• 전산구조공학
• /
• 제29권1호
• /
• pp.46-48
• /
• 2016

• Nuclear Engineering and Technology
• /
• 제37권2호
• /
• pp.127-138
• /
• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Nuclear Engineering and Technology
• /
• 제49권3호
• /
• pp.484-494
• /
• 2017

In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
• /
• pp.53-60
• /
• 1998

Efficiency of design process for large scale structures highly depends on the development of efficient structural analysis and structural response control algorithms because a successful design involves a number of structural analysis based on iterative structural response control process. In this paper, distributed structural analysis model on multiple personal computers connected by ethernet network is presented. To reduce communication cost required in the process of analysis, substructuring techniques are adopted to evenly distribute computational loads on each processor. With its applications on structural analysis of plane frame structures, performance of the proposed computational model are presented in detail.

• 전산구조공학
• /
• 제5권3호
• /
• pp.48-51
• /
• 1992

이 글에서 설계변수가 유한개이고 목적함수 및 제약함수가 설계변수의 비선형 함수로 표시되는 최적화 문제를 기술하고, 그 해법을 개념적으로 고찰하며 마지막으로 구조최적설계 문제의 특성과 최적화 과정을 살펴보기로 한다.

• Nuclear Engineering and Technology
• /
• 제38권3호
• /
• pp.225-230
• /
• 2006

With the advent of inexpensive computing power over the past two decades, applications of Monte Carlo radiation transport techniques have proliferated dramatically. At Los Alamos, the Monte Carlo codes MCNP5 and MCNPX are used routinely on personal computer platforms for radiation shielding analysis and dosimetry calculations. These codes feature a rich palette of variance reduction (VR) techniques. The motivation of VR is to exchange user efficiency for computational efficiency. It has been said that a few hours of user time often reduces computational time by several orders of magnitude. Unfortunately, user time can stretch into the many hours as most VR techniques require significant user experience and intervention for proper optimization. It is the purpose of this paper to outline VR strategies, tested in practice, optimized for several common radiation shielding tasks, with the hope of reducing user setup time for similar problems. A strategy is defined in this context to mean a collection of MCNP radiation transport physics options and VR techniques that work synergistically to optimize a particular shielding task. Examples are offered in the areas of source definition, skyshine, streaming, and transmission.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
• /
• pp.504-512
• /
• 2003

Simulation programs have been developed and used as an attempt to improve the accuracy of Non-Destructive Evaluation(NDE) techniques. The applicability of these programs is very limited, however, because it is difficult to describe the delicacy of the propagation of stress waves. To investigate the applicability of the finite element analysis for stress wave-based NDE techniques numerical simulation for Impact-Echo method and SASW method is performed. The numerical studies are performed to determine the essential parameters such as contact time of impact load, mesh size and time step size. These studies show that the choice of parameter is very important for improving the accuracy and confidence of the numerical procedure and, thereby, the applicability of the numerical analysis for stress wave-based NDE techniques

• 한국전산유체공학회:학술대회논문집
• /
• 한국전산유체공학회 1995년도 창립기념학술대회
• /
• pp.44-68
• /
• 1995

In the present paper, visualization techniques in fluid dynamic experiments such as Schlieren photograph are numerically simulated so that the same output as the experimental flow visualization can be obtained from the computed results for the fair comparison. Numerical methods to simulate optical visualizations, that are Schlieren photograph, shadowgraph and interferogram, are considered. Some examples of pictures obtained by the present methods show the importance of the simulations of visualization techniques for the correct comparisons of the computations and experiments.

• Journal of Information Processing Systems
• /
• 제9권4호
• /
• pp.633-650
• /
• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

• Journal of applied mathematics & informatics
• /
• 제8권2호
• /
• pp.305-326
• /
• 2001

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.