Prediction of the cross-sectional capacity of cold-formed CHS using numerical modelling and machine learning

The use of circular hollow sections (CHS) have seen a large increase in usage in recent years mainly because of the distinctive mechanical properties and unique aesthetic appearance. The focus of this paper is the behaviour of cold-rolled CHS beam-columns made from normal and high strength steel, aiming to propose a design formula for predicting the ultimate cross-sectional load carrying capacity, employing machine learning. A finite element model is developed and validated to conduct an extensive parametric study with a total of 3410 numerical models covering a wide range of the most influential parameters. The ANN model is then trained and validated using the data obtained from the developed numerical models as well as 13 test results compiled from various research available in the literature, and accordingly a new design formula is proposed. A comprehensive comparison with the design rules given in EC3 is presented to assess the performance of the ANN model. According to the results and analysis presented in this study, the proposed ANN-based design formula is shown to be an efficient and powerful design tool to predict the cross-sectional resistance of the CHS beam-columns with a high level of accuracy and the least computational costs

System reliability-based design of 2D steel frames by advanced analysis

The design of steel frames by geometric and material nonlinear analysis also referred to as -inelastic‖ or -advanced‖ analysis, is permitted by most specifications such as AISC360-10 and AS4100. In these specifications, the strength of a structural frame can be determined by system analysis in lieu of checking member resistances to the specific provisions of the Specification, provided a comparable or higher level of structural reliability. In designing by advanced analysis, the system resistance factor is applied to the frame strength determined by analysis. Provided that the design strength exceeds the required strength, the design is deemed adequate, requiring no further check of individual member resistance. The system-based design of steel structures by advanced analysis leads to a more efficient structural design process and achieves a more uniform level of structural reliability. The main impediment to adopting the procedure in practical applications is the apparent difficulty in assigning an appropriate resistance factor to the structural system. This thesis illustrates the novel framework of the system design-by-analysis approach and how to determine suitable system resistance factors accounting for inherent uncertainties in the ultimate strength of a frame. All key parameters influencing the frame strength are modelled as random and Monte-Carlo type simulations are conducted. New approaches for modelling initial geometric imperfections and residual stresses are introduced. The simulation results for a series of 2D low-to-mid-rise steel frames, which represent typical steel building inventory as well as frames from the literature, are presented obtained according to the proposed methodology. Braced and moment resisting frames are analysed under various load combinations and the system resistance factors are derived for different reliability levels

System reliability-based design of 2D steel frames by advanced analysis

The design of steel frames by geometric and material nonlinear analysis also referred to as -inelastic‖ or -advanced‖ analysis, is permitted by most specifications such as AISC360-10 and AS4100. In these specifications, the strength of a structural frame can be determined by system analysis in lieu of checking member resistances to the specific provisions of the Specification, provided a comparable or higher level of structural reliability. In designing by advanced analysis, the system resistance factor is applied to the frame strength determined by analysis. Provided that the design strength exceeds the required strength, the design is deemed adequate, requiring no further check of individual member resistance. The system-based design of steel structures by advanced analysis leads to a more efficient structural design process and achieves a more uniform level of structural reliability. The main impediment to adopting the procedure in practical applications is the apparent difficulty in assigning an appropriate resistance factor to the structural system. This thesis illustrates the novel framework of the system design-by-analysis approach and how to determine suitable system resistance factors accounting for inherent uncertainties in the ultimate strength of a frame. All key parameters influencing the frame strength are modelled as random and Monte-Carlo type simulations are conducted. New approaches for modelling initial geometric imperfections and residual stresses are introduced. The simulation results for a series of 2D low-to-mid-rise steel frames, which represent typical steel building inventory as well as frames from the literature, are presented obtained according to the proposed methodology. Braced and moment resisting frames are analysed under various load combinations and the system resistance factors are derived for different reliability levels

Hybrid cold-formed steel structural systems for buildings

Cold-formed steel (CFS) shear walls or strap-braced walls are the primary lateral load resisting components in light-weight steel framed (LSF) structures. Despite the increasing demand on the application of CFS systems in mid-rise construction, the relatively low lateral load resistance capacity of these systems has remained one of the major obstacles for further growth, as this low resistance becomes problematic in their use in cyclonic wind regions or highly seismic zones. In this thesis, in order to address this issue, a new Hybrid CFS wall composed of CFS open sections and square hollow sections (SHS) is developed and investigated. The proposed hybrid system is suitable for light-weight steel structures for mid- to high-rise construction, due to its satisfactory lateral load resistance. The thesis presented provides the results of the study which contains experimental and numerical investigation as outlined in the following. In the first stage of this study, a comprehensive literature review was conducted to reveal the existing gaps in the previous studies on CFS structures under lateral loads. In the second stage, a series of full-scale experimental tests were performed on seventeen hybrid CFS wall panels in order to investigate their lateral performance, shear resistance, failure modes and energy absorption. In the third stage of this thesis, a comprehensive study was performed on the theories and applications of the numerical models for analysis of the lateral behaviour of CFS wall systems during the past several decades, and all existing numerical methods for simulating the behaviour of CFS shear walls were accordingly classified. In stage four of this study, proposed hybrid wall panel was further developed, and twenty new wall configurations were evaluated using non-linear finite element analysis, aiming to further investigate the seismic performance of CFS hybrid walls. Finally, in the last stage, a sustainability analysis was performed which could be of interest to all stakeholders including owners, builders and investors, when assessing the potential use of hybrid CFS systems, in particular for mid-rise buildings

Optimization of maintenance performance for offshore production facilities

Master's thesis in Offshore technologyNew technologies are becoming advanced and complex for offshore production facilities. However this advancement and complexity in technology creates a more complicated and time consuming forensic processes for finding causes of failure, or diagnostic processes to identify events that reduce performance. As a result, micro-sensors, efficient signaling and communication technologies for collecting data efficiently, advanced software tools (such as fuzzy logic, neural networks, and simulation based optimization) have been developed, in parallel, to manage such complex assets. Given the nature and scale of ongoing changes on complexities, there are emerging concerns that increasing complexities, ill-defined interfaces, unforeseen events can easily lead to serious performance failures and major risks. To avoid such undesirable circumstances, „just-in-time‟ measures of performance to ensure fully functional is absolutely necessary. The increasing trend in complexity creates a motivation to develop an integrated maintenance management framework to get real-time information to solve problems quickly and hence to increase functional performance (help the asset to perform its required function effectively and efficiently while safeguarding life and the environment). Establishing “just-in-time” maintenance and repairs based on true machine condition maximizes critical asset useful life and eliminates premature replacement of functional components. This thesis focuses on developing an integrated maintenance management framework to establish „just-in-time‟ maintenance and to ensure continuous improvements based on maintenance domain experts as well as operational and historic data. To do this, true degradation of components must be identified. True level of degradation often cannot be inferred by the mere trending of condition indicator‟s level (CBM), because condition indicator levels are modulated under the influence of the diverse operating context. Besides, the maintenance domain expert does not have a precise knowledge about the correlation of the diverse operating context and level of degradation for a given level of condition indicator on specific equipment. Efforts have been made in here to identify the true degradation pattern of a component by analyzing these vagueness and imprecise knowledge. Key words: effective and efficient maintenance strategy, ‘just-in-time’ maintenance, condition based maintenance, P-F interval