Parallel simulation system for earthquake generation: Fault analysis modules and parallel coupling analysis

Solid earth simulations have recently been developed to address issues such as natural disasters, global environmental destruction and the conservation of natural resources. The simulation of solid earth phenomena involves the analysis of complex structures including strata, faults, and heterogeneous material properties. Simulation of the generation and cycle of earthquakes is particularly important, but such simulations require the analysis of complex fault dynamics. GeoFEM is a parallel finite-element analysis system intended for solid earth field phenomena problems. This paper describes recent development in the GeoFEM project for the simulation of earthquake generation and cycles.

Dynamic stability of laminated FGM plates based on higher-order shear deformation theory

This paper conducts a dynamic stability analysis of symmetrically laminated FGM rectangular plates with general out-of-plane supporting conditions, subjected to a uniaxial periodic in-plane load and undergoing uniform temperature change. Theoretical formulations are based on Reddy's third-order shear deformation plate theory, and account for the temperature dependence of material properties. A semi-analytical Galerkin-differential quadrature approach is employed to convert the governing equations into a linear system of Mathieu-Hill equations from which the boundary points on the unstable regions are determined by Bolotin's method. Free vibration and bifurcation buckling are also discussed as subset problems. Numerical results are presented in both dimensionless tabular and graphical forms for laminated plates with FGM layers made of silicon nitride and stainless steel. The influences of various parameters such as material composition, layer thickness ratio, temperature change, static load level, boundary constraints on the dynamic stability, buckling and vibration frequencies are examined in detail through parametric studies.

Historical and dialectical perspectives on the teaching of Aboriginal and Torres Strait Islander musics in the Australian education system

Indigenous studies (also referred to as Aboriginal and Torres Strait Islander studies) has a double identity in the Australian education system, consisting of the education of Indigenous students and education of all students about Aboriginal and Torres Strait Islander cultures and histories. Through explanations of the history of the inclusion of Aboriginal and Torres Strait Islander musics in Australian music education, this article critiques ways in which these musics have been positioned in relation to a number of agendas. These include definitions of Aboriginal and Torres Strait Islander musics as types of Australian music, as ethnomusicological objects, as examples of postcolonial discourse, and as empowerment for Indigenous students. The site of discussion is the work of the Australian Society for Music Education, as representative of trends in Australian school-based music education, and the Centre for Aboriginal Studies in Music at the University of Adelaide, as an example of a tertiary music program for Indigenous students.

Phase equilibria and surface tension of pure fluids using a molecular layer structure theory (MLST) model

This paper presents a new model based on thermodynamic and molecular interaction between molecules to describe the vapour-liquid phase equilibria and surface tension of pure component. The model assumes that the bulk fluid can be characterised as set of parallel layers. Because of this molecular structure, we coin the model as the molecular layer structure theory (MLST). Each layer has two energetic components. One is the interaction energy of one molecule of that layer with all surrounding layers. The other component is the intra-layer Helmholtz free energy, which accounts for the internal energy and the entropy of that layer. The equilibrium between two separating phases is derived from the minimum of the grand potential, and the surface tension is calculated as the excess of the Helmholtz energy of the system. We test this model with a number of components, argon, krypton, ethane, n-butane, iso-butane, ethylene and sulphur hexafluoride, and the results are very satisfactory. (C) 2002 Elsevier Science B.V. All rights reserved.

Quantum theory of the far-off-resonance continuous-wave Raman laser: Heisenberg-Langevin approach

We present the quantum theory of the far-off-resonance continuous-wave Raman laser using the Heisenberg-Langevin approach. We show that the simplified quantum Langevin equations for this system are mathematically identical to those of the nondegenerate optical parametric oscillator in the time domain with the following associations: pump pump, Stokes signal, and Raman coherence idler. We derive analytical results for both the steady-state behavior and the time-dependent noise spectra, using standard linearization procedures. In the semiclassical limit, these results match with previous purely semiclassical treatments, which yield excellent agreement with experimental observations. The analytical time-dependent results predict perfect photon statistics conversion from the pump to the Stokes and nonclassical behavior under certain operational conditions.

Critical behavior of a three-dimensional hardcore-cylinder composite system

In this work the critical indices β, γ , and ν for a three-dimensional (3D) hardcore cylinder composite system with short-range interaction have been obtained. In contrast to the 2D stick system and the 3D hardcore cylinder system, the determined critical exponents do not belong to the same universality class as the lattice percolation,although they obey the common hyperscaling relation for a 3D system. It is observed that the value of the correlation length exponent is compatible with the predictions of the mean field theory. It is also shown that, by using the Alexander-Orbach conjuncture, the relation between the conductivity and the correlation length critical exponents has a typical value for a 3D lattice system.

Green microfinance: the case of the Cresol System in Southern Brazil

Climate change which until recently seemed a luxury for the microfinance sector, now appears to be crucial for the future of the sector. Due to their low adaptive capacity, the millions of MF clients worldwide happen to be the most vulnerable to a changing climate. Adapting previous analysis conducted in Nepal and Bangladesh by Agrawala and Maëlis (2010) to the Brazilian context, in this inductive qualitative study we aim to assess potential synergies between MF and CC actions and what strategies can be harnessed to better respond to CC vulnerabilities at client/MF level. To do so, we investigated the case of the second largest rural microcredit programme in Brazil, Sistema Cresol de Cooperativas de Crédito Rural com Interação Solidária. Albeit important overlaps between Cresol's product envelope and CC strategies exist, there is still room to realise synergies to both mitigate a new potential source of risk to Cresol's portfolio and to increase clients' adaptive capacity.

Mathematical modeling of pressurized system behaviour with entrapped air

The presence of entrapped air in pressurized hydraulic systems is considered a critical condition for the infrastructure security, due to the transient pressure enhancement related with its dynamic behaviour, similar to non-linear spring action. A mathematical model for the assessment of hydraulic transients resulting from rapid pressurizations, under referred condition is presented. Water movement was modeled through the elastic column theory considering a moving liquid boundary and the entrapped air pocket as lumped gas mass, where the acoustic effects are negligible. The method of characteristics was used to obtain the numerical solution of the liquid flow. The resulting model is applied to an experimental set-up having entrapped air in the top of a vertical pipe section and the numerical results are analyzed.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.