1,182 research outputs found

    Optimal preliminary design of variable section beams criterion

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    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

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    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

    Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR): A critical overview on the most promising applications of molecular scissors in oral medicine

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    The scientific community is continuously working to translate the novel biomedical techniques into effective medical treatments. CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats-9), commonly known as the “molecular scissor”, represents a recently developed biotechnology able to improve the quality and the efficacy of traditional treatments, related to several human diseases, such as chronic diseases, neurodegenerative pathologies and, interestingly, oral diseases. Of course, dental medicine has notably increased the use of biotechnologies to ensure modern and conservative approaches: in this landscape, the use of CRISPR-Cas9 system may speed and personalize the traditional therapies, ensuring a good predictability of clinical results. The aim of this critical overview is to provide evidence on CRISPR efficacy, taking into specific account its applications in oral medicine

    Optimal design algorithm for seismic retrofitting of RC columns with steel jacketing technique

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    Steel jacketing (SJ) of beams and columns is widely employed as retrofitting technique to provide additional deformation and strength capacity to existing reinforced concrete (RC) frame structures. The latter are many times designed without considering seismic loads, or present inadequate seismic detailing. The use of SJ is generally associated with non-negligible costs depending on the amount of structural work and non-structural manufacturing and materials. Moreover, this kind of intervention results in noticeable downtime for the building. This paper presents a new optimization framework which is aimed at obtaining minimization of retrofitting costs by optimizing the position and the amount of steel jacketing retrofitting. The proposed methodology is applied to the case study of a 3D RC frame realized in OpenSEES and handled within the framework of a genetic algorithm. The algorithm iterates geometric and mechanical parameters configurations, based on the outcomes of static pushover analysis, in order to match the optimal retrofitting solution, intended as the one minimizing the costs and, at the same time, maintaining a specified safety level. Results of the proposed framework will provide optimized location and amount of steel-jacketing reinforcement. It is finally shown that the use of engineering optimization methods can be effectively used to limit retrofitting costs without a substantial modification of structural safety

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

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    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

    How Many Templates for GW Chirp Detection? The Minimal-Match Issue Revisited

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    In a recent paper dealing with maximum likelihood detection of gravitational wave chirps from coalescing binaries with unknown parameters we introduced an accurate representation of the no-signal cumulative distribution of the supremum of the whole correlator bank. This result can be used to derive a refined estimate of the number of templates yielding the best tradeoff between detector's performance (in terms of lost signals among those potentially detectable) and computational burden.Comment: submitted to Class. Quantum Grav. Typing error in eq. (4.8) fixed; figure replaced in version
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