Quadtree Decomposition Algorithm Research Articles

A numerical and experimental meso-mechanical approach for the prediction of creep of concrete

A two-step meso-scale approach is proposed to predict the creep of concrete. The approach requires the creep of cement paste as input, combined with meso-scale analysis of digital images of mortar and concrete that are obtained from X-ray microCT scanning. For the generation of input data and validation of the model, a comprehensive series of creep tests are carried out on cement paste, mortar and concrete cylinders for a period of 6 months. The model uses a robust and automatic quadtree decomposition algorithm to convert digital images into meshes, which are then solved using the scaled boundary finite element method based on a continuum approach. The proposed model is separately validated on the mortar and the concrete scale respectively. In the first step, knowing the creep response of cement paste from the tests, the creep of mortar is simulated by considering it as a two-phase composite comprising of viscoelastic cement paste and elastic fine aggregates. Validation of the predicted response is obtained through comparison with the measured creep response of mortar. A similar procedure is then applied for concrete which is treated as a two-phase composite of viscoelastic mortar and elastic coarse aggregates. Finally, by accounting for damage of the mortar phase, it is demonstrated that the nonlinear creep of concrete observed at high stress levels can be attributed to material damage developed at the meso-scale.

An image-based meso-scale model for the hygro-mechanical time-dependent analysis of concrete

A new computational framework is developed in this paper for investigating the time-dependent behaviour of concrete including creep, shrinkage and cracking. The developed model aims to explain certain aspects of the time-dependent cracking and creep of concrete that cannot be captured using homogeneous models. The model is based on the scaled boundary finite element method, and it is coupled with a quadtree decomposition algorithm which converts digital images of concrete meso-structures into meshes. Concrete is treated as a two-phase composite which consists of elastic aggregates and mortar that is subjected to time-dependent deformation. The basic creep behaviour is treated as viscoelastic, which is modelled based on a rate-type rheological model corresponding to a Kelvin chain. Drying creep is modelled using a viscous unit which depends on the stress level, and drying shrinkage is stress independent. Both drying creep and drying shrinkage are related to the internal humidity. The humidity distribution within concrete is determined using a diffusion analysis. The moisture movement within mortar is governed by a nonlinear diffusion equation, whereas the aggregates are assumed impermeable. The cracking of concrete is explicitly modelled on the meso-scale through coupling of the continuum damage model for cracking within the mortar phase, and the cohesive zone model for debonding between aggregates and mortar. The proposed model is verified by simulating well-documented experimental studies in the literature. The capability of the proposed model in simulating the time-dependent behaviour of concrete and capturing the crack patterns has also been demonstrated.

Non-conforming coupling RI-IGABEM for solving multidimensional and multiscale thermoelastic–viscoelastic problems

In this paper, a novel non-conforming coupling radial integration IGABEM (RI-IGABEM) is proposed to solve the multidimensional and multiscale thermoelastic–viscoelastic​ problems. Firstly, the displacement and regularized strain boundary integral equations for the thermoviscoelastic problems are derived. Secondly, the time-dependent shear modulus is expressed in the form of Prony series, and the memory stress is calculated by using the genetic integral, which reduces computing costs. In addition, the radial integration method (RIM) is applied to transform the domain integrals related to body force, temperature and memory stress into equivalent boundary integrals through applied points, which not only allows IGABEM to retain the advantage of discretization only on the boundary, but also reduces the singularity of the integral. Moreover, the adaptive integral method based on hierarchical quadtree decomposition algorithm is proposed to deal with the nearly singular integrals more flexible and efficient at optimal computational cost. The modified surface traction recovery method (TRM) of the thermoviscoelastic mechanics is proposed to solve the strains of the boundary points, which allows us to avoid solving hypersingular integrals. Furthermore, we construct the displacement (or tractions) coupling constraints among the non-conforming interface meshes by a virtual knot insertion technique. The main advantages of this method are simplicity and robustness, as it is problem-independent and only depends on the NURBS meshes on both sides of the interface. Some 2D and 3D examples are applied to prove the accuracy and efficiency of the present method for the multiscale thermoelastic–viscoelastic problems.

Automatic mesoscopic fracture modelling of concrete based on enriched SBFEM space and quad-tree mesh

• The methods by combining enriched SBFEM with quad-tree mesh are proposed to simulate crack propagation of concrete. • An improved random aggregate model is proposed to construct mesoscale concrete models. • The whole mesh generation process is highly efficient without any artificial interference. • Local remeshing is unnecessary as crack propagates. A novel approach for mesoscale modelling of concrete composites is proposed by combining enriched scaled boundary finite element methods with quad-tree mesh. The concrete meso -structures are comprised of randomly distributed aggregates, mortar matrix, and interface transition zone. An improved random aggregate generation technique is developed to construct digital images of mesoscale concrete models. Based on the quadtree decomposition algorithm, meshes can be generated automatically from the digital images of concrete mesostructure. The whole mesh generation process is highly efficient without any artificial interference and eliminates the issue of hanging nodes faced by standard finite elements. Additionally, local remeshing is unnecessary as crack propagates. Three numerical examples are modelled to demonstrate the performance of the proposed approach, and the effects of aggregate area fraction on the mechanical properties of concrete composites are also discussed.

Computational modelling of the basic creep of concrete: An image-based meso-scale approach

A 2D meso-scale numerical model is presented to investigate the basic creep of concrete, which is also applicable to various cementitious materials. The model runs a direct image-based analysis in which the internal structure of the material is obtained from X-ray micro-CT scanning. An automatic and robust quadtree decomposition algorithm is employed to convert digital images into meshes, which are then solved using the scaled boundary finite element method based on a continuum approach. Concrete and mortar are treated as a three-phase composite, consisting of viscoelastic binder, elastic aggregates and voids. The debonding of the interfacial transition zone between the aggregates and the binder is modelled using zero-thickness interface elements with traction separation laws. The basic creep model is based on a rate-type rheological model corresponding to a Kelvin chain and accounts for ageing. Numerical examples are carried out on both concrete and mortar images. The numerical study highlights some of the phenomena associated with the creep response and explores the capabilities of the proposed model.

Enhanced numerical integration scheme based on image-compression techniques: application to fictitious domain methods

In the present work, we propose a new approach, the so-called compressed adaptive integration scheme (C-AIS), for the computation of the stiffness and mass matrices in fictitious domain methods requiring the integration of discontinuous functions. The novel approach extends the conventional quadtree-decomposition-based adaptive integration scheme (AIS) by an additional step, in which established image-compression techniques are exploited to decrease the number of integration sub-cells. The benefits of the C-AIS are manifold: First, the compression of the sub-cells inevitably leads to significant savings in terms of computational time required by the numerical integration. Second, the compression procedure, which is executed directly after the quadtree-decomposition algorithm, can be easily included in existing codes. Third, if applied to polynomial integrands, the C-AIS yields exactly the same accuracy as the conventional AIS. Finally, the fourth advantage is seen in the fact that the C-AIS can readily be combined with other approaches seeking a reduction of the number of integration points such as the Boolean-FCM. The efficiency of the C-AIS approach is presented in the context of the FCM based on Cartesian meshes applied to problems of linear elastostatics and modal analysis, while it is also suitable for the quadrature in other fictitious domain approaches, e.g., CutFEM and cgFEM.

A novel scaled boundary finite element formulation with stabilization and its application to image‐based elastoplastic analysis

SummaryDigital images are increasingly being used as input data for computational analyses. This study presents an efficient numerical technique to perform image‐based elastoplastic analysis of materials and structures. The quadtree decomposition algorithm is employed for image‐based mesh generation, which is fully automatic and highly efficient. The quadtree cells are modeled by scaled boundary polytope elements, which eliminate the issue of hanging nodes faced by standard finite elements. A novel, simple, and efficient scaled boundary elastoplastic formulation with stablisation is developed. In this formulation, the return‐mapping calculation is only required to be performed at a single point in a polytope element, which facilitates the computational efficiency of the elastoplastic analysis and simplicity of implementation. Numerical examples are presented to demonstrate the efficiency and accuracy of the proposed technique for performing the elastoplastic analysis of high‐resolution images.

Hierarchical differential privacy hybrid decomposition algorithm for location big data

The biggest feature of the era of big data is that people can easily generate, access, and make use of massive data resources. As one of the most important and popular kind of big data, location big data and its application technology provide users with convenient services. However, improper collection, analysis and publishing of location big data also brings huge crisis of personal privacy disclosure. Spatial decomposition is one of the effective ways to achieve the statistics publication of location big data. In order to make full use of the redundant characteristics of location big data in spatial and temporal distribution, a hierarchical differential privacy hybrid decomposition algorithm is proposed in this paper. In the first layer of decomposition, an adaptive density grid structure is used to cluster the location big data, which not only reduces the uniform assumption errors but also avoids noise errors caused by large number of empty nodes. In order to guide the reasonable decomposition for skewed grids in the second layer, a heuristic quad-tree decomposition algorithm based on regional uniformity is designed, which solved the difficult problem for determining stop condition of the top-down decomposition of two-dimensional space. Comparative experiments show that the hierarchical differential privacy hybrid decomposition algorithm proposed in this paper has good effect in improving the accuracy of regional counting queries. The proposed algorithm has low computational complexity and obvious advantages in the publishing environment of big data.

A dual scheme for compression and restoration of sequentially transmitted images over Wireless Sensor Networks

A dual scheme for the compression and restoration of sequentially transmitted images over Wireless Sensor Networks (WSNs) is presented. These networks are characterized by low transmission rates, extended packet losses and limited power resources, factors that degrade the overall system performance. Especially in the cases of transmitting multimedia content, a considerable number of data packets are dropped, with a corresponding direct effect on the received image quality. For dealing with this loss of valuable information, various retransmission schemes have been proposed that act as quality of service modules. However, this approach increases energy consumption and inserts considerable time delays, due to the rise of the traffic load in the network. This article proposes a novel dual transmission scheme, targeting mainly the area of Multimedia WSNs (WMSN), that aims to decrease the overall traffic load introduced by the retransmission schemes, by performing image restoration for lost data packets, at the receiver side. The proposed novel dual scheme is based on: (a) the quad tree decomposition algorithm that is adopted for compressing the image data before transmission over the WSN, and (b) the fast image inpainting algorithm for restoring the effect of the missing data packets. The overall proposed scheme has been applied in multiple experimental studies that prove its efficacy.

Colour image segmentation using region-growing and region-merging methods

Image segmentation is the process of dividing the given image into regions homogeneous with respect to certain features, and which hopefully correspond to real objects in the actual scene. Region-growing algorithms have been used mostly in the analysis of greyscale images; however, some significant work has been completed in the colour. The original image is divided into image blocks, which are not overlapped; then, the mean and variance of each image block were calculated, and the image blocks were divided into homogeneous colour blocks and texture blocks by the variance of it. The initial seed regions are automatically selected depending on calculating the homogeneous colour. The quadtree decomposition algorithm was applied to split and merge the texture blocks. This process is followed until no more pixels can be added. The experimental segmentation results hold favourable consistency in terms of human perception, and confirm effectiveness of the algorithm.

Vision-Based Trajectory Generation for a Two-Link Robotic Arm Using Quadtree Decomposition and Curve Smoothing

In this article, the development of an autonomous robot trajectory generation system based on a single eye-in-hand webcam, where the workspace map is not known a priori, is described. The system makes use of image processing methods to identify locations of obstacles within the workspace and the Quadtree Decomposition algorithm to generate collision free paths. The shortest path is then automatically chosen as the path to be traversed by the robot end-effector. The method was implemented using MATLAB running on a PC and tested on a two-link SCARA robotic arm. The tests were successful and indicate that the method could be feasibly implemented on many practical applications.

An Application of the Inpainting Algorithm for Recovering Packet Losses from Transmitting Sequential Quad Tree Compressed Images Over Wireless Sensor Networks

In this article an application of the inpainting algorithm for recovering packet losses from transmitting sequential quad tree compressed images over wireless sensor networks is presented. The aim of the proposed scheme is to reconstruct the missing information at the receiver side, based on the inpainting algorithm, instead of increasing the overhead of the network by requesting from the transceiver to re-transmit the lost data packets. The proposed architecture initially compresses the images sequentially using the quad tree decomposition algorithm. In the sequel, at the receiver side, the image is reconstructed as a lossy image, based on the available successfully received data packets, while afterwards the proposed scheme applies the image inpainting algorithm, in order to restore any missing partitions of the image. The inpainting algorithm is performed based on information derived from the the received image itself. Experimental results are presented that prove the efficacy of the proposed scheme.

Adaptive Multiple-Resolution CMOS Active Pixel Sensor

A smart image sensor with adaptive multiple resolution ability is presented. This sensor is based on the quadtree decomposition algorithm, which decomposes an image into square homogeneous regions. After the image is segmented, only the value of the block and its size are stored or transmitted. On-chip implementation can solve the information bottleneck problem by reducing the amount of data for transmission. Good compression results can be achieved for scenes with predominant and homogeneous backgrounds. The algorithm is implemented on chip in a mixed-signal column parallel architecture in 0.35-mum 4M2P n-well TSMC CMOS technology available through MOSIS. Typical power dissipation for the test chip with 32times32 pixels is 70 mW at VDD=3.3 V

INTER-FRAME PREDICTION OF MEDICAL AND VIDEOPHONE SEQUENCES: A DEFORMABLE TRIANGLE-BASED APPROACH

Motion compensation using deformable triangle patches has been successfully used for low bit rate coding of videophone sequences. They were also shown to be particularly efficient for interframe coding of MRI sequences, for which the difference between image slices can be well modeled by locally affine deformations. Regular triangular meshes were used in previous works. In this paper, we present a quadtree decomposition algorithm to generate a triangle mesh for which smaller triangles are used in image areas where the motion or deformation is more complex. Grid points are recursively added to areas where the reduction in prediction error is more significant. Results show that using variable size triangular patches increases the PSNR of the motion-compensated image while reducing the number of grid points when compared to a regular triangular mesh.