Influence of the cohesive law parameters on the strength prediction of adhesively-bonded joints

Adhesive joints are largely employed nowadays as a fast and effective joining process. The respective techniques for strength prediction have also improved over the years. Cohesive Zone Models (CZM’s) coupled to Finite Element Method (FEM) analyses surpass the limitations of stress and fracture criteria and allow modelling damage. CZM’s require the energy release rates in tension (Gn) and shear (Gs) and respective fracture energies in tension (Gnc) and shear (Gsc). Additionally, the cohesive strengths (tn0 for tension and ts0 for shear) must also be defined. In this work, the influence of the CZM parameters of a triangular CZM used to model a thin adhesive layer is studied, to estimate their effect on the predictions. Some conclusions were drawn for the accuracy of the simulation results by variations of each one of these parameters.

PV system modeling by five parameters and in Situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Weather parameters and nosocomial bloodstream infection: a case-referent study

OBJECTIVE To evaluate if temperature and humidity influenced the etiology of bloodstream infections in a hospital from 2005 to 2010.METHODS The study had a case-referent design. Individual cases of bloodstream infections caused by specific groups or pathogens were compared with several references. In the first analysis, average temperature and humidity values for the seven days preceding collection of blood cultures were compared with an overall “seven-days moving average” for the study period. The second analysis included only patients with bloodstream infections. Several logistic regression models were used to compare different pathogens and groups with respect to the immediate weather parameters, adjusting for demographics, time, and unit of admission.RESULTS Higher temperatures and humidity were related to the recovery of bacteria as a whole (versus fungi) and of gram-negative bacilli. In the multivariable models, temperature was positively associated with the recovery of gram-negative bacilli (OR = 1.14; 95%CI 1.10;1.19) or Acinetobacter baumannii (OR = 1.26; 95%CI 1.16;1.37), even after adjustment for demographic and admission data. An inverse association was identified for humidity.CONCLUSIONS The study documented the impact of temperature and humidity on the incidence and etiology of bloodstream infections. The results correspond with those from ecological studies, indicating a higher incidence of gram-negative bacilli during warm seasons. These findings should guide policies directed at preventing and controlling healthcare-associated infections.

Optimization of magneto-electro-elastic composite structures using differential evolution

Magneto-electro-elastic structures are built from materials that provide them the ability to convert in an interchangeable way, magnetic, electric and mechanical forms of energy. This characteristic can therefore provide an adaptive behaviour to a general configuration elastic structure, being commonly used in association with any type of composite material in an embedded or surface mounted mode, or by considering the usage of multiphase materials that enable achieving different magneto-electro-elastic properties. In a first stage of this work, a few cases studies will be considered to enable the validation of the model considered and the influence of the coupling characteristics of this type of adaptive structures. After that we consider the application of a recent computational intelligence technique, the differential evolution, in a deflection profile minimization problem. Studies on the influence of optimization parameters associated to the problem considered will be performed as well as the adoption of an adaptive scheme for the perturbation factor. Results are also compared with those obtained using an enhanced particle swarm optimization technique. (C) 2013 Elsevier Ltd. All rights reserved.

Adaptive tackling of the swinging problem for a 2 DOF crane – payload system

The control of a crane carrying its payload by an elastic string corresponds to a task in which precise, indirect control of a subsystem dynamically coupled to a directly controllable subsystem is needed. This task is interesting since the coupled degree of freedom has little damping and it is apt to keep swinging accordingly. The traditional approaches apply the input shaping technology to assist the human operator responsible for the manipulation task. In the present paper a novel adaptive approach applying fixed point transformations based iterations having local basin of attraction is proposed to simultaneously tackle the problems originating from the imprecise dynamic model available for the system to be controlled and the swinging problem, too. The most important phenomenological properties of this approach are also discussed. The control considers the 4th time-derivative of the trajectory of the payload. The operation of the proposed control is illustrated via simulation results.

Fixed point transformations in the adaptive control of fractional-order MIMO systems

Though the formal mathematical idea of introducing noninteger order derivatives can be traced from the 17th century in a letter by L’Hospital in which he asked Leibniz what the meaning of D n y if n = 1/2 would be in 1695 [1], it was better outlined only in the 19th century [2, 3, 4]. Due to the lack of clear physical interpretation their first applications in physics appeared only later, in the 20th century, in connection with visco-elastic phenomena [5, 6]. The topic later obtained quite general attention [7, 8, 9], and also found new applications in material science [10], analysis of earth-quake signals [11], control of robots [12], and in the description of diffusion [13], etc.

Optimisation of exposure parameters for spinal curvature measurements in paediatric radiography

This review aims to identify strategies to optimise radiography practice using digital technologies, for full spine studies on paediatrics focusing particularly on methods used to diagnose and measure severity of spinal curvatures. The literature search was performed on different databases (PubMed, Google Scholar and ScienceDirect) and relevant websites (e.g., American College of Radiology and International Commission on Radiological Protection) to identify guidelines and recent studies focused on dose optimisation in paediatrics using digital technologies. Plain radiography was identified as the most accurate method. The American College of Radiology (ACR) and European Commission (EC) provided two guidelines that were identified as the most relevant to the subject. The ACR guidelines were updated in 2014; however these guidelines do not provide detailed guidance on technical exposure parameters. The EC guidelines are more complete but are dedicated to screen film systems. Other studies provided reviews on the several exposure parameters that should be included for optimisation, such as tube current, tube voltage and source-to-image distance; however, only explored few of these parameters and not all of them together. One publication explored all parameters together but this was for adults only. Due to lack of literature on exposure parameters for paediatrics, more research is required to guide and harmonise practice.

Crossing genetic and swarm intelligence algorithms to generate logic circuits

Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.

Evaluation of the influence of testing parameters on the melt flow index of thermoplastics

The main goals of the present work are the evaluation of the influence of several variables and test parameters on the melt flow index (MFI) of thermoplastics, and the determination of the uncertainty associated with the measurements. To evaluate the influence of test parameters on the measurement of MFI the design of experiments (DOE) approach has been used. The uncertainty has been calculated using a "bottom-up" approach given in the "Guide to the Expression of the Uncertainty of Measurement" (GUM). Since an analytical expression relating the output response (MFI) with input parameters does not exist, it has been necessary to build mathematical models by adjusting the experimental observations of the response variable in accordance with each input parameter. Subsequently, the determination of the uncertainty associated with the measurement of MFI has been performed by applying the law of propagation of uncertainty to the values of uncertainty of the input parameters. Finally, the activation energy (Ea) of the melt flow at around 200 degrees C and the respective uncertainty have also been determined.

Influence of reconstruction parameters for FBP in semiquantification of brain studies with 123I-FPCIT

Brain dopamine transporters imaging by Single Photon Emission Tomography (SPECT) with 123I-FP-CIT has become an important tool in the diagnosis and evaluation of parkinsonian syndromes, since this radiopharmaceutical exhibits high affinity for membrane transporters responsible for cellular reabsorption of dopamine on the striatum. However, Ordered Subset Expectation Maximization (OSEM) is the method recommended in the literature for imaging reconstruction. Filtered Back Projection (FBP) is still used due to its fast processing, even if it presents some disadvantages. The aim of this work is to investigate the influence of reconstruction parameters for FBP in semiquantification of Brain Studies with 123I-FPCIT compared with those obtained with OSEM recommended reconstruction.

A qualitative description of soil parameters variation due to a prescribed fire in Portuguese northwestern forests using Fuzzy Boolean Nets — The case study of Cabreira mountain

In this paper we study the modifications that occurred in some forest soil properties after a prescribed fire. The research focused on the alterations of soil pH, soil moisture and soil organic matter content during a two-year span, from 2008 to 2009. The study site is located in Anjos, Vieira do Minho municipality, a forest site that has suffered from recurrent wildfires for several decades. Furze (Ulex, sp.), broom (Cytisus, sp.), gorse (Chamaespartum tridentatum) and a very few disperse adult pine (Pinus sylvestris) are the predominant vegetation type in the study area. The average height of this shrub vegetation is around 1.5 m. The prescribed fire was conducted by the National Forestry Authority (AFN) in November 2008. Fuzzy Boolean Nets (FBN) were used to evaluate the alteration in soil parameters when compared with adjacent spots where: i) no fire occurrence was registered since 1998; ii) fire occurrence was registered in 2008; and iii) vegetation pruning by mechanical cut was done in Spring six months prior to the prescribed fire event. Results suggest that in the particular case of the studied site, Anjos, the observed soil properties alterations cannot be related with the prescribed fire.

Digitally programmable delay-locked-loop with adaptive charge pump current for UWB radar system

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

Acqusition and data analysis of the eco-efficiency for the establishment of indicators parameters for industrial environmental sustainability

The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.

Adaptive learning in agents behaviour: A framework for electricity markets simulation

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 (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Organic versus conventional tomatoes: Influence on physicochemical parameters, bioactive compounds and sensorial attributes

The effect of organic and conventional agricultural systems on the physicochemical parameters, bioactive compounds content, and sensorial attributes of tomatoes (‘‘Redondo’’ cultivar) was studied. The influence on phytochemicals distribution among peel, pulp and seeds was also accessed. Organic tomatoes were richer in lycopene (+20%), vitamin C (+30%), total phenolics (+24%) and flavonoids (+21%) and had higher (+6%) in vitro antioxidant activity. In the conventional fruits, lycopene was mainly concentrated in the pulp, whereas in the organic ones, the peel and seeds contained high levels of bioactive compounds. Only the phenolic compounds had a similar distribution among the different fractions of both types of tomatoes. Furthermore, a sensorial analysis indicated that organic farming improved the gustative properties of this tomato cultivar.