Influence of low-density polyethylene addition on coking pressure

Different amounts of low-density polyethylene (LDPE) were added to a bituminous coal used to produce metallurgical coke. The effect of the plastic waste on the carbonization process and more exactly, on the coking pressure were investigated. A movable wall oven at semi-pilot scale was used for measuring coking pressure generated. It was found that coking pressure increases for low LDPE addition levels (1-3 wt.%); however higher amounts of LDPE reduce coking pressure. To explain this behavior different blends of the coal and the residue were pyrolysed at three different temperatures (450, 500 and 600 C) in a Gray-King apparatus. The results show that LDPE causes a modification in the pyrolysis process and also influences the swelling process of the plastic stage. The increase of the coking pressure at low LDPE addition rates is associated with a less permeable coal plastic layer, which prevents the removal of the decomposition products and causes their retention in the semicoke matrix, evolving them in the post-plastic stage. Coking pressure decrease at high LDPE addition rates can be due to the charge shrinkage and the better permeability to the migration of oil components, which suggest a lower interaction between the coal and the LDPE. A delay in the degradation of LDPE is confirmed by the data provided by DRIFT and SEM

Relevance of the composition of municipal plastic wastes for metallurgical coke production

This study is concerned with the effects of the composition of mixed plastic wastes on the thermoplastic properties of coal, the generation of coking pressure and the quality of the resulting cokes in a movable wall oven at semipilot scale. The mixed plastic wastes were selected to cover a wide spectrum in the relative proportions of high- and low-density polyethylenes (HDPE and LDPE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET). From the results it was deduced that the reduction in Gieseler fluidity in the coal blend is linked to the total amount of polyolefins in the waste. It was also found that these thermoplastics increase the pressure exerted against the wall in the course of the coking process and that coke quality is maintained or even improved. However, when the level of aromatic polymers such PS and PET are increased at the expense of polyolefins, the coking pressure decreases. Thus, the amount of aromatic polymers such as PS and PET in the waste is critical, not only for controlling Gieseler fluidity and coking pressure, but also for avoiding deterioration in coke quality (reactivity towards CO CRI and mechanical strength of the partially-gasified coke CSR). An amount of polyolefins in the waste lower than 65 wt.% for a secure coking pressure is established

Bayesian Probabilistic Power Flow Analysis Using Jacobian Approximate Bayesian Computation

A probabilistic power flow (PPF) study is an essential tool for the analysis and planning of a power system when specific variables are considered as random variables with particular probability distributions. The most widely used method for solving the PPF problem is Monte Carlo simulation (MCS). Although MCS is accurate for obtaining the uncertainty of the state variables, it is also computationally expensive, since it relies on repetitive deterministic power flow solutions. In this paper, we introduce a different perspective for the PPF problem. We frame the PPF as a probabilistic inference problem, and instead of repetitively solving optimization problems, we use Bayesian inference for computing posterior distributions over state variables. Additionally, we provide a likelihood-free method based on the Approximate Bayesian Computation philosophy, that incorporates the Jacobian computed from the power flow equations. Results in three different test systems show that the proposed methodologies are competitive alternatives for solving the PPF problem, and in some cases, they allow for reduction in computation time when compared to MCS

Radio y cultura: Una propuesta de radio ciudadana en Internet

This article is the result of research project to qualify for a Master's degree "La Peña Cultural: model citizen Internet radio" carried out during 2013 and 2014 for Universidad de Medellin. It explored the Internet radio as a platform with multimedia tools that could strengthen the formation of reflective citizenship through content of cultural promotion. Similarly, it identifies, from a tracking station in Colombia, how these tools -social networks, podcasts, chats, video channels and new ways to communicate- allow the active participation of citizens in their production. Rescuing the use of technologies that facilitate communication, such as Internet radio, to recognize and retrieve the value of their own cultural promotion of a state in order to form a reflective citizenship, it is the approach that was made from the ethnographic and applied research and is now presented in this article. It is the way in which citizens could converge in a medium to produce content that will strengthen their cultural identity or, if you will, their vision of the nation. It is a commitment to establish an alternative to the traditional models, a guide to the community interested in promoting a reflexive citizen of cultural heritage

Efficient modeling of latent information in supervised learning using Gaussian processes

Often in machine learning, data are collected as a combination of multiple conditions, e.g., the voice recordings of multiple persons, each labeled with an ID. How could we build a model that captures the latent information related to these conditions and generalize to a new one with few data? We present a new model called Latent Variable Multiple Output Gaussian Processes (LVMOGP) that allows to jointly model multiple conditions for regression and generalize to a new condition with a few data points at test time. LVMOGP infers the posteriors of Gaussian processes together with a latent space representing the information about different conditions. We derive an efficient variational inference method for LVMOGP for which the computational complexity is as low as sparse Gaussian processes. We show that LVMOGP significantly outperforms related Gaussian process methods on various tasks with both synthetic and real data

Physically-inspired Gaussian process models for post-transcriptional regulation in Drosophila

The regulatory process of Drosophila is thoroughly studied for understanding a great variety of biological principles. While pattern-forming gene networks are analysed in the transcription step, post-transcriptional events (e.g. translation, protein processing) play an important role in establishing protein expression patterns and levels. Since the post-transcriptional regulation of Drosophila depends on spatiotemporal interactions between mRNAs and gap proteins, proper physically-inspired stochastic models are required to study the link between both quantities. Previous research attempts have shown that using Gaussian processes (GPs) and differential equations lead to promising predictions when analysing regulatory networks. Here we aim at further investigating two types of physically-inspired GP models based on a reaction-diffusion equation where the main difference lies in where the prior is placed. While one of them has been studied previously using protein data only, the other is novel and yields a simple approach requiring only the differentiation of kernel functions. In contrast to other stochastic frameworks, discretising the spatial space is not required here. Both GP models are tested under different conditions depending on the availability of gap gene mRNA expression data. Finally, their performances are assessed on a high-resolution dataset describing the blastoderm stage of the early embryo of Drosophila melanogaster

Genética de las proteínas de reserva del cotiledón en castaño (Castanea sativa Miller)

A first approximation to the inheritance of cotyledon storage proteins was studied in European sweet chestnut (Castanea sativa Mill.) by evaluating the offspring of a controlled cross between two local chestnut varieties (Corriente and Pilonga) from southern Spain. The analysis was carried out in 15 polymorphic bands corresponding to the albumin fraction of the storage proteins. The relationship between bands displayed one case of allelism and four of linkage. These results should be considered as the baseline of the genetics of these proteins and suggest that they could be useful for the evaluation of the genetic variability in chestnut.Se ha efectuado una primera aproximación a la genética de las proteínas de reserva del cotiledón en castaño (Castanea sativa Mill.). Para ello, se ha evaluado la progenie resultante del cruzamiento controlado entre dos variedades locales del sur de España (Corriente y Pilonga). El análisis se ha realizado en 15 bandas polimórficas correspondientes a la fracción albúmina de las proteínas de reserva. El estudio de la combinación entre bandas ha permitido identificar un caso de alelismo y cuatro de ligamiento. Estos resultados suponen una contribución al estudio de la genética de estas proteínas y sugieren que podrían ser una herramienta útil para la evaluación de la variabilidad genética del castaño

Linear Dynamics and Control of a Kinematic Wobble–Yoke Stirling Engine

This paper presents a control systems approach for the modeling and control of a kinematic wobble–yoke Stirling engine. The linear dynamics of the Stirling engine are analyzed based on the dynamical model of the system, developed by these authors. We show that the Stirling engine can be viewed as a closed–loop system, where the feedback control law is given by the pressure variations in the pistons. Since the closed–loop system exhibits unstable dynamics, we design a pre–compensator to stabilize the displacements of the engine’s pistons, and an observer to estimate their piston velocities