Values Of Parameters Research Articles

Enhanced heat transfer and fluid motion in 3D nanofluid with anisotropic slip and magnetic field

Abstract A mathematical model is envisaged that discusses the motion of 3D nanofluids (NFs) with anisotropic slip influence magnetic field past a stretching sheet. The heat transportation phenomenon is analysed by melting effect, heat generation, and chemical reaction. The main motivation of this study is to analyse the behaviour of liquid motion and heat transfer (HT) of NFs because this study has huge applications in boiling, solar energy, and micropower generation, which are used in the engineering process. The physical governing partial differential equation is transformed into a coupled non-linear system of ordinary differential equations using suitable appropriate transformations. The translated equations are calculated using Runge–Kutta–Fehlberg method via shooting procedure. The physical characteristics of various parameters on velocities, concentration, and thermal fields are explored in detail. The HT is high in NFs when compared to pure or regular liquids for ascending values of heat source parameter and slip factor. Also, the skin friction coefficients via coordinate axes and rate of Nusselt number were analysed.

Characteristics analysis and structure optimization of a hybrid micro-jet impingement/micro-channel heat sink

To solve the heat dissipation problem of high-power electronics, a novel hybrid micro-jet impingement/micro-channel heat sink is proposed in this work. Different from the continuous and straight rectangular micro-channel, the inclined and interrupted channel walls (fins) are adopted to enhance the fluid disturbance inside the heat sink. To obtain the thermal–hydraulic performance of the hybrid heat sink, an overall 3D modeling and numerical simulations are conducted instead of local cell numerical simulation. In addition, to further improve the heat transfer and flow resistance performance, the effects of variation of structural parameters on heat transfer and flow resistance properties are investigated, including the fin inclination angle, fin length and fin height. The results of structural parametric analysis reveal that there are interactions between different structural parameters, but with different levels of significance for different evaluation indicators. Then, to obtain the optimal combinations of structural parameters for different applications, the multi-objective genetic algorithm coupled with artificial neural network (ANN) is utilized to search for the optimal value of each structural parameter. The heat transfer thermal resistance, pressure drop and mean absolute temperature deviation of the heated surface are utilized as the optimization objectives to evaluate the cooling and resistance characteristics. The optimization results obtained by three-objective optimization and two-objective optimization are analyzed and compared. Finally, seven optimal compromise solutions are selected from the Pareto front by using TOPSIS algorithm with different weight factor matrices. For the optimal compromise solutions, the maximum relative errors between the predicted values of the ANN and numerical simulation values are only 3%, which further demonstrates the accuracy of the artificial neural network model and the effectiveness of using multi-objective optimization to guide heat sink design.

GLOBAL SENSITIVITY ANALYSIS AND OPTIMAL CONTROL OF TYPHOID FEVER TRANSMISSION DYNAMICS

This paper presents a mathematical model aimed at studying the global behaviour and optimal control strategies for Typhoid fever. The primary objective of this study is to identify the most effective control strategy that minimizes the spread of the disease. To achieve this, we calculate the effective and basic reproduction numbers and utilize them to investigate the existence and stability of the equilibria. Furthermore, we investigate the global impact of each model parameter on the variables using Latin Hypercube Sampling and Partial Rank Correlation Coefficient. The necessary conditions of the optimal control problem are analyzed using Pontryagin’s maximum principle, and the numerical values of the model parameters are estimated using the maximum likelihood estimator. The results indicate that the optimal use of vaccination for susceptible individuals, as well as the screening and treatment of asymptomatic infected individuals, have a significant impact on reducing the spread of the disease in endemic regions.

An Individual-Based Spatial Epidemiological Model for the Spread of Plant Diseases

AbstractIn the study of plant disease epidemics, the state of each individual in the population and their spatial location should be considered when modeling disease spread. We present a model to describe the spread of plant diseases, where the infection of a susceptible individual depends on the transmission rate of infected individuals and the spatial correlation. This latter is introduced through the Matérn correlation function, accounting for spatial dependence based on distance. Almond leaf scorch disease, caused by the bacterium Xylella fastidiosa, was used as a case study to test the behavior of the model parameters and the variability due to the characteristics and location of initial disease introduction using a proposed simulation algorithm. The greatest variability in the results depended on the range parameter of the Matérn correlation, i.e., the distance at which two observations can be considered spatially uncorrelated, and the initial introduction. The spatial distribution of individuals also had a strong influence on disease spread, highlighting that areas without trees acted as barriers when their extent was greater than the range parameter. It should be stressed that this individual-based model can be applied to other plant diseases, adapting the parameter values to their particular epidemiological characteristics.

Principle of multi-critical-points in the ALP-Higgs model and the corresponding phase transition

The principle of multi-critical-points (PMCP) may be a convincing approach to determine the emerging parameter values in different kinds of beyond-standard-model (BSM) models. This could certainly be applied to solve the problem of undetermined new parameters in the ALP-Higgs interaction models. In this paper, we apply this principle to such model and investigate whether there are suitable solutions. Then, using the 1-loop effective potential, we study the phase transition property of this model under the PMCP requirement. It is gratifying to find that under the requirement of PMCP, the phase transition can be not only first-order, but also strong enough to serve as a solution for electroweak baryongenesis (EWBG). Finally, we show the parameter space of ALP and provide the parameter range that leads to the first-order phase transition.

Soret Effect on MHD Casson Fluid over an Accelerated Plate with the Help of Constant Proportional Caputo Fractional Derivative.

Non-Newtonian fluid flow is significant in engineering and biomedical applications such as thermal exchangers, electrical cooling mechanisms, nuclear reactor cooling, drug delivery, blood flow analysis, and tissue engineering. The Caputo operator has emerged as a prevalent tool in fractional calculus, garnering widespread recognition. This research aims to introduce a novel derivative by merging the proportional and Caputo operators, resulting in the fractional operator known as the constant proportional Caputo. In order to demonstrate this newly defined operator's dynamic qualities, it was employed in the analysis of the unsteady Casson flow model. In addition, the current work shows an analytical analysis to determine the Soret effect on the fractionalized MHD Casson fluid over an oscillating vertical plate. Fractional partial differential equations (PDEs) are used to formulate the problem along with IBCs. The introduction of appropriate nondimensional variables converts the PDEs into dimensionless form. The precise solutions to the fractional governing PDEs are then determined by the Laplace transform method. Velocity, concentration, and temperature profiles; the impacts of the Prandtl number; fractional parameter β and γ; and Soret and Schmidt numbers are graphically depicted. The profiles of temperature, concentration, and velocity rise with rising time and fractional parameters. Interestingly, as the Casson flow parameter is higher, fluid velocity decreases closest to the plate but increases away from the plate. Tables showing the findings for the skin-friction coefficient, Sherwood, and Nusselt numbers for a range of flow-controlling parameter values are provided. Furthermore, an investigation is undertaken to compare fractionalized and ordinary velocity fields. The results suggest that the fractional model employing a constant proportional derivative exhibits a quicker decay than the model incorporating conventional Caputo and Caputo-Fabrizio operators.

Study of electromagnetic damping of an oscillating bar magnet and its energy budget

The oscillation of a bar magnet along the axis of a closed loop solenoid has been studied quantitatively using an ultrasonic sensor and Arduino microcontroller-based platform. Real-time displacement of the oscillatory magnet with and without the solenoid shows an additional damping effect due to electromagnetic induction in the presence of the closed-loop solenoid. Variation of the induced current in the solenoid circuit has been analyzed over several cycles by simultaneous recording of the voltage developed across two resistors using ‘analogread’ library function. Energy drained from the oscillator due to electromagnetic damping has been compared with the energy lost in Joule heating of the solenoid circuit. A phase plot for the underdamped oscillator was generated using the fitting parameter values of the curve fitted with the position vs. time data points on the plot. This portable and inexpensive microcontroller-based design is well suited for STEM education of high school and for sophomores in an undergraduate physics course.

Development of renewable energy fed three-level hybrid active filter for EV charging station load using Jaya grey wolf optimization

This work develops a hybrid active power filter (HAPF) in this article to operate in conjunction with the energy storage system (ESS), wind power generation system (WPGS), and solar energy system (SES). It employs three level shunt voltage source converters (VSC) connected to the DC-bus. Optimization of the gain values of the fractional-order proportional integral derivative controller (FOPIDC) and parameter values of the HAPF is achieved using the Jaya grey wolf hybrid algorithm (GWJA). The primary objectives of this study, aimed at enhancing power quality (PQ), include: (1) ensuring swift stabilization of DC link capacitor voltage (DCLCV); (2) reducing harmonics and improving power factor (PF); (3) maintaining satisfactory performance under different combinations of loads like EV charging load, non linear load and solar irradiation conditions. The proposed controller's performance is evaluated through three test scenarios featuring different load configurations and irradiation levels. Additionally, the HAPF is subjected to design using other optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) to assess their respective contributions to PQ improvement.

Current fluctuations in a partially asymmetric simple exclusion process with a defect particle.

We study an exclusion process on a ring comprising a free defect particle in a bath of normal particles. The model is one of the few integrable cases in which the bath particles are partially asymmetric. The presence of the free defect creates localized or shock phases according to parameter values. We use a functional approach to Bethe equationsresulting from a nested Bethe ansatz to calculate exactly the mean currents and diffusion constants. The results agree very well with Monte Carlo simulations and reveal the main modes of fluctuation in the different phases of the steady state.

Randomized block quasi-Monte Carlo sampling for generalized likelihood uncertainty estimation

Abstract Although hydrological model forecasts aid water management decisions, they normally have predictive uncertainties. Generalized likelihood uncertainty estimation (GLUE) is popular for constructing predictive uncertainty bounds (PUBs). GLUE is based on simple Monte Carlo sampling (SMCS), a technique known to be ineffective in establishing behavioural simulations. This study introduced randomized block quasi-Monte Carlo sampling (RBMC). In RBMC, each parameter's range is divided into a stipulated number of sub-blocks (Snb). Parameters' values are separately generated in each sub-block. Finally, the sub-blocks are shuffled while maintaining the sequence of generated values in each sub-block. When Snb is equal to the number of simulations, RBMC reduces to SMCS. Otherwise, each Snb leads to a separate RBMC configuration or sampling scheme. The number of RBMC-based behavioural solutions was often found to be greater than that of SMCS, in some cases, by up to 33.6%. The width of the 90% confidence interval on 95th percentile flow based on SMCS was often larger than those of RBMC, sometimes by up to 23.4%. PUBs were found to vary in widths among RBMC configurations, thereby revealing the influence of the choice of a sampling scheme. Thus, GLUE based on RBMC is recommended to take into account the said influence.

Estimation of actual evapotranspiration from different ecosystems on the Tibetan Plateau based on a generalized complementary evapotranspiration theory model

AbstractActual evapotranspiration constitutes a vital component of the exchange of energy and water vapour between the soil‐vegetation and atmospheric systems on terrestrial terrain. Nevertheless, the Tibetan Plateau, owing to its austere environmental conditions, harbours a scarcity of terrestrial monitoring stations. This circumstance presents a formidable challenge in attaining precise estimations of actual evapotranspiration. The complementary relationship method is a potential approach because it requires only routine meteorological data to estimate actual evapotranspiration on a regional or global scale. However, the suitability of the complementary relationship model across diverse ecosystems on the Tibetan Plateau necessitates further investigation. In this study, we scrutinized the simulation of daily and monthly actual evapotranspiration across 18 observation sites spanning eight distinct land use categories on the Tibetan Plateau. We employed the polynomial generalized complementary function introduced by Brutsaert (B2015), alongside its enhanced rendition proposed by Szilagyi (S2017) and Crago (C2018). The outcomes reveal that all three models adeptly replicate the fluctuations in actual evapotranspiration, irrespective of land use category or temporal scale—whether daily or monthly. This is true regardless of whether original or calibrated parameter values are applied. However, there exist significant variations in the performance of these models. In general, the C2018 model demonstrates superior performance across most ecosystems when original parameters are employed. Following parameter calibration, the simulation efficacy of the models experienced marked enhancement. Post parameter calibration, the B2015 model outperforms the other two models notably in desert and wetland environments. Furthermore, the simulation outputs from all three models display heightened sensitivity to parameter α, particularly in the context of the C2018 and S2017 models. These findings suggest that accurate estimation of parameter values is critical to improving the accuracy of estimating actual evapotranspiration. Calibrated parameter values, contingent on a fusion of vegetation, meteorology and surface roughness, exhibit variability across diverse ecosystems.

Dynamics of M-truncated optical solitons and other solutions to the fractional Kudryashov’s equation

The study of soliton theory plays a crucial role in the telecommunication industry’s utilization of nonlinear optics. The principal area of research in the field of optical solitons revolves around optical fibers, metamaterials, metasurfaces, magneto-optic waveguides, and other related technologies. Therefore, the examination of these solitons received significant attention from scholars in recent years. Optical solitons refer to electromagnetic waves that are confined within nonlinear dispersive medium, wherein the balance between dispersion and nonlinearity effects enables the intensity to remain constant. In this manuscript, the dynamical behavior of Kudryashov’s equation is discussed with the assistance of truncated M-fractional derivative. Kudryashov’s equation is a mathematical model utilized to characterize complex phenomena in telecommunications and transmission technology. It describes the propagation of nonlinear pulses in optical fibers. Different forms of soliton solutions like bright, dark, singular and combo solitions have been extracted. Moreover, hyperbolic, periodic and Jacobi elliptic function solutions are recovered. Two recently modern integration tools like Φ6-expansion method and modified generalized exponential rational function method have been adopted to recover the solutions. The used methods not only provides previously extracted solutions but also secures new solutions. In order to visually depict the output, a variety of graphs featuring distinct shapes are produced in response to appropriate parameter values. The results obtained from this research indicate that the chosen methodologies are effective in improving the understanding of nonlinear dynamical phenomena. A large number of engineers who employ engineering models are expected to find this research interesting. The results demonstrate that the selected methods are practical, straightforward to implement, and applicable to intricate systems across numerous domains, with a specific emphasis on the field of optical fibers. The findings indicate that the system may contain a considerable number of soliton structures.

Host Dependency of Boundary between Strong and Weak Crystal Field Strength of Cr3+ Luminescence.

Cr3+ doped near-infrared phosphors hold significant applications and generate considerable research interest. The critical parameter for assessing the strength of the crystal field for Cr3+ in the Tanabe-Sugano diagram is the boundary value of Dq/B, representing the ratio of crystal field splitting to the Racah parameter B. Nevertheless, there are conflicting values for this parameter, as reported in various studies, such as 2.1, 2.2, and 2.3 for C/B = 4.5-4.8. Moreover, some Cr3+ doped phosphors with wide-band emissions exhibit a Dq/B value that falls within the region of a contradictory strong field. In this study, we numerically determine the boundary value of Dq/B, which distinguishes between strong and weak fields. The results then demonstrate a dependence on the host material and are correlated with the values of Racah parameters B and C. This work resolves the inconsistency between the boundary values of Dq/B and the emission profile of Cr3+, providing researchers with a more profound comprehension of Cr3+ luminescence.

Semi-analytic modelling of Pop. III star formation and metallicity evolution - I. Impact on the UV luminosity functions at z = 9 − 16

Abstract We implemented Population III (Pop. III) star formation in mini-halos within the meraxes semi-analytic galaxy formation and reionisation model, run on top of a N-body simulation with L = 10h−1 cMpc with 20483 particles resolving all dark matter halos down to the mini-halos (∼105M⊙). Our modelling includes the chemical evolution of the IGM, with metals released through supernova-driven bubbles that expand according to the Sedov-Taylor model. We found that SN-driven metal bubbles are generally small, with radii typically of 150 ckpc at z = 6. Hence, the majority of the first galaxies are likely enriched by their own star formation. However, as reionization progresses, the feedback effects from the UV background become more pronounced, leading to a halt in star formation in low-mass galaxies, after which external chemical enrichment becomes more relevant. We explore the sensitivity of the star formation rate density and stellar mass functions on the unknown values of free parameters. We also discuss the observability of Pop. III dominated systems with JWST, finding that the inclusion of Pop. III galaxies can have a significant effect on the total UV luminosity function at z = 12 − 16. Our results support the idea that the excess of bright galaxies detected with JWST might be explained by the presence of bright top-heavy Pop. III dominated galaxies without requiring an increased star formation efficiency.

Random Forest Regression Analysis for Estimating Dielectric Properties in Epoxy Composites Doped with Hybrid Nano Fillers

Bisphenol-A resin epoxy resin composites doped with various concentrations of inorganic hybrid nanofillers, TiO2 + ZnO, were thoroughly examined in the research described in this report for their microwave dielectric relaxation spectroscopy. Ultrasonic dispersion techniques were used to disperse the TiO2 + ZnO hybrid nanofiller into the Bisphenol-A resin. X-ray diffraction (XRD) was employed to ascertain the structural characteristics of the TiO2 and ZnO nanoparticles (NPs) and TiO2 + ZnO hybrid NPs doped neat epoxy (epoxy + hardener). A Vector network analyzer was used to measure the dielectric properties of the hybrid NPs doped neat epoxy in the frequency range from 200 MHz to 20 GHz. Our findings offer important new perspectives on the polarization mechanisms and structural properties of these composite materials. The complex relationship between frequency and dielectric characterization led to measurement complexities that often come with extensive time and cost requirements. This paper presents the random forest regression model as an effective method for predicting the frequency-dependent dielectric constants in composite materials. The main objective of this study was to examine the performance metrics, such as the adjusted R-squared score, root mean squared error (RMSE), and mean absolute error (MAE), across various values of the minimum node size parameter (n min). This study showcases the effectiveness of the RF regression model to accurately and efficiently predict the frequency-dependent dielectric constants in composites. As a result, it eliminates the requirement for laborious and expensive laboratory testing.

Numerical analysis of field aging in asphalt pavements via coupling of diffusion process and kinetics aging model

The asphalt aging model is a crucial module in the Mechanistic-Empirical (ME) pavement design programme for asphalt pavement performance prediction. In this study, an analytical aging model that couples diffusion and kinetics aging model (CDKAM) is improved to analyze and predict the field aging of asphalt pavements. The complex modulus (E*) of field cores was used as the aging property to illustrate the derivation of explicit expressions of time-averaged thermal source term ( TST ¯ ( t ) ) and time-averaged diffusion coefficient ( D ¯ ( t ) ). The value of the material-related parameter (M) in TST ¯ ( t ) model differs among different mixtures, which could assess the mixture’s susceptibility to thermal oxidation. The CDKAM with TST ¯ ( t ) and D ¯ ( t ) was used to predict E* of field aging for asphalt pavements in Texas after 22-month service life. The calibrated CDKAM could reasonably quantify the aging extent over time and the aging gradient over depth for studied asphalt pavements.

Quasi-Global Sensitivity Analysis of Supersonic Computational Fluid Dynamics Simulations

Determining the sensitivity of model outputs to input parameters is an important precursor to developing informative parameter studies, building surrogate models, and performing rigorous uncertainty quantification. Determining parameter sensitivities over a range of parameter values, termed global sensitivity analysis, requires many model evaluations sampled over the parameter space, which is intractable for many large-scale computational fluid dynamics (CFD) applications. For moderate parameter dimensions, we propose the use of Morris screening, a one-at-a-time quasi-global method for estimating parameter sensitivities over a range of parameter values for CFD simulations. The Morris method is implemented within a CFD framework that utilizes adaptive grid refinement, thereby enabling its application to state-of-the-art production-level problems. The method is shown to be viable for a model problem of supersonic flow over an axisymmetric capsule geometry with both physical and nonphysical (i.e., simulation-informing) input parameters. It is shown that Morris screening identifies relative parameter sensitivities consistent with those of more costly experimental and computational studies that were previously performed on this geometry.

Phylogenetic analyses of the leafhopper tribe Chiasmini Distant, 1908 and delimination of species of the genus Exitianus Ball, 1929 (Hemiptera: Cicadellidae: Deltocephalinae: Chiasmini) in China based on molecular data

Previous phylogenetic analyses of the grass-specialist leafhopper tribe Chiasmini have resolved relationships among genera but have included few representatives of individual genera. Here the phylogeny of 20 Chinese species belonging to 8 chiasmine genera was investigated by combining DNA sequence data from two mitochondrial genes (COI, 16S) and two nuclear genes (H3, 28S). In both maximum likelihood (ML) and Bayesian inference (BI) analyses, relationships among genera were largely consistent with prior analyses, with most members of the tribe placed into two sister clades: (Exitianus + Nephotettix) and the remaining five sampled genera. To examine morphology-based species definitions in the taxonomically difficult genus Exitianus Ball, 1929, one mitochondrial gene (COI) and one nuclear gene (ITS2) were used to infer the phylogenetic relationships and status of two common and widespread species and compare the performance of different molecular species-delimitation methods. These analyses divide the included populations into two well-supported clades corresponding to current morphological species concepts but some inconsistencies occurred under the jMOTU, ABGD and bPTP methods depending on the which gene and analytical parameter values were selected. Considering the variable results yielded by methods employing single loci, the BPP method, which combines data from multiple loci, may be more reliable in Exitianus.

Impact of Glycosylation on Protein-Protein Self-Interactions of Monoclonal Antibodies.

Protein self-interactions measured via second osmotic virial coefficients (B22) and dynamic light scattering interaction parameter values (kD) are often used as metrics for assessing the favorability of protein candidates and different formulations during monoclonal antibody (MAb) product development. Model predictions of B22 or kD typically do not account for glycans, though glycosylation can potentially impact experimental MAb self-interactions. To the best of our knowledge, the impact of MAb glycosylation on the experimentally measured B22 and kD values has not yet been reported. B22 and kD values of two fully deglycosylated MAbs and their native (i.e., fully glycosylated) counterparts were measured by light scattering over a range of pH and ionic strength conditions. Significant differences between B22 and kD of the native and deglycosylated forms were observed at a range of low to high ionic strengths used to modulate the effect of electrostatic contributions. Differences were most pronounced at low ionic strength, indicating that electrostatic interactions are a contributing factor. Though B22 and kD values were statistically equivalent at high ionic strengths where electrostatics were fully screened, we observed protein-dependent qualitative differences, which indicate that steric interactions may also play a role in the observed B22 and kD differences. A domain-level coarse-grained molecular model accounting for charge differences was considered to potentially provide additional insight but was not fully predictive of the behavior across all of the solution conditions investigated. This highlights that both the level of modeling and lack of inclusion of glycans may limit existing models in making quantitatively accurate predictions of self-interactions.

Generalized wormhole models within galactic halo region in torsion and matter coupling gravity formalism

In the current analysis, we investigate the possible existence of generalized Wormhole models within the galactic halo region by analyzing specific dark matter models. The observational data is checked in the framework of torsion within minimal matter coupling gravity. By using the variational approach modified versions of the field equations under the anisotropic source of matter are calculated. To discuss the specific necessary characteristics of the embedded wormhole geometry, we have analyzed the energy conditions under the effect of dark matter halos. We consider two embedded wormhole-specific shape functions in terms of the tortoise coordinate for the current study. Further, we compare different wormhole solutions for the different regional ranges depending on the involved parametric values. To check the effect of the dark matter halos, we use the observational data within the signature of the M87 galaxy and the Milky Way galaxy.