Phase equilibrium studies in the "MnO"-Al2O3-SiO2 system

Phase relations and the liquidus surface in the system "MnO"-Al2O3-SiO2 at manganese-rich alloy saturation have been investigated in the temperature range from 1373 to 1773 K. This system contains the primary-phase fields of tridymite and cristobalite (SiO2); mullite (3Al(2)O(3).2SiO(2)); corundum (Al2O3); galaxite (MnO.Al2O3); manganosite (MnO); tephroite (2MnO.SiO2); rhodonite (MnO.SiO2); spessartine (3MnO.Al2O3.SiO2); and the compound MnO.Al2O3.2SiO(2).

Phase equilibrium data and liquidus for the system "MnO"-CaO-(Al2O3+SiO2) at Al2O3/SiO2 of 0.41

Phase-equilibrium data and the liquidus for the system. "MnO"-CaO-(Al2O3-SiO2) at a manganese-rich alloy saturation have been determined in the temperature range from 1423 to 1723 K. The results are presented in the form of a pseudoternary section "MnO"-CaO-(Al2O3 + SiO2) with an Al2O3/SiO2 weight ratio of 0.41. The following primary phases are present in the range of conditions investigated:, 3Al(2)O(3).2SiO(2); SiO2; MnO.Al2O3-2SiO(2); (Mn,Ca)O.SiO2; 2(Mn,Ca)O.SiO2; MnO.Al2O3; (Mn,Ca)O; alpha-2CaO.SiO2; alpha'-2CaO.SiO2; 2CaO.Al2O3.SiO2; CaO.SiO2, and CaO.Al2O3.2SiO(2). The presence of alumina in this system is shown to have a significant effect on the liquidus compared to the system "MnO"-CaO-SiO2, leading to, the stabilization of the anorthite and gehlenite phases.

Activation energy distribution of thermal annealing of a bituminous coal

A bituminous coal was pyrolyzed in a nitrogen stream in an entrained flow reactor at various temperatures from 700 to 1475 degreesC. Char samples were collected at different positions along the reactor. Each collected sample was oxidized nonisothermally in a TGA for reactivity determination. The reactivity of the coal char was found to decrease rapidly with residence time until 0.5 s, after which it decreased only slightly. On the bases of the reactivity data at various temperatures, a new approach was utilized to obtaining the true activation energy distribution function for thermal annealing without the assumption of any distribution function form or a constant preexponential factor. It appears that the true activation energy distribution function consists of two separate parts corresponding to different temperature ranges, suggesting different mechanisms in different temperature ranges. Partially burnt coal chars were also collected along the reactor when the coal was oxidized in air at various temperatures from 700 to 1475 degreesC. The collected samples were analyzed for the residual carbon content and the specific reaction rate was estimated. The characteristic time of thermal deactivation was compared with that of oxidation under realistic conditions. The characteristic times were found to be close to each other, indicating the importance of thermal deactivation during combustion of the coal studied.

Influence of growth temperature and carrier flux on the structure and transport properties of highly oriented CrO2 on Al2O3 (0001)

In this work we report on the structure and magnetic and electrical transport properties of CrO2 films deposited onto (0001) sapphire by atmospheric pressure (AP)CVD from a CrO3 precursor. Films are grown within a broad range of deposition temperatures, from 320 to 410 degrees C, and oxygen carrier gas flow rates of 50-500 seem, showing that it is viable to grow highly oriented a-axis CrO2 films at temperatures as low as 330 degrees C i.e., 60-70 degrees C lower than is reported in published data for the same chemical system. Depending on the experimental conditions, growth kinetic regimes dominated either by surface reaction or by mass-transport mechanisms are identified. The growth of a Cr2O3 interfacial layer as an intrinsic feature of the deposition process is studied and discussed. Films synthesized at 330 degrees C keep the same high quality magnetic and transport properties as those deposited at higher temperatures.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Efeito do teor em Y2O3 nos catalisadores suportados de 8%Ni/α-Al2O3 durante a reação de oxidação parcial do Metano para produção de Hidrogénio

Neste trabalho avaliou-se o desempenho de cinco catalisadores de Níquel suportados em α-Alumina, com diferentes teores em Ítria, durante a reação de Oxidação Parcial do Metano para a produção de Hidrogénio: 8%Ni/α-Al2O3, 8%Ni/2%Y2O3.α-Al2O3, 8%Ni/2,5%Y2O3.α-Al2O3, 8%Ni/5%Y2O3.α-Al2O3 e 8%Ni/Y2O3. Foram realizados testes catalíticos numa Unidade de Reação acoplada a um equipamento de análise, microGC. A reação decorreu à temperatura de 800 °C, num reator laboratorial de quartzo, durante 18 horas, com uma mistura pura de CH4 e O2 (Condição Concentrada). Os resultados demonstraram um aumento de atividade para os catalisadores de suporte misto com maior teor em Y2O3. Usando o mesmo procedimento, a reação de OPM foi realizada também para outra mistura reacional de CH4 e O2, mas agora diluída em Hélio (Condição Diluída). Estes resultados permitiram avaliar a velocidade de reação e a atividade dos catalisadores (TOF), para diferentes valores de temperatura, numa situação inicial de ausência de coque. Numa segunda etapa, avaliou-se o desempenho dos mesmos materiais durante 2 horas de reação à temperatura constante de 800 ℃. Finalmente, através da técnica de caraterização de XPS, identificaram-se as espécies presentes na superfície dos catalisadores. Os resultados sugerem que há formação de um composto intermediário NiYO3 formado entre o metal e o promotor Y2O3, conferindo atividade e estabilidade aos catalisadores e reduzindo a deposição de coque. O catalisador com maior teor em Y2O3 (8%Ni/5%Y2O3.α-Al2O3) foi o mais beneficiado com a adição do promotor, demonstrando melhor desempenho para a produção de H2 na Reação de Oxidação Parcial do Metano.

Evolution of the surface plasmon resonance of Au:TiO2 nanocomposite thin films with annealing temperature

This paper reports on the changes in the structural and morphological features occurring in a particular type of nanocomposite thin-film system, composed of Au nanoparticles (NPs) dispersed in a host TiO2 dielectric matrix. The structural and morphological changes, promoted by in-vacuum annealing experiments of the as-deposited thin films at different temperatures (ranging from 200 to 800 C), resulted in a well-known localized surface plasmon resonance (LSPR) phenomenon, which gave rise to a set of different optical responses that can be tailored for a wide number of applications, including those for optical-based sensors. The results show that the annealing experiments enabled a gradual increase of the mean grain size of the Au NPs (from 2 to 23 nm), and changes in their distributions and separations within the dielectric matrix. For higher annealing temperatures of the as-deposited films, a broad size distribution of Au NPs was found (sizes up to 100 nm). The structural conditions necessary to produce LSPR activity were found to occur for annealing experiments above 300 C, which corresponded to the crystallization of the gold NPs, with an average size strongly dependent on the annealing temperature itself. The main factor for the promotion of LSPR was the growth of gold NPs and their redistribution throughout the host matrix. On the other hand, the host matrix started to crystallize at an annealing temperature of about 500 C, which is an important parameter to explain the shift of the LSPR peak position to longer wavelengths, i.e. a red-shift.

Thin films composed of gold nanoparticles dispersed in a dielectric matrix: the influence of the host matrix on the optical and mechanical responses

Gold nanoparticles were dispersed in two different dielectric matrices, TiO2 and Al2O3, using magnetron sputtering and a post-deposition annealing treatment. The main goal of the present work was to study how the two different host dielectric matrices, and the resulting microstructure evolution (including both the nanoparticles and the host matrix itself) promoted by thermal annealing, influenced the physical properties of the films. In particular, the structure and morphology of the nanocomposites were correlated with the optical response of the thin films, namely their localized surface plasmon resonance (LSPR) characteristics. Furthermore, and in order to scan the future application of the two thin film system in different types of sensors (namely biological ones), their functional behaviour (hardness and Young's modulus change) was also evaluated. Despite the similar Au concentrations in both matrices (~ 11 at.%), very different microstructural features were observed, which were found to depend strongly on the annealing temperature. The main structural differences included: (i) the early crystallization of the TiO2 host matrix, while the Al2O3 one remained amorphous up to 800 °C; (ii) different grain size evolution behaviours with the annealing temperature, namely an almost linear increase for the Au:TiO2 system (from 3 to 11 nm), and the approximately constant values observed in the Au:Al2O3 system (4–5 nm). The results from the nanoparticle size distributions were also found to be quite sensitive to the surrounding matrix, suggesting different mechanisms for the nanoparticle growth (particle migration and coalescence dominating in TiO2 and Ostwald ripening in Al2O3). These different clustering behaviours induced different transmittance-LSPR responses and a good mechanical stability, which opens the possibility for future use of these nanocomposite thin film systems in some envisaged applications (e.g. LSPR-biosensors).