A functional basis for engineering design: Reconciling and evolving previous efforts

The main objective of this research is to develop a structured methodology to formulate end-of-life strategies, while still encouraging creative thinking. Current practices encourage general rules for a wide variety of products. This research identifies key characteristics that influence appropriate end-of-life strategies, in contrast to the "one-size-fits-all" approach. The research results are divided into two core sections. First, the methodology determines what end-of-life strategy is possible according to the products' technical characteristics. Second, the classification of end-of-life strategies is compared with current industry practice, in order to evaluate and validate the method. The software developed, called the End-of-Life Design Advisor (ELDA), guides product developers to specify appropriate end-of-life strategies. The ability to classify end-of-life strategies enables designers to redesign products that move to end-of-life strategies with lower environmental impact. This paper presents recommendations for designers and product managers for specific end-of-life strategies. By understanding better the end-of-life strategy appropriate for the product, the research results can help designers develop appropriate (and profitable) end-of-life strategies for their unique position, systematically. Putting ELDA results into perspective establishes that improvements in end-of-life are either through design innovation or value chain improvement. Revision received: 23 May 2001 Electronic Publication     

Age and visual impairment decrease driving performance as measured on a closed-road circuit

In this study the effects of visual impairment and age on driving were investigated and related to visual function. Participants were 139 licensed drivers (young, middle-aged, and older participants with normal vision, and older participants with ocular disease). Driving performance was assessed during the daytime on a closed-road driving circuit. Visual performance was assessed using a vision testing battery. Age and visual impairment had a significant detrimental effect on recognition tasks (detection and recognition of signs and hazards), time to complete driving tasks (overall course time, reversing, and maneuvering), maneuvering ability, divided attention, and an overall driving performance index. All vision measures were significantly affected by group membership. A combination of motion sensitivity, useful field of view (UFOV), Pelli-Robson letter contrast sensitivity, and dynamic acuity could predict 50% of the variance in overall driving scores. These results indicate that older drivers with either normal vision or visual impairment had poorer driving performance compared with younger or middle-aged drivers with normal vision. The inclusion of tests such as motion sensitivity and the UFOV significantly improve the predictive power of vision tests for driving performance. Although such measures may not be practical for widespread screening, their application in selected cases should be considered.     

Performance characteristics of soot primary particle size measurements by time-resolved laser-induced incandescence

A detailed analysis of various factors that influence the accuracy of time-resolved laser-induced incandescence for the determination of primary soot particles is given. As the technique relies on the measurement of the signal ratio at two detection times of the enhanced thermal radiation after an intense laser pulse, guidelines are presented for a suitable choice of detection times to minimize statistical uncertainty. An error analysis is presented for the issues of laser energy absorption, vaporization, heat conduction, and signal detection. Results are shown for a laminar ethene diffusion flame that demonstrate that concurring results are obtained for various laser irradiances, detection characteristics, and times of observation.     

A formal theory of matrix primeness

Primeness of nD polynomial matrices is of fundamental importance in multidimensional systems theory. In this paper we define a quantity which describes the “amount of primeness” of a matrix and identify it as the concept of grade in commutative algebra. This enables us to produce a theory which unifies many existing results, such as the Bézout identities and complementation laws, while placing them on a firm algebraic footing. We also present applications to autonomous systems, behavioural minimality of regular systems, and transfer matrix factorization. This work has been sponsored by EPSRC Grant No. GR/K 18504.     

Analysis of flow patterns in a patient-specific thoracic aortic aneurysm model

In this study, a newly developed two-equation transitional model was employed for the prediction of blood flow patterns in a thoracic aortic aneurysm (TAA) where the growth and progression are closely linked to low and oscillating wall shear stresses. Laminar–turbulent transition in the dilated vessel can alter the flow structure, shear stress and pressure distribution within the aneurysm. A patient-specific TAA model was reconstructed from magnetic-resonance (MR) images and measured velocity waveform was used as the inflow condition. Laminar flow and a correlation-based transitional version of Menter’s hybrid k ? ?/k ? ω Shear Stress Transport (SST Tran) model were implemented in pulsatile simulations from which WSS distribution was obtained throughout a cardiac cycle and velocity profiles were compared with MR measurements. The correlation-based transitional model was found to produce results in closer agreement with the MR data than the laminar flow simulation.     

Exploration of Shape Variation Using Localized Components Analysis

Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.     

Java-basiertes automatisiertes Test-Framework

Java-based Automated Test-Framework With an increasing number of software-systems built using components, software developers are faced with entirely new challenges. For example, testing these modu-lar systems has become far more complex. Manual test approaches are incapable of dealing with the new architectures, leaving several parts of the systems untested. Thorough tests require extensive use of human resources, with enormous financial repercussions. Most customers are unwilling to accept these, completely unaware of their eventual benefit. Even existing automated software test approaches can only remedy these problems in parts. They commonly require source code access to add the necessary test routines, making the approach unsuitable for third party compo-nents. The innovative CBTesten approach tackles this problem. A highly dynamic framework is introduced into the software-system after compilation, which allows de-riving of test cases as well as fully automated tests based on the collected data.     

Is my model too complex? Evaluating model formulation using model reduction

While mechanistic models tend to be detailed, they are less detailed than the real systems they seek to describe, so judgements are being made about the appropriate level of detail within the process of model development. These judgements are difficult to test, consequently it is easy for models to become over-parameterised, potentially increasing uncertainty in predictions. The work we describe is a step towards addressing these difficulties. We propose and implement a method which explores a family of simpler models obtained by replacing model variables with constants (model reduction by variable replacement). The procedure iteratively searches the simpler model formulations and compares models in terms of their ability to predict observed data, evaluated within a Bayesian framework. The results can be summarised as posterior model probabilities and replacement probabilities for individual variables which lend themselves to mechanistic interpretation. This provides powerful diagnostic information to support model development, and can identify areas of model over-parameterisation with implications for interpretation of model results. We present the application of the method to 3 example models. In each case reduced models are identified which outperform the original full model in terms of comparisons to observations, suggesting some over-parameterisation has occurred during model development. We argue that the proposed approach is relevant to anyone involved in the development or use of process based mathematical models, especially those where understanding is encoded via empirically based relationships.     

Metamodel-based collaborative optimization framework

This paper focuses on the metamodel-based collaborative optimization (CO). The objective is to improve the computational efficiency of CO in order to handle multidisciplinary design optimization problems utilising high fidelity models. To address these issues, two levels of metamodel building techniques are proposed: metamodels in the disciplinary optimization are based on multi-fidelity modelling (the interaction of low and high fidelity models) and for the system level optimization a combination of a global metamodel based on the moving least squares method and trust region strategy is introduced. The proposed method is demonstrated on a continuous fiber-reinforced composite beam test problem. Results show that methods introduced in this paper provide an effective way of improving computational efficiency of CO based on high fidelity simulation models.