Identification of inelastic parameters of the 304 stainless steel using multi-objective techniques

This work addresses identification of inelastic parameters based on an optimization method using a multi-objective technique. The problem consists in determining the best set of parameters which approximate three different tensile tests. The tensile tests use cylindrical specimens of different dimensions manufactured according to the American ASTM E 8M and Brazilian ABNT NBR ISO 6892 technical standards. A tensile load is applied up to macroscopic failure. The objective functions for each tensile test/specimen is computed and a global error measure is determined within the optimization scheme. The Nelder-Mead simplex algorithm is used as the optimization tool. The proposed identification strategy was able to determine the best set of material parameters which approximate all tensile tests up to macroscopic failure

Further studies on identification of inelastic parameters for damaged materials

A proper set of material parameters is one of the most important aspects for a successful simulation of metal forming processes. Several issues must be observed when choosing the constitutive relation and corresponding material parameters, amongst which the most important are: (i) the magnitude of the plastic deformation of the target forming operation must be contemplated by the parameters of the constitutive model, (ii) possibility of failure prediction in fracture-free materials, and (iii) accurate prediction of geometrical changes caused by plastic deformation. Within this framework, the present article discusses techniques to obtain constitutive parameters of a Lemaitre-type material model. The strategy requires compliance of multiple tensile tests with specimens prepared according to different technical standards. Parameter identification is regarded as an inverse problem and solved using optimization methods

Divide and conquer: resonance induced by competitive interactions

We study an Ising model in a network with disorder induced by the presence of both attractive and repulsive links. This system is subjected to a subthreshold signal, and the goal is to see how the response is enhanced for a given fraction of repulsive links. This can model a network of spin-like neurons with excitatory and inhibitory couplings. By means of numerical simulations and analytical calculations we find that there is an optimal probability, such that the coherent response is maximal

Non-Markovian Dynamics of Charge Carriers in Quantum Dots

We have investigated the dynamics of bound particles in multilevel current-carrying quantum dots. We look specifically in the regime of resonant tunnelling transport, where several channels are available for transport. Through a non-Markovian formalism under the Born approximation, we investigate the real-time evolution of the confined particles including transport-induced decoherence and relaxation. In the case of a coherent superposition between states with different particle number, we find that a Fock-space coherence may be preserved even in the presence of tunneling into and out of the dot. Real-time results are presented for various asymmetries of tunneling rates into different orbitals.Comment: 9 pages, 3 figures, International Workshop on Physics-Based Mathematical Models for Low-Dimensional Semiconductor Nanostructures. BIRS, November 18-23, 200

Rappresentazioni della città come spazio di insicurezza e criminalità: Lisbona (1850-1910)

The relationship between crime and the city, the idea that the city favoured the practice of crime, was a recurring issue in the 19th century. In Portugal, this idea mainly concerned the city of Lisbon. Using diverse documentation, this communication analyses the representations of the city understood as an insecure and criminal space, as opposed to the idyllic constructions then made about life in the countryside and the narratives that define the city as a space of modernity and well-being.info:eu-repo/semantics/publishedVersio

Reflection and Transmission at the Apparent Horizon during Gravitational Collapse

We examine the wave-functionals describing the collapse of a self-gravitating dust ball in an exact quantization of the gravity-dust system. We show that ingoing (collapsing) dust shell modes outside the apparent horizon must necessarily be accompanied by outgoing modes inside the apparent horizon, whose amplitude is suppressed by the square root of the Boltzmann factor at the Hawking temperature. Likewise, ingoing modes in the interior must be accompanied by outgoing modes in the exterior, again with an amplitude suppressed by the same factor. A suitable superposition of the two solutions is necessary to conserve the dust probability flux across the apparent horizon, thus each region contains both ingoing and outgoing dust modes. If one restricts oneself to considering only the modes outside the apparent horizon then one should think of the apparent horizon as a partial reflector, the probability for a shell to reflect being given by the Boltzmann factor at the Hawking temperature determined by the mass contained within it. However, if one considers the entire wave function, the outgoing wave in the exterior is seen to be the transmission through the horizon of the interior outgoing wave that accompanies the collapsing shells. This transmission could allow information from the interior to be transferred to the exterior.Comment: 19 pages, no figures. To appear in Phys. Rev.

A benchmark study on identification of inelastic parameters based on deep drawing processes using pso – nelder mead hybrid approach

Optimization techniques have been increasingly used to identification of inelastic material parameters owing to their generality. Development of robust techniques to solving this class of inverse problems has been a challenge to researchers mainly due to the nonlinear character of the problem and behaviour of the objective function. Within this framework, this work discusses application of Particle Swarm Optimization (PSO) and a PSO – Nelder Mead hybrid approach to identification of inelastic parameters based on a benchmark solution of the deep drawing process