On the Evaluation of the Mechanical Behaviour of Structural Glass Elements

Glass can be considered to be a high-technology engineering material with a multifunctional potential for structural applications. However, the conventional approach to the use of glass is often based only on its properties of transparency and isolation. It is thus highly appropriate and necessary to study the mechanical behaviour of this material and to develop adequate methods and models leading to its characterisation. It is evident that the great potential of growth for structural glass applications is an important opportunity of development for the glass industry and the building/construction sectors. The work presented in this paper is a reflection of this conclusion. The authors shortly present the state-of-the-art on the application of glass as a structural element in building and construction, and refer to other potential fields of application and available glass materials. The experimental procedures and methods adopted in three-point bending tests performed on 500 × 100 [mm2] float, laminated and tempered glass specimens with thicknesses between 4 and 19 mm are thoroughly described. The authors evaluated the mechanical strength and stiffness of glass for structural applications. This work contributes to a deeper knowledge of the properties of this material

Valence-bond theory of highly disordered quantum antiferromagnets

We present a large-N variational approach to describe the magnetism of insulating doped semiconductors based on a disorder-generalization of the resonating-valence-bond theory for quantum antiferromagnets. This method captures all the qualitative and even quantitative predictions of the strong-disorder renormalization group approach over the entire experimentally relevant temperature range. Finally, by mapping the problem on a hard-sphere fluid, we could provide an essentially exact analytic solution without any adjustable parameters.Comment: 5 pages, 3 eps figure

Constraining nonstandard neutrino-quark interactions with solar, reactor and accelerator data

We present a reanalysis of nonstandard neutrino-down-quark interactions of electron and tau neutrinos using solar, reactor and accelerator data. In addition updating the analysis by including new solar data from SNO phase III and Borexino, as well as new KamLAND data and solar fluxes, a key role is played in our analysis by the combination of these results with the CHARM data. The latter allows us to better constrain the axial and axial-vector electron and tau-neutrino nonstandard interaction parameters characterizing the deviations from the Standard Model predictions.Comment: 11 pages, 6 figures, 2 tables, typo corrected in Figure 2, version published in Phys. Rev.

Random Antiferromagnetic SU(N) Spin Chains

We analyze random isotropic antiferromagnetic SU(N) spin chains using the real space renormalization group. We find that they are governed at low energies by a universal infinite randomness fixed point different from the one of random spin-1/2 chains. We determine analytically the important exponents: the energy-length scale relation is $\Omega\sim\exp(-L^{\psi})$, where $\psi=1/N$, and the mean correlation function is given by $\bar{C_{ij}}\sim(-1)^{i-j}/|i-j|^{\phi}$, where $\phi=4/N$. Our analysis shows that the infinite-N limit is unable to capture the behavior obtained at any finite N.Comment: 4 pages, 3 figure

Bayesian inferencing for wind resource characterisation

The growing role of wind power in power systems has motivated R&D on methodologies to characterise the wind resource at sites for which no wind speed data is available. Applications such as feasibility assessment of prospective installations and system integration analysis of future scenarios, amongst others, can greatly benefit from such methodologies. This paper focuses on the inference of wind speeds for such potential sites using a Bayesian approach to characterise the spatial distribution of the resource. To test the approach, one year of wind speed data from four weather stations was modelled and used to derive inferences for a fifth site. The methodology used is described together with the model employed and simulation results are presented and compared to the data available for the fifth site. The results obtained indicate that Bayesian inference can be a useful tool in spatial characterisation of wind

Estimation of the rock deformation modulus and RMR based on data mining techniques

In this work Data Mining tools are used to develop new and innovative models for the estimation of the rock deformation modulus and the Rock Mass Rating (RMR). A database published by Chun et al. (2008) was used to develop these models. The parameters of the database were the depth, the weightings of the RMR system related to the uniaxial compressive strength (UCS), the rock quality designation (RQD), the joint spacing (JS), the joint condition (JC), the groundwater condition (GWC) and the discontinuity orientation adjustment (DOA), the RMR and the deformation modulus. As a modelling tool the R program environment was used to apply these advanced techniques. Several algorithms were tested and analysed using different sets of input parameters. It was possible to develop new models to predict the rock deformation modulus and the RMR with improved accuracy and, additionally, allowed to have an insight of the importance of the different input parameters.Fundação para a Ciência e a Tecnologia (FCT

Slope stability evaluation. Performance of neural networks versus support vector machines

Neste trabalho são comparados os desempenhos das Redes Neuronais Artificiais (RNA) com as Máquinas de Vetores de Suporte (MVS) na avaliação da estabilidade de taludes. Para isso foi gerada uma base de dados contendo os fatores de segurança (FS) calculados para 501 taludes homogéneos bem como as suas características geométricas e geotécnicas. Os fatores de segurança foram obtidos usando o método de Bishop modificado e o software SLOPE/W. Nas análises efetuadas foi usada a biblioteca RMiner no ambiente R para facilitar o uso deste nas tarefas de classificação e regressão. Para usar aquela tarefa as bases de dados foram ajustadas substituindo o fator de segurança dos taludes por “estável” quando FS é maior ou igual à unidade e “instável” quando FS é menor que 1. Constata-se que tanto as RNA como as MVS apresentam bons desempenhos nas tarefas de regressão e de classificação. No entanto, são as MVS que apresentam os melhores desempenhos nas duas tarefas.This work compares the performances of the Artificial Neural Networks (ANN) with the Support Vector Machines (SVM) in the slope stability evaluation. For this purpose a database containing the factors of safety (FS) computed for 501 homogeneous slopes as well as their geometric and geotechnical characteristics was generated. The factors of safety were obtained using the modified Bishop method and the SLOPE/W software. The analyses were performed using the RMiner library in the R environment to facilitate its use in classification and regression tasks. In the classification task the data were adjusted by replacing the FS for “stable” when FS is greater or equal to 1 and “unstable” when FS is lower than 1. Both ANN and SVM presented good performances in regression and classification tasks. Nevertheless, the SVM had better performance in both tasks

Correlações entre algumas propriedades mecânicas de rochas graníticas com vista à escavação de túneis

A escavação de túneis em maciços rochosos é uma tarefa complexa que requer uma rigorosa caracterização dos mesmos. Essa caracterização envolve a determinação de várias características, nomeadamente a capacidade resistente da rocha e as características de fracturação do maciço. Para avaliar estas características são efectuados ensaios e o levantamento da orientação e espaçamento das diacláses, bem como o material de enchimento das mesmas. No presente trabalho, para avaliar a capacidade resistente de rochas graníticas, foram usados resultados de ensaios de compressão uniaxial, de carga pontual e com o esclerómetro de Schmidt. Foram estabelecidas correlações quer entre os parâmetros de resistência obtidos nestes ensaios quer entre esses parâmetros e o módulo de elasticidade. Foram obtidas boas correlações entre os parâmetros envolvidos.The excavation of tunnels in rock masses is a complex task that requires its accurate characterization. This characterization involves the determination of several characteristics, mainly the rock strength and the rock mass fracturation. To evaluate these characteristics, tests are performed and the orientation and joint spacing, as well as the filling material are surveyed. In this work, to evaluate the strength of granitic rocks results of uniaxial compression test, point load test and Schmidt hammer test were used. Correlations were established both between the strength parameters and between these parameters and the modulus of elasticity. Good correlations were obtained between the involved parameters