4,965 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Magnetic Material Modelling of Electrical Machines

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    The need for electromechanical energy conversion that takes place in electric motors, generators, and actuators is an important aspect associated with current development. The efficiency and effectiveness of the conversion process depends on both the design of the devices and the materials used in those devices. In this context, this book addresses important aspects of electrical machines, namely their materials, design, and optimization. It is essential for the design process of electrical machines to be carried out through extensive numerical field computations. Thus, the reprint also focuses on the accuracy of these computations, as well as the quality of the material models that are adopted. Another aspect of interest is the modeling of properties such as hysteresis, alternating and rotating losses and demagnetization. In addition, the characterization of materials and their dependence on mechanical quantities such as stresses and temperature are also considered. The reprint also addresses another aspect that needs to be considered for the development of the optimal global system in some applications, which is the case of drives that are associated with electrical machines

    Modeling and Simulation in Engineering

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    The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering

    Predicting and Understanding Binding Affinities of Synthetic Anion Receptors

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    Anion receptors are molecules that can recognise and bind anions. They have applications in organocatalysis, anion sensing and the removal of anions from wastewater. Some anion receptors are also able to transport anions across cell membranes and show promise for the treatment of diseases such as cystic fibrosis and cancer. As such, it is of interest to develop computational methods that can reliably predict the physicochemical properties and anion binding affinities of these molecules. However, efforts to computationally model these molecules are hampered by the sheer size of typical receptors, making them too expensive to treat using accurate quantum chemical methods. Whilst efficient approximations such as local-correlation methods have been developed, the broader accuracy of these methods, particularly in their application to ionic non-covalent systems remains unclear. To address this gap, this thesis has carried out an extensive validation of local-correlation methods, and economical density functional theory (DFT) methods for receptors with different binding motifs. Additionally, multiscale models have also been examined with the view to extending the scope of these methods to model very large anion receptors. DFT methods giving good agreement with highly accurate calculations at a fraction of the cost were identified. The use of semiempirical methods combined with DFT in a multiscale model for calculating anion binding affinities lead to unexpectedly large errors with modest savings of computational time, while some "three-fold corrected" methods show promise in reducing the cost of geometry optimisations of large receptors. These validated protocols were subsequently applied to investigate the structure-binding relationships of a wide range of dual-hydrogen bonding receptors. Notably, different receptor motifs were found to have different conformational preferences, which could explain why experimentally, thioureas, thiosquaramides and croconamides show weaker chloride binding affinities than would be expected based on their acidity. The results suggest that pre-organising anion receptors in the conformer that facilitates hydrogen bond formation could be a promising strategy for the development of anion receptors. It is envisaged that these findings will aid in the design and screening of novel anion receptors with increased binding affinity and selectivity

    Light transport by topological confinement

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    The growth of data capacity in optical communications links, which form the critical backbone of the modern internet, is facing a slowdown due to fundamental nonlinear limitations, leading to an impending "capacity crunch" on the horizon. Current technology has already exhausted degrees of freedom such as wavelength, amplitude, phase and polarization, leaving spatial multiplexing as the last available dimension to be efficiently exploited. To minimize the significant energy requirements associated with digital signal processing, it is critical to explore the upper limit of unmixed spatial channels in an optical fiber, which necessitates ideally packing spatial channels either in real space or in momentum space. The former strategy is realized by uncoupled multi-core fibers whose channel count has already saturated due to reliability constraint limiting fiber sizes. The later strategy is realized by the unmixed multimode fiber whose high spatial efficiency suggest the possibility of high channel-count scalability but the right subset of mode ought to be selected in order to mitigate mode coupling that is ever-present due to the plethora of perturbations a fiber normally experiences. The azimuthal modes in ring-core fibers turn out to be one of the most spatially efficient in this regard, by exploiting light’s orbital angular momentum (OAM). Unmixed mode counts have reached 12 in a ~1km fiber and 24 in a ~10m fiber. However, there is a fundamental bottleneck for scalability of conventionally bound modes and their relatively high crosstalks restricts their utility to device length applications. In this thesis, we provide a fundamental solution to further fuel the unmixed-channel count in an MMF. We utilize the phenomenon of topological confinement, which is a regime of light guidance beyond conventional cutoff that has, to the best of our knowledge, never been demonstrated till publications based on the subject matter of this thesis. In this regime, light is guided by the centrifugal barrier created by light’s OAM itself rather than conventional total internal reflection arising from the index inhomogeneity of the fiber. The loss of these topologically confined modes (TCMs) decreases down to negligible levels by increasing the OAM of fiber modes, because the centrifugal barrier that keeps photons confined to a fiber core increases with the OAM value of the mode. This leads to low-loss transmission in a km-scale fiber of these cutoff modes. Crucially, the mode-dependent confinement loss of TCMs further lifts the degeneracy of wavevectors in the complex space, leading to frustration of phase-matched coupling. This thus allows further scaling the mode count that was previously hindered by degenerate mode coupling in conventionally bound fiber modes. The frustrated coupling of TCMs thus enables a record amount of unmixed OAM modes in any type of fiber that features a high index contrast, whether specially structured as a ring-core, or simply constructed as a step-index fiber. Using all these favorable attributes, we achieve up to 50 low-loss modes with record low crosstalk (approaching -45 dB/km) over a 130-nm bandwidth in a ~1km-long ring-core fiber. The TCM effect promises to be inherently scalable, suggesting that even higher modes counts can be obtained in the future using this design methodology. Hence, the use of TCMs promises breaking the record spectral efficiency, potentially making it the choice for transmission links in future Space-Division-Multiplexing systems. Apart from their chief attribute of significantly increasing the information content per photon for quantum or classical networks, we expect that this new light guidance may find other applications such as in nonlinear signal processing and light-matter interactions

    Towards Improved Hydrologic Land-Surface Modelling To Represent Permafrost

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    Permafrost affects hydrological, meteorological, and ecological processes in over one-quarter of the land surface in the Northern Hemisphere. Permafrost degradation has been observed over the last few decades and is projected to accelerate under climatic warming. However, simulating permafrost dynamics is challenging due to process complexity, scarcity of observations, spatial heterogeneity, and permafrost disequilibrium with external climate forcing. Hydrologic-land-surface models (H-LSMs), which act as the lower boundary condition of the current generation of Earth system models (ESMs), are suitable for diagnosing and predicting permafrost evolution, as they couple heat and water interactions across soil-vegetation-atmosphere interfaces and are applicable for large-scale assessments. This thesis aims to improve the ability of H-LSMs to simulate permafrost dynamics and concurrently represent hydrology. Specific research contributions are made on four fronts: (1) assessing the uncertainty introduced to the modelling due to permafrost initialization, (2) investigating the sensitivity of permafrost dynamics to different H-LSM parameters, associated issues of parameter identifiability, and sensitivity to external forcing datasets, (3) evaluating the strength of permafrost-hydrology coupling in H-LSMs in data-scarce regions under parameter uncertainty, and (4) assessing the fate of permafrost thaw and associated changes in streamflow under an ensemble of future climate projections. The analyses and results of this thesis that illuminate these central issues and various solutions for permafrost-based applications of H-LSMs are proposed. First, uncertainty in model initialization determines the length of required spin-up cycles; 200-1000 cycles may be required to ensure proper model initialization under different climatic conditions and initial soil moisture contents. Further, the uncertainty due to initialization can lead to divergent permafrost simulations, such as active layer thickness variations of up to ~2m. Second, the sensitivity of various permafrost characteristics is mainly driven by surface insulation (canopy height and snow-cover fraction) and soil properties (depth and fraction of organic matter content). Additionally, the results underscore the difficulties inherent in H-LSM simulation of all aspects of permafrost dynamics, primarily due to poor identifiability of influential parameters and the limitations of currently-available forcing data sets. Third, different H-LSM parameterizations favor different sources of data (i.e. streamflow, soil temperature profiles, and permafrost maps), and it is challenging to configure a model faithful to all data sources. Overall, the modelling results show that surface insulation (through snow cover) and model initialization are primary regulators of permafrost dynamics and different parameterizations produce different low-flow but similar high-flow regimes. Lastly, severe permafrost degradation is projected to occur under all climate change scenarios, even under the most optimistic ones. The degradation and climate change, collectively, are likely to alter several streamflow signatures, including an increase of winter and summer flows. Permafrost fate has strategic importance for the exchange of water, heat, and carbon fluxes over large areas, and can amplify the rate of climate change through a positive feedback mechanism. However, existing projections of permafrost are subject to significant uncertainty, stemming from several sources. This thesis quantifies and reduces this uncertainty by studying initialization, parameter identification, and evaluation of H-LSMs, which ultimately lead to configuring an H-LSM with higher fidelity to assess the impact of climate change. As a result, this work is a step forward in improving the realism of H-LSM simulations in permafrost regions. Further research is needed to refine simulation capability, and to develop improved observational datasets for permafrost and their associated climate forcing

    KYT2022 Finnish Research Programme on Nuclear Waste Management 2019–2022 : Final Report

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    KYT2022 (Finnish Research Programme on Nuclear Waste Management 2019–2022), organised by the Ministry of Economic Affairs and Employment, was a national research programme with the objective to ensure that the authorities have sufficient levels of nuclear expertise and preparedness that are needed for safety of nuclear waste management. The starting point for public research programs on nuclear safety is that they create the conditions for maintaining the knowledge required for the continued safe and economic use of nuclear energy, developing new know-how and participating in international collaboration. The content of the KYT2022 research programme was composed of nationally important research topics, which are the safety, feasibility and acceptability of nuclear waste management. KYT2022 research programme also functioned as a discussion and information-sharing forum for the authorities, those responsible for nuclear waste management and the research organizations, which helped to make use of the limited research resources. The programme aimed to develop national research infrastructure, ensure the continuing availability of expertise, produce high-level scientific research and increase general knowledge of nuclear waste management

    A Simulation of the Impacts of Climate Change on Civil Aircraft Takeoff Performance

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    Climate change affects the near-surface environmental conditions that prevail at airports worldwide. Among these, air density and headwind speed are major determinants of takeoff performance, and their sensitivity to global warming carries potential operational and economic implications for the commercial air transport industry. Previous archival and prospective research observed a weakening in headwind strength and predicted an increase in near-surface temperatures, respectively, resulting in an increase in takeoff distances and weight restrictions. The main purpose of the present study was to update and generalize the extant prospective research using a more representative sample of worldwide airports, a wider range of climate scenarios, and next-generation climate models. The research questions included how much additional thrust and payload removal will be required to offset the centurial changes in takeoff conditions. This study relied on a quantitative method using the simulation instrument. Forecast climate data corresponding to four shared socioeconomic pathways (SSP1‒2.6, SSP2‒4.5, SSP3‒7.0, and SSP5‒8.5) over the available 2015‒2100 period were sourced from a high-resolution CMIP6 global circulation model. These data were used to characterize the six-hourly near-surface environmental conditions prevailing at all 881 airports worldwide having at least one million passengers in pre-COVID‒19 traffic. The missing air density was iii numerically derived from the air temperature, pressure, and humidity variables, while the headwind speed for each airport’s active runway configuration was triangulated from the wind vector components. Separately, a direct takeoff-dynamics simulation model was developed from first principles and calibrated against published performance data under international standard atmospheric conditions for two narrowbody and two widebody aircraft. The model was used to simulate 1.8 billion unique takeoffs, each initiated at 75% of maximum takeoff thrust and 100% of maximum takeoff mass. When the resulting takeoff distance required exceeded that available, the takeoff thrust was gradually increased to 100%, after which the takeoff mass was gradually decreased to an estimated breakeven load factor. In total, 65 billion takeoff iterations were simulated. Longitudinal changes to takeoff thrust, distance, and payload were recorded and examined by aircraft type, climate scenario, and climate zone. The results show that despite a marked centurial increase in the global mean air temperature of 9.4%‒18.0% relative to the year 2015 under SSP2‒4.5 and SSP3‒7.0, air density will only decrease by 0.6%‒1.1% due to its weak sensitivity to temperature. Likewise, mean headwinds were observed to remain almost unchanged relative to the 2015 baseline. As a result, the global mean takeoff thrust was found to increase by no more than 0.3 percentage point while payload removals did not exceed 1.1 passenger. Significant deviations from the mean were observed at climatic outlier airports, including those located around the Siberian plateau, where takeoff operations may become more difficult. This study contributes to the air transport climate adaption body of knowledge by providing contrasting results relative to earlier research that reported strong impacts of global warming on takeoff performance

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
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