Conventional Dynamic Model Research Articles

A dynamic nonlinear subgrid-scale stress model

In this paper, a dynamic subgrid scale (SGS) stress model based on Speziale’s quadratic nonlinear constitutive relation [C. G. Speziale, J. Fluid Mech. 178, 459 (1987); T. B. Gatski and C. G. Speziale, J. Fluid Mech. 254, 59 (1993)] is proposed, which includes the conventional dynamic SGS model as its first-order approximation. The closure method utilizes both the symmetric and antisymmetric parts of the resolved velocity gradient, and allows for a nonlinear anisotropic representation of the SGS stress tensor. Unlike the conventional Smagorinsky type modeling approaches, the proposed model does not require an alignment between the SGS stress tensor and the resolved strain rate tensor. It exhibits significant flexibility in self-calibration of the model coefficients, and local stability without the need for plane averaging to avoid excessive backscatter of SGS turbulence kinetic energy and potential modeling singularity problems. It also allows for variable tensorial geometric relations between the SGS stress and its constituent terms, and reflects both forward and backward scatters of SGS turbulence kinetic energy between the filtered and subgrid scales of motions. Turbulent Couette flow for Reynolds numbers (based on channel height and one half the velocity difference between the two plates) of 2600 and 4762 was used in numerical simulations to validate the proposed approach.

A 3D Generic Inverse Dynamic Method using Wrench Notation and Quaternion Algebra

In the literature, conventional 3D inverse dynamic models are limited in three aspects related to inverse dynamic notation, body segment parameters and kinematic formalism. First, conventional notation yields separate computations of the forces and moments with successive coordinate system transformations. Secondly, the way conventional body segment parameters are defined is based on the assumption that the inertia tensor is principal and the centre of mass is located between the proximal and distal ends. Thirdly, the conventional kinematic formalism uses Euler or Cardanic angles that are sequence-dependent and suffer from singularities. In order to overcome these limitations, this paper presents a new generic method for inverse dynamics. This generic method is based on wrench notation for inverse dynamics, a general definition of body segment parameters and quaternion algebra for the kinematic formalism.

AN EFFICIENT SOLUTION SCHEME FOR APPLYING THE INTEGRAL-TYPE DYNAMIC LOCALIZATION SUBGRID-SCALE MODEL IN TURBULENCE WITH HOMOGENEOUS DIRECTIONS

The conventional integral-type dynamic localization subgrid-scale stress model is a Fredholm integral equation of the second kind. This model is mathematically consistent, but it has not been widely used in the large-eddy simulation community due to the relatively high computational cost of solving the Fredholm integral equation using an iterative scheme. In this article, a direct solution scheme based on a discrete Gaussian filter is developed to solve the integral system for turbulent flow with homogeneous dimensions. The proposed direct solution scheme is computationally efficient and makes the integral-type dynamic localization subgrid-scale stress model affordable. Turbulent Couette flows with Reynolds numbers of 2,600 and 4,762 are used in numerical simulations to validate the proposed approach.

PREDICTING RUNOFF FROM A YARD WASTE WINDROW COMPOSTING PAD

Composting is utilized increasingly as an aerobic treatment alternative to landfilling for bioconverting organicwastes such as municipal biosolids and yard wastes into soil amendments or landscaping materials. However, little informationis available to estimate composting operation runoff to corresponding design rainfall events. The objective of this workwas to evaluate dynamic versions of the simple . index and NRCS curve number runoff models currently used in agriculturalor urban stormwater management for predicting runoff from windrow composting operations. A 1.4 ha (approximately 48 300 m) windrow pad was constructed by placing 25 mm crusher-run aggregate on a tightly compacted Cecil sandy clay loam.The pad was sloped (<1% on the 300 m axis and 0% on the 48 m axis) and bermed to direct all runoff to a 0.2 ha 2 m deepcatchment pond with less than 3.175 mm/day seepage constructed with a regular trapezoidal shape, thus enabling astraightforward relationship between pond depth and volume. Precipitation, pond stage, and compost amount were monitoreddaily in accordance with environmental permit requirements. A dynamic NRCS curve number daily runoff model, in whichthe precipitation was adjusted with pad fraction covered and 7-day antecedent moisture, resulted in a validation R2 of 0.56and had a modeled vs. observed slope of 0.93 when applied to the validation data set. Applied to monthly data, the dynamiccurve number approach, which adjusted precipitation with average fraction covered with compost for the month, gave avalidation R2 of 0.75 and a validation slope of 0.76. Based on daily and monthly results, the dynamic NRCS-CN models withprecipitation adjustments yielded the best validation results. The more conventional dynamic NRCS-CN modeling approachwhere the curve number was modified performed nearly as well with daily and monthly runoff prediction. Theprecipitation-modified NRCS-CN equation tended to overpredict daily runoff at low precipitation rates, whereas theCN-modified version of the daily NRCS-CN equation was more consistent across the observed precipitation range. Bothdynamic NRCS-CN equations tended to overpredict monthly runoff.

Persistence of Employment Fluctuations: A Model of Recurring Job Loss

Standard models of employment fluctuations cannot reconcile the unemployment rate's remarkable persistence with the high job-finding rates found in worker flows data. A matching model emphasizing high hazard rates among newly formed firm-worker matches can resolve this shortcoming. In the model, matches are experience goods; consequently, newly employed workers face higher hazard rates. Following a job loss, workers may experience several short-lived jobs before finding stable employment. At an aggregate level, an initial burst of job loss precipitates a steady flow of recurring job loss. A simulation shows that this recurring job loss can account for the fact that the unemployment rate remains elevated for as much as 4 or 5 years following an initial jump. Intuitively, the labour market frictions associated with the difficult and time-consuming process of matching unemployed workers with appropriate jobs represent an appealing way to enhance conventional dynamic general equilibrium models of economic fluctuations that generally exhibit very little internal propagation of business cycle shocks.1 Nevertheless, although conventional matching models, such as the canonical Mortensen and Pissarides (1994) model, successfully explain many other important features of the labour market, they fail to explain the high degree of persistence observed in the U.S. unemployment rate. The primary reason for this failure is that data on labour market flows show that unemployed workers actually find jobs quite quickly. Therefore, following a shock that triggers a burst of job loss, the high job-finding rate implies that the unemployment rate in these models returns quite rapidly back toward its average level. This represents a significant obstacle to the notion that frictions in the labour market account for much of the propagation of business cycle shocks. This paper asserts that existing matching models fail to capture an important feature of the labour market that can reconcile the dramatic persistence of the unemployment rate with the evidence of high job-finding rates. Specifically, although unemployed workers find jobs quickly, the newly found jobs often last only a short time. After an initial job loss, a worker may experience several short-lived jobs before settling into more stable employment. This recurring job loss slows the pace at which the unemployment rate returns to its normal level following an adverse shock.

New Dynamic Modeling of Flexible-Link Robots

This paper shows that the conventional Lagrangian modeling of flexible-link robots does not fully incorporate the bending mechanism of flexible links. The conventional link deflection model allows free link elongation in addition to link deflection; the link elongation increases as link deflection increases. The link elongation, however, causes certain degrees of modeling inaccuracy in association with the rotational motion of the links. Therefore, this paper proposes a new link deflection model, compatible with the bending mechanism of flexible links. Then a new nonlinear dynamic model is derived based on the new link deflection model, fixing the modeling inaccuracy of the conventional dynamic model.

Fuzzy logic approach for description of meteorological impacts on urban air pollution species: a Hong Kong case study

An alternative approach to the conventional dynamic and photochemical models is presented to forecast urban air pollutants operationally. It is well known that there are some practical difficulties, which prevent the necessary progress in the development of these models as a forecasting tool. A fuzzy logic based method has been developed here to study the impact of meteorological factors on the evolution of air pollutant levels and to describe them quantitatively. This method meets all requirements but needs substantial amount of observational data. The developed model is based on simulation of diurnal cycles of principal meteorological variables (wind speed and direction, solar irradiance and air temperature) and the corresponding diurnal patterns of various air pollutants (O 3, NO 2, NO, NO y ). In addition, the spatial patterns of these parameters are also studied. Both temporal and spatial parameter distributions have been considered in order to investigate impacts of meteorological factors and they are incorporated into the models as state vectors in the multidimensional space. Here we suggest that most of the weather and air pollution phenomena could be simulated by sequences of its conservation inside some fuzzy sets and the transition from one fuzzy set to another. Therefore, the important key point here is the development of the transition rules.

Aggressive Longitudinal Aircraft Trajectory Tracking Using Nonlinear Control

Flight-control system designs are complicated if the aircraft dynamics are nonlinear and nonminimum phase. The nonminimum phase property can result from the choice of output vector and coupling between the moment generating actuators and the aerodynamic forces on the aircraft. In this paper we study a flight-control problem for a conventional aircraft longitudinal dynamic model that explicitly includes the coupling between the moment generating actuators and the aerodynamic forces. In particular, we study the execution of a maneuver for which the aircraft is intended to track a given motion in a vertical plane. We formulate the problem as a nonlinear tracking control problem. Controllers are developed for an aggressive maneuver that requires the use of a two-degrees-of-freedom controller design. We demonstrate the value of this control architecture in order to achieve aggressive maneuvering with good tracking performance. Our approach throughout is to make use of nonlinear control theory. Our analysis is complicated by the nonminimum phase characteristics of the flight model.

Influence of environment fluctuations on incoherent neutron scattering functions.

In extending the conventional dynamic models, we consider a simple model to account for the environment fluctuations of particle atoms in a protein system and derive the elastic incoherent structure factor (EISF) and the incoherent scattering correlation function C(Q,t) for both the jump dynamics between sites with fluctuating site interspacing and for the diffusion inside a fluctuating sphere. We find that the EISF of the system (or the normalized elastic intensity) is equal to that in the absence of fluctuations averaged over the distribution of site interspacing or sphere radius a. The scattering correlation function is C(Q,t)= Sigma(n)<e(-lambda(n)(a)t)> psi(t), where the average is taken over the Q-dependent effective distribution of relaxation rates lambda(n)(a), and psi(t) is the correlation function of the length a. When psi(t)=1, the relaxation of C(Q,t) is exponential for the jump dynamics between sites [since lambda(n)(a) is independent of a] while it is nonexponential for diffusion inside a sphere.

Prediction analysis of solid waste generation based on grey fuzzy dynamic modeling

Abstract Successful planning of a solid waste management system depends critically on the prediction accuracy of solid waste generation. But the prediction condition of generation trend in many developing countries is quite different from those in developed countries. The lack of sampling and analysis in many developing countries due to insufficient budget and unavailable management task force has resulted in a situation where the historical record of solid waste generation and composition can never be completed in the long term. To effectively handle these problems with only limited samples and fulfil the prediction analysis of solid waste generation with reasonable accuracy, a special analytical technique must be developed and applied before the subsequent system planning for urban solid waste management is carried out. This study presents a new theory — grey fuzzy dynamic modeling — for the prediction of solid waste generation in the urban area based on a set of limited samples. The practical implementation has been accessed by a case study in the city of Tainan in Taiwan. It shows that such a new forecasting technique may achieve better prediction accuracy than those of the conventional grey dynamic model, least-squares regression method, and the fuzzy goal regression technique.

Overall Evolution of Realistic Gamma-Ray Burst Remnant and Its Afterglow

Conventional dynamic model of gamma-ray burst remnants is found to be incorrect for adiabatic blastwaves during the non-relativistic phase. A new model is derived, which is shown to be correct for both radiative and adiabatic blastwaves during both ultra-relativistic and non-relativistic phases. Our model also takes the evolution of the radiative efficiency into account. The importance of the transition from the ultra-relativistic phase to the non-relativistic phase is stressed.

From safety analysis to software requirements

Software for safety critical systems must deal with the hazards identified by safety analysis. This paper investigates, how the results of one safety analysis technique, fault trees, are interpreted as software safety requirements to be used in the program design process. We propose that fault tree analysis and program development use the same system model. This model is formalized in a real-time, interval logic, based on a conventional dynamic systems model with state evolving over time. Fault trees are interpreted as temporal formulas, and it is shown how such formulas can be used for deriving safety requirements for software components.

Hardness Results for Dynamic Problems by Extensions of Fredman and Saks’ Chronogram Method

We introduce new models for dynamic computation based on the cell probe model of Fredman and Yao. We give these models access to nondeterministic queries or the right answer +-1 as an oracle. We prove that for the dynamic partial sum problem, these new powers do not help, the problem retains its lower bound of Omega(log n/log log n). &lt;br /&gt;From these results we easily derive a large number of lower bounds of order Omega(log n/log log n) for conventional dynamic models like the random access machine. We prove lower bounds for dynamic algorithms for reachability in directed graphs, planarity testing, planar point location, incremental parsing, fundamental data structure problems like maintaining the majority of the prefixes of a string of bits and range queries. We characterise the complexity of maintaining the value of any symmetric function on the prefixes of a bit string.

From Wagner-Whitin's dynamic lot size model towards zero inventory

This article discusses the interface between zero inventory (ZI) and the dynamic lot size problem. The conventional Wagner-Whitin dynamic lot size model shows a good ffi computational e ciency when obtaining the optimal lot-sizing policy, but it ignores reduction of lot size and total cost. The 'zero inventory' philosophy strives for the goals of zero inventory at the end of each period and minimum total cost. The setup cost is fixed in the Wagner-Whitin model, but is considered as a parameter in zero inventory (ZI) philosophy: in general, the setup cost is treated as a policy variable in ZI. Zangwill examined the case of stationary setup cost reduction, but did not discuss the case of nonstationary setup cost reduction. This paper presents a new expression for total setup cost and total holding cost for the Wagner-Whitin model. By adopting this new expression, we obtain a sufficient and necessary con dition such that ZI is the optimal policy in the Wagner-Whitin model. Regardless of whether the setup cost reduction is stationary or nonstationary, the total setup cost reduction over all periods increases when the amount of setup cost reduction increases. This result suggests that the optimal policy for the Wagner-Whitin model is close to ZI. Most presentations of ZI have been descriptive with very few mathematical models. This paper seeks to demonstrate by a mathematical approach that reducing the setup cost can make the Wagner-Whitin model approach ZI.

Coupling Model of Vertical and Lateral Vehicle/Track Interactions

SUMMARY A new dynamic model of vehicle/track interaction is presented. The model considers the vehicle and the track as a whole system and couples the vertical interaction with the lateral interaction. The vehicle subsystem is modeled as a multi-body system with 37 degrees of freedom, which runs on the track with a constant velocity. The track substructure is modeled as a discretely supported system of elastic beams representing the rails, sleepers and ballasts. The normal contact forces between wheels and rails are described by Hertzian nonlinear elastic contact theory and the tangential wheel/ rail forces are decided by the creep theory. Numerical results are compared with those of conventional dynamic models of railway vehicles. Applications of the coupling model to the investigation of safety limits against derailment due to the track twist and the combined alignment and cross-level irregularities are reported at the end of the paper.

Dynamic Modelling of Traffic Flow on the A1 Freeway In Paris

Conventional dynamic macroscopic models for traffic flow on freeways and their behaviours with respect to the Al freeway are investigated. An extension of the models for urban freeways with changing number of lanes and with many on- and off-ramps is discussed. Additional terms of speed equation regarding both the high ramp volume and the lane drop are presented. The extended model of traffic on the A1 freeway is developed, which describes traffic phenomena of the freeway with a fair accuracy and a considerable robustness.

Urban systems dynamics and cellular automata: Fractal structures between order and chaos

Two-dimensional cellular automata with rules defined on a large neighbourhood are used to simulate the evolution of urban land-use patterns. Both the simulated urban areas and actual cities are shown to be fractal objects characterized by very similar dimensions. But the fractality (and hence realism) of the cellular cities appears only when the degree of stochasticity is within a relatively narrow band; otherwise the city is too uniform or too random. The same phenomenon appears in a conventional dynamic model of the evolution of a system of cities: the size distribution of urban centres assumes a fractal form (one observed in many real systems) only with a ‘fine tuning’ of the relevant parameters. Otherwise the system either evolves toward a uniform state or collapses to a single large centre. The tendency to observe such poised behaviour in both the cellular and the urban system models for realistic calibrations may be a manifestation of a phase-transition phenomenon observed in simpler deterministic cellular automata, and may represent a requirement for evolvability in real systems.

A Network Model for Dynamic Traffic Assignment

Models for predicting traffic congestion over time on a road network have been formulated as non-linear optimization problems. In this paper, we construct a new dynamic flow model represented as an optimization problem on a time-space network. In this model, there is a one-to-one correspondence between any directed path on the time-space network and a travel actually taken by a user of the road network. This is an advantage over conventional dynamic flow models in which a travel by a user may correspond to multiple paths in the underlying time-space network. The proposed network model involves arc capacity constraints that depend on the amount of flows of relevant arcs. Since those capacity constraints prevent this model from being treated as network flow problem, we adopt a penalty function techinique to transfer them into the objective function, thereby obtaining a standard non-linear minimum cost flow problem. We report some numerical results to show the validity of the proposed model.

A dataflow model based on a vector queueing scheme

The average overhead required for producing a scalar result may be reduced by vectorizing dataflow computations. This reduction may lead to eliminating or reducing pipeline starvation during periods characterized by low degrees of parallelism. A dataflow model based on a vector queueing scheme is presented. The model supports parallelism between different activations of vector nodes, and requires less overhead than conventional dynamic models.

A rule-based ecological model for the management of an estuarine lake

It is often difficult to build conventional dynamic models for an ecological system because the relationships between the abiotic and biotic components of the system are understood only in a rough, qualitative rather than a detailed, quantitative sense. This paper shows how a rule-based model can be formulated and used in this type of situation. The purpose of the model is to assist managers of a large, shallow coastal lake connected to the sea by a narrow estuary. Fluctuations in the salinity of the lake have a marked effect on the biotic components and managers are interested in the likely effects of alternative strategies for ameliorating the salinity. The paper shows how available information lends itself to a representation in terms of rules that indicate how important biotic components change (on a crude scale of 1 to 5) depending on the prior state of the system and current water conditions. The model was incomplete at the time of writing, but at least one important (and unexpected) result has already emerged: the abundance of underwater plant biomass is sensitive to the rate of change of salinity rather than the salinity level per se. Several consequences of this type of modeling are noted: it draws on the experience of both scientists and non-scientists, provides a consistent, logical basis for discussion, improves communication between field biologists and managers, lends itself to an adaptive approach, and can provide assessments of the quality of each simulation. It is suggested that this approach is pertinent whenever the effects of abiotic events dominate mutual interactions between the biotic components of a system.