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One of the most promising and recent advances in computer-based planning is the transition from classical geometric modeling to building information modeling (BIM). Building information models support the representation, storage, and exchange of various information relevant to construction planning. This information can be used for describing, e.g., geometric/physical properties or costs of a building, for creating construction schedules, or for representing other characteristics of construction projects. Based on this information, plans and specifications as well as reports and presentations of a planned building can be created automatically. A fundamental principle of BIM is object parameterization, which allows specifying geometrical, numerical, algebraic and associative dependencies between objects contained in a building information model. In this paper, existing challenges of parametric modeling using the Industry Foundation Classes (IFC) as a federated model for integrated planning are shown, and open research questions are discussed.
IFC-BASED MONITORING INFORMATION MODELING FOR DATA MANAGEMENT IN STRUCTURAL HEALTH MONITORING
(2015)
This conceptual paper discusses opportunities and challenges towards the digital representation of structural health monitoring systems using the Industry Foundation Classes (IFC) standard. State-of-the-art sensor nodes, collecting structural and environmental data from civil infrastructure systems, are capable of processing and analyzing the data sets directly on-board the nodes. Structural health monitoring (SHM) based on sensor nodes that possess so called “on-chip intelligence” is, in this study, referred to as “intelligent SHM”, and the infrastructure system being equipped with an intelligent SHM system is referred to as “intelligent infrastructure”. Although intelligent SHM will continue to grow, it is not possible, on a well-defined formalism, to digitally represent information about sensors, about the overall SHM system, and about the monitoring strategies being implemented (“monitoring-related information”). Based on a review of available SHM regulations and guidelines as well as existing sensor models and sensor modeling languages, this conceptual paper investigates how to digitally represent monitoring-related information in a semantic model. With the Industry Foundation Classes, there exists an open standard for the digital representation of building information; however, it is not possible to represent monitoring-related information using the IFC object model. This paper proposes a conceptual approach for extending the current IFC object model in order to include monitoring-related information. Taking civil infrastructure systems as an illustrative example, it becomes possible to adequately represent, process, and exchange monitoring-related information throughout the whole life cycle of civil infrastructure systems, which is referred to as monitoring information modeling (MIM). However, since this paper is conceptual, additional research efforts are required to further investigate, implement, and validate the proposed concepts and methods.
Sensor faults can affect the dependability and the accuracy of structural health monitoring (SHM) systems. Recent studies demonstrate that artificial neural networks can be used to detect sensor faults. In this paper, decentralized artificial neural networks (ANNs) are applied for autonomous sensor fault detection. On each sensor node of a wireless SHM system, an ANN is implemented to measure and to process structural response data. Structural response data is predicted by each sensor node based on correlations between adjacent sensor nodes and on redundancies inherent in the SHM system. Evaluating the deviations (or residuals) between measured and predicted data, sensor faults are autonomously detected by the wireless sensor nodes in a fully decentralized manner. A prototype SHM system implemented in this study, which is capable of decentralized autonomous sensor fault detection, is validated in laboratory experiments through simulated sensor faults. Several topologies and modes of operation of the embedded ANNs are investigated with respect to the dependability and the accuracy of the fault detection approach. In conclusion, the prototype SHM system is able to accurately detect sensor faults, demonstrating that neural networks, processing decentralized structural response data, facilitate autonomous fault detection, thus increasing the dependability and the accuracy of structural health monitoring systems.
In this paper, we present an empirical approach for objective and quantitative benchmarking of optimization algorithms with respect to characteristics induced by the forward calculation. Due to the professional background of the authors, this benchmarking strategy is illustrated on a selection of search methods in regard to expected characteristics of geotechnical parameter back calculation problems. Starting from brief introduction into the approach employed, a strategy for optimization algorithm benchmarking is introduced. The benchmarking utilizes statistical tests carried out on well-known test functions superposed with perturbations, both chosen to mimic objective function topologies found for geotechnical objective function topologies. Here, the moved axis parallel hyper-ellipsoid test function and the generalized Ackley test function in conjunction with an adjustable quantity of objective function topology roughness and fraction of failing forward calculations is analyzed. In total, results for 5 optimization algorithms are presented, compared and discussed.
Polymer modification of mortar and concrete is a widely used technique in order to improve their durability properties. Hitherto, the main application fields of such materials are repair and restoration of buildings. However, due to the constant increment of service life requirements and the cost efficiency, polymer modified concrete (PCC) is also used for construction purposes. Therefore, there is a demand for studying the mechanical properties of PCC and entitative differences compared to conventional concrete (CC). It is significant to investigate whether all the assumed hypotheses and existing analytical formulations about CC are also valid for PCC. In the present study, analytical models available in the literature are evaluated. These models are used for estimating mechanical properties of concrete. The investigated property in this study is the modulus of elasticity, which is estimated with respect to the value of compressive strength. One existing database was extended and adapted for polymer-modified concrete mixtures along with their experimentally measured mechanical properties. Based on the indexed data a comparison between model predictions and experiments was conducted by calculation of forecast errors.
What is nowadays called (classic) Clifford analysis consists in the establishment of a function theory for functions belonging to the kernel of the Dirac operator. While such functions can very well describe problems of a particle with internal SU(2)-symmetries, higher order symmetries are beyond this theory. Although many modifications (such as Yang-Mills theory) were suggested over the years they could not address the principal problem, the need of a n-fold factorization of the d’Alembert operator. In this paper we present the basic tools of a fractional function theory in higher dimensions, for the transport operator (alpha = 1/2 ), by means of a fractional correspondence to the Weyl relations via fractional Riemann-Liouville derivatives. A Fischer decomposition, fractional Euler and Gamma operators, monogenic projection, and basic fractional homogeneous powers are constructed.
The sizing of simple resonators like guitar strings or laser mirrors is directly connected to the wavelength and represents no complex optimisation problem. This is not the case with liquid-filled acoustic resonators of non-trivial geometries, where several masses and stiffnesses of the structure and the fluid have to fit together. This creates a scenario of many competing and interacting resonances varying in relative strength and frequency when design parameters change. Hence, the resonator design involves a parameter-tuning problem with many local optima. As its solution evolutionary algorithms (EA) coupled to a forced-harmonic FE simulation are presented. A new hybrid EA is proposed and compared to two state-of-theart EAs based on selected test problems. The motivating background is the search for better resonators suitable for sonofusion experiments where extreme states of matter are sought in collapsing cavitation bubbles.
The stress state of a piecewise-homogeneous elastic body, which has a semi-infinite crack along the interface, under in-plane and antiplane loads is considered. One of the crack edges is reinforced by a rigid patch plate on a finite interval adjacent to the crack tip. The crack edges are loaded with specified stresses. The body is stretched at infinity by specified stresses. External forces with a given principal vector and moment act on the patch plate. The problem reduces to a Riemann-Hilbert boundary-value matrix problem with a piecewise-constant coefficient for two complex potentials in the plane case and for one in the antiplane case. The complex potentials are found explicitly using a Gaussian hypergeometric function. The stress state of the body close to the ends of the patch plate, one of which is also simultaneously the crack tip, is investigated. Stress intensity factors near the singular points are determined.
Steel profiles with slender cross-sections are characterized by their high susceptibility to instability phenomena, especially local buckling, which are intensified under fire conditions. This work presents a study on numerical modelling of the behaviour of steel structural elements in case of fire with slender cross-sections. To accurately carry out these analyses it is necessary to take into account those local instability modes, which normally is only possible with shell finite elements. However, aiming at the development of more expeditious methods, particularly important for analysing complete structures in case of fire, recent studies have proposed the use of beam finite elements considering the presence of local buckling through the implementation of a new effective steel constitutive law. The objective of this work is to develop a study to validate this methodology using the program SAFIR. Comparisons are made between the results obtained applying the referred new methodology and finite element analyses using shell elements. The studies were made to laterally restrained beams, unrestrained beams, axially compressed columns and columns subjected to bending plus compression.