Dyeing of poly(lactic acid) fibres with synthesised novel heterocyclic disazo disperse dyes

Poly(lactic acid) (PLA) is the first melt‐processable, renewable, sustainable and biodegradable natural‐based synthetic fibre. It has a broad range of uses and combines ecological advantages with outstanding performance in textiles. PLA fibre, as an aliphatic polyester, can be dyed with disperse dyes. Apart from the limited number of commercial disperse dyes, disperse dye exhaustion on PLA is generally lower than that on  poly(ethylene terephthalate) (PET). In this study, new heterocyclic disazo disperse dyes, substituted with methyl, nitro and chloro groups at their ortho‐, meta‐ and para‐ positions, synthesised in our previous study, were applied to PLA and PET fibres to examine their dyeing performance, and colour fastness and dye exhaustion properties. Different shades of yellow, orange, reddish brown and brown were obtained. Most of the synthesised novel heterocyclic disazo disperse dyes exhibited good build‐up properties with high K/S levels on both fibres. Para‐ bonding substituent provided higher K/S values than meta‐ and ortho‐ positions for –NO₂ and –Cl substituents for both fibres. Overall, the most synthesised novel heterocyclic disazo disperse dyes in this study exhibited good build‐up properties with high K/S, exhaustion and wet fastness levels on both PLA and PET fibres.      

Conceptual damage-sensitive features for structural health monitoring: Laboratory and field demonstrations

The use of damage-sensitive features to evaluate structural condition or health is a very critical aspect of structural health monitoring. The purpose of this paper is to investigate the potential of two different damage-sensitive features for detecting damage. Different damage scenarios are simulated on a large-scale laboratory structure and a three-span highway bridge for demonstration. The features presented in this paper are the modal flexibility-based deflection and curvature both of which are obtained directly from dynamic properties. In the literature, flexibility associated with mode shapes and mode shapes curvatures have been mostly explored. In this study, multi-input–multi-output dynamic data are used to obtain modal flexibility, which is a close approximation to the actual flexibility. A main novelty is that the curvature is calculated from the deflected shapes using the modal flexibility as opposed to using modal vectors. In this paper, the theory of the methodology is explained and then experimental studies and results are presented. For the experimental studies, the laboratory specimen and the three-span bridge were gradually damaged. It is shown that both deflection and curvature are conceptual and physically meaningful features for damage detection and localization. The issues and the requirements for these features to perform successfully are also presented.     

Synthesis and properties of chitosan-modified poly(vinyl butyrate)

Modification of chitosan by grafting of vinyl butyrate was carried out in homogeneous phase using potassium persulfate as redox initator and 1.5% acetic acid as solvent. The percent grafting and grafting efficiency were analysed and the high grafting efficiency up to 94% was observed. The effects of reaction variables such as monomer concentration, initiator concentration, temperature and reaction time were investigated. It was observed that the solubility of chitosan was markedly reduced after grafting with vinyl butyrate. The grafted product is insoluble in common organic solvents as well in dilute organic and inorganic acids. Characterization of the graft copolymers were carried out by using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM) technics. Characteristic signal of carbonyl group was observed at 1,731 cm⁻¹ which belongs to the poly vinyl butyrate segments in the graft copolymer. The melting transition of the chitosan main chain in the copolymer shifted to 124°C from its original value 101°C. In addition to these, we have also studied topology of the graft copolymer and the SEM micrograph showed continuous homogenous matrix which means there is no phase separation.     

Prediction of performance and exhaust emissions of a diesel engine fueled with biodiesel produced from waste frying palm oil

Biodiesel is receiving increasing attention each passing day because of its fuel properties and compatibility with the petroleum-based diesel fuel (PBDF). Therefore, in this study, the prediction of the engine performance and exhaust emissions is carried out for five different neural networks to define how the inputs affect the outputs using the biodiesel blends produced from waste frying palm oil. PBDF, B100, and biodiesel blends with PBDF, which are 50% (B50), 20% (B20) and 5% (B5), were used to measure the engine performance and exhaust emissions for different engine speeds at full load conditions. Using the artificial neural network (ANN) model, the performance and exhaust emissions of a diesel engine have been predicted for biodiesel blends. According to the results, the fifth network is sufficient for all the outputs. In the fifth network, fuel properties, engine speed, and environmental conditions are taken as the input parameters, while the values of flow rates, maximum injection pressure, emissions, engine load, maximum cylinder gas pressure, and thermal efficiency are used as the output parameters. For all the networks, the learning algorithm called back-propagation was applied for a single hidden layer. Scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) have been used for the variants of the algorithm, and the formulations for outputs obtained from the weights are given in this study. The fifth network has produced R² values of 0.99, and the mean % errors are smaller than five except for some emissions. Higher mean errors are obtained for the emissions such as CO, NO_x and UHC. The complexity of the burning process and the measurement errors in the experimental study can cause higher mean errors.     

The effect of categorizing returned products in remanufacturing

An increasing number of companies have been implementing comprehensive recycling and remanufacturing programs. These endeavors typically involve the operation of joint manufacturing and remanufacturing systems. One of the major challenges in managing such hybrid systems is the stochastic nature of product returns. In particular, there is significant variability in the condition of the returns. This paper presents an approach for assessing the impact of quality-based categorization of returned products. Through extensive numerical studies on a continuous-time Markov chain model, we show that incorporation of returned product quality in the remanufacturing and disposal decisions can lead to significant cost savings. We find that these savings are amplified as the return quality decreases, and as the return rate increases. We also show that prioritizing higher quality returns in remanufacturing is, in general, a better strategy.     

Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks

International Journal of Computer Vision - Sign languages are multi-channel visual languages, where signers use a continuous 3D space to communicate. Sign language production (SLP), the automatic...     

Decentralized Coordination Control for a Network of Mobile Robotic Sensors

A decentralized control approach is presented for a network of robotic sensors to achieve the global coordination: group aggregation or consensus flocking. Each robotic sensor obeys three local interaction rules: group cohesion, collision avoidance and velocity alignment. Accordingly, the resultant control law for each robotic sensor is composed of three associated control components. The cohesion control component is based on geometry and additionally enables maintaining initial interconnection of network. The alignment control component ensures that all members in an interconnected network eventually reach to a common velocity. The control component for collision avoidance among members, as a passive role, is embedded in cohesion control. Simulation results demonstrate the capability of the proposed control approach in achieving the coordination behaviour with an initially interconnected network. However, we observed that an initially non-interconnected network may also achieve the coordination behaviour depending on the initial distribution and velocities. Initial interconnection of a network is only a sufficient but not essential condition for the network to achieve the coordination behaviour for our control approach.     

An artificial neural network model for the prediction of critical submergence for intake in a stratified fluid medium

Density differences may occur because of temperature differentials, suspended sediments, dissolved salts or other chemicals. Most of the large surface reservoirs are stably stratified throughout most, or all, of the year. One of the means of assisting the management is to allow a selective withdrawal from the reservoir. And while an intake is used for withdrawal (from the lower layer), a maximum discharge is required not allowing the uptake of the upper layer fluids. The value of the intake's vertical distance from the upper layer elevation (submergence) when the upper layer fluids begin to be drawn into the intake is known as ‘critical submergence’. In this study, the critical submergence for a circular intake pipe in a stratified body (which has different layer thickness) is investigated. Experiments were conducted on a vertically flowing downward intake pipe in a still-water reservoir. Artificial neural network (ANN) models and formulas, which are found by the theoretical analysis of critical spherical sink surface (CSSS), are used for the analysis of experimental results. The CSSS has the same centre and discharge as the intake. The ANN model and CSSS results are compared with the experimental results.     

Robust quadratic stabilization applied to design of continuous-time and discrete-time observers

In this paper, an application of a robust quadratic stabilization algorithm (RQSA) to continuous-time and discrete-time observers is presented. The RQSA is based on checking end points of a bounding hyperpolyhedron. The RQSA applied to observers is introduced, and implemented for a simplified car model, in both continuous-time and discrete-time case. The paper concludes that the RQSA is feasible to estimate unavailable states, even though there are structured uncertainties in the system matrix and in the measurement matrix.