1,304 research outputs found
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
- …