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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.
The use of process models in the analysis, optimization and simulation of processes has proven to be extremely beneficial in the instances where they could be applied appropriately. However, the Architecture/Engineering/Construction (AEC) industries present unique challenges that complicate the modeling of their processes. A simple Engineering process model, based on the specification of Tasks, Datasets, Persons and Tools, and certain relations between them, have been developed, and its advantages over conventional techniques have been illustrated. Graph theory is used as the mathematical foundation mapping Tasks, Datasets, Persons and Tools to vertices and the relations between them to edges forming a directed graph. The acceptance of process modeling in AEC industries not only depends on the results it can provide, but the ease at which these results can be attained. Specifying a complex AEC process model is a dynamic exercise that is characterized by many modifications over the process model's lifespan. This article looks at reducing specification complexity, reducing the probability for erroneous input and allowing consistent model modification. Furthermore, the problem of resource leveling is discussed. Engineering projects are often executed with limited resources and determining the impact of such restrictions on the sequence of Tasks is important. Resource Leveling concerns itself with these restrictions caused by limited resources. This article looks at using Task shifting strategies to find a near-optimal sequence of Tasks that guarantees consistent Dataset evolution while resolving resource restrictions.
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.
Available construction time-cost trade-off analysis models can be used to generate trade-offs between these two important objectives, however, their application is limited in large-scale construction projects due to their impractical computational requirements. This paper presents the development of a scalable and multi-objective genetic algorithm that provides the capability of simultaneously optimizing construction time and cost large-scale construction projects. The genetic algorithm was implemented in a distributed computing environment that utilizes a recent standard for parallel and distributed programming called the message passing interface (MPI). The performance of the model is evaluated using a set of measures of performance and the results demonstrate the capability of the present model in significantly reducing the computational time required to optimize large-scale construction projects.
Designing a structure follows a pattern of creating a structural design concept, executing a finite element analysis and developing a design model. A project was undertaken to create computer support for executing these tasks within a collaborative environment. This study focuses on developing a software architecture that integrates the various structural design aspects into a seamless functional collaboratory that satisfies engineering practice requirements. The collaboratory is to support both homogeneous collaboration i.e. between users operating on the same model and heterogeneous collaboration i.e. between users operating on different model types. Collaboration can take place synchronously or asynchronously, and the information exchange is done either at the granularity of objects or at the granularity of models. The objective is to determine from practicing engineers which configurations they regard as best and what features are essential for working in a collaborative environment. Based on the suggestions of these engineers a specification of a collaboration configuration that satisfies engineering practice requirements will be developed.
The aim of this paper is to present so-called discrete-continual boundary element method (DCBEM) of structural analysis. Its field of application comprises buildings constructions, structures and also parts and components for the residential, commercial and un-inhabitant structures with invariability of physical and geometrical parameters in some dimensions. We should mention here in particular such objects as beams, thin-walled bars, strip foundations, plates, shells, deep beams, high-rise buildings, extensional buildings, pipelines, rails, dams and others. DCBEM comes under group of semianalytical methods. Semianalytical formulations are contemporary mathematical models which currently becoming available for realization due to substantial speed-up of computer productivity. DCBEM is based on the theory of the pseudodifferential boundary equations. Corresponding pseudodifferential operators are discretely approximated using Fourier analysis or wavelet analysis. The main DCBEM advantages against the other methods of the numerical analysis is a double reduction in dimension of the problem (discrete numerical division applied not to the full region of the interest but only to the boundary of the region cross section, as a matter of fact one is solving an one-dimensional problem with the finite step on the boundary area of the region), one has opportunities to carrying out very detailed analysis of the specific chosen zones, simplified initial data preparation, simplistic and adaptive algorithms. There are two methods to define and conduct DCBEM analysis developed – indirect (IDCBEM) and direct (DDCBEM), thus indirect like in boundary element method (BEM) applied and used little bit more than direct.