Nonlinear Distribution Research Articles

Frequency Analysis of Asymmetric Circular Organic Solar Cells Embedded in an Elastic Medium under Hygrothermal Conditions

This research represents the first theoretical investigation about the vibration behavior of circular organic solar cells. Therefore, the vibration response of asymmetric circular organic solar cells that represent a perfect renewable energy source is demonstrated. For this purpose, the differential quadrature method (DQM) is employed. The organic solar cell is modeled as a laminated plate consisting of five layers of Al, P3HT:PCBM, PEDOT:PSS, ITO, and Glass. This cell is rested on a Winkler–Pasternak elastic foundation and assumed to be exposed to various types of hygrothermal loadings. There are three different kinds of temperature and moisture variations that are taken into account: uniform, linear, and nonlinear distribution throughout the cell’s thickness. The displacement field is presented based on a new inverse hyperbolic shear deformation theory considering only two unknowns. The motion equations including hygrothermal effect and plate–foundation interaction are established within the framework of Hamilton’s principle. The DQM is utilized to solve these equations. In order to ensure the accuracy of the proposed theory, the present results are compared with those reported by other higher-order theories. A comprehensive parametric illustration is conducted on the impacts of different parameters involving the geometrical configuration, elastic foundation parameters, temperature, and moisture concentration on the deduced eigenfrequency of the circular organic solar cells.

Kernel-based testing for single-cell differential analysis

Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges. We propose a kernel-testing framework for non-linear cell-wise distribution comparison, analyzing gene expression and epigenomic modifications. Our method allows feature-wise and global transcriptome/epigenome comparisons, revealing cell population heterogeneities. Using a classifier based on embedding variability, we identify transitions in cell states, overcoming limitations of traditional single-cell analysis. Applied to single-cell ChIP-Seq data, our approach identifies untreated breast cancer cells with an epigenomic profile resembling persister cells. This demonstrates the effectiveness of kernel testing in uncovering subtle population variations that might be missed by other methods.

Simplified Model for Suction Pile Stiffness under Combined Loading in Elastic Soil: A Winkler-based Approach

Suction pile foundations are a promising option for offshore structures in deep locations covered by soft soil. A reasonable prediction of foundation stiffness may offer a reliable method for estimating the dynamic performance of the overall structure. Although the Winkler-based approach can effectively analyze the stiffness of caisson foundations, the current models can underestimate and/or overestimate the global stiffness subjected to combined loading under a relatively large embedment depth-to-diameter ratio L/D. Moreover, the non-linear distribution of local stiffness with depth has been neglected in current research methods. Thus, this study established a simplified Winkler model capable of providing reliable predictions of suction pile foundation stiffness under combined loading in homogeneous elastic soil. Finite element analysis (FEA) was performed to establish inter-relationship of local stiffness with soil properties and foundation geometries via the concept of “Inferred Winkler model.” Furthermore, the non-linear distribution of local stiffness with depth was considered. Finally, the proposed method was assessed against the FEA and current models to evaluate its applicability with different L/D subject to general single and combined loadings.

Height-modulating horizontal transport of dust particles in a dusty plasma ratchet

Dust particles are often electrostatically trapped and levitated within the non-electroneutral region of a sheath. The fascinating transport phenomena of dust particles strongly depend on the plasma parameters surrounding them within the sheath, whereas, that are quite difficult to obtain, leading to an unclear understanding of particle transport mechanisms. Here, we demonstrate a tunable horizontal transport of micron-sized dust particles by precisely manipulating their vertically suspended heights in an asymmetric ratchet sheath by designing dusty plasma ratchet. A collection of dust particles serves as micro-probes to detect the height-dependent transport properties and the feature of the sheath. Two methods are employed to lift or reduce the suspended heights of dust particles while maintaining the sheath unchanged. As the suspended heights of dust particles vary, their directional transport changes accordingly, including a flow reversal. A two-dimensional model of the ratchet sheath depicts the nonlinear distributions of plasma parameters and reveals that these unexpected transport phenomena can be attributed to the dependence of the electric ratchet potential and the resulting non-equilibrium net ion drag force on the suspended heights of dust particles. Our combined experimental and theoretical study provides insights into the fundamental transport properties of dust particles in an asymmetrical sheath.

Voting model prediction of nonlinear behavior for double-circumferential-slot air bearing system

Double-circumferential-slot air bearing (DCSAB) systems provide multidirectional supporting forces and have high stiffness, increasing the stability of instruments at high rotational speeds. However, DCSAB systems may exhibit chaotic motion because of a nonlinear pressure distribution within the gas film, supplied gas imbalances, or an inappropriate design. This study investigated the occurrence of nonperiodic motion in a DCSAB system by analyzing the dynamic response of systems with different rotor masses and bearing numbers. The dynamic trajectory, spectral response, bifurcation, Poincaré map, and maximum Lyapunov exponent were analyzed to identify chaotic behavior. Behavior was found to be highly sensitive to rotor mass and bearing number; the system exhibits chaotic behavior when the rotor mass has values in three intervals within 0.1–6.0 kg given a fixed bearing number of Λ = 3.8. To reduce the computational cost of predicting chaotic behavior, the maximum Lyapunov exponent was predicted using various machine learning models; a voting model combining random forest with XGBoost has the highest performance. The results can be used as a guideline for designing of DCASB systems for use in industrial applications.

Nonlinearity effects on thermal transport properties of a mass-spring chain

Using Green’s function technique, we present a self-consistent formalism to study the phonon transport properties of an extended nonlinear mass-spring chain. We calculate the phonon transmission coefficient, thermal conductivity, and specific heat for some chains with different configurations of masses feeling the nonlinearity potential. The numerical results show that in a critical value of the nonlinearity coefficient, a sharp decrease in thermal conductivity will be observed. The same scenario happens in a critical temperature proportional to the inverse of the nonlinearity coefficient for the specific heat. Indeed, thermal conductor-insulator transition can occur in the system depending on the strength and distribution of nonlinearity. The model can aid our understanding of the effect of lattice nonlinearity on the thermal properties of one-dimensional materials to design the thermal switches.

Numerical investigation of the wheel-rail interaction in a stacked multibody system with multipoint frictional contact dynamics under strong earthquakes

Stacked multibody systems, exemplified by overhead cranes in nuclear power plants (OCNPP), play a crucial role in engineering applications. Under strong earthquakes, non-smooth behaviors, including detachment and stick-slip between wheels and rails, may induce uncertain motions, potentially triggering catastrophic accidents. In this study, a co-simulation method using ANSYS and MATLAB is proposed for modeling the stacked components. The wheel-rail relationship is modeled with multiple frictional unilateral constraints, which are delineated by a set-valued force law. The resultant contact-impact problem is formulated as a nonlinear complementarity problem, and then reconstructed and rescaled using a model smoothing method combined with a normalization technique to facilitate convergence. Lastly, numerical simulations are conducted, taking into account various wheel locking conditions, to explore the nonlinear behavior and stress distribution. The results illustrate the non-smooth characteristics of frictional contact within the stacked components. The presented work is expected to guide the structural optimization of stacked multibody systems.

The symmetric and asymmetric effect of financial development on ecological footprint in South Africa: ARDL and NARDL approach

Introduction: The literature on the finance–emission nexus offers conflicting conclusions. This study resolves this inconsistency by investigating the symmetric and asymmetric effect of financial development on ecological footprint in South Africa, using the Environmental Kuznets Curve framework as a guide. Given the coexistence of ecological deficits and world-class financial development systems in South Africa, it is essential to explore and evaluate potential solutions to mitigating these deficits. Our empirical analysis contributes to the body of literature on the impact of financial development and ecological footprint by using a comprehensive measure of financial development and disaggregates it into its sub-indices to provide a nuanced analysis.Method: This study employs the linear auto regressive distribution lag and nonlinear auto regressive distribution lag techniques to explore the complex interactions of financial development and ecological footprint.Results and Discussion: The findings of this research indicate that financial markets and institutions seem to have varying effects on the ecological footprint. Financial market indices promote environmental quality, while financial institutions exacerbate environmental quality. These results call for policymakers to craft a watertight process that will encourage both financial markets and institutions to allocate capital to projects that are pro-environmental.

Enhancing photovoltaic systems using Gaussian process regression for parameter identification and fault detection

In recent years, significant efforts have been made to enhance the power-harnessing capacity of photovoltaic (PV) systems. Despite advancements, PV systems remain less efficient. Faults occurring in the PV system are one of the major reasons for reduced output power. Improving PV system efficiency reduces overall costs and extends the system’s operational lifespan. This research utilizes a machine learning-based non-linear Gaussian posterior distribution (GPR) algorithm for detecting, classifying, and localizing various faults in PV systems. The proposed technique uses solar cell parameters to classify the faults based on the severity levels. The experimental results validate the effectiveness of the proposed approach, emphasizing its potential to improve PV system performance and reliability. The model statistics show that training time for squared exponential GPR is shorter than exponential and rational quadratic GPR models, with squared exponential GPR taking 2771.5 s, while exponential GPR and rational quadratic GPR took 4227.6 s and 6660.5 s, respectively. Despite longer training time, rational quadratic GPR has the lowest root mean squared error (RMSE) validation, ranging from 0.016598 to 0.025616, among the three approaches. Exponential GPR, with an RMSE range of 363.59 to 397.1 across various faults, was chosen for its superior performance when compared to the other approaches.

Optimisation strategy for coplanar array capacitance imaging in rotational scanning mode

ABSTRACT Coplanar array capacitive imaging represents a non-destructive testing technology. To address the challenge of reduced utilisation of the high-sensitivity region caused by the ‘soft field’ effect characterised by severe nonlinear and inhomogeneous distribution of coplanar array capacitance sensitivity, resulting in difficulties in solving the problem of medium distribution, the proposed approach involves coplanar array capacitance sensor rotational scanning technology. This paper establishes both a physical rotation model and a sensitive field rotation model for a coplanar array capacitance sensor, demonstrating the inability to resolve the low-sensitivity region for medium distribution and illustrating how rotary scanning detection can enhance the utilisation rate of the high-sensitivity region. In conjunction with improved regional energy contrast, the images acquired under various rotation angles are fused, and experimental verification is conducted. The experimental results underscore that rotational scanning detection techniques can increase the utilisation rate of the high-sensitivity region within the coplanar array capacitance sensor by 74.69%. This enhancement effectively captures essential information within the reconstructed image and successfully addresses the challenge of solving difficulties in dielectric distribution. The research outcomes provide valuable insights for advancing non-destructive testing technologies employing coplanar array capacitance sensors.

Active vibration control of piezoelectric multilayers FG‐CNTRC and FG‐GPLRC plates

AbstractThis study investigates the active vibration control of multilayer Functionally Graded Carbon NanoTube Reinforced polymer Composite (FG‐CNTRC) plates and multilayer functionally graded graphene platelets reinforced polymer composite (FG‐GPLRC) plates covered with a piezoelectric layer (PZTG1195N) serve as both actuators and sensors. The plate's heart is supposed to be reinforced nonlinearly using both types of reinforcement. Active vibration control of plates under uniform load was achieved by utilizing a velocity feedback control algorithm with a specific gain value. The finite element method is employed to analyze both the static and dynamic behavior of a square plate discretized into 9‐node quadratic finite elements with 5 ° of freedom per node. The material properties are assumed to change across the thickness direction following a power law distribution, exhibiting various patterns: Uniform Distribution (UD), as well as Functionally Graded types X, O, and A (FG‐X, FG‐O, and FG‐A). The geometrical nonlinear equations are solved by the Newmark integration method. This work begins by validating the natural frequencies of a Functionally Graded (FG) composite plate reinforced with four different distributions of Nano‐filler and then aims to show the effect of the nonlinear distribution of nanofillers on the plate's stiffness. The Results obtained after the execution of a developed code highlight the significance of employing a nonlinear distribution of nanofillers to attenuate vibrations.Highlights FG composite and sandwich plates reinforced with GPLs and CNTs. Effect of nonlinear nanofillers distribution of reinforcement on free and forced vibration. The ability of the nonlinear distribution of nanofillers to attenuate forced vibrations.

Second-order deformation behaviors of free-rotational tension after free-end torsion for rolled AZ31B magnesium alloy

The accompanying dimensional change caused by the second-order deformation behaviors severely limits the accuracy of the size and shape control of the structural components. The effect of the microstructure evolution mechanism on the second-order deformation behaviors (e.g., Swift effect, inverse Swift effect) of magnesium (Mg) alloys has not been systematically reported. Therefore, in this study, in order to promote the precision forming , the deformation mechanisms of the second-order mechanical behaviors of rolled AZ31B Mg alloy were systematically investigated by employing the specifically designed multi-degree of freedom and multi-axial force-field coupling loading mode. The free-end torsion (FET) experiments were carried out in the range of 30°–90° along the transverse direction (TD) at room temperature and the free-rotatial tension was performed after FET. The Swift effect of axial shortening was observed during FET, and the cumulative effect of misfit strain caused by tensile twinning is the main reason for the Swift effect. Meanwhile, obvious inverse Swift effect was detected in the free-rotatial tension. It is found that the external reverse residual shear stress dominates the rapid reverse rotation of the first stage in the inverse Swift effect, and the nonlinear distribution of the residual shear strain increases this reverse rotation. The competitive effect of detwinning caused by reverse rotation and prismatic slip leads to a slow reverse rotation. The prismatic slip provides the driving force for the inverse Swift effect in the positive rotation stage until the residual shear stress is completely released.

Composite LaNi0.6Fe0.4O3-δ - La0.9Sr0.1Sc0.9Co0.1O3-δ cathodes for proton conducting solid oxide fuel cells: Electrode kinetics study

Composite LaNi0.6Fe0.4O3-δ - La0.9Sr0.1Sc0.9Co0.1O3-δ (LNF-LSSCo) electrodes with the compositions 50/50, 60/40, and 80/20 wt% LNF/LSSCo are successfully applied for La0.9Sr0.1ScO3-δ proton conducting electrolyte. Electrochemical activity of the electrodes is studied by impedance spectroscopy, depending on temperature and oxygen partial pressure. The best performance is observed for 60/40 LNF/LSSCo electrodes. Detailed analysis of impedance data is performed using non-linear least squares and distribution of relaxation times methods taking into account the shunt effect of electronic conductivity of La0.9Sr0.1ScO3-δ electrolyte. Two main rate-determining stages of the electrode reaction are determined, which are assigned to oxygen ion diffusion in the bulk of the electrode and oxygen interphase exchange with the gas phase. The application of the LNF current collector layer improves the electrochemical activity of the electrodes without changes in the electrode reaction mechanism, while the modification of the electrodes with Pr6O11 leads to a sufficient decrease in the resistance of the stage, corresponding to oxygen interphase exchange, resulting in a twice-improved electrochemical activity of the electrodes.

Thermo-elastic Characteristics of Thermal Barrier Coating in a Gas Turbine Combustion Chamber with an Intermediate FGM Layer

This study is focused on the analysis of thermos-elastic characteristics of a gas turbine combustion chamber, where the inner surface experiences a higher temperature while the outer region of the wall should be thermally conductive to dissipate the heat of combustion. Using a single material is not suitable to ensure the above two requirements simultaneously. Instead of using a single material, a layered combustion chamber with high-temperature material at the inner region and thermally conductive material at the outer region can be a solution. This produces the problem of a sharp interface where disbonding occurs due to high thermal stresses. The problem of sharp interface can be eliminated by using a functionally graded material (FGM) layer in between the inner and outer layers of the combustion chamber. The present study considers a gas turbine combustion chamber consisting of three layers: the inner layer is used as a thermal barrier coating, the intermediate layer is a smooth transition from the inner layer to the outer layer, and the outer layer is a thermally conductive material. ANSYS simulation is used for the analysis of thermos-elastic characteristics of the combustion chamber with homogeneous and FGM intermediate layers. The effect of linear and nonlinear material distributions in the FGM layer on the thermos-elastic characteristics is studied. A comparison of results reveals that thermal stress smoothly changes from the inner layer to the outer layer in the case of the FGM intermediate layer compared to the homogeneous intermediate layer. This suggests that a combustion chamber with an FGM intermediate layer is more reliable than a homogeneous intermediate layer.

Elucidating the Etiology and Temporal Progress of Rust on Physic Nut Genotypes and Their Relationship with Environmental Conditions in Ecuador

Physic nut (Jatropha curcas L.) has emerged as a promising fruit crop in Ecuador, but the recent identification of rust poses a potential threat to its productive development. This study focused on elucidating the morphological aspects of the basidiomycete and assessing rust intensity across different canopy levels of physic nut hybrids and genotypes under field and semi-controlled conditions in Manabí, Ecuador. For the first time, this study confirms that Phakopsora arthuriana should be responsible for rust on physic nut in Ecuador based on the characteristics of the fungal structures. Rust incidence was 100% across all canopy layers, with the lower and middle canopies exhibiting higher severity and lesion numbers than the upper canopy. Using the Weibull nonlinear distribution model, we epidemiologically modeled disease progression, revealing that hybrid JAT 001100 displayed the highest temporal progress, recording 15% severity and an area under the disease progression curve of 3228.9 units. Promising genotypes CP-041 and CP-052 demonstrated lower rust intensity. Environmental parameters, including dew point, temperature, precipitation, and relative humidity, were correlated with rust severity and lesion numbers. In greenhouse assays, hybrid JAT 001165 showed higher severity, whereas JAT 001103 and JAT 001164 had more lesions than other genotypes. In contrast, promising genotypes CP-041 and CP-052 consistently exhibited lower rust intensity in both field and greenhouse environments. This study demonstrated that P. arthuriana could be epidemiologically modeled with the Weibull model, providing crucial insights into the dynamic interplay between rust infection and physic nut hybrids and genotypes under diverse conditions in the Manabí region of Ecuador.

Thermoelastic free vibration of rotating pretwisted porous p-FGM, e-FGM, and s-FGM conical shells in nonlinear temperature distribution

The free vibration response of rotating pretwisted functionally graded (FG) conical shells in nonlinear thermal conditions is investigated using a finite element approach with the purpose of application in turbomachinery blades. With the aid of power, exponential, and sigmoid laws, the pretwisted conical shell is functionally graded in its transverse direction. The distribution of both even and uneven porosity is considered. The one-dimensional Fourier heat conduction equation is used to assess the nonlinear temperature distribution across the thickness of the FG conical shell. Lagrange’s equation is used to obtain the dynamic equation of motion of the rotating pretwisted FG conical shell. The proposed finite element model employs an eight-noded isoparametric shell element with five degrees of freedom per node. The effect of several factors, including porosity, temperature, twist angle, and rotational speed on the free vibration response of the FG porous conical shell has been investigated. The findings reveal that the porosity volume fraction has a significant influence on the natural frequency. The nonlinear temperature difference and pretwist angle both cause stiffness reduction to the FG conical shell upon increasing, whereas the presence of rotational speed inducts geometrical stiffness resulting in centrifugal stiffening.

Multi-Source energy optimization method for supersonic aircraft based on multi-objective adaptive covariance matrix and chaotic search group algorithm

In the trend of increasing aircraft electrical power levels, future supersonic aircraft will have an urgent need for multi-source, adaptive, and high-energy-efficient approach to electrical power generation. In this paper, a multi-source energy optimization method based on multi-objective optimization algorithm MOACCGA is proposed. The method considers fuel consumption rate and thrust as the objective functions, with engine safety as a constraint. Based on the establishment of a small bypass ratio turbofan engine with multi-source energy extraction system, the influence mechanism of energy extraction on engine performance is analyzed. It is concluded that the generation of multi-source energy is optimizable, and the objective function has strong nonlinear and multi-peak distribution in the solution space. Then, the multi-objective adaptive covariance matrix and chaotic search group algorithm (MOACCGA) is proposed to solve the multi-source energy optimization problem. The algorithm utilizes the evolutionary approach with an adaptive covariance matrix to adapt to the strong nonlinearity of the system. Additionally, it overcomes the problem of getting trapped in local optima within the solution space characterized by multiple peak distributions by employing chaotic search. Finally, the multi-source energy optimization method is validated through simulations. In each condition, multi-source energy optimization can save fuel consumption by 0.7% of the total fuel consumption and reduce thrust loss by 1.5% of the total thrust.

A dual-reciprocity boundary element method based transient seepage model with nonlinear distributed point source dual-porosity gas reservoir

As a result of advancements in gas reservoir development technologies and a deeper understanding of seepage theory, numerous nonlinear seepage problems have emerged. Consequently, conventional analytical solution models are no longer applicable. Moreover, existing semi-analytical and numerical solution models suffer from issues like high computational complexity and limited flexibility, significantly constraining their practical utility. For this purpose, a gas reservoir transient seepage model is established based on the dual-reciprocity boundary element method (DRBEM). This model couples the wellbore storage coefficients with skin factor and introduces a novel dual-porosity transient interporosity seepage algorithm, enabling the resolution of transient seepage problems in dual-porosity gas reservoirs with nonlinear point source distributions. Additionally, it investigates the dynamic behavior of bottomhole pressure during the early production stage of gas wells, while capturing the dynamic pressure distribution within the seepage field. This approach offers the advantages of semi-analyticity, meshless, and eliminates the need for Laplace transforms, resulting in a significant reduction in computational complexity. Ultimately, the application of our model to well-pattern production with the production system transition issues, in conjunction with the log-log type curves of bottomhole pressure, and the dynamics of gas reservoir pressure, enables the analysis of interference characteristics between injection-production wells. This showcases the practical advantages of the model's application. The findings of this study provide valuable assistance for modeling and solving transient seepage problems in dual-porosity oil and gas reservoirs production. The application of DRBEM in unsteady-state diffusion, heat conduction, stress fields, and other potential field problems is relevant for reference.

Market risk spillover and the asymmetric effects of macroeconomic fundamentals on market risk across Vietnamese sectors

Global economic downturns and multiple extreme events threaten Vietnam's economy, leading to a surge in stock market risk and significant spillovers. This study investigates market risk spillovers and explores the asymmetric effects of macroeconomic indicators on market risk across 24 sectors in Vietnam from 2012 to 2022. We use the value-at-risk (VaR) technique and a vector autoregression (VAR) model to estimate market risks and their spillovers across Vietnamese sectors. We then examine the asymmetric effects of macroeconomic indicators on market risk using a panel nonlinear autoregressive distribution lag (NARDL) model. Our results confirm that Vietnam’s market risk increases rapidly in response to extreme events. Additionally, market risks exhibit substantial inter-connectedness across the Vietnamese sectors. The Building Materials, Technology, and Securities sectors are primary risk transmitters, whereas the Minerals, Development Investment, and Education sectors are major risk absorbers. Our results also confirm that market risk responds asymmetrically to changes in interest rates, exchange rates (USD/VND), trade openness, financial development, and economic growth in the short and long run. Minerals, Oil & Gas, and Rubber are the sectors that are most affected by macroeconomic indicators in the long run. Based on these important findings, implications focused on limiting market risks and their spillovers, along with sustainable investing, have emerged.

Stochastic ambulance dispatching and routing in mass casualty incident under road vulnerability

This paper investigates the stochastic ambulance dispatching and routing (SADR) problem with multiple casualty collection points in the mass casualty incidents (MCI) under uncertainty of road vulnerability and traffic congestion caused by an earthquake. A two-stage stochastic mixed-integer nonlinear programming model is formulated to derive a reliable and high-quality ambulance scheduling, dispatching and routing solution for maximizing expected number of survivors of all casualties. An integrated simulation optimization approach combining a data-driven travel time scenario generation algorithm, sample average approximation, and a column-generation-based heuristic method is developed to efficiently solve this complicated two-stage SADR model with a nonlinear objective function and continuous travel time distributions. Collaborating with the National Science and Technology Center for Disaster Reduction (NCDR), an empirical study using a potential real-world earthquake scenario occurring in Taiwan is conducted to demonstrate the usefulness and effectiveness of our proposed model and solution approach compared to the deterministic model and two current-practice heuristics.