Variación de las características mecánicas de armaduras de alta ductilidad B500SD en función de su grado de corrosión / Mechanical properties variation of B500SD high ductility reinforcement regarding its corrosion degree

Los efectos de la corrosión sobre las armaduras se manifiestan por la pérdida de sección y la variación de las propiedades mecánicas relacionadas con la ductilidad. En este trabajo se han ensayado a tracción 96 barras de acero B500SD que previamente se han sometido a niveles variables de corrosión. Los resultados muestran que los alargamientos de las barras disminuyen y el cociente entre la tensión máxima y el límite elástico aumenta conforme el nivel de corrosión avanza. A partir del estudio del efecto de entalla y de la distinta constitución metalográfica del acero a nivel de sección debido a su procedimiento de fabricación se pueden explicar los fenómenos anteriores.

A level II reliability approach to tunnel support design

A reliability approach to tunnel support design is presented in this paper. The aim of the work is the incorporation of classical Level II techniques to the current design method based on the study of the ground-support interaction diagram.

Components of a Wind Tunnel Balance: Design and Calibration

Components of a Wind Tunnel Balance: Design and Calibration

Measurement of Distributed Antenna Systems at 2.4 GHz in a Realistic Subway Tunnel Environment.

Accurate characterization of the radio channel in tunnels is of great importance for new signaling and train control communications systems. To model this environment, measurements have been taken at 2.4 GHz in a real environment in Madrid subway. The measurements were carried out with four base station transmitters installed in a 2-km tunnel and using a mobile receiver installed on a standard train. First, with an optimum antenna configuration, all the propagation characteristics of a complex subway environment, including near shadowing, path loss,shadow fading, fast fading, level crossing rate (LCR), and average fade duration (AFD), have been measured and computed. Thereafter, comparisons of propagation characteristics in a double-track tunnel (9.8-m width) and a single-track tunnel (4.8-m width) have been made. Finally, all the measurement results have been shown in a complete table for accurate statistical modeling.

Performance analysis of AlGaAs/GaAs tunnel junctions for ultra-high concentration photovoltaics

An n(++)-GaAs/p(++)-AlGaAs tunnel junction with a peak current density of 10 100Acm(-2) is developed. This device is a tunnel junction for multijunction solar cells, grown lattice-matched on standard GaAs or Ge substrates, with the highest peak current density ever reported. The voltage drop for a current density equivalent to the operation of the multijunction solar cell up to 10 000 suns is below 5 mV. Trap-assisted tunnelling is proposed to be behind this performance, which cannot be justified by simple band-to-band tunnelling. The metal-organic vapour-phase epitaxy growth conditions, which are in the limits of the transport-limited regime, and the heavy tellurium doping levels are the proposed origins of the defects enabling trap-assisted tunnelling. The hypothesis of trap-assisted tunnelling is supported by the observed annealing behaviour of the tunnel junctions, which cannot be explained in terms of dopant diffusion or passivation. For the integration of these tunnel junctions into a triple-junction solar cell, AlGaAs barrier layers are introduced to suppress the formation of parasitic junctions, but this is found to significantly degrade the performance of the tunnel junctions. However, the annealed tunnel junctions with barrier layers still exhibit a peak current density higher than 2500Acm(-2) and a voltage drop at 10 000 suns of around 20 mV, which are excellent properties for tunnel junctions and mean they can serve as low-loss interconnections in multijunction solar cells working at ultra-high concentrations.

Co-evolutionary and Reinforcement Learning Techniques Applied to Computer Go players

The objective of this thesis is model some processes from the nature as evolution and co-evolution, and proposing some techniques that can ensure that these learning process really happens and useful to solve some complex problems as Go game. The Go game is ancient and very complex game with simple rules which still is a challenge for the Artificial Intelligence. This dissertation cover some approaches that were applied to solve this problem, proposing solve this problem using competitive and cooperative co-evolutionary learning methods and other techniques proposed by the author. To study, implement and prove these methods were used some neural networks structures, a framework free available and coded many programs. The techniques proposed were coded by the author, performed many experiments to find the best configuration to ensure that co-evolution is progressing and discussed the results. Using co-evolutionary learning processes can be observed some pathologies which could impact co-evolution progress. In this dissertation is introduced some techniques to solve pathologies as loss of gradients, cycling dynamics and forgetting. According to some authors, one solution to solve these co-evolution pathologies is introduce more diversity in populations that are evolving. In this thesis is proposed some techniques to introduce more diversity and some diversity measurements for neural networks structures to monitor diversity during co-evolution. The genotype diversity evolved were analyzed in terms of its impact to global fitness of the strategies evolved and their generalization. Additionally, it was introduced a memory mechanism in the network neural structures to reinforce some strategies in the genes of the neurons evolved with the intention that some good strategies learned are not forgotten. In this dissertation is presented some works from other authors in which cooperative and competitive co-evolution has been applied. The Go board size used in this thesis was 9x9, but can be easily escalated to more bigger boards.The author believe that programs coded and techniques introduced in this dissertation can be used for other domains.

Extended description of tunnel junctions for distributed modeling of concentrator multi-junction solar cells

One of the key components of highly efficient multi-junction concentrator solar cells is the tunnel junction interconnection. In this paper, an improved 3D distributed model is presented that considers real operation regimes in a tunnel junction. This advanced model is able to accurately simulate the operation of the solar cell at high concentraions at which the photogenerated current surpasses the peak current of the tunnel junctionl Simulations of dual-junction solar cells were carried out with the improved model to illustrate its capabilities and the results have been correlated with experimental data reported in the literature. These simulations show that under certain circumstances, the solar cells short circuit current may be slightly higher than the tunnel junction peak current without showing the characteristic dip in the J-V curve. This behavior is caused by the lateral current spreading toward dark regions, which occurs through the anode/p-barrier of the tunnel junction.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Reliability of tunnel liners

The possibility of application of structural reliability theory to the computation of the safety margins of excavated tunnels is presented. After a brief description of the existing procedures the limitations of the safety coefficients such as they usually defined, the proposed limit states are precised as well as the random variables and the applied methodology. Also presented are simple examples, some of them based in actual cases, and to end, some conclusions are established the most important one being the probability of using the method to solve the inverse problem of identification.

Probabilistic Analysis of Tunnel Liners

The use of probabilistic methods to analyse reliability of structures is being applied to a variety of engineering problems due to the possibility of establishing the failure probability on rational grounds. In this paper we present the application of classical reliability theory to analyse the safety of underground tunnels.

Design equations for reinforced concrete members strengthened in shear with external FRP reinforcement formulated in an evolutionary multi-objective framework

Methods for predicting the shear capacity of FRP shear strengthened RC beams assume the traditional approach of superimposing the contribution of the FRP reinforcing to the contributions from the reinforcing steel and the concrete. These methods become the basis for most guides for the design of externally bonded FRP systems for strengthening concrete structures. The variations among them come from the way they account for the effect of basic shear design parameters on shear capacity. This paper presents a simple method for defining improved equations to calculate the shear capacity of reinforced concrete beams externally shear strengthened with FRP. For the first time, the equations are obtained in a multiobjective optimization framework solved by using genetic algorithms, resulting from considering simultaneously the experimental results of beams with and without FRP external reinforcement. The performance of the new proposed equations is compared to the predictions with some of the current shear design guidelines for strengthening concrete structures using FRPs. The proposed procedure is also reformulated as a constrained optimization problem to provide more conservative shear predictions.

Reliability of tunnel liners

The possibility of application of structural reliability theory to the computation of the safety margins of excavated tunnels is presented. After a brief description of the existing procedures and the limitations of the safety coefficients such as they are usually defined, the proposed limit states are precised as well as the random variables and the applied methodology. Also presented are simple examples, some of them based in actual cases, and to end, some conclusions are established the most important one being the probability of using the method to solve the inverse problem of identification.

The online case study development for the teaching of building structures reinforcement

The Reinforcement of Building Structures is one of the topics of the Master in Building Innovation Technology (MBIT) of Universidad Politécnica de Madrid (UPM). Since the beginning of the delivery of this master, case studies have been chosen as the teaching methodology. For the 2011-2012 course the online education of this subject was implemented, instead of the classical learning based on attendance. Through ICT’s (Information and Communication Technologies) students are provided with much more and more selective information than through the classical learning. ICT’s can be used for search, enquiries and reporting. Using the online tools has been proved, through the results obtained and based on the surveys made amongst students, to be a successful experience.

An experimental and numerical study of the pattern of cracking of concrete due to steel reinforcement corrosion

In this work, cracking of concrete due to steel reinforcement corrosion is experimentally and numerically studied. The tests combined accelerated corrosion—to generate the cracks—with impregnation under vacuum with resin containing fluorescein—to enhance their visibility under ultraviolet light. In parallel, a model—called expansive joint element—was developed to simulate the expansion of the oxide and finite elements with an embedded adaptable cohesive crack were used to describe concrete cracking. The results show that a good agreement exists between the experimental and numerical crack patterns, which constitutes promising progress towards a comprehensive understanding of corrosion-induced cracking in reinforced concrete.

Evaluating the reinforcement of inorganic fullerene-like nanoparticles in thermoplastic matrices by depth-sensing indentation

The reinforcing effect of inorganic fullerene-like tungsten disulfide (IF-WS2) nanoparticles in two different polymer matrices, isotactic polypropylene (iPP) and polyphenylene sulfide (PPS), has been investigated by means of dynamic depth-sensing indentation. The hardness and elastic modulus enhancement upon filler addition is analyzed in terms of two main contributions: changes in the polymer matrix nanostructure and intrinsic properties of the filler including matrix-particle load transfer. It is found that the latter mainly determines the overall mechanical improvement, whereas the nanostructural changes induced in the polymer matrix only contribute to a minor extent. Important differences are suggested between the mechanisms of deformation in the two nanocomposites, resulting in a moderate mechanical enhancement in case of iPP (20% for a filler loading of 1%), and a remarkable hardness increase in case of PPS (60% for the same filler content). The nature of the polymer amorphous phase, whether in the glassy or rubbery state, seems to play here an important role. Finally, nanoindentation and dynamic mechanical analysis measurements are compared and discussed in terms of the different directionality of the stresses applied.