대규모 점군 및 폴리곤 모델의 GLSL 기반 실시간 렌더링 알고리즘

박상근(Sangkun Park) (사)한국CDE학회 2014 한국CDE학회 논문집 Vol.19 No.3

This paper presents a real-time rendering algorithm of large-scale geometric data using GLSL (OpenGL shading language). It details the VAO (vertex array object) and VBO(vertex buffer object) to be used for up-loading the large-scale point clouds and polygon meshes to a graphic video memory, and describes the shader program composed by a vertex shader and a fragment shader, which manipulates those large-scale data to be rendered by GPU. In addition, we explain the global rendering procedure that creates and runs the shader program with the VAO and VBO. Finally, a rendering performance will be measured with application examples, from which it will be demonstrated that the proposed algorithm enables a real-time rendering of large amount of geometric data, almost impossible to carry out by previous techniques.

근사 최적화 기법을 이용한 펀치 단조품의 예비성형체 설계

박상근(Park, Sangkun) 한국산학기술학회 2014 한국산학기술학회논문지 Vol.15 No.7

본 연구는 본 연구에서 제안하는 근사 최적화 방법(메타모델 기반의 시뮬레이션 최적화)을 사용하여 저렴한 해석 비용으로 펀치 단조품의 예비성형체(preform)를 설계한다. 본 연구에서 사용한 설계목표는 유효변형률의 균일한 분포이고 설계변수는 예비성형체 치수이며, 구속조건으로 최대 미충진 비율을 사용한다. 이를 위해 먼저 예비성형펀치(반재), 마스터펀치(상부다이) 및 하부다이로 구성되는 단조성형 공정을 DEFORM 시뮬레이션에 의해 모사하고, 이 시뮬레이션 결과가 실제 단조 공정을 모사하고 있는지 확인하는 검증 방법에 관해 소개한다. 또한 본 연구에서 수행한 설계 최적화 과정, 즉 (i) 초기 메타모델의 생성, (ii) 메타모델의 최적화 수행, (iii) 메타모델 최적해의 검증, (iv) 메타모델의 개선에 관하여 상세히 기술한다. In this paper, attempts were made to design a preform for a final punch inexpensively using the proposed approximate optimization method or metamodel-based simulation optimization. The design objective of this work is to achieve a uniform distribution of effective strains, the angle dimension of the preformed punch is chosen as a design variable, and maximum underfill ratio is used as a constraint. For this optimization, a computer simulation of a practical punch forging process is run using DEFORM software, in which a preformed punch(workpiece), a master punch(upper die), and a bottom die are dealt with. A validation method is introduced to determine if the simulation results match the actual forging process. In addition, this work presents the detailed design optimization procedure consisting of (i) generation of an initial metamodel, (ii) metamodel optimization, (iii) validation of metamodel-predicted optimum, and (iv) metamodel improvement.

나사 풀림 방지를 위한 삽입 부품의 설계 최적화

박상근(Park, Sangkun) 한국산학기술학회 2015 한국산학기술학회논문지 Vol.16 No.4

본 연구는 볼트강도등급 10.9에 의해 추천되는 조임 토크 640~800(Nm)가 볼트-너트 체결체에 가해졌을 때 풀림 방지를 위한 코일 스프링의 삽입 및 시뮬레이션 기반 설계 최적화에 관한 것이다. 먼저 볼트-너트-코일스프링으로 구성된 조립체에 대하여 등가응력에 기반을 둔 구조 안전성 판단을 위한 조립체 구조해석 시뮬레이션을 수행한다. 그리고 이러한 해석 시뮬레이션 결과로부터 설계 개선안 도출을 위한 설계전략을 수립한다. 또한 이 전략 안에서 기존 설계의 성능을 개선 해 나가는 반복 과정을 제안한다. 이 과정에서는 먼저 반응표면법을 사용하여 설계 파라미터 후보점을 찾고, 그 후보점의 반응값과 실제 시뮬레이션 결과를 비교함으로써 설계 후보점(코일스프링 감감수 N = 6)이 최적인지를 검증한다. This study deals the optimization design with the simulation based design of a coil spring inserted into the lock nut for preventing the screw thread from loosening at the bolted joint when the high-strength steel bolt with the property class of 10.9 is used and the screw torque of 640 to 800 (Nm) is applied. In this study, structural analysis of assembly composed of bolt, nut and coil spring is carried out to evaluate its safety factors on the basis of the equivalent stress with commercial finite element analysis software. And the design strategy to extract the design improvement from these simulation results is established. An iterative process performed with the proposed design strategy is also proposed for improving the performance of the existing design. At the proposed procedure, the feasible design parameters using response surface method are found, and then these parameters are verified to be optimal or not by comparing with the response values and the simulation results obtained from the feasible parameters.

딥러닝 성능 향상을 위한 3D 의료 영상 증강법

박상근(Sangkun Park) (사)한국CDE학회 2021 한국CDE학회 논문집 Vol.26 No.2

This paper proposes a 3D image augmentation method for improving the generalization performance of deep neural networks. It allows us to enrich the diversity of training data samples that is essential in medical image segmentation tasks, thus reducing the data overfitting problem caused by the fact the scale of medical image dataset is typically smaller. It also enables us to predict medical segmentation surfaces in Euclidean space without additional labeled datasets. This method includes image transformation functions, which are comprised of a spatial deformation and image intensity change, enabling the synthesis of complex effects such as variations in anatomy and image acquisition procedures. Our numerical experiments demonstrate that the proposed approach provides significant improvements over state-of-the-art methods for 3D medical image segmentation.

지향점 데이터로부터 폴리곤 곡면 재건 방법

박상근(Sangkun Park) (사)한국CDE학회 2020 한국CDE학회 논문집 Vol.25 No.4

We present a fast, memory efficient algorithm that reconstructs a manifold polygonal mesh approximately passing through a set of 3D oriented points. Nothing is assumed about the distribution of point set except that the point set is sampled from a real manifold surface. Our algorithm includes 3D convex hull, octree structure, SDF(signed distance function) for implicit framework, and marching cubes. The 3D convex hull provides us with a fast computation of SDF, octree structure allows us to compute a minimal distance for SDF, and marching cubes lead to iso-surface generation with SDF. Our approach gives us flexibility in the choice of the resolution of the reconstructed surface, and it also enables us to use on low-level PCs with minimal peak memory usage. Experimenting with publicly available scan data shows that we can reconstruct a polygonal mesh from point cloud of sizes varying from 10,000~1,000,000 in about 1~60 seconds on Intel(R) i7-7700K CPU @ 4.20 ㎓, 16 GB RAM.

비정렬 다변수 데이터의 B-스플라인 근사화 기법

박상근(Sangkun Park) 대한기계학회 2011 大韓機械學會論文集A Vol.35 No.8

본 연구는 B-스플라인 하이퍼볼륨을 사용하여 주어진 비정렬 데이터를 근사화하는 데이터 근사 기법에 관한 것이다. 개발 구현을 위한 B-스플라인 하이퍼볼륨의 자료 구조가 기술되며 해당 메모리 크기의 측정을 통해 간결한 표현 모델임을 보인다. 제안하는 근사 기법은 두 가지 알고리즘으로 구성된다. 하나는 B-스플라인 하이퍼볼륨의 절점 벡터 결정에 관한 것이고, 다른 하나는 조정점 결정에 관한 것으로 최소자승 최소화 문제의 해를 구함으로써 얻게 된다. 여기서 구한 해는 데이터 복잡성에 의존하지 않는다. 본 연구 방식은 다양한 형태의 데이터 분포를 가지고 근사 정밀도, 메모리 사용량, 계산 시간 등의 근사화 성능(수준)을 평가한다. 더불어 기존 방법과의 비교를 통해 유용성을 보이며, 비구속 최적화 예제를 통하여 다양한 응용 분야로의 가능성을 보여준다. This paper presents a data-fitting technique in which a B-spline hypervolume is used to approximate a given data set of scattered data samples. We describe the implementation of the data structure of a B-spline hypervolume, and we measure its memory size to show that the representation is compact. The proposed technique includes two algorithms. One is for the determination of the knot vectors of a B-spline hypervolume. The other is for the control points, which are determined by solving a linear least-squares minimization problem where the solution is independent of the data-set complexity. The proposed approach is demonstrated with various data-set configurations to reveal its performance in terms of approximation accuracy, memory use, and running time. In addition, we compare our approach with existing methods and present unconstrained optimization examples to show the potential for various applications.

전역 최적화를 위한 B-스플라인 기반의 Branch & Bound 알고리즘

박상근(Sangkun Park) (사)한국CDE학회 2010 한국CDE학회 논문집 Vol.15 No.1

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

무작위 데이터 근사화를 위한 유계오차 B-스플라인 근사법

박상근(Sangkun Park) (사)한국CDE학회 2012 한국CDE학회 논문집 Vol.17 No.4

This paper presents an error-bounded B-spline fitting technique to approximate unorganized data within a prescribed error tolerance. The proposed approach includes two main steps: leastsquares minimization and error-bounded approximation. A B-spline hypervolume is first described as a data representation model, which includes its mathematical definition and the data structure for implementation. Then we present the least-squares minimization technique for the generation of an approximate B-spline model from the given data set, which provides a unique solution to the problem: overdetermined, underdetermined, or ill-conditioned problem. We also explain an algorithm for the error-bounded approximation which recursively refines the initial base model obtained from the least-squares minimization until the Euclidean distance between the model and the given data is within the given error tolerance. The proposed approach is demonstrated with some examples to show its usefulness and a good possibility for various applications.

볼트 체결체 나사풀림 방지를 위한 삽입 부품 설계에 관한 연구

박상근(Sangkun Park),오현종(Hyeon Jong O) (사)한국CDE학회 2011 한국 CAD/CAM 학회 학술발표회 논문집 Vol.2011 No.1

본 연구는 볼트강도등급 10.9 에 의해 추천되는 조임 토크 640~800(Nm)가 볼트-너트 체결체에 가해졌을 때 풀림 방지를 위한 코일 스프링의 삽입 및 설계 파라미터 선정에 관한 것으로서, 먼저 볼트-너트-코일스프링으로 구성된 조립체에 대하여 등가응력에 기반을 둔 구조 안전성 판단을 위한 조립체 구조해석 시뮬레이션을 수행한다. 그리고 이러한 해석 시뮬레이션 결과로부터 설계 개선안 도출을 위한 전략 수립 및 점차적으로 기존 설계를 개선해 나가는 반복 과정을 제안한다. 또한 이러한 제안된 설계 개선 과정에 의해 도출된 최종 시뮬레이션 결과와 이로부터 탐색된 근사 최적화 결과를 함께 제시한다.

고비용 블랙박스 함수의 RBF기반 근사 최적화 기법

박상근(Sangkun Park) (사)한국CDE학회 2016 한국CDE학회 논문집 Vol.21 No.4

This paper proposes a method for expensive black box optimization using radial basis functions (RBFs). The proposed algorithm is a computational strategy that uses a RBF model approximating the expensive black box function to predict an optimum. First, a RBF-based approximation technique is introduced and a sampling plan for estimation of the black box function is described. Then the proposed algorithm is explained, which presents the pseudo-codes for implementation and the detailed description of each step performed in the optimization process. In addition, numerical experiments will be given to analyze the performance of the proposed algorithm, by investigating computation accuracy, number of function evaluations, and convergence history. Finally, geometric distance problem as application example will be also presented for showing the algorithm applicability to different engineering problems.