Wyniki wyszukiwania - BazTech

1

Numerical investigation of the effect of topology optimisation methods parameters in the topology quality, the strength, and the computational cost

Ait Ouchaoui A., Nassraoui M., Radi B.

Archives of Materials Science and Engineering

|

2023

|

Vol. 123, nr 2

55--71

EN

Purpose: The literature abounds with many distinct topology optimisation methods, many of which share common parameter configurations. This study demonstrates that alternative parameter configurations may produce better results than common parameters. Additionally, we try to answer two fundamental questions: identifying the most effective topology optimisation method and determining the optimal parameter selection within this optimisation method. In order to respond to these questions, we conducted a comparative and objective analysis of topology optimisation methods. Design/methodology/approach: This paper evaluates four prominent topology optimisation methodologies, SIMP, RAMP, BESO, and LSM, based on three essential criteria: structural strength, topology quality, and computational cost. We conducted an in-depth examination of 12,500 topology optimisation results spanning a broad range of critical parameter values. These outcomes were generated using MATLAB codes. In the meantime, we comprehensively compared our findings with the existing literature on this subject. Findings: As predicted, our chosen parameters had a substantial effect on the topology quality, structural strength, and computational cost of the topology optimisation outcomes. Across the 12,500 results, many parameter combinations appeared to produce favourable results compared to conventional parameters commonly found in the existing literature. Research limitations/implications: This study focuses exclusively on four specific topology optimisation methods; however, its findings may be extrapolated to apply to other methodologies. Additionally, while it extensively examines the effects of parameters on topology quality, strength, and computational cost, it does not encompass an exploration of these parameters' impacts on other performance criteria. Originality/value: Novel parameter configurations for topology optimisation have been identified, yielding enhanced outcomes in terms of topology quality, structural strength, and computational efficiency.

2

Deep-segmentation of plantar pressure images incorporating fully convolutional neural networks

Wang Dan, Li Zairan, Dey Nilanjan, Ashour Amira S., Moraru Luminita, Simon Sherratt R., Shi Fuqian

Biocybernetics and Biomedical Engineering

|

2020

|

Vol. 40, no. 1

546--558

EN

Comfort shoe-last design relies on the key points of last curvature. Traditional plantar pressure image segmentation methods are limited to their local and global minimization issues. In this work, an improved fully convolutional networks (FCN) employing SegNet (SegNet+FCN 8 s) is proposed. The algorithm design and operation are performed using the visual geometry group (VGG). The method has high efficiency for the segmentation in positive indices of global accuracy (0.8105), average accuracy (0.8015), and negative indices of average cross-ratio (0.6110) and boundary F1 index (0.6200). The research has potential applications in improving the comfort of shoes.

3

A hybrid approach for the delineation of brain lesion from CT images

Gautam A., Raman B., Raghuvanshi S.

Biocybernetics and Biomedical Engineering

|

2018

|

Vol. 38, no. 3

504--518

EN

Brain lesion segmentation from radiological images is the most important task in accurate diagnosis of patients. This paper presents a hybrid approach for the segmentation of brain lesion from computed tomography (CT) images based on the combination of fuzzy clustering using hyper tangent function as the robust kernel and distance regularized level set evolution (DRLSE) function as the edge based active contour method. Kernel based fuzzy clustering method divides the image into different regions. These regions can be used to find region of interest by using DRLSE algorithm to generate the optimal region boundary. The proposed method results in smooth boundary of the required regions with high accuracy of segmentation. In this paper, results are compared with standard fuzzy c-means (FCM) clustering, spatial FCM, robust kernel based fuzzy clustering (RFCM) and DRLSE algorithms. The performance of the proposed method is evaluated on CT scan images of hemorrhagic lesion, which shows that our method can segment brain lesion more accurately than the other conventional methods.

4

Automatic brain hemorrhage segmentation and classification algorithm based on weighted grayscale histogram feature in a hierarchical classification structure

Shahangian B., Pourghassem H.

Biocybernetics and Biomedical Engineering

|

2016

|

Vol. 36, no. 1

217--232

EN

Brain hemorrhage is the first cause of death in ages between 15 and 24, and the third after heart diseases and cancers in other ages. Saving the lives of such patients completely depends on detecting the correct location and type of the hemorrhage in an early stage. In this paper, an automatic brain hemorrhage detection and classification algorithm on CT images is proposed. To achieve this purpose, after preprocessing, a modified version of Distance Regularized Level Set Evolution (MDRLSE) is used to detect and separate the hemorrhage regions. Then a perfect set of shape and texture features from each detected hemorrhage region are extracted. Moreover, we define a synthetic feature that is called weighted grayscale histogram feature. In this feature, valuable information from shape, position and area of the hemorrhage are integrated with the grayscale histogram of hemorrhage region. After that a synthetic feature selection algorithm is applied to select the most convenient features. Eventually, the seg- mented regions are classified into four types of the hemorrhages such as EDH, ICH, SDH and IVH by a hierarchical structure of classification. Our proposed algorithm is evaluated on a perfect set of CT-scan images and obtains the accuracy rate of 96.15%, 95.96% and 94.87% for the segmentation of the EDH, ICH, and SDH types, respectively. Also our proposed classification structure provides the accuracy rate of 92.46% and 94.13% for the first and second classifiers of the hierarchical classification structure for classifying the IVH from normal class and the EDH, ICH and SDH hemorrhage classes, respectively.

5

Level-set image processing methods in medical image segmentation

Maciejewski M., Surtel W., Maciejewska B., Małecka-Massalska T.

Bio-Algorithms and Med-Systems

|

2015

|

Vol. 11, no. 1

47--51

EN

In this paper, two image processing methods for use in medical image processing based on the level set method are described. The theoretical bases are described and the methods are applied to a set of sample computed tomography images. The results are then compared. The results indicate that the Chan-Vese method is more useful for image segmentation in medicine than the distanceregulated method owing to both the significant differences in calculation time and the quality of results obtained for noisy images.

6

Integrated region-based segmentation using color components and texture features with prior shape knowledge

Emambakhsh M., Ebrahimnezhad H., Sedaaghi M. H.

International Journal of Applied Mathematics and Computer Science

|

2010

|

Vol. 20, no 4

711-726

EN

Segmentation is the art of partitioning an image into different regions where each one has some degree of uniformity in its feature space. A number of methods have been proposed and blind segmentation is one of them. It uses intrinsic image features, such as pixel intensity, color components and texture. However, some virtues, like poor contrast, noise and occlusion, can weaken the procedure. To overcome them, prior knowledge of the object of interest has to be incorporated in a top-down procedure for segmentation. Consequently, in this work, a novel integrated algorithm is proposed combining bottom-up (blind) and top-down (including shape prior) techniques. First, a color space transformation is performed. Then, an energy function (based on nonlinear diffusion of color components and directional derivatives) is defined. Next, signeddistance functions are generated from different shapes of the object of interest. Finally, a variational framework (based on the level set) is employed to minimize the energy function. The experimental results demonstrate a good performance of the proposed method compared with others and show its robustness in the presence of noise and occlusion. The proposed algorithm is applicable in outdoor and medical image segmentation and also in optical character recognition (OCR).

7

Optimal internal dissipation of a damped wave equation using a topological approach

Münch A

International Journal of Applied Mathematics and Computer Science

|

2009

|

Vol. 19, no 1

15-37

EN

We consider a linear damped wave equation defined on a two-dimensional domain [...], with a dissipative term localized in a subset [...]. We address the shape design problem which consists in optimizing the shape of [...] in order to minimize the energy of the system at a given time T. By introducing an adjoint problem, we first obtain explicitly the (shape) derivative of the energy at time T with respect to the variation in [...]. Expressed as a boundary integral on [...], this derivative is then used as an advection velocity in a Hamilton-Jacobi equation for shape changes. We use the level-set methodology on a fixed working Eulerian mesh as well as the notion of the topological derivative. We also consider optimization with respect to the value of the damping parameter. The numerical approximation is presented in detail and several numerical experiments are performed which relate the over-damping phenomenon to the well-posedness of the problem.

8

Object based segmentation of video using variational level sets

Cheng B., Wang Y., Zheng N., Bian Z.

Machine Graphics and Vision

|

2005

|

Vol. 14, No. 2

145-157

EN

The paper demonstrates a new approach to video segmentation which retains some of the attractive features of existing methods and overcomes some of their limitations. The video sequence is represented as a spatio-temporal volume, and is segmented by an extension of active contour model based on Mumford-Shah techniques. The energy function minimization is similar to 3D interface evolution with curvature-dependent speeds. The spatio-temporal volume need not to be smoothed before processing because our method is not sensitive to noise. Each object needs a closed interface, which is embedded as a level set of a higher-dimensional functions, and is propagated by solving a partial differential equation. The interface stops in the vicinity of object boundaries, which are not necessarily defined by the gradient and can be represented with complex topologies. Finally, an experiment is given to show the effectiveness and robustness of the method.

9

A new approach for simultaneous shape and topology optimization based on dynamic implicit surface function

Guo H., Zhao K., Wang M. Y.

Control and Cybernetics

|

2005

|

Vol. 34, no 1

255-282

EN

In the present paper, a new approach for structural topology optimization based on dynamic implicit surface function (DISF) is proposed. DISF is used to describe the shape/topology of a structure, which is approximated in terms of the nodal values. Then, a relationship is established between the element stiffness and the values of the implicit surface function on its four nodes. In this way and with some non-local treatments of the design sensitivities, not only the shape derivative but also the topological derivative of the optimal design can be incorporated in the numerical algorithm in a unified way. Numerical experiments demonstrate that by employing this approach, the computational efforts associated with DISF (and level set) based algorithms can be diminished. Clear optimal topologies and smooth structural boundaries free from any sign of numerical instability can be obtained simultaneously and efficiently.

10

Accurate numerical simulation of interface phenomena in two phase flow

Sehgal B. R., Bui V. A., Dinh T. N.

Zeszyty Naukowe Politechniki Świętokrzyskiej. Mechanika

|

1999

|

Z. 67

113--125

EN

Surface phenomena and hydrodynamic interactions, occuring at the liquid-liquid interfaces, are numerically investigated using an advanced modeling approach, based on Eulearian representation of the flow field coupled with an explicit interface tracking method, named the Level Set Method, which accurately follows the interfacial evolution in time. A high-order numerical scheme, called CIP (Cubic-lnterpolated-Pseudoparticle), is employed to solve the Navier-Stokes and the level set equations with high accuracy. The surface tension force is modeled and included as a source term in the momentum equations. The modeling approach was applied to study some important practical problems, such as the development of the Kelvin-Helmholtz instability at an interface and the deformation and fragmentation of high-density jet/drops in a flow field. Sensitivity analysis was also performed, which helped to identify factors, important in governing the interfacial interactions and their effects.