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CONSTITUTIVE MODELS FOR SUBSOIL IN THE CONTEXT OF STRUCTURAL ANALYSIS IN CONSTRUCTION ENGINEERING
(2010)
Parameters of constitutive models are obtained generally comparing the results of forward numerical simulations to measurement data. Mostly the parameter values are varied by trial-and-error in order to reach an improved fit and obtain plausible results. However, the description of complex soil behavior requires advanced constitutive models where the rising complexity of these models mainly increases the number of unknown constitutive parameters. Thus an efficient identification "by hand" becomes quite difficult for most practical geotechnical problems. The main focus of this article is on finding a vector of parameters in a given search space which minimizes discrepancy between measurements and the associated numerical result. Classically, the parameter values are estimated from laboratory tests on small samples (triaxial tests or oedometer tests). For this purpose an automatic population-based approach is present to determine the material parameters for reconstituted and natural Bothkennar Clay. After the identification a statistical assessment is carried out of numerical results to evaluate different constitutive models. On the other side a geotechnical problem, stone columns under an embankment, is treated in a well instrumented field trial in Klagenfurt, Austria. For the identification purpose there are measurements from multilevel-piezometers, multilevel-extensometers and horizontal inclinometer. Based on the simulation of the stone columns in a FE-Model the identification of the constitutive parameters is similar to the experimental tests by minimizing the absolute error between measurement and numerical curves.
In order to model and simulate collapses of large scale complex structures, a user-friendly and high performance software system is essential. Because a large number of simulation experiments have to be performed, therefore, next to an appropriate simulation model and high performance computing, efficient interactive control and visualization capabilities of model parameters and simulation results are crucial. To this respect, this contribution is concerned with advancements of the software system CADCE (Computer Aided Demolition using Controlled Explosives) that is extended under particular consideration of computational steering concepts. Thereby, focus is placed on problems and solutions for the collapse simulation of real world large scale complex structures. The simulation model applied is based on a multilevel approach embedding finite element models on a local as well as a near field length scale, and multibody models on a global scale. Within the global level simulation, relevant effects of the local and the near field scale, such as fracture and failure processes of the reinforced concrete parts, are approximated by means of tailor-made multibody subsystems. These subsystems employ force elements representing nonlinear material characteristics in terms of force/displacement relationships that, in advance, are determined by finite element analysis. In particular, enhancements concerning the efficiency of the multibody model and improvements of the user interaction are presented that are crucial for the capability of the computational steering. Some scenarios of collapse simulations of real world large scale structures demonstrate the implementation of the above mentioned approaches within the computational steering.
Tests on Polymer Modified Cement Concrete (PCC) have shown significant large creep deformation. The reasons for that as well as additional material phenomena are explained in the following paper. Existing creep models developed for standard concrete are studied to determine the time-dependent deformations of PCC. These models are: model B3 by Bažant and Bajewa, the models according to Model Code 90 and ACI 209 as well as model GL2000 by Gardner and Lockman. The calculated creep strains are compared to existing experimental data of PCC and the differences are pointed out. Furthermore, an optimization of the model parameters is performed to fit the models to the experimental data to achieve a better model prognosis.
The main aim of the research project in progress is to develop virtual models as tools to support decision-making in the planning of construction maintenance. The virtual models gives the capacity to allow them to transmit, visually and interactively, information related to the physical behaviour of materials, components of given infrastructures, defined as a function of the time variable. The interactive application allows decisions to be made on conception options in the definition of plans for maintenance, conservation or rehabilitation. The first virtual prototype that is now in progress concerns just lamps. It allows the examination of the physical model, visualizing, for each element modelled in 3D and linked to a database, the corresponding technical information concerned with the wear and tear aspects of the material, calculated for that period of time. In addition, the analysis of solutions for repair work or substitution and inherent cost are predicted, the results being obtained interactively and visualized in the virtual environment itself. The aim is that the virtual model should be able to be applied directly over the 3D models of new constructions, in situations of rehabilitation. The practical usage of these models is directed, then, towards supporting decision-making in the conception phase and the planning of maintenance. In further work other components will be analysed and incorporated into the virtual system.
The changed global security situation in the last eight years has shown the importance of emergency management plans in public buildings. Therefore, the use of computer simulators for surveying fire safety design and evacuation process is increasing. The aim of these simulators is to have more realistic evacuation simulations. The challenge is, firstly, to realize the virtual simulation environment based on geometrical and material boundary conditions, secondly, to considerate the mutual interaction effects between different parameters and, finally, to have a realistic visualization of the simulated results. In order to carry out this task, an especial new software method on a BIM-platform has to be developed which can integrate all required simulations and will be able to have an immersive output BIM ISEE (Immersive Safety Engineering Environment). The new BIM-ISEE will integrate the Fire Dynamics Simulator (FDS) for fire and evacuation simulation in the Autodesk Revit which is a BIM-platform and will represent the simulation results in the immersive virtual environment at the institute (CES-Lab). With BIM-ISEE the fire safety engineer will be able to obtain more realistic visualizations in the immersive environment, to modify his concept more effectively, to evaluate the simulation results more accurately and to visualize the various simulation results. It can also give the rescue staff the opportunity to perform and evaluate emergency evacuation trainings.
Models in the context of engineering can be classified in process based and data based models. Whereas the process based model describes the problem by an explicit formulation, the data based model is often used, where no such mapping can be found due to the high complexity of the problem. Artificial Neuronal Networks (ANN) is a data based model, which is able to “learn“ a mapping from a set of training patterns. This paper deals with the application of ANN in time dependent bathymetric models. A bathymetric model is a geometric representation of the sea bed. Typically, a bathymetry is been measured and afterwards described by a finite set of measured data. Measuring at different time steps leads to a time dependent bathymetric model. To obtain a continuous surface, the measured data has to be interpolated by some interpolation method. Unlike the explicitly given interpolation methods, the presented time dependent bathymetric model using an ANN trains the approximated surface in space and time in an implicit way. The ANN is trained by topographic measured data, which consists of the location (x,y) and time t. In other words the ANN is trained to reproduce the mapping h = f(x,y,t) and afterwards it is able to approximate the topographic height for a given location and date. In a further step, this model is extended to take meteorological parameters into account. This leads to a model of more predictive character.
Geotechnical constructions are sophisticated structures due to the non-linear soil behaviour and the complex soil-structure interaction, which entails great exigencies on the liable engineer during the design process. The process can be schematised as a difficult and, depending on the opportunities and skills of the processor more or less innovative, creative and heuristic search for one or a multiple of defined objectives under given boundary conditions. Wholistic approaches including numerical optimisation which support the constructing engineer in this task do not currently exist. Abstract problem formulation is not state of the art; commonly parameter studies are bounded by computational effort. Thereby potential regarding cost effectiveness, construction time, load capacity and/or serviceability are often used insufficiently. This paper describes systematic approaches for comprehensive optimisation of selected geotechnical constructions like combined pile raft foundations and quay wall structures. Several optimisation paradigms like the mono- and the multi-objective optimisation are demonstrated and their use for a more efficient design concerning various intentions is shown in example. The optimisation is implemented by using Evolutionary Algorithms. The applicability to geotechnical real world problems including nonlinearities, discontinuities and multi-modalities is shown. The routines are adapted to common problems and coupled with conventional analysis procedures as well as with numerical calculation software based on the finite element method. Numerical optimisation of geotechnical design using efficient algorithms is able to deliver highly effective solutions after investing more effort into the parameterization of the problem. Obtained results can be used for realizing different constructions near the stability limit, visualizing the sensitivity regarding the construction parameters or simply procuring more effective solutions.
In the context of finite element model updating using vibration test data, natural frequencies and mode shapes are used as validation criteria. Consequently, the order of natural frequencies and mode shapes is important. As only limited spatial information is available and noise is present in the measurements, the automatic selection of the most likely numerical mode shape corresponding to a measured mode shape is a difficult task. The most common criterion to indicate corresponding mode shapes is the modal assurance criterion. Unfortunately, this criterion fails in certain cases. In this paper, the pure mathematical modal assurance criterion will be enhanced by additional physical information of the numerical model in terms of modal strain energies. A numerical example and a benchmark study with real measured data are presented to show the advantages of the enhanced energy based criterion in comparison to the traditional modal assurance criterion.
The application of a recent method using formal power series is proposed. It is based on a new representation for solutions of Sturm-Liouville equations. This method is used to calculate the transmittance and reflectance coefficients of finite inhomogeneous layers with high accuracy and efficiency. Tailoring the refraction index profile defining the inhomogeneous media it is possible to develop very important applications such as optical filters. A number of profiles were evaluated and then some of them selected in order to perform an improvement of their characteristics via the modification of their profiles.
We present recent developments of adaptive wavelet solvers for elliptic eigenvalue problems. We describe the underlying abstract iteration scheme of the preconditioned perturbed iteration. We apply the iteration to a simple model problem in order to identify the main ideas which a numerical realization of the abstract scheme is based upon. This indicates how these concepts carry over to wavelet discretizations. Finally we present numerical results for the Poisson eigenvalue problem on an L-shaped domain.