Numerical prediction of the non-linear behaviour of perforated metal shear panels

Steel plate shear walls (SPSWs) are innovative systems able to confer to either new or existing structures a significant capacity to resist earthquake and wind loads. Many tests have shown that these devices may exhibit high strength, initial stiffness and ductility, as well as an excellent ability to dissipate energy. When full SPSWs are used as bracing devices of buildings, they may induce excessive stresses in the surrounding main structure where they are inserted, so to require the adoption of large cross section profiles. For this reason, perforated steel panels, which are weakened by holes aiming at limiting the actions transmitted to the surrounding frame members, represent a valid alternative to full panels. In this work, aiming at showing the advantages of such devices, a FEM model of perforated panels has been calibrated on the basis of recent experimental tests. Subsequently, a parametric FEM analysis on different series of perforated panels, by changing the number and diameter of the holes, the plate thickness and the metal material, has been carried out. Finally, the achieved numerical results have been used to set up design charts to correctly estimate the strength and stiffness of perforated metal shear panels

Modeling random and non-random decision uncertainty in ratings data: A fuzzy beta model

Modeling human ratings data subject to raters' decision uncertainty is an attractive problem in applied statistics. In view of the complex interplay between emotion and decision making in rating processes, final raters' choices seldom reflect the true underlying raters' responses. Rather, they are imprecisely observed in the sense that they are subject to a non-random component of uncertainty, namely the decision uncertainty. The purpose of this article is to illustrate a statistical approach to analyse ratings data which integrates both random and non-random components of the rating process. In particular, beta fuzzy numbers are used to model raters' non-random decision uncertainty and a variable dispersion beta linear model is instead adopted to model the random counterpart of rating responses. The main idea is to quantify characteristics of latent and non-fuzzy rating responses by means of random observations subject to fuzziness. To do so, a fuzzy version of the Expectation-Maximization algorithm is adopted to both estimate model's parameters and compute their standard errors. Finally, the characteristics of the proposed fuzzy beta model are investigated by means of a simulation study as well as two case studies from behavioral and social contexts.Comment: 24 pages, 0 figures, 5 table

Observation of the BL Lac objects 1ES 1215+303 and 1ES 1218+304 with the MAGIC telescopes

The two BL Lac objects 1ES 1215+303 and 1ES 1218+304, separated by 0.8 deg, were observed with the MAGIC telescopes in 2010 and 2011. The 20 hours of data registered in January 2011 resulted in the first detection at Very High Energy (>100 GeV) of 1ES 1215+303 (also known as ON-325). This observation was triggered by a high optical state of the source reported by the Tuorla blazar monitoring program. Comparison with the 25 hours of data carried out from January to May 2010 suggests that 1ES 1215+303 was flaring also in VHE gamma-rays in 2011. In addition, the Swift ToO observations in X-rays showed that the flux was almost doubled respect to previous observations (December 2009). Instead, 1ES 1218+304 is a well known VHE gamma-ray emitter lying in the same field of view, which was then simultaneously observed with the MAGIC telescopes. The overall observation time of nearly 45 hours has permitted to measure the spectrum of this source with a much higher precision than previously reported by MAGIC. Here, we present the results of the MAGIC and the multi-wavelength observations of these two VHE gamma-ray emitting AGNs.Comment: 4 pages, 5 figures, Proceedings of the 32nd ICRC (2011) Beijin

QAL-BP: An Augmented Lagrangian Quantum Approach for Bin Packing Problem

The bin packing is a well-known NP-Hard problem in the domain of artificial intelligence, posing significant challenges in finding efficient solutions. Conversely, recent advancements in quantum technologies have shown promising potential for achieving substantial computational speedup, particularly in certain problem classes, such as combinatorial optimization. In this study, we introduce QAL-BP, a novel Quadratic Unconstrained Binary Optimization (QUBO) formulation designed specifically for bin packing and suitable for quantum computation. QAL-BP utilizes the augmented Lagrangian method to incorporate the bin packing constraints into the objective function while also facilitating an analytical estimation of heuristic, but empirically robust, penalty multipliers. This approach leads to a more versatile and generalizable model that eliminates the need for empirically calculating instance-dependent Lagrangian coefficients, a requirement commonly encountered in alternative QUBO formulations for similar problems. To assess the effectiveness of our proposed approach, we conduct experiments on a set of bin-packing instances using a real Quantum Annealing device. Additionally, we compare the results with those obtained from two different classical solvers, namely simulated annealing and Gurobi. The experimental findings not only confirm the correctness of the proposed formulation but also demonstrate the potential of quantum computation in effectively solving the bin-packing problem, particularly as more reliable quantum technology becomes available.Comment: 14 pages, 4 figures, 1 tabl

A Morse Theory for Massive Particles and Photons in General Relativity

In this paper we develop a Morse Theory for timelike geodesics parameterized by a constant multiple of proper time. The results are obtained using an extension to the timelike case of the relativistic Fermat Principle, and techniques from Global Analysis on infinite dimensional manifolds. In the second part of the paper we discuss a limit process that allows to obtain also a Morse theory for light rays

FULL AND PERFORATED METAL PLATE SHEAR WALLS AS BRACING SYSTEMS FOR SEISMIC UPGRADING OF EXISTING RC BUILDINGS

Metal Plate Shear Walls (MPSWs) represent an effective, practical and economical system for the seismic protection of existing RC framed buildings. They consist of one or more metallic thin plates, bolted or welded to a stiff steel frame, which are installed in the bays of RC framed structures. A case study of an existing RC residential 5-storey building, designed between the ‘60s and ‘70s of the last century and retrofitted with MPSWs, has been examined in this paper. The retrofitting design of the existing structure has been carried out by using four different MPSWs, namely three common full panels made of steel, low yield steel and aluminium and one innovative perforated steel plates. Finally, the used retrofitting solutions have been compared each to other in terms of performance and economic parameters, allowing to select the best intervention

A novel CFA+EFA model to detect aberrant respondents

Aberrant respondents are common but yet extremely detrimental to the quality of social surveys or questionnaires. Recently, factor mixture models have been employed to identify individuals providing deceptive or careless responses. We propose a comprehensive factor mixture model that combines confirmatory and exploratory factor models to represent both the non-aberrant and aberrant components of the responses. The flexibility of the proposed solution allows for the identification of two of the most common aberant response styles, namely faking and careless responding. We validated our approach by means of two simulations and two case studies. The results indicate the effectiveness of the proposed model in handling with aberrant responses in social and behavioral surveys.Comment: 24 pages, 5 figures, 7 table