Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field

The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management(IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.

Multi-field dynamic modeling and numerical simulation of aluminum alloy resistance spot welding

In order to explore the influence of welding parameters and to investigate the Al alloy (AA) nugget formation process, a comprehensive model involving electrical-thermal-mechanical and metallurgical analysis was established to numerically display the resistance spot welding (RSW) process within multiple fields and understand the AA-RSW physics. A multi-disciplinary finite element method (FEM) framework and a empirical sub-model were built to analyze the affecting factors on weld nugget and the underlying nature of welding physics with dynamic simulation procedure. Specifically, a counter-intuitive phenomenon of the resistance time-variation caused by the transient inverse virtual variation (TIVV) effect was highlighted and analyzed on the basis of welding current and temperature distribution simulation. The empirical model describing the TIVV phenomenon was used for modifying the dynamic resistance simulation during the AA spot welding process. The numerical and experimental results show that the proposed multi-field FEM model agrees with the measured AA welding feature, and the modified dynamic resistance model captures the physics of nugget growth and the electrical-thermal behavior under varying welding current and fluctuating heat input.

Trajectory Tracking of Quadrotor Aerial Robot Using Improved Dynamic Inversion Method

This paper presents trajectory tracking control works concerning quadrotor aerial robot with rigid cross structure. The quadrotor consists of four propellers which are two paired clockwise rotate and anticlockwise rotate. A nonlinear dynamic model of the quadrotor is provided, and a controller based on the improved dynamic inverse is synthesized for the purpose of stabilization and trajectory tracking. The proposed control strategy has been tested in simulation that can balance the deviation of model inaccuracy well.

PARAMETER IDENTIFICATION OF DYNAMIC MODELS USING A BAYES APPROACH

The Bayesian method of statistical analysis has been applied to the parameter identification problem. A method is presented to identify parameters of dynamic models with the Bayes estimators of measurement frequencies. This is based on the solution of an inverse generalized evaluate problem. The stochastic nature of test data is considered and a normal distribution is used for the measurement frequencies. An additional feature is that the engineer's confidence in the measurement frequencies is quantified and incorporated into the identification procedure. A numerical example demonstrates the efficiency of the method.

A statistical dynamics model of the marine ecosystem and its application in Jiaozhou Bay

Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.

Dynamic Modeling of Heterogeneous Spatial Analysis for Energy and Natural Resources in Grid Integration Environment

With the high-tech industrialization of earth observation satellite remote sensing and the implementation of digital earth strategy,the energy and natural resources have been decided to be the key research fields in China.In these fields,from the model based on topology data,through simple feature data model to rule-based data model,the basic spatial analysis algorithms have been developed

PROPER APPLICATION OF A KIND OF MATRIX CON-STRUCTION METHOD IN PHYSICAL PARAMETER IDENTIFICATION OF DYNAMIC MODEL

The expressions of matrix construction by using the singular value decomposition (SVD) are applied to the physics parameter identification of dynamic model. Then, based upon to the characteristics of a kind of matrix construction method, the orders of the parameter identification model can be reduced. After reducing, the mathematics and physics correspondence relations between the subsystem and the original system are distinct. the condensation errors can be avoided. The numerical example shows the benefit of the presented methodology.

Suiting Dynamic Models of Fixed-Bed Catalytic Reactors for Computer-Based Applications

This work investigated the applicability of heterogeneous and pseudo-homogeneous models to predict the dynamic behavior of a fixed-bed catalytic reactor. Some issues concerning the dynamic behavior of the system were discussed, such as the prediction of the inverse response phenomenon. The proposed models (Het- erogeneous I and II and Pseudo-homogeneous) were able to predict with qualitative similarity the main characteristics of the dynamic behavior of a fixed-bed catalytic reactor, including the inverse response. The computational time demanded for the solution of the heterogeneous models was 10 to 50% longer than in the case of the pseudo-homogeneous model, making the use of the former suitable for applications where computational time is not the major restriction (off-line applications). On the other hand, when on-line applications are required, the simplified model (Pseudo-homogeneous model) showed to be a good alternative because this model was able to predict (qualitatively) the dynamics of the reactor using a faster and easier numerical solution.

Reconstructing the Absorption Function in a Quasi-Linear Sorption Dynamic Model via an Iterative Regularizing Algorithm

This study addresses the parameter identification problem in a system of time-dependent quasi-linear partial differential equations(PDEs).Using the integral equation method,we prove the uniqueness of the inverse problem in nonlinear PDEs.Moreover,using the method of successive approximations,we develop a novel iterative algorithm to estimate sorption isotherms.The stability results of the algorithm are proven under both a priori and a posteriori stopping rules.A numerical example is given to show the efficiency and robustness of the proposed new approach.

Dynamic mechanical behavior and nonlinear hyper-viscoelastic constitutive model of SiO_(2) particle-reinforced silicone rubber composite:experimental and numerical investigation

SiO_(2)-particle reinforced silicon rubber composite(SP-RSRC)is a widely utilized material that offers shock absorption protection to various engineering structures in impact environments.This paper presents a comprehensive investigation of the mechanical behavior of SP-RSRC under various strain rates,employing a combination of experimental,theoretical,and numerical analyses.Firstly,quasi-static and dynamic compression tests were performed on SP-RSRC utilizing a universal testing machine and split Hopkinson pressure bar(SHPB)apparatus.Nonlinear stress-strain relationships of SP-RSRC were obtained for strain rates ranging from 1×10^(−3) to 3065 s^(−1).The results indicated that the composite showed evident strain rate sensitivity,along with nonlinearity.Then,a nonlinear visco-hyperelastic constitutive model was developed,consisting of a hyperelastic component utilizing the 3rd-order Ogden energy function and a viscous component employing a rate-dependent relaxation time scheme.The model accurately characterized the dynamic mechanical response of SP-RSRC,effectively mitigating the challenge of calibrating an excessive number of material parameters inherent in conventional viscoelastic models.Furthermore,the simplified rubber material(SRM)model,integrated within the LS-DYNA software,was chosen to depict the mechanical properties of SP-RSRC in numerical simulations.The parameters of the SRM model were further calibrated based on the strain-stress relationships of SP-RSRC,as predicted by the developed nonlinear visco-hyperelastic constitutive model.Finally,an inverse ballistic experiment using a single-stage air gun was conducted for SP-RSRC.Numerical simulations of SHPB experiments and the inverse ballistic experiment were then performed,and the reliability of the calibrated SRM model was verified by comparing the results of experiments and numerical simulations.This study offers a valuable reference for the utilization of SP-RSRC in the realm of impact protection.

Time-Lapse Full-Waveform Inversion Using Cross-Correlation-Based Dynamic Time Warping

Offshore carbon capture, utilization, and storage(OCCUS) is regarded as a crucial technology for mitigating greenhouse gas emissions.Quantitative monitoring maps of sealed carbon dioxide are necessary in a comprehensive OCCUS project. A potential high-resolution method for the aforementioned purpose lies in the full-waveform inversion(FWI) of time-lapse seismic data. However, practical applications of FWI are severely restricted by the well-known cycle-skipping problem. A new time-lapse FWI method using cross-correlation-based dynamic time warping(CDTW) is proposed to detect changes in the subsurface property due to carbon dioxide(CO_(2)) injection and address the aforementioned issue. The proposed method, namely CDTW, which combines the advantages of cross-correlation and dynamic time warping, is employed in the automatic estimation of the discrepancy between the seismic signals simulated using the baseline/initial model and those acquired. The proposed FWI method can then back-project the estimated discrepancy to the subsurface space domain, thereby facilitating retrieval of the induced subsurface property change by taking the difference between the inverted baseline and monitor models. Numerical results on pairs of signals prove that CDTW can obtain reliable shifts under amplitude modulation and noise contamination conditions. The performance of CDTW substantially outperforms that of the conventional dynamic time warping method. The proposed time-lapse fullwaveform inversion(FWI) method is applied to the Frio-2 CO_(2) storage model. The baseline and monitor models are inverted from the corresponding time-lapse seismic data. The changes in velocity due to CO_(2) injection are reconstructed by the difference between the baseline and the monitor models.

基于干扰观测器与终端滑模的车辆纵向控制

为了消除未知干扰和不确定性对车辆纵向控制的影响,设计了基于干扰观测器和终端滑模控制的分层式车辆纵向控制系统.利用干扰观测器对系统干扰进行实时观测,实现对系统的反馈补偿,降低滑模控制的切换增益,从而抑制滑模控制的抖振.利用Lyapunov函数证明了控制系统的稳定性,并通过Carsim/Simulink进行了联合仿真试验.结果表明:在两种仿真工况条件下,控制器对参考速度跟踪效果良好,速度误差最大仅为0.22 m/s,干扰观测器对系统干扰能够准确快速估计,估计误差仅为0.003 14,切换逻辑执行器发挥良好;与传统滑模控制相比,所设计的控制器稳定性更好,抑制了滑模控制的抖振,实现了对车辆纵向速度的稳定跟踪.

ACG-TypeMethod for InverseQuadratic Eigenvalue Problems in Model Updating of Structural Dynamics

In this paper we first present a CG-type method for inverse eigenvalue problem of constructing real and symmetric matrices M,D and K for the quadratic pencil Q(λ)=λ^(2)M+λD+K,so that Q(λ)has a prescribed subset of eigenvalues and eigenvectors.This method can determine the solvability of the inverse eigenvalue problem automatically.We then consider the least squares model for updating a quadratic pencil Q(λ).More precisely,we update the model coefficient matrices M,C and K so that(i)the updated model reproduces the measured data,(ii)the symmetry of the original model is preserved,and(iii)the difference between the analytical triplet(M,D,K)and the updated triplet(M_(new),D_(new),K_(new))is minimized.In this paper a computationally efficient method is provided for such model updating and numerical examples are given to illustrate the effectiveness of the proposed method.

基于黏弹性Chapman-Kelvin模型的裂缝储层频变AVAZ反演研究

为了在地震资料和裂缝储层特征之间建立联系,对裂缝储层采用了等效介质模型.而传统的等效介质模型未充分考虑非完全弹性介质理论和基于频变各向异性理论的双相或多相流体假设,也不能对实际裂缝储层中的地震波频散和衰减现象提供准确合理的解释,并且储层参数的反演研究对裂缝储层的定性预测和定量描述举足轻重.为此,本文首先根据所提出的黏弹性Chapman-Kelvin动态等效介质模型,该模型考虑了耦合的双相流体假设、黏弹性理论、喷射流以及斑块效应,并在此基础上分析了裂缝储层参数(主要为裂缝密度、裂缝长度、孔隙度和含水饱和度)对地震波频变特征的影响.然后基于黏弹性Chapman-Kelvin模型与Schoenberg和Protazio概括的Zoeppritz方程所计算出的频变反射系数,分析了反射PP波和PS波的频变AVAZ(Amplitude Versus Angle and Azimuth)特性和PP波频变反射系数与裂缝储层参数的关系.同时考虑到发生地震频散时,反射系数和频率产生关系,构建了在角度、方位和时间域内的新型正演方程.最后,基于PP波频变反射系数对裂缝密度、裂缝长度、孔隙度和含水饱和度的变化有较好的敏感性特点,进行了两种反演方法研究:其一是基于贝叶斯理论直接反演方法,其中以对数绝对范数作为似然函数和高斯分布,即L2范数度量作为先验约束;其二是基于频变反射系数的MCMC(Markov Chain Monte Carlo)随机反演方法.通过频变AVAZ进行裂缝储层参数的反演研究,结果表明,MCMC随机反演方法在缺失先验的储层参数信息时,反演结果的不确定性较强.当存在有效且足够的先验信息时,反演结果的可靠性进一步提升.而基于贝叶斯理论直接反演方法,则显示出基于频变AVAZ来区别大尺度裂缝和微尺度裂隙的潜力.

基于HYDRUS-1D模型的水库近坝区土壤水分动态模拟

为探究五强溪水库近坝区土壤水分动态变化规律,以研究区内土壤墒情站为研究对象,利用实测逐日降雨与逐日蒸发数据驱动HYDRUS-1D模型反演土壤水力特性参数,分别在深度为10、20、40 cm观察点处进行土壤水分动态模拟,探讨研究区土壤水分动态变化规律及模型的应用效果。结果表明:不同观察点土壤水分模拟值与实测值的决定系数平均值为0.74,纳什效率系数平均值为0.71,均方根误差在0.011~0.035 cm^(3)/cm^(3)之间;0~10 cm深度的土壤水分对降雨和蒸发的响应最灵敏,波动最大;在水库主汛期(4—6月份)土壤水分变化平稳,且保持在较高的水平;研究期内7—12月份土壤水分在较大降雨情况下出现短暂饱和,土壤干湿变化明显,模拟值与实测值吻合度较高;整体上,HYDRUS-1D模型在研究区土壤水分动态模拟中具有较高的精度,可为研究区土壤水分估计及其动态变化规律研究提供有效方法。

基于肌肉协同和肌肉力相对关系的人体行走下肢肌肉力计算方法

针对现有计算肌肉力的方法中缺乏对运动过程中肌肉协同机制和肌肉力相对关系考量的问题,提出一种基于行走过程中肌肉力相对关系与肌肉协同的肌肉力计算方法。该方法在二次优化的基础上,将人体行走过程中一段时间的肌肉力以及不同肌肉收缩力之间的关系纳入逆动力学计算中。在所建立的肌肉骨骼模型的基础上,利用该方法得到行走过程中下肢主要肌肉的肌肉力,计算结果可以有效地反映人体运动规律以及行走过程中的肌肉协同机制。该计算方法可为人体运动形成机制、运动康复与训练以及仿人机器控制等提供理论依据。

临近空间球载飞行器投放控制关键技术综述

临近空间作为地球新的认知领域和重要的国家安全空间逐渐受到世界主要大国的重视.临近空间飞行器球载投放起飞方式能够使飞行器快速达到期望的飞行高度,同时减少因穿越对流层稠密大气所需的能源消耗,因而受到广泛关注并迅速发展成为临近空间飞行器起飞的一种重要方式.独特的球载投放起飞方式对高空气球及被投放飞行器的多项控制关键技术提出了较高的要求,高空低密度的飞行环境使得低速飞行具有明显的低雷诺数特性,随高度剧烈变化的风场增加了球载平台定点区域驻空的难度,载球系统上升过程的旋转运动给投放控制带来巨大的干扰,投放时刻的判断与拉起控制给大翼展柔性飞行器带来了新挑战.本文梳理了临近空间球载飞行器投放控制的关键技术及其研究现状,并对其未来的应用进行了展望.

船用橡胶隔振器参数反演及预测模型应用

以BE型橡胶隔振器为研究对象,根据隔振器的额定参数,通过ABAQUS与ISIGHT联合仿真反演橡胶材料的超弹本构参数和黏弹本构参数,利用反演参数建立橡胶隔振器的预测模型。结果表明,预测模型垂、纵、横3个方向静刚度和3个方向动刚度的误差均小于7%;使用此预测模型研究橡胶隔振器频率、振幅和预载荷对动刚度的影响时,仿真结果与同类橡胶器件的试验结果基本一致;将此预测模型应用于系统级振动模拟时,仿真结果能较好地吻合振动试验结果。

Inter-relationship between approximate dynamic inversion and MRAC augmented with proportional-integral controller

Approximate Dynamic Inversion (ADI) is basically an approximation of exact dynamic inversionor feedback linearisation, which converts a nonlinear system to an equivalent linear structure.This method can be widely applied for controlling minimum phase, nonaffine-in-control systems.For applying the ADI method, a fast dynamic subsystem for deriving explicit inversion of thenonaffine equation is required. With full state feedback, ADI may be expressed in the same way asa Proportional Integral (PI) controller with only knowledge of the sign of control effectiveness andalso without any approximation. The Model Reference Adaptive Controller (MRAC) augmentedwith the PI method is an adaptive control technique where the PI parameters are updated/tunedas per the control methodology based on the MRAC-Massachusetts Institute of Technology (MIT)rule so that the plant is capable to follow the reference model. The main objective of this paperis to find the relationship between ADI and MRAC augmented with a PI controller.

INVERSION OF A NONLINEAR DYNAMICAL MODEL FROM THE OBSERVATION

A technique for inversion of a nonlinear dynamical model from the observations has been developed, and examined by using the Lorenz system. The results show that the Lorenz system can be accurately inversed by using the observation data set. This technique will be broadly used in establishing the nonlinear dynamical model from an actual data set.