The wettability and bonding performance of densified VTC beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.) bonded with phenol–formaldehyde adhesive and liquefied wood

The influence of viscoelastic thermal compression (VTC) on surface wettability and bonding performance of wood was evaluated. Low quality beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.) were densified with the VTC process to different degrees of densification. Control and densified strips were bonded with phenol–formaldehyde (PF) adhesive and liquefied wood (LW). Shear strength of bonded assemblies was determined after 1 week of conditioning at 20 °C and relative humidity of 65 %. Wettability was determined on the basis of the contact angle of water, PF adhesive, and LW using the Wilhelmy method. Results showed that densification of beech and spruce wood did not significantly affect the shear strength of specimens bonded with PF adhesive. In beech assemblies bonded with LW shear strength decreased significantly with increased density, whereas in bonded spruce specimens decrease of shear strength was not significant. It was found that degree of densification and bonding process used in the study were not appropriately chosen for spruce wood specimens, since major deformations after the bonding process occurred. Wettability changed significantly after densification. Contact angle of water and LW increased after densification, whereas contact angle of PF showed inverse trend and decreased after VTC process. Furthermore, the degree of densification had a minor effect on the wettability.     

Properties of liquefied wood modified melamine-formaldehyde (MF) resin adhesive and its application for bonding particleboards

In this study, we modified melamine-formaldehyde (MF) resin adhesive with liquefied wood (LW) and determined the properties of MF–LW adhesive mixtures. Furthermore, we produced particleboards using prepared MF–LW mixtures and evaluated their mechanical and physical properties. Results showed that with increasing content of LW in the adhesive mixture gel time and peak temperature increased while reaction enthalpy decreased. With increasing substitution of MF resin adhesive with LW the thermal stability of adhesive mixture reduced, namely thermal degradation started at lower temperature and weight loss increased. Properties of particleboards improved with increasing amount of LW in the adhesive mixture up to 20% and then deteriorated. Nevertheless, the properties of particleboard with 30% LW in the adhesive mixture were comparable to the properties of particleboard without LW while they worsen at greater portion of LW. Consequently, MF resin adhesive with 30% LW substitution could be used to produce particleboards with suitable mechanical properties and reduced formaldehyde release content.     

Numerical and experimental investigation of axial fan with trailing edge self-induced blowing

Axial fans often show adverse flow conditions at the fan hub and at the tip of the blades. In the present paper, a modification of conventional axial fan blades with numerical and experimental investigation is presented. Hollow blades were manufactured from the hub to the trailing edge at the tip of the blades. They enable the formation of self-induced internal flow through internal passages. The internal flow enters the internal radial flow passages of the hollow blades through the openings near the fan hub and exits through the trailing edge slots at the tip of the blade. The study of the influence of internal flow on the flow field of axial fan and the modifications of aerodynamic characteristics of the axial fan have been made. The numerical and experimental results show a comparison of integral and local characteristics of the axial fan with the internal flow, compared to characteristics of a geometrically equivalent fan without internal flow. The experimental results of local characteristics were performed with a five-hole probe and computer-aided visualization. A reduction of adverse flow conditions near the trailing edge at the tip of the blade was achieved, as well as boundary layer reduction on the blade suction side and the reduction of flow separation. The introduction of self-induced blowing led to the preservation of the direction of external flow, defined by blade geometry, and enabled maximal local energy conversion. The integral characteristic reached higher degree of efficiency.     

Natural convection of micropolar fluid in an enclosure with boundary element method

The contribution deals with numerical simulation of natural convection in micropolar fluids, describing flow of suspensions with rigid and underformable particles with own rotation. The micropolar fluid flow theory is incorporated into the framework of a velocity–vorticity formulation of Navier–Stokes equations. The governing equations are derived in differential and integral form, resulting from the application of a boundary element method (BEM). In integral transformations, the diffusion-convection fundamental solution for flow kinetics, including vorticity transport, heat transport and microrotation transport, is implemented. The natural convection test case is the benchmark case of natural convection in a square cavity, and computations are performed for Rayleigh number values up to 10⁷. The results show, which microrotation of particles in suspension in general decreases overall heat transfer from the heated wall and should not therefore be neglected when computing heat and fluid flow of micropolar fluids.     

Conformity enhances network reciprocity in evolutionary social dilemmas

The pursuit of highest payoffs in evolutionary social dilemmas is risky and sometimes inferior to conformity. Choosing the most common strategy within the interaction range is safer because it ensures that the payoff of an individual will not be much lower than average. Herding instincts and crowd behaviour in humans and social animals also compel to conformity in their own right. Motivated by these facts, we here study the impact of conformity on the evolution of cooperation in social dilemmas. We show that an appropriate fraction of conformists within the population introduces an effective surface tension around cooperative clusters and ensures smooth interfaces between different strategy domains. Payoff-driven players brake the symmetry in favour of cooperation and enable an expansion of clusters past the boundaries imposed by traditional network reciprocity. This mechanism works even under the most testing conditions, and it is robust against variations of the interaction network as long as degree-normalized payoffs are applied. Conformity may thus be beneficial for the resolution of social dilemmas.     

IMPACT OF HIGH-LEVEL KNOWLEDGE ON ECONOMIC WELFARE THROUGH INTERACTIVE DATA MINING

This paper describes a novel algorithm for finding the most important relations with the use of data mining. As an example application, the impact of high-level knowledge on economic welfare was analyzed. Our approach, based on interactive data mining, not only helps to discover the most relevant models, but also enables an evaluation of their relevance. The approach is specialized for the analysis of macroeconomic data that often contains incomplete and noisy attributes and, initially, complex relations, where several relations are statistically seemingly important, but only a few are indeed the most relevant. Although data mining algorithms are designed to detect the relevant attributes, irrelevant attributes often appear in the models due to chance-choice, reducing their quality and understandability, and consequently even leading to incorrect conclusions. We present our method and show its application at finding the most relevant relations between high-level knowledge and the state of development of a country.     

A probabilistic risk analysis for multimodal entry control

Entry control is an important security measure that prevents undesired persons from entering secure areas. The advanced risk analysis presented in this paper makes it possible to distinguish between acceptable and unacceptable entries, based on several entry sensors, such as fingerprint readers, and intelligent methods that learn behavior from previous entries. We have extended the intelligent layer in two ways: first, by adding a meta-learning layer that combines the output of specific intelligent modules, and second, by constructing a Bayesian network to integrate the predictions of the learning and meta-learning modules. The obtained results represent an important improvement in detecting security attacks.     

Assessment of differential evolution for multi-objective optimization in a natural convection problem solved by a local meshless method

The performance of Differential Evolution for Multi-objective Optimization (DEMO) in a nonlinear coupled transport problem, solved by a Meshless Local Strong form Method (MLSM), is assessed from different points of view. First, the behaviour of the optimization algorithm is tested for different scenarios, ranging from optimization of trivial diffusive transport to more complex nonlinear natural convection problems. Second, a hybrid parallel implementation of both the optimization and simulation codes, is introduced to optimize execution time, since such simulation-based optimization might require a vast amount of computational power. The goal of optimization is partially to cover the differentially heated cavity with non-permeable obstacles so as maximally to obstruct the flow with minimal possible coverage. Different scenarios are taken into account to analyse the optimization performance. The results are presented in terms of temperature contour plots, velocity profiles, analysis of heat losses, Pareto fronts of optimal solutions, convergence of optimal solutions, and sensitivity analysis of the optimizer and parallel execution performance.     

Mechanochemical Route for the Preparation of Nanosized Aluminum and Gallium Sulfide and Selenide

Aluminum and gallium chalcogenides are promising, yet relatively underexplored photoelectric and semiconducting materials. Many studies confirmed the applicability of gallium sulfides and selenides in photovoltaics and as electrode materials. In present work, a simple and convenient mechanochemical method has been developed for preparation of aluminum and gallium sulfide and selenide from elemental powders. The products have been characterized by X-ray powder diffraction (XRPD) and transmission electron microscopy (TEM), including energy-dispersive X-ray spectroscopy (EDX). The following products have been obtained: Al₂S₃, Al₂Se₃, Ga₂S₃, and Ga₂Se₃, with crystallite sizes in the range 8–12 nm.