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.

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.

Análisis mecánico de albañilería arqueológica de adobe bajo cargas de compresión uniaxial: El caso de Huaca de la Luna

This article presents an experimental and numerical study for the mechanical characterization under uniaxial compressive loading of the adobe masonry of one of the most emblematic archaeological complex in Peru, 'Huaca de la Luna' (100-650AD). Compression tests of prisms were carried out with original material brought to the laboratory. For measuring local deformations in the tests, displacement transducers were used which were complemented by a digital image correlation system which allowed a better understanding of the failure mechanism. The tests were then numerically simulated by modelling the masonry as a continuum media. Several approaches were considered concerning the geometrical modelling, namely 2D and 3D simplified models, and 3D refined models based on a photogrammetric reconstruction. The results showed a good approximation between the numerical prediction and the experimental response in all cases. However, the 3D models with irregular geometries seem to reproduce better the cracking pattern observed in the tests.

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.

Experimental analysis of the cyclic response of traditional timber joints and their influence on the seismic capacity of timber frame structures

Timber connections represent the crucial part of a timber structure and a great variability exists in terms of types of connections and mechanisms. Taking as case study the widespread traditional timber frame structures, in particular the Portuguese Pombalino buildings, one of the most common timber connection is the half-lap joint. Connections play a major role in the overall behaviour of a structure, particularly when assessing their seismic response, since damage is concentrated at the connections. For this reason, an experimental campaign was designed and distinct types of tests were carried out on traditional half-lap joints to assess their in-plane response. In particular, pull-out and in-plane cyclic tests were carried out on real scale unreinforced connections. Subsequently, the connections were retrofitted, using strengthening techniques such as self-tapping screws, steel plates and GFRP sheets. The tests chosen were meant to capture the hysteretic behaviour and dissipative capacity of the connections and characterise their response and, therefore, their influence on the seismic response of timber frame walls, particularly concerning their uplifting and rotation capacity, that could lead to rocking in the walls. In this paper, the results of the experimental campaign are presented in terms of hysteretic curves, dissipated energy and equivalent viscous damping ratio. Moreover, recommendations are provided on the most appropriate retrofitting solutions.

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

Effect of environmental ageing on the numerical response of FRP-strengthened masonry walls

Recent durability studies have shown the susceptibility of bond in fiber-reinforced polymer (FRP) strengthened masonry components to hygrothermal exposures. However, it is not clear how this local material degradation affects the global behavior of FRP-strengthened masonry structures. This study addresses this issue by numerically investigating the nonlinear behavior of FRP-masonry walls after aging in two different environmental conditions. A numerical modeling strategy is adopted and validated with existing experimental tests on FRP-strengthened masonry panels. The model, once validated, is used for modeling of four hypothetical FRP-strengthened masonry walls with different boundary conditions, strengthening schemes, and reinforcement ratios. The nonlinear behavior of the walls is then simulated before and after aging in two different environmental conditions. The degradation data are taken from previous accelerated aging tests. The changes in the failure mode and nonlinear response of the walls after aging are presented and discussed.

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.

High strain rate constitutive modeling forhistorical structures subjected to blast loading

Doctoral Thesis Civil Engineering

Poly-N-acetyl glucosamine expression in Staphylococcus epidermidis biofilm cells affects the immune response and promotes tissue pathology in infected hosts

Staphylococcus epidermidis is a biofilm - forming bacterium and a leading etiological agent of nosocomial infections. The ability to establish biofilms on indwelling medical devices is a key virulence factor for this bacterium. Still, the influence of poly - N - acetyl glucosamine (PNAG), the major component of the extracellular biofilm matrix, in the host immune response has been scarcely studied. Here, t h is influence was assessed in mice challenged i.p. with PNAG - p roducing (WT) and isogenic - mutant lacking PNAG (M10) bacteria grown in biofilm - inducing conditions. Faster bacterial clearance was observed in the mice infected with WT bacteria than in M10 - infected counterparts , which w as accompanied by earlier neutrophil recruitment and higher IL - 6 production. Interestingly, in the WT - infected mice, but not in those infected with M10 , elevated serum IL - 10 was detected . To further study the effe ct of PNAG in the immune response, mice were primed with WT or M10 biofilm bacteria and subsequently infected with WT biofilm - released cells. WT - primed mice presented a higher frequency of splenic IFN - γ + and IL - 17 + CD4 + T cells, and more severe liver patho logy than M10 - primed counterparts. Nevertheless, T reg cells obtained from the WT - primed mice presented a higher suppressive function than those obtained from M10 - primed mice. This effect was abrogated when IL - 10 - deficient mice were similarly primed and infected indicating that PNAG promotes the differentiati on of highly suppressive T reg cells by a mechanism dependent on IL - 10. Altogether, these results provide evidence help ing explain ing the coexistence of inflammation and bacterial persistence often observed in biofilm - originated S. epidermidis infections

Attachment style impacts behavior and early oculomotor response to positive, but not negative, pictures

The present study investigated whether oculomotor behavior is influenced by attachment styles. The Relationship Scales Questionnaire was used to assess attachment styles of forty-eight voluntary university students and to classify them into attachment groups (secure, preoccupied, fearful, and dismissing). Eye-tracking was recorded while participants engaged in a 3-seconds free visual exploration of stimuli presenting either a positive or a negative picture together with a neutral picture, all depicting social interactions. The task consisted in identifying whether the two pictures depicted the same emotion. Results showed that the processing of negative pictures was impermeable to attachment style, while the processing of positive pictures was significantly influenced by individual differences in insecure attachment. The groups highly avoidant regarding to attachment (dismissing and fearful) showed reduced accuracy, suggesting a higher threshold for recognizing positive emotions compared to the secure group. The groups with higher attachment anxiety (preoccupied and fearful) showed differences in automatic capture of attention, in particular an increased delay preceding the first fixation to a picture of positive emotional valence. Despite lenient statistical thresholds induced by the limited sample size of some groups (p < 0.05 uncorrected for multiple comparisons), the current findings suggest that the processing of positive emotions is affected by attachment styles. These results are discussed within a broader evolutionary framework.

Determination of the magnetostrictive response of nanoparticles via magnetoelectric measurements

It is successfully demonstrated that nanoparticle’s magnetostriction can be accurately determined based on the magnetoelectric effect measured on polymeric-composite materials. This represents a novel, simple and versatile method for the determination of particle’s magnetostriction at their nano-sized and dispersed state, which is, up to date, a difficult and imprecise task.

Size effects on the magnetoelectric response on PVDF/Vitrovac 4040 laminate composites

Tri-layered and bi-layered magnetoelectric (ME) flexible composite structures of varying geometries and sizes consisting on magnetostrictive Vitrovac and piezoelectric poly(vinylidene fluoride) (PVDF) layers were fabricated by direct bonding. From the ME measurements it was determined that tri-layered composites structures (magnetostrictive-piezoelectric-magnetostrictive type), show a higher ME response (75 V.cm-1.Oe-1) than the bi-layer structure (66 V.cm 1.Oe-1). The ME voltage coefficient decreased with increasing longitudinal size aspect ratio between PVDF and Vitrovac layers (from 1.1 to 4.3), being observed a maximum ME voltage coefficient of 66 V.cm-1.Oe-1. It was also observed that the composite with the lowest transversal aspect ratio between PVDF and Vitrovac layers resulted in better ME performance than the structures with higher transversal size aspect ratios. It was further determined an intimate relation between the Vitrovac PVDF Area Area ratio and the ME response of the composites. When such ratio values approach 1, the ME response is the largest. Additionally the ME output value and magnetic field response was controlled by changing the number of Vitrovac layers, which allows the development of magnetic sensors and energy harvesting devices.

Mechanical vs. electrical hysteresis of carbon nanotube/styrene-butadiene-styrene composites and their influence in the electromechanical response

The interesting properties of thermoplastics elastomers can be combined with carbon nanotubes (CNT) for the development of large strain piezoresistive composites for sensor applications. Piezoresistive properties of the composites depend on CNT content, with the gauge factor increasing for concentrations around the percolation threshold, mechanical and electrical hysteresis. The SBS copolymer composition (butadiene/styrene ratio) influences the mechanical and electrical hysteresis of composites and, therefore, the piezoresistive response. This work reports on the electrical and mechanical response of CNT/SBS composites with 4%wt nanofiller content, due to the larger electromechanical response. C401 and C540 SBS copolymers with 80% and 60% butadiene content, respectively have been selected. The copolymer with larger amount of soft phase (C401) shows a rubber-like mechanical behavior, with mechanical hysteresis increasing linearly with strain until 100% strain. The copolymer with the larger amount of hard phase (C540) just shows rubber-like behavior for low strains. The piezoresistive sensibility is similar for both composites for low strains, with a GF≈ 5 for 5% strain. The electrical hysteresis shows opposite behavior than the mechanical hysteresis, increasing with strain for both composites, but with higher increase for softer copolymer, C401. The GF increases with increasing strain, but this increase is larger for composites with lower amounts of soft phase due to the distinct initial modulus and deformation of the soft and hard phases of the copolymer. The soft phase shows larger strain under a given stress than the harder phase and the conductive pathway rearrangements in the composites are different for both phases, the harder copolymer (C540) showing higher piezoresistive sensibility, GF≈ 18, for 20% strain.