Dynamic 3D modelling for architectural design

A graphics design system employing 2D input and display devices (such as the pen and tablet and the calligraphic CRT) to input, edit, and view 3D objects representing landscapes and architectural structures in realtime is discussed. Landscape is entered via a procedure that uses an inking algorithm to obtain 2D data defining the site's contours and additional available interactive devices to obtain the contour heights. Extrusion techniques and compound transformations are used to generate volumes from facial elements input via a suite of rubberband algorithms that take advantage of the graphics hardware. Dynamic menus, displayed transformation parameter values and extensive editing features facilitate user interaction. Architectural studies of complex structures built by combining basic architectural units input using extrusion techniques are presented.     

压电陶瓷执行器的动态迟滞非线性特性建模

针对精密定位系统中压电陶瓷执行器的迟滞非线性特性建模问题,提出了一种基于Hammerstein迟滞模型的建模方法。通过引入一个Backlash类的算子来描述迟滞非线性的轮廓。在利用"扩展输入空间法"将迟滞特性的多值映射转换为一一映射的基础上,采用引力搜索算法优化的支持向量回归机建立静态迟滞模型。为体现迟滞的动态特性,用ARX模型表征迟滞环的率相关性,从而建立了Hammerstein级联模型。并从精密定位系统中采集了实测数据,通过电容传感器获取压电陶瓷执行器给定电压下的位移值,对所提出的模型进行了实验。实验表明:该模型具有较好的性能,辨识过程简便且易于工程实现。     

Dynamic modelling using neural networks

A neural network structure is presented that uses feedback of unmeasured system states to represent dynamic systems more efficiently than conventional feedforward and recurrent networks, leading to better predictions, reduced training requirement and more reliable extrapolation. The structure identifies the actual system states based on imperfect knowledge of the initial state, which is available in many practical systems, and is therefore applicable only to such systems. It also enables a natural integration of any available partial state-space model directly into the prediction scheme, to achieve further performance improvement. Simulation examples of three varied dynamic systems illustrate the various options and advantages offered by the state-feedback neural structure. Although the advantages of the proposed structure, compared with the conventional feedforward and recurrent networks, should hold for most practical dynamic systems, artificial systems can readily be created and real systems can surely be found for which one or more of these advantages would vanish or even get reversed. Caution is therefore recommended against interpreting the suggested advantages as strict theorems valid in all situations.     

Dynamic delamination modelling using interface elements

Existing techniques in explicit dynamic Finite Element (FE) codes for the analysis of delamination in composite structures and components can be simplistic, using simple stress-based failure function to initiate and propagate delaminations.This paper presents an interface modelling technique for explicit FE codes. The formulation is based on damage mechanics and uses only two constants for each delamination mode; firstly, a stress threshold for damage to commence, and secondly, the critical energy release rate for the particular delamination mode. The model has been implemented into the LLNL DYNA3D Finite Element (FE) code and the LS-DYNA3D commercial FE code.The interface element modelling technique is applied to a series of common fracture toughness based delamination problems, namely the DCB, ENF and MMB tests. The tests are modelled using a simple dynamic relaxation technique, and serves to validate the methodology before application to more complex problems.Explicit Finite Elements codes, such as DYNA3D, are commonly used to solve impact type problems. A modified BOEING impact test at two energy levels is used to illustrate the application of the interface element technique, and it’s coupling to existing in-plane failure models. Simulations are also performed without interface elements to demonstrate the need to include the interface when modelling impact on composite components.     

Dynamic image modelling by neural networks

Sometimes an image can be characterized with the help of a dynamic system in terms of a first-order differential equation, e.g. when a scanner output contains additive noise and/or is degraded due to interaction between the sensing elements (the cameras) or by other phenomena. In this paper, an algorithm for image estimation from the noisy output of a scanner is hypothesized. Determination of the parameters A, B, and the C matrices of a dynamic system leads to the design of an estimator whose input is the output of a scanner with uniform speed. A portion of the overall algorithm using neural networks trained by a gradient descent learning algorithm is discussed in detail. In particular, the determination of A. B, C from states, time derivatives of states and inputs are highlighted. The details of implementation are included. The salient points regarding the development of the complete algorithm are discussed. It is hoped that the results achieved so far will give rise to new techniques for the application of neural networks to image enhancement in particular and to image processing in general.     

Dynamic modelling of a four-legged robot

A unified dynamic modelling approach of closed and/or open kinematic chain mechanisms is established. It is based on the use of the Newton-Euler formalism and the explicit formulation of kinematic holonomic constraints for the closed loop mechanisms. The approach is then applied to derive the dynamic modelling of a four-legged robot adopting a walking gait. The different movement sequences of the gait are analysed in order to calculate the all necessary terms in the dynamic equations of the quadruped robot.Nomenclature g acceleration vector due to the gravity - m _i mass of bodyS _i - G _i mass centre of bodyS _i - I _i inertia tensor of the bodyS _i about its mass centre - f coefficient of viscous friction - V _Gi 3-dim absolute velocity vector - _i 3-dim absolute angular velocity vector - t _i 6-dim twist vector of the bodyS _i defined as - n, l number of bodies, joints - d _i number of degree of freedom of the jointi - I _d 3×3 identity matrix - T _infi ^supr 6-dim wrench vector acting on the bodyS _i in whichr stands for:l (constraint wrench),g (gravity wrench),f (friction wrench),e (external wrench),m (driving wrench) - _i joint angle of the bodyS _i - O₍₃₎ 3-dim zero vector     

Dynamic aspects of visual modelling languages

A large class of diagrammatic languages falls under the broad definition of “executable graphics”, meaning that some transformational semantics can be devised for them. On the other hand, the definition of static aspects of visual languages often relies on some form of parsing or constructive process. We propose here an approach to the definition of visual languages syntax and semantics based on a notion of transition as production/consumption of resources. Transitions can be represented in forms which are intrinsic to the diagrams or external to them. A collection of abstract metamodels is presented to discuss the approach.     

Dynamic modelling of a simple existence constraint

A method is described for systematically deriving from a static formulation of a simple existence constraint the corresponding dynamic formulation. The latter formulation is embedded, under the form of applicability conditions, in a set of axiomatized update operations. A many-sorted first-order predicate calculus is used as the specification language. Update behaviour issues are identified and discussed.     

Dynamic metabolic modelling under the balanced growth condition

The issue of bioprocess dynamical modelling is addressed in the situation where measurements of extracellular species are the only available data besides measurements of the biomass itself. This question is investigated under the assumption that a metabolic network connecting the extracellular species is available. A metabolic flux analysis is first performed in order to test the consistency of the metabolic network. The elementary flux modes are computed and translated into a set of macro-reactions connecting the extracellular substrates and products. Then a dynamical model, compatible with the underlying metabolic network, is build on the basis of these macro-reactions. The approach is illustrated with the example of CHO cells cultivated in stirred flasks on a serum-free medium.     

Dynamic physical and economic modelling of riparian restoration options

A dynamic simulation framework is used to compare benefit-cost ratios of riparian restoration investment strategies to pursue ecosystem service benefits. The model is meant to be adaptable to generic restoration planning applications, with the Middle Rio Grande riparian corridor in Albuquerque, New Mexico, U.S.A. presented here as the illustrating case. Model inputs include ecosystem service values from an original choice experiment, values from regional benefit transfer studies, and information from land managers.The model includes three control variable modules: forest management, river restoration, and recreation infrastructure. Investment influences these modules, which in turn affect ecosystem service flows for the region. The model is exercised to compare a “No-Action” alternative with “Optimal Benefit-Cost Ratio” restoration funding. An extended sensitivity analysis explores a range of both physical and economic assumptions. The analysis has two major outcomes. The first is that directed restoration funding yields significant gains as compared with No-Action for all scenarios tested. The second major finding is that although optimized benefit-cost ratios are above unity for all “states of the world” tested, the ratio itself and funding patterns varied widely. These sensitivities underscore the need for a transparent adaptive management decision process supported by tools aimed not at deterministic prediction, but rather at structuring dialogue and inquiry into issues that defy simple intuition.     

Dynamic multi-compartmental modelling of metal bioaccumulation in fish: Identifiability implications

Metal bioaccumulation in fish is influenced by factors specific to the chemical and environmental conditions, the exposure route and the species. For a better understanding of the main interactions among these factors, models are needed to capture the basic principles driving the dynamics of metal bioaccumulation in fish, taking into account different exposure routes and the distribution among representative organs. There is a significant amount of data in the literature concerning metal bioaccumulation experiments in different species of fish. Quantitative information about rate constants of the processes involved in bioaccumulation (diffusion, uptake and elimination) can be obtained from these data by means of dynamic models, that, once validated, can be used for predictive purposes. In this work, a compartmental model structure is developed aiming, in the first instance, to obtain the maximum amount of information from published experimental data. Once calibrated, the model can be further used to predict metal bioaccumulation under different scenarios. The model structure is able to reproduce the experimental behaviour for those species-metal pairs tested and, in addition, is demonstrated to be robust and identifiable. Then, the complete set of parameters can be estimated uniquely, for a specific species-metal pair by using concentration measures in a reduced number of organs. In this way, the optimal parameter sets obtained for different pairs can be compared, and the parameter specificity with respect to the metal or the species can be investigated.     

Dynamic modelling and stabilization of a new configuration of two-wheeled machines

This paper presents a novel design of two-wheeled vehicles and an associated stabilization approach. The proposed design provides the vehicle with more flexibility in terms of increased degrees of freedom which enable the vehicle to enlarge its working space. The additional translational degree of freedom (DOF), offered by the linear actuator, assists an attached payload to reach different levels of height as and when required. The model of the system mimics the scenario of the double inverted pendulum on a moving base, with the added DOF. Lagrangian dynamic formulation is used to derive the system dynamics. Joints frictions based on the Coulomb friction model are considered so as to retain nonlinear characteristics of the system. A PD-PID robust control approach is derived for the stabilization of the system. An investigation of the impact of damping associated with joints on the stability of the system is carried out. Simulation results validating the model and the control approach are presented and discussed.     

Dynamic influent pollutant disturbance scenario generation using a phenomenological modelling approach

Activated Sludge Models are widely used for simulation-based evaluation of wastewater treatment plant (WWTP) performance. However, due to the high workload and cost of a measuring campaign on a full-scale WWTP, many simulation studies suffer from lack of sufficiently long influent flow rate and concentration time series representing realistic wastewater influent dynamics. In this paper, a simple phenomenological modelling approach is proposed as an alternative to generate dynamic influent pollutant disturbance scenarios. The presented set of models is constructed following the principles of parsimony (limiting the number of parameters as much as possible), transparency (using parameters with physical meaning where possible) and flexibility (easily extendable to other applications where long dynamic influent time series are needed). The proposed approach is sub-divided in four main model blocks: 1) model block for flow rate generation, 2) model block for pollutants generation (carbon, nitrogen and phosphorus), 3) model block for temperature generation and 4) model block for transport of water and pollutants. The paper is illustrated with the results obtained during the development of the dynamic influent of the Benchmark Simulation Model no. 2 (BSM2). The series of simulations show that it is possible to generate a dry weather influent describing diurnal flow rate dynamics (low rate at night, high rate during day time), weekend effects (with different flow rate during weekends, compared to weekdays), holiday effects (where the wastewater production is assumed to be different for a number of weeks) and seasonal effects (with variations in the infiltration and thus also the flow rate to the WWTP). In addition, the dry weather model can be extended with a rain and storm weather generator, where the proposed phenomenological model can also mimic the “first flush” effect from the sewer network and the influent dilution phenomena that are typically observed at full-scale WWTPs following a rain event. Finally, the extension of the sewer system can be incorporated in the influent dynamics as well: the larger the simulated sewer network, the smoother the simulated diurnal flow rate and concentration variations. In the discussion, it is pointed out how the proposed phenomenological models can be expanded to other applications, for example to represent heavy metal or organic micro-pollutant loads entering the treatment plant.     

Probabilistic counter updates for predictor hysteresis and bias

Hardware predictor designers have incorporated hysteresis and/or bias to achieve desired behavior by increasing the number of bits per counter. Some resulting proposed predictor designs are currently impractical because their counter tables are too large. We describe a method for dramatically reducing the amount of storage required for a predictor's counter table with minimal impact on prediction accuracy. Probabilistic updates to counter state are implemented using a hardware pseudo-random number generator to increment or decrement counters a fraction of the time, meaning fewer counter bits are required. We demonstrate the effectiveness of probabilistic updates in the context of Fields et al.'s critical path predictor, which employs a biased 6-bit counter. Averaged across the SPEC CINT2000 benchmarks, our 2-bit and 3-bit probabilistic counters closely approximate a 6-bit deterministic one (achieving speedups of 7.75% and 7.91% compared to 7.94%) when used for criticality-based scheduling in a clustered machine. Performance degrades gracefully, enabling even a 1-bit probabilistic counter to outperform the best 3-bit deterministic counter we found.     

The neural dynamics for hysteresis in visual perception

The hysteresis in the perception has been observed in many perceptual experiments, but little is known about the underlying dynamical mechanism. We simulate a visual discrimination task, as an example of hysteresis in the perception, using a spiking neuron network and the corresponding slow dynamic system. The hysteresis in visual perception has been reproduced in our simulation. We find that hysteresis is influenced by the change speed of the external stimuli and the excitatory recurrent interaction inside the selective neuron pool. The slow dynamic system reveals the dynamical mechanism underlying the hysteresis: emerging from the lag between the response of neural system and the fast change external stimuli when the slow dynamic system has a single steady state; emerging from the multiple steady states regardless of the change speed of the external stimuli. In particularly, the multiplicity of the steady state of the slow dynamic system comes from the codimension three swallowtail catastrophe which exhibits two interacting cusp catastrophes.     

Semilinear Duhem model for rate-independent and rate-dependent hysteresis

The classical Duhem model provides a finite-dimensional differential model of hysteresis. In this paper, we consider rate-independent and rate-dependent semilinear Duhem models with provable properties. The vector field is given by the product of a function of the input rate and linear dynamics. If the input rate function is positively homogeneous, then the resulting input-output map of the model is rate independent, yielding persistent nontrivial input-output closed curve (that is, hysteresis) at arbitrarily low input frequency. If the input rate function is not positively homogeneous, the input-output map is rate dependent and can be approximated by a rate-independent model for low frequency inputs. Sufficient conditions for convergence to a limiting input-output map are developed for rate-independent and rate-dependent models. Finally, the reversal behavior and orientation of the rate-independent model are discussed.     

磁流变阻尼器磁滞补偿控制器设计

针对磁流变阻尼器内部铁磁材料所固有的磁滞非线性,根据反馈磁感应强度的磁滞补偿控制方法,设计了磁滞补偿控制器。以STM32F103ZET6单片机为控制核心,通过设计霍尔传感器的调理电路、脉宽调制(PWM)信号滤波电路、电压放大电路,以及实时化的比例—积分—微分(PID)控制算法和人机交互界面,实现了磁流变阻尼器磁滞补偿控制器的功能。通过实验验证了控制器在窗函数、阶梯函数和半正弦函数等三种不同输入电流条件下的磁滞补偿控制效果。实验结果表明:相比无磁滞补偿控制,在磁滞补偿控制器的作用下,磁流变阻尼器的阻尼通道磁场能较好地跟踪控制电流,验证了磁滞补偿控制器的有效性。