Papers by Keyword: Environmental Conditions

Abstract: In this study we compare the effectiveness of the Normalised Smoothed Envelope (NSET) method for Artificial Neural Network (ANN) based impact localisation under simulated environmental and operational conditions with respect to other ANN based localisation methods developed by other studies. It is shown that when the testing and training impact case is the same, most studies give comparably good accuracy of localisation irrespective of feature extraction method or structure geometry. However, when the testing and training impact cases are not the same, only the NSET method is able to negate the variations caused by various impact cases and provide good localisation accuracy for an ANN trained using only a single impact case thus allowing for smaller training data set size requirements and increasing feasibility for real life application.

Abstract: ANNs are only accurate for the scope of the given training data which is not suitable for real life impact localisation due to the large range of possible impact variation. Impact data was collected for a variation of impact cases (angle, mass and energy) on a sensorized curved composite panel. From observation of the obtained data, a robust signal Time of Arrival (TOA) extraction method is proposed using a Normalised Smooth Envelope Threshold (NSET) which is a modification of the currently known Normalised Threshold (NT) method. Two ANNs were trained using TOA extracted with the NT and NSET method from a baseline case and tested with TOA extracted from cases having added variation of impact condition. The results show that the proposed NSET method results in more accurate results for impact cases different to the training case and thus allows for only a single impact training case to accurately predict cases with multiple variation. This enhances the applicability of ANNs for impact localisation in real life conditions.

Abstract: Industrial waste pollution in the cities and the areas beyond them is a burning issue today. The only solution is recycling the by-products of primary production. Thus, the magnesia caustics are widely used in construction. However, their application is limited due to their high hygroscopicity. Many scientists were involved into the study of this problem justifying their achieved positive result by either using different types of sealers or introduction of fine composition active mineral additives into the binder. Moreover, all these studies mainly focused on the improvement of the water resistance of magnesia composites, while hygroscopic regulation was not significant. So it is important to study the process of environmental moisture accumulation in the pores of the magnesia material. When establishing the causes of the high hygroscopicity of magnesium materials, it was found that its value depends on environmental conditions (temperature, pressure and relative humidity); the specific surface area of magnesia stone; density of the sealer for magnesia binder; the chemical composition of various modifying additives and their influence on the properties of magnesia stone and materials based on it; the composition of the hydrated phases of magnesia stone with additives and without them; the presence of pores, their size and number in the structure of the stone; the surface charge of a magnesia stone. Studies have shown that high-strength water resistant chlorine magnesia stone in combination with modifying additives allows obtaining a composite material with hygroscopicity less than 2 %.

Abstract: Pipe leaks detection has a great economic, environmental and safety impact. Although several methods have been developed to solve the leak detection problem, some drawbacks such as continuous monitoring and robustness should be addressed yet. Thus, this paper presents the main results of using a leaks detection and classification methodology, which takes advantage of piezodiagnostics principle. It consists of: i) transmitting/sensing guided waves along the pipe surface by means of piezoelectric device ii) representing statistically the cross-correlated piezoelectric measurements by using Principal Component Analysis iii) identifying leaks by using error indexes computed from a statistical baseline model and iv) verifying the performance of the methodology by using a Self-Organizing Map as visualization tool and considering different leak scenario. In this sense, the methodology was experimentally evaluated in a carbon-steel pipe loop under different leaks scenarios, with several sizes and locations. In addition, the sensitivity of the methodology to temperature, humidity and pressure variations was experimentally validated. Therefore, the effectiveness of the methodology to detect and classify pipe leaks, under varying environmental and operational conditions, was demonstrated. As a result, the combination of piezodiagnostics approach, cross-correlation analysis, principal component analysis, and Self-Organizing Maps, become as promising solution in the field of structural health monitoring and specifically to achieve robust solution for pipe leak detection.

Abstract: The durability and reliability of electromechanical drives is inseparably linked to the broadly defined environmental conditions under which they operate. The design of new solutions characterised by a high level of safety requires the execution of laboratory tests in accordance with the applicable legal regulations, and with a particular focus on the user requirements, that would simulate the actual environment of application. The aim of the research was to develop a test system for electromechanical drives that can be used in particularly demanding systems, e.g. fire protection or process control systems. The hardware and software solutions applied allow one to determine the characteristics (force, displacement, current, and supply voltage as a function of time) in changeable climatic conditions. As part of the verification of the system, the author studied the prototypes of electromechanical ball-screw actuators developed at the Institute for Sustainable Technologies – National Research Institute (ITeE-PIB) and dedicated for the rail traffic control system.

Abstract: LGJ150/25 steel core aluminum stranded wires were selected as the test wires, and the aeolian vibrations which work in different cycle times of wire that is under the conditions of dry and acidic corrosion were simulated by the self-made test bed. The electronic number of corona discharge of each pre-set conductor was measured, when applying AC high voltage on the wearing wires step by step,so that the corona inception voltages of the conductors could be confirmed. And the effect of the vibration cycle times and environmental conditions on the corona discharge was researched. Taking the sum of all aluminium stands wear area of a pre-set wire as the fretting wearing capacity, the relationship between the wire wearing capacity and the corona discharge was studied. The results indicate that the corona inception voltages of the conductors decrease with the increase of the cycle times and the wires wear capacity. In general, the wear capacity of the acidic corrosion conductors is larger, and its corona inception voltage is lower. Therefore the decrease of the conductor fretting wear can effectively reduce the corona loss of transmission lines and other hazards.

Abstract: The monitoring of timber structures exposed to natural climate fluctuations during their service life is an important topic for both their serviceability and safety. Numerical methods based on the recent advances in hygro-thermal modelling of wood can integrate the usual sensor-based monitoring techniques by reducing the maintenance costs for timber structures. In this paper, a 3D full coupled analysis based on the multi-Fickian theory with sorption hysteresis of wood is implemented in Abaqus FEM code by defining a new finite element in a user subroutine. To verify the method, the hygro-thermal behaviour of a glulam beam tested in laboratory under variable humidity within a previous research is analysed and the numerical values of moisture content are found to be in agreement with the experimental data. Furthermore, a numerical case-study of a glulam cross section under real climate variations is presented and the related results show the capability of the method to predict the moisture states in each points of the glulam member under continuously variable humidity and temperature.

Abstract: Roofs from the fifth skin of buildings and define the character of the architecture. Their main function is sometimes to provide protection against the sun and wind, and sometimes to channel, collect and store rain water. Each climate required a different type of roof to its specific need protection of human life. The choice of one type of roof another depends fundamentally on the client brief, on the implications of the environment, on the climatic conditions and on the resources available or current technology. For a roof with certain quality characteristics there may be different technological and budgetary solutions. The roof must be conceived constructively, rationalized and adapted to the variable conditions of its environment. In this paper, we review the different types of roof, the materials used and their auxiliary elements.

Abstract: Structural Health Monitoring (SHM) allows to perform a diagnosis on demand which assists the operator to plan his future maintenance or repair activities. Using structural vibrations to extract damage sensitive features, problems can arise due to variations of the dynamical properties with changing environmental and operational conditions (EOC). The dynamic changes due to changing EOCs like variations in temperature, rotational speed, wind speed, etc. may be of the same order of magnitude as the variations due to damage making a reliable damage detection impossible. In this paper, we show a method for the compensation of changing EOC. The well-known null space based fault detection (NSFD) is used for damage detection. In the first stage, a training is performed using data from the undamaged structure under varying EOC. For the compensation of the EOC-e ects the undamaged state is modeled by different reference data corresponding to different representative EOC conditions. Finally, in the application, the influences of one or other EOC on each incoming data is weighted separately by means of a fuzzy-classiffcation algorithm. The theory and algorithm is successfully tested with data sets from a real wind turbine and with data from a laboratory model.

Abstract: This paper presents the test results of an experimental study that investigates the durability of a new generation of Glass Fiber Reinforced Polymer (GFRP) bars. A total of 60 GFRP bars were embedded in concrete prisms and exposed to ten environmental conditions for 6 and 12 months. The environments included exposure to ordinary tap water, sea water, and alkaline solution at two temperatures (room and 50°C). The environments also included two typical field conditions of the Kingdom of Saudi Arabia (Gulf area and Riyadh area). The performance of the GFRP bars was evaluated by conducting tensile tests on the bars extracted out of the concrete specimens after exposure to the environmental conditions. After 12 months of exposure, the test results showed that the tap water at 50°C had the maximum effect on the tensile strength of the GFRP bars. The two field conditions did not show any harmful effect on the tensile properties of the bars after 12 months of exposure.