Multi-scale model updating for the mechanical properties of cross-laminated timber

2016 ◽  
Vol 177 ◽  
pp. 83-90 ◽  
Author(s):  
E.I. Saavedra Flores ◽  
R.M. Ajaj ◽  
I. Dayyani ◽  
Y. Chandra ◽  
R. Das
Keyword(s):  
Mechanical Properties ◽  
Model Updating ◽  
Scale Model ◽  
Cross Laminated Timber ◽  
Multi Scale

scholarly journals Multi-scale model updating of a timber footbridge using experimental vibration data

2017 ◽  
Vol 34 (3) ◽  
pp. 754-780 ◽  
Author(s):  
Rafael Castro-Triguero ◽  
Enrique Garcia-Macias ◽  
Erick Saavedra Flores ◽  
M.I. Friswell ◽  
Rafael Gallego
Keyword(s):  
Structural Model ◽  
Model Updating ◽  
Ambient Vibration ◽  
Scale Model ◽  
Structural Behavior ◽  
Modal Parameters ◽  
Content Type ◽  
Multi Scale ◽  
Ambient Vibration Tests ◽  
Vibration Tests

Purpose The purpose of this paper is to capture the actual structural behavior of the longest timber footbridge in Spain by means of a multi-scale model updating approach in conjunction with ambient vibration tests. Design/methodology/approach In a first stage, a numerical pre-test analysis of the full bridge is performed, using standard beam-type finite elements with isotropic material properties. This approach offers a first structural model in which optimal sensor placement (OSP) methodologies are applied to improve the system identification process. In particular, the effective independence (EFI) method is used to determine the optimal locations of a set of sensors. Ambient vibration tests are conducted to determine experimentally the modal characteristics of the structure. The identified modal parameters are compared with those values obtained from this preliminary model. To improve the accuracy of the numerical predictions, the material response is modeled by means of a homogenization-based multi-scale computational approach. In a second stage, the structure is modeled by means of three-dimensional solid elements with the above material definition, capturing realistically the full orthotropic mechanical properties of wood. A genetic algorithm (GA) technique is adopted to calibrate the micromechanical parameters which are either not well-known or susceptible to considerable variations when measured experimentally. Findings An overall good agreement is found between the results of the updated numerical simulations and the corresponding experimental measurements. The longitudinal and transverse Young's moduli, sliding and rolling shear moduli, density and natural frequencies are computed by the present approach. The obtained results reveal the potential predictive capabilities of the present GA/multi-scale/experimental approach to capture accurately the actual behavior of complex materials and structures. Originality/value The uniqueness and importance of this structure leads to an intensive study of its structural behavior. Ambient vibration tests are carried out under environmental excitation. Extraction of modal parameters is obtained from output-only experimental data. The EFI methodology is applied for the OSP on a large-scale structure. Information coming from several length scales, from sub-micrometer dimensions to macroscopic scales, is included in the material definition. The strong differences found between the stiffness along the longitudinal and transverse directions of wood lumbers are incorporated in the structural model. A multi-scale model updating approach is carried out by means of a GA technique to calibrate the micromechanical parameters which are either not well-known or susceptible to considerable variations when measured experimentally.

Multi-scale characterization and modelling of damage evolution in nuclear Gilsocarbon graphite

2015 ◽  
Vol 1809 ◽  
pp. 1-6 ◽  
Author(s):  
Dong Liu ◽  
Peter Heard ◽  
Branko Šavija ◽  
Gillian Smith ◽  
Erik Schlangen ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Mechanical Testing ◽  
Numerical Models ◽  
Ion Beam ◽  
Microstructural Characterization ◽  
Scale Model ◽  
Small Scale ◽  
Length Scale ◽  
Multi Scale ◽  
Scale Characterization

ABSTRACTIn the present work, the microstructure and mechanical properties of Gilsocarbon graphite have been characterized over a range of length-scales. Optical imaging, combined with 3D X-ray computed tomography and 3D high-resolution tomography based on focus ion beam milling has been adopted for microstructural characterization. A range of small-scale mechanical testing approaches are applied including an in situ micro-cantilever technique based in a Dualbeam workstation. It was found that pores ranging in size from nanometers to tens of micrometers in diameter are present which modify the deformation and fracture characteristics of the material. This multi-scale mechanical testing approach revealed the significant change of mechanical properties, for example flexural strength, of this graphite over the length-scale from a micrometer to tens of centimeters. Such differences emphasize why input parameters to numerical models have to be undertaken at the appropriate length-scale to allow predictions of the deformation, fracture and the stochastic features of the strength of the graphite with the required confidence. Finally, the results from a multi-scale model demonstrated that these data derived from the micro-scale tests can be extrapolated, with high confidence, to large components with realistic dimensions.

Three-dimensional Reconstruction of Microscopic Image Based on Multi-ST Algorithm

2020 ◽  
Vol 64 (2) ◽  
pp. 20506-1-20506-7
Author(s):  
Min Zhu ◽  
Rongfu Zhang ◽  
Pei Ma ◽  
Xuedian Zhang ◽  
Qi Guo
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Scale Model ◽  
Microscopic Image ◽  
Multi Scale ◽  
Gaussian Pyramid ◽  
Cost Aggregation ◽  
Dimensional Reconstruction ◽  
Image Pairs ◽  
Accurate Matching

Abstract Three-dimensional (3D) reconstruction is extensively used in microscopic applications. Reducing excessive error points and achieving accurate matching of weak texture regions have been the classical challenges for 3D microscopic vision. A Multi-ST algorithm was proposed to improve matching accuracy. The process is performed in two main stages: scaled microscopic images and regularized cost aggregation. First, microscopic image pairs with different scales were extracted according to the Gaussian pyramid criterion. Second, a novel cost aggregation approach based on the regularized multi-scale model was implemented into all scales to obtain the final cost. To evaluate the performances of the proposed Multi-ST algorithm and compare different algorithms, seven groups of images from the Middlebury dataset and four groups of experimental images obtained by a binocular microscopic system were analyzed. Disparity maps and reconstruction maps generated by the proposed approach contained more information and fewer outliers or artifacts. Furthermore, 3D reconstruction of the plug gauges using the Multi-ST algorithm showed that the error was less than 0.025 mm.

Effects of parametric uncertainty on multi-scale model predictions of shock response of a pressed energetic material

2019 ◽  
Vol 125 (23) ◽  
pp. 235104 ◽  
Author(s):  
Sangyup Lee ◽  
Oishik Sen ◽  
Nirmal Kumar Rai ◽  
Nicholas J. Gaul ◽  
K. K. Choi ◽  
...  
Keyword(s):  
Energetic Material ◽  
Parametric Uncertainty ◽  
Scale Model ◽  
Multi Scale ◽  
Model Predictions ◽  
Shock Response

scholarly journals The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2454
Author(s):  
Yue Sun ◽  
Yanze Yu ◽  
Jinhao Guo ◽  
Minghai Zhang
Keyword(s):  
Habitat Selection ◽  
Environmental Factors ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Scale Model ◽  
Winter Habitat ◽  
Multi Scale ◽  
Optimal Scale ◽  
Scale Models ◽  
Selection Of

Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to assess habitat selection. The results showed that: (1) Univariate logistic regression analysis showed that the response scale of red deer to environmental factors was different among different covariate. The optimal scale of the single covariate was 800–3200 m, slope (SLP), altitude (ELE), and ratio of deciduous broad-leaved forests were 800 m in large scale, except that the farmland ratio was 200 m in fine scale. The optimal scale of road density and grassland ratio is both 1600 m, and the optimal scale of net forest production capacity is 3200 m; (2) distance to forest edges, distance to cement roads, distance to villages, altitude, distance to all road, and slope of the region were the most important factors affecting winter habitat selection. The outcomes of this study indicate that future studies on the effectiveness of habitat selections will benefit from multi-scale models. In addition to increasing interpretive and predictive capabilities, multi-scale habitat selection models enhance our understanding of how species respond to their environments and contribute to the formulation of effective conservation and management strategies for ungulata.

Sign in / Sign up

Export Citation Format

Share Document