Optimal finite element model with response surface methodology for concrete structures based on Terrestrial Laser Scanning technology

Abstract Terrestrial Laser Scanning (TLS) technology, which is hailed as another technological revolution in the field of surveying and mapping, is well known as a structural deformation monitoring device for concrete structures. In the current paper, we frame the finite element model (FEM) of concrete structure based on three-dimensional TLS technology and optimize the model by response surface methodology (RSM). It is theorized and confirmed that volume-based FEM model will be more precise than the displacement-based model, due to that the distortion of specimen is considered with the benefit from volumetric analysis when composite structures is distorted with loads.

[1]  Ingo Neumann,et al.  Laser Scanning-Based Updating of a Finite-Element Model for Structural Health Monitoring , 2016, IEEE Sensors Journal.

[2]  Mihailo Ristic,et al.  Fast and accurate NURBS fitting for reverse engineering , 2011 .

[3]  Herbert Edelsbrunner,et al.  Geometry and Topology for Mesh Generation , 2001, Cambridge monographs on applied and computational mathematics.

[4]  A. Abellán,et al.  Detection and spatial prediction of rockfalls by means of terrestrial laser scanner monitoring , 2010 .

[5]  George Vosselman,et al.  Airborne and terrestrial laser scanning , 2011, Int. J. Digit. Earth.

[6]  Ángel M. Felicísimo,et al.  Analysis of Uncertainty and Repeatability of a Low-Cost 3D Laser Scanner , 2012, Sensors.

[7]  Mohammad Omidalizarandi,et al.  Terrestrial laser scanning technology for deformation monitoring and surface modeling of arch structures , 2017 .

[8]  Norbert Pfeifer,et al.  DEFORMATION ANALYSIS OF A BORED TUNNEL BY MEANS OF TERRESTRIAL LASER SCANNING , 2006 .

[9]  T. Schmalz,et al.  An adaptive Kalman-filtering approach for the calibration of finite difference models of mass movements , 2010 .

[10]  Fernando Fraternali,et al.  A tensegrity approach to the optimal reinforcement of masonry domes and vaults through fiber-reinforced composite materials , 2015 .

[11]  Franco Bontempi,et al.  Genetic Algorithms for the Dependability Assurance in the Design of a Long‐Span Suspension Bridge , 2012, Comput. Aided Civ. Infrastructure Eng..

[12]  LinRen Zhou,et al.  Response Surface Method Based on Radial Basis Functions for Modeling Large-Scale Structures in Model Updating , 2013, Comput. Aided Civ. Infrastructure Eng..

[13]  Ingo Neumann,et al.  The Benefit of 3D Laser Scanning Technology in the Generation and Calibration of FEM Models for Health Assessment of Concrete Structures , 2014, Sensors.

[14]  Hyo Seon Park,et al.  A Deformed Shape Monitoring Model for Building Structures Based on a 2D Laser Scanner , 2013, Sensors.

[15]  Giordano Teza,et al.  Terrestrial Laser Scanner Resolution: Numerical Simulations and Experiments on Spatial Sampling Optimization , 2011, Remote. Sens..

[16]  Hyungjun Park,et al.  B-spline surface fitting based on adaptive knot placement using dominant columns , 2011, Comput. Aided Des..

[17]  Pedro Arias,et al.  Terrestrial laser scanning and limit analysis of masonry arch bridges , 2011 .

[18]  Nicolas Gayton,et al.  AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation , 2011 .

[19]  Hyo Seon Park,et al.  Computing Method for Estimating Strain and Stress of Steel Beams Using Terrestrial Laser Scanning and FEM , 2007 .

[20]  Fernando Fraternali,et al.  On the thrust surface of unreinforced and FRP-/FRCM-reinforced masonry domes , 2015 .

[21]  Alexandre Boulch,et al.  Fast and Robust Normal Estimation for Point Clouds with Sharp Features , 2012, Comput. Graph. Forum.

[22]  Hojjat Adeli,et al.  A New Approach for Health Monitoring of Structures: Terrestrial Laser Scanning , 2007, Comput. Aided Civ. Infrastructure Eng..