Masked Signal Modeling for Plastic Waste Resin Classification

Feedstock recycling has received attention as an effective method to recycle waste plastics. However, estimating the reduction potential by life cycle assessment using coke oven and blast furnace in steel works has been a challenging task due to the complex structure of energy flow in steel works. Municipal waste plastics consist of several plastic resins. Previous studies have generally disregarded the composition of waste plastics, which varies significantly depending on the geographical area. If the reduction potentials by using each plastic resin in steel works can be quantified, the potential of municipal waste plastics (mixtures of plastic resins) can be estimated by summing up the potential of each resin multiplied by the composition of each resin in municipal waste plastics. Therefore, the goal of this study is to investigate the reduction potentials of CO2 emissions by using individual plastic resins (polyethylene (PE), polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET)) and those for municipal waste plastics in the coke oven and blast furnace. A model was developed to clarify the energy flow in steel works. In order to estimate the changes in energy and material balance in coke ovens when waste plastics are charged, the equations to calculate the coke product yield, gas product yield, and oil product yields of each plastic resin were derived from previous studies. The Rist model was adopted to quantify the changes in the inputs and outputs when plastics were fed into a blast furnace. Then, a matrix calculation method was used to calculate the change in energy balance before and after plastics are fed into a coke oven. It was confirmed that product yields of municipal waste plastics (mixtures of plastic resins) could be estimated by summing up the product yield of each plastic resin multiplied by the composition of each resin in municipal waste plastics. In both cases of coke oven and blast furnace feedstock recycling, the reduction potential of CO2 emissions varies significantly depending on the plastic resins. For example, in the case of coke oven chemical feedstock recycling, the reduction potential of PS and PP is larger than that of PE. On the other hand, in the case of blast furnace feedstock recycling, PE has the largest CO2 emissions reduction potential, whereas the CO2 emission reduction potential of PP is smaller than those of PE and PS. In both cases, PET has negative CO2 emission reduction potentials, i.e., there is an increase of CO2 emissions. In addition, the reduction potentials of CO2 emissions are slightly different in each city. The differences in the reduction potentials of CO2 emissions by coke oven chemical feedstock recycling of each plastic resin is attributable to the differences in calorific values and coke product yields of each plastic resin. On the other hand, the difference in the CO2 emission reduction potential for each plastic resin in blast furnace feedstock recycling is attributable to the difference in calorific values and the carbon and hydrogen content of each plastic resin, which leads to a difference in the coke substitution effect by each plastic resin. In both cases, the difference in those of municipal waste plastics is mostly attributable to the amount of impurities (e.g., ash, water) in the municipal waste plastics. It was found that the reduction potential of CO2 emissions by coke oven and blast furnace feedstock recycling of municipal waste plastics (mixtures of plastic resins) could be estimated by summing up the potential of each resin multiplied by the composition of each resin in municipal waste plastics. It was also clarified that feedstock recycling of waste plastic in steel works is effective for avoiding the increase in CO2 emissions by incinerating waste plastics, such as those from household mixtures of different resins. With the results obtained in this study, reduction potentials of CO2 emissions can be calculated for any waste plastics because differences in composition are taken into account.

Background, Aim and Scope. Feedstock recycling has received attention as an effective method to recycle waste plastics. However, estimating the reduction potential by LCA using coke oven and blast furnace in steel works has been a challenging task due to the complex structure of energy flow in steel works. Municipal waste plastics consist of several plastic resins. Previous studies have generally disregarded the composition of waste plastics, which varies significantly depending on the geographical area. If the reduction potentials by using each plastic resin in steel works can be quantified, the potential of municipal waste plastics (mixtures of plastic resins) can be estimated by summing up the potential of each resin multiplied by the composition of each resin in municipal waste plastics. Therefore, the goal of this study is to investigate the reduction potentials of CO2 emissions by using individual plastic resins (PE, PP, PS, PET) and those for municipal waste plastics in the coke oven and blast furnace.Materials and Methods. A model was developed to clarify the energy flow in steel works. In order to estimate the changes in energy and material balance in coke ovens when waste plastics are charged, the equations to calculate the coke product yield, gas product yield, and oil product yields of each plastic resin were derived from previous studies. The Rist model was adopted to quantify the changes in the inputs and outputs when plastics were fed into a blast furnace. Then, a matrix calculation method was used to calculate the change in energy balance before and after plastics are fed into a coke oven.Results. It was confirmed that product yields of municipal waste plastics (mixtures of plastic resins) could be estimated by summing up the product yield of each plastic resin multiplied by the composition of each resin in municipal waste plastics. In both cases of coke oven and blast furnace feedstock recycling, the reduction potential of CO2 emissions varies significantly depending on the plastic resins. For example, in the case of coke oven chemical feedstock recycling, the reduction potential of PS and PP is larger than that of PE. On the other hand, in the case of blast furnace feedstock recycling, PE has the largest CO2 emissions reduction potential, whereas, the CO2 emission reduction potential of PP is smaller than those of PE and PS. In both cases, PET has negative CO2 emission reduction potentials, i.e., there is an increase of CO2 emissions. In addition, the reduction potentials of CO2 emissions are slightly different in each city.Discussions. The differences in the reduction potentials of CO2 emissions by coke oven chemical feedstock recycling of each plastic resin is attributable to the differences in calorific values and coke product yields of each plastic resin. On the other hand, the difference in the CO2 emission reduction potential for each plastic resin in blast furnace feedstock recycling is attributable to the difference in calorific values and the carbon and hydrogen content of each plastic resin, which leads to a difference in the coke substitution effect by each plastic resin. In both cases, the difference in those of municipal waste plastics is mostly attributable to the amount of impurities (e.g., ash, water) in the municipal waste plastics.(View PDF for the rest of the abstract.)

Plastics and climate change—Breaking carbon lock-ins through three mitigation pathways

To elucidate the possibility and availability of thermal recycling of waste plastic resin from a basic and microscopic viewpoint, a series of abrupt heating processes of a spherical micro plastic particle having a diameter of about 200 μm is observed, when it is abruptly exposed to hot oxidizing combustion gas. Three ingenious devices are introduced and two typical plastic resins of polyethylene terephthalate and polyethylene are used. In this paper the dependency of internal and external appearances of residual plastic embers on the heating time and the ingredients of plastic resins is optically analyzed, along with appearances of internal micro bubbling, multiple micro explosions and jets, and micro diffusion flames during abrupt heating. Based on temporal variations of the surface area of a micro plastic particle, the apparent burning rate constant is also evaluated and compared with those of well-known volatile liquid fuels.

Asphalt is one of the materials used as road pavement material. One way to prevent damage to road pavement due to vehicle load is to improve the quality and stability of the pavement, but considering that road pavement materials such as asphalt cannot be renewed, other alternative materials are needed as asphalt replacement materials. The material used as a substitute for asphalt is a mixture of plastic waste and resin resin. This utilization is intended to reduce the existence of more and more plastic waste and utilize materials from natural plants. This study aims to determine the characteristics of a mixture of plastic waste and resin resin as a substitute for asphalt on flexible pavement. The test results obtained with the addition of more plastic waste, the penetration test value decreases, the test value of the softening point increases, the specific gravity test value decreases.

In the present study it was demonstrated that organic additives eluted from plastic resins could be utilized as substrates by sulfate-reducing bacteria. Two laboratory-scale experiments, a microcosm experiment and a leaching experiment, were conducted using polyvinyl chloride (PVC) as a model plastic resin. In the former experiment, the conversion of sulfate to sulfide was evident in microcosms that received plasticized PVC as the sole carbon source, but not in those that received PVC homopolymer. Additionally, dissolved organic carbon accumulated only in microcosms that received plasticized PVC, indicating that the dissolved organic carbon originated from additives. In the leaching experiment, phenol and bisphenol A were found in the leached solutions. These results suggest that the disposal of waste plastics in inert waste landfills may result in the production of H(2)S.

This study aimed to identify the impact of achieving the 1.5 °C target on the petroleum supply chain in Japan, and discuss the feasibility and challenges of decarbonization. First, a national material flow was established for the petroleum supply chain in Japan, including processes for crude petroleum refining, petroleum product manufacturing, plastic resin and product manufacturing, and by-product manufacturing. In particular, by-product manufacturing processes, such as hydrogen, gaseous carbon dioxide, and sulfur, were selected because they are utilized in other industries. Next, the outlook for the production of plastic resin, hydrogen, dry ice produced from carbon dioxide gas, and sulfur until 2050 was estimated for reducing petroleum consumption required to achieve the 1.5 °C target. As a result, national petroleum treatment is expected to reduce from 177,048.00 thousand kl in 2019 to 126,643.00 thousand kl in 2030 if the reduction in petroleum consumption is established. Along with this decrease, plastic resin production is expected to decrease from 10,500.00 thousand ton in 2019 to 7511.00 thousand ton by 2030. Conversely, the plastic market is expected to grow steadily, and the estimated plastic resin production in 2030 is expected to be 20,079.00 thousand ton. This result indicates that there is a large output gap between plastic supply and demand. To mitigate this gap, strongly promoting the recycling of waste plastics and making the price competitiveness of biomass plastics equal to that of petroleum-derived plastics are necessary.

Classification modeling of valve internal leakage acoustic emission signals based on optimal wavelet scattering coefficients

Digitization and analysis processing technology of music signals is the core of digital music technology. The paper studies the music signal feature recognition technology based on the mathematical equation inversion method, which is aimed at designing a method that can help music learners in music learning and music composition. The paper firstly studies the modeling of music signal and its analysis and processing algorithm, combining the four elements of music sound, analyzing and extracting the characteristic parameters of notes, and establishing the mathematical model of single note signal and music score signal. The single note recognition algorithm is studied to extract the Mel frequency cepstrum coefficient of the signal and improve the DTW algorithm to achieve single note recognition. Based on the implementation of the single note algorithm, we combine the note temporal segmentation method based on the energy-entropy ratio to segment the music score into single note sequences to realize the music score recognition. The paper then goes on to study the music synthesis algorithm and perform simulations. The benchmark model demonstrates the positive correlation of pitch features on recognition through comparative experiments and explores the number of harmonics that should be attended to when recognizing different instruments. The attention network-based classification model draws on the properties of human auditory attention to improve the recognition scores of the main playing instruments and the overall recognition accuracy of all instruments. The two-stage classification model is divided into a first-stage classification model and a second-stage classification model, and the second-stage classification model consists of three residual networks, which are trained separately to specifically identify strings, winds, and percussions. This method has the highest recognition score and overall accuracy.

ABSTRACTWe have been developing a solvent‐based plastic recycling technology called STRAP. The technology is based on dissolving a targeted plastic resin in a specific solvent that does not dissolve other resins. We have demonstrated STRAP in thousands of bench scale experiments for a large variety of wastes. Recently we have demonstrated the technology for PCR, using mixed plastic wastes (MPWs), from a wet Material Recovery Facility (MRF). The process includes (1) infrared (IR) characterization to determine the plastic composition for accurate selection of the solvent to be used for the extraction of the pure resins. (2) Shredding to the right size and aspect ratio required for flowable and fast dissolvable process. (3) Mixing the MPW in the first solvent to dissolve the first resin. (4) Filtration of the solution plastic blend, to separate the nondissolved plastic from the solution. (5) Further filtration of the solution to remove micron‐sized particle of pigments and fibers. (6) Cooling for precipitation. (7) Filtration of pure resins. (8) Drying of a pure resin. (9) Extrusion of the resin to pellets. (10) Generating films or other products from the pure resin. Steps 1–10 can be considered as one‐cycle that extracted the first resin. (11) A second resin can be extracted with a respective solvent from the plastic that did not dissolve in the first cycle and following steps 1–10 described above. The process also includes characterization of interim and final products. The effort includes building a pilot system at 25 kg/h throughput. We will present specific results for various PCR.

The focus of this chapter is environmental injustice produced in one strand of the global production network for plastics manufacturing using ethane, a gas liquid found in natural gas. I examine environmental injustices generated at each point in the network, from wells producing ethane from fracked natural gas, along high-pressure ethane transmission pipelines, to LNG export terminals where ethane is exported, at the fenceline of the petrochemical plants where ethane is transformed into plastic resins, and finally at disposal sites for discarded plastics. I conclude with some thoughts about the place in society of these unsustainable products and the prospects for their phaseout. Low gas prices and debt financing have increased incentives for the petrochemicals industry to invest in infrastructures that enable cheap ethane to be transformed into profitable plastic. More than a third of plastics are made into packaging and other disposable items, and the industry intends to increase production of disposable plastic items. This plan rests upon the fiction that increased recycling of plastics, and not source reduction, is the solution to widespread pollution with plastic garbage. In the U.S., plastic waste is either disposed of in marginalized communities or exported to poorer nations, causing global threats to health, safety and food webs as well as distributional injustice. Examining this global production network illustrates the political economic context behind the increasing production and use of unsustainable products and how the profitability of unsustainable practices is supported by negative externalities imposed upon less powerful groups of people.

IA121 view of the traditional BP model in classification of speech characteristic signal, the model has low classification accuracy, poor stability, easy to fall into the local minimum, and so on, therefore, the adaptive genetic algorithm is introduced to the optimization of BP model parameters to overcome the problems of the model. The adaptive genetic algorithm has strong adaptability and robustness, so the genetic algorithm is used to optimize the weights and threshold parameters of the BP model, which can effectively improve the performance of the neural network. Establish the classification system of speech characteristic signal based on adaptive genetic neural network, using the folk song, guzheng, rock and pop four different music speech characteristic signal to train and test the classification model. The test results show that, compared with the traditional BP model, the classification model of speech characteristic signal based on adaptive genetic neural network has higher classification accuracy.

The utility of plastics and engine oils is very important due to their wide application in the packaging and automotive industries respectively and as such their continued use has led to an in increase in plastics and oil waste. However, the huge amount of plastic and engine oil waste produced may be treated with thermal catalytic methods to produce fossil fuel substitutes. In this research, the co-processing of polyethylene resin with petrol engine oil into high value hydrocarbons using thermal catalytic cracking (consisting of initial pyrolytic stage followed by a catalytic reforming stage) was investigated. Plastic resins and petrol engine oil were loaded in the thermal reactor and HZSM-5 zeolite catalyst placed in the catalytic chamber. The system was purged with nitrogen at temperatures between 400 and 520oC. The resulting products were compared with those obtained in the absence of a catalyst. At temperatures greater than 460oC the conversion into liquid and gas fuels is above 70% wt. At similar temperatures and in the absence of catalyst, thermal cracking of low density polyethylene generated majorly liquid products with a low calorific value. The use of HZSM-5 as a catalyst caused a significant increase in the proportion of gaseous hydrocarbons that consisted mainly of light fraction olefins and liquid oil with calorific value of 43.9 MJ/kg and also comparable to regular petrol fuel. This study focuses on developing a method of conversion that can be adopted by industries as a means of converting waste plastics and waste oils into resources rather than waste.

When using BP model to classify speech feature signal, the initial weight and threshold of BP model randomly causes the model to fall into local minimum. A differential evolution algorithm is proposed to optimize the weight and threshold parameters of BP model, then establishing a classification model of speech feature signal based on differential evolution BP neural network algorithm. The classification models are trained and tested using the speech feature signals of four different kinds of music, folk songs, zither, rock and pop music. The test results show that compared with the traditional BP model, the improved BP algorithm model, the speech feature signal classification model based on differential evolution BP neural network is better in operation stability and classification accuracy.

The production of electronic products is one of the world's fasting growing industries today. Due to this phenomena, the amount of electronic waste generated increases proportionately with the production. The growing numbers of uses of plastic products in this sector contribute to electronic plastic waste generated. From the management of solid waste aspect, the production of electronic plastic waste has to be handled effectively. Generally, there are three options for electronic plastic waste recycling which is chemical, mechanical or thermal recycling. The main purpose of this paper is to discuss the research conducted on electronic plastic waste which consisted of various types of resin to determine the electronic plastic waste's potential as a source of energy. The physical and chemical characteristics of the electronic plastic waste are determined by the proximate analysis, ultimate analysis and the heavy metal content analysis of the plastic waste resin sample. The dulong formula was applied to calculate the heating value of electronic plastic waste based on the data obtained from the ultimate analysis. The result shows that the average heat value for an electronic waste is 30, 872.42 kj/kg or 7, 375 kcal/kg. The emmission factor analysis shows the concentration of air emission value which would probably be formed due to incineration activitiy is less than the effluent parameter of standard A and standard B limits fixed by the environmental quality act (clean air) 1978 for control air pollution. Basically, this research has succeeded in proving the potential of electronic plastic waste to be used as a source of energy in the future.