Self-mated tribological systems based on multilayer micro/nanocrystalline CVD diamond coatings

The tribological response of multilayer micro/nanocrystalline diamond coatings grown by the hot filament CVD technique is investigated. These multigrade systems were tailored to comprise a starting microcrystalline diamond (MCD) layer with high adhesion to a silicon nitride (Si3N4) ceramic substrate, and a top nanocrystalline diamond (NCD) layer with reduced surface roughness. Tribological tests were carried out with a reciprocating sliding configuration without lubrication. Such composite coatings exhibit a superior critical load before delamination (130–200 N), when compared to the mono- (60–100 N) and bilayer coatings (110 N), considering ∼10 µm thick films. Regarding the friction behaviour, a short-lived initial high friction coefficient was followed by low friction regimes (friction coefficients between 0.02 and 0.09) as a result of the polished surfaces tailored by the tribological solicitation. Very mild to mild wear regimes (wear coefficient values between 4.1×10−8 and 7.7×10−7 mm3 N−1 m−1) governed the wear performance of the self-mated multilayer coatings when subjected to high-load short-term tests (60–200 N; 2 h; 86 m) and medium-load endurance tests (60 N; 16 h; 691 m).

A feedback-based decentralised coordination model for distributed open real-time systems

Moving towards autonomous operation and management of increasingly complex open distributed real-time systems poses very significant challenges. This is particularly true when reaction to events must be done in a timely and predictable manner while guaranteeing Quality of Service (QoS) constraints imposed by users, the environment, or applications. In these scenarios, the system should be able to maintain a global feasible QoS level while allowing individual nodes to autonomously adapt under different constraints of resource availability and input quality. This paper shows how decentralised coordination of a group of autonomous interdependent nodes can emerge with little communication, based on the robust self-organising principles of feedback. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The proposed protocol is general enough to be used in a wide range of scenarios characterised by a high degree of openness and dynamism where coordination tasks need to be time dependent. As the reported results demonstrate, it requires less messages to be exchanged and it is faster to achieve a globally acceptable near-optimal solution than other available approaches.

Elaboração de um projeto de uma central fotovoltaica de miniprodução e estudo de viabilidade técnica, económica e financeira

Desde o final do século XVIII, quando se iniciou a revolução industrial, o crescimento económico tem sido assente num consumo elevado de combustíveis fósseis que libertam gases com efeito de estufa. A emissão destes gases e a escassez dos combustíveis fósseis são temas que, desde as últimas duas décadas do século XX, ocupam um lugar de destaque nas agendas de política mundial. A produção de energia através de fontes renováveis surge como alternativa e poderá ser a solução para países com escassos recursos de origem fóssil, como é o caso de Portugal, minimizando também a sua dependência energética do exterior. Uma das medidas de incentivo lançada pelo Governo Português em 2007, foi a criação de um regime simplificado aplicável à microprodução descentralizada de eletricidade através de fontes de energia renováveis e de cogeração. À semelhança da maioria dos países europeus, o principal meio de promoção destes sistemas em Portugal foram as Feed-in-Tariffs, que consistem numa tarifa de venda de energia elétrica de origem renovável acima da tarifa de mercado. Estas tarifas permitiram, sobretudo, o crescimento do setor fotovoltaico em Portugal. Atualmente, o amadurecimento da tecnologia fotovoltaica, associado ao constante aumento das tarifas de energia elétrica, permite que se torne vantajosa a instalação de sistemas fotovoltaicos para autoconsumo. Neste contexto, o atual Governo Português, criou recentemente um regime jurídico aplicável à produção de eletricidade para autoconsumo. O objetivo deste trabalho é demonstrar, com base na minha experiência profissional, a metodologia de dimensionamento de uma central fotovoltaica ligada à Rede Elétrica de Serviço Público. Será utilizado como objeto de estudo um projeto constituído por 28 centrais fotovoltaicas de Miniprodução de 100 kW, dispersas por Portugal Continental, para o qual será efetuada a análise financeira do investimento. Pretende-se ainda apresentar o novo enquadramento legislativo para o Autoconsumo e Pequena Produção distribuída, detalhar as suas principais caraterísticas e efetuar um estudo económico para cada um destes regimes.

Estudo comparativo da resistência à tração de juntas adesivas de sobreposição simples e dupla

O método de união com ligações adesivas está cada vez mais a ser utilizado na conceção de estruturas mecânicas, por causa das vantagens significativas desta técnica em comparação com as ligações tradicionais. De facto, as juntas com ligação adesiva estão sob investigação intensa há bastante tempo. Entre as vantagens, destaca-se a redução de peso e possibilidade de unir diferentes materiais, incluindo compósitos, sem danificar as estruturas a ligar. Os adesivos comerciais variam desde resistentes e frágeis (por exemplo, Araldite® AV138) a menos resistentes e dúcteis (por exemplo, Araldite® 2015). Uma nova família de adesivos de poliuretano combina elevada resistência e ductilidade (por exemplo, Sikaforce® 7888). Este trabalho compara o desempenho à tração dos três adesivos supracitados, em juntas de alumínio (Al6082-T651) de sobreposição simples e dupla, com variação dos valores de comprimento de sobreposição (LO). A análise numérica de modelos de dano coesivo (MDC) foi realizada para analisar as tensões de arrancamento (oy) e as de corte (txy) na camada adesiva, para estudar a variável de dano do MDC durante o processo de rotura e para avaliar a capacidade MDC na previsão da resistência da junta. A análise da resistência e da variável de dano ajudou na compreensão das diferenças entre os adesivos no que se refere ao processo de rotura e resistência da junta. Observou-se que as juntas de sobreposição dupla apresentam uma distribuição de tensões bastante mais favorável relativamente às juntas de sobreposição simples, principalmente devido à eliminação da flexão do substrato interior. Como resultado, a resistência destas juntas foi tipicamente superior ao dobro da observada para as juntas de sobreposição simples, com exceção de algumas configurações de junta em que houve plastificação extensa ou mesmo rotura dos substratos por tração. O trabalho proposto permitiu também concluir que as previsões MDC são tipicamente precisas, e qual a família de adesivos é mais adequada para cada configuração de junta, com a clara vantagem para o Sikaforce® 7888. Como resultado deste trabalho, foram propostas diretrizes de conceção para juntas adesivas.

Structural adhesives modified with thermally expandable particles

In this study, the behaviour of two structural adhesives modified with thermally expandable particles (TEPs) was investigated as a preliminary study for further investigations on the potential of TEPs in adhesive joints. Tensile bulk tests were performed to get the tensile properties of the adhesives and TEPs-modified adhesives. In order to determine the expansion temperature of the particles while encapsulated in these particular adhesive systems, the variation of the volume of adhesive samples modified with different TEPs concentration as a function of temperature was measured. Further, the possibility of any chemical interactions between TEPs and adhesives matrix in the TEPs-modified specimens was verified by a Fourier transform infrared spectroscopy analysis. Finally, the fracture surfaces of the unmodified and TEPs-modified specimens, as well as the dispersion and the morphology of the particles, were examined by a scanning electron microscopy analysis. It was found that the stiffness of the TEPs-modified adhesives is not affected by incorporation of TEPs in the adhesives matrix, while the tensile yield strength decreased by increasing the wt% TEPs content. In applications of such particular materials (TEPs-modified adhesives), the temperature should be controlled to stay between 90°C and 120°C in order to obtain the highest expansion ratio. At a lower temperature, not all the particles will expand, and above, the TEPs will deteriorate and as a result the TEPs-modified adhesives will deteriorate.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

Self-optimization aspects for dynamic scheduling

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. At this scenario, self-optimizing arise as the ability of the agent to monitor its state and performance and proactively tune itself to respond to environmental stimuli.

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.