Parameter Dependence Research Articles

Dissipative inflation via scalar production

We describe a new mechanism that gives rise to dissipation during cosmic inflation.In the simplest implementation, the mechanism requires the presence of a massive scalar field with a softly-broken global U(1) symmetry, along with the inflaton field.Particle production in this scenario takes place on parametrically sub-horizon scales, at variance with the case of dissipation into gauge fields.Consequently, the backreaction of the produced particles on the inflationary dynamics can be treated in a local manner, allowing us to compute their effects analytically.We determine the parametric dependence of the power spectrum which deviates from the usual slow-roll expression.Non-Gaussianities are always sizeable whenever perturbations are generated by the noise induced by dissipation: f NL eq ≳ O(10).

Nonlinear saturation of whistler modes driven by runaway electrons

Runaway electrons exhibit kinetic instabilities with potentially beneficial consequences. The anomalous Doppler resonance between the electrons and whistler modes is a primary underlying mechanism. These instabilities require a first-principle nonlinear theoretical analysis, which would ultimately enable assessment of their impact on disruption mitigation and diagnostics, especially in ITER-relevant conditions. This paper presents recent progress in developing the required theoretical framework for isolated nonlinear resonances. By employing the generic bump-on-tail model, we predict the wave saturation levels in both near-threshold and strongly driven regimes. Remarkably, for the waves of interest, the parallel component of the wave vector dictates the parallel momentum of the resonant particles. This feature, together with the expected wave saturation level, provides a complete description of the resonance impact on the runaway electron distribution function. We show that the parametric dependence of the nonlinearly saturated mode provides a way to recover certain features of the runaway momentum distribution function.

Senseless Control of Permanent Magnet Synchronous Motors Based on New Fuzzy Adaptive Sliding Mode Observer

Based on the problems of sliding mode observer (SMO), such as strong parameter dependency, large overshoot, and severe inherent sliding mode chattering, this paper studies fuzzy control in depth using a sigmoid (s) function with smooth and continuous characteristics instead of a discontinuous symbolic function to design a new type of fuzzy sliding mode observer. Firstly, the boundary layer thickness was introduced to enable the system to achieve adaptive sliding mode gain adjustment based on the system state. Then, based on PLL technology, PI adjustment was used to obtain rotor position information. Finally, in order to verify the effectiveness of the new method, a model was built for experimental verification, and the simulation waveforms of the traditional sliding mode observer and the new fuzzy sliding mode observer were compared. The results show that the new fuzzy sliding mode observer can more accurately estimate rotor position and speed information. Under the same operating conditions, the rotational speed estimation error is only 3 r/min, the rotor position error is reduced by 0.1 rad, the overshoot is smaller, and the chattering is significantly reduced.

Lateral load resistance of reinforced concrete columns with brittle details

AbstractAnalytical models for shear strength and deformation capacity estimation of reinforced concrete members are essential for the practical implementation of performance‐based seismic evaluation of existing structures and form a key part of current seismic assessment codes (e.g., EN 1998‐3 (2005), (2022), ASCE/SEI 41‐17). Although these models have been derived from regression or calibration of large datasets collected from experimental literature, discrepancy persists between experimental and analytical estimates, especially in cases of members with old‐type detailing. The evident uncertainty about parametric dependencies of the underlying mechanistic problem motivated the present work, where a set of benchmark columns that represent older structural detailing are studied parametrically through advanced finite element simulation. Parameters considered were, the axial load ratio, transverse reinforcement amount and spacing, longitudinal reinforcement ratio, and anchorage/lap splice detailing; results were gauged in terms of the resulting drift ratio (deformation capacity) at the performance limit states and were compared with the Code estimates to evaluate their limits and conservatism. The simulation results were used to vet the assumptions that underlie the simple mechanistic models used in deriving seismic design expressions for yield and ultimate deformation capacities, shear strength, and the rate of its degradation with increasing ductility.

DSVM-Based Model-Free Predictive Current Control of an Induction Motor

Classical model-free predictive current control (MFPCC) is a robust control technique for a two-level inverter-fed induction-motor drive, with advantages that consist of a simple concept, rapid response, simple implementation, and excellent performance. However, the classic finite-control-set MFPCC still exhibits a significant current ripple. This article presents a method to enhance performance using a combination of model-free predictive current control (MFPCC) and discrete-space vector modulation (DSVM). The MFPCC employs an ultralocal model with an extended-state observer (ESO) that does not consider motor parameters, therefore improving the control system’s reliability by eliminating the parameter dependency. The proposed method integrates DSVM, which divides a single sample period into N equal intervals and generates virtual vectors to reduce stator current ripple. It achieves the minimum cost-function value across the entire operating range of the induction-motor (IM) drive by selecting the optimal vector from a limited set of permissible voltage vectors. Using DSVM effectively reduces the total harmonic distortion (THD) without any detrimental effects during transients or steady states. Experimental studies validate the effectiveness and superiority of the suggested technique over the Finite-Control-Set (FCS) MFPCC, which only considers real voltage vectors in its computations.

Finite element analysis of the underslung carrier rocket effect on stress and strain distribution in a structure of the MiG-29 aircraft

The paper presents selected aspect of the analytical-conceptual research project entitled: Airborne-Rocket Launch System for Delivering Satellite Payloads into Low Earth Orbit – Feasibility Study. The aim of the project is to conduct series of aerodynamic, strength, and aeroelastic simulations of Polish aging combat aircraft (Mig-29 and Su-22) to explore applicability of both fighters as an airborne platform for carrying out carrier rockets with a detachable satellite payload. This work presents exemplary analyses in the area of airframe loads and structural strength and deformability of MiG-29 for predicted operational variants with carrier rockets put to the hardpoints under fuselage. The numerical simulations were conducted for a structural discrete model of the aircraft prepared for finite element analysis in MSC Software. Model development involved such aspects as precise discretization of geometric model, declaration of material constants, identification of structural properties, introduction of suitable merging connections for included airframe assemblies, and final validation of model mass and stiffness. The model was analyzed in MSC Nastran software with application of linear “Statics” solution. External flight loads introduced into the model were calculated for specific points of the flight envelope—the highest values of load factor were taken into consideration ( n=9). The counterpart aerodynamic force distribution in a form of a set of equivalent lumped forces was calculated. Then, the aerodynamic and weight loads were added to the model as a set of forces applied to specific structural nodes. Additionally, weights of applicable carrier rockets were taken into account as concentrated forces applied to under-fuselage suspension hardpoints. Calculations were performed for several rockets of mass values between 250 and 1200 kg. Parametric dependencies were investigated as an effect of missile mass and size on stress and strain distribution over the whole structure. The areas of stress cumulations were identified. On the basis of static structural deformation, maximum wing tip displacements were assessed.

Flow Parameter Dependence of Laminar Plumes with Buoyancy Reversal from a Line Source

Laminar plumes that under goes buoyancy reversal have just been studied. It is true that fast penetration of the rising fluid will result to strong interaction between the rising plume and the ambient fluid which will lead to a quick halt based on the production of denser fluid that in turn halt their rise height. Thus, the present work have considered some sort of balance between viscous, inertia and buoyancy to have a reasonable plume’s rise height and effective mixing as we observe the behavior of these rising plumes while varying Reynolds number. At initial time interval, plumes were symmetric. There was a sideways flapping and bobbing motion after when the penetrating head became dense and detached. Two regimes of Re dependence fountains height over the range of Re ≤ 200 and the time τn taken to attain that height was recorded. Relations were also drawn that describes the rate of decrease in the fountain’s height from our empirically determined data set. Profiles of temperature and the various velocity components were also determined. Thus, with the quadratic dependence relation assumption, laminar fountains are feasible for Pr = 7 or 11.4, 5 ≤ Re ≤ 200 and 0.5 Fr. The fountains here are independent of Pr but dependent of both Re and Fr.

Impact of Temperature on the Reliability of UTB-DG-FE-TFETs and Their RF/Analog and Linearity Parameter Dependence

Impact of Temperature on the Reliability of UTB-DG-FE-TFETs and Their RF/Analog and Linearity Parameter Dependence

Decision support system for power cable insulation vulcanization production line management

The paper proposes a structural model of a decision support system for controlling a cable insulation continuous vulcanization line. The proposed decision support system is based on a mathematical model of the cable insulation continuous vulcanization technological process, a database, and a mode correction algorithm. The DSS will make it possible to quickly develop a new regime in case of using new materials or structures, as well as to correct the current regime in case of unplanned changes during the production process. The core of the DSS is the proposed mathematical model, which is based on conservation laws and is presented as a system of differential equations closed by boundary conditions. The vulcanization process is described taking into account the temperature-time dependence of the kinetic parameters, which made it possible to take into account the uneven heating of the cable, both in the radial direction and along the length. The numerical implementation of the differential mathematical model made it possible to carry out a systematic analysis of the nature of the processes in the vulcanization pipe and to evaluate the influence of various technological, structural and material parameters on the cable insulation vulcanization completion degree. As a result of the analysis, significant parameters were identified that significantly affect the vulcanization process completion degree. Based on the obtained numerical results, technological parameters dependence technological surfaces on the geometry of the product and the properties of the materials used were constructed, a regression mathematical model was proposed that allows determining the values of the process control parameters without resorting to the use of a differential mathematical model. Based on the results of the analysis, an algorithm for correcting the technological regime is proposed, taking into account only significant process parameters. The proposed algorithm allows you to adjust the value of the isolation rate, depending on external influences and deviations from the specified parameters. The results of the study can be used in the production of cable and wire products with vulcanizable insulation, when it is necessary to quickly select the optimal technological mode, take into account changes in the cable design, properties of the insulation material, as well as possible pressure deviations inside the vulcanization pipe.

Automated Estimation of Aquifer Parameters from Arbitrary-Rate Pumping Tests in Python and MATLAB.

Inspired by the analysis by Mishra et al. (2012) of variable pumping rate tests using piecewise-linear reconstructions of the pumping history, this article contains a derivation of the convolutional form of pumping tests in which the pumping history may take any possible form. The solution is very similar to the classical Theis (1935) equation but uses the Green's function for a pumped aquifer given by taking the time derivative of the well function . This eliminates one integration inside another and renders the convolution including the pumping history about as computationally demanding as calculating the well function alone, so that the convolution can be completed using handy mathematical software. It also allows nonlinear well losses, and because an easily-computed deterministic model exists for all data points and pumping history, an objective function may include all data, so that errors are reduced in calculating any nonlinear-well losses. In addition, data from multiple observation wells may be used simultaneously in the inversion. We provide codes in MATLAB and Python to solve for drawdown resulting from an arbitrary pumping history and compute the optimal aquifer parameters to fit the data. We find that the subtleties in parameter dependencies and constructing an appropriate objective function have a substantial effect on the interpreted parameters. Furthermore, the optimization from step-drawdown tests is typically nonunique and strongly suggests that a Bayesian inversion should be used to fully estimate the joint probability density of the parameter vector.

Gas, dust, and the CO-to-molecular gas conversion factor in low-metallicity starbursts

The factor relating CO emission to molecular hydrogen column density, XCO, is still subject to uncertainty, in particular at low metallicity. In this paper, to quantify XCO at two different spatial resolutions, we exploited a dust-based method together with ALMA 12-m and ACA data and H I maps of three nearby metal-poor starbursts, NGC 625, NGC 1705, and NGC 5253. Dust opacity at 250 pc resolution was derived based on dust temperatures estimated by fitting two-temperature modified blackbodies to Herschel PACS data. By using the HI maps, we were then able to estimate dust-to-gas ratios in the regions dominated by atomic gas, and, throughout the galaxy, to infer total gas column densities and H2 column densities as the difference with HI. Finally, from the ACA CO(1–0) maps, we derived XCO. We used a similar technique with 40 pc ALMA 12-m data for the three galaxies, but instead derived dust attenuation at 40 pc resolution from reddening maps based on VLT/MUSE data. At 250 pc resolution, we find XCO ∼ 1022 − 1023 cm−2/K km s−1, 5–1000 times the Milky Way value, with much larger values than would be expected from a simple metallicity dependence. Instead, at 40 pc resolution, XCO again shows large variation, but is roughly consistent with a power-law metallicity dependence, given the Z ∼ 1/3 Z⊙ metal abundances of our targets. The large scatter in both estimations could imply additional parameter dependence, which we have investigated by comparing XCO with the observed velocity-integrated brightness temperatures, ICO, as predicted by recent simulations. Indeed, larger XCO is significantly correlated with smaller ICO, but with slightly different slopes and normalizations than predicted by theory. Such behavior can be attributed to the increasing fraction of CO-faint (or dark) H2 gas with lower spatial resolution (larger beams). This confirms the idea the XCO is multivariate, depending not only on metallicity but also on the CO brightness temperature and beam size. Future work is needed to consolidate these empirical results by sampling galaxies with different metal abundances observed at varying spatial resolutions.

Minimal decoherence from inflation

We compute the rate with which super-Hubble cosmological fluctuations are decohered during inflation, by their gravitational interactions with unobserved shorter-wavelength scalar and tensor modes. We do so using Open Effective Field Theory methods, that remain under control at the late times of observational interest, contrary to perturbative calculations. Our result is minimal in the sense that it only incorporates the self-interactions predicted by General Relativity in single-clock models (additional interaction channels should only speed up decoherence). We find that decoherence is both suppressed by the first slow-roll parameter and by the energy density during inflation in Planckian units, but that it is enhanced by the volume comprised within the scale of interest, in Hubble units. This implies that, for the scales probed in the Cosmic Microwave Background, decoherence is effective as soon as inflation proceeds above ∼ 5 × 109 GeV. Alternatively, if inflation proceeds at GUT scale decoherence is incomplete only for the scales crossing out the Hubble radius in the last ∼ 13 e-folds of inflation. We also compute how short-wavelength scalar modes decohere primordial tensor perturbations, finding a faster rate unsuppressed by slow-roll parameters. Identifying the parametric dependence of decoherence, and the rate at which it proceeds, helps suggest ways to look for quantum effects.

Homomorphic filtering in digital multichannel image processing

Purpose. The purpose of this article is to develop a preprocessing method for digital multispectral remote sensing images obtained through optical and infrared means in the electromagnetic spectrum. The method aims to ensure invariance with respect to positional formation conditions that determine spatial and radiometric resolution. By implementing homomorphic filtering in this method, we can significantly increase the informative value of processed imagery. Methodology. The problem solving, including the development of the spatial and radiometric resolution increase ways for multispectral geospatial data are based on the methods of brightness spatial distribution fusion, methods of data dimension reduction, de-correlation techniques and geometric correction of image spatial distributions. Findings. The method of preprocessing digital remote sensing data has been developed, which is a component of the methodology for identifying geometric shapes (GS) of objects in multi-channel aerospace images, allowing for a significant improvement in their recognition efficiency when noise is present. Originality. The method of preprocessing photogrammetric scenes using homomorphic filtering to enhance their informational significance is proposed. The method ensures invariance to positional conditions of fixation, improves the accuracy of further recognition, eliminates the drawbacks of known methods associated with the existence of parametric uncertainty dependence, the features of fixation of species information, low values of information indices of synthesized images, and computational process peculiarities. Practical value. Practical value is consists in improving of identification accuracy of objects GS in digital geospatial data, in significant increasing of raster multispectral images information value and in rising of automated image processing efficiency. The use of the method can greatly enhance the value and usefulness of multispectral photogrammetric images in a wide range of applications, from environmental monitoring to urban planning.

Growth-Rate Prediction for Low-Speed Variable-Density Spatially Developing Turbulent Planar Shear Layers: Status and Prospects

Abstract Progress in analysis of the growth rate of low-speed variable-density spatially developing turbulent planar shear layers is examined from the viewpoint of global trends across the relevant parameter space. Several approaches have been shown to agree with available measurements. Here, it is noted that comparable agreement is also obtained using a simple extension of the canonical Kelvin–Helmholtz linear stability theory. Beyond the range of the experimentally explored parameter space, available predictions disagree qualitatively as well as quantitatively. To a degree that is not generally recognized, this indicates that the governing parameter dependences and associated phenomenology are open questions. Further investigation needed to address these questions is discussed.

Cocoon cooling emission in neutron star mergers

ABSTRACT In the gravitational wave event GW170817, there was a ∼10 h gap before electromagnetic (EM) observations, without detection of the cocoon. The cocoon is heated by a short gamma-ray burst (sGRB) jet propagating through the ejecta of a neutron star (NS) merger, and a part of the cocoon escapes the ejecta with an opening angle of 20°–30°. Here, we model the cocoon and calculate its EM emission. Our 2D hydrodynamic simulations suggest that the density and energy distributions, after entering homologous expansion, are well-fitted with power-law functions, in each of the relativistic and non-relativistic parts of the escaped cocoon. Modelling these features, we calculate the cooling emission analytically. We find that the cocoon outshines the r-process kilonova/macronova at early times (10–103 s), peaking at UV bands. The relativistic velocity of the cocoon’s photosphere is measurable with instruments such as Swift, ULTRASAT, and LSST. We also imply that energetic cocoons, including failed jets, might be detected as X-ray flashes. Our model clarifies the physics and parameter dependence, covering a wide variety of central engines and ejecta of NS mergers and sGRBs in the multimessenger era.

Parameter dependence of density pedestal width and correlation with pedestal turbulence in EAST type-I ELMy H-mode plasma

The density pedestal structures in a series of type-I ELMy H-mode discharges (0.6 MA/2.5 T) with upper single null (USN) divertor configuration have been studied in EAST. To obtain the pedestal width, density profiles are fitted via the modified hyperbolic tangent (mtanh) function and the two-line method. The pedestal widths from these two methods have a similar tendency. Significant impacts of pedestal poloidal beta and pedestal collisionality on the density pedestal width have been observed for the first time in EAST. The non-linear regressions suggest the density width scaling in type-I ELMy EAST plasma are wne∝c(νped⁎)0.27−0.33⋅(βp,ped)0.5−0.58. The density fluctuations in the bottom of the pedestal from the fluctuation reflectometry imply an enhanced density fluctuation (Pfluc) and an obvious spectral broadening in the high collisionality regime of νped⁎≥3. The experimental results suggest that the pedestal turbulence would play an important role in the evolution of the pedestal structure.

Reduced-order variational mode decomposition to reveal transient and non-stationary dynamics in fluid flows

A novel data-driven modal analysis method, reduced-order variational mode decomposition (RVMD), is proposed, inspired by the Hilbert–Huang transform and variational mode decomposition (VMD), to resolve transient or statistically non-stationary flow dynamics. First, the form of RVMD modes (referred to as an ‘elementary low-order dynamic process’, ELD) is constructed by combining low-order representation and the idea of intrinsic mode function, which enables the computed modes to characterize the non-stationary properties of space–time fluid flows. Then, the RVMD algorithm is designed based on VMD to achieve a low-redundant adaptive extraction of ELDs in flow data, with the modes computed by solving an elaborate optimization problem. Further, a combination of RVMD and Hilbert spectral analysis leads to a modal-based time-frequency analysis framework in the Hilbert view, providing a potentially powerful tool to discover, quantify and analyse the transient and non-stationary dynamics in complex flow problems. To provide a comprehensive evaluation, the computational cost and parameter dependence of RVMD are discussed, as well as the relations between RVMD and some classic modal decomposition methods. Finally, the virtues and utility of RVMD and the modal-based time-frequency analysis framework are well demonstrated via two canonical problems: the transient cylinder wake and the planar supersonic screeching jet.

Traveling wave structures and analysis of bifurcation and chaos theory for Biswas–Milovic Model in conjunction with Kudryshov’s law of refractive index

The present study investigates the generalized Biswas–Milovic model using Kudryshov’s law of refractive index by employing the G′/(bG′+G+a)-Expansion method. This technique facilitates the extraction of singular exponential, trigonometric and kink soliton solutions for the model under examination. The outcomes are subsequently presented as 2D, 3D, and contour plots. Additionally, the model is transformed into a planner dynamical system, and the bifurcation theory is utilized to explore all potential parameter dependencies of the governing model. The chaotic behavior of dynamical systems is also studied by adding an external periodic force. The phase portraits of the obtained findings are also displayed. The results demonstrate the rich and sophisticated behavior of dynamical systems and emphasized the significance of exact solutions for determining their behavior.

Modeling and simulation of supersonic nozzle gas jet laden with polydisperse fire suppressant particles injected from a bypass injector

Dry powder fire extinguishing techniques are widely used due to the environmental friendliness and high efficiency. An Eulerian-Lagrangian interphase coupled modeling is performed for 2D axisymmetric nozzle supersonic gas jets laden with polydisperse fire suppressant particles complying with a Rosin-Rammler distribution injected from a bypass injector. A corrected drag model is developed applicable for very large ranges of particle Reynolds and Mach numbers. A parametric study on performance indexes of jet determining the fire extinguishment efficiency indicates that an increase in injected particle velocity vp,inj, mean diameter dp,m or spread parameter ns, or decrease in mass flow rate qm,p usually causes a monotonous increase of particle streamwise average velocity vp,a, decrease of velocity inhomogeneity Φvp and dispersion Ψp. However, the monotonicity of parametric dependency is probably violated under extreme conditions. It is exemplified by the vp,a, Φvp or Ψp at very large vp,inj, or the Ψp at extremely large ns.

Collapsing the Tower - On the Complexity of Multistage Stochastic IPs

In this paper we study the computational complexity of solving a class of block structured integer programs (IPs) - so called multistage stochastic IPs. A multistage stochastic IP is an IP of the form min { c ⊺ x ∣ Ax = b , x ≥ 0 , x integral} where the constraint matrix A consists of small block matrices ordered on the diagonal line and for each stage there are larger blocks with few columns connecting the blocks in a tree like fashion. Over the last years there was enormous progress in the area of block structured IPs. For many of the known block IP classes - such as n -fold, tree-fold, and two-stage stochastic IPs, nearly matching upper and lower bounds are known concerning their computational complexity. One of the major gaps that remained however was the parameter dependency in the running time for an algorithm solving multistage stochastic IPs. Previous algorithms require a tower of t exponentials, where t is the number of stages. In contrast, only a double exponential lower bound was known based on the exponential time hypothesis. In this paper we show that the tower of t exponentials is actually not necessary. We show an improved running time of \(2^{(d\left\Vert A \right\Vert _\infty)^{\mathcal {O}(d^{3t+1})}} \cdot rn\log ^{\mathcal {O}(2^d)}(rn) \) for the algorithm solving multistage stochastic IPs, where d is the sum of columns in the connecting blocks and rn is the number of rows. Hence, we obtain the first bound by an elementary function for the running time of an algorithm solving multistage stochastic IPs. In contrast to previous works, our algorithm has only a triple exponential dependency on the parameters and only doubly exponential for every constant t . By this we come very close to the known double exponential bound that holds already for two-stage stochastic IPs, i.e. multistage stochastic IPs with two stages. The improved running time of the algorithm is based on new bounds for the proximity of multistage stochastic IPs. The idea behind the bound is based on generalization of a structural lemma originally used for two-stage stochastic IPs. While the structural lemma requires iteration to be applied to multistage stochastic IPs, our generalization directly applies to inherent combinatorial properties of multiple stages. Already a special case of our lemma yields an improved bound for the Graver complexity of multistage stochastic IPs.