• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.127-135
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• 2024

Recent studies have shown that inverse design using deep learning has the potential to rapidly generate the optimal design that satisfies the target performance without the need for iterative optimization processes. Unlike traditional methods, deep learning allows the network to rapidly generate a large number of solution candidates for the same objective after a single training, and enables the generation of diverse designs tailored to the objectives of inverse design. These inverse design techniques are expected to significantly enhance the efficiency and innovation of design processes in various fields such as aerospace, biology, medical, and engineering. We analyzes inverse design models that are mainly utilized in the nano and chemical fields, and proposes inverse design models based on supervised and unsupervised learning that can be applied to the engineering system. It is expected to present the possibility of effectively applying inverse design methodologies to the design optimization problem in the field of engineering according to each specific objective.

• 대한기계학회논문집A
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• 제28권10호
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• pp.1574-1582
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• 2004

Binary manipulators have recently received much attention due to hyper-redundancy, light weight, good controllability and high reliability. The precise positioning of the manipulator end-effecter requires the use of many modules, which results in a high-dimensional workspace. When the workspace dimension is large, existing inverse kinematics methods such as the Ebert-Uphoff algorithm may require impractically large memory size in determining the binary positions of all actuators. To overcome this limitation, we propose a new inverse kinematics algorithm: the inverse kinematics problem is formulated as an optimization problem using real-valued design variables, The key procedure in this approach is to transform the integer-variable optimization problem to a real-variable optimization problem and to push the real-valued design variables as closely as possible to the permissible binary values. Since the actual optimization is performed in real-valued design variables, the design sensitivity becomes readily available, and the optimization method becomes extremely efficient. Because the proposed formulation is quite general, other design considerations such as operation power minimization can be easily considered.

• ETRI Journal
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• 제44권5호
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• pp.805-815
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• 2022

The model-based evolutionary algorithms are divided into three groups: estimation of distribution algorithms, inverse modeling, and surrogate modeling. Existing inverse modeling is mainly applied to solve multi-objective optimization problems and is not suitable for many-objective optimization problems. Some inversed-model techniques, such as the inversed-model of multi-objective evolutionary algorithm, constructed from the Pareto front (PF) to the Pareto solution on nondominated solutions using a random grouping method and Gaussian process, were introduced. However, some of the most efficient inverse models might be eliminated during this procedure. Also, there are challenges, such as the presence of many local PFs and developing poor solutions when the population has no evident regularity. This paper proposes inverse modeling using random forest regression and uniform reference points that map all nondominated solutions from the objective space to the decision space to solve many-objective optimization problems. The proposed algorithm is evaluated using the benchmark test suite for evolutionary algorithms. The results show an improvement in diversity and convergence performance (quality indicators).

• 소성∙가공
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• 제26권1호
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• pp.41-47
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• 2017

Cyclic behavior of advanced high strength steel sheets was measured using an inverse-optimization approach with pre-straining and bending. First, tensile specimens were pre-strained, and three-point bending was conducted for the pre-strained specimens. By using the inverse finite element optimization, the combined isotropic-kinematic hardening parameters that minimize the error between the measured and predicted bending force-displacement curves. The measured cyclic behavior agreed well with the cyclic behavior measured by sheet tension-compression test, which confirms the validity of the measuring procedure based on inverse optimization.

• 대한기계학회논문집A
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• 제20권11호
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• pp.3398-3407
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• 1996

In this paper, we derive an algorithm and develope a computer program which analyze rapidly and precisely the inverse kinematics of robotic mechanism with spatial complex chain structure based on the relative coordinates. We represent the inverse kinematic problem as an optimization problem with the kinematic constraint equations. The inverse kinematic analysis algorithm, therefore, consists of two algorithms, the main, an optimization algorithm finding the motion of independent joints from that of an end-effector and the sub, a forward kinematic analysis algorithm computing the motion of dependent joints. We accomplish simulations for the investigation upon the accuracy and efficiency of the algorithm.

• 대한기계학회논문집B
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• 제34권7호
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• pp.679-688
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• 2010

본 연구에서는 기존의 역열전달 문제(inverse heat transfer problem)와 같이 역해석(inverse analysis)을 통해 미지의 파라미터를 추정(estimation)하는 개념을 복잡한 연소문제에 도입하였다. 기존의 연구에서는 역해석 기법을 연소문제 자체에 보다는 대부분 연소현상을 동반한 복사열전달과 같은 역열전달 문제에 국한해서 적용하고 있기 때문에, 열전달 문제에 한정되어 사용되고 있는 기존의 역해석을 새로운 공학문제에 확장하여 적용함과 동시에 효율적인 연소기 설계 및 최적화 개념을 제시하는데 본 연구의 의의가 있다고 할 수 있다. 이를 위해 실제적으로 많이 사용하고 있는 축대칭 원통형 연소기 내부로 주입되는 메탄($CH_4$)과 산소($O_2$) 성분의 초기 질량분율 값을 연소기 입구 근방에서 측정한 개스의 온도 데이터를 이용하여 역추정하였다. 이때, 복잡한 확산지배 연소 현상을 효율적으로 역해석하기 위해 최적화 방법 중의 하나인 반발 입자 군집 최적화 방법을 역해석 기법으로 적용하였다.

• 한국전산유체공학회지
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• 제3권1호
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• pp.37-45
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• 1998

A new and efficient inverse design method based on the numerical optimization technique has been developed. The 2-D incompressible Navier-Stokes equations are solved for obtaining the objective functions and coupled with the optimization procedure to perform the inverse design. The steepest descent and the conjugate gradient method have been applied to find the searching direction. The golden section method was applied to compute the design variable intervals. It has been found that the airfoil and the pump impellers are well converged to their targeting shapes.

• 대한기계학회논문집A
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• 제24권7호
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• pp.1753-1762
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• 2000

An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• 한국컴퓨터정보학회논문지
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• 제24권11호
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• pp.119-126
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• 2019

부분역최적화는 역최적화의 흥미로운 변형으로, 주어진 최적화문제와 그 문제의 부분해가 주어지면 이 부분해가 최적해에 포함되도록 문제를 최소한으로 수정하는 문제이다. 이 논문은 라인위에서 정의되는 순환외판원문제(TSP)를 다루는데, 이는 배달시스템, 창고 선반에서 물건을 수집하는 것, 등의 많은 응용을 가진다. 라인 위에서 위치하는 n개의 일이 주어지고 이 중 연속적으로 처리해야하는 일 k개가 부분적으로 주어진다. 각각의 일은 라인 위의 특정 장소에 위치하고 라인을 움직이는 서버에 의해 처리되어야 한다. 우리의 임무는 k개의 일이 최적해에서 연속적으로 처리되도록 n개의 일의 위치를 라인 위에서 최소한으로 조정하는 것이다. 이 논문에서 이 문제와 이 문제의 다양한 변종을 다항시간 내에 푸는 알고리즘을 개발한다. 구체적으로, 서버가 특정한 Forward Trip이라는 특정한 내부 알고리즘을 사용하는 경우와 일반적인 최적 알고리즘을 사용하는 경우에 대한 부분역최적화를 다룬다.