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  • [ Janurary 07, 2019]

    Turbulent/non-turbulent interfaces and their relation to turbulent entrainment

    | In many relevant flow cases, such as in jets or turbulent boundary layers, turbulent regions of the flow are bounded by non-turbulent fluid. The interface between such regions, the so-called turbulent/non- turbulent interface (TNTI) is known to remain sharp and well-defined even after long times. Here, we investigate how processes at the TNTI are related to turbulent entrainment, i.e. the incorporation of previously non-turbulent fluid into the turbulent flow. We show that turbulent entrainment is a viscous, small-scale process that is amplified by interface contortions across a range of scales. We also elucidate how these processes change in the presence of a stable stratification across the TNTI.
  • [ December 18, 2018]

    A Global Perspective on Energy Challenges and Mechanics

    | Based in Aberdeen, the “Energy Capital of Europe", from our recent research collaborations with the energy industries, and the experience chairing the 1st-9th International Symposium on Energy, this talk explores issues related to energy challenges and mechanics from a global perspective. The aim is to get a complete view of energy-related problems. The following topics are covered:
    - Life on earth currently faces a threat on a genuinely global scale.
    - Asset life extension.
    - The DESERTEC idea was initially developed in Germany for power production at a large scale, making use of solar energy in the deserts of North Africa with the option to transport a significant fraction of power to Europe.
    - Fusion energy is among the most environmentally friendly sources of energy.
  • [ December 18, 2018]

    Highly efficient differentiation of human iPSCs into functional endothelial cells using ETV2 mRNA

    | Current protocols to differentiate human induced pluripotent stem cells (h-iPSCs) into endothelial cells (h-iECs) lack reliability. Here we describe a method for rapid, consistent and highly efficient generation of h-iECs from h-iPSCs. The protocol entails delivery of modified mRNA encoding the transcription factor ETV2 at the intermediate mesodermal stage of differentiation. This approach reproducibly differentiated thirteen diverse h-iPSC lines into h-iECs with exceedingly high efficiency. In contrast, differentiation with the standard protocol, which relies on endogenous ETV2, was inefficient and notably inconsistent. Our method generated h-iECs that were functionally competent in many respects, including ability to form perfused vascular networks in vivo. Importantly, timely activation of ETV2 was critical and bypassing the mesodermal stage produced putative h-iECs with reduced expansion potential and that lacked ability to form functional vessels. Our protocol could have broad application in regenerative medicine and reliably provide an unlimited number of autologous h-iECs for vascular therapies.
  • [ December 14, 2018]

    Data-Driven Control of a Production System by Using Marking-Dependent Threshold Policy

    | This study is motivated by the need of developing effective data-driven control methods for production systems. Our aim is answering the following research questions: How can we control production by using partial information (markings) obtained from a production system?; How can the control parameters be determined by using the real-time data? How well does the data-driven control policy perform?; and How can the markings be selected for a given system?
    In order to analyze the performance of a production system controlled with partial information, we introduce the Marked Markov Arrival Process (MMAP) framework to model a system that generates different signals, referred as markings, based on the system status. We then propose a marking-dependent threshold policy to control the system. An analytical method that is based on a matrix analytical approach is developed to analyze a production/inventory system with MMAP information and demand arrivals and a partially observable production time process modeled as a MMAP. A mathematical programming formulation is used to determine the optimal thresholds of the control policy based on the matrix geometric model of the system. We then present a joint simulation and optimization (JSO) approach to determine the parameters of the threshold policy by using the shop-floor data collected from the system.
    We test these methods on two production systems.
    We show that using a marking-dependent control policy together with a JSO approach that determines the policy parameters works effectively as a data-driven control method for manufacturing.
  • [ December 05, 2018]

    Emulsion and foam stability: one drop and bubble at a time

    | The stability of emulsions and foams are affected by a number of physical processes. As thin liquid films surrounding bubbles and drops drain, film rupture can occur, leading to coalescence and to coarsening. A common approach to appreciating stability in these systems is to create a bulk emulsion or foam and to follow the rate of creaming (for an emulsion) or collapse and drainage (for a foam). In this lecture, an alternative approach is described whereby individual bubbles and drops are monitored as they approach a fluid/fluid interface until coalescence ensues. These measurements utilize a newly developed instrument, the Dynamic Fluid Film Interferometer (DFI) where draining film thicknesses can be measured in space and time as well as the pressure drop (Laplace pressure) across the interface. Application of the DFI to study two problems is presented: (1) coalescence of oil/water emulsions in the presence of asphaltenes and (2) antifoaming of lubricating oils.
  • [ December 03, 2018]

    Screening and Tomographic Reconstruction of Defects by Structural Guided Ultrasonic Waves

    | Detecting and quantifying damages in large structures is of growing interest in various industries. Conventional ultrasonic methods are tedious and expensive, especially for inaccessible areas. Ultrasonic structural guided wave offers an attractive alternative for the rapid inspection of defects from a remote position in a large structure. In this talk, two interesting applications of ultrasonic guide waves will be discussed: defect screening in structural features such as weld, stiffeners and bends, as well as defect characterization using guided wave tomographic approach. A numerical forward model is used to predict the scattering of guided wave through defects, and an iterative inverse model is developed to reconstruct the defect profile. The imaging algorithm allows higher order diffraction and scattering to be considered in its numerical solver, thus can provide accurate inversion results. Despite two guided wave applications, recent progress in the research of acoustic metamaterial and laser ultrasound will also be shared in the talk.
  • [ November 28, 2018]

    Control of “Valley” Properties in 2D Materials by Magnetism

    | Exploiting the “valley” degree of freedom to store and manipulate information is an emerging direction of condensed matter physics, and provides a novel paradigm for future electronics. Valley is the local extremum in the electronic band structure. Transition metal dichalcogenides (TMDC), such as MoS2, WS2 and WSe2, are semiconductor analogy of graphite with atomic layers bonded together by Van der Waals interactions. A monolayer TMDC with broken inversion symmetry possesses two degenerate valleys that can be selectively excited by circularly polarized light. Breaking the valley degeneracy allows convenient control of valley degree of freedom. This can be done by applying an external magnetic field to Zeeman split the band edge states. We demonstrate that the valley properties can be controlled by magnetism. We show that valley splitting can be enhanced by more than an order of magnitude, utilizing the interfacial exchange field from a ferromagnetic substrate. We further show that transition metal doped TMDs demonstrate ferromagnetism with their magnetization tunable by light. These approaches open up new avenue for valley control forvalleytronics applications.
  • [ November 08, 2018]

    Reconfigurable Systems for Manufacturing and Automotive Applications

    | We live in an engineered world, where mechatronics is enabling the design of smart systems in which knowledge about the system can be embedded in the system itself. The design of such smart systems requires new engineering design methods, such as reconfiguration, co-design and component swapping modularity, which are introduced here in the context of applications in manufacturing and automotive systems. Reconfigurable manufacturing systems (RMS) provide exactly the manufacturing functionality and capacity needed, exactly when needed. Examples are presented to highlight the role that dynamics and control plays in designing systems to be more reconfigurable. These examples include optimal capacity management in an RMS, dynamics of a reconfigurable machine tool, and a reconfigurable stamping control system. Methods for combined design, or co-design, of an artifact and its controller and for component swapping modularity in controller design, are also presented with applications to active suspension design, and controller design for a plug-in hybrid electric vehicle, respectively.
  • [ 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.
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