Benefit analysis of airborne GPS occultation approach : a case study for the Australian region

This paper aims to present a preliminary benefit analysis for airborne GPS occultation technique for the Australian region. The simulation studies are based on current domestic commercial flights between major Australian airports. With the knowledge of GPS satellite ephemeris data, occultation events for for any particular flight can be determined. Preliminary analysis shows a high resolution occultation observations can be achieved with this approach, for instance, about 15 occultation events for a Perth-to-Sydney flight. The simulation result agrees to the results published by other researchers for a different region. Of course, occultation observation during off-peak hours might be affected due to the limited flight activities. --------- High resolution occultation observations obtainable from airborne GPS occultation system provides an opportunity to improve the current global numerical weather prediction (NWP) models and ultimately improves the accuracy in weather forecasting. More intensive research efforts and experimental demonstrations are required in order to demonstrate the technical feasibility of the airborne GPS technology.

Automated symbolic and numeric procedure for manipulator rigid-body dynamic significance analysis and simplification

This paper describes an automated procedure for analysing the significance of each of the many terms in the equations of motion for a serial-link robot manipulator. Significance analysis provides insight into the rigid-body dynamic effects that are significant locally or globally in the manipulator's state space. Deleting those terms that do not contribute significantly to the total joint torque can greatly reduce the computational burden for online control, and a Monte-Carlo style simulation is used to investigate the errors thus introduced. The procedures described are a hybrid of symbolic and numeric techniques, and can be readily implemented using standard computer algebra packages.

An adaptive local meshfree updated Lagrangian approach for large deformation analysis of metal forming

The large deformation analysis is one of major challenges in numerical modelling and simulation of metal forming. Because no mesh is used, the meshfree methods show good potential for the large deformation analysis. In this paper, a local meshfree formulation, based on the local weak-forms and the updated Lagrangian (UL) approach, is developed for the large deformation analysis. To fully employ the advantages of meshfree methods, a simple and effective adaptive technique is proposed, and this procedure is much easier than the re-meshing in FEM. Numerical examples of large deformation analysis are presented to demonstrate the effectiveness of the newly developed nonlinear meshfree approach. It has been found that the developed meshfree technique provides a superior performance to the conventional FEM in dealing with large deformation problems for metal forming.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Analytical modeling and sensitivity analysis for travel time estimation on signalized urban networks

This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

Stability analysis based on birfurcation theory of the DSTATCOM operating in current control mode

This paper presents the stability analysis for a distribution static compensator (DSTATCOM) that operates in current control mode based on bifurcation theory. Bifurcations delimit the operating zones of nonlinear circuits and, hence, the capability to compute these bifurcations is of important interest for practical design. A control design for the DSTATCOM is proposed. Along with this control, a suitable mathematical representation of the DSTATCOM is proposed to carry out the bifurcation analysis efficiently. The stability regions in the Thevenin equivalent plane are computed for different power factors at the point of common coupling. In addition, the stability regions in the control gain space, as well as the contour lines for different Floquet multipliers are computed. It is demonstrated through bifurcation analysis that the loss of stability in the DSTATCOM is due to the emergence of a Neimark bifurcation. The observations are verified through simulation studies.

Computer simulation and modeling in railway applications

An electrified railway system includes complex interconnections and interactions of several subsystems. Computer simulation is the only viable means for system evaluation and analysis. This paper discusses the difficulties and requirements of effective simulation models for this specialized industrial application; and the development of a general-purpose multi-train simulator.

Measurement of affect during simulation-based training

Training designed to support and strengthen higher-order mental abilities now often involves immersion in Virtual Reality where dangerous real world scenarios can be safely replicated. However despite the growing popularity of advanced training simulations, methods for evaluating their use rely heavily on subjective measures or analysis of final outcomes. Without dynamic, objective performance measures the outcome of training in terms of impact on cognitive skills and ability to transfer newly acquired skills to the real world is unknown. The relationship between affective intensity and cognitive learning provides a potential new approach to ensure the processing of cognitions which occur prior to final outcomes, such as problem-solving and decision-making, are adequately evaluated. This paper describes the technical aspects of pilot work recently undertaken to develop a new measurement tool designed to objectively track individual affect levels during simulation-based training.

Modelling of operating theatres using simulation

This paper describes the development of a simulation model for operating theatres. Elective patient scheduling is complicated by several factors; stochastic demand for resources due to variation in the nature and severity of a patient’s illness, unexpected complications in a patient’s course of treatment and the arrival of non-scheduled emergency patients which compete for resources. Extend simulation software was used for its ability to represent highly complex systems and analyse model outputs. Patient arrivals and lengths of surgery are determined by analysis of historical data. The model was used to explore the effects increasing patient arrivals and alternative elective patient admission disciplines would have on the performance measures. The model can be used as a decision support system for hospital planners.

Shakedown stress analysis of insulated rail joint (IRJ)

A finite element numerical simulation is carried out to examine stress distributions on railhead in the cicinity of the endpost of an insulated rail joint. The contact patch and pressure distribution are considered using modified Hertzian simulation. A combined elasto-plastic material modelling available in Abaqus is employed in the simulation. A dynamic load factor of 1.21 is considered in modelling for the wheel load based on a previous study as part of this on going research. Shakedown theorem is employed in this study. A peak pressure load which is above the shakedown limit is determined as input load. As a result, a progressive damage in the railhead has been captured as depicted in the equivalent plastic strain plot.

An enriched radial point interpolation method (e-RPIM) for analysis of crack tip fields

In this paper, an enriched radial point interpolation method (e-RPIM) is developed the for the determination of crack tip fields. In e-RPIM, the conventional RBF interpolation is novelly augmented by the suitable trigonometric basis functions to reflect the properties of stresses for the crack tip fields. The performance of the enriched RBF meshfree shape functions is firstly investigated to fit different surfaces. The surface fitting results have proven that, comparing with the conventional RBF shape function, the enriched RBF shape function has: (1) a similar accuracy to fit a polynomial surface; (2) a much better accuracy to fit a trigonometric surface; and (3) a similar interpolation stability without increase of the condition number of the RBF interpolation matrix. Therefore, it has proven that the enriched RBF shape function will not only possess all advantages of the conventional RBF shape function, but also can accurately reflect the properties of stresses for the crack tip fields. The system of equations for the crack analysis is then derived based on the enriched RBF meshfree shape function and the meshfree weak-form. Several problems of linear fracture mechanics are simulated using this newlydeveloped e-RPIM method. It has demonstrated that the present e-RPIM is very accurate and stable, and it has a good potential to develop a practical simulation tool for fracture mechanics problems.

Theoretical analysis of serrated chip formation based on ideal models in high speed cutting

In this paper, two ideal formation models of serrated chips, the symmetric formation model and the unilateral right-angle formation model, have been established for the first time. Based on the ideal models and related adiabatic shear theory of serrated chip formation, the theoretical relationship among average tooth pitch, average tooth height and chip thickness are obtained. Further, the theoretical relation of the passivation coefficient of chip's sawtooth and the chip thickness compression ratio is deduced as well. The comparison between these theoretical prediction curves and experimental data shows good agreement, which well validates the robustness of the ideal chip formation models and the correctness of the theoretical deducing analysis. The proposed ideal models may have provided a simple but effective theoretical basis for succeeding research on serrated chip morphology. Finally, the influences of most principal cutting factors on serrated chip formation are discussed on the basis of a series of finite element simulation results for practical advices of controlling serrated chips in engineering application.