Nonlinear Effects Research Articles

Nonlinear Crack-Wave Modulations in Shear Horizontal Wave Propagation for Fatigue Crack Detection

The nonlinear interaction of shear horizontal waves with fatigue cracks is investigated for structural damage detection. The focus is on the non-classical modulation effect in the presence of damage. The major principle of the method is explained theoretically and supported by a semi-analytical solution. The method is tested experimentally in aluminium beams with fatigue cracks. A combination of high-frequency ultrasonic and low-frequency vibration shear excitations are introduced to monitored beam components using low-profile piezoceramic shear actuators. Nonlinear vibro-acoustic responses are gathered using laser vibrometry. Vibration excitation frequencies are selected using experimental and numerical modal analysis. A series of vibro-acoustic experiments is performed for fatigue crack detection. The results show that the non-classical nonlinear vibro-acoustic effect – based on shear horizontal wave propagation – can be used for crack detection. In addition, the method also allows for damage localisation.

Spool-Nematic Ordering of dsDNA and dsRNA under Confinement.

The ability of double-stranded DNA or RNA to locally melt and form kinks leads to strong nonlinear elasticity effects that qualitatively affect their packing in confined spaces. Using analytical theory and numerical simulation we show that kink formation entails a mixed spool-nematic ordering of double-stranded DNA or RNA in spherical capsids, consisting of an outer spool domain and an inner, twisted nematic domain. These findings explain the experimentally observed nematic domains in viral capsids and imply that nonlinear elasticity must be considered to predict the configurations and dynamics of double-stranded genomes in viruses, bacterial nucleoids or gene-delivery vehicles. The nonlinear elastic theory suggests that spool-nematic ordering is a general feature of strongly confined kinkable polymers.

Exploring swirling flow dynamics: Unsupervised machine learning in Maxwell hybrid nanofluid convection over an exponentially stretching cylinder with non-linear radiation effects

This article analyses the flow of Maxwell hybrid nanofluid induced by an exponentially stretching and rotating cylinder. The presence of non-linear convection, non-linear radiation, and magnetic field is also assumed. The factors covered in the study has a wide spectrum of application in various disciplines, and therefore we analyse the influence of different flow parameters after numerically solving the set of modelled differential equations. A data-free physics-informed neural network using a wavelet activation function is used to approximate the numerical solution. The reliability of the used methodology is validated by comparing the results of the limiting case with the available results. The paper demonstrates the effectiveness of using PINN in an unsupervised fashion to tackle fluid flow problems, showcasing their ability to provide reliable and accurate solutions without the need for extensive datasets. This approach highlights the potential of PINN to address complex fluid dynamics problems by utilizing physical laws within the neural network framework. From the numerical study, it is observed that hybrid nanofluid has a better rate of heat transfer compared to the nanofluid. Furthermore, radiation parameter and maxwell flow parameter is seen to exhibit significant impact of the flow profiles.

Impact of ICT diffusion and opportunity entrepreneurship on environmental sustainability in Saudi Arabia

The need to prioritize sustainable development is expanding in light of the world's environmental concerns. To address these concerns, entrepreneurship is essential as a catalyst for inventions, economic expansion, and social change. Entrepreneurship activities have direct and indirect effects in the face of environmental risks and uncertainties. This study addresses gaps in understanding entrepreneurship's non-linear and complementarity effects, particularly opportunity-driven entrepreneurship and information and communication technologies (ICT), on the quality of the environment in Saudi Arabia. The dynamic ordinary least squares (DOLS) method is used to estimate long-run relationships. Saudi Arabia will be the perfect context for sustainability because the country has prioritized sustainability through its Vision 2030, and the Saudi government has substantially supported entrepreneurship. The main contribution of this paper to the existing literature is evident in its examination of the quadratic relationships between both opportunity-driven entrepreneurship and ICT diffusion, including ICT access, use, and skills, on environmental quality. In addition, the study delves into the ICT diffusion's modulating effects on the nexus of opportunity entrepreneurship with environmental quality, providing insights into how these factors can effectively improve environmental quality. The findings show that opportunity entrepreneurship and ICT diffusion initially deteriorate environmental quality before leading to improvements as their levels mature in the economy. Moreover, interactions between ICT proxies and opportunity entrepreneurship yield mixed effects, with negative net effects on CO2 emissions and ecological footprint countered by positive net effects on the environmental performance index. These findings highlight the dual role of ICT diffusion as a contributor to environmental challenges and a potential solution, depending on the level of its diffusion and interaction with entrepreneurial activities. Therefore, policymakers should create plans that encourage and direct business activity toward more environmentally friendly methods. They should also consider the short- and long-term effects of growing digital technologies on environmental sustainability and how they might revolutionize how entrepreneurship and sustainability goals are aligned.

The pharmacokinetic differences between 10- and 15-μg daily vitamin D doses.

The reference nutrient intake for vitamin D in people aged ≥4years is 10μg/day (400 IU/day) in the UK, but the recommended daily allowance is 15 μg/day (600 IU/day) for people aged 1-70 years in the USA. Here, we aim to compare the 25-hydroxyvitamin D (25(OH)D) serum concentration profiles between the 2 doses. With world-wide trial data of adults aged ≥18 years, 45-93 kg, we constructed a minimal physiologically based pharmacokinetics model of serum concentrations of vitamin D and 25(OH)D using nonlinear mixed effects modelling. We used this model to forecast the mean, 2.5th and 97.5th percentiles for serum 25(OH)D concentrations in British adults aged ≥16 years. Our final model used bodyweight to adjust volume of each compartment and maximum clearance of 25(OH)D. No other covariate was identified. The model accurately predicted independent data from trials of a broad range of dosing regimens. We simulated British adults and showed that circulating 25(OH)D concentrations in 95% of people taking 10μg/day for a year is predicted to reach 50 nmol/L in 32 weeks, while 97.5% of those on 15 μg/day were predicted to attain this threshold within 28 weeks. Both doses are efficacious in >95% of the British population. The daily dose of 15 μg can help 97.5% of the British adults achieve 50 nmol/L serum 25(OH)D and reach the 25 nmol/L threshold in 4weeks.

Система ввода цифровых предыскажений на основе обобщенной полиномиальной модели с памятью для GaN усилителей мощности

Modern power amplifiers based on GaN transistors face a number of problems related to their physical properties and operating conditions. The high output power of such power amplifiers is accompanied by significant nonlinear distortions, especially when operating in saturation mode. Amplifiers based on GaN transistors have pronounced «short» memory effects, which leads to the dependence of current distortions on previous signal states. At the same time, support for broadband signals requires high processing speeds and large computing resources. Classical digital pre-distortion methods do not always cope with the task of effectively compensating for real-time distortion for power amplifiers based on GaN transistors. These problems complicate the process of linearization of power amplifiers based on GaN transistors and require the development of new methods that can effectively compensate for non-linearities and memory effects without significantly increasing the cost and complexity of the system. The purpose of the work is to create and analyze the effectiveness of a digital pre-imaging system based on a generalized polynomial model with memory to improve the linearity and efficiency of power amplifiers based on GaN transistors in wireless communication systems. The paper presents the architecture of the digital preimage input system based on a generalized polynomial model with memory. The use of this model makes it possible to improve the efficiency of suppressing nonlinear distortions at the output of a power amplifier based on GaN transistors. Practical significance – the proposed architecture can be implemented on FPGAs, VLSI or SOC with a minimum amount of computing resources.

Forecasting realized volatility with spillover effects: Perspectives from graph neural networks

We present a novel nonparametric methodology for modeling and forecasting multivariate realized volatilities using customized graph neural networks to incorporate spillover effects across stocks. The proposed model offers the benefits of incorporating spillover effects from multi-hop neighbors, capturing nonlinear relationships, and flexible training with different loss functions. The empirical findings suggest that incorporating spillover effects from multi-hop neighbors alone does not yield a clear advantage in terms of predictive accuracy. Furthermore, modeling nonlinear spillover effects enhances the forecasting accuracy of realized volatilities, particularly for short-term horizons of up to one week. More importantly, our results consistently indicate that training with the quasi-likelihood loss leads to substantial improvements in model performance compared to the commonly used mean squared error, primarily due to its superior handling of heteroskedasticity. A comprehensive series of empirical evaluations in alternative settings confirm the robustness of our results.

Nonlinear associations and threshold effects between agricultural industrial development and carbon emissions: insights from China

Abstract With the inevitability of global climate change, it has become increasingly important to understand the relationship between Agro-industrial Development (AID) and Agricultural Carbon Emissions (ACE) to promote the development of low carbon production in agriculture. Using a panel of datasets, as based on the ‘element-structure-function’ framework of 30 Chinese provinces over the period from 2011–2021, the entropy weight method was used to calculate the level of AID in each province. With this approach, it was possible to assess correlations and mechanisms between AID and ACE. Here, with use of fixed-effect, regulatory and threshold models, we determined some of the critical factors contributing to the effects of AID and ACE. Our findings revealed: (1) AID displays an inverse U-shape relationship with ACE, as verified through endogeneity and robustness assessment, (2) A review of the mechanisms suggests that the crossing of the turning point of the inverted u-curve can be accelerated by the moderating effect of agricultural finance. and (3) As based on the threshold effect analysis, a two-tier effect of the digital economy, rural human capital and farmers’ net income on AID, with facilitating effects on carbon emission reductions was obtained after the threshold crossing. The significance of this effect increases as a function of the post-threshold interval. Taken together, these findings demonstrate the long-standing interplay between AID and ACE. Thus, additional insights and empirical evidence that can inform the ongoing development of sustainable agricultural practices can be realized.

A compliant helical structure to amplify inertia for nonlinear vibration absorption

The vibration absorption is a passive approach for vibration control by attaching a secondary vibration system to realize the energy transfer and dissipation. To generate a sufficient inertial force, vibration absorbers need to introduce large additional mass, and thus the engineering applications are limited. In this study, a novel compliant structure is proposed with the inertial amplified through a helical movement, and the structure is adopted for nonlinear vibration absorption. The dynamic equations of the absorber are established based on the Lagrange equation, characterizing the nonlinear characteristics arising from the large deformation of the structure and the nonlinear kinetic relationship between the translation and the rotation. Amplitude-frequency responses of the absorber under different excitations are solved using the harmonic balance method and the arc-length continuation method. A rotation-inertial dominant absorber (RIDA) and a translation-inertial dominant absorber (TIDA) are fabricated with the same helical structure while different mass distributions and experiments are performed to validate the nonlinear characteristics and vibration absorption effects. It is observed that both RIDA and TIDA demonstrate effective vibration absorption performances., RIDA introduces smaller additional mass than TIDA. The proposed helical structure absorbers exhibit combined nonlinearities of softening stiffness and displacement-dependent inertia and damping, demonstrating resonance shifting and jump phenomena. With an increasing excitation amplitude, the vibration absorption efficiency decreases and then increases.

Nonlinear scintillation effects in the intrinsic luminescence from Sc1.318Y0.655Si1.013O4.987 crystal excited by electrons and γ-quanta

The spectral and kinetic properties of intrinsic luminescence from (Y2Sc1)0.(3)(Sc)[Si]O5 crystal are studied. The emission is excited by electrons and γ-quanta. The composition (Y2Sc1)0.(3)(Sc)[Si]O5 is the congruent one for Sc2SiO5-Y2SiO5 solid solutions. It is found, that the crystal emits fairly bright intrinsic cathodololuminescence (CL) and radioluminescence (RL) at room temperature. In particular, the light yield of scintillation excited by γ-quanta with the energies of 661.7 keV is of 12000 photons/MeV. An increase in the beam flux by ∼20 times leads to the shift in the maximal CL energy spectral density from 315 to 340 nm and to the decrease in the CL decay time at 415 nm from 1377 ± 3 ns to 1165 ± 1 ns. Simultaneously, the decay time of RL excited by a photoelectron with the energy of 644.7 keV is of 1310 ± 10 ns while a Compton electron with the energy of 477 keV excites RL with the decay time of 1050 ± 10 ns. Also, we observed differences in the CL yield dependencies on the volume-averaged density of electronic excitations (EEs) at different wavelengths. An explanation of the results is given considering the nonlinear scintillation phenomena induced by an interaction between EEs. It is based on a conception that an increase in EE volume density leads to an increase in EEs nonradiative quenching due to these interactions.

Digital Economy and Urban Innovation Ability: From the Spatial Nonlinear Perspective

Using the panel data of China’s 286 prefecture-level cities from 2011 to 2019, this paper explores the causal relationship between digital economy and urban innovation ability by panel vector auto-regression (PVAR), examines the spatial and dynamic effects of digital economy on urban innovation ability by spatial dynamic panel Durbin (SDPD) model, and studies the nonlinear effects of digital economy on urban innovation ability under different external environments using threshold spatial dynamic panel (TSDP) model. The results show that: (a) The urban innovation ability has significant spatial dependence and presents a U-shaped evolution trend. (b) In the short term, the digital economy has a positive impact on urban innovation ability, both directly and indirectly; in the long term, only the indirect effect of the digital economy remains significantly positive. (c) In different external environments, the impact of digital economy on urban innovation ability is nonlinear and has significant external environmental threshold characteristics. Specifically, the digital economy is more conducive to the improvement of urban innovation ability with a moderate degree of marketization; the effect of digital economy empowering urban innovation ability is better in a good legal environment or technological environment.

A fast search method of buckling load for telescopic boom structure

The telescopic boom structures are extensively utilized in engineering applications involving large mobile cranes, aerial work platforms of significant height, and similar mechanical devices. These are predominantly fabricated using solid-webbed box types, latticed truss designs, or a combination thereof. Under load, they exhibit pronounced geometric nonlinear effects, with the relationship between load and displacement demonstrating marked nonlinear characteristics. This paper focuses on the geometric nonlinear modeling of slender multi flexible beam structures. The overall structural system is divided into several substructures, and the concept of multi flexible system modeling is borrowed to establish a follow-up connected body foundation on each substructure. By decomposing the node displacement and rotation in the substructure, the large displacement and large rotation of the node are decomposed into rigid body motion of the connected base and small displacement and small rotation relative to the connected base, effectively representing the large displacement and large rotation of the substructure as rigid body motion of the connected base. A modeling method for the geometric nonlinear analysis of slender and flexible multibody beam structures is proposed. By decomposing the nodal displacement and rotation within the substructures, the large displacement and rotation of the nodes are broken down into the rigid body motion of the body-fixed coordinate and small displacement and rotation relative to the body-fixed coordinate. This approach establishes the application conditions for calculating the structure’s virtual power of deformation using traditional beam elements with linear strain. A method for solving the instability load of slender and flexible multibody structures is proposed. This method integrates the characteristics of the system’s nonlinear equilibrium equations with respect to load, by deriving the system equations with respect to a load increment control parameter. This paper converts nonlinear equilibrium equations into first-order ordinary differential equation (ODE). The method proposed in this paper provides a more efficient solution for the buckling load of the telescopic boom. It can be used to systematically and quickly calculate the structure of the telescopic boom.

Can green buildings reduce carbon dioxide emissions?

Green buildings are a pivotal strategy for realizing the low-carbon evolution within the construction industry. However, the emission reduction effect of green buildings remains unexplored. This study utilizes prefecture-level data from green building projects in Jiangsu Province, China, from 2008 to 2019, to systematically analyze the nonlinear effects, heterogeneous impacts, and mechanisms of influence that green buildings have on carbon dioxide (CO2) emissions. The research findings are as follows: first, during the early stages of green building development, when the scale of green buildings is relatively small, green buildings lead to an increase in CO2 emissions. However, as the scale of green buildings expands, they can exhibit a significant effect on decreasing CO2 emissions. Second, green buildings have heterogeneous impacts on CO2 emissions: lower-rated green buildings (one or two-star) have an increasing impact on CO2 emissions, while the emission reduction effect of green buildings mainly comes from higher-rated green buildings (three-star). These high-rated green buildings substantially affect the advancement of low-carbon technologies, playing an essential role in achieving emission reduction. Third, the mechanisms through which green buildings influence CO2 emissions are identified: on the one hand, green buildings provide a technical effect that decreases CO2 emissions; on the other hand, by promoting the growth of the construction industry, green buildings would cause an increase in CO2 emissions. Lastly, this study proposes relevant policy implications centered around leveraging the emission reduction potential of green buildings.

Nonlinear free vibrations of a structurally tailored anisotropic pre-twisted thin-walled beam subjected to large deformations

It is essential to understand the nonlinear free vibration behaviour of a thin-walled composite structure as they find their applications in harsher environments prone to large deformations. Further, these structures made of fibrous materials, have directional properties for different fibre orientations resulting in a diversified and a complex nonlinear behaviour. In this regard, present work provides a comprehensive mathematical formulation on nonlinear vibration of pre-twisted thin-walled anisotropic box beam. The mathematical model is derived as coupled (flap-lag-extension-torsion) model considering shear deformation and green's strain tensor for large displacements in order to study the influence of nonlinear couplings on the dynamic behaviour. The derived energy equations are presented depending on degree of nonlinearity. These nonlinear equations those derived are nondimensionalized and solved with in the frame work of energy method using classical Ritz approximation. An iterative method is used to solve the nonlinear equations pertaining displacement terms. This nonlinear behaviour is evaluated for two important types of structural tailoring techniques available for thin-walled composite beams namely Circumferentially Asymmetric Stiffness (CAS) and Circumferentially Uniform Stiffness (CUS). It is found that CAS layup experiences significantly severe nonlinear effects compared to CUS due to the presence of 3rd degree nonlinear coupling terms. The variation of nonlinear frequency ratios over different ply angles showing the influence of nonlinearity on fibres orientation is presented for the first time for the two ply lay ups. The influence of degree of nonlinearity on the accuracy of the nonlinear frequencies is evaluated and presented. Moreover, the impact of nonlinearity on the pre-twisted beam is presented for different pre-twist angles.

Extended King integral for modeling of parametric array loudspeakers with axisymmetric profiles.

Parametric array loudspeakers have been widely used in audio applications for generating directional audio beams. However, accurately calculating audio sound with a low computational load remains challenging, even for basic axisymmetric source profiles. This work addresses this challenge by extending the King integral in linear acoustics to incorporate both cumulative and local nonlinear effects, under the framework of the quasilinear solution without the paraxial approximation. The proposed method exploits the azimuthal symmetry in cylindrical coordinates to simplify modeling. To further improve computational efficacy, fast Hankel and Fourier transforms are employed for the radial and beam radiation directions, respectively. Numerical results with both uniform and focusing profiles demonstrate the advantages of the proposed approach over the traditional spherical wave expansion and direct integration methods, especially for larger aperture sizes. Specifically, for typical configurations with source aperture size of 0.2 m, we observe at least a 24-fold improvement in computational speed and a 227-fold reduction in memory requirements. These advancements allow us, for the first time, to present the sound field radiated by parametric array loudspeakers with a large aperture size of up to 0.5 m, without paraxial approximations. The implementation codes are available on https://github.com/ShaoZhe-LI/PAL_King.

Trade Liberalization and the Performance of the Manufacturing Subsector in Nigeria

Trade liberalization is a widely accepted policy for fostering economic growth, particularly in developing countries. Advocates argue that open economies, through increased competition, specialization, and access to global markets, outperform closed economies. However, the short-term effects on developing economies like Nigeria remain debated, especially within the manufacturing sector. Nigeria's trade policy has fluctuated between protectionism and openness, significantly influencing its manufacturing performance. Critics, drawing from dependency theory, argue that liberalization exposes weaker economies to exploitation by stronger nations, leading to trade imbalances and inhibiting industrial growth. This study investigates the nonlinear effects of trade liberalization on Nigeria’s manufacturing sector, addressing a gap in the literature by employing a quadratic approach to determine threshold effects. By incorporating a quadratic form of the trade variable, the study tests the hypothesis that trade liberalization initially boosts the manufacturing sector but results in diminishing returns as openness intensifies. The research is framed within the Laffer Curve of Trade, suggesting that beyond a certain threshold, excessive openness may harm the manufacturing sector. The AutoRegressive Distributed Lag (ARDL) model is used to assess both short-run and long-run effects, with findings indicating a convex relationship between trade liberalization and manufacturing output, highlighting the critical importance of identifying optimal policy thresholds to maximize industrial growth.

Ion optical design of the magnetic proton recoil neutron spectrometer for the SPARC tokamak.

A magnetic proton recoil (MPR) neutron spectrometer is being designed for SPARC, a high magnetic field (BT = 12T), compact (R0 = 1.85m, a = 0.57m) tokamak currently under construction in Devens, MA, USA. MPR neutron spectrometers are versatile tools for making high fidelity abinitio calibrated measurements of fusion neutron flux spectra and have been used to infer fusion power, ion temperature, fuel ion ratio, and suprathermal fuel populations at several high performance fusion experiments. The performance of an MPR neutron spectrometer is in large part determined by the design of the magnetic field, which disperses and focuses recoil protons. This article details the ion optical design of a high-resolution MPR neutron spectrometer, including the amelioration of image aberrations due to nonlinear effects. An optimized design is presented that achieves ion optical energy resolution δE/E < 1% and focal plane properties that enable straightforward integration with the hodoscope detector array.

Deep‐Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic‐Climate Data From Moxa Geodynamic Observatory

AbstractHighly sensitive laser strainmeters at Moxa Geodynamic Observatory (MGO) measure motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters installed in the gallery of the observatory is relatively low, the recorded time series are strongly influenced by local meteorological phenomena. To estimate the nonlinear effect of the meteorological variables on strain measurements in a non‐stationary environment, advanced methods capable of learning the nonlinearity and discovering causal relationships in the non‐stationary multivariate tectonic‐climate time series are needed. Methods for causal inference generally perform well in identifying linear causal relationships but often struggle to retrieve complex nonlinear causal structures prevalent in real‐world systems. This work presents a novel model invariance‐based causal discovery (CDMI) method that utilizes deep networks to model nonlinearity in a multivariate time series system. We propose to use the theoretically well‐established Knockoffs framework to generate in‐distribution, uncorrelated copies of the original data as interventional variables and test the model invariance for causal discovery. To deal with the non‐stationary behavior of the tectonic‐climate time series recorded at the MGO, we propose a regime identification approach that we apply before causal analysis to generate segments of time series that possess locally consistent statistical properties. First, we evaluate our method on synthetically generated time series by comparing it to other causal analysis methods. We then investigate the hypothesized effect of meteorological variables on strain measurements. Our approach outperforms other causality methods and provides meaningful insights into tectonic‐climate causal interactions.

Investigation into forces on offshore piles with constant and linearly varying diameters using CFD and extended Morison equation under separate wave and current loadings

This study presents a comparative analysis of hydrodynamic forces on cylindrical offshore piles with both constant and linearly varying diameters utilizing computational fluid dynamics (CFD) simulations. The classical Morison equation is evaluated alongside an extended version to address limitations in predicting forces on geometrically complex structures. Mesh convergence studies are performed to select the optimum grid size for separate wave and current simulations. The focus is on test cases characterized by small Keulegan-Carpenter (KC) numbers and relatively high Reynolds (Re) numbers within both inertia-dominated and diffraction zones. Numerical simulation results are utilized to compare the force predictions of the classical Morison equation and the extended Morison equation. It is observed that the classical Morison equation performs adequately for constant diameter piles, but it fails to predict forces on variable diameter piles accurately. In contrast, the extended Morison equation, incorporating nonlinear effects and variable cross-sections, provides significantly more accurate force predictions, particularly in the diffraction zone compared to the numerical simulations. This study emphasizes the critical importance of accounting for geometric variations, such as linearly varying pile diameters, under separate waves and currents loadings in hydrodynamic force calculations. These considerations support the development of enhanced design methods and optimization strategies, leading to safer and more efficient offshore structures.

Green finance and land ecological security: A potential mechanism for sustainable development

With growing global concern for environmental issues, green finance (GF) has emerged as a key tool for promoting sustainable development. However, research on its impact on land ecological security (LES) is limited. This study explores the spatial and non-linear effects of GF on LES, focusing on the roles of agricultural e-commerce (AEC) and agricultural industry agglomeration (AIA). Our findings reveal significant first, spatial auto-correlation in LES and an inverted U-shaped pattern in the spatial impact of GF. Second, AEC enhances this inverted U-shaped relationship, shifting the knee point leftward and resulting in a higher marginal effect of GF on LES. Conversely, AIA weakens the relationship, shifting the knee point rightward and potentially flipping the pattern. Additionally, heterogeneity researches results indicate that this spatial effect exists only in primary grain distribution areas, and not in primary grain producing areas or grain production and distribution balanced areas. Robustness tests, including instrumental variables and alternative core explanatory variables, confirm the credibility of these results. This research offers targeted policy recommendations for the GF-LES relationship.