36 research outputs found
Structural optimization in steel structures, algorithms and applications
No full textL'abstract è presente nell'allegato / the abstract is in the attachmen
Retrofitting of a Steel Truss Joint by Creating Composite Connections and PTMSs (Post-Tensioned Metal Straps)
No full textThe fatigue phenomenon has a significant effect on the joints of steel truss bridges, causing the formation of plastic hinges leading to potential collapse configurations. For this reason, in the last few years, the development of new methods to effectively strengthen such joints has gained attention. In this article, a mechanism for the improvement of the resistance to fatigue of these types of connections is proposed, by employing composite joints and post-tensioned metal straps (PTMSs). Following this approach, first the overstressed connections of the structure have been identified during the inspection phase, and subsequently, they have been encased in a concrete casting with a proper level of strength. To analyze the behavior of the steel–concrete mixed solution, a finite element model has been realized in ABAQUS (rel. 2022.0) and it has been validated based on comparison between the numerical results and the experimental ones obtained by laboratory tests. Then, a parametric analysis was performed to investigate the effect of the concrete type employed in the connection behavior. In the second stage of the research, based on the first cracks configuration obtained numerically and observed experimentally, PTMSs have been used to control the cracks and strengthen the joint. The strains and stresses on the concrete and steel parts of the connection were measured before and after the insertion of the PTMSs and compared with the outputs of the model. Additionally, a parametric analysis was carried out to assess the optimal number of straps. The effect of this solution on the resistance of the joint and on the behavior of concrete was analyzed and the effectiveness of the strengthening technique was assessed
Numerical models comparison for fluid-viscous dampers: Performance investigations through Genetic Algorithm
No full textFluid-viscous dampers played a crucial role in the protection of new or existing buildings against external actions as earthquakes and winds. In the last decade, several investigations have been conducted aiming to develop accurate numerical models. However, none has been focused on a comprehensive comparison between the most used fluid-viscous damper models considering the variability of their parameters in a mass-production series. In this paper, an identification procedure has been performed by comparing nine different existing literature models with the objective of evaluating their ability to match experimental loops of mass-produced fluid-viscous devices, both in terms of accuracy and robustness. Indeed, the model that is most effective for reproducing the characteristic of a specific specimen may not be representative (i.e., showing larger parameters variability) of the mass production of the same device type. For this purpose, dynamic tests have been developed in the laboratory and the experimental outputs have been adopted as the target function of the procedure. The identification scheme has been designed by implementing an optimization procedure via Genetic Algorithm. Results demonstrate how differential laws better fit the experimental cycles with respect to algebraic ones, and also show how few models in the series can offer a high level of both accuracy and robustness
Corrosion effects on the capacity and ductility of concrete half-joint bridges
No full textMonitoring and evaluating the deterioration of structures is one of the most pressing challenges of the last decades. Bridges and overpasses represent a significant percentage of infrastructures requiring ongoing maintenance and monitoring. In this scenario, a typical static solution used in the last century is the Gerber half-joint, obtained by reducing the cross-section of a beam end, supported by the nib of the adjacent beam or abutment. The particular geometry gives many benefits. However, at the same time, it is the origin of damages and failure due to the difficulty to access for inspections, and the proneness to corrosion phenomena. This study estimates the effect of corrosion on the capacity and ductility of two case studies: a half-joint tested by Desnerk et al. used for model calibration and a real-case half-joint. The author simulated an increasing level of corrosion in the two case studies by reducing the cross-section of the re-bars and modifying the ductility of steel. The analyses showed different behaviour in the two case studies. While the first exhibited a significant reduction of capacity and ductility, the real-case half joint did not show a manifest capacity reduction, still, accompanied by minor embrittlement of the response
Structural Control and Health Monitoring Contributions to Service‐life Extension of Bridges
No full textTransportation Infrastructure networks are acknowledged as crucial for economic growth, territorial coherence, and social change. Unfortunately, some of this vast system's most important structural elements, like the bridges, are rapidly aging while the load conditions that these systems were designed to withstand are now being exceeded as a result of various threats, including natural disasters and newly discovered man-made phenomena. Considering that a large amount of the existing bridge stock was built many years ago, if countermeasures are not taken, deterio-ration phenomena and an increase in service conditions larger than those used in the original design may have contributed to diminishing the dependability level. Hence, it becomes crucial to evaluate the existing status of transportation infra-structure, make predictions about its future state, and safeguard it from outside threats. This contribution focuses on an in-depth investigation of the impact of Structural Control and Health Monitoring in increasing the structural resilience of transportation infrastructure and subsequently its life-cycle
Cutting Stock Problem (CSP) applied to Structural Optimization for the minimum waste cost
No full textIn this study, an optimization method to design simple truss structures for the evaluation
of the optimal stock of existing elements is introduced. To achieve this goal,
the well-known Bin Packing Problem (BPP) will be implemented within the structural
optimization procedure. Specifically, among all the BPP variants, one of the most
common applications in real-world cases is the Cutting Stock Problem (CSP) in which
the objective is to produce dj copies of each item type j by employing the minimum
number of bins. In the civil engineering field, structural optimization is often employed
aiming to improve the load-bearing capacity of the structure itself, i.e. maximization
of the performance ratio through the minimization of the structure weight.
However, this goal doesn’t guarantee maximum efficiency in terms of minimization
of waste during the industrial production phase. To overcome these limits, authors
propose a stock-constrained structural optimization in which a heuristic search technique
is adopted and the best arrangement of bars whit the lowest cut-off waste is
obtained for a 10-bar-truss case study. For completeness reasons, a comparison
between the solution obtained by the classic minimum weight optimization problem
and the stock-constrained one is discussed
Performance-based optimization of steel exoskeletons: An alternative approach to standard regulations
No full textAmong the various seismic retrofitting techniques, steel exoskeletons are distinguished as a valuable retrofitting approach to mitigate structural vulnerability under lateral loads while simultaneously preserving the buildings’ functionality and activities’ full operability. However, they are not a commonly selected option by designers, as several standard regulations recommend a design approach based on the relative stiffness between the exoskeletons and the building. They establish a restrictive limit for this ratio, resulting in costly and heavy designs. This paper proposes a paradigm shift in exoskeleton design, moving from the control of the stiffness ratio to a performance-based design approach. Different inter-story drift thresholds are adopted as performance constraints of an innovative optimized design procedure where the number, position, and sizing of the exoskeletons are assumed as design variables. Based on the outcomes of the optimization processes conducted on three real-world inspired case studies, a sensitivity analysis is performed. In all scenarios, the results demonstrate that the performance-based approach allows for greater utilization of the building's capacity in the elastic field to resist horizontal actions while preserving structural safety. Consequently, in contrast with the conservative designs obtained following standard regulations, the proposed approach leads to lighter and more economically efficient designs, which make the exoskeletons a more attractive alternative
Review on deep learning in structural health monitoring
No full textRoad bridges are fundamental and most critical elements of land transportation routes which allow to overpass many physical obstacles. Therefore, these elements have to be preserved in order to maintain structural performances over time degradation actions. At the beginning, the first monitoring techniques which were developed are related to dynamic identification which was proven to provide reliable indicators of the current health state of a structural system. Analysing the variations of modal properties (natural frequency, damping ratio and mode shapes) over a certain period of time it is possible to identify if some events or damages occurred in the structural system which determine some changes in structural properties, safety levels and structural performances. Most adopted methodologies are based on frequency domain as frequency domain decomposition and even time-domain approaches are usual such as autoregressive models, moving average models, their combination with or without exogenous term and stochastic subspace identifications. Nowadays, structural health monitoring (SHM) techniques are classified into different levels based on the level of depth of information which is provided from the only damage detection until the accurate structural diagnosis with damage identification and localization and structural prognosis. In recent years, machine learning tools have provided innovative and vibrant developments in this field especially through the deep learning (DL) approaches. These approaches provide a change of paradigm of the feature engineering approach because the feature extraction is automatically conducted in the learning phase of the network. In the present work, the most recent deep learning architectures such as convolutional neural networks, capsule neural networks, recurrent neural networks and neural transformers adopted in the SHM field are analysed and described in order to focus on the most advantages of the state-of-art approaches and to address future direction of further developments of these outstanding new technologies
Optimal strengthening by steel truss arches in prestressed girder bridges
No full textThis work focuses on the proposal and the evaluation of a new consolidation system for prestressed reinforced concrete (PRC) beams of girder bridges. The system consists of two arch-shaped steel trusses placed alongside the
lateral faces of the beam to be consolidated. The arches develop longitudinally along the entire span of the beam and in elevation using the available height of the PRC cross section. The consolidation system is characterized by
its own external constraints, independent from those serving the pre-existing element. The efficiency of the system with respect to parameters variability is described also focusing on the ratio between the load discharged by the
consolidation system and the total applied load. Referring to a case study, the consolidation of a PRC beam is presented adopting the proposed system with respect to the usually adopted external prestressing technique. The
cross sections properties of the steel arch shaped trusses are defined by means of a structural optimization process using a genetic algorithm, identifying the minimum steel consumption. Finally, a preliminary cost-benefit analysis is performed for the proposed solution for a comparison with other commonly adopted techniques
