Influence of the wood mechanical properties in the dovetail joint behavior

The force distribution inside a dovetail joint is complex. Wood is simultaneously loaded in different directions in the several connected surfaces. The analytical solutions available for the analysis of the behavior of those carpentry joints rely on the mechanical properties of wood. In particular, the stiffness properties of wood under compression are crucial for the forces equilibrium. Simulations showed that the stiffness values considered in each of the springs normally assumed in the analytical models, have great influence in the bearing capacity and stiffness of the dovetail joints, with important consequence on the stress distribution over the overall structure. In a wide experimental campaign, the properties under compression of the most common wood species of existing timber structures have been determined. Then, a solved example of a dovetail joint is presented assuming different wood species and the corresponding strength and stiffness properties values obtained in the tests.

Fundamental studies on natural deep eutectic solvents: physico-chemical, thermal and rheological properties

When combined at particular molar fractions, sugars, aminoacids or organic acids a present a high melting point depression, becoming liquids at room temperature. These are called Natural Deep Eutectic Solvents – NADES and are envisaged to play a major role on the chemical engineering processes of the future. Nonetheless, there is a significant lack of knowledge of its fundamental and basic properties, which is hindering their industrial applications. For this reason it is important to extend the knowledge on these systems, boosting their application development [1]. In this work, we have developed and characterized NADES based on choline chloride, organic acids, amino acids and sugars. Their density, thermal behavior, conductivity and polarity were assessed for different compositions. The conductivity was measured from 0 to 40 °C and the temperature effect was well described by the Vogel-Fulcher-Tammann equation. The morphological characterization of the crystallizable materials was done by polarized optical microscopy that provided also evidence of homogeneity/phase separation. Additionally, the rheological and thermodynamic properties of the NADES and the effect of water content were also studied. The results show these systems have Newtonian behavior and present significant viscosity decrease with temperature and water content, due to increase on the molecular mobility. The anhydrous systems present viscosities that range from higher than 1000Pa.s at 20°C to less than 1Pa.s at 70°C. DSC characterization confirms that for water content as high as 1:1:1 molar ratio, the mixture retains its single phase behavior. The results obtained demonstrate that the NADES properties can be finely tunned by careful selection of its constituents. NADES present the necessary properties for use as extraction solvents. They can be prepared from inexpensive raw materials and tailored for the selective extraction of target molecules. The data produced in this work is hereafter importance for the selection of the most promising candidates avoiding a time consuming and expensive trial and error phase providing also data for the development of models able to predict their properties and the mechanisms that allow the formation of the deep eutectic mixtures.

Valorization of eucalyptus wood by glycerol-organosolv pretreatment within the biorefinery concept: an integrated and intensified approach

The efficient utilization of lignocellulosic biomass and the reduction of production cost are mandatory to attain a cost-effective lignocellulose-to-ethanol process. The selection of suitable pretreatment that allows an effective fractionation of biomass and the use of pretreated material at high-solid loadings on saccharification and fermentation (SSF) processes are considered promising strategies for that purpose. Eucalyptus globulus wood was fractionated by organosolv process at 200 C for 69 min using 56% of glycerol-water. A 99% of cellulose remained in pretreated biomass and 65% of lignin was solubilized. Precipitated lignin was characterized for chemical composition and thermal behavior, showing similar features to commercial lignin. In order to produce lignocellulosic ethanol at high-gravity, a full factory design was carried to assess the liquid to solid ratio (3e9 g/g) and enzyme to solid ratio (8e16 FPU/g) on SSF of delignified Eucalyptus. High ethanol concentration (94 g/L) corresponding to 77% of conversion at 16FPU/g and LSR ¼ 3 g/g using an industrial and thermotolerant Saccharomyces cerevisiae strain was successfully produced from pretreated biomass. Process integration of a suitable pretreatment, which allows for whole biomass valorization, with intensified saccharification-fermentation stages was shown to be feasible strategy for the co-production of high ethanol titers, oligosaccharides and lignin paving the way for cost-effective Eucalyptus biorefinery.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

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

Autor proof

Continuous monitoring of concrete mechanical properties since an early age to support construction phasing

The assessment of concrete mechanical properties during construction of concrete structures is of paramount importance for many intrinsic operations. However many of the available non-destructive methods for mechanical properties have limitations for use in construction sites. One of such methodologies is EMM-ARM, which is a variant of classic resonant frequency methods. This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties such as E-modulus and compressive strength. To achieve the aforementioned objective, a set of adaptations to the method have been successfully implemented and tested: (i) the reduction of the beam span; (ii) the use of a different mould material and (iii) a new support system for the beams. Based on these adaptations, a reusable mould was designed to enable easier systematic use of EMMARM. A pilot test was successfully performed under in-situ conditions during a bridge construction.

A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

The effect of secular trends in the classroom furniture mismatch: support for continuous update of school furniture standards

In order to create safer schools, the Chilean authorities published a Standard regarding school furniture dimensions. The aims of this study are twofold: to verify the existence of positive secular trend within the Chilean student population and to evaluate the potential mismatch between the anthropometric characteristics and the school furniture dimensions defined by the mentioned standard. The sample consists of 3078 subjects. Eight anthropometric measures were gathered, together with six furniture dimensions from the mentioned standard. There is an average increase for some dimensions within the Chilean student population over the past two decades. Accordingly, almost 18% of the students will find the seat height to be too high. Seat depth will be considered as being too shallow for 42.8% of the students. It can be concluded that the Chilean student population has increased in stature, which supports the need to revise and update the data from the mentioned Standard. Practitioner Summary: Positive secular trend resulted in high levels of mismatch if furniture is selected according to the current Chilean Standard which uses data collected more than 20 years ago. This study shows that school furniture standards need to be updated over time.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Process simulation support in BPM tools: The case of BPMN

Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Methodology for real-time adaptation of tunnels support using the observational method

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

Tailored magnetic and magnetoelectric responses of polymer-based composites

The manipulation of electric ordering with applied magnetic fields has been realized on magnetoelectric (ME) materials, however, their ME switching is often accompanied by significant hysteresis and coercivity that represents, for some applications, a severe weakness. To overcome this obstacle, this work focus on the development of a new type of ME polymer nanocomposites that exhibits tailored ME response at room temperature. The multiferroic nanocomposites are based on three different ferrite nanoparticles, Zn0.2Mn0.8Fe2O4 (ZMFO), CoFe2O4 (CFO) and Fe3O4 (FO), dispersed in a piezoelectric co-polymer poly(vinylindene fluoride-trifluoroethylene), P(VDF-TrFE), matrix. No substantial differences were detected on the time-stable piezoelectric response of the composites (≈ -28 pC.N−1) with distinct ferrite fillers and for the same ferrite content of 10wt.%. Magnetic hysteresis loops from pure ferrite nanopowders showed different magnetic responses. ME results of the nanocomposite films with 10wt.% ferrite content revealed that the ME induced voltage increases with increasing DC magnetic field until a maximum of 6.5 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.26 T, and 0.8 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.15T, for the CFO/P(VDF-TrFE) and FO/P(VDF-TrFE) composites, respectively. On the contrary, the ME response of the ZMFO/P(VDF-TrFE) exposed no hysteresis and high dependence on the ZMFO filler content. Possible innovative applications such as memories and information storage, signal processing, ME sensors and oscillators have been addressed for such ferrite/PVDF nanocomposites.

Ag-TiNx electrodes deposited on piezoelectric poly(vinylidene fluoride) for biomedical sensor applications

Electroactive polymers are one of the most interesting class of polymers used as smart materials in various applications, such as the development of sensors and actuators for biomedical applications in areas such as smart prosthesis, implantable biosensors and biomechanical signal monitoring, among others. For acquiring or applying the electrical signal from/to the piezoelectric material, suitable electrodes can be produced from Ti based coatings with tailored multifunctional properties, conductivity and antibacterial characteristics, through Ag inclusions. This work reports on Ag-TiNx electrodes, deposited by d. c. and pulsed magnetron sputtering at room temperature on poly(vinylidene fluoride), PVDF, the all-round best piezoelectric polymer.. Composition of the electrodes was assessed by microanalysis X-ray system (EDS - energy dispersive spectrometer). The XRD results revealed that the deposition conditions preserve the polymer structure and suggested the presence of crystalline fcc-TiN phase and fcc-Ag phase in samples with N2 flow above 3 sccm. According to the results obtained from SEM analysis, the coatings are homogeneous and Ag clusters were found for samples with nitrogen flow above 3 sccm. With increasing nitrogen flow, the sheet resistivity tend to be lower than the samples without nitrogen, leading also to a decrease of the piezoelectric response. It is concluded that the deposition conditions do significantly affect the piezoelectric polymer, which maintain its characteristics for sensor/actuator applications.

Phase morphology and crystallinity of poly(vinylidene fluoride)/poly(ethylene oxide) piezoelectric blend membranes

Polymer blends based on poly(vinylidene fluoride), PVDF and poly(ethylene oxide), PEO, with varying compositions have been prepared by solvent casting, the polymer blend films being obtained from solutions in dimethyl formamide at 70ºC. Under these conditions PVDF crystallizes from solution while PEO remains in the molten state. Then, PEO crystallizes from the melt confined by PVDF crystalls during cooling to room temperature. PVDF crystallized from DMF solutions adopt predominantly the electroactive β-phase (85%). Nevertheless when PEO is introduced in the polymer blend the β-phase content decreases slightly to 70%. The piezoelectric coefficient (d33) in pristine PVDF is -5 pC/N and decreases with increasing PEO content in the PVDF/PEO blends. Blend morphology, observed by electron and atomic force microscopy, shows the confinement of PEO between the already formed PVDF crystals. On the other hand the sample contraction when PEO is extracted from the blend with water (which is not a solvent for PVDF) allows proving the co-continuity of both phases in the blend. PEO crystallization kinetics have been characterized by DSC both in isothermal and cooling scans experiments showing important differences in crystalline fraction and crystallization rate with sample composition.