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  • [ November 06, 2018]

    Computational Intelligence in Smart Power Grid Management and Energy Feasibility Studies

    | Today, big data is a significant matter! This seminar will discuss research in predictive modelling with artificial intelligence. It will describe briefly big data principles, with less technical detail but a greater focus on applications and result. In application space it will provide case studies in recent papers demonstrating the merits of advanced data analytic models in real-life, particularly in energy management systems. Models considered will include, but not limited to, deep learning, extreme learning machines(极限学习机器), artificial neural network(人工神经网络), support vector machines(支持向量机器), multivariate adaptive regression spline (多元自适应回归样条)and M5 Tree, whereas model optimisation tools will include the results obtained by applying meta-heuristic feature selection (元启发式特征选择)(or ‘search’) algorithms, feature weight optimisation (or ‘add-in’) algorithms and multi-resolution tools such as empirical mode decomposition applied to model data to improve the prediction. In particular, feature selections are required to screen optimal inputs, improve the accuracy and reduce the computational burden, whereas add-in algorithms can help extract most, if not all of the predictive features from a large pool of carefully screened input variables. Empirical mode decompositions, can assist in identifying the frequency components in model inputs and addressing issues of non-stationarity, trends, jumps and periodicities present in model design data. This seminar will reveal the importance of ancillary tools in predictive modelling with applications of artificial intelligence models in energy demand management and solar energy simulations. The seminar will discuss and expect to exchange ideas and future challenges that we as, researchers, face in predictive modelling that must be considered in practical energy management models that are used in real-life simulations to design decision systems for energy management with big data analytics.
  • [ October 24, 2018]

    Defects on carbon for electrocatalysis

    | Electrocatalysis is the key for energy conversion and storage devices such as fuel cells, metal-air batteries and water splitting. The development of highly efficient and non-precious metal catalyst is extremely important. Recently, we presented a new concept of defect electrocatalysis, in which the topological defects on carbons or in oxides/compounds are the active sites for electrochemical reactions. A series of non-metal catalysts have been developed based on this new theory. Besides, the defects are such characterized points with higher energy, thus provides ideal sites to interact with non-/metal species in various sizes. The strong interactions may provide both high reactivity and stability. When the size of metal species reduces to atomic level, the general configurations are metal atoms trapped into defects according to the minimum energy theory. The coordination of the defect and atomic species plays the central role for electrocatalysis as the local electronic structures defined by this coordination determines the interaction of reactant and active sites.
  • [ October 17, 2018]

    Fluid mechanics for functional materials

    | Additive manufacturing, commonly known as 3D printing, has accelerated the development of complex, multi-scale materials. These materials can be designed to exhibit special functional properties, such as sensing, support of living cells, sound or shock absorption, or controlled expansion/shrinkage. Therefore, they are highly relevant both from a scientific and a societal point of view.

    In this talk I will discuss novel, droplet-based additive manufacturing strategies for metals, biological (living) materials, and cellular materials, in which micro-droplets or bubbles are used as modular building blocks that constitute the functional material properties. High-speed imaging proves a crucial step in the development of these processes, as it enables studying the dynamics of droplet ejection, deposition, and manipulation. Understanding these aspects is required to tune the shape, size, and constitution of the building blocks, which determine the functional properties of the deposited materials.
  • [ September 27, 2018]

    Continuous Finite- and Fixed-Time High-Order Regulators

    | It is well known that a state of a controllable linear system of an arbitrary dimension can be asymptotically driven as close to zero as necessary by means of a linear scalar feedback control. Using a continuous nonlinear scalar control law, a chain of integrators of an arbitrary dimension can be driven to the origin in finite time. Given that an arbitrary minimum phase linear system can be transformed into a chain of integrators form by using an appropriate change of variables, finite-time high-order regulators are applicable to an arbitrary minimum phase multi-dimensional linear system. A relevant problem consists in estimating the convergence (settling) time for the finite-time convergent control laws Another challenging problem is to design a fixed-time continuous control law such that a system state converges to the origin for a pre-established or fixed settling time, independently of a magnitude of initial conditions.

    The contribution of this study is twofold. First, an upper estimate of the convergence (settling) time is calculated for the finite-time convergent control algorithm that drives the state of a series of integrators to the origin. To the best of the authors’ knowledge, such an estimate is obtained for the first time. Second, a novel fixed-time continuous control law is proposed for a chain of integrators of an arbitrary dimension. Its fixed-time convergence is established and the uniform upper bound of the settling time is computed. The theoretical developments are applied to a case study of controlling a DC motor.

    Finally, an extension of the developed approach to design fixed-time observers for integrator chain systems (differentiators) is discussed and compared to a built-in Simulink differentiation technique.
  • [ September 21, 2018]

    Flame Folding and Wrinkling Factor for 2D and 3D Hydrogen-Air Flames

    | An experimental study and theoretical analysis of laminar flame propagation in spherical 3D- and planar 2D-geometries for hydrogen-air mixtures was carried out in order to investigate an effect of flame instability, a flame structure and a mechanism of initial quasi-laminar flame acceleration prior turbulent flame acceleration and DDT. The theory of laminar flames and theoretical analysis based on solution of Sivashinsky-Michelson equation was performed to explain the experimental results. It was theoretically found, that the burning velocity increased by the factor of 1.2-1.6 due to the flame instability. This value was found to be exactly proportional to the flame area amplification and well confirmed by current experimental data in 2D- and 3D-geometries. Such a flame wrinkling leads to primary flame acceleration remaining the flame of laminar structure in general.?
  • [ September 20, 2018]

    Extrapolating turbulence to higher Reynolds numbers

    | In many practical applications, the Reynolds number Re is much greater than the largest Re that can be achieved in direct numerical simulations and wind-tunnel experiments. Hence, to apply the turbulence-related results obtained in a wind tunnels or with computers, extrapolation to higher Re is needed. For the part of the flow very close to the wall such extrapolation is usually based on the classical universality hypothesis that states that near the wall the turbulent flow parameters, expressed in so-called wall units, are independent of Re. However, in recent years it was established that the large-scale structures residing further away from the wall affect the near-wall turbulence. Since these structures, if expressed in wall units, are not Re-independent, the classical universality hypothesis is not correct. Moreover, recent data indicate that as Re increases the outer large-scale structures become stronger. An outline will be given of the new technique for extrapolating statistical characteristics of near-wall turbulence from medium to higher Re, based on the recently developed quasi-steady quasi-homogeneous (QSQH) theory. The QSQH theory is an alternative to the classical universality hypothesis. The QSQH theory provided relationships between many turbulence parameters previously thought to be unrelated, including for example those entering the well-known empirical formula for the modulation of near-wall turbulence by outer structures, and threw a new light on the Re-dependence of the logarithmic law constants. An overview of the theory will be followed by an explanation of the extrapolation method and examples of its application. The lecture will be concluded by a description of a sensor probe designed for applying the extrapolating technique in experiments.
  • [ July 07, 2018]

    Nanofluidics: A New Arena for Materials Science

    | A significant growth of research in nanofluidics is achieved over the past decade, but the field is still facing considerable challenges toward the transition from the current physics-centered stage to the next application-oriented stage. To conquer these challenges, we established a technology called “nano-in-nano integration”, which allows the integration of a variety of functional (eg., fluidic, electrical, optical, thermal, magnetic, chemical and biological) components in tiny nanofluidic channels. The nano-in-nano integration technology opens up a new arena to exploit chemistry, biology, and materials science at femtoliter, attoliter, single-nanoparticle, and single-molecule scales through nanofluidics, as demonstrated by us in our recent works which will be presented in this talk.
  • [ July 03, 2018]

    Mechano-adaptable Materials for Flexible and Conformal Electronics

    | Smart wearable sensors not only enrich daily lives by providing enhanced smart functions, but also provide health information by monitoring body conditions. For example, patchable sensors have the potential to better interface with human skin, thus improving the sensitivity of detection of health indicators. However, the crucial aspects toward the advancement of such sensors include the development of novel mechanically durable materials, flexible and stretchable substrates, deformable electrodes and circuits, bio-stable and bio-compatible, and so on. In this talk, I will present our latest progress fabricating conformal sensors based on the rational design of structural materials, individual devices development, and integration.
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