Design and process selection for joints in flexible materials

The application of high performance textiles has grown significantly in the last 10 to 15 years. Various research groups throughout the United Kingdom, such as the Department of Trade and Industry, have identified technical textiles as a field for future development. There is little design guidance for joining of flexible materials or general property models that can be applied to theses materials. This lack is due to the large diversity of properties, structures and resulting behaviours of the materials that are classified as "Flexible Materials". This dissertation explores the issues that are involved in characterising the materials at the fibre, bulk and textile levels. Different units of measurement are used for each stage of the manufacturing process of flexible materials and this disparity creates problems when trying to make general comparisons (e.g. comparing textiles to polymer films). Thus, a possible solution to this is to create selection charts that allow designers to compare the strength of materials for a given mass per unit area. A design tool was created using the Cambridge Engineering Selector (CES) software to enable the selection of joining processes for material. The tool is effective in selecting a reduced number of viable joining processes. Through case studies it was shown that designers are required to examine the selected processes (identified by the software) in greater detail - in particular the economics and geometry of the joint - in order to identify the optimum joining process.

Customizing the technology roadmapping technique for software companies

Software importance keeps growing fast and consistently for many organizations. The growth of software functionality in manufactured products and the emergence of digital media, convergent spaces including digital content, software, and multi-channels to the market, are recent examples of organizational changes where software assumed a central position for the corporate strategy. This paper analyzes the alignment between strategic objectives and software development processes at software companies and proposes a methodology to ensure that development processes are aligned with the corporate capabilities required to exploit future market opportunities. The methodology includes the categorization of different software companies according to their core capabilities and the customization of the technology roadmapping technique for software companies. The research process included the realization of case studies and a survey. (c) 2006 PICMET.

Quality practices and problems in free software projects

Free software and open source projects are often perceived to be of high quality. It has been suggested that the high level of quality found in some free software projects is related to the open development model which promotes peer review. While the quality of some free software projects is comparable to, if not better than, that of closed source software, not all free software projects are successful and of high quality. Even mature and successful projects face quality problems; some of these are related to the unique characteristics of free software and open source as a distributed development model led primarily by volunteers. In exploratory interviews performed with free software and open source developers, several common quality practices as well as actual quality problems have been identified. The results of these interviews are presented in this paper in order to take stock of the current status of quality in free software projects and to act as a starting point for the implementation of quality process improvement strategies.

Free energy surface reconstruction from umbrella samples using Gaussian process regression

We demonstrate how the Gaussian process regression approach can be used to efficiently reconstruct free energy surfaces from umbrella sampling simulations. By making a prior assumption of smoothness and taking account of the sampling noise in a consistent fashion, we achieve a significant improvement in accuracy over the state of the art in two or more dimensions or, equivalently, a significant cost reduction to obtain the free energy surface within a prescribed tolerance in both regimes of spatially sparse data and short sampling trajectories. Stemming from its Bayesian interpretation the method provides meaningful error bars without significant additional computation. A software implementation is made available on www.libatoms.org.

Free energy surface reconstruction from umbrella samples using Gaussian process regression II: Multiple collective variables

We demonstrate how a prior assumption of smoothness can be used to enhance the reconstruction of free energy profiles from multiple umbrella sampling simulations using the Bayesian Gaussian process regression approach. The method we derive allows the concurrent use of histograms and free energy gradients and can easily be extended to include further data. In Part I we review the necessary theory and test the method for one collective variable. We demonstrate improved performance with respect to the weighted histogram analysis method and obtain meaningful error bars without any significant additional computation. In Part II we consider the case of multiple collective variables and compare to a reconstruction using least squares fitting of radial basis functions. We find substantial improvements in the regimes of spatially sparse data or short sampling trajectories. A software implementation is made available on www.libatoms.org.