Using a multi-phase model to predict flushing of sprayed seal pavements

Flushing is a pavement defect that has a negative effect on the structural integrity and performance of a pavement surface. The aim of this study was to develop a model to predict the occurrence and progression of flushing on sprayed seal pavements. Data analysis and model development were performed using data sourced from New Zealand's Long-Term Pavement Performance programme. The developed model consists of two phases to model (1) the probability of flushing initiating on a pavement and (2) the progression of flushing. The probability of flushing initiation was modelled using a logistic model format, and the progression of flushing was modelled using a linear model format. Testing of the developed model revealed that the logistic model predicted the probability of flushing initiation at 76% accuracy, whereas the linear model had statistically robust predictions of flushing. The developed model is recommended for use in sprayed seal pavement management processes.     

基于超弹性、分数导数和摩擦模型的碳黑填充橡胶隔振器动态建模

碳黑填充橡胶隔振器（以下简称＂橡胶隔振器＂）的动态特性与预载、激振频率和激振振幅相关。实验测试了一橡胶隔振器的动态特性,建立了基于超弹性、分数导数和摩擦模型的橡胶隔振器动态特性的非线性模型,其中超弹性模型用于描述橡胶隔振器的弹性,分数导数模型用于表征橡胶隔振器动态特性的激振频率相关性,摩擦模型用于表征橡胶隔振器动态特性与激振振幅相关的特性,文中论述了建模方法和参数辨识方法。有限元分析获得橡胶隔振器的静态力-位移曲线,利用测试得到的橡胶隔振器在大振幅、低频激励下的力-位移关系,拟合得到橡胶隔振器动态模型中摩擦模型的参数,利用测试得到的橡胶隔振器在小振幅、高频激励下的力-位移关系,拟合得到橡胶隔振器动态模型中分数导数模型的参数。利用建立的模型和拟合得到的参数计算分析了橡胶隔振器动态特性的振幅相关性、频率相关性和预载相关性,并与实验结果进行了对比分析。分析结果表明,建立的模型可以较好的描述橡胶隔振器的动态特性。     

Macroscopic models of magnetization

Four magnetization models, now considered as classical, are presented: the Stoner-Wolhfarth model, the Jiles-Atherton model, the Globus model, and the Preisach model. The paper describes the methods each model uses to simulate the magnetization mechanisms, reversible and irreversible processes, major and minor loops, and anhysteretic behavior. Improvements and changes are proposed to the Stoner-Wolhfarth and Globus models. The necessary simplifying assumptions define the limits of applicability of the models. The paper concludes with a table of the main characteristics of each model to help a potential user to make a suitable choice     

Self-adapting traffic flow status forecasts using clustering

A key problem for the efficient use of stationary traffic prediction models is that for adaptation to new data they require human-made re-calibration with a new database. So far, there has been a lack of knowledge of how to develop a practical prediction model that would learn while working online. Anyone providing real-time traffic information and making forecasts of the traffic situation could benefit from such models. The aim of the study is to develop a method to make a self-adapting short-term prediction model for the status of traffic flow. The principles for such a model are described. The method is based on self-organising map and the model is implemented on a highway in the Helsinki Metropolitan Area. Specifically, the structure of the model makes it possible for the model to learn by itself without the need to save all the data into databases. Consequently, long-term online use of the model makes fewer demands on computers. The results indicated that the selfadapting principle improved the performance of the model. The principles of the model can also be applied in other locations.     

波轮式全自动洗衣机刚柔耦合模型的建立

摘要：刚柔耦合模型是波轮式全自动洗衣机结构设计的基础。为建立这一模型,首先在ANSYS中建立了盛水桶的有限元模型并进行模态分析,进而通过与实验结果的对比验证了有限元模型的正确性。采用修正的Craig-Bampton模态对盛水桶进行动力学建模,并与刚性模型进行耦合,推导得到系统整体的刚柔耦合模型。最后,采用 方法求解系统DAE方程组,得到了脱水过程中盛水桶的变形信息与载荷信息。将载荷信息反馈给ANSYS进行分析,其计算结果与本文结果进行了对比,验证了本文模型的有效性。     

自回归分布滞后模型在数控机床热误差建模中的应用

对多元线性回归模型、回归与残差AR叠合模型和自回归分布滞后模型3种热误差建模方法进行了介绍与比对分析。多元线性回归模型方法简单快捷,但因热误差呈非线性且具有互交作用,较难获得精确热误差数学模型。后两个模型均属时间序列分析方法,其优点是能够比较精确地建立热误差数学模型,两者的区别是叠合模型把参数估计分成两部分,而自回归分布滞后模型是统一估计参数,因此叠合模型的精度要低于自回归分布滞后模型精度,并通过实例验证,自回归分布滞后模型在精密数控机床热误差建模中具有较好的建模精度。     

火灾事故的灰色-马尔可夫模型预测研究

鉴于火灾事故的发生受多种复杂因素的影响,并且具有较大的随机性和波动性的特点,笔者等将灰色模型和马尔可夫模型相结合,建立火灾事故的灰色?马尔可夫模型,利用灰色模型的灰色性和马尔可夫模型的随机性来体现各自的优点,并运用该模型对全国农村火灾事故进行预测。实际应用表明,灰色?马尔可夫模型的预测精度明显高于灰色模型的预测精度,完全能满足预测精度的要求,可以较好地用于火灾事故的预测。     

Automatic identification of time-series models from long autoregressive models

Identification is the selection of the model type and of the model order by using measured data of a process with unknown characteristics. If the observations themselves are used, it is possible to identify automatically a good time-series model for stochastic data. The selected model is an adequate representation of the statistically significant spectral details in the observed process. Sometimes, identification has to be based on many less than N characteristics of the data. The reduced statistics information is assumed to consist of a long autoregressive (AR) model. That AR model has to be used for the estimation of moving average (MA) and of combined ARMA models and for the selection of the best model orders. The accuracy of ARMA models is improved by using four different types of initial estimates in a first stage. After a second stage, it is possible to select automatically which initial estimates were most favorable in the present case by using the fit of the estimated ARMA models to the given long AR model. The same principle is used to select the best type of the time-series models and the best model order. No spectral information is lost in using only the long AR representation instead of all data. The quality of the model identified from a long AR model is comparable to that of the best time-series model that can be computed if all observations are available.     

A numerical model for the simulation of two-dimensional convective-dispersion in shallow estuaries

A numerical model for describing two-dimensional convective-dispersive processes in tidally influenced shallow bays in given. The model uses a multi-stage implicit technique with finite difference formulation, for solving the basic mass balance equation for a conservative constituent. The basic inputs to this model consist of instantaneous tidal velocities and depths obtained from an operational tidal hydrodynamic model. The sensitivity of the output concentrations to the variation of dispersion coefficients is investigated. Application of the model to a practical situation is demonstrated by considering Galveston Bay. Texas, U.S.A. The transport model is operated to generate results which are compared with measurements from dye release studies made in a physical model of Galveston Bay.     

高温下不同比例钢筋混凝土柱力学性能相似性有限元分析

为研究高温下缩尺模型和足尺模型力学性能的相似性,力求通过缩尺模型结果反推得到足尺模型的耐火性能,设计12根钢筋混凝土柱的足尺模型,并基于相似理论建立对应的2/3、1/2和1/3缩尺模型,同时,根据缩尺比调整各组缩尺模型的实际升温曲线、轴力和位移加载速率,并基于ABAQUS软件对各组模型进行耐火性能分析,对比各组原型化的缩尺模型和足尺模型的高温力学性能。研究结果表明:通过调整结构相似关系、时间相似关系和温度场相似关系,经过原型化的缩尺模型和足尺模型的截面温度分布、柱顶轴向位移、耐火极限和极限承载力均具有较好的相似关系,即通过缩尺模型柱可以相对较为准确地反映足尺模型柱的耐火性能。     

钢筋混凝土结构小比例尺模型设计方法及相似性研究

为研究高温下缩尺模型和足尺模型力学性能的相似性,力求通过缩尺模型结果反推得到足尺模型的耐火性能,设计12根钢筋混凝土柱的足尺模型,并基于相似理论建立对应的2/3、1/2和1/3缩尺模型,同时,根据缩尺比调整各组缩尺模型的实际升温曲线、轴力和位移加载速率,并基于ABAQUS软件对各组模型进行耐火性能分析,对比各组原型化的缩尺模型和足尺模型的高温力学性能。研究结果表明：通过调整结构相似关系、时间相似关系和温度场相似关系,经过原型化的缩尺模型和足尺模型的截面温度分布、柱顶轴向位移、耐火极限和极限承载力均具有较好的相似关系,即通过缩尺模型柱可以相对较为准确地反映足尺模型柱的耐火性能。     

采用粘弹性分数导数模型的橡胶隔振器动态特性的建模及应用

橡胶隔振器的动态特性与激振振幅及激振频率相关。给出一个可以表征橡胶隔振器动态特性与激振振幅及激振频率相关性的模型,其中,用摩擦力模型表征其动态特性与振幅的相关性,用分数导数粘弹性模型表征其动态特性与频率的相关性。计算分析了所建立的模型与目前广泛采用的两种描述橡胶隔振器动态特性模型(基于Maxwell的模型和粘性阻尼模型)在表征其与激振振幅及激振频率的相关性;使用分数导数和Kelvin-Voigt模型时,计算分析了一个含有橡胶隔振器的单自由度振动系统的自由振动和阶跃激励的时域响应。计算结果表明:采用分数导数模型能更加准确地描述橡胶隔振器的动态特性,建立的模型可以用于含有橡胶隔振器的振动系统的动态特性分析。     

A new bi-fidelity model reduction method for Bayesian inverse problems

This work presents a new bi-fidelity model reduction approach to the inverse problem under the framework of Bayesian inference. A low-rank approximation is introduced to the solution of the corresponding forward problem and admits a variable-separation form in terms of stochastic basis functions and physical basis functions. The calculation of stochastic basis functions is computationally predominant for the low-rank expression. To significantly improve the efficiency of constructing the low-rank approximation, we propose a bi-fidelity model reduction based on a novel variable-separation method, where a low-fidelity model is used to compute the stochastic basis functions and a high-fidelity model is used to compute the physical basis functions. The low-fidelity model has lower accuracy but efficient to evaluate compared with the high-fidelity model; it accelerates the derivative of recursive formulation for the stochastic basis functions. The high-fidelity model is computed in parallel for a few samples scattered in the stochastic space when we construct the high-fidelity physical basis functions. The required number of forward model simulations in constructing the basis functions is very limited. The bi-fidelity model can be constructed efficiently while retaining good accuracy simultaneously. In the proposed approach, both the stochastic basis functions and physical basis functions are calculated using the model information. This implies that a few basis functions may accurately represent the model solution in high-dimensional stochastic spaces. The bi-fidelity model reduction is applied to Bayesian inverse problems to accelerate posterior exploration. A few numerical examples in time-fractional derivative diffusion models are carried out to identify the smooth field and channel-structured field in porous media in the framework of Bayesian inverse problems.     

An Application of Stochastic and Dynamic Models for the Control of a Papermaking Process

A statistical approach to model a papermaking process and to control paper basis weight is presented. The process behavior is described by a mathematical model which takes into consideration both the input-output dynamics and disturbances coming into the system. The model building procedure was based on a three-step approach of identification, estimation and diagnostic checking. The disturbance model is accounted for by a discrete time series model, whereas the dynamic model is a discrete transfer function model. The simplicity of the modeling process lies in the fact that only the input-outpul data are necessary without recourse to a complicated analysis of the physical system itself.

An optimal control equation was arrived at whereby the basis weight of the paper was to be controlled at a specified target value. Confirmation runs were conducted to check the effectiveness of the control equation.     

Influence of constituent properties and microstructural parameters on the tensile modulus of a polymer/clay nanocomposite

A multi-scale model to predict the moduli of polymer–clay nanocomposites (PCNs) is presented. The model uses a locally orthotropic finite element model to develop constitutive equations to describe the stiffness properties of a group of aligned clay flakes with surrounding interphase suspended in a polymer matrix. The model then assembles a number of flake groups with varied orientations to predict the actual moduli seen in PCNs. The model is in good agreement with an experimentally obtained tensile modulus found in the literature. The model was also applied to estimate the relative influence of constituent properties and microstructural parameters on the anisotropic tensile modulus of the PCN.     

Modeling the Ultrasonic Radiation of a Planar Transducer Through a Plane Fluid—Solid Interface

Three types of transducer beam models are developed for obtaining the bulk waves generated by a plane piston transducer radiating through a planar fluid—solid interface. The first type, called the surface integral model, is based on a Rayleigh—Sommerfeld-like integral that requires a two-dimensional surface integral to be evaluated. The second model, called the boundary diffraction wave (BDW) paraxial model, simplifies the two-dimensional integration of the surface integral model to a one-dimensional line integration. The third type of model, called the edge element model, is shown to be a novel way of efficiently evaluating the two-dimensional surface integration of the surface integral model. The limitations of these models for simulating inspections near critical refracted angles and near the interface are discussed. It is shown that the introduction of the paraxial approximation in the BDW model allows that model to be computed with a very large (300—1) speed advantage over the surface integral while retaining the same accuracy in most cases. The edge element model, while having a smaller (5—1) advantage over the direct numerical integration of the surface integral model, retains the accuracy of the surface integral model in cases where the paraxial approximation fails and can be easily generalized to more complex testing situations (focused probes, curved interfaces, etc.).     

Finite-element model for phase-change recording

The finite-element method is applied to model phase-change recording in a grooved recording stack. A rigorous model for the scattering of a three-dimensional focused spot by a one-dimensional periodic grating is used to determine the absorbed light in a three-dimensional region inside the phase-change layer. The optical model is combined with a three-dimensional thermal model to compute the temperature distribution. Land and groove recording and polarization dependence are studied, and the model is applied to the Blu-ray Disc.     

A four-exponential model to describe the behaviour of fibre reinforced concrete

The paper reports on a proposed four-exponential (four-e) model to describe the behaviour of fibre reinforced concrete (FRC) in flexure. The four-e model was found to be capable to model a variety of curves and has the advantage of being able to model the complete load-deformation response of FRC with one continuous function. The four-e model is also mathematically efficient and differentiation and integration can be readialy applied. In addition, a rational and objective procedure by applying the model has been proposed increasing the potential of the four-e model.A comparison was carried out between theoretical and experimental load-deflection curves obtained for steel fibre reinforced concrete beams under three point bending. It was found that the four-e model can satistifactorily describe the experimental load-deflection curves. The principles applied for the comparison may possibly be applicable to FRC subjected to other types of loading.     

Implementation of the Preisach-Stoner-Wohlfarth Classical Vector Model

A useful vector magnetic model must accurately simulate both the magnitude and direction of the magnetization when a magnetic medium is subjected to a linear or rotating applied field. Such a model has been recently presented as the Preisach-Stoner-Wohlfarth (PSW) model. The Preisach model computes the magnitude of the magnetization; the Stoner-Wohlfarth model computes the direction of the magnetization. These two models are combined into the PSW model. The PSW model is now initially implemented in a two-dimensional vector classical Preisach model. The model is computationally efficient since the magnetization angle is accessed for all applied fields from a single lookup table, which is generated by a one-time Stoner-Wohlfarth computation.