Experimental and numerical approaches for structural assessment in new footbridge designs (SFRSCC–GFPR hybrid structure)

Within the civil engineering field, the use of the Finite Element Method has acquired a significant importance, since numerical simulations have been employed in a broad field, which encloses the design, analysis and prediction of the structural behaviour of constructions and infrastructures. Nevertheless, these mathematical simulations can only be useful if all the mechanical properties of the materials, boundary conditions and damages are properly modelled. Therefore, it is required not only experimental data (static and/or dynamic tests) to provide references parameters, but also robust calibration methods able to model damage or other special structural conditions. The present paper addresses the model calibration of a footbridge bridge tested with static loads and ambient vibrations. Damage assessment was also carried out based on a hybrid numerical procedure, which combines discrete damage functions with sets of piecewise linear damage functions. Results from the model calibration shows that the model reproduces with good accuracy the experimental behaviour of the bridge.

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

A multi-criteria decision support system for a routing problem in waste collection

Autor proof

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Numerical Assessment of the out-of-plane response of a brick masonry structure without box behaviour

This paper presents the assessment of the out-of-plane response due to seismic loading of a masonry structure without rigid diaphragm. This structure corresponds to real scale brick masonry specimen with a main façade connected to two return walls. Two modelling approaches were defined for this evaluation. The first one consisted on macro modelling, whereas the second one on simplified micro modelling. As a first step of this study, static nonlinear analyses were conducted to the macro model aiming at evaluating the out-of-plane response and failure mechanism of the masonry structure. A sensibility analyses was performed in order to assess the mesh size and material model dependency. In addition, the macro models were subjected to dynamic nonlinear analyses with time integration in order to assess the collapse mechanism. Finally, these analyses were also applied to a simplified micro model of the masonry structure. Furthermore, these results were compared to experimental response from shaking table tests. It was observed that these numerical techniques simulate correctly the in-plane behaviour of masonry structures. However, the

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

Structure-property relationships in polymer nanocomposites

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Relationship between galactomannan structure and physicochemical properties of films produced thereof

In this work five sources of galactomannans, Adenanthera pavonina, Cyamopsis tetragonolobus, Caesalpinia pulcherrima, Ceratonia siliqua and Sophora japonica, presenting mannose/galactose ratios of 1.3, 1.7, 2.9, 3.4 and 5.6, respectively, were used to produce galactomannan-based films. These films were characterized in terms of: water vapour, oxygen and carbon dioxide permeabilities (WVP, O 2 P and CO 2 P); moisture content, water solubility, contact angle, elongation-at-break (EB), tensile strength (TS) and glass transition temperature (T g ). Results showed that films properties vary according to the galactomannan source (different galactose distribution) and their mannose/galactose ratio. Water affinity of mannan and galactose chains and the intermolecular interactions of mannose backbone should also be considered being factors that affect films properties. This work has shown that knowing mannose/galactose ratio of galactomannans is possible to foresee galactomannan-based edible films properties.

Influence of glucose concentration on the structure and quantity of biofilms formed by Candida parapsilosis

Candida parapsilosis is nowadays an emerging opportunistic pathogen and its increasing incidence is part related to the capacity to produce biofilm. In addition, one of the most important C. parapsilosis pathogenic risk factors includes the organisms\textquoteright selective growth capabilities in hyper alimentation solutions. Thus, in this study, we investigated the role of glucose in C. parapsilosis biofilm modulation, by studying biofilm formation, matrix composition and structure. Moreover, the expression of biofilm-related genes (BCR1, FKS1 and OLE1) were analyzed in the presence of different glucose percentages. The results demonstrated the importance of glucose in the modulation of C. parapsilosis biofilm. The concentration of glucose had direct implications on the C. parapsilosis transition of yeast cells to pseudohyphae. Additionally, it was demonstrated that biofilm related genes BCR1, FKS1 and OLE1 are involved in biofilm modulation by glucose. The mechanism by which glucose enhances biofilm formation is not fully understood, however with this study we were able to demonstrate that C. parapsilosis respond to stress conditions caused by elevated levels of glucose by up-regulating genes related to biofilm formation (BCR1, FKS1 and OLE1).

Structure-properties relationships in thermoplastic polyurethane elastomer nanocomposites: Interactions between polymer phases and nanofillers

Polyurethane thermoplastic elastomer (TPU) nanocomposites were prepared by the incorporation of 1 wt% of high-structured carbon black (HSCB), carbon nanofibers (CNF), nanosilica (NS) and nanoclays (NC), following a proper high-shear blending procedure. The TPU nanofilled mechanical properties and morphology was assessed. The nanofillers interact mainly with the TPU hard segments (HS) domains, determining their glass transition temperature, and increasing their melting temperature and enthalpy. A significant improvement upon the modulus, sustained stress levels and deformation capabilities is evidenced. The relationships between the morphology and the nanofilled TPU properties are established, evidencing the role of HS domains on the mechanical response, regardless the nanofiller type.

Effect of butadiene/styrene ratio, block structure and carbon nanotube content on the mechanical and electrical properties of thermoplastic elastomers after UV ageing

Thermoplastic elastomers based on a triblock copolymer styrene-butadiene-styrene (SBS) with different butadiene/styrene ratios, block structure and carbon nanotube (CNT) content were submitted to accelerated weathering in a Xenontest set up, in order to evaluate their stability to UV ageing. It was concluded that ageing mainly depends on butadiene/styrene ratio and block structure, with radial block structures exhibiting a faster ageing than linear block structures. Moreover, the presence of carbon nanotubes in the SBS copolymer slows down the ageing of the copolymer. The evaluation of the influence of ageing on the mechanical and electrical properties demonstrates that the mechanical degradation is higher for the C401 sample, which is the SBS sample with the largest butadiene content and a radial block structure. On the other hand, a copolymer derivate from SBS, the styrene-ethylene/butadiene-styrene (SEBS) sample, retains a maximum deformation of ~1000% after 80 h of accelerated ageing. The hydrophobicity of the samples decreases with increasing ageing time, the effect being larger for the samples with higher butadiene content. It is also verified that cytotoxicity increases with increasing UV ageing with the exception of SEBS, which remains not cytotoxic up to 80 h of accelerated ageing time, demonstrating its potential for applications involving exposition to environmental conditions.

Mechanical fatigue performance of PCL-chondroprogenitor constructs after cell culture under bioreactor mechanical stimulus

In tissue engineering of cartilage, polymeric scaffolds are implanted in the damaged tissue and subjected to repeated compression loading cycles. The possibility of failure due to mechanical fatigue has not been properly addressed in these scaffolds. Nevertheless, the macroporous scaffold is susceptible to failure after repeated loading-unloading cycles. This is related to inherent discontinuities in the material due to the micropore structure of the macro-pore walls that act as stress concentration points. In this work, chondrogenic precursor cells have been seeded in Poly-ε-caprolactone (PCL) scaffolds with fibrin and some were submitted to free swelling culture and others to cyclic loading in a bioreactor. After cell culture, all the samples were analyzed for fatigue behavior under repeated loading-unloading cycles. Moreover, some components of the extracellular matrix (ECM) were identified. No differences were observed between samples undergoing free swelling or bioreactor loading conditions, neither respect to matrix components nor to mechanical performance to fatigue. The ECM did not achieve the desired preponderance of collagen type II over collagen type I which is considered the main characteristic of hyaline cartilage ECM. However, prediction in PCL with ECM constructs was possible up to 600 cycles, an enhanced performance when compared to previous works. PCL after cell culture presents an improved fatigue resistance, despite the fact that the measured elastic modulus at the first cycle was similar to PCL with poly(vinyl alcohol) samples. This finding suggests that fatigue analysis in tissue engineering constructs can provide additional information missed with traditional mechanical measurements.

Effect of surface plasmon resonance in TiO2/Au thin films on the fluorescence of self-assembled CdTe QDs structure

The exceptional properties of localised surface plasmons (LSPs), such as local field enhancement and confinement effects, resonant behavior, make them ideal candidates to control the emission of luminescent nanoparticles. In the present work, we investigated the LSP effect on the steady-state and time-resolved emission properties of quantum dots (QDs) by organizing the dots into self-assembled dendrite structures deposited on plasmonic nanostructures. Self-assembled structures consisting of water-soluble CdTe mono-size QDs, were developed on the surface of co-sputtered TiO2 thin films doped with Au nanoparticles (NPs) annealed at different temperatures. Their steady-state fluorescence properties were probed by scanning the spatially resolved emission spectra and the energy transfer processes were investigated by the fluorescence lifetime imaging (FLIM) microscopy. Our results indicate that a resonant coupling between excitons confined in QDs and LSPs in Au NPs located beneath the self-assembled structure indeed takes place and results in (i) a shift of the ground state luminescence towards higher energies and onset of emission from excited states in QDs, and (ii) a decrease of the ground state exciton lifetime (fluorescence quenching).