Role of abrasive material on micro-abrasion wear tests

Micro-abrasion wear tests with ball-cratering configuration are widely used. Sources of variability are already studied by different authors and conditions for testing are parameterized by BS EN 1071-6: 2007 standard which refers silicon carbide as abrasive. However, the use of other abrasives is possible and allowed. In this work, ball-cratering wear tests were performed using four different abrasive particles of three dissimilar materials: diamond, alumina and silicon carbide. Tests were carried out under the same conditions on a steel plate provided with TiB2 hard coating. For each abrasive, five different test durations were used allowing understanding the initial wear phenomena. Composition and shape of abrasive particles were investigated by SEM and EDS. Scar areas were observed by optical and electronic microscopy in order to understand the wear effects caused by each of them. Scar geometry and grooves were analyzed and compared. Wear coefficient was calculated for each situation. It was observed that diamond particles produce well-defined and circular wear scars. Different silicon carbide particles presented dissimilar results as consequence of distinct particle shape and size distribution.

Influence of the abrasive particles size in the micro-abrasion wear tests of TiAlSiN thin coatings

Ball rotating micro-abrasion tribometers are commonly used to carry out wear tests on thin hard coatings. In these tests, different kinds of abrasives were used, as alumina (Al2O3), silicon carbide (SiC) or diamond. In each kind of abrasive, several particle sizes can be used. Some studies were developed in order to evaluate the influence of the abrasive particle shape in the micro-abrasion process. Nevertheless, the particle size was not well correlated with the material removed amount and wear mechanisms. In this work, slurry of SiC abrasive in distilled water was used, with three different particles size. Initial surface topography was accessed by atomic force microscopy (AFM). Coating hardness measurements were performed with a micro-hardness tester. In order to evaluate the wear behaviour, a TiAlSiN thin hard film was used. The micro-abrasion tests were carried out with some different durations. The abrasive effect of the SiC particles was observed by scanning electron microscopy (SEM) both in the films (hard material) as in the substrate (soft material), after coating perforation. Wear grooves and removed material rate were compared and discussed.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Dimensionamento de um secador em leito fluidizado para secagem de cereais

O objectivo desta tese é dimensionar um secador em leito fluidizado para secagem de cereais, nomeadamente, secagem de sementes de trigo. Inicialmente determinaram-se as condições de hidrodinâmica (velocidade de fluidização, TDH, condições mínimas de “slugging”, expansão do leito, dimensionamento do distribuidor e queda de pressão). Com as condições de hidrodinâmica definidas, foi possível estimar as dimensões físicas do secador. Neste ponto, foram realizados estudos relativamente à cinética da secagem e à própria secagem. Foi também estudado o transporte pneumático das sementes. Deste modo, determinaram-se as velocidades necessárias ao transporte pneumático e respectivas quedas de pressão. Por fim, foi realizada uma análise custos para que se soubesse o custo deste sistema de secagem. O estudo da secagem foi feito para uma temperatura de operação de 50ºC, tendo a ressalva que no limite se poderia trabalhar com 60ºC. A velocidade de operação é de 2,43 m/s, a altura do leito fixo é de 0,4 m, a qual sofre uma expansão durante a fluidização, assumindo o valor de 0,79 m. O valor do TDH obtido foi de 1,97 m, que somado à expansão do leito permite obter uma altura total da coluna de 2,76 m. A altura do leito fixo permite retirar o valor do diâmetro que é de 0,52 m. Verifica-se que a altura do leito expandido é inferior à altura mínima de “slugging” (1,20 m), no entanto, a velocidade de operação é superior à velocidade mínima de “slugging” (1,13 m/s). Como só uma das condições mínimas é cumprida, existe a possibilidade da ocorrência de “slugging”. Finalmente, foi necessário dimensionar o distribuidor, que com o diâmetro de orifício de 3 mm, valor inferior ao da partícula (3,48 mm), permite a distruibuição do fluido de secagem na coluna através dos seus 3061 orifícios. O inicio do estudo da secagem centrou-se na determinação do tempo de secagem. Além das duas temperaturas atrás referidas, foram igualmente consideradas duas humidades iniciais para os cereais (21,33% e 18,91%). Temperaturas superiores traduzem-se em tempos de secagem inferiores, paralelamente, teores de humidade inicial inferiores indicam tempos menores. Para a temperatura de 50ºC, os tempos de secagem assumiram os valores de 2,8 horas para a 21,33% de humidade e 2,7 horas para 18,91% de humidade. Foram também tidas em conta três alturas do ano para a captação do ar de secagem, Verão e Inverno representando os extremos, e a Meia- Estação. Para estes três casos, foi possível verificar que a humidade específica do ar não apresenta alterações significativas entre a entrada no secador e a corrente de saída do mesmo equipamento, do mesmo modo que a temperatura de saída pouco difere da de entrada. Este desvio de cerca de 1% para as humidades e para as temperaturas é explicado pela ausência de humidade externa nas sementes e na pouca quantidade de humidade interna. Desta forma, estes desvios de 1% permitem a utilização de uma razão de reciclagem na ordem dos 100% sem que o comportamento da secagem se altere significativamente. O uso de 100% de reciclagem permite uma poupança energética de cerca de 98% no Inverno e na Meia-Estação e de cerca de 93% no Verão. Caso não fosse realizada reciclagem, seria necessário fornecer à corrente de ar cerca de 18,81 kW para elevar a sua temperatura de 20ºC para 50ºC (Meia-Estação), cerca de 24,67 kW para elevar a sua temperatura de 10ºC para 50ºC (Inverno) e na ordem dos 8,90 kW para elevar a sua temperatura dos 35ºC para 50ºC (Verão). No caso do transporte pneumático, existem duas linhas, uma horizontal e uma vertical, logo foi necessário estimar o valor da velocidade das partículas para estes dois casos. Na linha vertical, a velocidade da partícula é cerca de 25,03 m/s e cerca de 35,95 m/s na linha horizontal. O menor valor para a linha vertical prende-se com o facto de nesta zona ter que se vencer a força gravítica. Em ambos os circuitos a velocidade do fluido é cerca de 47,17 m/s. No interior da coluna, a velocidade do fluido tem o valor de 10,90 m/s e a velocidade das partículas é de 1,04 m/s. A queda de pressão total no sistema é cerca de 2408 Pa. A análise de custos ao sistema de secagem indicou que este sistema irá acarretar um custo total (fabrico mais transporte) de cerca de 153035€. Este sistema necessita de electricidade para funcionar, e esta irá acarretar um custo anual de cerca de 7951,4€. Embora este sistema de secagem apresente a possibilidade de se realizar uma razão de reciclagem na ordem dos 100% e também seja possível adaptar o mesmo para diferentes tipos de cereais, e até outros tipos de materiais, desde que possam ser fluidizados, o seu custo impede que a realização deste investimento não seja atractiva, especialmente tendo em consideração que se trata de uma instalação à escala piloto com uma capacidade de 45 kgs.

Biofiltration of Air/Styrene and Air/Styrene/Acetone mixtures in a bubble column reactor

The goal of this work was the treatment of polluted waste gases in a bubble column reactor (BCR), in order to determinate the maximum value of reactor’s efficiency (RE), varying the inlet concentration (C in) of the pollutants. The gaseous mixtures studied were: (i) air with styrene and (ii) air with styrene and acetone. The liquid phase used to contain the biomass in the reactor was a basal salt medium (BSM), fundamental for the microorganisms’ development. The reactor used in this project consists of a glass column of 620mm height and inside diameter 75mm. In all essays there were continually measured: pH, dissolved oxygen and liquid’s temperature. Temperature and pH were controlled (T=24ºC, 7.0 ≤ pH ≤ 7.7). In all experiments the liquid volume (including the biomass) used in the reactor was kept constant (1.5L) as well as the total gas flowrate (1 L/min). Concerning the goal of the work, some parameters were calculated: the organic load (OL), removal efficiency (RE), elimination capacity (EC), biomass concentration (xf) and dry biomass concentration (Xdw). In a first series of experiments, the gas mixture used was air with styrene, varying its concentration from 191 mg.m-3 to 6500 mg.m-3.It was concluded that the RE maximum value (97%) was obtained for C in Sty = 4200 mg.m-3. For the maximum tested value of C in Sty, RE obtained was 20%. In a second step, the gaseous mixture included acetone, varying C in Sty between 225 mg.m-3 and 2659 mg.m-3 and C in Ac between 153mg.m-3 and 1389 mg.m-3. The aim of these tests was the determination of C in Ac for which RE was maximum, obtaining C in Ac = 750 mg.m-3. A third series of experiments was performed, in which C in Ac was maintained equal to that value and C in Sty was varied until higher values (5422 mg.m-3). RE maximum values obtained in this last series were 100% for styrene and 40% for acetone. One important conclusion is the fact that the microorganisms available degrade better styrene than acetone. On the ambit of this study, it was possible to identify the species available in biomass: Xanthobacter antotrophicus py2, Enterobacter aerogenes, Nocardia, Corynebacterium Spp., Rhodococcus rhodochrous e Pseudomonas Sp.

Air pollution from traffic emissions in Oporto, Portugal: health and environmental implications

Air pollution represents a serious risk not only to environment and human health, but also to historical heritage. In this study, air pollution of the Oporto Metropolitan Area and its main impacts were characterized. The results showed that levels of CO, PM10 and SO2 have been continuously decreasing in the respective metropolitan area while levels of NOx and NO2 have not changed significantly. Traffic emissions were the main source of the determined polycyclic aromatic hydrocarbons (PAHs; 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in air of the respective metropolitan area. The mean concentration of 18 PAHs in air was 69.9±39.7 ng m−3 with 3–4 rings PAHs accounting for 75% of the total ΣPAHs. The health risk analysis of PAHs in air showed that the estimated values of lifetime lung cancer risks considerably exceeded the health-based guideline level. Analytical results also confirm that historical monuments in urban areas act as passive repositories for air pollutants present in the surrounding atmosphere. FTIR and EDX analyses showed that gypsum was the most important constituent of black crusts of the characterized historical monument Monastery of Serra do Pilar classified as “UNESCO World Cultural Heritage”. In black crusts, 4–6 rings compounds accounted approximately for 85% of ΣPAHs. The diagnostic ratios confirmed that traffic emissions were the major source of PAHs in black crusts; PAH composition profiles were very similar for crusts and PM10 and PM2.5.

Remediation efficiency of vapour extraction of sandy soils contaminated with cyclohexane: influence of air flow rate, water and natural organic matter content

Abstract This work reports the analysis of the efficiency and time of soil remediation using vapour extraction as well as provides comparison of results using both, prepared and real soils. The main objectives were: (i) to analyse the efficiency and time of remediation according to the water and natural organic matter content of the soil; and (ii) to assess if a previous study, performed using prepared soils, could help to preview the process viability in real conditions. For sandy soils with negligible clay content, artificially contaminated with cyclohexane before vapour extraction, it was concluded that (i) the increase of soil water content and mainly of natural organic matter content influenced negatively the remediation process, making it less efficient, more time consuming, and consequently more expensive; and (ii) a previous study using prepared soils of similar characteristics has proven helpful for previewing the process viability in real conditions.

Entropy diversity in multi-objective particle swarm optimization

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.

PAH air pollution at a Portuguese urban area: carcinogenic risks and sources identification

This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM10 and PM2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO2, PM10, NO2, CO, and O3; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ngm−3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10−6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98×10−7 in PM10 and 1.06×10−6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO2, NO2, PM10, CO, and solar radiation had positive correlation with PAHs concentrations, while O3, temperature, relative humidity, and wind speed were negatively correlated.

Demand response management in power systems using a particle swarm optimization approach

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.