1,249 research outputs found

    Monitoring soil moisture dynamics and energy fluxes using geostationary satellite data

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    High Performance Synchronous Reluctance Machines: Design and Applications

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    As one of the oldest machine topologies, the concept of synchronous reluctance (REL) machine can be traced back as early as 1900s. In the last 20 years, particularly, the REL machines have attracted more and more attention in both academic and industrial fields. Without permanent magnets and rotor bars, the rotor construction of the REL machine is more robust than either permanent magnet (PM) machines or induction machines (IMs). In addition, it achieves the merits of low cost, low maintenance, and high reliability. All these features reveal the REL machine to be an attractive alternative to the widely used machine topologies. Therefore, the investigation of REL machines is essential, and specific applications will be of great interest. In this thesis, the design and analysis of high performance REL machines are developed and discussed. Furthermore, two particular applications are investigated: REL motors for electric vehicle (EV) applications and self-excited reluctance generators (SERG) for isolated wind applications. To start with, the transversely-laminated anisotropy rotor type with multiple flux-barriers is chosen to be designed and analyzed. More specifically, a detailed parametric analysis of this kind of rotor geometry is carried out, which aims to suggest an automatic drawing and simulating procedure. The shape of flux-barriers is selected to achieve both high d-axis inductance and low q-axis inductance. Methods to properly design the geometry of barrier ends and PMs are adopted. Some tuning steps are suggested in order to achieve the high performance design. Such a procedure is then used to rapidly analyze the impact of some rotor parameters on the machine performance, in order to provide a guideline for the preliminary design of the REL machine. After that, as a practical example, a REL motor according to the dimension of a commercial motor is designed. Certain design procedures are followed, and optimization is also carried out. The performance comparisons between the optimized REL motor and the commercial product are given. Merits and defects of the REL machine for EV application are highlighted. The study on SERG starts with the recognition of the steady-state performance, both analytically and experimentally. The conditions related to successful self-excitation in SERG, such as required capacitance, rotor residual magnetism, rotor acceleration and pre-charging capacitors, are investigated. The possibility to adopt self-excited PM-assisted reluctance generator is also dealt with, and the performance comparison with SERG is made. The effect of some design parameters on the performance of the PMAREL generator is analyzed. Referring to wind applications, the method to maintain the generated voltage constant at variable speeds is proposed. Finally, the prediction of the "optimal capacitor and resistor combination" that achieves the maximum utilization of the mechanical power produced by the wind turbine will be presented

    Structure and properties of Mn4Cl9: An antiferromagnetic binary hyperhalogen

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    Calculations based on density functional theory show that the structure of Mn4Cl9 anion is that of a Mn atom at the core surrounded by three MnCl3 moieties. Since Mn is predominantly divalent and MnCl3 is known to be a superhalogen with a vertical detachment energy (VDE) of 5.27 eV, Mn4Cl9 can be viewed as a hyperhalogen with the formula unit Mn(MnCl3)3. Indeed, the calculated VDE of Mn4Cl9 anion, namely 6.76 eV, is larger than that of MnCl3 anion. More importantly, unlike previously discovered hyperhalogens, Mn4Cl9 is the first such hyperhalogen species composed of only two constituent atoms. We further show that Mn4Cl9 can be used as a ligand to design molecules with even higher VDEs. For example, Li[Mn(MnCl3)3]2 anion has a VDE of 7.26 eV. These negatively charged clusters are antiferromagnetic with most of themagnetic moments localized at the Mn sites. Our studies show new pathways for creating binary hyperhalogens

    Electromagnetic modelling using T-A formulation for high-temperature superconductor (RE)Ba2Cu3Oxhigh field magnets

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    Second generation (2G) high-temperature superconductor (HTS) (RE)Ba2Cu3Ox(REBCO) shows a great potential in building high field magnets beyond 23.5 T. The electromagnetic modelling is vital for the design of HTS magnet, however, this always suffers the challenge of huge computation for high field magnets with large number of turns. This study presents a novel electromagnetic modelling based on T-A formulation for REBCO magnets with thousands of turns. An equivalent turn method is proposed to reduce the number of turns in calculation, so that the computation cost can be reduced significantly, and meanwhile the key electromagnetic behaviour of HTS magnet can be simulated with enough accuracy. The ramping operation of a fully HTS magnet with 12,000 turns are analysed using both the original T-A model with actual turns and improved T-A model with equivalent turns. The two models show a good agreement on the key electromagnetic behaviours of the magnet: distribution of current density, magnetic fields, screen current induced field and magnetisation loss, so that this improved T-A model using equivalent turns is validated. The T-A modelling of REBCO magnet is a powerful tool for the electromagnetic analysis of industry-scale high field magnets

    Study of the magnetization loss of CORC® cables using a 3D T-A formulation

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    A Conductor on Round Core (CORC®) cable wound with a high temperature superconductor is an important cable concept for high current density applications. The design of a CORC cable makes understanding its electromagnetic performance—for example its AC losses—challenging. This paper presents a thorough study of CORC cables by combining experimental and numerical methods. In particular, it focuses on understanding how the cable structure influences the magnetization losses and on how these can be reduced. A novelty of this paper lies in the use of a new T-A formulation, which, for the first time, is employed for three-dimensional modelling of a CORC cable with real geometry. The use of the new T-A formulation in finite element software enables the study of how the winding direction and multiple-layer structure affect the magnetization losses of CORC cables. Moreover, influence of striation in CORC cables is studied as an effective way to reduce their losses. A CORC cable with striated tapes shows a significant magnetization loss reduction at high magnetic fields, in comparison to its counterpart without striated tapes. At low magnetic fields, tape striation leads to an increase in loss when the number of filaments is low, then the loss drops with a further increase in the number of filaments, but this loss reduction is much weaker than that at high fields. This paper provides an efficient tool for investigating the electromagnetic behaviour of CORC cables, which can provide valuable guidance in designing CORC cables with minimized losses for high energy physics and energy conversion applications

    Optimizacija prehospitalnih strategija upravljanja prvom pomoći za bolesnike sa zaraznim bolestima u gradu Huizhou pomoću algortima za duboko učenje

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    The aim of the study was to optimize the pre-hospital first aid management strategy for patients with infectious diseases in Huizhou city, which is expected to provide a basis for the epidemic prevention and control, to save lives, and increase the pre-hospital first aid efficiency. At the Department of Emergency, Huizhou Third People’s Hospital as the research subject, the common pre-hospital first aid procedure for infectious diseases was identified. The Petri net was used to model and determine the execution time of each link of the pre-hospital first aid process. The isomorphic Markov chain was used to optimize the pre-hospital first aid procedure for infectious diseases. In terms of the emergency path, deep learning was combined with the reinforcement learning model to construct the reinforcement learning model for ambulance path planning. Isomorphic Markov chain analysis revealed that the patient status when returning to the hospital, the time needed for the ambulance to come to designated location, and the on-site treatment were the main problems in the first aid process, and the time needed for the pre-hospital first aid process was reduced by 25.17% after optimization. In conclusion, Petri net and isomorphic Markov chain can optimize the pre-hospital first aid management strategies for patients with infectious diseases, and the use of deep learning algorithm can effectively plan the emergency path, achieving intelligent and informationalized pre-hospital transfer, which provides a basis for reducing the suffering, mortality, and disability rate of patients with infectious diseases.Cilj istraživanja bio je optimizirati strategiju prehospitalnog upravljanja prvom pomoći za bolesnike sa zaraznim bolestima u gradu Huizhou, Kina, za koju se očekuje da pruži osnovu za prevenciju i kontrolu epidemije, da spasi živote te da poveća učinkovitost prehospitalne prve pomoći. Istraživanje je provedeno na Hitnom odjelu Treće narodne bolnice u gradu Huizhou, gdje je utvrđen opći prehospitalni postupak prve pomoći za zarazne bolesti. Petrijeva mreža je primijenjena kako bi se modeliralo i odredilo vrijeme izvršenja svake karike u procesu prehospitalne prve pomoći. Izomorfni Markovljev lanac primijenjen je za optimizaciju prehospitalnog postupka prve pomoći za zarazne bolesti. Za putanju hitnosti, duboko učenje je kombinirano s modelom pojačanog učenja kako bi se konstruirao model osnaživanja učenja za planiranje putanje vozila hitne pomoći. Analiza Markovljeva lanca pokazala je da su status bolesnika na povratku u bolnicu, vrijeme potrebno da vozilo hitne pomoći dođe na određenu lokaciju i skrb na mjestu događaja glavni problemi u procesu prve pomoći te da je vrijeme potrebno za prehospitalni proces prve pomoći smanjeno za 25,17% nakon optimizacije. Zaključeno je da Petrijeva mreža i izomorfni Markovljev lanac mogu optimizirati strategije upravljanja prehospitalnom prvom pomoći za bolesnike sa zaraznim bolestima te da primjena algoritma dubokog učenja može učinkovito planirati putanju tima hitne pomoći, čime se postiže pametan i informatizirani prehospitalni prijevoz, što čini osnovu za smanjenje patnje, smrtnosti i stope invalidnosti za bolesnike sa zaraznim bolestima
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