989 resultados para PARTICLE PRODUCTION


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This study uses the process simulator ASPEN Plus and Life Cycle Assessment (LCA) to compare three process design alternatives for biodiesel production from waste vegetable oils that are: the conventional alkali-catalyzed process including a free fatty acids (FFAs) pre-treatment, the acid-catalyzed process, and the supercritical methanol process using propane as co-solvent. Results show that the supercritical methanol process using propane as co-solvent is the most environmentally favorable alternative. Its smaller steam consumption in comparison with the other process design alternatives leads to a lower contribution to the potential environmental impacts (PEI’s). The acid-catalyzed process generally shows the highest PEI’s, in particular due to the high energy requirements associated with methanol recovery operations.

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Dissertação para obtenção do grau de Mestre em Engenharia Química

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Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

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This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

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CYCLOTech is a high-tech Project, related with an innovative method for direct production of a radioactive pharmaceutical, used in excess of 85% of 35 Million Nuclear Medicine procedures done yearly, worldwide, representing globally more than 3 Billion Euros. The CYCLOTech team has developed an innovative proprietary methodology based on the use of Cyclotron Centers, formally identified as the Clients (actually, there are around 450 of this Centers in function worldwide), to directly produce and deliver the radiopharmaceutical to the final users, at the Hospitals and other Health Institutions (estimating at around 25.000, worldwide). The investment still need to finish Research and Technological Development (RTD), Industrial, Regulatory and Intellectual Property Rights (IPR) issues and allow the introduction in the Market is 4,35 M€, with a Payback of 3 years, with an Investment Return Rate (IRR) of 81,7% and a Net Present Value (NPV) of 60.620.525€ (in 2020).

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The interest in zero-valent iron nanoparticles has been increasing significantly since the development of a green production method in which extracts from natural products or wastes are used. However, this field of application is yet poorly studied and lacks knowledge that allows the full understanding of the production and application processes. The aim of the present work was to evaluate the viability of the utilization of several tree leaves to produce extracts which are capable of reducing iron(III) in aqueous solution to form nZVIs. The quality of the extracts was evaluated concerning their antioxidant capacity. The results show that: i) dried leaves produce extracts with higher antioxidant capacities than non-dried leaves, ii) the most favorable extraction conditions (temperature, contact time, and volume:mass ratio) were identified for each leaf, iii) with the aim of developing a green, but also low-cost,method waterwas chosen as solvent, iv) the extracts can be classified in three categories according to their antioxidant capacity (expressed as Fe(II) concentration): >40 mmol L−1; 20–40 mmol L−1; and 2–10 mmol L−1; with oak, pomegranate and green tea leaves producing the richest extracts, and v) TEManalysis proves that nZVIs (d=10–20 nm) can be produced using the tree leaf extracts.

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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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This paper studies a discrete dynamical system of interacting particles that evolve by interacting among them. The computational model is an abstraction of the natural world, and real systems can range from the huge cosmological scale down to the scale of biological cell, or even molecules. Different conditions for the system evolution are tested. The emerging patterns are analysed by means of fractal dimension and entropy measures. It is observed that the population of particles evolves towards geometrical objects with a fractal nature. Moreover, the time signature of the entropy can be interpreted at the light of complex dynamical systems.

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This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.

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Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

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Fungi on crops produce mycotoxins in the field, during handling, and in storage. Exposure of animals and humans are usually through consumption of contaminated feedstuffs or foods. Molds can grow and mycotoxins can be produced either pre-harvest or post-harvest, during storage, transport, processing, or feeding. Worldwide, approximately 25% of crops are affected by mycotoxins annually. Because of this is possible to concluded that mycotoxins occur frequently in a variety of feedstuffs that are given to animals causing several effects: subclinical losses in performance, increases the incidence of disease and reduced reproductive performance. Aim of study: A study was developed intending to know environmental fungal contamination in a Portuguese feed production unit. Corn, wheat and soybeans were the most common cereals used in the feed production.

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The most common scenario in occupational settings is the co-exposure to several risk factors. This aspect has to be considered in the risk assessment process because can alter the toxicity and the health effects when dealing with a co-exposure to two or more chemical agents. A study was developed aiming to elucidate if there is occupational co-exposure to aflatoxin B1 (AFB1) and ochratoxin (OTA) in Portuguese swine production. To assess occupational exposure to both mycotoxins, a biomarker of internal dose was used. The same blood samples from workers of seven swine farms and controls were consider to measure AFB1 and OTA. Twenty one workers (75%) showed detectable levels of AFB1 with values ranging from <1 ng/ml to 8.94 ng/ml and with significantly higher concentration when compared with controls. In the case of OTA, there wasn't found a statistical difference between workers and controls and the values for workers group ranged from 0.34 ng/ml to 3.12 ng/ml and 1.76 ng/ml to 3.42 ng/ml for control group. The results suggest that occupational exposure to AFB1 occurs. However, in the case of OTA results, seems that food consumption plays an important role in both groups exposure. The results claim attention for the possible implications on health of this co-exposure.

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Contrary to fungi, exposure to mycotoxins is not usually identified as a risk factor present in occupational settings. This is probably due to the inexistence of limits regarding concentration of airborne mycotoxins, and also due to the fact that these compounds are rarely monitored in occupational environments. Aflatoxin B1 (AFB1) is the most prevalent aflatoxin and is associated with carcinogenicity, teratogenicity, genotoxicity and immunotoxicity but only a few studies examined exposure in occupational settings. Workers can be exposed to high airborne levels during certain operations in specific occupational settings. Aim of study: The study aimed to assess exposure to AFB1 in three settings: poultry, swine production and waste management.

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Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.