Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.

A review of rhizosphere carbon flow modelling

Rhizosphere processes play a key role in nutrient cycling in terrestrial ecosystems. Plant rhizodeposits supply low-molecular weight carbon substrates to the soil microbial community, resulting in elevated levels of activity surrounding the root. Mechanistic compartmental models that aim to model carbon flux through the rhizosphere have been reviewed and areas of future research necessary to better calibrate model parameters have been identified. Incorporating the effect of variation in bacterial biomass physiology on carbon flux presents a considerable challenge to experimentalists and modellers alike due to the difficulties associated with differentiating dead from dormant cells. A number of molecular techniques that may help to distinguish between metabolic states of bacterial cells are presented. The calibration of growth, death and maintenance parameters in rhizosphere models is also discussed. A simple model of rhizosphere carbon flow has been constructed and a sensitivity analysis was carried out on the model to highlight which parameters were most influential when simulating carbon flux. It was observed that the parameters that most heavily influenced long-term carbon compartmentalisation in the rhizosphere were exudation rate and biomass yield. It was concluded that future efforts to simulate carbon flow in the rhizosphere should aim to increase ecological realism in model structure.

Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

Hidden Markov Models With Set-Valued Parameters

Hidden Markov models (HMMs) are widely used probabilistic models of sequential data. As with other probabilistic models, they require the specification of local conditional probability distributions, whose assessment can be too difficult and error-prone, especially when data are scarce or costly to acquire. The imprecise HMM (iHMM) generalizes HMMs by allowing the quantification to be done by sets of, instead of single, probability distributions. iHMMs have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. In this paper, we consider iHMMs under the strong independence interpretation, for which we develop efficient inference algorithms to address standard HMM usage such as the computation of likelihoods and most probable explanations, as well as performing filtering and predictive inference. Experiments with real data show that iHMMs produce more reliable inferences without compromising the computational efficiency.

Modelling the fresh properties of self-compacting concrete using support vector machine approach

The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.

Techno-Economic Feasibility of Selective CO2 Capture Processes from Biogas Streams using Ionic Liquids as Physical Absorbents

Biogas from anaerobic digestion of sewage sludge is a renewable resource with high energy content, which is formed mainly of CH4 (40-75 vol.%) and CO2 (15-60 vol.%) Other components such as water (H2O, 5-10 vol.%) and trace amounts of hydrogen sulfide and siloxanes can also be present. A CH4-rich stream can be produced by removing the CO2 and other impurities so that the upgraded bio-methane can be injected into the natural gas grid or used as a vehicle fuel. The main objective of this paper is to develop a new modeling methodology to assess the technical and economic performance of biogas upgrading processes using ionic liquids which physically absorb CO2. Three different ionic liquids, namely the 1-ethyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide, 1-hexyl-3-methylimidazoliumbis[(trifluoromethyl)sulfonyl]imide and trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)sulfonyl]imide, are considered for CO2 capture in a pressure-swing regenerative absorption process. The simulation software Aspen Plus and Aspen Process Economic Analyzer is used to account for mass and energy balances as well as equipment cost. In all cases, the biogas upgrading plant consists of a multistage compressor for biogas compression, a packed absorption column for CO2 absorption, a flash evaporator for solvent regeneration, a centrifugal pump for solvent recirculation, a pre-absorber solvent cooler and a gas turbine for electricity recovery. The evaluated processes are compared in terms of energy efficiency, capital investment and bio-methane production costs. The overall plant efficiency ranges from 71-86 % whereas the bio-methane production cost ranges from £6.26-7.76 per GJ (LHV). A sensitivity analysis is also performed to determine how several technical and economic parameters affect the bio-methane production costs. The results of this study show that the simulation methodology developed can predict plant efficiencies and production costs of large scale CO2 capture processes using ionic liquids without having to rely on gas solubility experimental data.

Contribution to the study of the Ria de Aveiro inlet morphodynamics

Over the years it was observed at the Ria de Aveiro lagoon inlet, near the head of the north breakwater, a depth increase that might threaten the stability of this structure. A trend of accretion in the navigation channel of this lagoon is observed, endangering the navigation in this region. In order to understand the origin of these and other trends observed, the knowledge of the sediment transport in the study area is imperative. The main aim of this work is understanding the dominant physical processes in the sediment transport of sediment at the Ria de Aveiro lagoon inlet and adjacent area, improving knowledge of this region morphodynamics. The methodology followed in this study consisted in the analyzes of the topohydrographic surveys performed by the Administration of the Aveiro Harbor, and in the numerical simulations results performed with the morphodynamic modeling system MORSYS2D. The analysis of the surveys was performed by studying the temporal evolution of the bathymetry. The numerical analysis was based on the implementation of the model at the study area, sensitivity analysis of the formulations used to compute the sediment transport to the variation of input parameters (e.g. depth, sediment size, tidal currents) and analysis of the sediment uxes and bathymetric changes predicted. The simulations considered as sediment transport forcing the tidal currents only and the coupled forcing of tides and waves. Considering the wave e ect as sediment transport forcing, both monochromatic waves and a wave regime were simulated. The results revealed that the observed residual sediment transport patterns are generated due to the channel con guration. Inside the lagoon the uxes are mainly induced by the tidal currents action, restricting the action of waves to the inlet and adjacent coast. In the navigation channel the residual sediment uxes predicted are directed o - shore with values between 7 and 40 m3=day generating accretions of approximately 10 m3=day for the shallower region and 35 m3=day for the region between the tidal gauge and the tri^angulo das mar es. At the inlet, the residual uxes are approximately 30 m3=day inducing trends of erosion of approximately 20 m3=day. At the North side of the nearshore accretion is predicted, while at the South side is predicted erosion, at the rates of 250 and 1500 m3=day, respectively. It was also concluded that the waves with higher contribution to the residual sediment uxes are those with heights between 4 and 5 m. However, the storm waves with heights bigger than 5 m, despite their 10% of frequency of occurrence are responsible for 25% of the observed sediment transport.

Effects of the climatic factors and anthropogenic actions in the Ria de Aveiro

A compreensão dos impactes das alterações climáticas é fundamental para a gestão a longo do prazo dos ecossistemas estuarinos. Esta compreensão só poderá ser efectiva considerando a variabilidade climática natural e o papel relativo das intervenções antropogénicas nestes ecossistemas. Assim, a presente dissertação analisa a influência das alterações climáticas e pressões antropogénicas na qualidade da água e dinâmica ecológica da Ria de Aveiro com base numa abordagem integrada, que combinou a análise de séries temporais dos últimos 25 anos e a modelação numérica de elevada resolução de cenários futuros de alterações climáticas e intervenções antropogénicas. A componente de modelação de qualidade da água e ecológica foi melhorada a vários níveis. A análise de sensibilidade do modelo 3D hidrodinâmicoecológico ECO-SELFE aplicado à Ria de Aveiro e a revisão das constantes de semi-saturação para absorção de nutrientes pelo fitoplâncton contribuíram para a precisão e robustez das aplicações. A concentração do fitoplâncton foi significativamente influenciada pelas taxas de crescimento do fitoplâncton e de mortalidade e excreção do zooplâncton, e apresentou uma sensibilidade reduzida à variação das constantes de semi-saturação na gama identificada para as diatomáceas. O acoplamento do ECO-SELFE a um modelo de campo próximo e a integração do ciclo do oxigénio aumentaram a sua capacidade de representação dos processos e das escalas espaciais relevantes. A validação do ECO-SELFE foi realizada com base num conjunto de campanhas específicas realizadas no canal de Mira. Os padrões espaciais e temporais observados para as várias variáveis (clorofila a, nutrientes, oxigénio dissolvido, salinidade, temperatura da água, correntes e níveis) foram simulados com erros menores ou semelhantes aos obtidos neste tipo de aplicações. A análise dos padrões de variabilidade espacial e temporal da qualidade da água e ecológica na Ria de Aveiro a diferentes escalas, efectuada com base nos dados históricos de 1985 a 2010 complementados pelas campanhas realizadas, sugeriu uma influência combinada da variabilidade climática e das acções antropogénicas. Os cenários futuros de alterações climáticas e intervenções antropogénicas simulados evidenciaram uma influência mais significativa das alterações climáticas quando comparadas com os efeitos das acções antropogénicas analisadas. As variações mais significativas são previstas para os cenários de subida do nível do mar, seguidos dos cenários de alterações dos regimes hidrológicos, evidenciando o papel da circulação (maré e caudal fluvial) no estabelecimento da qualidade da água e dinâmica ecológica na laguna. Para os cenários de subida do nível do mar são previstos decréscimos significativos da clorofila a e dos nutrientes a jusante e nas zonas intermédias do canal, e um aumento significativo da salinidade a montante. Estas alterações poderão favorecer modificações da composição e distribuição das comunidades, afectando a cadeia alimentar e causando uma progressão para montante de espécies marinhas. Os resultados sugerem ainda que os efeitos poderão ser mais significativos em estuários pouco profundos.

Descarga costeira de águas subterrâneas com elevado conteúdo em nitratos para a Ria Formosa

Dissertação de Mestrado, Estudos Marinhos e Costeiros, Faculdade de Ciências do Mar e Ambiente, Universidade do Algarve, 2007

Landslide susceptibility evaluation and validation at a regional scale

Tese de doutoramento, Geografia (Geografia Física), Universidade de Lisboa, Instituto de Geografia e Ordenamento do Território, 2014

Comparison of allocation approaches in soybean biodiesel life cycle assessment

This work shows the influence of using different allocation approaches when modelling the inventory analysis in a soybean biodiesel life cycle assessment (LCA). Results obtained using mass, energy and economic based allocations are compared, focusing on the following aspects: normalised potential environmental impact (PEI) categories, total PEI and relative contributions to the total PEI from each life cycle stage and environmental impact category. Similar results are obtained either using economic and energy based allocations. However, different results are obtained when mass based allocation is used when compared with the other two. This study also illustrates that using different allocation approaches in biodiesel LCA may influence the final conclusions, especially in comparative assertions, emphasising the need to perform a sensitivity analysis in the LCA interpretation step.

Reabilitação de um imóvel industrial em Marvila: projeto de investimento

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil

Self-Scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach

This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

Projecto de investimento imobiliário no edifício residencial no Estoril

Trabalho de Projecto para obtenção do grau de Mestre em Engenharia Civil

Forças em estruturas de acostagem descontínuas em zonas desabrigadas: avaliação de ferramentas de cálculo existentes

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de especialização em Hidráulica