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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.
Assessing Essential Qualities of Urban Space with Emotional and Visual Data Based on GIS Technique
(2016)
Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and more accurate using innovative information techniques that have become available in the era of big data. This study introduces an integrated method based on geographical information systems (GIS) and an emotion-tracking technique to quantify the relationship between people’s emotional responses and urban space. This method can evaluate the degree to which people’s emotional responses are influenced by multiple urban characteristics such as building shapes and textures, isovist parameters, visual entropy, and visual fractals. The results indicate that urban spaces may influence people’s emotional responses through both spatial sequence arrangements and shifting scenario sequences. Emotional data were collected with body sensors and GPS devices. Spatial clustering was detected to target effective sampling locations; then, isovists were generated to extract building textures. Logistic regression and a receiver operating characteristic analysis were used to determine the key isovist parameters and the probabilities that they influenced people’s emotion. Finally, based on the results, we make some suggestions for design professionals in the field of urban space optimization.
This dissertation is devoted to the theoretical development and experimental laboratory verification of a new damage localization method: The state projection estimation error (SP2E). This method is based on the subspace identification of mechanical structures, Krein space based H-infinity estimation and oblique projections. To explain method SP2E, several theories are discussed and laboratory experiments have been conducted and analysed.
A fundamental approach of structural dynamics is outlined first by explaining mechanical systems based on first principles. Following that, a fundamentally different approach, subspace identification, is comprehensively explained. While both theories, first principle and subspace identification based mechanical systems, may be seen as widespread methods, barely known and new techniques follow up. Therefore, the indefinite quadratic estimation theory is explained. Based on a Popov function approach, this leads to the Krein space based H-infinity theory. Subsequently, a new method for damage identification, namely SP2E, is proposed. Here, the introduction of a difference process, the analysis by its average process power and the application of oblique projections is discussed in depth.
Finally, the new method is verified in laboratory experiments. Therefore, the identification of a laboratory structure at Leipzig University of Applied Sciences is elaborated. Then structural alterations are experimentally applied, which were localized by SP2E afterwards. In the end four experimental sensitivity studies are shown and discussed. For each measurement series the structural alteration was increased, which was successfully tracked by SP2E. The experimental results are plausible and in accordance with the developed theories. By repeating these experiments, the applicability of SP2E for damage localization is experimentally proven.
The task-based view of web search implies that retrieval should take the user perspective into account. Going beyond merely retrieving the most relevant result set for the current query, the retrieval system should aim to surface results that are actually useful to the task that motivated the query.
This dissertation explores how retrieval systems can better understand and support their users’ tasks from three main angles: First, we study and quantify search engine user behavior during complex writing tasks, and how task success and behavior are associated in such settings. Second, we investigate search engine queries formulated as questions, and explore patterns in a large query log that may help search engines to better support this increasingly prevalent interaction pattern. Third, we propose a novel approach to reranking the search result lists produced by web search engines, taking into account retrieval axioms that formally specify properties of a good ranking.
In this work, practice-based research is conducted to rethink the understanding of aesthetics, especially in relation to current media art. Granted, we live in times when technologies merge with living organisms, but we also live in times that provide unlimited resources of knowledge and maker tools. I raise the question: In what way does the hybridization of living organisms and non-living technologies affect art audiences in the culture that may be defined as Maker culture? My hypothesis is that active participation of an audience in an artwork is inevitable for experiencing the artwork itself, while also suggesting that the impact of the umwelt changes the perception of an artwork. I emphasize artistic projects that unfold through mutual interaction among diverse peers, including humans, non-human organisms, and machines. In my thesis, I pursue collaborative scenarios that lead to the realization of artistic ideas: (1) the development of ideas by others influenced by me and (2) the materialization of my own ideas influenced by others. By developing the scenarios of collaborative work as an artistic experience, I conclude that the role of an artist in Maker culture is to mediate different types of knowledge and different positions, whereas the role of the audience is to actively engage in the artwork itself. At the same time, aesthetics as experience is triggered by the other, including living and non-living actors. It is intended that the developed methodologies could be further adapted in artistic practices, philosophy, anthropology, and environmental studies.
In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Text
Tall buildings have become an integral part of cities despite all their pros and cons. Some current tall buildings have several problems because of their unsuitable location; the problems include increasing density, imposing traffic on urban thoroughfares, blocking view corridors, etc. Some of these buildings have destroyed desirable views of the city. In this research, different criteria have been chosen, such as environment, access, social-economic, land-use, and physical context. These criteria and sub-criteria are prioritized and weighted by the analytic network process (ANP) based on experts’ opinions, using Super Decisions V2.8 software. On the other hand, layers corresponding to sub-criteria were made in ArcGIS 10.3 simultaneously, then via a weighted overlay (map algebra), a locating plan was created. In the next step seven hypothetical tall buildings (20 stories), in the best part of the locating plan, were considered to evaluate how much of theses hypothetical buildings would be visible (fuzzy visibility) from the street and open spaces throughout the city. These processes have been modeled by MATLAB software, and the final fuzzy visibility plan was created by ArcGIS. Fuzzy visibility results can help city managers and planners to choose which location is suitable for a tall building and how much visibility may be appropriate. The proposed model can locate tall buildings based on technical and visual criteria in the future development of the city and it can be widely used in any city as long as the criteria and weights are localized.
The initial shear modulus, Gmax, of soil is an important parameter for a variety of geotechnical design applications. This modulus is typically associated with shear strain levels about 5*10^-3% and below. The critical role of soil stiffness at small-strains in the design and analysis of geotechnical infrastructure is now widely accepted.
Gmax is a key parameter in small-strain dynamic analyses such as those to predict soil behavior or soil-structure interaction during earthquake, explosions, machine or traffic vibration where it is necessary to know how the shear modulus degrades from its small-strain value as the level of shear strain increases. Gmax can be equally important for small-strain cyclic situations such as those caused by wind or wave loading and for small-strain static situations as well. Gmax may also be used as an indirect indication of various soil parameters, as it, in many cases, correlates well to other soil properties such as density and sample disturbance. In recent years, a technique using bender elements was developed to investigate the small-strain shear modulus Gmax.
The objective of this thesis is to study the initial shear stiffness for various sands with different void ratios, densities, grain size distribution under dry and saturated conditions, then to compare empirical equations to predict Gmax and results from other testing devices with results of bender elements from this study.
For many purposes geometric information about existing buildings is necessary, e.g. planing of conservation or reconstruction. Architectural photogrammetry is a technique to acquire 3D geometric data of buildings for a CAD model from images. In this paper the state of the art in architectural photogrammetry and some developments towards automation are described. The photogrammetric process consists of image acquisition, orientation and restitution. Special attention is put on digital methods, from digital image acquisition to restitution methods, supported by digital image processing. There are a few field of development towards automation, e.g. feature extraction, extraction of edges and lines and the detection of corresponding points. The acquired data may be used in a CAD environment or for visualization in Virtual Reality Models, using digital orthoimages for texture mapping.
Effective knowledge management is increasingly considered as a cornerstone of sustainable business success. Knowledge management systems are strategically valuable for both ensuring consistency and continuous improvement of various aspects such as quality delivery, productivity and competitiveness. The small and medium enterprises (SMEs) in the construction industry are mostly operating under tighter timeframes, narrower profit margins and more constrained resources. Hence the recently commenced SMILE-SMC (Strategic Management with Information Leveraged Excellece for Small and Medium Contractors) project aims to support the information and knowledge management needs of the small and medium contractors in Hong Kong. This paper presents some snapshots on the SMILE-SMC project, and its conceptualized deliverables with some highlights of recent developments.