Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Experimental characterization of the out-of-plane performance of regular stone masonry walls, including test setups and axial load influence

Stone masonry is one of the oldest and most worldwide used building techniques. Nevertheless, the structural response of masonry structures is complex and the effective knowledge about their mechanical behaviour is still limited. This fact is particularly notorious when dealing with the description of their out-of-plane behaviour under horizontal loadings, as is the case of the earthquake action. In this context, this paper describes an experimental program, conducted in laboratory environment, aiming at characterizing the out-of-plane behaviour of traditional unreinforced stone masonry walls. In the scope of this campaign, six full-scale sacco stone masonry specimens were fully characterised regarding their most important mechanic, geometric and dynamic features and were tested resorting to two different loading techniques under three distinct vertical pre-compression states; three of the specimens were subjected to an out-of-plane surface load by means of a system of airbags and the remaining were subjected to an out-of-plane horizontal line-load at the top. From the experiments it was possible to observe that both test setups were able to globally mobilize the out-of-plane response of the walls, which presented substantial displacement capacity, with ratios of ultimate displacement to the wall thickness ranging between 26 and 45 %, as well as good energy dissipation capacity. Finally, very interesting results were also obtained from a simple analytical model used herein to compute a set of experimental-based ratios, namely between the maximum stability displacement and the wall thickness for which a mean value of about 60 % was found.

Metodologias no Controlo de Compactação em Aterros

O presente trabalho pretende abordar aspectos relacionados com o controlo de compactação em aterros, com base na avaliação de parâmetros “in situ”, tais como: pesos volúmicos, teores em água, graus de compactação e módulos de deformabilidade. Recorrendo aos métodos correntes no controlo de compactação, como o ensaio de carga em placa, gamadensímetro, garrafa e ao ensaio de deflectómetro de impacto portátil. Visa-se comparar os resultados obtidos, nas diferentes condições, de modo a possibilitar alcançar correlações entre os ensaios, bem como determinar aqueles que apresentam maior grau de confiança técnico e vantagens operacionais e económicas. De modo a garantir os índices de qualidade da obra é necessário fazer cumprir os critérios exigidos pelo caderno de encargos, nomeadamente nos parâmetros de avaliação do controlo de compactação, para que estas satisfaçam o seu estado funcional e estrutural. Neste tipo de obras os cadernos de encargos de referência em Portugal são os das Estradas de Portigal (EP) e da Brisa, Auto-estradas de Portugal (Brisa), os quais se baseiam em recomendações de classificações de solos. No contexto experimental, foram efectuados dois estudos com condições e materiais diferentes, em obras pertencentes à empresa Mota-Engil Engenharia e Construções, S.A. Nas campanhas de ensaios foram realizados ensaios “in situ” na obra da Subconcessão do Douro Interior – Lote 6 – IC5 – Troço Murça/ Nó de Pombal nas camadas de sub-base e base num agregado de granulometria extensa, e na obra de modernização do troço ferroviário Bombel e Vidigal a Évora, em solos.

Adaptação Cultural e Linguística do Trunk Control Test: avaliação das propriedades psicométricas

Introdução: O controlo postural do tronco é um fator preditivo de autonomia, sendo fundamental a existência de instrumentos válidos e fiáveis a fim da sua avaliação na população portuguesa. Objetivo: Traduzir e adaptar o Trunk Control Test (TCT) para a população portuguesa em indivíduos após AVE e avaliar as suas propriedades psicométricas. Métodos: O TCT foi sujeito aos processos de tradução e retroversão para a população portuguesa por dois tradutores bilingues e realizadas duas reuniões com painel de peritos na área. Avaliou-se a validade, a fiabilidade, a sensibilidade, a especificidade e o poder de resposta em 19 indivíduos com AVE. Para avaliar a validade de critério os indivíduos foram adicionalmente submetidos à Escala de Equilíbrio de Berg (EEB), à Avaliação Motora de Rivermead (AMR) e à Escala de Comprometimento do Tronco (ECT). A fiabilidade inter-observadores foi garantida por uma segunda amostra de 25 fisioterapeutas, através da avaliação do desempenho de um participante no TCT. Os dados foram analisados no programa SPSS 22.0. Resultados: O TCT apresentou baixa consistência interna ( =0,523) e fiabilidade inter-observadores substancial (k=0,662). Obteve-se forte correlação do TCT com a ECT (r=0,885) e AMR (r=0,864), e correlação moderada com a EEB (r=0,700). A validade de construção aponta para uma moderada correlação entre itens (KMO=0,755; Bartlett=0,001). Não foi possível obter os valores de sensibilidade, especificidade e poder de resposta do TCT. Conclusão: O estudo demonstrou que o TCT é um instrumento válido e fiável na avaliação da população portuguesa após AVE.

Kitchen robot prod. line development. Proj. of Bowden cables cutting and thermal forming machine.

This document presents particular description of work done during student’s internship in PR Metal company realized as ERASMUS PROJECT at ISEP. All information including company’s description and its structure, overview of the problems and analyzed cases, all stages of projects from concept to conclusion can be found here. Description of work done during the internship is divided here into two pieces. First part concerns one activities of the company which is robotic chefs (kitchen robot) production line. Work, that was done for development of this line involved several tasks, among them: creating a single-worker montage station for screwing robots housing’s parts, improve security system for laser welding chamber, what particularly consists in designing automatically closing door system with special surface, that protects against destructive action of laser beam, test station for examination of durability of heating connectors, solving problem with rotors vibrations. Second part tells about main task, realized in second half of internship and stands a complete description of machine development and design. The machine is a part of car handle latch cable production line and its tasks are: cutting cable to required length and hot-forming plastic cover for further assembly needs.