G- and IV-optimality criteria using a GA which considers a certain amount of randomness. The minimum, average and maximum scaled prediction variances for the generated response surface designs are provided. Based on the average and maximum scaled prediction variances for k = 3, 4 and 5 design variables, the MODs from a genetic algorithm (GA) have better statistical property than does the theoretically optimal designs and the MODs are more flexible and useful than single-criterion optimal designs.