• 대한의용생체공학회:의공학회지
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• 제32권1호
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• pp.15-24
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• 2011

While Compton imaging is recognized as a valuable 3-D technique in nuclear medicine, reconstructing an image from Compton scattered data has been of a difficult problem due to its computational complexity. The most complex and time-consuming computation in Compton camera reconstruction is to perform the conical projection and backprojection operations. To alleviate the computational burden imposed by these operations, we investigate a rebinning method which can convert conical projections into parallel projections. The use of parallel projections allows to directly apply the existing deterministic reconstruction methods, which have been useful for conventional emission tomography, to Compton camera reconstruction. To convert conical projections into parallel projections, a cone surface is sampled with a number of lines. Each line is projected onto an imaginary plane that is mostly perpendicular to the line. The projection data rebinned in each imaginary plane can then be treated as the standard parallel projection data. To validate the rebinning method, we tested with the representative deterministic algorithms, such as the filtered backprojection method and the algebraic reconstruction technique. Our experimental results indicate that the rebinning method can be useful when the direct application of existing deterministic methods is needed for Compton camera reconstruction.

• Nuclear Engineering and Technology
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• 제44권2호
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• pp.113-150
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• 2012

The point we made in this paper is that, although detailed and precise three-dimensional (3D) whole-core transport calculations may be obtained in the future with massively parallel computers, they would have an application to only some of the problems of the nuclear industry, more precisely those regarding multiphysics or for methodology validation or nuclear safety calculations. On the other hand, typical design reactor cycle calculations comprising many one-point core calculations can have very strict constraints in computing time and will not directly benefit from the advances in computations in large scale computers. Consequently, in this paper we review some of the deterministic 3D transport methods which in the very near future may have potential for industrial applications and, even with low-order approximations such as a low resolution in energy, might represent an advantage as compared with present industrial methodology, for which one of the main approximations is due to power reconstruction. These methods comprise the response-matrix method and methods based on the two-dimensional (2D) method of characteristics, such as the fusion method.

• Industrial Engineering and Management Systems
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• 제12권1호
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• pp.9-15
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• 2013

An inverse minimum spanning tree problem makes the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, the concept of uncertain ${\alpha}$-minimum spanning tree is initiated for minimum spanning tree problem with uncertain edge weights. Using different decision criteria, two uncertain programming models are presented to formulate a specific inverse minimum spanning tree problem with uncertain edge weights involving a sum-type model and a minimax-type model. By means of the operational law of independent uncertain variables, the two uncertain programming models are transformed to their equivalent deterministic models which can be solved by classic optimization methods. Finally, some numerical examples on a traffic network reconstruction problem are put forward to illustrate the effectiveness of the proposed models.

• Structural Engineering and Mechanics
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• 제88권4호
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• pp.301-309
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• 2023

In this paper, a new modified conjugate gradient (MCG) method is presented which is based on a new gradient regularizer, and this method is used to identify the dynamic load on airfoil structure without and with considering random structure parameters. First of all, the newly proposed algorithm is proved to be efficient and convergent through the rigorous mathematics theory and the numerical results of determinate dynamic load identification. Secondly, using the perturbation method, we transform uncertain inverse problem about force reconstruction into determinate load identification problem. Lastly, the statistical characteristics of identified load are evaluated by statistical methods. Especially, this newly proposed approach has successfully solved determinate and uncertain inverse problems about dynamic load identification. Numerical simulations validate that the newly developed method in this paper is feasible and stable in solving load identification problems without and with considering random structure parameters. Additionally, it also shows that most of the observation error of the proposed algorithm in solving dynamic load identification of deterministic and random structure is respectively within 11.13%, 20%.

• 대한토목학회논문집
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• 제31권1B호
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• pp.37-45
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• 2011

본 연구에서는 비선형 카오스 계열에 대한 잡음의 영향 분석을 위하여 대표적인 비선형 카오스 특성을 보이는 것으로 알려진 Logistic Map 자료계열을 이용하여 연구를 수행하였다. 잡음을 임의로 추가하여 잡음 수준에 따라 자료계열을 재생성 하였으며 비선형 자료의 분석 방법으로 활용되고 있는 상태공간 재건, 상관차원 추정, BDS 통계, DVS 알고리즘 분석을 실시하였다. 분석 결과 자료계열은 잡음의 수준이 높아짐에 따라 비선형 카오스적 특성을 보이는 원시자료의 특성이 사라지고 무작위한 추계학적 특성을 보이는 자료로 변화하였다. 그리고 잡음의 영향을 받고 있는 자료에 대한 잡음제거 방법으로 Low Pass Filter와 Kalman Filter 기법을 적용하였다. 전통적인 비모수 통계기법은 비선형 무작위 시계열 또는 비선형 시계열을 구분하는데 어려움이 있지만 비선형 통계기법인 BDS 통계는 비선형 시계열을 구분할 수 있는 것으로 알려져 있다. 분석을 수행한 결과 잡음 수준이 높을 경우 Low Pass Filter는 잡음을 효과적으로 제거하지 못하여 비선형 자료를 선형자료로 판정하였지만 Kalman Filter의 경우 잡음을 효과적으로 제거하는 것으로 나타나 적용성이 우수함을 알 수 있었다.