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Optimization of concrete structures using stochastic optimization methods
Slowik, Ondřej ; Pukl,, Radomír (referee) ; Novák, Drahomír (advisor)
The thesis focuses the reader on the sense of optimization and its importance for civil engineering. It outlines the principles used by some optimization methods and discusses the possibility of combination of any type of methods LHS with other optimization method. The result is a new type of optimization method named Nested LHS described in the text of the third chapter. The fifth chapter applies some of the lessons learned to solve practical optimization problem - reinforced concrete bridge solved by nonlinear finite element analysis using pseudostochastic optimization method LHS mean.
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Stochastic analysis of shear failure of reinforced concrete beams
Kucek, Martin ; Doležel, Jiří (referee) ; Novák, Drahomír (advisor)
The diploma thesis is focused on a solution of the load reaction of the bridge construction from girders KA-73. Proposal methods of the nonlinear analysis by means of final elements on the stochastic and deterministic level are used for the solution of the load reaction. A simulation technique Latin Hypercube Sampling is used within the stochastic analysis. A material degradation in the form of the trussing corrosion is solved with the expected decrease of the construction lifetime. The conclusion of the thesis contains an evaluation of initial quantities of material parameters for the load reaction of the construction in the form of the sensitivity analysis.
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Utilization of inverse reliability analysis tools for probability based design of selected structural parameters
Lipowczan, Martin ; Novák, Drahomír (referee) ; Lehký, David (advisor)
This bachelor thesis deals with the application of methodology and tools of inverse analysis in regards to probabilistic design of selected design parameters of structure. The first step was to get familiar with the probabilistic design and analysis, then understanding of the inverse analysis methodology itself which is based on artificial neural networks. After researching the topic we could get to the actual issue. To put the theory in practice easier examples were used at first. These were mathematical functions and one practical-based example, whereas the results were known in advance. This simplified a process of checking achieved values. Using software tools and especially DLNNET software allowed us to take on practical exercises. Used exercises are chosen from earlier undergraduate studies at the Faculty of Civil Engineering, Brno. The first of these was a design of reinforced concrete slab, where desired parameters were slab’s height and area of reinforcement. The second one was a design of a diagonal truss screw connection, aimed to size the screw diameter and its quantity.
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An efficiency comparison of simulation methods for artificial neural network training and inverse analysis
Nezval, Michal ; Novák, Drahomír (referee) ; Lehký, David (advisor)
The thesis deals with inverse analysis which is based on combination of artificial neural network and stochastic methods. The goal is to compare an efficiency of new simulation method Hierarchical Subset Latin Hypercube Sampling to classical Monte Carlo method and standard Latin Hypercube Sampling method used for neural network training. The efficiency is compared for a different neural network structures. The inverse analysis is then applied for engineering tasks – identification of limit state fiction parameters related to pitched-roof frame and material parameters of concrete specimen subjected to three-point bending. Finally an efficiency of Hierarchical Subset Latin Hypercube method comparing to Monte Carlo and Latin Hypercube Sampling methods is discussed.
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Reliability-based structural optimization
Slowik, Ondřej ; Pukl, Radomír (referee) ; Novák, Drahomír (advisor)
This thesis presents the reader the importance of optimization and probabilistic assessment of structures for civil engineering problems. Chapter 2 further investigates the combination between previously proposed optimization techniques and probabilistic assessment in the form of optimization constraints. Academic software has been developed for the purposes of demonstrating the effectiveness of the suggested methods and their statistical testing. 3th chapter summarizes the results of testing previously described optimization method (called Aimed Multilevel Sampling), including a comparison with other optimization techniques. In the final part of the thesis, described procedures have been demonstrated on the selected optimization and reliability problems. The methods described in text represents engineering approach to optimization problems and aims to introduce a simple and transparent optimization algorithm, which could serve to the practical engineering purposes.
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Surrogate modelling and safety formats in probabilistic analysis of structures
Novák, Lukáš ; Sýkora,, Miroslav (referee) ; Šejnoha,, Michal (referee) ; Novák, Drahomír (advisor)
The presented doctoral thesis is focused on the development of theoretical methods for probabilistic design and assessment of structures. In order to reduce the computational burden of the probabilistic approach, the developed methods are based on surrogate models. Specifically, Taylor series expansion has been utilized for the derivation of a novel analytical method for a simplified semi-probabilistic design of structures represented by non-linear finite element models. The novel approach estimates a variance of quantity of interest and the influence of correlation among input random variables. The second part of the doctoral thesis aims at the development of efficient numerical algorithms for the construction of a surrogate model based on polynomial chaos expansion and its utilization for uncertainty quantification. Although the proposed algorithm is based on cutting edge techniques, it was beneficial to improve its accuracy and efficiency by advanced statistical sampling. Therefore, a novel technique for adaptive sequential statistical sampling, reflecting the exploration of the design domain, and exploitation of the surrogate model, is proposed specifically for polynomial chaos expansion.
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Life-cycle analysis of reinforced concrete bridges
Doležel, Jiří ; Vítek,, Jan (referee) ; Pukl,, Radomír (referee) ; Novák, Drahomír (advisor)
With increasing age of the concrete road bridges, the highly topical question is to determine their reliability and load-bearing capacity level required for the residual life of the structure. Doctoral thesis presents a comprehensive methodology for assessing the reliability of reinforced and prestressed concrete bridges based on non-linear finite element method damage and failure virtual simulations at both deterministic and stochastic levels. Load-bearing capacity values are specified by the structure’s design load capacity estimation by global safety factor methods or they are based on a fully probabilistic load capacity analysis using the direct resistance estimation. For the fully probabilistic calculations, the simulation technique Latin Hypercube Sampling is used.
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Inverse reliability analysis of prestressed bridge
Lipowczan, Martin ; Novák, Drahomír (referee) ; Lehký, David (advisor)
The proposed diploma thesis deals with the application of methodology and tools of inverse analysis for design of selected structural parameters using a fully probabilistic analysis to determine the level of its reliability. The method based on artificial neural networks is used to approximate the inverse function. The inverse analysis was carried out in two ways that differs in the method of obtaining reliability indicators. The structure analyzed in this work was an existing bridge. The year of construction is estimated approximately between the years 1955 to 1960. The bridge is located close to the Uherský Ostroh. It is a one-piece concrete slab made of MPD3 and MPD4 girders post-tensioned by tendons. Based on the 2006 and 2007 diagnostic surveys, laboratory tests, normative regulations and recommendations and, last but not least, sensitivity analyses, an inverse design of selected design parameters was performed for required limit states. Various load levels, different alternatives of design parameters and different neural network structures were studied.
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Life-time assessment of bridge based on nonlinear analysis and degradation modelling
Kucek, Martin ; Lehký, David (referee) ; Novák, Drahomír (advisor)
The aim of this work is to calculate the lifetime period of the bridge construction based on the nonlinear analysis and the degradation modelling. As a solution was the probabilistic nonlinear finite element analysis. The nonlinear numerical analysis is provided by the programme ATENA, developed by the Červenka Consulting. We have modeled one prefabricated bridge beam KA-73, which was overloaded by power effects until the structure was damaged. Observed limit states, limit state of the decompression, crack formation and limit state of the bearing were compared with characteristic material. It is possible to determine the maximum weighted capacity for the given construction based on discovered values.
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