Recycling of Tire Waste Using Pyrolysis: An Environmental Perspective

End-of-life tires are a common and hazardous type of waste. According to estimates, over 2 billion tires are produced each year, and all of these tires will eventually be discarded as waste. Landfilling waste tires is strictly prohibited by the regulations of the European Union and the Environmental Protection Agency; they should be retreated and reused in an alternative scenario. As a waste-to-energy technology, pyrolysis, can emerge as a useful technique to thermally degrade waste tires and produce useful byproducts in the form of liquid, gas, and char. The derived products can be filtered and used in further industries as biofuel substances. Pyrolytic oil has a high calorific value of 35–45 MJ/kg and can be used as an alternative to diesel to fuel specific vehicles. However, the environmental footprint of the technology has been widely neglected when using waste tires as feedstock. Made from synthetic and natural rubbers, tires contain a high amount of sulfur and styrene, which can cause toxic emissions and negatively affect the environmental sustainability of pyrolysis. This concept paper aims to elaborate the parameters of an operating rotary kiln reactor by reviewing previous life cycle assessment studies and applying the methodology to an industrial-scale pyrolysis plant in Northern Cyprus. Results found a maximum production yield of 45.6% oil at an optimal temperature of 500 °C. Influential parameters such as temperature, residence time, and heating rate are reviewed based on their overall contribution to the production yield and the environment. The outcome of this paper emphasizes the need in the literature to apply environmental analyses to industrial and commercial-scale reactors to test the sustainability of using pyrolysis as a tire waste management strategy. In addition, complex engineering concepts and tasks in waste recycling will be discussed in a broad and accessible manner, with the implications and future work discussed

Geometrical Effects in Determination of Fickian Mass Diffusivity of Polymers

Hydrophilicity of polymers makes them prone to moisture absorption that leads to degradation of mechanical properties. Kinetics of moisture ingress needs to be fully characterized to perform reliable designs with polymeric materials. The rate of diffusion is the essential parameter in determining the time scale of the moisture uptake in polymeric materials. The model from which the diffusion coefficient is to be determined can be mathematically complex when the viscoelastic relaxation and diffusion time scales are comparable (i.e. Deborah Number ~ l). However, Fickian type of diffusion is shown to be adequate in modeling the moisture absorption into a broad range of polymers. Most methods for determining the diffusion coefficient are based on the solution of Fick's second law in semi-infinite and slab domains from which, a closed form solution has been adapted by the American Society of Testing and Materials (ASTM). However, those techniques either do not consider the errors due to finite sample dimension or the correction factors provided are not precise enough. In addition, fabrication of samples conforming ASTM standard (i.e. length or width to thickness ratio of 100 or greater) may not be practical due to difficulties in producing and testing very thin coupons. In this study, the solution of the Fickian diffusion equation for a three-dimensional rectangular domain is utilized to generate mass gain data for geometries with length to thickness ratios ranging from l to I 00. These data are then used to demonstrate the errors introduced by the two conventional methods used to determine the diffusion coefficient for sample dimensions deviating from an infinitely wide slab. After applying the correction factor suggested by ASTM, up to 13% error is observed in the diffusion coefficient. In order to improve the prediction of diffusion coefficient, a least square curve fit method, which yields accurate predictions regardless of the sample geometry, is proposed.YesPeer reviewed and presented at the 23rd Oklahoma AIAA/ASME Symposium

Evolved model for early fault detection and health tracking in marine diesel engine by means of machine learning techniques

The Coast Guard Command, which has a wide range of duties as saving human lives, protecting natural resources, preventing marine pollution and battle against smuggling, uses diesel main engines in its ships, as in other military and commercial ships. It is critical that the main engines operate smoothly at all times so that they can respond quickly while performing their duties, thus enabling fast and early detection of faults and preventing failures that are costly or take longer to repair. The aim of this study is to create and to develop a model based on current data, to select machine learning algorithms and ensemble methods, to develop and explain the most appropriate model for fast and accurate detection of malfunctions that may occur in 4-stroke high-speed diesel engines. Thus, it is aimed to be an exemplary study for a data-based decision support mechanism

Rapid Microwave Polymerization of Porous Nanocomposites with Piezoresistive Sensing Function

In this paper, polydimethylsiloxane (PDMS) and multi-walled carbon nanotube (MWCNT) nanocomposites with piezoresistive sensing function were fabricated using microwave irradiation. The effects of precuring time on the mechanical and electrical properties of nanocomposites were investigated. The increased viscosity and possible nanofiller re-agglomeration during the precuring process caused decreased microwave absorption, resulting in extended curing times, and decreased porosity and electrical conductivity in the cured nanocomposites. The porosity generated during the microwave-curing process was investigated with a scanning electron microscope (SEM) and density measurements. Increased loadings of MWCNTs resulted in shortened curing times and an increased number of small well-dispersed closed-cell pores. The mechanical properties of the synthesized nanocomposites including stress–strain behaviors and Young’s Modulus were examined. Experimental results demonstrated that the synthesized nanocomposites with 2.5 wt. % MWCNTs achieved the highest piezoresistive sensitivity with an average gauge factor of 7.9 at 10% applied strain. The piezoresistive responses of these nanocomposites were characterized under compressive loads at various maximum strains, loading rates, and under viscoelastic stress relaxation conditions. The 2.5 wt. % nanocomposite was successfully used in an application as a skin-attachable compression sensor for human motion detection including squeezing a golf ball.This research received no external funding and The APC was funded by University Libraries Open Access fund. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Nano-scale Flexible Interphase in a Glass Fiber/Epoxy Resin System Obtained by Admicellar Polymerization

Organosilane coupling agents are widely used in the composites industry to improve the wetting of inorganic reinforcements by low surface energy resins. An increased wettability is often a harbinger of better mechanical properties in a structural composite. Silane coatings effectively increase the spreading of liquid matrixes over glass reinforcement by altering the surface energetics of glass, not by extensive coverage, but by eradication of the high-energy sites present in the oxide surface. Commercial sizings often applied to glass fibers contain up to 10% of the active silane agent, while the remaining 90% is a mixture of lubricants, surfactants, anti-stats, and film formers. Recent investigations have demonstrated that non-reactive components tend to remain in high concentrations within the interphase, thus weakening the resin network crosslink density and increasing the potential for water ingress. Further, sizing formulations are proprietary and designed for specific resin system, which make them expensive, consequently limiting their widespread use. In this paper, admicellar polymerization, a versatile technique to prepare elastomeric thin films of styrene-isoprene copolymer and polystyrene on the surface of random glass-fiber mats is presented. This hydrophobic coating of monolayer thickness applied to the glass fibers is not expected to disrupt the matrix cross-linking reaction; and due to its higher elastic modulus, is believed to cause a change in the stress distribution along the fiber length. Admicellar-modified reinforcements were impregnated with an epoxy resin system: EPON 815C/EPICURE 3232, and molded by Resin Transfer Molding (RTM) into disk shaped parts. Tensile strength, stiffness and interlaminar shear strength (ILSS) were measured for the flexible interphase composites, and compared to parts containing commercially sized and bare fibers. Void fraction, void size and shape distributions, as well as water diffusivity were investigated for each system.YesPeer reviewed and presented at the 18th International Conference of the Polymer processing Society

Design of a novel THz sensor for structural health monitoring applications

In this paper, we propose a study on the characterization, design and simulation of a THz sensor for applications in Structural Health Monitoring (SHM). The proposed sensor is assembled using two frequency selective surfaces (FSSs) based on metamaterial wire resonators. We present a theoretical model to describe its electromagnetics which is used not only to understand the physical principles underlying the functioning of the sensor but also to determine a set of optimized parameters for its operation in the THz window from 395 GHz to 455 GHz. We present our numerical simulations, involving both electromagnetic and mechanical simulation techniques, to determine the reflectance profile of the sensor as a function of applied force. In this study we considered the possibility of using two thermoplastic polymers as host materials: High-Density PolyEthylene (HDPE) and PolyTetraFluoroEthylene (PTFE). The two sensors have a good dynamic range and comparable characteristics. However, we found that with HDPE it is possible to construct a sensor with a more linear response, although not as sensitive as in the case of PTFE. With HDPE we are able to pass from a situation of full transparency to almost full opacity using only its linear operating zone.info:eu-repo/semantics/acceptedVersio

Terahertz Time-Domain Study of Silver Nanoparticles Synthesized by Laser Ablation in Organic Liquid

We report the investigation of laser-synthesized Ag nanoparticles (Ag-NPs) in an organic liquid environment by using terahertz time-domain spectroscopy (THz-TDS) technique. Colloidal Ag-NPs with an average diameter of 10 nm in two-propanol solution through nanosecond pulsed laser ablation were synthesized. THz-TDS measurements were performed on different volumetric concentration of Ag-NPs suspensions placed in 2-mm path length quartz cuvette. Due to the dispersive and highly absorptive nature of the nano liquids, an approach based on extracting the optical properties through the changes in amplitude and phase solely around the main peak of THz waveform is developed. This approach allowed for an accurate estimation of the complex refractive index of the Metallic-NPs suspension for the different prepared volumetric concentrations. In addition, using Maxwell-Garnett theory, the NP concentration is also extracted. This method shows that the time-domain nature of the THz pulse measurement technique is extremely useful in instances where slight variations in highly dispersive samples need to be investigated. � 2016 IEEE

Process Induced Defects in Resin Transfer Molded Composites

PreviewResin transfer molding (RTM) is an attractive, versatile and cost-effective alternative to autoclave processing for manufacturing geometrically complex, structural polymer matrix composites (PMC). However, process induced defects such as microvoids or unwetted, dry spots often limit wider usage of RTM parts in high performance, mission critical applications. Understanding morphology of these defects, in addition to their formation mechanisms and removal techniques is an important step towards developing improved RTM processes. In this work, process induced defects in RTM parts are presented and contrasted to other defects encountered in PMCs. Defects in PMCs, which are classified as design induced and process induced, are both reviewed. Thereafter, more attention is drawn on voids and dry spots since they are known to be the most significant defects in RTM PMCs. Hence, dry spot formation mechanisms in RTM and available prevention techniques are summarized. In addition to adverse effects, formation mechanisms, and characterization methods of voids as well as their removal techniques are presented.Ye

A Debiasing Variational Autoencoder for Deforestation Mapping

Deep Learning (DL) algorithms provide numerous benefits in different applications, and they usually yield successful results in scenarios with enough labeled training data and similar class proportions. However, the labeling procedure is a cost and time-consuming task. Furthermore, numerous real-world classification problems present a high level of class imbalance, as the number of samples from the classes of interest differ significantly. In various cases, such conditions tend to promote the creation of biased systems, which negatively impact their performance. Designing unbiased systems has been an active research topic, and recently some DL-based techniques have demonstrated encouraging results in that regard. In this work, we introduce an extension of the Debiasing Variational Autoencoder (DB-VAE) for semantic segmentation. The approach is based on an end-to-end DL scheme and employs the learned latent variables to adjust the individual sampling probabilities of data points during the training process. For that purpose, we adapted the original DB-VAE architecture for dense labeling in the context of deforestation mapping. Experiments were carried out on a region of the Brazilian Amazon, using Sentinel-2 data and the deforestation map from the PRODES project. The reported results show that the proposed DB-VAE approach is able to learn and identify under-represented samples, and select them more frequently in the training batches, consequently delivering superior classification metrics

Characterization of Nanoclay Dispersion in Epoxy Matrix by Combined Image Analysis and Wavelength Dispersive Spectrometry

Nanoclay has been gaining acceptance as a nano-meter scale reinforcement for polymers during the last two decades [1]. It has proven to be successful for reinforcing thermoplastics [2], however, its utilization in thermosetting resins has been problematic. To improve dispersion of nanoclay into thermosetting resins, a number of companies developed surface modifications, which replace the sodium ions with larger organic molecules. In the current study, we are investigating the dispersion characteristics of three commercially available nanoclays from Southern Clay Products Inc., by combining microscopic image analysis and wavelength dispersive spectrometry.YesPeer reviewed and presented at the 22nd International Conference of the Polymer Processing Society