Fractional generalization of memristor and higher order elements

Fractional calculus generalizes integer order derivatives and integrals. Memristor systems generalize the notion of electrical elements. Both concepts were shown to model important classes of phenomena. This paper goes a step further by embedding both tools in a generalization considering complex-order objects. Two complex operators leading to real-valued results are proposed. The proposed class of models generate a broad universe of elements. Several combinations of values are tested and the corresponding dynamical behavior is analyzed.

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.

Visualizing non-linear control system performance by means of multidimensional scaling

This paper addresses the use of multidimensional scaling in the evaluation of controller performance. Several nonlinear systems are analyzed based on the closed loop time response under the action of a reference step input signal. Three alternative performance indices, based on the time response, Fourier analysis, and mutual information, are tested. The numerical experiments demonstrate the feasibility of the proposed methodology and motivate its extension for other performance measures and new classes of nonlinearities.

Development of a platform for lean manufacturing simulation games

More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program “Lean Learning Academy,”http://www.leanlearningacademy.eu/ and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours.

Development of procedures for the simulation of atmospheric flows over complex terrain, using OpenFOAM

The main purpose of this work was the development of procedures for the simulation of atmospheric ows over complex terrain, using OpenFOAM. For this aim, tools and procedures were developed apart from this code for the preprocessing and data extraction, which were thereafter applied in the simulation of a real case. For the generation of the computational domain, a systematic method able to translate the terrain elevation model to a native OpenFOAM format (blockMeshDict) was developed. The outcome was a structured mesh, in which the user has the ability to de ne the number of control volumes and its dimensions. With this procedure, the di culties of case set up and the high computation computational e ort reported in literature associated to the use of snappyHexMesh, the OpenFOAM resource explored until then for the accomplishment of this task, were considered to be overwhelmed. Developed procedures for the generation of boundary conditions allowed for the automatic creation of idealized inlet vertical pro les, de nition of wall functions boundary conditions and the calculation of internal eld rst guesses for the iterative solution process, having as input experimental data supplied by the user. The applicability of the generated boundary conditions was limited to the simulation of turbulent, steady-state, incompressible and neutrally strati ed atmospheric ows, always recurring to RaNS (Reynolds-averaged Navier-Stokes) models. For the modelling of terrain roughness, the developed procedure allowed to the user the de nition of idealized conditions, like an uniform aerodynamic roughness length or making its value variable as a function of topography characteristic values, or the using of real site data, and it was complemented by the development of techniques for the visual inspection of generated roughness maps. The absence and the non inclusion of a forest canopy model limited the applicability of this procedure to low aerodynamic roughness lengths. The developed tools and procedures were then applied in the simulation of a neutrally strati ed atmospheric ow over the Askervein hill. In the performed simulations was evaluated the solution sensibility to di erent convection schemes, mesh dimensions, ground roughness and formulations of the k - ε and k - ω models. When compared to experimental data, calculated values showed a good agreement of speed-up in hill top and lee side, with a relative error of less than 10% at a height of 10 m above ground level. Turbulent kinetic energy was considered to be well simulated in the hill windward and hill top, and grossly predicted in the lee side, where a zone of ow separation was also identi ed. Despite the need of more work to evaluate the importance of the downstream recirculation zone in the quality of gathered results, the agreement between the calculated and experimental values and the OpenFOAM sensibility to the tested parameters were considered to be generally in line with the simulations presented in the reviewed bibliographic sources.

Desenvolvimento de apoio à decisão operacional – previsão de curto prazo de geração distribuída de tecnologia eólica ligada à RND

No contexto da penetração de energias renováveis no sistema elétrico, Portugal ocupa uma posição de destaque a nível mundial, muito devido à produção de eólica. Com um sistema elétrico com forte presença de fontes de energia renováveis, novos desafios surgem, nomeadamente no caso da energia eólica pela sua imprevisibilidade e volatilidade. O recurso eólico embora seja ilimitado não é armazenável, surgindo assim a necessidade da procura de modelos de previsão de produção de energia elétrica dos parques eólicos de modo a permitir uma boa gestão do sistema. Nesta dissertação apresentam-se as contribuições resultantes de um trabalho de pesquisa e investigação sobre modelos de previsão da potência elétrica com base em valores de previsões meteorológicas, nomeadamente, valores previstos da intensidade e direção do vento. Consideraram-se dois tipos de modelos: paramétricos e não paramétricos. Os primeiros são funções polinomiais de vários graus e a função sigmoide, os segundos são redes neuronais artificiais. Para a estimação dos modelos e respetiva validação, são usados dados recolhidos ao longo de dois anos e três meses no parque eólico do Pico Alto de potência instalada de 6 MW. De forma a otimizar os resultados da previsão, consideram-se diferentes classes de perfis de produção, definidas com base em quatro e oito direções do vento, e ajustam-se os modelos propostos em cada uma das classes. São apresentados e discutidos resultados de uma análise comparativa do desempenho dos diferentes modelos propostos para a previsão da potência.