978 resultados para LINEAR-DEPENDENCE CONDITION


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The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism) depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.

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One key problem in modern medical imaging is linking measured data and actual physiological quantities. In this article we derive such a link between the electrical bioimpedance of lung parenchyma, which can be measured by electrical impedance tomography (EIT), and the magnitude of regional ventilation, a key to understanding lung mechanics and developing novel protective ventilation strategies. Two rat-derived three-dimensional alveolar microstructures obtained from synchrotron-based x-ray tomography are each exposed to a constant potential difference for different states of ventilation in a finite element simulation. While the alveolar wall volume remains constant during stretch, the enclosed air volume varies, similar to the lung volume during ventilation. The enclosed air, serving as insulator in the alveolar ensemble, determines the resulting current and accordingly local tissue bioimpedance. From this we can derive a relationship between lung tissue bioimpedance and regional alveolar ventilation. The derived relationship shows a linear dependence between air content and tissue impedance and matches clinical data determined from a ventilated patient at the bedside.

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La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

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La adecuada estimación de avenidas de diseño asociadas a altos periodos de retorno es necesaria para el diseño y gestión de estructuras hidráulicas como presas. En la práctica, la estimación de estos cuantiles se realiza normalmente a través de análisis de frecuencia univariados, basados en su mayoría en el estudio de caudales punta. Sin embargo, la naturaleza de las avenidas es multivariada, siendo esencial tener en cuenta características representativas de las avenidas, tales como caudal punta, volumen y duración del hidrograma, con el fin de llevar a cabo un análisis apropiado; especialmente cuando el caudal de entrada se transforma en un caudal de salida diferente durante el proceso de laminación en un embalse o llanura de inundación. Los análisis de frecuencia de avenidas multivariados han sido tradicionalmente llevados a cabo mediante el uso de distribuciones bivariadas estándar con el fin de modelar variables correlacionadas. Sin embargo, su uso conlleva limitaciones como la necesidad de usar el mismo tipo de distribuciones marginales para todas las variables y la existencia de una relación de dependencia lineal entre ellas. Recientemente, el uso de cópulas se ha extendido en hidrología debido a sus beneficios en relación al contexto multivariado, permitiendo superar los inconvenientes de las técnicas tradicionales. Una copula es una función que representa la estructura de dependencia de las variables de estudio, y permite obtener la distribución de frecuencia multivariada de dichas variables mediante sus distribuciones marginales, sin importar el tipo de distribución marginal utilizada. La estimación de periodos de retorno multivariados, y por lo tanto, de cuantiles multivariados, también se facilita debido a la manera en la que las cópulas están formuladas. La presente tesis doctoral busca proporcionar metodologías que mejoren las técnicas tradicionales usadas por profesionales para estimar cuantiles de avenida más adecuados para el diseño y la gestión de presas, así como para la evaluación del riesgo de avenida, mediante análisis de frecuencia de avenidas bivariados basados en cópulas. Las variables consideradas para ello son el caudal punta y el volumen del hidrograma. Con el objetivo de llevar a cabo un estudio completo, la presente investigación abarca: (i) el análisis de frecuencia de avenidas local bivariado centrado en examinar y comparar los periodos de retorno teóricos basados en la probabilidad natural de ocurrencia de una avenida, con el periodo de retorno asociado al riesgo de sobrevertido de la presa bajo análisis, con el fin de proporcionar cuantiles en una estación de aforo determinada; (ii) la extensión del enfoque local al regional, proporcionando un procedimiento completo para llevar a cabo un análisis de frecuencia de avenidas regional bivariado para proporcionar cuantiles en estaciones sin aforar o para mejorar la estimación de dichos cuantiles en estaciones aforadas; (iii) el uso de cópulas para investigar tendencias bivariadas en avenidas debido al aumento de los niveles de urbanización en una cuenca; y (iv) la extensión de series de avenida observadas mediante la combinación de los beneficios de un modelo basado en cópulas y de un modelo hidrometeorológico. Accurate design flood estimates associated with high return periods are necessary to design and manage hydraulic structures such as dams. In practice, the estimate of such quantiles is usually done via univariate flood frequency analyses, mostly based on the study of peak flows. Nevertheless, the nature of floods is multivariate, being essential to consider representative flood characteristics, such as flood peak, hydrograph volume and hydrograph duration to carry out an appropriate analysis; especially when the inflow peak is transformed into a different outflow peak during the routing process in a reservoir or floodplain. Multivariate flood frequency analyses have been traditionally performed by using standard bivariate distributions to model correlated variables, yet they entail some shortcomings such as the need of using the same kind of marginal distribution for all variables and the assumption of a linear dependence relation between them. Recently, the use of copulas has been extended in hydrology because of their benefits regarding dealing with the multivariate context, as they overcome the drawbacks of the traditional approach. A copula is a function that represents the dependence structure of the studied variables, and allows obtaining the multivariate frequency distribution of them by using their marginal distributions, regardless of the kind of marginal distributions considered. The estimate of multivariate return periods, and therefore multivariate quantiles, is also facilitated by the way in which copulas are formulated. The present doctoral thesis seeks to provide methodologies that improve traditional techniques used by practitioners, in order to estimate more appropriate flood quantiles for dam design, dam management and flood risk assessment, through bivariate flood frequency analyses based on the copula approach. The flood variables considered for that goal are peak flow and hydrograph volume. In order to accomplish a complete study, the present research addresses: (i) a bivariate local flood frequency analysis focused on examining and comparing theoretical return periods based on the natural probability of occurrence of a flood, with the return period associated with the risk of dam overtopping, to estimate quantiles at a given gauged site; (ii) the extension of the local to the regional approach, supplying a complete procedure for performing a bivariate regional flood frequency analysis to either estimate quantiles at ungauged sites or improve at-site estimates at gauged sites; (iii) the use of copulas to investigate bivariate flood trends due to increasing urbanisation levels in a catchment; and (iv) the extension of observed flood series by combining the benefits of a copula-based model and a hydro-meteorological model.

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We proposed in our previous work V-substituted In2S3 as an intermediate band (IB) material able to enhance the efficiency of photovoltaic cells by combining two photons to achieve a higher energy electron excitation, much like natural photosynthesis. Here this hyper-doped material is tested in a photocatalytic reaction using wavelength-controlled light. The results evidence its ability to use photons with wavelengths of up to 750 nm, i.e. with energy significantly lower than the bandgap (=2.0 eV) of non-substituted In2S3, driving with them the photocatalytic reaction at rates comparable to those of non-substituted In2S3 in its photoactivity range (λ ≤ 650 nm). Photoluminescence spectra evidence that the same bandgap excitation as in V-free In2S3 occurs in V-substituted In2S3 upon illumination with photons in the same sub-bandgap energy range which is effective in photocatalysis, and its linear dependence on light intensity proves that this is not due to a nonlinear optical property. This evidences for the first time that a two-photon process can be active in photocatalysis in a single-phase material. Quantum calculations using GW-type many-body perturbation theory suggest that the new band introduced in the In2S3 gap by V insertion is located closer to the conduction band than to the valence band, so that hot carriers produced by the two-photon process would be of electron type; they also show that the absorption coefficients of both transitions involving the IB are of significant and similar magnitude. The results imply that V-substituted In2S3, besides being photocatalytically active in the whole visible light range (a property which could be used for the production of solar fuels), could make possible photovoltaic cells of improved efficiency.

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Lift and velocity circulation around airfoils are two aspects of the same phenomenon when airfoils are not stalled and the Kutta—Joukowski theorem applies. This theorem establishes a linear dependence between lift and circulation, which breaks when stalling occurs. As the angle of attack increases beyond this point, the circulation vanishes. Since the circulation determines to a great extent the position of the forward stagnation point on an airfoil, the measurement of this position is an easy and simple way to determine the circulation, which is of help in understanding the role of the latter in the generation of aerodynamic forces on airfoils.

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Quais propriedades magnéticas são modificadas quando se agrupam átomos de Fe/Co para formar estruturas quasi-2D, se comparadas aos nanofios (quasi-1D) de FexCo1-x? E como estas propriedades reagem com a variação da proporção de Fe/Co nos aglomerados? A fim de responder a estas questões, trímeros de FexCo1-x depositados em Pt(111) são investigados utilizando o método de primeiros princípios Real Space-Linear Muffin-Tin Orbital-Atomic Sphere Approximation (RS-LMTO-ASA) no âmbito da Teoria do Funcional da Densidade (DFT). Diferentes configurações de trímeros triangulares são consideradas, variando-se as posições e a concentração dos átomos de Fe/Co. Neste trabalho, demonstra-se a ocorrência de uma tendência não-linear estritamente decrescente dos momentos orbitais médios como função da concentração de Fe, distinta do encontrado tanto para os nanofios de FexCo1-x (dependência linear) quanto para a monocamada correspondente (dependência não-linear). Os resultados obtidos mostram ainda que os momentos orbitais variam com o ambiente local e com a direção de magnetização, especialmente quando associados aos átomos de Co, em concordância com publicações anteriores. A mudança de dimensionalidade quasi-1D (nanofios) para quasi-2D (trímeros compactos) não afeta o comportamento dos momentos de spin, que permanecem descritos por uma função linear com respeito à proporção de Fe/Co. Ambos o formato e a concentração de Fe nos sistemas apresentam um papel importante nos valores de energia de anisotropia magnética. Em adição, observou-se que o subtrato de Pt opera ativamente na definição das propriedades magnéticas dos aglomerados. Embora todas as configurações lineares e compactas dos aglomerados de FexCo1-x sejam estáveis e exibam interações fortemente ferromagnéticas entre os primeiros vizinhos, nem todas revelaram o ordenamento colinear como estado fundamental, apresentando uma interação de Dzyaloshinskii-Moriya não-desprezível induzida pelo acoplamento spin-órbita. Estes casos específicos são: o trímero triangular de Co puro e o trímero linear (nanofio) de Fe puro, para o qual foi verificado o acoplamento do tipo Ruderman-Kittel-Kasuya-Yosida entre os átomos de Fe constituintes. Os resultados obtidos contribuem para o entendimento de quais mecanismos definem o magnetismo nos trímeros de FexCo1-x/Pt(111), e discutem as questões presentes atualmente na literatura no contexto destes sistemas.

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Limitations in the performance of coherent transmission systems employing digital back-propagation due to four-wave mixing impairments are reported for the first time. A significant performance constraint is identified, originating from four-wave mixing between signals and amplified spontaneous emission noise which induces a linear increase in the standard deviation of the received field with signal power, and linear dependence on transmission distance.

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Copper(II) complexes of hexadentate ethylenediaminetetracarboxylic acid type ligands Heda3p and Heddadp (Heda3p = ethylenediamine-N-acetic-N,N',N'-tri-3-propionic acid; H eddadp = ethylenediamine-N,N'-diacetic-N,N'-di-3- propionic acid) have been prepared. An octahedral trans(O) geometry (two propionate ligands coordinated in axial positions) has been established crystallographically for the Ba[Cu(eda3p)]·8HO compound, while Ba[Cu(eddadp)]·8HO is proposed to adopt a trans(O ) geometry (two axial acetates) on the basis of density functional theory calculations and comparisons of IR and UV-vis spectral data. Experimental and computed structural data correlating similar copper(II) chelate complexes have been used to better understand the isomerism and departure from regular octahedral geometry within the series. The in-plane O-Cu-N chelate angles show the smallest deviation from the ideal octahedral value of 90°, and hence the lowest strain, for the eddadp complex with two equatorial ß-propionate rings. A linear dependence between tetragonality and the number of five-membered rings has been established. A natural bonding orbital analysis of the series of complexes is also presented.

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We describe the characterization of the temperature and strain responses of fiber Bragg grating sensors by use of an interferometric interrogation technique to provide an absolute measurement of the grating wavelength. The fiber Bragg grating temperature response was found to be nonlinear over the temperature range -70°C to 80°C. The nonlinearity was observed to be a quadratic function of temperature, arising from the linear dependence on temperature of the thermo-optic coefficient of silica glass over this range, and is in good agreement with a theoretical model.

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We describe the characterization of the temperature and strain responses of fiber Bragg grating sensors by use of an interferometric interrogation technique to provide an absolute measurement of the grating wavelength. The fiber Bragg grating temperature response was found to be nonlinear over the temperature range -70 °C to 80 °C. The nonlinearity was observed to be a quadratic function of temperature, arising from the linear dependence on temperature of the thermo-optic coefficient of silica glass over this range, and is in good agreement with a theoretical model.

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The "living" and/or controlled cationic ring-opening bulk copolymerization of oxetane (Ox) with tetrahydropyran (THP) (cyclic ether with no homopolymerizability) at 35°C was examined using ethoxymethyl-1 -oxoniacyclohexane hexafluoroantimonate (EMOA) and (BF3 · CH3OH)THP as fast and slow initiator, respectively, yielding living and nonliving polymers with pseudoperiodic sequences (i.e., each pentamethylene oxide fragment inserted into the polymer is flanked by two trimethylene oxide fragments). Good control over number-average molecular weight (Mn up to 150000 g mol-1) with molecular weight distribution (MWD ∼ 1.4-1, 5) broader than predicted by the Poison distribution (MWDs > 1 +1/DPn) was attained using EMOA as initiating system, i.e., C 2H5OCH2Cl with 1.1 equiv of AgSbF6 as a stable catalyst and 1.1 equiv of 2,6-di-tert-butylpyridine used as a non-nucleophilic proton trap. With (BF3 · CH 3OH)THP, a drift of the linear dependence M n(GPC) vs Mn(theory) to lower molecular weight was observed together with the production of cyclic oligomers, ∼3-5% of the Ox consumed in THP against ∼30% in dichloromethane. Structural and kinetics studies highlighted a mechanism of chains growth where the rate of mutual conversion between "strain ACE species" (chain terminated by a tertiary 1-oxoniacyclobutane ion, Al) and "strain-free ACE species" (chain terminated by a tertiary 1-oxoniacyclohexane ion, Tl) depends on the rate at which Ox converts the stable species T1 (kind of "dormant" species) into a living "propagating" center A1 (i.e., k aapp[Ox]). The role of the THP solvent associated with the suspension of irreversible and reversible transfer reactions to polymer, when the polymerization is initiated with EMOA, was predicted by our kinetic considerations. The activation -deactivation pseudoequilibrium coefficient (Qt) was then calculated in a pure theoretical basis. From the measured apparent rate constant of Ox (kOxapp) and THP (kTHPapp = ka(endo)app) consumption, Qt and reactivity ratio (kp/kd, k a(endo)/ka(exo), and ks/ka(endo) were calculated, which then allow the determination of the transition rate constant of elementary step reactions that governs the increase of Mu with conversion. © 2009 American Chemical Society.

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The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea–hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals.

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In this study wave propagation, dispersion relations, and energy relations for linear elastic periodic systems are analyzed. In particular, the dispersion relations for monoatomic chain of infinite dimension are obtained analytically by writing the Block-type wave equation for a unit cell in order to capture the dynamic behavior for chains under prescribed vibration. By comparing the discretized model (mass-spring chain) with the solid bar system, the nonlinearity of the dispersion relation for chain indicates that the periodic lattice is dispersive in contrast to the continuous rod, which is non dispersive. Further investigations have been performed considering one-dimensional diatomic linear elastic mass-spring chain. The dispersion relations, energy velocity, and group velocity have been derived. At certain range of frequencies harmonic plane waves do not propagate in contrast with monoatomic chain. Also, since the diatomic chain considered is a linear elastic chain, both of the energy velocity and the group velocity are identical. As long as the linear elastic condition is considered the results show zero flux condition without residual energy. In addition, this paper shows that the diatomic chain dispersion relations are independent on the unit cell scheme. Finally, an extension for the study covers the dispersion and energy relations for 2D- grid system. The 2x2 grid system show a periodicity of the dispersion surface in the wavenumber domain. In addition, the symmetry of the surface can be exploited to identify an Irreducible Brillouin Zone (IBZ). Compact representations of the dispersion properties of multidimensional periodic systems are obtained by plotting frequency as the wave vector’s components vary along the boundary of the IBZ, which leads to a widely accepted and effective visualization of bandgaps and overall dispersion properties.

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Utilization of graphene covered waveguide inserts to form tunable waveguide resonators is theoretically explained and rigorously investigated by means of full-wave numerical electromagnetic simulations. Instead of using graphene-based switching elements, the concept we propose incorporates graphene sheets as parts of a resonator. Electrostatic tuning of the graphene surface conductivity leads to changes in the electromagnetic field boundary conditions at the resonator edges and surfaces, thus producing an effect similar to varying the electrical length of a resonator. The presented outline of the theoretical background serves to give phenomenological insight into the resonator behavior, but it can also be used to develop customized software tools for design and optimization of graphene-based resonators and filters. Due to the linear dependence of the imaginary part of the graphene surface impedance on frequency, the proposed concept was expected to become effective for frequencies above 100 GHz, which is confirmed by the numerical simulations. A frequency range from 100 GHz up to 1100 GHz, where the rectangular waveguides are used, is considered. Simple, all-graphene-based resonators are analyzed first, to assess the achievable tunability and to check the performance throughout the considered frequency range. Graphene–metal combined waveguide resonators are proposed in order to preserve the excellent quality factors typical for the type of waveguide discontinuities used. Dependence of resonator properties on key design parameters is studied in detail. Dependence of resonator properties throughout the frequency range of interest is studied using eight different waveguide sections appropriate for different frequency intervals. Proposed resonators are aimed at applications in the submillimeter-wave spectral region, serving as the compact tunable components for the design of bandpass filters and other devices.