Progress and challenges in sustainability,compatibility, and production of eco-composites: A state-of-art review

Owing to economic and environmental benefits, new generations of materials/commodities follow “from waste to wealth” strategy. Recently, there has been a huge upsurge in research on the development of eco-composites using recycled plastic polymers and agro-residues because the eco-composites satisfy the stringent environment regulations and are cost-effective. Herein, we present a detailed review on the potential use of several types of natural fillers as an efficient reinforcement for recycled plastic polymers. In particular, the characterization of different categories of eco-composites according to their morphological, physical, thermal, and mechanical properties is extensively reviewed and their results are analyzed, compared, and highlighted. Furthermore, a framework to produce functional eco-composites, which includes functionalization of ingredients, critical issues on microstructural parameters, processing, and fabrication methods, is outlined and supported with sufficient data from the literature. Finally, the review outlines the emerging challenges and future prospects of eco-composites to be addressed by interested researchers to bridge the gap between research and commercialization of such a class of material. Overall, the acquired knowledge will guide researchers, scientists, and manufacturers to plan, select, and develop various forms of eco-composites with enhanced properties and optimized production processes.     

Investigation into the evolution of corrosion product layer (CPL) of 1018 C-steel exposed to multiphase environment using FIB and EIS techniques

This communication reports into the effects of flow, fluid composition and the effectiveness of imidazoline inhibitors on the evolution and distribution of corrosion products on 1018 C-steel exposed to CO₂ corrosion. Focused ion beam technique was used to measure the thickness of the corrosion product layer (CPL), in contrast to the conventional techniques used to observe the cross-section of specimens. Morphological analysis using scanning electron microscopy revealed topographical variations on the surface with the change in the multiphase environment. The CPL was found to be more porous in nature with the presence of oil in the multiphase environment. Electrochemical impedance spectroscopy was also used in the present study to measure the corrosion rates and was subsequently correlated to the CPL evolution for 1018 C-steel in multiphase environment.     

Oxidation and sulfidation behavior of Fe-20Cr-16Ni-4Al-1Y2O3 oxide-dispersion-strengthened alloy

High-temperature oxidation and sulfidation studies were conducted on an oxide-dispersion-strengthened alloy of composition Fe-20Cr-16Ni-4Al-1Y₂O₃. The oxidation studies were conducted in air and low-PO₂ environments over a temperature range of 650–1200°C. Results are also reported on the sulfidation resistance of preformed oxide scales and the influence of reoxidation of preformed sulfide scales. Detailed microstructural results and x-ray diffraction analysis data are presented to substantiate the corrosion behavior of the alloy over the wide range of conditions anticipated in fossil-energy systems. Data are also presented on the corrosion behavior of the alloy in oxygen/sulfur mixed gas atmospheres, and the results are used to compare the corrosion behavior of the present alloy with other chromia- and alumina-forming alloys.     

Crack initiation in relation to the tool edge radius and cutting conditions in nanoscale cutting of silicon

In cutting of brittle materials, experimentally it was observed that there is a ductile–brittle transition when the undeformed chip thickness is increased from smaller to larger than the tool cutting edge radius of the zero rake angle. However, how the crack is initiated in the ductile–brittle mode transition as the undeformed chip thickness is increased from smaller to larger than the tool cutting edge radius has not been fully understood. In this study, the crack initiation in the ductile–brittle mode transition as the undeformed chip thickness is increased from smaller to larger than the tool cutting edge radius has been simulated using the Molecular Dynamics (MD) method on nanoscale cutting of monocrystalline silicon with a non-zero edge radius tool, from which, for the first time, a peak deformation zone in the chip formation zone has been found in the transition from ductile mode to brittle mode cutting. The results show that as the undeformed chip thickness is larger than the cutting edge radius, in the chip formation zone there is a peak deformation depth in association with the connecting point of tool edge arc and the rake face, and there is a crack initiation zone in the undeformed workpiece next to the peak deformation zone, in which the material is tensile stressed and the tensile stress is perpendicular to the direction from the connecting point to the peak. As the undeformed chip thickness is smaller than the cutting edge radius, there is no deformation peak in the chip formation zone, and thus there is no crack initiation zone formed in the undeformed workpiece. This finding explains well the ductile–brittle transition as the undeformed chip thickness increases from smaller to larger than the tool cutting edge radius.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

What can possibly go wrong? Anticipatory work in space operations

This paper explores how different forms of anticipatory work contribute to reliability in high-risk space operations. It is based on ethnographic field work, participant observation and interviews supplemented with video recordings from a control room responsible for operating a microgravity greenhouse at the International Space Station (ISS). Drawing on examples from different stages of a biological experiment on the ISS, we demonstrate how engineers, researchers and technicians work to anticipate and proactively mitigate possible problems. Space research is expensive and risky. The experiments are planned over the course of many years by a globally distributed network of organizations. Owing to the inaccessibility of the ISS, every trivial detail that could possibly cause a problem is subject to scrutiny. We discuss what we label anticipatory work: practices constituted of an entanglement of cognitive, social and technical elements involved in anticipating and proactively mitigating everything that might go wrong. We show how the nature of anticipatory work changes between planning and the operational phases of an experiment. In the planning phase, operators inscribe their anticipation into technology and procedures. In the operational phase, we show how troubleshooting involves the ability to look ahead in the evolving temporal trajectory of the ISS operations and to juggle pre-planned fixes along these trajectories. A key objective of this paper is to illustrate how anticipation is shared between humans and different forms of technology. Moreover, it illustrates the importance of including considerations of temporality in safety and reliability research.     

Buoyancy convection in a cavity with mutually orthogonal heated plates

Buoyancy driven convection in a square cavity induced by two mutually orthogonal arbitrarily placed heated thin plates is studied numerically under isothermal and isoflux boundary conditions. The flow is assumed to be two-dimensional. The coupled governing equations were solved by the finite difference method using the Alternating Direction Implicit technique and Successive Over Relaxation method. The steady state results are depicted in terms of streamline and isotherm plots. It is found that the resulting convection pattern is stronger for the isothermal boundary condition. A better overall heat transfer can be achieved by placing one of the plates far away from the center of the cavity for isothermal boundary condition and near the center of the cavity for isoflux boundary condition.     

Learning to Locate Informative Features for Visual Identification

Object identification is a specialized type of recognition in which the category (e.g. cars) is known and the goal is to recognize an object’s exact identity (e.g. Bob’s BMW). Two special challenges characterize object identification. First, inter-object variation is often small (many cars look alike) and may be dwarfed by illumination or pose changes. Second, there may be many different instances of the category but few or just one positive “training” examples per object instance. Because variation among object instances may be small, a solution must locate possibly subtle object-specific salient features, like a door handle, while avoiding distracting ones such as specular highlights. With just one training example per object instance, however, standard modeling and feature selection techniques cannot be used. We describe an on-line algorithm that takes one image from a known category and builds an efficient “same” versus “different” classification cascade by predicting the most discriminative features for that object instance. Our method not only estimates the saliency and scoring function for each candidate feature, but also models the dependency between features, building an ordered sequence of discriminative features specific to the given image. Learned stopping thresholds make the identifier very efficient. To make this possible, category-specific characteristics are learned automatically in an off-line training procedure from labeled image pairs of the category. Our method, using the same algorithm for both cars and faces, outperforms a wide variety of other methods.     

A new approach to water quality modelling and environmental decision support systems

The concepts and technology of environmental decision support systems (EDSS) have developed considerably over recent decades, although core concepts such as flexibility and adaptability within a changing decision environment remain paramount. Much recent EDSS theory has focussed on model integration and re-use in decision support system (DSS) tools and for design and construction of ‘DSS generators’. Many current specific DSS have architectures, tools, models and operational characteristics that are either fixed or difficult to change in the face of changing management needs. This paper reports on development and deployment of an EDSS that encompasses a new approach to DSS tools, generators and specific DSS applications. The system, named E2, is built upon a conceptualisation of terrestrial and aquatic environmental systems that has resulted in a robust and flexible system architecture. The architecture provides a set of base classes to represent fundamental concepts, and which can be instantiated and combined to form DSS generators of varying complexity. A DSS generator is described within which system users are able to select and link models, data, analysis tools and reporting tools to create specific DSS for particular problems, and for which new models and tools can be created and, through software reflection (introspection), discovered to provide expanded capability where required. This system offers a new approach within which environmental systems can be described in the form of specific DSS at a scale and level of complexity suited to the problems and needs of decision makers.