A computationally efficient shear deformable beam element for large deformation multibody applications

In this paper, a new two-dimensional shear deformable beam element based on the absolute nodal coordinate formulation is proposed. The nonlinear elastic forces of the beam element are obtained using a continuum mechanics approach without employing a local element coordinate system. In this study, linear polynomials are used to interpolate both the transverse and longitudinal components of the displacement. This is different from other absolute nodal-coordinate-based beam elements where cubic polynomials are used in the longitudinal direction. The accompanying defects of the phenomenon known as shear locking are avoided through the adoption of selective integration within the numerical integration method. The proposed element is verified using several numerical examples, and the results are compared to analytical solutions and the results for an existing shear deformable beam element. It is shown that by using the proposed element, accurate linear and nonlinear static deformations, as well as realistic dynamic behavior, can be achieved with a smaller computational effort than by using existing shear deformable two-dimensional beam elements.

Comparison of application frameworks designed to support application extensibility

Reusability has become more popular factor in modern software engineering. This is mainly because object-orientation has brought methods that allow reusing more easily. Today more and more application developer thinks how they can reuse already existing applications in their work. If the developer wants to use existing components outside the current project, he can use design patterns, class libraries or frameworks. These provide solution for specific or general problems that has been already encountered. Application frameworks are collection of classes that provides base for the developer. Application frameworks are mostly implementation phase tools, but can also be used in application design. The main purpose of the frameworks is separate domain specific functionalities from the application specific. Usually the frameworks are divided into two categories: black and white box. Difference between those categories is the way the reuse is done. The application frameworks provide properties that can be examined and compared between different frameworks. These properties are: extensibility, reusability, modularity and scalability. These examine how framework will handle different platforms, changes in framework, increasing demand for resources, etc. Generally application frameworks do have these properties in good level. When comparing general purpose framework and more specific purpose framework, the main difference can be located in reusability of frameworks. It is mainly because the framework designed to specific domain can have constraints from external systems and resources. With general purpose framework these are set by the application developed based on the framework.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Rigid Rod Polymer Fillers in Acrylic Denture and Dental Adhesive Resin Systems

Polymeric materials have been used in dental applications for decades. Adhesion of polymeric materials to each other and to the tooth substrate is essential to their successful use. The aim of this series of studies was two-folded. First, to improve adhesion of poly(paraphenylene) based rigid rod polymer (RRP) to other dental polymers, and secondly, to evaluate the usability of a new dentin primer system based on RRP fillers. Poly(paraphenylene) based RRP would be a tempting material for dental applications because of its good mechanical properties. To be used in dental applications, reliable adhesion between RRP and other dental polymers is required. In this series of studies, the adhesion of RRP to denture base polymer and the mechanical properties of RRP-denture base polymer-material combination were evaluated. Also adhesion of BisGMA-TEGDMA-resin to RRP was determined. Different surface treatments were tested to improve the adhesion of BisGMA-TEGDMA-resin to RRP. Results were based on three-point bending testing, Vickers surface hardness test and scanning electron microscope analysis (SEM), which showed that no reliable adhesion between RRP and denture base polymer was formed. Addition of RRP filler to denture base polymer increased surface hardness and flexural modulus but flexural strength decreased. Results from the shear bond strength test and SEM revealed that adhesion between resin and RRP was possible to improve by surface treatment with dichloromethane (DCM) based primer and a new kind of adhesive surface can be designed. The current dentin bonding agents have good immediate bond strength, but in long term the bond strength may decrease due to the detrimental effect of water and perhaps by matrix metalloproteinases. This leads to problems in longevity of restorations. Current bonding agents use organic monomers. In this series of studies, RRP filled dentin primer was tested in order to decrease the water sorption of the monomer system of the primers. The properties of new dentin primer system were evaluated in vitro by comparing it to commercial etch and rinse adhesive system. The results from the contact angle measurements and SEM showed that experimental primer with RRP reinforcement provided similar resin infiltration to dentin collagen and formed the resin-dentin interface as the control primer. Microtensile bond strength test and SEM revealed that in short term water storing, RRP increased bond strength and primer with BMEP-monomer (bis[2-(methacryloyloxy)-ethyl]phosphate) and high solvent concentration provided comparable bonding properties to the commercial control primers. In long term water storing, the high solvent-monomer concentration of the experimental primers decreased bond strength. However, in low solvent-monomer concentration groups, the long-term water storing did not decrease the bond strength despite the existence of hydrophilic monomers which were used in the system. These studies demonstrated that new dentin primer system reached the mechanical properties of current traditional etch and rinse adhesive system in short time water storing. Improved properties can be achieved by further modifications of the monomer system. Studies of the adhesion of RRP to other polymers suggest that adhesion between RRP and other dental polymers is possible to obtain by certain surface treatments.

Poster presentation as a report of a self-designed laboratory experiment : a case study

Julkaisumaa: 203 CZ CZE Tšekki

Fiber-reinforced composite fixed dental prostheses: Studies of the materials used as pontics

Fiber-reinforced composite fixed dental prostheses – Studies of the materials used as pontics University of Turku, Faculty of Medicine, Institute of Dentistry, Department of Biomaterials Science, Finnish Doctoral Program in Oral Sciences – FINDOS, Annales Universitatis Turkuensis, Turku, Finland 2015 Fiber-reinforced composites (FRC), a non-metallic biomaterial, represent a suitable alternative in prosthetic dentistry when used as a component of fixed dental prostheses (FDPs). Some drawbacks have been identified in the clinical performance of FRC restorations, such as delamination of the veneering material and fracture of the pontic. Therefore, the current series of studies were performed to investigate the possibilities of enhancing the mechanical and physical properties of FRC FDPs by improving the materials used as pontics, to then heighten their longevity. Four experiments showed the importance of the pontic design and surface treatment in the performance of FRC FDPs. In the first, the load-bearing capacities of inlay-retained FRC FDPs with pontics of various materials and thicknesses were evaluated. Three different pontic materials were assessed with different FRC framework vertical positioning. Thicker pontics showed increased load-bearing capacities, especially ceramic pontics. A second study was completed investigating the influence of the chemical conditioning of the ridge-lap surface of acrylic resin denture teeth on their bonding to a composite resin. Increased shear bond strength demonstrated the positive influence of the pretreatment of the acrylic surfaces, indicating dissolution of the denture surfaces, and suggesting potential penetration of the monomer systems into the surface of denture teeth. A third study analyzed the penetration depth of different monomer systems on the acrylic resin denture teeth surfaces. The possibility of establishing a durable bond between acrylic pontics and FRC frameworks was demonstrated by the ability of monomers to penetrate the surface of acrylic resin denture teeth, measured by a confocal scanning type microscope. A fourth study was designed to evaluate the load-bearing capacities of FRC FDPs using the findings of the previous three studies. In this case, the performance of pre-shaped acrylic resin denture teeth used as pontics with different composite resins as filling materials was evaluated. The filling material influenced the load-bearing capacities, providing more durable FRC FDPs. It can be concluded that the mechanical and physical properties of FRC FDPs can be improved as has been shown in the development of this thesis. The improvements reported then might provide long lasting prosthetic solutions of this kind, positioning them as potentially permanent rehabilitation treatments. Key words: fiber-reinforced composite, fixed dental prostheses, inlay-retained bridges, adhesion, acrylic resin denture teeth, dental material.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.