Modelling and system identification of active magnetic bearing systems

Active magnetic bearing (AMB) systems have recently attracted much attention in the rotating machinery industry due to their advantages over traditional bearings such as fluid film and rolling element bearings. The AMB control system must provide robust performance over a wide range of machine operating conditions and over the machine lifetime in order to make this technology commercially viable. An accurate plant model for AMB systems is essential for the aggressive design of control systems. In this paper, we propose two approaches to obtain accurate AMB plant models for the purpose of control design: physical modelling and system identification. The former derives a model based upon the underlying physical principles. The latter uses input – output data without explicitly resorting to physical principles. For each problem, a brief summary of the theoretical derivation and assumptions is given. Experimental results based on data collected from an AMB test facility at the United Technologies Research Center provide a vehicle for a comparison of the two approaches.     

Modelling and prediction of machining errors using ARMAX and NARMAX structures

Forecasting compensatory control, which was first proposed by Wu [ASME J. Eng. Ind. 99 (1977) 708], has been successfully employed to improve the accuracy of workpieces in various machining operations. This low-cost approach is based on on-line stochastic modelling and error compensation. The degree of error improvement depends very much on the accuracy of the modelling technique, which can only be performed on-line in a real-time recursive manner. In this study, the effect of the control input (i.e. the cutting force) is considered in the development of the error models, and the formulation of recursive exogenous autoregressive moving average (ARMAX) models becomes necessary. The nonlinear ARMAX or NARMAX model is also used to represent this nonlinear process. ARMAX and NARMAX models of different autoregressive (AR), moving average (MA) and exogenous (X) orders are proposed and their identifications are based on the recursive extended least square (RELS) method and the neural network (NN) method, respectively. An analysis of the computational results has confirmed that the NARMAX model and the NN method are superior to the ARMAX model and the RELS method in forecasting future machining errors, as indicated by its higher combined coefficient of efficiency.     

Computational approaches to parameter estimation and model selection in immunology

One of the significant challenges in biomathematics (and other areas of science) is to formulate meaningful mathematical models. Our problem is to decide on a parametrized model which is, in some sense, most likely to represent the information in a set of observed data. In this paper, we illustrate the computational implementation of an information-theoretic approach (associated with a maximum likelihood treatment) to modelling in immunology.The approach is illustrated by modelling LCMV infection using a family of models based on systems of ordinary differential and delay differential equations. The models (which use parameters that have a scientific interpretation) are chosen to fit data arising from experimental studies of virus-cytotoxic T lymphocyte kinetics; the parametrized models that result are arranged in a hierarchy by the computation of Akaike indices. The practical illustration is used to convey more general insight. Because the mathematical equations that comprise the models are solved numerically, the accuracy in the computation has a bearing on the outcome, and we address this and other practical details in our discussion.     

Active magnetic damper in a power transmission system

In rotor dynamics, the bearing characteristics exerts a decisive influence on dynamics of the rotating shaft. The research and application experience have led to active magnetic bearings (AMBs), which allow for unique applications in rotating systems. The paper presents the investigations concerning optimization of the magnetic bearing construction. An active magnetic bearing operates as a radial, auxiliary damper, which cooperates with the long, flexible shaft line (aircraft industry applications) and modifies its dynamic properties. In the developed concept of AMBs for aviation purposes, a necessity of increasing its bearing load capacity and damping has occurred. The second important criterion is a weight reduction. This advanced problem leads to specific requirements on the design and materials for the AMB. To achieve these goals, some simulations have been performed. The experimental results are presented as well.     

Analytical modeling of active magnetic bearing geometry

The aim of this paper is to present a new graphical approach to the shape design of the active magnetic bearing (AMB) stator. The AMB is a tool to levitate the rotor without contact. The standard design method uses a computer-aided design (CAD) software in the modeling process. Therefore the designed AMB shape consists of graphical primitives like lines and arcs with fixed properties. For the advanced interdisciplinary analysis of the AMB construction the shape generation and modifications ought to be done automatically. The proposed method is based on mathematical analysis and representation of the AMB stator by curves. Second and third order Bézier curves given in polynomial and rational form are compared to the circle and arc based arcs. The fitting quality is considered for the selection of the appropriate arc representation. The obtained shapes are ready to be used in the magnetic field analysis and optimization procedures to find an optimal form of the AMB construction. The author’s experience in modeling and vector graphics was a motivation to look at the AMB construction from mathematical and programming point of view. The AMB components are modeled with parametric curves under constraints defined by the AMB static and dynamic properties. Such a described 2D or 3D model can be generated automatically in a programming way for a wide range of AMB configurations in further research. Selected configurations are presented to show features of the proposed method and realized algorithm. The selected features of the proposed solution as well as feedback from industry are discussed.     

Stochastic modelling of reservoir operations

The nature of hydrologic parameters in reservoir management models is uncertain. In mathematical programming models the uncertainties are dealt with either indirectly (sensitivity analysis of a deterministic model) or directly by applying a chance-constrained type of formulation or some of the stochastic programming techniques (LP and DP based models). Various approaches are reviewed in the paper. Moran's theory of storage is an alternative stochastic modelling approach to mathematical programming techniques. The basis of the approach and its application is presented. Reliability programming is a stochastic technique based on the chance-constrained approach, where the reliabilities of the chance constraints are considered as extra decision variables in the model. The problem of random event treatment in the reservoir management model formulation using reliability programming is addressed in this paper.     

Atomistic-continuum multiscale modelling of magnetisation dynamics at non-zero temperature

In this article, a few problems related to multiscale modelling of magnetic materials at finite temperatures and possible ways of solving these problems are discussed. The discussion is mainly centred around two established multiscale concepts: the partitioned domain and the upscaling-based methodologies. The major challenge for both multiscale methods is to capture the correct value of magnetisation length accurately, which is affected by a random temperature-dependent force. Moreover, general limitations of these multiscale techniques in application to spin systems are discussed.     

Numerical simulation of bubble growth in a supersaturated solution

In this paper, a Volume of Fluid (VOF) based approach to simulate the growth of a pre-existing bubble in a supersaturated solution is developed and implemented in OpenFOAM^Ⓡ. The model incorporates the Compressive Continuous Species Transfer approach to describe the transport of dissolved gas and surface tension is treated using the Sharp Surface Force method. The driving force for bubble growth is defined using Fick’s 1^st law and a Sherwood number based correlation. The source terms for the governing equations are implemented by extending the work by Hardt and Wondra, J. Comp. Phys. 227 (2008) 5871–5895. The predictions of the proposed solver is compared against theoretical models for bubble growth in supersaturated solutions. The effect of spurious currents, which are generated while modelling surface tension, on bubble growth is also investigated. The proposed approach is used to model the growth of a rising bubble in the supersaturated solution.     

Simulation modelling of emergency medical services

This paper deals with the problem of application of simulation modelling in Emergency Medical Services (EMS) systems. Approaches to modelling of EMS are discussed and a review of EMS simulation models is presented. A simple simulation model of a rural EMS system in Poland is described. Some results of the initial application of the model are presented. Possibilities of simulation modelling for solving EMS managerial and planning problems are briefly analysed.     

Choice of modelling technique for evaluating health care interventions

Economic evaluation, such as cost effectiveness analysis, provides a method for comparing healthcare interventions. These evaluations often use modelling techniques such as decision trees, Markov processes and discrete event simulations (DES). With the aid of examples from coronary heart disease, the use of these techniques in different health care situations is discussed. Guidelines for the choice of modelling technique are developed according to the characteristics of the health care intervention.The choice of modelling technique is shown to depend on the acceptance of the modelling technique, model ‘error’, model appropriateness, dimensionality and ease and speed of model development. Generally decision trees are suitable for acute interventions but they cannot model recursion and Markov models are suitable for simple chronic interventions. It is further recommended that population based models be used in order to provide health care outcomes for the likely cost, health benefits and cost effectiveness of the intervention. The population approach will complicate the construction of the model. DES will allow the modeller to construct more complex, dynamic and accurate systems but these may involve a corresponding increase in development time and expense. The modeller will need to make a judgement on the necessary complexity of the model in terms of interaction of individuals and model size and whether queuing for resources, resource constraints or the interactions between individuals are significant issues in the health care system.     

Shaft-hub press fit subjected to bending couples: Analytical evaluation of the shaft-hub detachment couple

A mathematical modelling of a shaft-hub press-fit subjected to bending couples applied to the shaft extremities is developed, and the value of the bending couple inducing an undesired shaft-hub incipient detachment is analytically determined. The shaft-hub contact is modelled in terms of two elastic Timoshenko beams connected by a distributed elastic spring, whose stiffness is analytically evaluated. Two models of the distributed spring are considered. The first model expresses the combined deformability of both the shaft and the hub cross sections. The second model accounts for the stiffening effect exerted by the shaft portion protruding from the hub on the adjacent shaft part that is in contact with the hub, and, consequently, it assumes only a rigid body motion of the shaft cross section, thus neglecting its deformability.Based upon this beam-like model, the bending couple producing the incipient detachment between the shaft and the hub is theoretically determined in term of the shaft-hub geometry, of the initial shaft-hub interference, and of the elastic constants. Comparisons with selected Finite Element (FE) forecasts indicate that the first modelling produces an incipient detachment couple that appreciably overrates the FE forecasts, whereas the second modelling lowers the error down to technically acceptable predictions.     

Modelling class hierarchies in the fuzzy object-oriented data model

In this paper we describe a fuzzy logic based approach to modelling uncertainty in class hierarchies. It is shown that the traditional view of class hierarchies is subsumed in this model as a special case. The problem of multiple inheritance in class hierarchies is discussed and analyzed. The membership value derivations in the inheritance hierarchy reflects the degree of fuzziness existing in the data values and the semantics of the situation being modelled. Thus a more realistic modelling of the universe of discourse is possible through this approach. This model is compatible with existing object-oriented data models.     

Modelling Intra-City Time-Dependent Travel Speeds for Vehicle Scheduling Problems

Many research papers have presented mathematical models for vehicle scheduling. Several of these models have been embedded in commercial decision support systems for intra-city vehicle scheduling for launderies, grocery stores, banks, express mail customers, etc. Virtually all of these models ignore the important issue of time-dependent travel speeds for intra-city travel. Travel speeds (and times) in nearly all metropolitan areas change drastically during the day because of congestion in certain parts of the city road network. The assumption of constant (time-independent) travel speeds seriously affects the usefulness of these models. This is particularly true when time windows (earliest and latest stop time constraints) and other scheduling issues are important. This research proposes a parsimonious model for time-dependent travel speeds and several approaches for estimating the parameters for this model. An example is presented to illustrate the proposed modelling approach. The issue of developing algorithms to find near-optimal vehicle schedules with time-dependent travel speeds is also discussed. The modelling approach presented in this paper has been implemented in a commercial courier vehicle scheduling system and was judged to be ‘very useful’ by users in a number of different metropolitan areas in the United States.     

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This article includes a review of established methods of inverse simulation, giving some emphasis on iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach that is based on feedback principles. This feedback method is suitable for a wide range of linear and non-linear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model, and in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus, the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on non-linear and multi-input multi-output models.     

Towards modelling skeletal muscle growth and adaptation

Despite an increasing interest in modelling skeletal muscles adaptation, models that address the phenomena within a continuum-mechanical framework using muscle-specific material models are rare in literature. This work focuses on modelling one form of skeletal musle adaptation, namely sarcomerogenesis. Sarcomerogenesis occurs when a given stretch is sustained over a period of time and the number of basic contractile units, which are the sarcomeres, increase. To model sarcomerogenesis within a continuum-mechanical setting, the growth framework based on a multiplicative split of the total deformation gradient is employed. An evolution equation that describes sarcomerogenesis is used and incorporated in a transversally isotropic material model that accounts for a skeletal muscle's active force production capabilities. The material tangent modulus is derived and implemented within the finite-element analysis software. Using this model, one sees that increased number of sarcomeres results in a decreased force response of the muscle tissue over time. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On the modelling of heat exchangers and heat exchanger network dynamics using bond graphs

ABSTRACT

Heat exchanger networks are important systems in most thermal engineering systems and are found in applications ranging from power plants and the process industry to domestic heating. Achieving cost-effective design of heat exchanger networks relies heavily on mathematical modelling and simulation-based design. Today, stationary design calculations are carried out for all new designs, but for some special applications, the transient response of complete networks has been researched. However, simulating large heat exchanger networks poses challenges due to computational speed and stiff initial value problems when flow equations are cast in differential algebraic form. In this article, a systems approach to heat exchanger and heat exchanger network modelling is suggested. The modelling approach aims at reducing the cost of system model development by producing modular and interchangeable models. The approach also aims at improving the capability for large and complex network simulation by suggesting an explicit formulation of the network flow problem.     

Semi-dynamic modelling of heterogeneous land combat

We propose a semi-dynamic approach to tactical level land combat modelling from the attacker's viewpoint. Our approach decomposes a battle between heterogeneous forces into stages and mini battles. For each mini battle in a stage, we use three models: a mathematical programming model for optimizing force allocations, a Lanchester simulation model for predicting whether or not the stage targets are reached under the allocations, and a model for weapon effectiveness update from one stage to the next. These models interact with each other within the framework of a decision support system to help the user with allocation decisions as well as prediction of force requirements to win the battle.     

Parsimonious modelling and forecasting of seasonal time series

Some seasonal time series models are considered which are appropriate for the univariate modelling and forecasting of many time series. The equivalent ARIMA forms of these models provide the basis for a critical examination of the Box-Jenkins approach to seasonal model-building. It is concluded that this approach is unsatisfactory and in particular can often result in over-differencing and the adoption of an inappropriate model. Two main reasons for this are discussed: (a) the inadequate class of models considered which rests on a restricted view of parsimony, and (b) the shortcomings of the basic approach to model identification.     

Coupled differential algebraic equations in the simulation of flexible multibody systems with hydrodynamic force elements

The mathematical modelling of elastohydrodynamic bearings in combustion engines leads to a coupled system of (partial) differential algebraic equations, which is represented by a flexible multibody system model of the engine including crankshaft and bearing and by the Reynolds equation that describes the non-linear effects in the fluid film. The hydrodynamic forces depend strongly on the position and the elastic deformation of crankshaft and bearing shell. We discuss the influence of the spatial discretization on accuracy and numerical effort. Since a fine spatial discretization substantially slows down the numerical solution, we propose a semi-analytical method based on singular perturbation theory to speed-up time integration. Numerical tests for a simplified benchmark problem illustrate the advantages of this approach. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)