A Flexible Architecture for the Computation of Direct and Inverse Transforms in H.264/AVC Video Codecs

A new high throughput and scalable architecture for unified transform coding in H.264/AVC is proposed in this paper. Such flexible structure is capable of computing all the 4x4 and 2x2 transforms for Ultra High Definition Video (UHDV) applications (4320x7680@ 30fps) in real-time and with low hardware cost. These significantly high performance levels were proven with the implementation of several different configurations of the proposed structure using both FPGA and ASIC 90 nm technologies. In addition, such experimental evaluation also demonstrated the high area efficiency of theproposed architecture, which in terms of Data Throughput per Unit of Area (DTUA) is at least 1.5 times more efficient than its more prominent related designs(1)

Geomechanical parameters updating in an underground work

In geotechnical engineering, and in the particular case of underground works, a great number of uncertainties arise due to the lack of knowledge of the involved formations and their variability. Geomechanical parameters are one of the main issues in the underground works design. In the initial stages, the available information about the rock masses characteristics is scarce. As the project advances to other stages more and more information from different sources becomes available and can be used for updating the geomechanical model. Bayesian methodologies use probability as the main tool to deal with uncertainty and manage to reduce it using new data via the Bayes theorem. In this work, a part of a developed Bayesian framework to the updating of the deformability modulus (E) in an underground structure is presented. Assuming E as a random variable, data from LFJ tests is used to obtain a posterior and less uncertain distribution of E. This approach led to good results and considerable uncertainty reduction and increased reliability. The developed Bayesian framework constitutes a rational and structured way of dealing with data with different sources and uncertainty levels.Fundação para a Ciência e a Tecnologia (FCT) - projecto POCI/ECM/57495/2004 entitled “Geotechnical Risk inTunnels for High Speed Trains”

Determination of geomechanical parameters in granite formations using a knowledge based system

Nesta comunicação apresenta-se um sistema computacional para a obtenção de parâmetros geomecânicos para a modelação de túneis em formações graníticas. Este sistema, designado GEOPAT, utiliza técnicas de inteligência artificial baseadas em conhecimento (KBS - Knowledge Based System). Para este efeito, estabeleceram-se redes causais, com vista a congregar o conhecimento de especialistas nos domínios das rochas e dos solos em geral e no domínio da engenharia de túneis em particular para o apoio à decisão. O GEOPAT determina os parâmetros para formações rochosas, terrosas e heterogéneas. As interfaces com o utilizador são interactivas e o sistema recorre a plataformas de Visual Basic, KAPPA-PC e Excel.In this paper a computational system for the calculation of geomechanical parameters for tunnels modelling in granite formations is presented. This system called GEOPAT uses artificial intelligence techniques (KBS systems). To congregate the specialists' knowledge in rocks and soils domains and in particular in the tunnel engineering domain causal nets has been established for decision support. GEOPAT determines the parameters for rock masses, soils and heterogeneous rock formations. The interfaces are interactive and the system uses Visual Basic, KAPPA-PC and Excel platforms.Sociedade Portuguesa de Geotecnia (SPG)Associação Brasileira de Mecânica dos Solos e Engenharia GeotécnicaUniversidade de Aveiro. Secção Autónoma de Engenharia Civi

Use of aI techniques and updating in geomechanical characterisation

Fundação para a Ciência e a Tecnologia (FCT) - projecto POCI/ECM/57495/2004 "Geotechnical Risk in Tunnels for High Speed Trains

Determination of geomechanical parameters using a KBS system and application to an underground station

In this paper a KBS computational system, designated by GEOPAT, for the calculation of geomechanical parameters for modelling underground structures in rock and soil formations is presented. To congregate the specialists' knowledge in rock and soil domains, and in particular in the tunnel engineering, causal nets have been established for decision support. GEOPAT determines the parameters for rock and soil formations, as well as heterogeneous rock formations. The developed GEOPAT system was applied to a large underground station in urban environment, excavated in granite formations, in order to obtain the deformability and strength parameters of the surrounding rock masses. Numerical models were developed considering either the obtained geomechanical parameters using artificial intelligence techniques or the parameters used in design. The numerical results obtained with the two sets of parameters are compared, as well as with the monitoring results. Some conclusions are drawn

Determinação de parâmetros geomecânicos em formações rochosas e maciços heterogéneos

Neste trabalho apresentam-se metodologias desenvolvidas para a obtenção de parâmetros geomecânicos em formações rochosas, incluindo-se a situação de maciços heterogéneos. No caso das formações rochosas, a quantificação desses parâmetros é analisada com base nos principais ensaios in situ e de laboratório e com recurso aos sistemas empíricos, com destaque para os sistemas RMR (Rock Mass Rating), Q e GSI (Geological Strength Index). No que se refere aos maciços rochosos claramente heterogéneos como acontece nas formações graníticas da região do Porto, faz-se uma referência às possíveis abordagens do problema, identificando-se, contudo, ainda a necessidade de investigação neste domínio

Prediction of rockburst based on experimental systems and artificial intelligence techniques

Rockburst is characterized by a violent explosion of a certain block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoided andor managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are one of the ways. A description of a system developed at the State Key Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing is described. Also, several cases of rockburst that occurred around the world were collected, stored in a database and analyzed. The analysis of the collected cases allowed one to build influence diagrams, listing the factors that interact and influence the occurrence of rockburst, as well as the relations between them. Data Mining (DM) techniques were also applied to the database cases in order to determine and conclude on relations between parameters that influence the occurrence of rockburst during underground construction. A risk analysis methodology was developed based on the use of Bayesian Networks and applied to the existing information of the database and some numerical applications were performed. Conclusions were established.Fundação para a Ciência e a Tecnologia (FCT

Structural behaviour analysis of Faria Guimarães station

No presente estudo efectua-se a modelação e análise do comportamento estrutural da estação Faria Guimarães, do Metro do Porto. A estação é constituída por um cruzamento oblíquo de duas grandes galerias executadas através do método SEM/NATM. A obra é de elevada complexidade devido aos condicionamentos geométricos da estação e obras adjacentes, à grande heterogeneidade do maciço e à ocupação intensa da superfície. A análise do comportamento estrutural da estação foi realizada recorrendo a modelos numéricos 2D e 3D, bem como a resultados obtidos com a observação da estação.In present paper the modelling and structural behaviour analysis of the Faria Guimarães station, of Metro do Porto, is presented. The station includes the inclined intersection of two large galleries executed through SEM/NATM method. The work is highly complex due to geometric limitations of the station and adjacent works, the heterogeneity of the rock mass and the dense occupation at surface. The structural behaviour analysis of the station was performed using 2D and 3D numerical models, as well as results obtained through the observation of the station.Fundação para a Ciência e Tecnologia (FCT) - Projecto POCI/ECM/57495/2004, intitulado Geotechnical Risk in Tunnels for High Speed Trains

Prediction of geomechanical parameters using a KBS system. Application to two case studies of underground structures

In this paper the knowledge based system called GEOPAT is presented. The system calculates geomechanical parameters for modelling underground structures in rock, soil and heterogeneous formations. Specialists knowledge in this field was congregated and organized in causal nets. GEOPAT is still under developmentand aims to be an important tool for decision support. Nevertheless GEOPAT was already applied to some underground structures with success. In this work two of these applications are presented. The first is a largeunderground station of Metro of Porto and the last is the powerhouse complex composed by two caverns ofthe Venda Nova II hydroelectric scheme. Both structures were built in a granite rock mass. The geomechani-cal parameters were obtained using GEOPAT based on some information gathered in the field. Numerical models were developed and the results were compared with the monitored values. They showed in general a good agreement however it is still necessary to improve and increase the knowledge inside the system