Determination of drawbead contacts with variable bead penetration

In stamping operations, the sliding of the sheet metal over the drawbeads is of great importance. The geometry of the drawbead and the degree of penetration both influence material flow and alter the frictional effects between the work and the tool. The effect of drawbead penetration over drawbeads has been studied using the Drawbead Simulator (DBS) test. The contact phenomenon between the sheet and drawbeads was analysed by examining deformed samples with an image fitting technique. The results were compared with an FE simulation and with an approximate geometric analysis. The results give a useful relationship between the rates of change of the contact angle with increasing bead penetration.

Automotive can network response time analysis with variable jitter

Many methods to calculate message latencies for Controller Area Network (CAN) have previously been presented based upon the static worst-case behaviour of the system. With the use of modern simulation tools however, the behaviour of CAN networks can be simulated dynamically in order to find the likely worst-case response times for CAN messages. This paper shows the development of an automotive body control network model to be used as the basis for further simulations. A method to simulate the Worst-Case Response Time of this model is then presented, taking into account random queuing jitter.

The eight variable homogeneous degree three bent functions

We determine the affine equivalence classes of the eight variable degree three homogeneous bent functions using a new algorithm. Our algorithm applies to general bent functions and can systematically determine the automorphism groups. We provide a partial verification of the computer enumeration of bent functions by Meng et al.

Analysis of work hardening and recrystallization during the hot working of steel using a statistically based internal variable model

A mathematical model has been developed which describes the hot deformation and recrystallization behavior of austenite using a single internal variable: dislocation density. The dislocation density is incorporated into equations describing the rate of recovery and recrystallization. In each case no distinction is made between static and dynamic events, and the model is able to simulate multideformation processes. The model is statistically based and tracks individual populations of the dislocation density during the work-hardening and softening phases. After tuning using available data the model gave an accurate prediction of the stress–strain behavior and the static recrystallization kinetics for C–Mn steels. The model correctly predicted the sensitivity of the post deformation recrystallization behavior to process variables such as strain, strain rate and temperature, even though data for this were not explicitly incorporated in the tuning data set. In particular, the post dynamic recrystallization (generally termed metadynamic recrystallization) was shown to be largely independent of strain and temperature, but a strong function of strain rate, as observed in published experimental work.

Iterative variable aggregation and disaggregation in IP : an application

This paper, using the Unconstrained Shape Matrix Optimization Problem as a test bed, we investigate various aspects of variable aggregation and disaggregation for a class of integer programs that contains binary expansion. We present theoretical and numerical results, and propose an iterative algorithm for exact solutions.

Variable definitions: implications for the prediction of pulmonary complications after adult cardiac surgery

Aim: The aim of this paper was to review the implications that variable definitions have for the prediction of post-operative pulmonary complications after cardiac surgery.

Method: A review of the literature from 1980 to 2002. Selected studies demonstrated an original attempt to examine multivariate associations between pre, intra or post-operative antecedents and pulmonary outcomes in patients undergoing coronary artery bypass grafting (CABG). Reports that described the validation of established clinical prediction rules, testing interventions or research conducted in non-human cohorts were excluded from this review.

Results: Consistently, variable factor and outcome definitions are combined for the development of multivariate prediction models that subsequently have limited clinical value. Despite being prevalent there are very few attempts to examine post-operative pulmonary complications (PPC) as endpoints in isolation. The trajectory of pulmonary dysfunction that precedes complications in the post-operative context is not clear. As such there is little knowledge of post-operative antecedents to PPC that are invariably excluded from model development.

Conclusion: Multivariate clinical prediction rules that incorporate antecedent patient and process factors from the continuum of cardiovascular care for specific pulmonary outcomes are recommended. Models such as these would be useful for practice, policy and quality improvement.

Presence of fish on the shallow flooded margins of a small intermittently open estuary in South Eastern Australia under variable flooding regimes

Shallow water habitats within estuarine systems are believed to be important areas for small fish. While a wide variety of shallow habitats have been studied, the land that becomes inundated by the damming effect after the closure of intermittently open mouths has previously been overlooked. Fish were sampled monthly from both the main channel and flood zone of an intermittently open estuary between July 2004 and June 2005 using minifyke nets during the day and at night. A total of 7,787 fish were collected during the study representing 13 species and 11 families. Philypnodon grandiceps was the most abundant species and, together with Atherinosoma microstoma, Pseudogobius olorum, and Galaxias maculatus, made up 94% of the total catch. Inundation of the flood zone occurred in two discrete forms associated with mouth condition, which consisted of sporadic flooding while the mouth was open, to long-term flooding for 6 months after its closure. Large numbers of fish were captured on the flood zone, which included nine species; however, A. microstoma dominated the catch. A distinct shift in the flood zone fish assemblage occurred between the two mouth conditions, which is likely associated with changes in hydro-period and food availability of the flood zone and physico-chemical parameters in the main channel. There was no longitudinal variation in the fish assemblage in both the main channel and flood zone; similarly, the diel period was found to have little effect on the fish assemblage. The total catch per unit effort did not vary across seasons and suggests that fish abundance within the estuary is stable throughout the year. Unlike other estuarine systems where shallow water fish assemblages may be structured by variations in tide and elevation within the Surrey, freshwater inflow and, more importantly, mouth condition appear to have the greatest influence in composition of the shallow water flood zone fish assemblage of intermittently open estuaries.

Variable step-size LMS algorithm with a quotient form

An improved robust variable step-size least mean square (LMS) algorithm is developed in this paper. Unlike many existing approaches, we adjust the variable step-size using a quotient form of filtered versions of the quadratic error. The filtered estimates of the error are based on exponential windows, applying different decaying factors for the estimations in the numerator and denominator. The new algorithm, called more robust variable step-size (MRVSS), is able to reduce the sensitivity to the power of the measurement noise, and improve the steady-state performance for comparable transient behavior, with negligible increase in the computational cost. The mean convergence, the steady-state performance and the mean step-size behavior of the MRVSS algorithm are studied under a slow time-varying system model, which can be served as guidelines for the design of MRVSS algorithm in practical applications. Simulation results are demonstrated to corroborate the analytic results, and to compare MRVSS with the existing representative approaches. Superior properties of the MRVSS algorithm are indicated.

A class of modified variable step-size NLMS algorithms for system identification

This paper proposes a class of modified variable step-size normalized least mean square (VS NLMS) algorithms. The class of schemes are obtained from estimating the optimum step-size of NLMS that minimizes the mean square deviation (MSD). During the estimation, we consider the properties of the additive noise and the input excitation together. The developed class of VS NLMS algorithms have simple forms and give improved tradeoff of fast convergence rate and low misadjustment in system identification.