A parametric analysis technique for design of fuel cell and hybrid-electric vehicles

This paper presents a new simplified parametric analysis technique for the design of fuel cell and hybrid-electric vehicles. The technique utilizes a comprehensive set of ∼30 parameters to fully characterize the vehicle platform, powertrain components, vehicle performance requirements and driving conditions. It is best applied to the sizing of powertrain components and prediction of energy consumption in a vehicle. This new parametric technique makes a good complement to existing vehicle simulation software packages and therefore represents a potentially valuable tool for the hybrid vehicle designer.

Parametric analysis of acoustic emission signals for evaluating damage in composites using a PVDF film sensor

With the increased utilization of advanced composites in strategic industries, the concept of Structural Health Monitoring (SHM) with its inherent advantages is gaining ground over the conventional methods of NDE and NDI. The most attractive feature of this concept is on-line evaluation using embedded sensors. Consequently, development of methodologies with identification of appropriate sensors such as PVDF films becomes the key for exploiting the new concept. And, of the methods used for on-line evaluation acoustic emission has been most effective. Thus, Acoustic Emission (AE) generated during static tensile loading of glass fiber reinforced plastic composites was monitored using a Polyvinylidene fluoride (PVDF) film sensor. The frequency response of the film sensor was obtained with pencil lead breakage tests to choose the appropriate band of operation. The specimen considered for the experiments were chosen to characterize the differences in the operation of the failure mechanisms through AE parametric analysis. The results of the investigations can be characterized using AE parameter indicating that a PVDF film sensor was effective as an AE sensor used in structural health monitoring on-line.

Parametric Analysis Of Turbulent Wall Jets

The concept of a fully-developed flow based on the hypothesis of selective memory is here applied to general wall-jet type flows. In the presence of a (constant) external stream, the free-stream velocity and the jet momentum flux are taken to be the chief quantities governing the development of the wall jet: two additional nondimensional parameters, representing a momentum flux Reynolds number and the relative momentum defect in the initial boundary layer, are shown to have only a secondary effect on the fully-developed flow. The standard correlations so determined are also found to predict quite well the flow development in Gartshore and Newman's experiments on wall jets in adverse pressure gradients; possible reasons for this somewhat surprising result are discussed. Finally it is shown, by application to the still-air case, that the parameters discovered in incompressible flow are, with appropriate but straightforward modification, successful in describing compressible wall jets also.

Single-machine scheduling with past-sequence-dependent setup times and learning effects: a parametric analysis

In this article, we consider the single-machine scheduling problem with past-sequence-dependent (p-s-d) setup times and a learning effect. The setup times are proportional to the length of jobs that are already scheduled; i.e. p-s-d setup times. The learning effect reduces the actual processing time of a job because the workers are involved in doing the same job or activity repeatedly. Hence, the processing time of a job depends on its position in the sequence. In this study, we consider the total absolute difference in completion times (TADC) as the objective function. This problem is denoted as 1/LE, (Spsd)/TADC in Kuo and Yang (2007) ('Single Machine Scheduling with Past-sequence-dependent Setup Times and Learning Effects', Information Processing Letters, 102, 22-26). There are two parameters a and b denoting constant learning index and normalising index, respectively. A parametric analysis of b on the 1/LE, (Spsd)/TADC problem for a given value of a is applied in this study. In addition, a computational algorithm is also developed to obtain the number of optimal sequences and the range of b in which each of the sequences is optimal, for a given value of a. We derive two bounds b* for the normalising constant b and a* for the learning index a. We also show that, when a < a* or b > b*, the optimal sequence is obtained by arranging the longest job in the first position and the rest of the jobs in short processing time order.

Parametric Analysis for Monitoring 2D Kinetics of Receptor-Ligand binding

Thermal fluctuation approach is widely used to monitor association kinetics of surface-bound receptor-ligand interactions. Various protocols such as sliding standard deviation (SD) analysis (SSA) and Page's test analysis (PTA) have been used to estimate two-dimensional (2D) kinetic rates from the time course of displacement of molecular carrier. In the current work, we compared the estimations from both SSA and modified PTA using measured data from an optical trap assay and simulated data from a random number generator. Our results indicated that both SSA and PTA were reliable in estimating 2D kinetic rates. Parametric analysis also demonstrated that such the estimations were sensitive to parameters such as sampling rate, sliding window size, and threshold. These results furthered the understandings in quantifying the biophysics of receptor-ligand interactions.

Semi-Parametric Analysis of Extreme Forest Fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.

Parametric analysis of discrepant sets of data

In this paper a new parametric method to deal with discrepant experimental results is developed. The method is based on the fit of a probability density function to the data. This paper also compares the characteristics of different methods used to deduce recommended values and uncertainties from a discrepant set of experimental data. The methods are applied to the (137)Cs and (90)Sr published half-lives and special emphasis is given to the deduced confidence intervals. The obtained results are analyzed considering two fundamental properties expected from an experimental result: the probability content of confidence intervals and the statistical consistency between different recommended values. The recommended values and uncertainties for the (137)Cs and (90)Sr half-lives are 10,984 (24) days and 10,523 (70) days, respectively. (C) 2009 Elsevier B.V. All rights reserved.

Parametric Analysis of Effective Material Properties of Thickness-Shear Piezoelectric Macro-Fibre Composites

A previous study on the characterization of effective material properties of a d(15) thickness-shear piezoelectric Macro-Fibre Composite (MFC) made of seven layers (Kapton, Acrylic, Electrode, Piezoceramic Fibre and Epoxy Composite, Electrode, Acrylic, Kapton) using a finite element homogenization method has shown that the packaging reduces significantly the shear stiffness of the piezoceramic material and, thus, leads to significantly smaller effective electromechanical coupling coefficient k(15) and piezoelectric stress constant e(15) when compared to the piezoceramic fibre properties. Therefore, the main objective of this work is to perform a parametric analysis in which the effect of the variations of fibre volume fraction, Epoxy elastic modulus, electrode thickness and active layer thickness on the MFC effective material properties is evaluated. Results indicate that an effective d(15) MFC should use relatively thick fibres having relatively high shear modulus and relatively stiff epoxy filler. On the other hand, the electrode thickness does not affect significantly the MFC performance.

Parametric analysis of effective material properties of thickness-shear piezoelectric macro-fibre composites

A previous study on the characterization of effective material properties of a d15 thickness-shear piezoelectric Macro-Fibre Composite (MFC) made of seven layers (Kapton, Acrylic, Electrode, Piezoceramic Fibre and Epoxy Composite, Electrode, Acrylic, Kapton) using a finite element homogenization method has shown that the packaging reduces significantly the shear stiffness of the piezoceramic material and, thus, leads to significantly smaller effective electromechanical coupling coefficient k15 and piezoelectric stress constant e15 when compared to the piezoceramic fibre properties. Therefore, the main objective of this work is to perform a parametric analysis in which the effect of the variations of fibre volume fraction, Epoxy elastic modulus, electrode thickness and active layer thickness on the MFC effective material properties is evaluated. Results indicate that an effective d15 MFC should use relatively thick fibres having relatively high shear modulus and relatively stiff epoxy filler. On the other hand, the electrode thickness does not affect significantly the MFC performance.