Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

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 simulator 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 provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Radiographers practice concerning breast compression in mammography: gradual versus no gradual

Purpose: Evaluate the type of breast compression (gradual or no gradual) that provides less discomfort to the patient. Methods and Materials: The standard projections were simulated [craniocaudal/(CC) and mediolateral-oblique/(MLO)] with the two breast compressions in 90 volunteers women aged between 19 and 86. The women were organised in groups according to the breast density. The intensity of discomfort was evaluated using the scale that have represented several faces (0-10) proposed by Wong Baker in the end of each simulation. It was also applied an interview using focus group to debate the score that were attributed during pain evaluation and to identify the criteria that were considered to do the classification. Results: The women aged between 19-29y (with higher breast density) classified the pain during no gradual compression as 4 and the gradual compression as 2 for both projections. The MLO projection was considered the most uncomfortable. During the focus group interview applied to this group was highlighted that compression did not promoted pain but discomfort. They considered that the high expectations of pain did not correspond to the discomfort that they felt. Similar results were identified for the older women (30-50y; > 50y). Conclusion: The radiographers should considerer the technique for breast compression. The gradual compression was considered for the majority of the women as the most comfortable regardless of breast density. The MLO projection was considered as uncomfortable due to the positioning (axila and inclusion of pectoral muscle) and due to the higher breast compression compared to the CC projection.

Reusability assessment of thermoset polymeric composite wastes as reinforcement and filler replacement for polymer concrete materials

The development and applications of thermoset polymeric composites, namely fiber reinforced polymers (FRP), have shifted in the last decades more and more into the mass market [1]. Production and consume have increased tremendously mainly for the construction, transportation and automobile sectors [2, 3]. Although the many successful uses of thermoset composite materials, recycling process of byproducts and end of lifecycle products constitutes a more difficult issue. The perceived lack of recyclability of composite materials is now increasingly important and seen as a key barrier to the development or even continued used of these materials in some markets.

New end-use application for GFRP recyclates as reinforcement for concrete-polymer materials’

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both: cross-linked nature of thermoset resins, which cannot be remolded, and complex composition of the composite itself, which includes glass fibres, matrix and different types of inorganic fillers. Presently, most of the GFRP waste is landfilled leading to negative environmental impacts and supplementary added costs. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. There are several methods to recycle GFR thermostable materials: (a) incineration, with partial energy recovery due to the heat generated during organic part combustion; (b) thermal and/or chemical recycling, such as solvolysis, pyrolisis and similar thermal decomposition processes, with glass fibre recovering; and (c) mechanical recycling or size reduction, in which the material is subjected to a milling process in order to obtain a specific grain size that makes the material suitable as reinforcement in new formulations. This last method has important advantages over the previous ones: there is no atmospheric pollution by gas emission, a much simpler equipment is required as compared with ovens necessary for thermal recycling processes, and does not require the use of chemical solvents with subsequent environmental impacts. In this study the effect of incorporation of recycled GFRP waste materials, obtained by means of milling processes, on mechanical behavior of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste materials, with distinct size gradings, were incorporated into polyester polymer mortars as sand aggregates and filler replacements. The effect of GFRP waste treatment with silane coupling agent was also assessed. Design of experiments and data treatment were accomplish by means of factorial design and analysis of variance ANOVA. The use of factorial experiment design, instead of the one-factor-at-a-time method is efficient at allowing the evaluation of the effects and possible interactions of the different material factors involved. Experimental results were promising toward the recyclability of GFRP waste materials as aggregates and filler replacements for polymer mortar, with significant gain of mechanical properties with regard to non-modified polymer mortars.

Carbon nanotubes as reinforcement of cellulose liquid crystalline responsive networks

The incorporation of small amount of highly anisotropic nanoparticles into liquid crystalline hydroxypropylcellulose (LC-HPC) matrix improves its response when is exposed to humidity gradients due to an anisotropic increment of order in the structure. Dispersed nanoparticles give rise to faster order/disorder transitions when exposed to moisture as it is qualitatively observed and quantified by stress-time measurements. The presence of carbon nanotubes derives in a improvement of the mechanical properties of LC-HPC thin films.

Text classification using compression-based dissimilarity measures

Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Experimental Reinforcement of Wood Beams

Rehabilitation is becoming more and more usual in the construction sector in Portugal. The introduction of newer construction materials and technical know-how of integrating different materials for achieving desired engineering goals is an important step to the development of the sector. Wood industry is also getting more and more adapted to composite technologies with the introduction of the so called “highly engineered wood products” and with the use of modification treatments. This work is an attempt to explain the viability of using stainless steel and glass fibre reinforced polymer (GFRP) as reinforcements in wood beams. This thesis specifically focuses on the flexural behaviour of Portuguese Pine unmodified and modified wood beams. Two types of modification were used: 1,3-dimethylol-4,5- dihydroxyethyleneurea (DMDHEU) resin and amid wax. The behaviour of the material was analysed with a nonlinear model. The latter model simulates the behaviour of the reinforced wood beams under flexural loading. Small-scale beams (1:15) were experimented in flexural bending and the experimental results obtained were compared with the analytical model results. The experiments confirm the viability of the reinforcing schemes and the working procedures. Experimental results showed fair agreement with the nonlinear model. A strength increase between 15% and 80% was achieved. Stiffness increased by 40% to 50% in beams reinforced with steel but no significant increase was achieved with the glass fibre reinforcement.

TEA: Timing and Energy Aware compression architecture for Efficient Configuration in CGRAs

Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

Hierarchical Reinforcement Learning in Behavior and the Brain

Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience

Optimisation and design of post-tensioning anchorage corner blisters in concrete box girder bidges

The design of anchorage blisters of internal continuity post-tensioning tendons of bridges built by the cantilever method, presents some peculiarities, not only because they are intermediate anchorages but also because these anchorages are located in blisters, so the prestressing force has to be transferred from the blister the bottom slab and web of the girder. The high density of steel reinforcement in anchorage blisters is the most common reason for problems with concrete cast in situ, resulting in zones with low concrete compacity, leading to concrete crushing failures under the anchor plates. A solution may involve improving the concrete compression and tensile strength. To meet these requirements a high-performance fibre reinforced self-compacting mix- ture (HPFRC) was used in anchorage corner blisters of post-tensioning tendons, reducing the concrete cross-section and decreasing the reinforcement needed. To assess the ultimate capacity and the adequate serviceability of the local anchorage zone after reducing the minimum concrete cross-section and the confining reinforcement, specified by the anchorage device supplier for the particular tendon, load transfer tests were performed. To investigate the behaviour of anchorage blisters regarding the transmission of stresses to the web and the bottom slab of the girder, and the feasibility of using high performance concrete only in the blister, two half scale models of the inferior corner of a box girder existing bridge were studied: a reference specimen of ordinary reinforced concrete and a HPFRC blister specimen. The design of the reinforcement was based in the tensile forces obtained on strut-and-tie models. An experimental program was carried out to assess the models used in design and to study the feasibility of using high performance concrete only in the blister, either with casting in situ, or with precast solutions. A non-linear finite element analysis of the tested specimens was also performed and the results compared.

Design formula for the flexural strengthening of RC beams using prestressed CFRP reinforcement

Applying a certain prestress level to the carbon fiber reinforced polymer (CFRP) reinforcement according to either externally bonded reinforcing (EBR) or near surface mounted (NSM) techniques can mobilize the strengthening potentialities of this high tensile strength composite material. For the prediction of the flexural behavior of reinforced concrete (RC) structures strengthened with prestressed EBR or NSM CFRPs, however, simplified analytical and design formulations still need to be developed as a guidance for engineers to design this type of strengthened structures by hand calculation without any programming help. Hence, the current work aims to briefly explain a developed simplified analytical approach, with a design framework, to predict the flexural behavior of RC beams flexurally strengthened with either prestressed EBR or NSM CFRP reinforcements. Moreover, an upper limit for the prestress level is proposed in order to optimize the ductility performance of the NSM prestressing technique. The good predictive performance of the analytical approaches was appraised by simulating the results of experimental programs composed of RC beams strengthened with prestressed NSM CFRP reinforcements.

High performance fiber reinforced concrete for the shear reinforcement: experimental and numerical research

High performance fiber reinforced concrete (HPFRC) is developing rapidly to a modern structural material with unique rheological and mechanical characteristics. Despite applying several methodologies to achieve self15 compacting requirements, some doubts still remain regarding the most convenient strategy for developing a HPFRC. In the present study, an innovative mix design method is proposed for the development of high17 performance concrete reinforced with a relatively high dosage of steel fibers. The material properties of the developed concrete are assessed, and the concrete structural behavior is characterized under compressive, flexural and shear loading. This study better clarifies the significant contribution of fibers for shear resistance of concrete elements. This paper further discusses a FEM-based simulation, aiming to address the possibility of calibrating the constitutive model parameters related to fracture modes I and II.

Assessment of the effectiveness of steel fibre reinforcement for the punching resistance of flat slabs by experimental research and design approach

The present paper deals with the experimental assessment of the effectiveness of steel fibre reinforcement in terms of punching resistance of centrically loaded flat slabs, and to the development of an analytical model capable of predicting the punching behaviour of this type of structures. For this purpose, eight slabs of 2550 x 2550 x 150 mm3 dimensions were tested up to failure, by investigating the influence of the content of steel fibres (0, 60, 75 and 90 kg/m3) and concrete strength class (50 and 70 MPa). Two reference slabs without fibre reinforcement, one for each concrete strength class, and one slab for each fibre content and each strength class compose the experimental program. All slabs were flexurally reinforced with a grid of ribbed steel bars in a percentage to assure punching failure mode for the reference slabs. Hooked ends steel fibres provided the unique shear reinforcement. The results have revealed that steel fibres are very effective in converting brittle punching failure into ductile flexural failure, by increasing both the ultimate load and deflection, as long as adequate fibre reinforcement is assured. An analytical model was developed based on the most recent concepts proposed by the fib Mode Code 2010 for predicting the punching resistance of flat slabs and for the characterization of the behaviour of fibre reinforced concrete. The most refined version of this model was capable of predicting the punching resistance of the tested slabs with excellent accuracy and coefficient of variation of about 5%.

A model to simulate the moment-rotation and crack width of FRC members reinforced with longitudinal bars

The present work describes a model for the determination of the moment–rotation relationship of a cross section of fiber reinforced concrete (FRC) elements that also include longitudinal bars for the flexural reinforcement (R/FRC). Since a stress–crack width relationship (σ–w)(σ–w) is used to model the post-cracking behavior of a FRC, the σ–w directly obtained from tensile tests, or derived from inverse analysis applied to the results obtained in three-point notched beam bending tests, can be adopted in this approach. For a more realistic assessment of the crack opening, a bond stress versus slip relationship is assumed to simulate the bond between longitudinal bars and surrounding FRC. To simulate the compression behavior of the FRC, a shear friction model is adopted based on the physical interpretation of the post-peak compression softening behavior registered in experimental tests. By allowing the formation of a compressive FRC wedge delimited by shear band zones, the concept of concrete crushing failure mode in beams failing in bending is reinterpreted. By using the moment–rotation relationship, an algorithm was developed to determine the force–deflection response of statically determinate R/FRC elements. The model is described in detail and its good predictive performance is demonstrated by using available experimental data. Parametric studies were executed to evidence the influence of relevant parameters of the model on the serviceability and ultimate design conditions of R/FRC elements failing in bending.