1,484 research outputs found
Energy harvesting from earthquake for vibration-powered wireless sensors
Wireless sensor networks can facilitate the acquisition of useful data for the assessment and retrofitting of existing structures and infrastructures. In this perspective, recent studies have presented numerical and experimental results about self-powered wireless nodes for structural monitoring applications in the event of earthquake, wherein the energy is scavenged from seismic accelerations. A general computational approach for the analysis and design of energy harvesters under seismic loading, however, has not yet been presented. Therefore, this paper proposes a rational method that relies on the random vibrations theory for the electromechanical analysis of piezoelectric energy harvesters under seismic ground motion. In doing so, the ground acceleration is simulated by means of the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with concentrated mass at the free-end, and its global behavior is approximated by the dynamic response of the fundamental vibration mode only (which is tuned with the dominant frequency of the site soil). Once the Lyapunov equation of the coupled electromechanical problem has been formulated, mean and standard deviation of the generated electric energy are calculated. Numerical results for a cantilever bimorph which piezoelectric layers made of electrospun PVDF nanofibers are discussed in order to understand issues and perspectives about the use of wireless sensor nodes powered by earthquakes. A smart monitoring strategy for the experimental assessment of structures in areas struck by seismic events is finally illustrated
4126 Subretinal choroidal neovascular membranes in hereditary macular diseases: A fluorescein angiography and ICGV study
Influence of curing thermal history on cross-linking degree of a polydimethylsiloxane: Swelling and mechanical analyses
In this work, the change of the elastic properties induced by a change in cross-linking conditions of polydimethylsiloxane is investigated by measuring its shear modulus by dynamic mechanical analysis and correlating it to that predicted
from swelling measurements. Polymer cross-linking is performed at different curing temperatures reached with ramps at different heating rates. From both mechanical and swelling measurements, the molecular weight between cross-links, MC, is determined, and its dependency on the applied thermal history is analyzed. The main results are: (i) the elastic modulus of the cured material is not significantly affected by the heating rate adopted, while (ii) the curing temperature has a significant influence on the polydimethylsiloxane mechanical properties. In addition, (iii) MC evaluation from swelling measurements is in good agreement with that estimated from mechanical measurements when appropriate theories are considered. This last result suggests that swelling experiments can be considered as a reliable tool to predict the elastic modulus of the polydimethylsiloxane studied. The quantitative information reported in this paper, also obtainable by the suggested method if other thermal curing histories are applied, is extremely useful for the proper design of devices based on polydimethylsiloxane
Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks
The mine detection in an unexplored area is an optimization problem where multiple mines, randomly distributed throughout an area, need to be discovered and disarmed in a minimum amount of time. We propose a strategy to explore an unknown area, using a stigmergy approach based on ants behavior, and a novel swarm based protocol to recruit and coordinate robots for disarming the mines cooperatively. Simulation tests are presented to show the effectiveness of our proposed Ant-based Task Robot Coordination (ATRC) with only the exploration task and with both exploration and recruiting strategies. Multiple minimization objectives have been considered: the robots' recruiting time and the overall area exploration time. We discuss, through simulation, different cases under different network and field conditions, performed by the robots. The results have shown that the proposed decentralized approaches enable the swarm of robots to perform cooperative tasks intelligently without any central control
Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption
Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios
Tharros - Capo San Marco in the Phoenician and Punic Age. Geophysical investigations and virtual rebuilding
The project described in this paper was started in 2012 and concerns the study of the relationship between the urban and suburban districts of the Phoenician and Punic city of Tharros (Cabras, Oristano). The structures of Phoenician and Punic Tharros have been largely cancelled by the Roman occupation. For this reason it is very difficult to determine the original function of many of the neighbourhoods during the Carthaginian period. The archaeological excavation primarily involved the southern necropolis of Capo San Marco. The cemetery must still be fully explored and understood under several aspects, mainly because of the devastation of the site caused by the repeated plundering of the ancient tombs which occurred during the 19th century. In addition to the new dig activities, a 3D topographical survey aimed at the complete documentation of the site and at the virtual rebuilding of the Phoenician and Punic funerary landscape was completed. Another goal of the project is the insertion of this sector of the promontory into the usual tourist route, in order to foster the public fruition of Capo San Marco, while continuing to adopt proper scientific methods and modern techniques. In this direction, geophysical prospecting surveys were carried out in the southern sector of the Capo San Marco, near the so-called ‘Rustic Temple’, in order to assess human presence in the farthest point of the Sinis peninsula (characterised by the presence of the Late Punic ruins of a probable light-house with sacred functions), and across the whole isthmus Sa Codriola towards the hill of San Giovanni, with the aim of analysing the northern boundary of the cemetery and its relationship to the city. The Punic-Roman settlement is now enclosed in the archaeological park, which is a fraction of what was supposed to be the administrative capital of Carthage in Sardinia. 3D modelling and virtual reconstructions were focused also on the residential Punic and Roman area inside the park. The integrated application of the most advanced topographical and geophysical techniques to the site greatly contributed to the recording and understanding of the ancient landscape
Cost and EAL based optimization for seismic reinforcement of RC structures
In this paper, a new genetic algorithm-based framework aimed at efficiently design multiple seismic retrofitting interventions is proposed. The algorithm focuses on the minimization of retrofitting intervention costs of reinforced concrete (RC) frame structures. The feasibility of each tentative solution is assessed by considering in an indirect way the expected annual loss (EAL), this evaluation is performed by referring to different limit states whose repairing costs are expressed as a percentage of reconstruction costs and evaluating the respective mean annual frequency of exceedance. As the EAL takes into account the overall structural performances, to involves both serviceability and ultimate limit states, two different seismic retrofitting techniques are considered. In particular, FRP wrapping of columns is employed to increase the ductility of RC elements managing life safety and collapse limit state demands. On the other hand, steel bracings are used to increase the global stiffness of the structure and mainly increase operational and damage limit states performances. The optimization procedure is carried out by the novel genetic algorithm-based framework developed in Matlab® that is connected to a 3D RC frame fiber-section model implemented in OpenSees. For both the retrofitting systems, the algorithm provides their position within the structure (topological optimization) and their sizing. Results will show that seismic retrofitting can be effectively designed to increase the overall structural safety by efficaciously optimizing the intervention costs
A new genetic algorithm framework based on Expected Annual Loss for optimizing seismic retrofitting in reinforced concrete frame structures
The design of seismic retrofitting for existing reinforced concrete frame structures concerns the determination of the position and the arrangement of reinforcements. Currently, this design practice is mainly based on trial-and-error attempts and engineers' experience, without a formal implementation of cost/performance optimization. Though, the implementation of this intervention is associated with significant costs, noticeable downtimes, and elevated invasiveness. This paper presents a new genetic algorithm-based framework for the optimization of two different retrofitting techniques (FRP column wrapping and concentric steel braces) that aims at minimizing costs considering indirectly the lessening of expected annual values. The feasibility of each tentative solution is controlled by the outcomes of static pushover analyses in the framework of the N2 method, achieved by a 3D fiber-section model implemented in OpenSees. Application of the framework in a realistic case study structure will show that the sustainability of retrofitting intervention is achievable by employing artificial intelligence aided structural design
A novel genetic algorithm-based optimization framework for minimizing seismic retrofitting interventions costs in existing masonry structures
The pressing necessity of enhancing the seismic safety of existing masonry structures in earthquake-prone areas has led, in recent years, the research to propose a vast amount of new retrofitting techniques. However, retrofitting interventions are generally associated with important costs. Currently, there are no formal methods to optimize these interventions thus, their design is entrusted only to engineers' intuition. This paper presents a novel optimization framework aimed at the minimization of seismic retrofitting-related costs by an optimal placement (topological optimization) of reinforced plasters in masonry structures. In the proposed framework a 3D equivalent masonry model implemented in OpenSees is handled by a genetic algorithm developed in MATLAB® routine that iterates reinforcement configurations to match the optimal solution. The feasibility of each solution is controlled by the outcomes of a seismic static equivalent analysis by controlling the safety check of masonry walls with respect to both flexural and shear collapse. It is also shown, through a case study, that the proposed approach is efficient to pinpoint optimal retrofitting configurations, significantly reducing invasiveness and downtime
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