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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.
The effective and efficient cooperation in communities and groups requires that the members of the community or group have adequate information about each other and the environment. In this paper, we outline the basic challenges of managing awareness information. We analyse the management of awareness information in face-to-face situations, and discuss challenges and requirements for the support of awareness management in distributed settings. Finally, after taking a look at related work, we present a simple, yet powerful framework for awareness management based on constraint pattern named COBRA.
The release of the large language model-based chatbot ChatGPT 3.5 in November 2022 has brought considerable attention to the subject of artificial intelligence, not only to the public. From the perspective of higher education, ChatGPT challenges various learning and assessment formats as it significantly reduces the effectiveness of their learning and assessment functionalities. In particular, ChatGPT might be applied to formats that require learners to generate text, such as bachelor theses or student research papers. Accordingly, the research question arises to what extent writing of bachelor theses is still a valid learning and assessment format. Correspondingly, in this exploratory study, the first author was asked to write his bachelor’s thesis exploiting ChatGPT. For tracing the impact of ChatGPT methodically, an autoethnographic approach was used. First, all considerations on the potential use of ChatGPT were documented in logs, and second, all ChatGPT chats were logged. Both logs and chat histories were analyzed and are presented along with the recommendations for students regarding the use of ChatGPT suggested by a common framework. In conclusion, ChatGPT is beneficial for thesis writing during various activities, such as brainstorming, structuring, and text revision. However, there are limitations that arise, e.g., in referencing. Thus, ChatGPT requires continuous validation of the outcomes generated and thus fosters learning. Currently, ChatGPT is valued as a beneficial tool in thesis writing. However, writing a conclusive thesis still requires the learner’s meaningful engagement. Accordingly, writing a thesis is still a valid learning and assessment format. With further releases of ChatGPT, an increase in capabilities is to be expected, and the research question needs to be reevaluated from time to time.
A technique for using object-oriented technologies to write structural analysis software has been developed. The structural design information of an individual building is stored in an object-oriented database. A global database provides general design values as material data and safety factors. A class library for load elements has been evolved to model the transfer of loads in a building. This class library is the basis for the development of further classes for other structural elements such as beams, columns or slabs. A software has been developed to monitor the forces transferred from one structural member to another in a building for load cases and combinations according to Eurocode 1. The results of the analysis are stored in the projects database from which a structural design report may be generated. The software was developed under Microsoft Visual C++. The Microsoft Foundation Class Library (MFC) was used to program the Graphical User Interface (GUI). Object Linking and Embedding (OLE) technology is useful to include any type of OLE server objects for example texts written with a word processor or CAD drawings in the structural design report. The Object-Oriented Database Management System (OODBMS) ObjectStore provides services to store the large amount of objects.
This study permits a reliability analysis to solve the mechanical behaviour issues existing in the current structural design of fabric structures. Purely predictive material models are highly desirable to facilitate an optimized design scheme and to significantly reduce time and cost at the design stage, such as experimental characterization.
The present study examined the role of three major tasks; a) single-objective optimization, b) sensitivity analyses and c) multi-objective optimization on proposed weave structures for woven fabric composites. For single-objective optimization task, the first goal is to optimize the elastic properties of proposed complex weave structure under unit cells basis based on periodic boundary conditions.
We predict the geometric characteristics towards skewness of woven fabric composites via Evolutionary Algorithm (EA) and a parametric study. We also demonstrate the effect of complex weave structures on the fray tendency in woven fabric composites via tightness evaluation. We utilize a procedure which does not require a numerical averaging process for evaluating the elastic properties of woven fabric composites. The fray tendency and skewness of woven fabrics depends upon the behaviour of the floats which is related to the factor of weave. Results of this study may suggest a broader view for further research into the effects of complex weave structures or may provide an alternative to the fray and skewness problems of current weave structure in woven fabric composites.
A comprehensive study is developed on the complex weave structure model which adopts the dry woven fabric of the most potential pattern in singleobjective optimization incorporating the uncertainties parameters of woven fabric composites. The comprehensive study covers the regression-based and variance-based sensitivity analyses. The second task goal is to introduce the fabric uncertainties parameters and elaborate how they can be incorporated into finite element models on macroscopic material parameters such as elastic modulus and shear modulus of dry woven fabric subjected to uni-axial and biaxial deformations. Significant correlations in the study, would indicate the need for a thorough investigation of woven fabric composites under uncertainties parameters. The study describes here could serve as an alternative to identify effective material properties without prolonged time consumption and expensive experimental tests.
The last part focuses on a hierarchical stochastic multi-scale optimization approach (fine-scale and coarse-scale optimizations) under geometrical uncertainties parameters for hybrid composites considering complex weave structure. The fine-scale optimization is to determine the best lamina pattern that maximizes its macroscopic elastic properties, conducted by EA under the following uncertain mesoscopic parameters: yarn spacing, yarn height, yarn width and misalignment of yarn angle. The coarse-scale optimization has been carried out to optimize the stacking sequences of symmetric hybrid laminated composite plate with uncertain mesoscopic parameters by employing the Ant Colony Algorithm (ACO). The objective functions of the coarse-scale optimization are to minimize the cost (C) and weight (W) of the hybrid laminated composite plate considering the fundamental frequency and the buckling load factor as the design constraints.
Based on the uncertainty criteria of the design parameters, the appropriate variation required for the structural design standards can be evaluated using the reliability tool, and then an optimized design decision in consideration of cost can be subsequently determined.
As human thought was developing, likewise, the technology used for illumination was growing. But a haul through history, reviewing its pages and analyzing it, inherently brings up old and new question, like: Is it possible to alter negatively the image of historic buildings and monuments through inadequate lighting to the degree of distorting the perception that people have of the work? and if so, what are the causes that generate it? Do the light designers take into consideration criteria to protect not only historic buildings and monuments, but also the environment? What are the consequences that may generate the inadequate lighting of urban heritage to the environment? What are the factors to consider for a proper illumination of urban heritage? The answers to these questions will help lay the foundation for proper illumination of the urban heritage, avoiding at the maximum the light pollution and the effects that it generates, seeking a balance and harmonious reconciliation between the technology, urban heritage and environment, taking as a framework and the case study the urban heritage of a city from the colonial era in southern Mexico, with pre-Hispanic roots and where today you can still see through its streets and buildings an atmosphere of mysticism reflection of their folklore and traditions, this city is known as Chiapa de Corzo, Chiapas.
Object-Oriented Damage Information Modeling Concepts and Implementation for Bridge Inspection
(2022)
Bridges are designed to last for more than 50 years and consume up to 50% of their life-cycle costs during their operation phase. Several inspections and assessment actions are executed during this period. Bridge and damage information must be gathered, digitized, and exchanged between different stakeholders. Currently, the inspection and assessment practices rely on paper-based data collection and exchange, which is time-consuming and error-prone, and leads to loss of information. Storing and exchanging damage and building information in a digital format may lower costs and errors during inspection and assessment and support future needs, for example, immediate simulations regarding performance assessment, automated maintenance planning, and mixed reality inspections. This study focused on the concept for modeling damage information to support bridge reviews and structural analysis. Starting from the definition of multiple use cases and related requirements, the data model for damage information is defined independently from the subsequent implementation. In the next step, the implementation via an established standard is explained. Functional tests aim to identify problems in the concept and implementation. To show the capability of the final model, two example use cases are illustrated: the inspection review of the entire bridge and a finite-element analysis of a single component. Main results are the definition of necessary damage data, an object-oriented damage model, which supports multiple use cases, and the implementation of the model in a standard. Furthermore, the tests have shown that the standard is suitable to deliver damage information; however, several software programs lack proper implementation of the standard.
Die Einflüsse polymerer Zusätze auf die Ausbildung der Mikrostruktur im frühen Stadium der Erhärtung und auf die Eigenschaften, insbesondere die Dauerhaftigkeit der modifizierten Mörtel wurden erforscht. Es sollte die Frage beantwortet werden, ob durch die Modifizierung die Dauerhaftigkeit von Mörteln mehr verbessert werden kann, als dies durch übliche betontechnologische Maßnahmen möglich ist. Die Ausbildung der Mikrostruktur in den ersten 24 Stunden der Erhärtung wurde mit verschiedenen Methoden, u.a. mittels ESEM, untersucht. Es wurden Modellvorstellungen zur Ausbildung der organischen Matrix und der anorganischen Matrix entwickelt: Interaktionen sind Adsorptionsreaktionen, Agglomerationen und Behinderung der Hydratation. Es wurden Frisch- und Festmörteluntersuchungen beschrieben und interpretiert. Unterschiedliche Dauerhaftigkeitsuntersuchungen wurden durchgeführt und bewertet. Die Mikrostruktur der Festmörtel wurde hinsichtlich ihres Einflusses auf die Dauerhaftigkeit betrachtet.
In machine learning, if the training data is independently and identically distributed as the test data then a trained model can make an accurate predictions for new samples of data. Conventional machine learning has a strong dependence on massive amounts of training data which are domain specific to understand their latent patterns. In contrast, Domain adaptation and Transfer learning methods are sub-fields within machine learning that are concerned with solving the inescapable problem of insufficient training data by relaxing the domain dependence hypothesis. In this contribution, this issue has been addressed and by making a novel combination of both the methods we develop a computationally efficient and practical algorithm to solve boundary value problems based on nonlinear partial differential equations. We adopt a meshfree analysis framework to integrate the prevailing geometric modelling techniques based on NURBS and present an enhanced deep collocation approach that also plays an important role in the accuracy of solutions. We start with a brief introduction on how these methods expand upon this framework. We observe an excellent agreement between these methods and have shown that how fine-tuning a pre-trained network to a specialized domain may lead to an outstanding performance compare to the existing ones. As proof of concept, we illustrate the performance of our proposed model on several benchmark problems.