Nonlinear Decrement Research Articles

Solving UAV 3D Path Planning Based on the Improved Lemur Optimizer Algorithm

This paper proposes an Improved Lemur Optimization algorithm (ILO), which combines the advantages of the Spider Monkey Optimization algorithm, Simulated Annealing algorithm, and Lemur Optimization algorithm. Through the use of an adaptive nonlinear decrement model, adaptive learning factors, and updated jump rates, the algorithm enhances its global exploration and local exploitation capabilities. A Gaussian function model is used to simulate the mountain environment, and a mathematical model for UAV flight is established based on constraints and objective functions. The fitness function is employed to determine the minimum cost for avoiding obstacles in a designated airspace, and cubic spline interpolation is used to smooth the flight path. The Improved Lemur Optimization algorithm was tested using the CEC2017 benchmark set, assessing its search capability, convergence speed, and accuracy. The simulation results show that ILO generates high-quality, smooth paths with fewer iterations, overcoming the issues of premature convergence and insufficient local search ability in traditional genetic algorithms. It adapts to complex terrain, providing an efficient and reliable solution.

Nonlinear dielectric decrement of electrolyte solutions: An effective medium approach

HypothesisThe dielectric constant of an electrolyte solution, which determines electrostatic interactions between colloids and interfaces, depends nonlinearly on the salinity and also on the type of salt. The linear decrement at dilute solutions is due to the reduced polarizability in the hydration shell around an ion. However, the full hydration volume cannot explain the experimental solubility, which indicates the hydration volume should decrease at high salinity. Volume reduction of the hydration shell is supposed to weaken dielectric decrement and thus should be relevant to the nonlinear decrement. SimulationsAccording to the effective medium theory for the permittivity of heterogeneous media, we derive an equation which relates the dielectric constant with the dielectric cavities created by the hydrated cations and anions, and the effect of partial dehydration at high salinity is taken into account. FindingsAnalysis of experiments on monovalent electrolytes suggests that weakened dielectric decrement at high salinity originates primarily from the partial dehydration. Furthermore, the onset volume fraction of the partial dehydration is found to be salt-specific, and is correlated with the solvation free energy. Our results suggest that while the reduced polarizability of the hydration shell determines the linear dielectric decrement at low salinity, ion-specific tendency of dehydration is responsible for nonlinear dielectric decrement at high salinity.

Nonlinear Stress dependent Resonant Studies on Press-fit ME Composites

Considering the wide applications of magnetoelectric (ME) composites in sensors, actuators, and microelectronic devices, optimizing them for the maximum ME coupling response has recently sought great attention among researchers. The coupling response of ME composites is maximum when operated in resonance conditions. In this article, a two-dimensional coupled in-plane formulation is proposed based on the in-plane vibrational theory to capture the resonant ME response of Press-fit ME composites. The study is extended to analyze the effect of stress and temperature on the resonant ME response of press-fit ME composites. The proposed theoretical formulation is validated experimentally and found to agree with each other. The numerical analysis is performed using the commercially available finite element software COMSOL® utilizing the Frequency Domain Perturbation study steps. The study reveals a nonlinear decrement in the peak resonant ME response with respect to both externally applied pre-stress and temperature conditions.

Study of thermal and physical properties of sodium modified zinc borate glasses

A glass series for composition 20ZnO.(80-x)B 2 O 3 .xNa 2 O with x = 10, 20, 30, 40, and 50 have been prepared using melt quenching technique, the thermal and physical properties of prepared samples were studied. To analyze the role of modifier the parameters like glass transition temperature ( T g ), density ( ρ ), molar volume ( V m ), crystalline volume ( V c ), oxygen packing density (OPD), interionic distance ( R i ), polaron radius ( R p ), boron molar volume (V M B ), average boron-boron distance <d B-B > and field strength ( F ) were calculated. Glass transition temperature exhibits a nonlinear decrement with increment in modifier content. As sodium oxide content increases molar volume decreases and density showcase increasing pattern with decrease in rate of change of ρ with increasing sodium oxide percentage.

Acoustic Signal NLOS Identification Method Based on Swarm Intelligence Optimization SVM for Indoor Acoustic Localization

The demand for an indoor localization system is increasing, and related research is also becoming more universal. Previous works on indoor localization systems mainly focus on the acoustic signals in Line of Sight (LOS) scenario to obtain accurate localization information, but their effectiveness in Nonline of Sight (NLOS) scenario remains comparatively untouched. These works are usually less efficient as the acoustic signals often bring diffraction, refraction, scattering, energy decays, and so on in NLOS environments. So the system needs adjusting accordingly in a complex NLOS scenario based on NLOS identification results. Therefore, the identification of NLOS acoustic signal turns out to be significant in the indoor localization system. If the system only uses original support vector machine (SVM) to complete NLOS identification, the result turns out to be poor by our test. To address this challenge, we propose a novel indoor localization system, named ZKLocPro, which utilizes an advanced swarm intelligence method to optimize the traditional SVM classification model to deal with NLOS acoustic signal identification. Its results can help the system adjust the localization process if necessary in a complex NLOS scenario. Obviously, it is also significant to build our own NLOS data set, which is suitable for an indoor localization system’s situation. Specifically, four methods are added: (1) new LOS and NLOS acoustic localization signal sample production, rearrangement, and reselecting process; (2) advanced parameter optimization process; (3) elitist strategy; and (4) inertia weight nonlinear decrement. The experimental result shows that our system is efficient and performs better than state-of-the-art congeneric works even in a complex NLOS scenario.

Hybrid optimization strategy for lithium-ion battery's State of Charge/Health using joint of dual Kalman filter and Modified Sine-cosine Algorithm

In order to improve the accuracy of State of Charge / Health (SOC/SOH) estimation, Modified-Sine-cosine Algorithm-based dual Extend Kalman filter (MSCA-DEKF) is proposed. Second-order RC model is applied, the model parameters are obtained by Pulse discharge test and Open circuit voltage test (OCV). DEKF is divided into state filter and parameter filter. Nonlinear decrement of transformation parameter r1 in Sine-cosine Algorithm (SCA) is proposed. Modified SCA (MSCA) is applied to optimizing the covariance noise matrix in the state filter. Parameter filter is applied to estimating the Ohm internal resistance and capacity online, Meanwhile, the time scale of parameters’ online update is adjusted to 60 time steps for reducing computing costs. SOH is also obtained by Ohm internal resistance and capacity. Simulation results show that the proposed method improves the accuracy of SOC estimation, and the initial errors of SOC and Ro can be corrected in the first parameter estimation. Ro-based SOH has a better robustness and precision than capacity-based SOH.

Comment on “The Nonlinear Decrement in Static Permittivity of Electrolytes in High-Polarity Solvents”

Comment on “The Nonlinear Decrement in Static Permittivity of Electrolytes in High-Polarity Solvents”

Research Based on The Improved Grey Wolf Optimization Algorithm

With the continuous progress of machine learning methods, more and more methods are widely used in various fields. Grey Wolf Optimization Algorithm (GWO), as a kind of population algorithm, has become a research hotspot in recent years because of its good optimization ability. Similar to other population algorithms, gray wolf optimization algorithm itself has the problem of imbalance between global search and local search capabilities. In order to solve this problem, the following improvements are proposed to the standard gray wolf optimization algorithm: First, change the decrement method of the convergence factor and adopt a non-linear decrement method to meet the actual search process; At the same time, a weighting strategy is introduced to dynamically assign weights to the guide wolves. It can ensure that the population jumps out of the local optimal solution. In order to verify the effectiveness of the improved algorithm, an international general test function is selected for simulation. The simulation results show that the improved gray wolf optimization algorithm has faster convergence speed, higher solution accuracy and better stability.

The Nonlinear Decrement in Static Permittivity of Electrolytes in High-Polarity Solvents

A theoretical model describing the nonlinear decrement in the static permittivity of electrolytes in high-polarity solvents is developed on the basis of the Langevin statistical theory with a subsequent customization. This customization is in relation to the dilution of the polar dipoles by free ions and the influence of the local electric field radiated by ions on the solvent molecules in the proximity of the ions. It is interesting that the mean ionic size and the interaction between ions and solvent molecules responsible for the decrement in the static permittivity of electrolyte solutions are shown. The model exhibits not only the linear decrement in permittivity for dilute solutions but also the nonlinear one for concentrated solutions of electrolytes in different high-polarity solvents at a definite temperature with a single parameter. It is pointed out that the influence of the local electric field on the polarization of methanol is much stronger than that of water. Moreover, the factors affecting the solvation energies of electrolyte ions in high-polarity solvents are interpreted. Because of the simple form of the static permittivity function, the concentration dependence of the Debye screening length is carefully and obviously considered.

Improvement of Inertia Weight Declining Strategy Based on Particle Swarm Optimization Algorithm

The standard particle swarm optimization algorithm introduces the inertia weighetw, which becomes a calculation method for finding the extremum of the function effectively. It is easy to converge fast. Nowadays, the linear decreasing dynamic, inertia weighting strategy is widely used. Although this improvement is very successful. However, the search process is a nonlinear and complex process. In order to better maintain the balance between global and local search capabilities, this paper proposes a nonlinear decreasing dynamic inertia weighting strategy based on the linear decreasing strategy, using Griewank, Rastrigrin, Sphere, The simulation experiments of four standard test functions of JDSchaffer were carried out, and the inertia weights in the basic particle swarm optimization algorithm were compared with the nonlinear decrement of fixed weight w = 0.95, linear decreasing LDIW and Chen[6] exponential curve respectively. The improved nonlinear weight decrement strategy is superior to other algorithms in terms of convergence speed, convergence precision number of iterations.

An extensive validation of computer simulation frameworks for neural prognostication of tractor tractive efficiency

To optimize power and energy resources in field operations, there is an inevitable demand for attempts to be conducted regarding determination of performance parameters of tractor-implement. Computer simulation is a potential assistive tool for researchers concerned in this realm. This is the first investigation covering comparative ability of computer simulation frameworks, based on artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), for neural prognostication of tractor tractive efficiency during tillage operations. In tillage operations, forward speed (2-6 km/h), plowing depth (10–30 cm), and tractor mode (two-wheel drive (2WD) and four-wheel drive (4WD)) were considered as main treatments affecting tractor tractive efficiency. Among several computer simulation frameworks developed in the investigation, the best ANFIS framework yielded coefficient of determination, root mean square error, mean absolute percentage error, and mean of absolute values of simulation residual errors of 0.987, 1.857%, 2.314% and 1.582%, respectively. On the account of obtained statistical parameters, the best ANFIS computer simulation framework was validated as the more distinguished framework than that of the ANN. The ANFIS simulation results revealed that increment of plowing depth and forward speed caused nonlinear decrement of tractor tractive efficiency in each tractor mode. Moreover, physical perception obtained from the integrated ANFIS simulation results indicated that application of the 4WD mode rather than the 2WD mode increased tractor tractive efficiency. Therefore, it can be asserted that the ANFIS simulation results improved state of the art in domain of studying tractor tractive efficiency.

On the neurocomputing based intelligent simulation of tractor fuel efficiency parameters

Tractor fuel efficiency parameters (TFEPs) (fuel consumption per working hour (FCWH), fuel consumption per tilled area (FCTA) and specific volumetric fuel consumption (SVFC)) were intelligently simulated. A neurocomputing based simulation strategy (adaptive neuro-fuzzy inference system (ANFIS)) was used to simulate the TFEPs. A comparison was also made between results of the best ANFIS environment and those of another neurocomputing based simulation strategy, artificial neural network (ANN). Field experiments were conducted at plowing depths of 10, 20 and 30 (cm) and forward speeds of 2, 4 and 6 (km/h) using a disk plow implement. Statistical descriptor parameters applied to evaluate simulation environments indicated that the best simulation environment of both ANFIS and ANN were able to perfectly predict the TFEPs. However, the best comprehensive ANN simulation environment with a simple architecture of 2-6-3 was easier to use than three individual ANFIS simulation environments. The ANN results revealed that simultaneous increase of forward speed from 2 to 6 (km/h) and plowing depth from 10 to 30 (cm) led to nonlinear increment of the FCWH from 5.29 to 14.89 (L/h) and nonlinear decrement of the SVFC from 2.95 to 0.67 (L/h kW). Meanwhile, forward speed increment along with plowing depth decrement resulted in nonlinear decrement of the FCTA from 28.13 to 12.24 (L/ha). Interaction of forward speed and plowing depth on the FCWH and SVFC was congruent, while it was incongruent for the FCTA. It is suggested to employ the ANN environment in developing future fuel planning schemes of tractor during tillage operations.

Determination of the mastoid surface area and volume based on micro-CT scanning of human temporal bones. Geometrical parameters depend on scanning resolutions

The mastoid air cell system (MACS) with its large complex of interconnected air cells reflects an enhanced surface area (SA) relative to its volume (V), which may indicate that the MACS is adapted to gas exchange and has a potential role in middle ear pressure regulation. These geometric parameters of the MACS have been studied by high resolution clinical CT scanning. However, the resolution of these scans is limited to a voxel size of around 0.6 mm in all dimensions, and so, the geometrical parameters are also limited. Small air cells may appear below the resolution and cannot be detected. Such air cells may contribute to a much higher SA, and thus, also the SA/V ratio. More accurate parameters are important for analysis of the function of the MACS including physiological modeling.Our aim was to determine the SA, V, and SA/V ratio in the MACS in human temporal bones at highest resolution by using micro-CT-scanning. Further, the influence of the resolution on these parameters was investigated by downsampling the data. Eight normally aerated temporal bones were scanned at the highest possible resolution (30–60 μm). The SA was determined using a triangular mesh fitted onto the segmented MACS. The V was determined by summing all the voxels containing air. Downsampling of the original data was applied four times by a factor of 2.The mean SA was 194 cm2, the mean V was 9 cm3, and the mean SA/V amounted to 22 cm−1 (22 cm2/cm3). Decreasing the resolution resulted in a non-linear decrement of SA and SA/V, whereas V was mainly independent of the resolution.The current study found significantly higher SA and SA/V compared with previous studies using clinical CT scanning at lower resolutions. These findings indicate a role of the MACS different from that of the tympanum, though they are limited to only a smaller sample of temporal bones without knowledge about the disease history of the subjects. The current data on mastoid geometry seems important for a more accurate modeling of the middle ear physiology and future studies may include morphological investigations of the air cells with possible implications for their postnatal development.

Contact angle hysteresis of bovine serum albumin (BSA) solution/metal (Au-Cr) coated glass substrate

Bovine serum albumin (BSA) has an extraordinary property to carry biomolecules. An experimental study on the wettability of BSA is presented in this study. The variations in the surface tension and the equilibrium contact angle with the change in BSA concentration are also reported. The surface tension and the contact angle are measured with pendant and sessile drop techniques, respectively. A nonlinear decrement in the surface tension with the increment in the BSA concentration is observed. An equilibrium contact angle of a BSA solution with particular concentration is determined by studying the hysteresis in the contact angle from dynamic contact angle measurements. The needle-in-drop technique is used to study the hysteresis of the contact angle. It is observed that the obtained surface tension and the equilibrium contact angle vary with the BSA concentration. In this reported study, for the considered combination of the BSA concentration and solid surface, the liquid drop does not recede as the drop volume decreases, which represents nonreceding contact angle condition. The increment in the contact angle with the increment in the BSA concentration is observed. Finally, it is observed that the inclusion of the proteins not only changes the surface tension but also changes the contact angle.

Acceleration of soliton by nonlinear Landau damping of dust-helical waves

The problem of nonlinear Landau damping of helicon waves in dusty plasma in particular emphasis to the acceleration of soliton is presented here. This in the framework of a collisionless, anisotropic homogeneous dusty plasma in one dimension, can be well described by two coupled dynamical equations of the generalized Zakharov type, with one extra nonlocal term coming from Landau damping. Nonlinear-nonlocal term gives rise to essential contributions relative to the local term. Then under different conditions, kinetic nonlinear Schrödinger equation is constructed and nonlinear decrement is obtained for two cases. It is noticed that the time dependant term in the ponderomotive force plays a significant role for this kind of damping. Additionally, it is shown that nonlinear Landau damping leads to the amplitude modulation of dust helicon waves, further modulational instability, and maximal growth rate is obtained when the group velocity of the helicon wave reaches the dust-acoustic speed. It is demonstrated that how the nonlinear Landau damping leads to the acceleration of soliton, which is eventually slowed down after transferring some of its energy to the wave. Emission of dust-acoustic wave by accelerated soliton is discussed briefly.

A practical approach to parameter identification for a lightly damped, weakly nonlinear system

Fluidelastic systems are often lightly damped and exhibit weak nonlinear damping. The weak linear and nonlinear damping forces have a significant effect on the long-term behaviour of the system. However, parameter identification methods tend to concentrate on identifying the strongest forces. In this paper the applicability of two identification methods to a single degree of freedom fluidelastic system is investigated using experimental data. The system is weakly nonlinear under flow conditions and is prone to fluidelastic instability (i.e. self-excited limit cycle behaviour). The crucial effect of the weak damping forces on the system stability and post-stable behaviour has been demonstrated. The nonlinearity detection and identification has been done using an analytic representation of the displacement signal (FREEVIB method) and subsequently a nonlinear decrement method was used for comparison. The identified models were used to predict the global behaviour of the system in the form of limit cycle amplitudes and this has been used as an indication of accuracy. It was found that the nonlinear decrement method yields superior predictions, but it suffers from the limitation that the functional form of the system must be known a priori. Therefore, it is concluded that employing both methods together provides a more powerful approach for parameter estimation in a lightly damped system where weak nonlinear damping plays an important role.

EFFECT OF SINGLE VS. MULTIPLE DOSING ON PERFLUOROCHEMICAL (PFC) ELIMINATION PROFILE DURING PARTIAL LIQUID VENTILATION WITH LIQUIVENT®. † 2029

Previously, PFC elimination during partial liquid ventilation (PLV) has been qualitatively estimated from theoretical calculations, radiographic assessment, and visualization of PFC in the endotracheal tube at zero end expiratory pressure. The objective of this study was to quantitate PFC elimination kinetics following initial fill and with or without hourly dosing. Eleven adolescent New Zealand rabbits (1.55 ± 0.05 SE kg) were surgically instrumented and studied in two groups: Gr I: (n=6) PLV with LiquiVent® (S: single dose); Gr II: (n=5) PLV with LiquiVent® and hourly dosing (M: multiple doses). All rabbits were studied for four hours following initial instillation of PFC liquid (17 ± 0.72 SE ml/kg) equal to the measured gas functional residual capacity. Animals were ventilated at constant breathing frequency (30 bpm), tidal volume (9.3 ± 0.3 SE ml/kg), positive end expiratory pressure (4 cmH2O), inspiratory time(0.3 sec), and temperature (33 °C). PFC saturation of mixed expired gas(PFC-Sat) was assessed with a thermal conductivity analyzer and PFC elimination was calculated from PFC-Sat, minute ventilation, and temperature. For the M group additional doses were determined via hourly PFC elimination calculations. Arterial blood gases and lung mechanics were also assessed. PFC elimination data (mean ± SE) during 4 hrs of study are tabulated below:Table Results of this study demonstrate an appreciable increase in PFC-Sat and PFC elimination over time from the respiratory system with hourly supplementation when compared to animals which did not receive additional doses (p < 0.05). Additionally, PFC loss decreases with time independent of group (p < 0.05). These data demonstrate that PFC elimination rate is not constant and follows a non-linear decrement with time. This may have occurred due to distributional differences of ventilation and PFC between the M and S groups. These data are relevant in that the protective benefit of PFC in the lung may be sustained by frequent dosing which maintains PFC lung volume. (Supp. in part by NIH grant # R29HD26341 and Alliance Pharm. Corp.)