Optimal preliminary design of variable section beams criterion

The present paper discusses about optimal shape solution for a non-prismatic planar beam. The proposed model is based on the standard Timoshenko kinematics hypothesis (i.e., planar cross-section remains planar in consequence of a deformation, but it is able to rotate with respect to the beam center-line). The analytical solution for this type of beam is thus used to obtain deformations and stresses of the beam, under different constraints, when load is assumed as the sum of a generic external variable vertical one and the self-weight. The solution is obtained by numerical integration of the beam equation and constraints are posed both on deflection and maximum stress under the hypothesis of an ideal material. The section variability is, thus, described assuming a rectangular cross section with constant base and variable height which can be described in general with a trigonometric series. Other types of empty functions could also be analyzed in order to find the best strategy to get the optimal solution. Optimization is thus performed by minimizing the beam volume considering the effects of non-prismatic geometry on the beam behavior. Finally, several analytical and numerical solutions are compared with results existing in literature, evaluating the solutions’ sensibility to some key parameters like beam span, material density, maximum allowable stress and load distribution. In conclusion, the study finds a critical threshold in terms of emptying function beyond which it is not possible to neglect the arch effect and the curvature of the actual axis for every different case study described in this work. In order to achieve this goal, the relevance of beam span, emptying function level and maximum allowable stress are investigated

Enhanced Multi-Strategy Particle Swarm Optimization for Constrained Problems with an Evolutionary-Strategies-Based Unfeasible Local Search Operator

Nowadays, optimization problems are solved through meta-heuristic algorithms based on stochastic search approaches borrowed from mimicking natural phenomena. Notwithstanding their successful capability to handle complex problems, the No-Free Lunch Theorem by Wolpert and Macready (1997) states that there is no ideal algorithm to deal with any kind of problem. This issue arises because of the nature of these algorithms that are not properly mathematics-based, and the convergence is not ensured. In the present study, a variant of the well-known swarm-based algorithm, the Particle Swarm Optimization (PSO), is developed to solve constrained problems with a different approach to the classical penalty function technique. State-of-art improvements and suggestions are also adopted in the current implementation (inertia weight, neighbourhood). Furthermore, a new local search operator has been implemented to help localize the feasible region in challenging optimization problems. This operator is based on hybridization with another milestone meta-heuristic algorithm, the Evolutionary Strategy (ES). The self-adaptive variant has been adopted because of its advantage of not requiring any other arbitrary parameter to be tuned. This approach automatically determines the parameters’ values that govern the Evolutionary Strategy simultaneously during the optimization process. This enhanced multi-strategy PSO is eventually tested on some benchmark constrained numerical problems from the literature. The obtained results are compared in terms of the optimal solutions with two other PSO implementations, which rely on a classic penalty function approach as a constraint-handling method

Experimental Investigation of the Static and Dynamic behaviors of 3D-Printed Shell Structures

Over the last years, several optimization strategies were conducted to find the optimal shape minimizing internal stress or total weight (volume) of shell structures. In recent times, this structure typology gained a great importance among researchers and the scientific community for the renowed interest in the form-findind optimization of column-free space solution for large span roofing constructions. In the present paper, a form-finding of a shallow grid shells was introduced basing on the multy-body rope approach (MRA) for the definitions of vault shapes and different hole percentage. In order to obtain an experimental validation, a physical model was reproduced at the laboratory scale performing ad hoc measurements to compare the observed respect to the simulated behaviour. A 3D printing procedure based on the Fuse Deposition Modeling (FDM) technique in polylactide (PLA) material was used to realise form-works of the cement based blocks of the scaled prototype. Several static and dynamic load configurations are investigated, collecting into a sensitivity analysis the parameters which mainly affect the structural behaviour. To simulate earthquake ground motion an assigned frequency range as dynamic input to the structure was provided by a shaking table. Finally, some preliminary considerations of the dynamic response of the model were provided testing the robustness of the form-finding approach when horizontal load are taken into account

FRCM retrofitting techniques for masonry walls: a literature review and some laboratory tests

The experimental characterisation of externally bonded composite materials as strengthening solutions for masonry structures, such as basalt textile reinforced mortar (BTRM) or fiber reinforced concrete (FRC), has been receiving increasing attention due to their outstanding mechanical performance. Several studies have been demonstrated the efficiency of this retrofitting solution for increasing the mechanical strength and the displacement capacity of masonry material. In this paper the state-of-art of the most relevant achievements in the experimental investigations and numerical analysis of retrofitted masonry wall have been critically reviewed. Firstly, a detailed collection of several experimental tests using different textile reinforced mortar and/or fiber reinforced mortar has been conducted. Special focus has been given to the test set-up and load configuration type adopted for experiments. Subsequently, several modelling techniques have been treated in order to detect the best approach simulating the interaction between reinforcement system and masonry ranging from macro and micro modelling, concentrated and diffused plasticity model and diverse constitutive laws. Finally, an overview of some original experimental outcomes from laboratory tests is presented. This results will play a major role in for the validation of the numerical models for the prediction of the shear strength and the ductile behavior of reinforced masonry that will be developed in a further step of this research

Are protected areas covering important biodiversity sites? An assessment of the nature protection network in Sicily (Italy)

GIS spatial analysis of three indicators (vegetation value, faunal richness and landscape heterogeneity) was used to detect and map High-Value Biodiversity Areas (HVBAs), estimate the coverage of biodiversity in the Sicilian protected areas network, and identify new priority areas that could improve long-term biodiversity conservation outcomes. Findings indicated that only 32% of HVBAs are currently covered by the protected areas network. Hotspot analysis revealed that a modest expansion (less than 1%) in the current extent of protected areas would include a disproportionate amount (56%) of biodiversity hotspots, and identified prioritized candidates HVBAs for designation of new protected areas. © 2018 Elsevier Lt

ADVANCED DEEP LEARNING COMPARISONS FOR NON-INVASIVE TUNNEL LINING ASSESSMENT FROM GROUND PENETRATING RADAR PROFILES

Innovative, automated, and non-invasive techniques have been developed by scientific community to indirectly assess structural conditions and support the decision-making process for a worthwhile maintenance schedule. Nowadays, machine learning tools are in the spotlight because of their outstanding capabilities to deal with data coming from even heterogeneous sources and their ability to extract information from the structural systems, providing highly effective, reliable, and efficient damage classification tools. In the current study, a supervised multi-level damage classification strategy has been developed regarding Ground Penetrating Radar (GPR) profiles for the assessment of tunnel lining conditions. In previous research, the authors firstly considered a convolutional neural network (CNN), adopting the quite popular ResNet-50, initialized through transfer learning. In the present work, further enhancements have been attempted by adopting two configurations of the newest state-of-art advanced neural architectures: the neural transformers. The foremost is the original Vision Transformer (ViT), whose core is an encoder entirely based on the innovative self-attention mechanism and does not rely on convolution at all. The second is an improvement of ViT which merges convolution and self-attention, the Compact Convolution Transformer (CCT). In conclusion, a critical discussion of the different pros and cons of adopting the above-mentioned different architectures is finally provided, highlighting the actual powerfulness of these technologies in the future civil engineering paradigm nevertheless

Vulnerability assessment and lifecycle analysis of an existing masonry arch bridge

This paper presents a comprehensive study on structural verification and proposed improvements for an ancient masonry arch bridge. The research encompasses multiple stages, starting with a detailed survey utilizing LiDAR and aerial techniques to collect precise data on the bridge’s condition. Mechanical inspections assess deterioration levels and identify critical areas requiring attention. Based on the gathered data, a structural model of the bridge is developed, considering geometric parameters and material properties. The model undergoes rigorous verification procedures to assess its seismic response and ensure compliance with safety standards. The analysis includes identifying potential collapse mechanisms, such as the formation of plastic hinges, which can lead to structural failure. The study proposes structural improvements to enhance the bridge’s performance and safety. These interventions specifically target vulnerabilities identified during the verification process. They include additional support elements, reinforcing critical areas, and utilizing advanced materials to improve tensile strength and durability. The feasibility of the proposed retrofitting solutions will be proved by performing a cost analysis, while environmental impacts are evaluated through an environmental assessment (Lifecycle Assessment — LCA) in which all the main bridge refurbishment phases have been included. Finally, some of the advantages of bridge refurbishment measures are shown by comparing the proposed intervention with a bridge reconstruction in terms of costs and environmental impacts. The outcomes of this study contribute to the existing knowledge on the rehabilitation of masonry arch bridges and serve as a valuable reference for engineers and practitioners involved in preserving architectural heritage

Service-life extension of transport infrastructure through structural control

Transportation Infrastructure Systems are recognized as essential for economic development, territorial cohesion, and social transformation. Due to the increasing age of bridges, and given that a large part of the existing stock was built several decades ago, some of their key structural components, such as bridges, are getting older while loading conditions are often exceeding those initially envisaged as they are subjected to harsher natural events and growing levels of traffic. The increasing age of bridges, the deterioration phenomena and the increase in service conditions, exceeding those used in the initial design, contribute to reduce their reliability level. This contribution firstly explores the role that structural control can play, then it proposes a suitable measure for the formalization of this role within the life-cycle assessment of bridges and overcrossing structures. The effects of structural control are evaluated for the case study of a cable-supported bridge subjected to fatigue deterioration due to wind actions

Numerical models comparison for fluid-viscous dampers: Performance investigations through Genetic Algorithm

Fluid-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