Free energies of ferroelectric crystals from a microscopic approach

The free energy of barium titanate is computed around the Curie temperature as a function of polarization from the first-principles derived effective hamiltonian of Zhong, Vanderbilt and Rabe [Phys. Rev. Lett. 73, 1861 (1994)], through Molecular Dynamics simulations coupled to the method of the Thermodynamic Integration. The main feature of this approach is to calculate the gradient of the free energy in the 3-D space (Px,Py,Pz) from the thermal averages of the forces acting on the local modes, that are obtained by Molecular Dynamics under the constraint of fixed P. A careful analysis of the states of constrained polarization is performed at T=280 K (~ 15-17 K below Tc) especially at low order parameter. These states are found reasonably homogeneous for small supercell size (L=12 and L=16), until inhomogeneous states are observed at low order parameter for large supercells (L=20). However, for reasonable supercell sizes (L=12), the free energy curves obtained are in very good agreement with phenomenological Landau potentials of the litterature. Moreover, the free energy obtained is quite insensitive to the supercell size from L=12 to L=16 at T=280 K, suggesting that interfacial contributions, if any, are negligible at these sizes around Tc. The method allows a numerical estimation of the free energy barrier separating the paraelectric from the ferroelectric phase at Tc. However, our tests evidence phase separation at low temperature and low order parameter, in agreement with the results of Tr\"oster et al [Phys. Rev. B 72 (2005), 094103].Comment: submitted to Computer Physics Communication

Scheduling uncertain orders in the customer–subcontractor context

Within the customer–subcontractor negotiation process, the first problem of the subcontractor is to provide the customer with a reliable order lead-time although his workload is partially uncertain. Actually, a part of the subcontractor workload is composed of orders under negotiation which can be either confirmed or cancelled. Fuzzy logic and possibility theory have widely been used in scheduling in order to represent the uncertainty or imprecision of processing times, but the existence of the manufacturing orders is not usually set into question. We suggest a method allowing to take into account the uncertainty of subcontracted orders. This method is consistent with list scheduling: as a consequence, it can be used in many classical schedulers. Its implementation in a scheduler prototype called TAPAS is described. In this article, we focus on the performance of validation tests which show the interest of the method

Hybridation of Bayesian networks and evolutionary algorithms for multi-objective optimization in an integrated product design and project management context

A better integration of preliminary product design and project management processes at early steps of system design is nowadays a key industrial issue. Therefore, the aim is to make firms evolve from classical sequential approach (first product design the project design and management) to new integrated approaches. In this paper, a model for integrated product/project optimization is first proposed which allows taking into account simultaneously decisions coming from the product and project managers. However, the resulting model has an important underlying complexity, and a multi-objective optimization technique is required to provide managers with appropriate scenarios in a reasonable amount of time. The proposed approach is based on an original evolutionary algorithm called evolutionary algorithm oriented by knowledge (EAOK). This algorithm is based on the interaction between an adapted evolutionary algorithm and a model of knowledge (MoK) used for giving relevant orientations during the search process. The evolutionary operators of the EA are modified in order to take into account these orientations. The MoK is based on the Bayesian Network formalism and is built both from expert knowledge and from individuals generated by the EA. A learning process permits to update probabilities of the BN from a set of selected individuals. At each cycle of the EA, probabilities contained into the MoK are used to give some bias to the new evolutionary operators. This method ensures both a faster and effective optimization, but it also provides the decision maker with a graphic and interactive model of knowledge linked to the studied project. An experimental platform has been developed to experiment the algorithm and a large campaign of tests permits to compare different strategies as well as the benefits of this novel approach in comparison with a classical EA

Distributed machining control and monitoring using smart sensors/actuators

The study of smart sensors and actuators led, during the past few years, to the development of facilities which improve traditional sensors and actuators in a necessary way to automate production systems. In an other context, many studies are carried out aiming at defining a decisional structure for production activity control and the increasing need of reactivity leads to the autonomization of decisional levels close to the operational system. We suggest in this paper to study the natural convergence between these two approaches and we propose an integration architecture dealing with machine tool and machining control that enables the exploitation of distributed smart sensors and actuators in the decisional system

Hybridization of Bayesian networks and belief functions to assess risk. Application to aircraft deconstruction

This paper aims to present a study on knowledge management for the disassembly of end-of-life aircraft. We propose a model using Bayesian networks to assess risk and present three approaches to integrate the belief functions standing for the representation of fuzzy and uncertain knowledge

Strong Isotopic Effect in Phase II of Dense Solid Hydrogen and Deuterium

Quantum nuclear zero-point motions in solid H$_2$ and D$_2$ under pressure are investigated at 80 K up to 160 GPa by first-principles path-integral molecular dynamics calculations. Molecular orientations are well-defined in phase II of D$_2$, while solid H$_2$ exhibits large and very asymmetric angular quantum fluctuations in this phase, with possible rotation in the (bc) plane, making it difficult to associate a well-identified single classical structure. The mechanism for the transition to phase III is also described. Existing structural data support this microscopic interpretation.Comment: 5 pages, 3 figure

Low-temperature anharmonicity of barium titanate: a path-integral molecular dynamics study

We investigate the influence of quantum effects on the dielectric and piezoelectric properties of barium titanate in its (low-temperature) rhombohedral phase, and show the strongly anharmonic character of this system even at low temperature. For this purpose, we perform path-integral molecular-dynamics simulations under fixed pressure and fixed temperature, using an efficient Langevin thermostat-barostat, and an effective hamiltonian derived from first-principles calculations. The quantum fluctuations are shown to significantly enhance the static dielectric susceptibility (~ by a factor 2) and the piezoelectric constants, reflecting the strong anharmonicity of this ferroelectric system even at very low temperature. The slow temperature-evolution of the dielectric properties observed below ~ 100 K is attributed (i) to zero-point energy contributions and (ii) to harmonic behavior if quantum effects are turned off.Comment: submitted to Phys. Rev.

Integration of experience feedback into the product lifecycle: an approach to best respond to the bidding process

Bidding process allows a client to choose a bidder to realize an embodiment of work, supply or service. From the bidder point of view, there are several obvious risks when responding because he bets on a future development that hasn’t been yet realized. We propose to assist the bidder with decision support tools based on past experiences to detect, report and minimize these potential risks. In this paper, we present the definition of a conceptual architecture to integrate experience feedback into the product lifecycle taking into account all stages of product lifecycle to best respond new bidding processes