• 지구물리와물리탐사
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• 제26권3호
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• pp.114-125
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• 2023

편미분방정식의 해를 구하기 위한 여러 수치해법들의 한계와 순수 데이터 기반 기계학습의 단점을 극복하기 위해 물리정보신경망(physics-informed neural network, PINN)이 제안되었다. 물리정보신경망은 편미분방정식을 손실함수 구성에 직접 활용하여 기계학습 훈련에 물리적 제약을 주는 기법으로 파동방정식 모델링에도 활용될 수 있다. 그러나 물리정보신경망을 이용하여 파동방정식을 풀기 위해서는 신경망 훈련 시 입력에 대한 2차 미분이 수행되어야 하고, 그 결과로 출력되는 파동장은 복잡한 역학적 현상들을 포함하고 있어 섬세한 전략이 필요하다. 이 해설 논문에서는 물리정보신경망의 기본 개념을 설명하고 파동방정식 모델링에 활용하기 위한 고려사항들에 대해 고찰하였다. 이러한 고려사항에는 공간좌표 정규화, 활성함수 선정, 물리손실 추가 전략이 포함된다. 훈련자료의 공간좌표를 정규화한 후 사용하면 파동방정식 모델링을 위한 신경망 훈련에서 초기 조건이 더 정확하게 반영되는 것을 수치 실험을 통해 보였다. 또한 신경망을 통한 파동장 예측에 가장 적절한 활성함수를 선정하기 위해 여러 함수들의 특성을 비교했다. 특성 비교는 각 활성함수들의 입력자료에 대한 미분과 수렴성을 중심으로 이루어졌다. 마지막으로 신경망 훈련 중 손실함수에 물리손실을 추가하는 두가지 시나리오의 결과를 비교하였다. 수치 실험을 통해 훈련 초기부터 물리손실을 활용하는 전략보다 초기 훈련단계 이후부터 물리손실을 적용하는 커리큘럼 기반 학습전략이 효과적이라는 결과를 도출했다. 추가로 이 결과를 물리손실을 전혀 사용하지 않은 훈련 결과와 비교하여 PINN기법의 효과를 확인하였다.

• Current Optics and Photonics
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• 제1권2호
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• pp.143-149
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• 2017

LED arrays with pixel numbers of $3{\times}3$, $4{\times}4$, and $5{\times}5$ have been studied in this paper in order to enhance the optical output power and decrease heat dissipation of an AlGaInP-based light emitting diode display device (pixel size of $280{\times}280{\mu}m$) fabricated by micro-opto-electro-mechanical systems. Simulation results showed that the thermal resistances of the $3{\times}3$, $4{\times}4$, $5{\times}5$ arrays were $52^{\circ}C/W$, $69.7^{\circ}C/W$, and $84.3^{\circ}C/W$. The junction temperature was calculated by the peak wavelength shift method, which showed that the maximum value appears at the center pixel due to thermal crosstalk from neighboring pixels. The central temperature would be minimized with $40{\mu}m$ pixel pitch and $150{\mu}m$ substrate thickness as calculated by thermal modeling using finite element analysis. The modeling can be used to optimize parameters of highly integrated AlGaInP-based LED arrays fabricated by micro-opto-electro-mechanical systems technology.

• Nuclear Engineering and Technology
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• 제51권4호
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• 지구물리와물리탐사
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• 제26권4호
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• pp.268-274
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• 2023

유한 단층 미끌림 역산에는 지진 변위 측지 자료와 그린 함수 행렬(Green's function matrix)을 주로 사용한다. 그린 함수 행렬은 일반적으로 오카다 모형(Okada, 1985)을 기반으로 한다. 그러나 최근 물리 기반 지진 모델링을 활용하여 그린 함수 행렬을 제작하고 유한 단층 미끌림 역산을 수행하는 연구가 활발하다. 물리 기반 지진 모델링은 다양한 물성(탄성, 점탄성, 탄소성 등)을 고려하여 현실적인 환경에서 지진을 모사할 수 있다는 장점이 있다. 물리 기반 유한요소 소프트웨어 PyLith는 단층을 구성하는 절점을 두 개로 나누어 지진을 모사할 수 있으므로 지진 모사 모델링에 적합하다. 하지만 PyLith는 격자망 생성 기능을 자체 제공하지 않아, 모형 내부에 수십~수백 개의 소단층과 관측점을 설정해야 하는 유한 단층 미끌림 역산 수행에는 어려움이 있다. 본 연구에서는 소단층과 관측점을 포함한 수치 모형을 제작하고, 지진 모사 모델링을 수행하여 그린 함수 행렬을 제작하는 일련의 과정을 연계하여 유한 단층 미끌림 역산의 편리성을 높이기 위해 CPInterface (COMSOL-PyLith Interface)를 개발하였다. CPInterface는 COMSOL의 격자 생성 능력과 PyLith의 지진 모사 능력을 결합하여 그린 함수 행렬을 자동으로 생성할 수 있다. CPInterface는 간단한 변수들로 모형 및 단층 정보를 조절할 수 있고, 지하 탄성 이상체와 GPS 관측점을 자유롭게 배치할 수 있다. 또한, 그린 함수 행렬을 생성하는 복잡한 과정을 간소화하여 더욱 편리하게 유한 단층 미끌림 역산을 할 수 있게 한다.

• Current Optics and Photonics
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• 제4권6호
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• pp.509-515
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• 2020

A practical single photon source for fiber-based quantum information processing is still lacking. As a possible 1.55-㎛ quantum-dot single photon source, an InGaAsP/InP-air-aperture micropillar cavity is investigated in terms of fabrication tolerance. By properly modeling the processing uncertainty in layer thickness, layer diameter, surface roughness and the cavity shape distortion, the fabrication imperfection effects on the cavity quality are simulated using a finite-difference time-domain method. It turns out that, the cavity quality is not significantly changing with the processing precision, indicating the robustness against the imperfection of the fabrication processing. Under thickness error of ±2 nm, diameter uncertainty of ±2%, surface roughness of ±2.5 nm, and sidewall inclination of 0.5°, which are all readily available in current material and device fabrication techniques, the cavity quality remains good enough to form highly efficient and coherent 1.55-㎛ single photon sources. It is thus implied that a quantum dot contained InGaAsP/InP-air-aperture micropillar cavity is prospectively a practical candidate for single photon sources applied in a fiber-based quantum information network.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.612-615
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• 2007

This research studies the Virtual Reality simulation of Newton's physics law on rigid body type of objects for physics learning. With network support, collaborative interaction is enabled so that people from different places can interact with the same set of objects in Collaborative Virtual Environment. The taxonomy of the interaction in different levels of collaboration is described as: distinct objects and same object, in which there are same object - sequentially, same object - concurrently - same attribute, and same object - concurrently - distinct attributes. The case studies are the interaction of users in two cases: destroying and creating a set of arranged rigid bodies. We identify a specific type of application for contents authoring with modeling systems integrated with real-time physics and implemented in VR system. In our application called Virtual Dollhouse, users can observe physics law while constructing a dollhouse using existing building blocks, under gravity effects.

• International Journal of CAD/CAM
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• 제9권1호
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• pp.93-102
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• 2010

Shaping realistic hairstyles for digital characters is a difficult, long and tedious task. The lack of appropriate interaction metaphors enabling efficient and simple, yet accurate hair modeling further aggravates the situation. This paper presents 3D interaction metaphors for modeling virtual hair using haptic interfaces. We discuss user tasks, ergonomic aspects, as well as haptics-based styling and fine-tuning tools on an experimental prototype. In order to achieve faster haptic rates with respect to the hair simulation and obtain a transparent rendering, we adapt our simulation models to comply with the specific requirements of haptic hairstyling actions and decouple the simulation of the hair strand dynamics from the haptic rendering while relying on the same physiochemical hair constants. Besides the direct use of the discussed interaction metaphors in the 3D modeling area, the presented results have further application potential in hair modeling facilities for the entertainment industry and the cosmetic sciences.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.728-744
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• 2024

The presence of hydrogen absorbed by zirconium-based cladding materials during reactor operation can trigger degradation mechanisms and endanger the rod integrity. Ensuring the durability of the rods in extended time-frames like dry storage requires anticipating hydrogen behavior using numerical modeling. In this context, the present paper describes a hydrogen post-processing tool for Falcon - HYPE, a PSI's in-house tool able to calculate hydrogen uptake, transport, thermochemistry, reorientation of hydrides and hydrogen-related failure criteria. The tool extracts all necessary data from a Falcon output file; therefore, it can be considered loosely coupled to Falcon. HYPE has been successfully validated against experimental data and applied to reactor operation and interim storage scenarios to present its capabilities.

• 전기학회논문지
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• 제59권11호
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• pp.2012-2015
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• 2010

In this paper, the mathematical models of the superheater and the desuperheater are derived based on the fundamental laws of physics, mass and energy balance. The parameters of the models are developed for the 500[MW] thermal power plant using the actual data. The simulated model outputs are well matched with the actual ones. It is expected that the proposed models are useful for the temperature controller design of the thermal power plant.