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In photogrammetry and computer vision the trifocal tensor is used to describe the geometric relation between projections of points in three views. In this paper we analyze the stability and accuracy of the metric trifocal tensor for calibrated cameras. Since a minimal parameterization of the metric trifocal tensor is challenging, the additional constraints of the interior orientation are applied to the well-known projective 6-point and 7-point algorithms for three images. The experimental results show that the linear 7-point algorithm fails for some noise-free degenerated cases, whereas the minimal 6-point algorithm seems to be competitive even with realistic noise.
By the use of numerical methods and the rapid development of computer technology in the recent years, a large variety, complexity, refinement and capability of partial models have been achieved. This can be noticed in the evaluation of the reliability of structures, e.g. the increased use of spatial structural systems. For the different fields of civil engineering, well developed partial models already exist. Because these partial models are most often used separately, the general view is not entirely illustrated. Until now, there has been no common methodology for evaluating the efficiency of models; the trust in the prediction of a special engineering model has generally relied on the engineer’s experience. In this paper the basics of evaluation of simple models and coupled partial models of frame structures will be discussed using sustainable numerical methods. Furthermore, quality classes (levels) of design tasks will be defined based on their practical relevance. In addition, analysis methods will be systemized. After analysis of different published assessment methods, it may be noted, that the Efficiency Indicator Method (EWM) is most suitable for the observed evaluation problem. Therefore, the EWM was modified to the Model Efficiency Analysis (MEA) for the purpose of a holistic evaluation. The criteria are characterized by two groups, benefit and expenditure, and it is possible by calculating the quotient (benefit/expenditure) to make a statement about the efficiency of the observed models. Presently, the expenditure value is not a subject of investigation, and so the model efficiency is calculated only by the benefit value. This paper also contains the associated criteria catalog, different normalization methods, as well as weighting possibilities.
The aim of this study is to show an application of model robustness measures for soilstructure interaction (henceforth written as SSI) models. Model robustness defines a measure for the ability of a model to provide useful model answers for input parameters which typically have a wide range in geotechnical engineering. The calculation of SSI is a major problem in geotechnical engineering. Several different models exist for the estimation of SSI. These can be separated into analytical, semi-analytical and numerical methods. This paper focuses on the numerical models of SSI specific macro-element type models and more advanced finite element method models using contact description as continuum or interface elements. A brief description of the models used is given in the paper. Following this description, the applied SSI problem is introduced. The observed event is a static loaded shallow foundation with an inclined load. The different partial models to consider the SSI effects are assessed using different robustness measures during numerical application. The paper shows the investigation of the capability to use these measures for the assessment of the model quality of SSI partial models. A variance based robustness and a mathematical robustness approaches are applied. These different robustness measures are used in a framework which allows also the investigation of computational time consuming models. Finally the result shows that the concept of using robustness approaches combined with other model–quality indicators (e.g. model sensitivity or model reliability) can lead to unique model–quality assessment for SSI models.
ESTIMATING UNCERTAINTIES FROM INACCURATE MEASUREMENT DATA USING MAXIMUM ENTROPY DISTRIBUTIONS
(2010)
Modern engineering design often considers uncertainties in geometrical and material parameters and in the loading conditions. Based on initial assumptions on the stochastic properties as mean values, standard deviations and the distribution functions of these uncertain parameters a probabilistic analysis is carried out. In many application fields probabilities of the exceedance of failure criteria are computed. The out-coming failure probability is strongly dependent on the initial assumptions on the random variable properties. Measurements are always more or less inaccurate data due to varying environmental conditions during the measurement procedure. Furthermore the estimation of stochastic properties from a limited number of realisation also causes uncertainties in these quantities. Thus the assumption of exactly known stochastic properties by neglecting these uncertainties may not lead to very useful probabilistic measures in a design process. In this paper we assume the stochastic properties of a random variable as uncertain quantities caused by so-called epistemic uncertainties. Instead of predefined distribution types we use the maximum entropy distribution which enables the description of a wide range of distribution functions based on the first four stochastic moments. These moments are taken again as random variables to model the epistemic scatter in the stochastic assumptions. The main point of this paper is the discussion on the estimation of these uncertain stochastic properties based on inaccurate measurements. We investigate the bootstrap algorithm for its applicability to quantify the uncertainties in the stochastic properties considering imprecise measurement data. Based on the obtained estimates we apply standard stochastic analysis on a simple example to demonstrate the difference and the necessity of the proposed approach.
In nonlinear simulations the loading is, in general, applied in an incremental way. Path-following algorithms are used to trace the equilibrium path during the failure process. Standard displacement controlled solution strategies fail if snap-back phenomena occur. In this contribution, a path-following algorithm based on the dissipation of the inelastic energy is presented which allows for the simulation of snap-backs. Since the constraint is defined in terms of the internal energy, the algorithm is not restricted to continuum damage models. Furthermore, no a priori knowledge about the final damage distribution is required. The performance of the proposed algorithm is illustrated using nonlinear mesoscale simulations.
Recently there has been a surge of interest in PDEs involving fractional derivatives in different fields of engineering. In this extended abstract we present some of the results developedin [3]. We compute the fundamental solution for the three-parameter fractional Laplace operator Δ by transforming the eigenfunction equation into an integral equation and applying the method of separation of variables. The obtained solutions are expressed in terms of Mittag-Leffer functions. For more details we refer the interested reader to [3] where it is also presented an operational approach based on the two Laplace transform.
DISCRETE CRACK MODEL OF BORCZ FOR CALCULATING THE DEFLECTIONS OF BENDING REINFORCED CONCRETE BEAM
(2012)
In the design of the reinforced concrete beams loaded by the bending moment, it is assumed that the structure can be used at a level of load, that there are local discontinuities - cracks. Designing the element demands checking two limit states of construction, load capacity and usability. Limit states usability include also the deflection of the element. Deflections in the reinforced concrete beams with cracks are based on actual rigidity of the element. After cracking there is a local change in rigidity of the beam. The rigidity is variable in the element’s length and due to the heterogeneous structure of concrete, it is not possible to clearly describe those changes. Most standards of testing methods tend to simplify the calculations and take the average value of the beam’s rigidity on its entire length. The rigidity depends on the level of the maximal load of the beam. Experimental researches verify the value by inserting the coefficients into the formulas used in the theory of elasticity. The researches describe the changes in rigidity in the beam’s length more precisely. The authors take into consideration the change of rigidity, depending on the level of maximum load (continuum models), or localize the changes in rigidity in the area of the cracks (discrete models). This paper presents one of the discrete models. It is distinguished by the fact that the left side of the differential equation, that depends on the rigidity, is constant, and all effects associated with the scratches are taken as the external load and placed on the right side of the equation. This allows to generalize the description. The paper presents a particular integral of the differential equation, which allow analyzing the displacement and vibration for different rigidity of the silo’s walls, the flow rate and type of the flowing material.
Bridge vibration due to traffic loading has been subject of extensive research in the last decades. Such studies are concerned with deriving solutions for the bridge-vehicle interaction (BVI) and analyzing the dynamic responses considering randomness of the coupled model’s (BVI) input parameters and randomness of road unevenness. This study goes further to examine the effects of such randomness of input parameters and processes on the variance of dynamic responses in quantitative measures. The input parameters examined in the sensitivity analysis are, stiffness and damping of vehicle’s suspension system, axle spacing, and stiffness and damping of bridge. This study also examines the effects of the initial excitation of a vehicle on the influences of the considered input parameters. Variance based sensitivity analysis is often applied to deterministic models. However, the models for the dynamic problem is a stochastic one due to the simulations of the random processes. Thus, a setting using a joint meta-model; one for the mean response and other for the dispersion of the response is developed. The joint model is developed within the framework of Generalized Linear Models (GLM). An enhancement of the GLM procedure is suggested and tested; this enhancement incorporates Moving Least Squares (MLS) approximation algorithms in the fitting of the mean component of the joint model. The sensitivity analysis is then performed on the joint-model developed for the dynamic responses caused by BVI.
Sensor faults can affect the dependability and the accuracy of structural health monitoring (SHM) systems. Recent studies demonstrate that artificial neural networks can be used to detect sensor faults. In this paper, decentralized artificial neural networks (ANNs) are applied for autonomous sensor fault detection. On each sensor node of a wireless SHM system, an ANN is implemented to measure and to process structural response data. Structural response data is predicted by each sensor node based on correlations between adjacent sensor nodes and on redundancies inherent in the SHM system. Evaluating the deviations (or residuals) between measured and predicted data, sensor faults are autonomously detected by the wireless sensor nodes in a fully decentralized manner. A prototype SHM system implemented in this study, which is capable of decentralized autonomous sensor fault detection, is validated in laboratory experiments through simulated sensor faults. Several topologies and modes of operation of the embedded ANNs are investigated with respect to the dependability and the accuracy of the fault detection approach. In conclusion, the prototype SHM system is able to accurately detect sensor faults, demonstrating that neural networks, processing decentralized structural response data, facilitate autonomous fault detection, thus increasing the dependability and the accuracy of structural health monitoring systems.
CRITICAL STRESS ASSESSMENT IN ANGLE TO GUSSET PLATE BOLTED CONNECTION BY SIMPLIFIED FEM MODELLING
(2010)
Simplified modelling of friction grip bolted connections of steel member – to – gusset plate is often applied in engineering practise. The paper deals with the simplification of pre-tensioned bolt model and simplification of load transfer within connection. Influence on normal strain (and thus stress) distribution at critical cross-section is investigated. Laboratory testing of single-angle or double-angle members – to – gusset plates bolted connections were taken as basis for numerical analysis. FE models were created using 1D and 2D elements. Angles and gusset plates were modelled with shell elements. Two methods of modelling of friction grip bolting were considered: bolt-regarding approach with 1D element systems modelling bolts and two variants of bolt-disregarding approach with special constraints over some part of member and gusset plate surfaces in contact: a) constraints over whole area of contact, b) constraints over the area around each bolt shank (“partially tied”). Modelling of friction grip bolted connections using simplified bolt modelling may be effective, especially in the case of analysis concerning elastic range only. In such a case disregarding bolts and replacing them with “partially tied” modelling seems to be more attractive. It is less time-consuming and provides results of similar accuracy in comparison to analysis utilizing simplified bolt modelling.