Balance Method Research Articles

Nonlinear harmonic resonant behaviors and bifurcation in a Two Degree-of-Freedom Duffing oscillator coupled system of Tension Leg Platform type Floating Offshore Wind Turbine

The surge-heave coupled motion model of a Tension Leg Platform type Floating Offshore Wind Turbine (TLP FOWT) is first established. By taking the tendons stretching and platform set-down motion into consideration, the nonlinear model is a Duffing oscillator coupled system. We analyze the nonlinear feature in the surge-heave coupled motions by the semi-analytical algorithms in nonlinear dynamics. The harmonic balance method is applied to obtain the analytical solutions of the nonlinear system under wind and wave excitations. The analytical solution verifies the excellent accuracy. To further achieve the heave motion response, we organize the bifurcation analysis and discuss the effects of the dynamic parameters on the heave responses. The results reveal the multi components of heave motion, which consist of constant, primary harmonic resonate and higher order harmonic resonate. In addition, the change of dynamic parameters has various effects on the response. The increment of wave load leads to the expansion of heave response, and an instantaneous expansion appear. Both linear surge and heave damping only affect the amplitudes of heave motion. The nonlinear surge stiffness and heave stiffness can barely affect the primary harmonic resonance amplitudes, but they present different effects on the higher order harmonic resonance component.

Implementation of High Availability Based on Load Balancing and Failover Method in E-commerce Using MySQL Database

The rapid growth of e-commerce has brought about challenges in managing traffic loads and ensuring the availability of database servers. One critical issue is what happens when the main database server fails, potentially leading to downtime or data loss. This research aims to address these problems by optimizing server resource distribution and implementing data replication across multiple database servers. The goal is to enhance system efficiency, prevent server overloads, ensure data availability, and minimize downtime or data loss when server failures occur.This research utilizes a multi-stage methodology. First, data collection was conducted to gather relevant information. In the second stage, a needs analysis was performed to identify system requirements. The third stage involved designing the system architecture, including the creation of entity-relationship diagrams (ERD), flowcharts, and network topologies. In the final stage, the system was implemented through database replication and the application of failover methods.The results demonstrate that the failover mechanism operates effectively, ensuring that data is successfully replicated across all database servers. This confirms that the system achieves high availability and minimizes the risk of data loss or service downtime. The implications of this research provide a reliable solution for improving the resilience and performance of e-commerce systems, particularly in managing database server failures.

Development of Flexible Rotor Balancing Procedure Using Response Matching Technique

Abstract Purpose The two main methods under use for balancing of flexible rotor know as Influence Coefficient Method (ICM) and Modal Balancing Method (MBM). It needs few trials to arrive at predicting the unbalance mass. In presence of initial bow along with unbalance these methods will fail to give accurate predictions. It becomes further complex when rotors are mounted on flexible supports. To overcome the limitations of these two methods, a new method called response matching method is disused here for flexible rotor balancing. Method The objective of present work is to develop a balancing procedure for flexible rotor balancing, wherein unbalance response of Finite element model (FEM) is matched with experimental response using iterative technique. Unbalance masses, moments and shaft stiffness of FEM model was iterated to match experimental unbalance responses at three distinct speeds below its first flexural critical speed. Further, unbalances mass was estimated iteratively to cross the bending critical speed with lower residual amplitudes at critical speeds. Results Experimental test setup was developed to validate the proposed method. Results show that present method predicts the unbalance masses and moments to compensate the bow more accurately. Conclusion Results shows that with single run, rotor unbalance masses and movements are predicted accurately. Corrected masses are used in experimental test setup to check the rotor amplitudes during its bending critical speeds. It shows rotor passes first bending critical speed without excessive amplitudes.

A study on generalized balanced split drift stochastic Runge- Kutta methods for stochastic differential equations

To reduce computational complexity, the balanced numerical approximations of the general split drift stochastic Runge-Kutta methods are analyzed. The primary reasons for considering the numerical approximations of these balanced split stochastic Runge-Kutta methods are their improved stability characteristics and lower mean square error compared to other methods. By balancing the drift and diffusion components, the splitting techniques outperform the mean square error over longer time increments. For Ito multi-dimensional stochastic differential equations, we propose a novel family of balanced universal split stochastic Runge-Kutta procedures. The Kronecker product concept is utilized to derive the mean-square stability conditions. We conduct numerical tests to evaluate these methods against an existing weak order 2 split drift method. Ultimately, a specific numerical example validates the theoretical outcomes of the balanced general split stochastic Runge-Kutta procedures.

Study on vibration control performance of pendulum TMD with additional stoppers and its application on high-rise buildings

Although pendulum tuned mass damper (PTMD) is one of the most classic and commonly used vibration control devices, it has clear limitation due to the natural feature of linear TMD. Additional stoppers for the pendulum string (PTMD-AS) were proposed and introduced to improve the PTMD's performance by triggering its nonlinearity. A 2-DOF model was established to analyze the dynamic response of the system subjected to harmonic excitation, and the governing equations were formulated using the Lagrange equation. The extended incremental harmonic balance (EIHB) method and the Runge-Kutta (R-K) method were utilized to calculate the frequency response and time history of the system. Nonlinear dynamic characteristics of the pendulum with stiffness hardening were explored in detail. Sensitivity analyses were performed to investigate the effect of stopper position. It was found that aperiodic responses or multiple solutions could be induced when the pendulum underwent significant stiffness hardening upon passing the additional stoppers. Finally, the effectiveness and robustness of PTMD-AS are demonstrated in a numerical simulation of a high-rise building subjected to random wind excitation based on wind tunnel experiments.

The High-Precision Balance Method for Hemispherical Resonator Based on Synchronous Trimming System

The High-Precision Balance Method for Hemispherical Resonator Based on Synchronous Trimming System

Evaporative characteristics of winter wheat in the guanzhong loess plateau region of shaanxi, china

This study explain the evaporative characteristics of winter wheat in the Guanzhong Loess Plateau region of Shaanxi through stem flow meters and weighing lysimeters. It examines the diurnal variations in evapotranspiration rates, leaf area index, and soil moisture's impact on winter wheat evaporation. Additionally, it explores the ratio of transpiration to evaporation and compares the evaporation measured by the water balance method with that of the lysimeters. The findings reveal distinct diurnal variations in transpiration rates under different weather conditions, with sunny days exhibiting an unimodal curve while cloudy and rainy days showcase irregular multi-peaked curves. The evaporation curve generally follows an unimodal pattern, with both leaf area index and soil moisture significantly influencing the evaporation process. From heading to early grain filling, the ratio of transpiration to evaporation ranges from 80.3 to 83.4%. Evaporation obtained through the water balance method (0-220 cm) is 6% less than that measured by the lysimeters. Bangladesh J. Bot. 53(3): 689-695, 2024 (September) Special

Complexity and response of bio-inspired energy harvesters based on wing-beat pattern

This paper aims to investigate the dynamical mechanism of bio-inspired energy harvesters based on wing-beat pattern under harmonic excitation. Due to the existence of the gravity force in the established model, the harmonic balance method is utilized to calculate the theoretical results, which has the advantage to keep the influence of gravity force. Multiple solutions are found in the high frequency region, and they are very close in the amplitude of displacement and voltage due to the special structure of the bio-inspired energy harvester. Direct time-domain analysis verifies the effectiveness of theoretical results. The influence mechanism of the equivalent stiffness is also explored, which leads to the appearance of different states. Then, the root mean square (RMS) voltage and average power are analyzed. It is observed that a smaller damping coefficient and equivalent capacitance enhance the average electrical output and achieve greater output power. Subsequently, the bifurcation and complexity properties of the harvester are discussed. Complex phenomena are observed under different external excitations and equivalent damping, including double periodic bifurcation, multiple periodic bifurcation, and chaos phenomena. The complexity analyses confirm the effectiveness of the bifurcation results. The distribution of complexity also exhibits significant fluctuations, closely correlated with the trend of the bifurcation diagram.

Supply chain finance and outward foreign direct investment

This study empirically examines the impact of Chinese A-share-listed companies' supply chain finance (SCF) application on outward foreign direct investment (OFDI) by textually analyzing SCF keywords from listed companies' announcements from 2010 to 2021. The results show that applying SCF can significantly increase OFDI. Having taken the Staggered Differences-in-Differences (DID) test, Propensity Score Matching (PSM) test, entropy balancing (EB) method, and IV test to solve potential endogeneity problems, the results remain robust. Further, alleviating financial constraints and strengthening total factor productivity are critical mechanisms of SCF on OFDI. Moreover, the location of firms in regions with higher levels of the rule of law or advanced financial technology could further amplify the positive impact of SCF on OFDI. Finally, compared with exports, firms are more likely to choose OFDI. Besides the depth and breadth of OFDI, the investment amount of OFDI is also increasing because of SCF.

АНАЛІЗ ВПЛИВУ ІНДИВІДУАЛЬНИХ ХАРАКТЕРИСТИК КОМІРОК LiFePO4 НА ПАРАМЕТРИ РОБОТИ АКУМУЛЯТОРНИХ ЗБІРОК

The article analyzes the influence of the individual characteristics of lithium-iron-phosphate (LiFePO4) cells on the overall efficiency, stability and duration of operation of battery assemblies. The influence of such parameters as internal resistance, polarization resistance and capacity on the operation of battery assemblies under different load regimes and changes in temperature conditions was studied. It was found that these parameters can vary significantly between cells within the same assembly, which leads to an imbalance during the operation of the battery system. Such an imbalance causes an uneven distribution of charge between the cells, which reduces the overall performance of the system, accelerates the degradation of the cells and shortens their service life. To overcome these problems, the use of active balancing methods based on Unscented Kalman Filter (UKF) algorithms was proposed. The application of UKF allows for dynamic evaluation of the state of charge (SOC) of each cell and adjustment of system parameters in real time, which provides more accurate management of battery assemblies in conditions of variable external factors such as temperature and current loads. Special attention is paid to online identification of battery parameters, such as polarization resistance and capacity, which change over time due to cell aging. The conducted studies confirmed that constant monitoring of temperature regimes is critically important for maintaining stable operation of battery cells, preventing overheating and ensuring uniform load distribution. The performed simulation confirmed the effectiveness of the application of adaptive methods of balancing and temperature control, which allows to increase the reliability and overall performance of battery assemblies.

Ratios of organic mass to organic carbon in fine particulate matter at urban sites in China and Korea during winter and summer.

This study evaluates the composition and seasonal characteristics of fine particulate matter (PM2.5) during winter and summer through simultaneous measurements conducted at the Gwangju Institute of Science and Technology in South Korea and the Changping campus of Peking University in China. PM2.5 samples were concurrently collected at both sites, and chemical analyses were conducted to quantify various components, including carbonaceous materials, ionic species, and metals. Although the average PM2.5 concentrations were comparable between the two sites, there were distinct differences in the concentrations of major components. Organic indicator compounds were analyzed to discern the contributions of primary and secondary pollution sources. Changping displayed a mix of primary and secondary pollution, characterized by higher concentrations of primary organic carbon (POC) such as polycyclic aromatic hydrocarbons and hopanes, compared to Gwangju. In contrast, Gwangju demonstrated a higher prevalence of secondary organic carbon (SOC), particularly water-soluble organic carbon not related to biomass burning (WSOCnbb) and various polar organic compounds. The organic mass to organic carbon (OM/OC) ratios estimated using the mass balance method revealed significant differences, with Gwangju showing a higher ratio of 2.3 compared to 1.9 at Changping, indicating a greater influence of secondary pollutants at Gwangju. Additionally, both Changping and Gwangju exhibited higher OM/OC ratios in summer (Changping: 2.0, Gwangju: 2.5) compared to winter (Changping: 1.8, Gwangju: 2.2), indicating seasonal differences in organic mass contributions to PM2.5. These findings underscore the importance of accounting for spatial and seasonal variations in air pollution studies and suggest that updating commonly used OM/OC ratios could enhance the reliability of research outcomes.

Generation and evaluation of energy and water fluxes from the HOLAPS framework: Comparison with satellite-based products during extreme hot weather

Improving our understanding of the energy and water exchanges between the land surface and the lower atmosphere (i.e. land–atmosphere interactions), and how climate change may affect them, is crucial to predict changes in temperature and precipitation extremes. Observations of energy and water fluxes at the land surface are typically retrieved from the eddy covariance method, which presents limitations related to spatial and temporal gaps, and the non-closure of the energy and water balances. Meanwhile, soil moisture (SM) products derived from satellite data have been widely used at regional and global scales, but they are limited to capture only surface soil water content and variations. The combination of remote sensing (RS) data and modelling frameworks is called to be the solution to improve the spatial coverage and vertical resolution of land–atmosphere interactions data, ensuring the energy and water balance closure. Here, we explore the combination of remote sensing and meteorological data with a physical-based modelling framework, the High resOlution Land Atmosphere Parameters from Space (HOLAPS). We used HOLAPS to produce hourly consistent estimates of energy and water fluxes over Europe at 5 km resolution. HOLAPS and other satellite-based evapotranspiration and sensible heat flux products from the literature are evaluated against the water balance method and eddy covariance measurements. HOLAPS SM estimates together with other RS-modelling products are also evaluated against ground-based measurements at the surface and in the root zone. The evaluation of HOLAPS ET estimates show similar performance to the other products with Kling–Gupta efficiency (KGE) ¿ -0.41 in comparison with eddy covariance measurements from FLUXNET in all seasons but in boreal winter. The simulation of H is more uncertain than for ET with KGE values ranging from -2.5 to 0.8 along the products and stations at monthly scales. HOLAPS reaches slightly better results than the rest of ET and H products at daily scales in summer (KGE ¿ 0.3 for ET and KGE ¿ 0.0 for H) and during hot conditions (KGE ¿ 0.2 for ET and KGE ¿-0.2 for H), while the state-of-the-art products show KGE ¿ 0.1 for ET and KGE ¿ -0.41 for H in summer and KGE ¿ -0.1 for ET and KGE ¿ -0.6 for H during hot conditions. All products evaluated here yield a reasonable performance (KGE ¿-0.41 at most sites) in simulating SM at the surface and in the root zone. Our results expose the need for further investigating and improving product performances during extreme conditions. The good performance of HOLAPS together with its inherent advantages (RS data driven, high temporal and spatial resolution, spatial and temporal continuity, soil moisture at different depths and long-term consistent evapotranspiration and sensible heat flux estimates) support its use for agricultural and forest management activities as well as to study land–atmosphere interactions based on Earth Observations.

Multi-frequency harmonic balance method for nonlinear vibration of pipe conveying fluid under arbitrary dual-frequency excitation

Multi-frequency harmonic balance method for nonlinear vibration of pipe conveying fluid under arbitrary dual-frequency excitation

Deep Learning-Based Segmentation and Prediction of Liver Cancer Using CT Images

Background: Liver cancer presents a significant global health challenge, particularly in Asia, due to high incidence rates and the difficulty of early detection. Despite advances in medical imaging, the accurate segmentation and prediction of liver tumors remain critical for effective treatment planning. Deep-learning is a revolutionary tool in medical imaging, offering promising solutions for automated analysis of liver cancer using CT images. Methods: This study develops a framework based on deep-learning- for the segmentation, and prediction cancer of the liver from Computed Tomography images. The framework leverages advanced convolutional neural network (CNN) architectures, including U-Net and its variants, optimized with class balancing methods. The model is trained and authenticated using a high-quality annotated images, dataset of liver CT images. Key techniques such as transfer learning, data augmentation, and hyper parameter tuning are employed to enhance model performance. Evaluation metrics include accuracy, sensitivity, specificity, Dice-coefficient, and (IoU).Intersection over Union Results: The design of proposed program achieved significant improvements in segmentation, accuracy, with an average Dice, Similarity-Coefficient (DSC) of 0.96 for liver segmentation and 0.84 for the tumor segmentation. The results demonstrate the superior performance of the model's compared to the other traditional methods and other existing deep learning models. Cascaded fully convolutional networks (FCNs) combined with 3D Conditional Random Fields (CRFs) showed robust performance, achieving true value accuracy rates of approximately 99.55% for liver segmentation. Conclusion: This study presents a novel and effective deep learning framework for liver cancer segmentation and prediction, highlighting the clinical applicability and relevance of the developed models in real-world medical settings. The findings highlight the potential in deep-learning for enhancing liver cancer diagnosis, facilitating early detection, timely interventions, and improved patient outcomes. This research contributes in increasing the body of knowledge in medical image analysis, enlighten the way for future advancements in the field. Keywords: Computed Tomography, Deep Learning, Machine Learning, U-Net, 3D, Segmentation, Fully Convolutional Networks, Conditional Random Fields, Dice Similarity Coefficient, Intersection over Union, Conventional Neural Network

Closing the geologic carbon cycle

Estimates of sedimentary organic carbon burial fluxes based on inventory and isotope mass balance methods have been divergent. A new calculation of the isotope mass balance using a revised assessment of the inputs to the ocean-atmosphere system resolves the apparent discrepancy. Inputs include weathering of carbonate and old kerogen, geogenic methane oxidation, and volcanic and metamorphic degassing. Volcanic and metamorphic degassing comprise ≈23% of the total C input. Inputs from isotopically light OCpetro and CH4-geo drive the mean δ13C of the input to =-8.0 ± 1.9‰, notably lower than the commonly assumed volcanic degassing value. The isotope mass balance model yields a modern burial flux =15.9 ± 6.6 Tmol y-1. The impact of the mid-Miocene Climatic Optimum isotope anomaly is an integrated excess deposition ≈ 4.3 × 106 Tmol between 18 and 11 Ma, which is both longer and larger than estimates for the total degassing by the Columbia River Basalt eruptions, implying a complex carbon system response to large eruptive events. Monte Carlo evaluation finds that late Cenozoic net growth of the carbonate reservoir is very likely while net growth of the Corg reservoir is less certain but more likely than not. At present, subduction does not appear to keep up with net sedimentation and the overall masses of sedimentary carbonate and organic carbon are likely increasing. Growth in the sedimentary Corg reservoir implies oxidation of the surface environment and likely increases in atmospheric pO2.

Enhancing accuracy and robustness in FBS decoupling through Tikhonov regularization and unit balancing

Frequency-based Substructuring (FBS) enables the prediction of transfer functions for an assembled system based on those of a single-unit system. Conversely, FBS decoupling derives the frequency response function (FRF) of a single-unit system from the assembled system. This approach is valuable when obtaining the transfer functions of a system is challenging due to boundary conditions and deformation conditions. FBS decoupling can enhance accuracy by using additional indicator sensors. However, this often results in significant noise due to the ill-posed FRF matrix inversion. In this paper, Tikhonov regularization is employed to reduce noise-induced errors. Furthermore, this paper addresses the issue of inadequate Tikhonov regularization caused by the inherent scaling differences between the rotational and translational components within the FRF matrix. To rectify this challenge, a unit balancing method is proposed to mitigate the influence of scaling differences. This method enhances the accuracy and reliability of FRF matrix inversion processes, contributing to enhanced noise reduction and robustness in practical applications.

Utilizing porous dielectric material to enhance the performance of capacitive MEMS accelerometers for shaft monitoring

This research investigates the optimization of the performance of a capacitive-based microelectromechanical systems (MEMS) shaft monitoring accelerometer using a porous soft dielectric material with high polarization capability and low Young’s modulus. The nonlinear governing equations of a microbeam with a proof mass coupled with the squeeze motion equation of the polymeric dielectric material excited by shaft vibrations are extracted and solved in both the spatial and temporal domains. The studied model considers the stiffness, dissipative, and inertial effects of the polymeric material and incorporates porosity as a displacement-dependent variable, which introduces an additional nonlinearity. After discretizing the coupled nonlinear differential equations using the Galerkin method, the response in the frequency domain is obtained by applying an energy balance method, where the coefficients of the Fourier expansion of the response are found by arc-length continuation through a physical gradient descent learning-based approach method. The occurrence of secondary and primary resonances in different harmonic responses is studied for different harmonic acceleration inputs. The equivalent rigidity of the design is investigated for different shaft frequency magnitudes and different proof mass geometries. The effect of the initial porosity volume fraction of the elastomeric dielectric material on the dynamic response of the accelerometer is also examined. The sensor’s sensitivity is dependent on its geometry and properties and can vary based on the structure’s material parameters. Consequently, the selection of different geometries and materials may result in either an improvement or a deterioration of the sensor’s performance.

Computing the dynamic response of a periodic structure coupled with a nonlinear junction using the harmonic balance method and Floquet-Bloch modelling

Structures constituted of assembled sub-components are often subject to nonlinear effects due to the presence of joints or contacts, which can induce higher-order harmonics of the source excitation. In the context of periodic structures, these nonlinearities cannot be tackled using the Floquet-Bloch theory in its usual harmonic formulation. This study hence presents an adaptation of the classical Floquet-Bloch theory to address multi-harmonic systems arising from a finite number of localized nonlinearities in periodic waveguides. We adopt the Harmonic Balance Method to recast the governing equations into a nonlinear algebraic system, which can then be solved using numerical continuation algorithms. To demonstrate the validity and benefit of this approach, the predictions derived from the proposed methodology are compared to results obtained through conventional Finite Element analysis. Excellent agreement and a notable reduction in computational cost are observed. This efficient procedure for analysing the nonlinear dynamic response of periodic waveguides opens up new possibilities in the study of damaged composite structures.

Inertial amplification as a performance enhancement method for snap-through vibration energy harvester

In recent years, there has been a lot of interest in exploiting the bistable behavior of snap-through systems to harvest energy from vibration sources. The efficient operation of any bistable VEH depends on its ability to exhibit large-amplitude interwell motion. Under weak ambient excitation, bistable VEH performs marginally because of the confinement of motion to a single well. Frequency up-conversion, multi-stability, and adaptive techniques are some of the performance enhancement strategies suggested for bistable-VEH. Considering the VEH's space constraints, the above designs are hard to implement in practical cases. This study introduces an inertial amplification mechanism (IAM) as a simple passive strategy to enhance the performance of a snap-through VEH, a concept not explored in previous studies. The addition of IAM increases the effective mass without increasing the physical mass and thereby enhances energy harvesting, especially from weak ambient excitation sources. The dynamics and performance of the enhanced snap-through VEH are investigated analytically and numerically under harmonic and random excitations. The harmonic balance method (HBM) derives the frequency-amplitude relationship, which shows a hardening behavior and an increase in bandwidth. The effective potential method provides a closed-form expression for the joint probability density function (Joint PDF), which is governed by the Fokker-Planck equation. The joint PDF shows a transition from bimodal to unimodal with an increase in the value of the geometrical parameter. The stochastic averaging method is employed to obtain the stationary probability density function, which defines the long-term dynamics of the VEH. The effects of noise intensity, mass ratio, and inertial amplifier angle on the dynamics are investigated. Finally, the performance of the proposed VEH is compared with a conventional snap-through VEH, an equivalent linear VEH, and a multistable VEH under harmonic and random excitation conditions. The findings suggest that the snap-through VEH with the IAM has advantages over the linear and multistable nonlinear VEH in terms of extracting energy from low-intensity harmonic and random excitation sources. This simple augmentation strategy preserves the original system's bistability, eliminating the need for the complex design of a multistable VEH.

HLSM-MIPV Algorithm of unbalance vibration suppression of dual-rotor in contra-rotating propfan

The inner and outer rotors of the contra-rotating propfan dual-rotor system, utilizing dual intershaft bearings, exhibit anisotropic support characteristics, whereas the vibration of the dual-rotor system is cross-coupled. This combination makes the identification of unbalanced responses and the efficiency of dynamic balancing challenging. To address this issue, this paper proposes a method for the dynamic balancing of the contra-rotating dual-rotor based on Harmonic Least Squares Method and Modified Initial Phase Vector (HLSM-MIPV). Firstly, a test bench for the contra-rotating dual-rotor system is constructed using two Micro-Electro-Mechanical Systems (MEMS) sensors. Secondly, unbalanced vibration vectors of the dual-rotor are identified using Harmonic Least Squares Method (HLSM). Thirdly, the Harmonic Component Method with the Modified Initial Phase Vector (MIPV-HCM) is introduced to balance the force and couple unbalance under anisotropic stiffness conditions. Finally, dynamic balancing tests on the test bench demonstrate that the MIPV-HCM method achieves an additional vibration reduction of 4 %–17 % compared to the traditional HCM.