13 research outputs found
A Numerical Study on the Failure of Nuclear Reactor Vessel Lower Head and ICI Tube by Core Melt during Severe Accident
Get PDFNuclear energy is one of the easiest and the most economical energy resources to use. However, nuclear energy that can be used easily and inexpensively also has various risks, one of which is nuclear accident.
This study aims to develop a safety analysis methodology through which the integrity of both the lower head and the in-core instrumentation (ICI) tubes can be verified by applying finite element analyses. The ICI is used to measure the neutron flux distribution and to control in the core of the reactor.
Two analysis models were implemented. One was a two-dimensional model for verifying integrity of structures of the lower head, and the other was a three-dimensional model for verifying ejection of ICI tube.
Heat transfer and thermo-mechanical analyses were also performed. The heat transfer analysis was conducted to evaluate the heat flux caused by the high-temperature melt and the boundary conditions caused by external vessel cooling. The thermo-mechanical analysis was performed by using thermal loading, internal pressure, and deadweight of debris.
The results showed that the melting and breakage of the ICI tube occurred because of the high temperature, but the ejection of the ICI tube was delayed because of the contact between the ICI tube and the lower head. However, the ICI tube was eventually ejected, thereby confirming that the structural combination of the reactor head and tube could not prevent the ejection.
Substructure analysis was performed to propose the method that can be applied to prevent ICI tube failure. Consequently, the analysis result confirmed that the ICI tube could be prevented from ejection if the lower structure has sufficient stiffness.
However, if these proposed preventive measures are not properly applied in situation of unexpected exception, the inner melt may be ejected and contact with the cooling water may cause an external steam explosion. An external steam explosion analysis was performed because the steam explosion may influence on the reactor vessel. As a result of the analysis, failure of the reactor vessel was confirmed.Abstract ⅰ
Nomenclature ⅲ
List of Tables v
List of Figures vi
1. 서론 1
1.1 연구 배경 1
1.2 연구 동향 2
1.3 연구 목표 및 범위 5
2. 유한요소 해석의 이론적 배경 6
2.1 유한요소법 6
2.2 탄소성 유한요소해석 7
2.3 크리프 해석 9
3. 하부헤드의 열-구조 신뢰성 분석 13
3.1 해석 모델링 13
3.1.1 유한요소 모델링 15
3.1.2 재료의 기계적 특성 20
3.1.3 해석 조건 23
3.1.4 파손 기준 28
3.2 열전달 해석 29
3.2.1 열전달 해석에 대한 가정 29
3.2.2 열 유속 모델 해석 30
3.2.3 일체형 모델 해석 33
3.2.4 접촉저항 모델 해석 36
3.2.5 외부 온도 변화에 따른 해석 39
3.3 구조 해석 결과 42
3.4 크리프 파손 해석 결과 47
4. ICI 튜브 파손 평가 51
4.1 해석 모델링 및 파손기준 51
4.1.1 유한요소 모델링 51
4.1.2 해석 조건 56
4.1.3 용접부위 파손기준 57
4.2 ICI 튜브 파손 해석 결과 59
4.2.1 열 해석 59
4.2.2 ICI 튜브의 파손 평가 67
4.3 ICI 튜브의 파손 방지 대책 76
4.3.1 ICI 튜브의 파손 방지 개념 76
4.3.2 원자로 하부 구조물 76
4.3.3 하부구조물 물성 및 경계조건 77
4.3.4 하부구조물 파손 평가 81
4.3.5 ICI 튜브 파손 평가 81
5. 외부 증기 폭발에 의한 원자로 건전성 평가 85
5.1 외부 증기폭발 개념 85
5.2 원자로 건전성 평가 86
5.2.1 외부 증기폭발 데이터 86
5.2.2 구조해석 및 평가 91
6. 결론 94
참고문헌 96
부록 A. 2차원 열-구조 해석 Input file 102
부록 B. 3차원 열-구조 해석 Input file 105
부록 C. 증기폭발해석 Input file 108
부록 D. Element death Input file 110Docto
GIS를 導入한 共同住宅 再建築 制御方案에 관한 硏究 : 地區單位 再建築 範圍設定 및 管理를 中心으로
No full text학위논문(석사)--서울大學校 環境大學院 :環境造景學科,1997.Maste
Radar Image Reconstruction Based on Compressive Sensing
No full textDoctorThis dissertation discusses a study on radar image reconstruction using sparse recovery based on compressive sensing (CS) theory. The organization of this study is as follows. First, we compare the performance of sparse recovery algorithms (SRAs) for the reconstruction of a two-dimensional (2D) inverse synthetic aperture radar (ISAR) image from incomplete radar-cross-section (RCS) data. The three methods considered for the SRA include the basis pursuit (BP), the basis pursuit denoising (BPDN), and the orthogonal matching pursuit (OMP) methods. The performance of the methods in terms of the reconstruction accuracy of the ISAR image is compared using the incomplete RCS data. In addition, traditional interpolation methods such as nearest-neighbor interpolation (NIP), linear interpolation (LIP), and spline interpolation (SIP) are applied to the incomplete RCS data to reconstruct ISAR images, and their performance is compared to that of the SRAs. Consequently, the relaxed constraint rather than the strictly equality constraint for the SRA is more adequate for SRA applied to radar imaging.
Next, we proposes a one-dimensional (1D) scattering center extraction (SCE) method that includes mainly two steps: coarse estimation of scattering centers using the iteratively reweighted least square (IRLS) coupled with a peak-finding algorithm, and fine estimation of scattering centers using the OMP procedure from the adaptively sampled Fourier dictionary. Consequently, the proposed method can achieve high SCE accuracy regardless of whether data are missing in the collected RCS dataset or not.
Next, we also propose a 2D SCE method using sparse recovery based on CS theory regardless of whether data are missing in the received RCS data or not. The proposed method first generates a 2D grid with adaptive discretization that has a much smaller size than the fully sampled fine grid. As a result, this adaptive grid generation enables us to significantly reduce the computational complexity of the proposed method. Then, coarse estimation of 2D scattering centers is implemented using the IRLS coupled with a general peak-finding algorithm. Finally, fine estimation of 2D scattering centers is performed using the OMP procedure from an adaptively sampled Fourier dictionary. Measured RCS data as well as simulation data using the point scatterer model are used to evaluate the 2D SCE accuracy of the proposed method. The results show that the proposed method can achieve high SCE accuracy for both the complete RCS dataset in a noisy environment and the incomplete RCS dataset with missing data compared with the conventional OMP and existing Fourier-transform (FT)-based discrete spectral estimation (DSE) techniques such as CLEAN and RELAX.
Finally, we develop a new method based on an OMP-type group-searching scheme for bistatic ISAR (Bi-ISAR) imaging using incomplete bistatic RCS (Bi-RCS) datasets with missing data. If the conventional FT-based algorithm is applied to the incomplete dataset, the resultant Bi-ISAR image is usually corrupted, leading to severe deterioration in image quality. To overcome this problem, the parameters that are related to the bistatic angle in the Bi-ISAR signal model are estimated suboptimally by using a combination of the OMP-type searching scheme and rank-based group selection. Next, a clear Bi-ISAR image, without any corruption caused by the missing data, can be obtained from the reconstructed Bi-ISAR signal using the estimated parameters. To validate the reconstruction capability of the proposed method, bistatic scattered field data using the physical optics (PO) technique as well as the point-scatterer model are used for Bi-ISAR image reconstruction. The results show that the proposed method can give high reconstruction accuracy for the incomplete Bi-RCS dataset compared to conventional reconstruction methods
바이스태틱 레이다를 이용한 이동표적에 대한 표적식별 성능 분석
No full text바이스태틱(Bistatic) 레이다는 기존의 모노스태틱(Monostatic) 레이다로는 수행하기 어려운 저피탐(stealth) 표적에 대한탐지 및 식별을 용이하게 해준다. 하지만 표적식별을 위해 바이스태틱 레이다의 수신신호로부터 고해상도 거리 측면도(high resolution range profile: HRRP)를 형성할 시, 바이스태틱 고유의 기하구조로 인해 바이스태틱 HRRP 내 왜곡현상이발생하고, 이는 표적에 대한 정확한 거리 정보를 획득하기 어렵게 한다. 더욱이 바이스태틱 HRRP 내 나타나는 표적의전자기적 산란 메커니즘은 바이스태틱 기하구조에 따라 다양하게 변하기 때문에 효율적인 훈련 데이터베이스 구축은바이스태틱 표적식별에서의 핵심 사항이 된다. 본 논문에서는 모노스태틱 표적식별에서 효과적인 성능을 보였던 비행시나리오에 기반한 훈련 데이터베이스 구축 기법을 바이스태틱 표적식별에 적용해 보고, 그 성능과 효율성을 분석한다.
시뮬레이션에서는 레이다와 표적의 거리가 충분히 먼 경우, 비행시나리오에 기반한 데이터베이스를 이용하여 효율적으로 바이스태틱 표적식별을 수행할 수 있음을 보인다.22Nkc
