4,144 research outputs found
Beam scanning by liquid-crystal biasing in a modified SIW structure
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
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
Advances in Methane Production from Coal, Shale and Other Tight Rocks
This collection reports on the state of the art in fundamental discipline application in hydrocarbon production and associated challenges in geoengineering activities. Zheng et al. (2022) report an NMR-based method for multiphase methane characterization in coals. Wang et al. (2022) studied the genesis of bedding fractures in Ordovician to Silurian marine shale in the Sichuan basin. Kang et al. (2022) proposed research focusing on the prediction of shale gas production from horizontal wells. Liang et al. (2022) studied the pore structure of marine shale by adsorption method in terms of molecular interaction. Zhang et al. (2022) focus on the coal measures sandstones in the Xishanyao Formation, southern Junggar Basin, and the sandstone diagenetic characteristics are fully revealed. Yao et al. (2022) report the source-to-sink system in the Ledong submarine channel and the Dongfang submarine fan in the Yinggehai Basin, South China Sea. There are four papers focusing on the technologies associated with hydrocarbon productions. Wang et al. (2022) reported the analysis of pre-stack inversion in a carbonate karst reservoir. Chen et al. (2022) conducted an inversion study on the parameters of cascade coexisting gas-bearing reservoirs in coal measures in Huainan. To ensure the safety CCS, Zhang et al (2022) report their analysis of available conditions for InSAR surface deformation monitoring. Additionally, to ensure production safety in coal mines, Zhang et al. (2022) report the properties and application of gel materials for coal gangue control
Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions
In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request
Aerosol modelling : Improving the understanding of aerosol processes and their effects on the climate at process and global-scale
Atmospheric aerosol particles have the ability to affect climate through cloud interactions and direct scattering and absorption of radiation. These aerosol particles can also affect human health through respiratory system. Aerosol particles are emitted to the atmosphere through direct sources or they can be formed through chemical processes from gas phase precursors. The different atmospheric processes and climate feedbacks of aerosol particles can be studied using process-scale models as well as larger global-scale models. In recent years, it has been found out that certain aerosol species lack information on their thermodynamic properties, causing uncertainties in process-scale modelling as well as global-scale modelling. In addition, transport of aerosols to remote regions, where emissions of aerosol particles are low, is poorly modelled in global-scale models. Furthermore, sources for formed secondary organic aerosol (SOA) include uncertainties in global aerosol-climate models, which causes uncertainty to estimating the radiative forcing (RF).
In this thesis, these aspects relating to uncertainties are addressed using process and global-scale modelling. This was done first by evaluating the capability of thermodynamic equilibrium model to reproduce observed hygroscopicity in terms of dimethylamine, sulfuric acid and ammonia containing particles. Second, an in-cloud wet deposition scheme was developed (hereafter referred to as the newly-developed scheme) for global models which use sectional aerosol description. The newlydeveloped wet deposition scheme was tested using ECHAM-HAMMOZ global aerosol-climate model with Sectional Aerosol model for Large-Scale Applications (SALSA) in terms of aerosol vertical distributions and lifetimes. Third, the biotic stress effects to trees over boreal region and their effects to SOA formation, clouds and radiative effects were studied using ECHAM-HAMMOZ with SALSA.
The results showed that when the thermodynamic equilibrium model was used to model particles with sizes of the order of couple of tens of nanometers, it was inadequate in estimating the hygroscopic growth of dimethylamine (DMA), sulfuric acid (SA) and ammonia containing particles. Thus, more investigation is needed in terms of thermodynamics of DMA containing systems to properly evaluate its effects to climate. Global aerosol-climate models are very complex and thus making aerosol processes more physically sound can even impair the results. This was seen in the results of the newly-developed, more physical, in-cloud wet deposition scheme as it produced spurious vertical profiles and atmospheric black carbon lifetime when compared to the preexisting scheme. Especially, the atmospheric lifetime of black carbon, in the newly-developed scheme, was 1.6 times longer than in the pre-existing scheme and over 2.6 times longer than has been suggested by experimental studies. Thus, the sensitivity of the newly-developed scheme was tested in terms of internal mixing and emission size distribution of black carbon as well as ageing of aerosol species. These results showed that mixing black carbon with soluble substances produced best results in comparison with the observations as well as atmospheric lifetimes of aerosol species when compared to AEROCOM model means. Lastly, the results studying the biotic stress effects on climate showed that increasing the extent of stress in boreal trees enhanced SOA formation as the emissions of volatile organic compounds (VOCs) were increased. The enhanced SOA formation increased cloud droplet number concentration (CDNC) at cloud top and caused stronger negative RF in both all-sky and clear-sky cases. In the future, aerosol model development should investigate further on the thermodynamic properties of aerosol species, especially with respect to DMA. The wet removal and extent of internal mixing of different aerosol species, especially black carbon, should be further investigated and revised, in global climate models, to properly evaluate the transport of aerosol particles. In addition, sources of atmospheric SOA needs further investigation to properly describe its behaviour in the atmosphere as well as the effects on the climate.Ilmakehän aerosolihiukkasilla on kyky vaikuttaa ilmastoon pilvivuorovaikutusten kautta sekä suoraan sirottamalla ja absorboimalla itseensä säteilyä. Nämä aerosolihiukkaset voivat myös vaikuttaa ihmisterveyteen hengityselimien kautta. Aerosolihiukkasia vapautuu ilmakehään suorien lähteiden kautta tai ne voivat syntyä kemiallisissa prosesseissa kaasufaasin esiasteista. Eri aerosoliprosesseja ja aerosolihiukkasten ilmastovaikutuksia voidaan tutkia käyttäen prosessi- ja globaalin mittakaavan malleja. Viime vuosina on havaittu, että tietyiltä aerosoliyhdisteiltä puuttuu tietoja niiden termodynaamisista ominaisuuksista, joka aiheuttaa epävarmuutta prosessi- ja globaalitason mallinnuksessa. Lisäksi aerosolien kaukokulkeuma syrjäisille alueille, joilla aerosolihiukkasten päästöt ovat vähäisiä, on heikosti mallinnettu globaalin mittakaavan malleissa. Lisäksi sekundaarisen orgaanisen aerosolin (SOA) päästölähteet sisältävät epävarmuuksia globaalin mittakaavan malleissa, joka aiheuttaa epävarmuutta säteilypakotteen arvioinnissa.
Tässä työssä näitä näkökohtia, jotka liittyvät kyseisiin epävarmuuksiin, käsitellään käyttäen prosessi- ja globaalin mittakaavan mallinnusta. Tämä tehtiin ensiksi arvioimalla termodynaamisen tasapainomallin kykyä kuvata dimetyyliamiinia, rikkihappoa ja ammoniakkia sisältävien hiukkasten vedenottokykyä verrattuna mittauksiin. Toiseksi työssä kehitettiin pilven sisäinen märkäpoistumajärjestelmä globaalitason malleille, jotka käyttävät kokoon perustuvaa aerosolikuvausta. Vasta kehitettyä märkäpoistumajärjestelmää testattiin aerosolien pystyprofiilien ja elinikien suhteen käyttämällä ECHAM-HAMMOZ globaalia aerosoli-ilmastomallia, joka sisälsi ”Sectional Aerosol model for Large-Scale Applications (SALSA)” -mikrofysiikkakuvauksen. Kolmanneksi tutkittiin havumetsävyöhykkeen puihin kohdistuneen bioottisen stressin vaikutusta SOA:n muodostumiseen, pilviin ja säteilyvaikutuksiin käyttämällä ECHAM-HAMMOZ:ia SALSA:n kanssa.
Tulokset osoittivat, että kun termodynaamista tasapainomallia käytettiin mallinnettaessa hiukkasia, joiden koko oli muutamien kymmenien nanometrien luokkaa, malli oli epäpätevä arvioimaan dimetyyliamiinia (DMA), rikkihappoa ja ammoniakkia sisältävien hiukkasten hygroskooppisuutta. Näin ollen lisätutkimuksia tarvitaan DMA:a sisältävien systeemien termodynamiikasta, jotta voidaan arvioida kunnolla sen vaikutusta ilmastoon. Globaalit aerosoli-ilmastomallit ovat erittäin monimutkaisia ja siksi aerosoliprosessien muuttaminen fysikaalisemmaksi voi jopa heikentää tuloksia. Tämä havaittiin vasta kehitetyn, fysikaalisemman, märkäpoistumajärjestelmän tuottamista tuloksista, jotka osoittivat kehitetyn menetelmän tuottavan harhaanjohtavia pystyprofiileja sekä vääristävän mustan hiilen elinikää verrattuna aiempaan järjestelmään. Erityisesti mustan hiilen elinikä, vasta kehitetyssä järjestelmässä, oli 1.6 kertaa pidempi kuin aiemmassa järjestelmässä ja yli 2.6 kertaa pidempi kuin kokeellisissa tutkimuksissa on ehdotettu. Siksi vasta kehitetyn järjestelmän herkkyyttä testattiin mustan hiilen sisäisen sekoittumisen ja päästökokojakauman sekä aerosoliyhdisteiden ikääntymisen kannalta. Nämä tulokset osoittivat, että mustan hiilen sekoittaminen liukoisten yhdisteiden kanssa tuotti parhaat tulokset verrattuna havaintoihin sekä aerosoliyhdisteiden eliniät verrattuna AEROCOM mallien keskiarvoihin. Lopuksi tulokset, joissa tutkittiin bioottisen stressin vaikutusta ilmastoon, osoittivat, että stressin lisääminen havumetsävyöhykkeen puissa lisäsi SOA:n muodostumista, koska haihtuvien orgaanisten yhdisteiden päästöt lisääntyivät. Lisääntynyt SOA:n muodostus lisäsi myös pilvipisaroiden lukumäärää pilvien yläpinnassa sekä aiheutti voimakkaamman negatiivisen säteilypakotteen. Tulevaisuudessa aerosolimallikehityksessä tulisi tutkia tarkemmin aerosoliyhdisteiden termodynaamisia ominaisuuksia erityisesti DMA:n suhteen. Märkäpoistumaa sekä eri aerosoliyhdisteiden, erityisesti mustan hiilen, sisäisen sekoittumisen määrää tulisi tutkia ja uudistaa globaaleissa ilmastomalleissa, jotta aerosolihiukkasten kaukokulkeumaa voitaisiin arvioida kunnolla. Lisäksi ilmakehän SOA:n lähteet tarvitsevat lisätutkimusta, jotta sen käyttäytymistä ilmakehässä ja ilmastovaikutuksia voitaisiin kuvata oikein
Modified Theories of Gravity and Cosmological Applications
This reprint focuses on recent aspects of gravitational theory and cosmology. It contains subjects of particular interest for modified gravity theories and applications to cosmology, special attention is given to Einstein–Gauss–Bonnet, f(R)-gravity, anisotropic inflation, extra dimension theories of gravity, black holes, dark energy, Palatini gravity, anisotropic spacetime, Einstein–Finsler gravity, off-diagonal cosmological solutions, Hawking-temperature and scalar-tensor-vector theories
Model Compression Methods for YOLOv5: A Review
Over the past few years, extensive research has been devoted to enhancing
YOLO object detectors. Since its introduction, eight major versions of YOLO
have been introduced with the purpose of improving its accuracy and efficiency.
While the evident merits of YOLO have yielded to its extensive use in many
areas, deploying it on resource-limited devices poses challenges. To address
this issue, various neural network compression methods have been developed,
which fall under three main categories, namely network pruning, quantization,
and knowledge distillation. The fruitful outcomes of utilizing model
compression methods, such as lowering memory usage and inference time, make
them favorable, if not necessary, for deploying large neural networks on
hardware-constrained edge devices. In this review paper, our focus is on
pruning and quantization due to their comparative modularity. We categorize
them and analyze the practical results of applying those methods to YOLOv5. By
doing so, we identify gaps in adapting pruning and quantization for compressing
YOLOv5, and provide future directions in this area for further exploration.
Among several versions of YOLO, we specifically choose YOLOv5 for its excellent
trade-off between recency and popularity in literature. This is the first
specific review paper that surveys pruning and quantization methods from an
implementation point of view on YOLOv5. Our study is also extendable to newer
versions of YOLO as implementing them on resource-limited devices poses the
same challenges that persist even today. This paper targets those interested in
the practical deployment of model compression methods on YOLOv5, and in
exploring different compression techniques that can be used for subsequent
versions of YOLO.Comment: 18 pages, 7 Figure
Data assimilation with autocorrelated model error
Data assimilation has often been performed under the perfect model assumption, but in reality, numerical models often contain model errors with spatial and temporal correlations.
The objective of this thesis is to thoroughly investigate the impact of an inaccurate time
correlation in the model error description on data assimilation results, both analytically
and numerically using the ensemble Kalman Smoother (EnKS). Furthermore, we try to
develop an efficient way to perform online estimation of certain model error autocorrelation parameters with the data assimilation scheme.
With a simple linear model and a single-parameter autocorrelation, we find that the performance of the data assimilation scheme can be impacted by the departures between the
actual values of the parameter and the value proposed in the data assimilation process with
sparse observations. However, the impact of the incorrect parameter can be diminished
with dense observations. Furthermore, we show that the correct model error decorrelation
timescale can be estimated after multiple simulation windows using the state augmentation method with the linear system.
More complex autocorrelation, in which decaying and oscillatory scales are considered,
is later examined on the linear model and, furthermore, a nonlinear logistic map. It seems
impossible for the EnKS to track both decaying and oscillatory parameters in the autocorrelation, and the iterative variant of the EnKS (IEnKS) is required. With the nonlinear
logistic map, even the IEnKS fails to find the correct values for the two parameters and can
get stuck in local minima. Fortunately, we can find the correct values of the parameters
with careful tuning of the IEnKS and transformation of the solution space.
When the problem confronts a high-dimensional nonlinear system such as the quasigeostrophic model, a large part of the state has to be observed in space, even for the
simplest case of the model error autocorrelation. In this case, it shows the limitations
of our method for practical weather forecast systems since the observation cannot be as
dense as needed for the parameter estimation to work, and result in an affordable scheme
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