Virtual Manufacturing of Composite Structures Applying Implicit and Explicit FE Techniques

Virtual manufacturing of composites can yield an initial early estimation of the induced residual thermal stresses that affect component fatigue life, and deformations that affect required tolerances for assembly. Based on these estimation, the designer can make early decisions, which can help in reducing cost, regarding changes in part design or material properties. In this paper, an approach is proposed to simulate the autoclave manufacturing technique for unidirectional composites. The proposed approach consists of three modules. The first module is a Thermochemical model to estimate temperature and the degree of cure distributions in the composite part during the cure cycle. The second and third modules are stress analysis using FE-Implicit and FE-Explicit respectively. User-material subroutine will be used to model the Viscoelastic properties of the material based on micromechanical theory. Estimated deformation of the composite part can be corrected during the autoclave process by modifying the process-tool design. The deformed composite surface is sent to CATIA for design modification of the process-tool.

Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level. © 2012 Emmert-Streib.

New algorithms and VLSI architectures for SRT division and square root

In real time digital signal processing, high performance modules for division and square root are essential if many powerful algorithms are to be implemented. In this paper, a new radix 2 algorithms for SRT division and square root are developed. For these new schemes, the result digits and the residuals are computed concurrently and the computations in adjacent rows are overlapped. Consequently, their performance should exceed that of the radix 2 SRT methods. VLSI array architectures to implement the new division and square root schemes are also presented.

Review of: Tykot, R.H. and Andrews, T.K. 1992. Sardinia: a footprint in the sea: studies in Sardinian Archaeology presented to Miriam Balmuth. Sheffield Academic Press

Proceedings of the Prehistoric Society, 1994. 60: p. 455-6.

Flowfield analysis of a linear clustered plug nozzle with round-to-square modules

The plug nozzle is one of the advanced expansion devices proposed to improve the overall performance of launcher liquid rocket engines. The present work investigates the three-dimensional flow field generated on this kind of nozzle by partitioning the primary nozzle into modules. A linear plug nozzle has been designed together with modules having two different geometries: a rectangular cross section and round-to-square module. Numerical simulations have been carried out considering the case where all modules of the primary nozzle are active and the case where one module is turned off. The solutions are compared and specific three-dimensional flow structures taking place inside the modules and on the plug are identified. The relationship between these structures and the skin friction distribution within the module and along the plug surface is investigated. Finally, the effect on performance of these three-dimensional flow features is emphasized. © 2006 Elsevier Masson SAS. All rights reserved.

The efficacy of a CDIO based integrated curriculum as preparation for professional practice in product design and development

The School of Mechanical and Aerospace Engineering at Queen’s University Belfast started BEng and MEng degree programmes in Product Design and Development (PDD) in 2004. Intended from the outset to be significantly different from the existing programmes within the School the PDD degrees used the syllabus and standards defined by the CDIO Initiative as the basis for an integrated curriculum. Students are taught in the context of conceiving, designing, implementing and operating a product. Fundamental to this approach is a core sequence of Design-Build-Test (DBT) experiences which facilitates the development of a range of professional skills as well as the immediate application of technical knowledge gained in strategically aligned supporting modules.
The key objective of the degree programmes is to better prepare students for professional practice. PDD graduates were surveyed using a questionnaire developed by the CDIO founders and interviewed to examine the efficacy of these degree programmes, particularly in this key objective. Graduate employment rates, self assessment of graduate attributes and examples of work produced by MEng graduates provided positive evidence that their capabilities met the requirements of the profession. The 24% questionnaire response rate from the 96 graduates to date did not however facilitate statistically significant conclusions to be drawn and particularly not for BEng graduates who were under represented in the response group. While not providing proof of efficacy the investigation did provide a good amount of useful data for consideration as part of a continuous improvement process.

NFA decomposition and multiprocessing architecture for parallel regular expression processing

This work presents a novel algorithm for decomposing NFA automata into one-state-active modules for parallel execution on Multiprocessor Systems on Chip (MP-SoC). Furthermore, performance related studies based on a 16-PE system for Snort, Bro and Linux-L7 regular expressions are presented. ©2009 IEEE.

Wave loads on the foundation of a bottom-hinged modular flap structure

Large loads result in expensive foundations which are a substantial proportion of the capital cost of flap-type Wave Energy Converters (WECs). Devices such as Oyster 800, currently deployed at the European Marine Energy Centre (EMEC), comprise a single flap for the full width of the machine. Splitting a flap-type device into smaller vertical flap modules, to make a ‘modular-flap’, might reduce the total foundation loads, whilst still providing acceptable performance in terms of energy conversion.
This paper investigates the foundation loads of an undamped modular-flap device, comparing them to those for a rigid flap of an equivalent width. Physical modelling in a wave tank is used, with loads recorded using a six degree of freedom (DoF) load cell. Both fatigue and extreme loading analysis was conducted. The rotations of the flaps were also recorded, using a motion-tracking system.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Cultivating creative learners in higher education: Engaging students in anatomy through art

Introduction
Nursing and midwifery students often struggle to engage with bioscience modules because they lack confidence in their ability to study science (Fell et al., 2012). Consequently many have difficulty applying anatomical and physiological information, essential to providing safe and effective patient care (Rogers, 2014; Rogers and Sterling, 2012); therefore a need exists for nurse educators to explore different methods of delivery of these important topics to enhance current curricula (Johnston, 2010). Inspired by the reported success of creative methods to enhance the teaching and learning of anatomy in medical education (Noel, 2013; Finn and McLachlan, 2010), this pilot study engaged nursing students in anatomy through the art of felt. The project was underpinned by the principles of good practice in undergraduate education, staff-student engagement, cooperation among students, active learning, prompt feedback, time on task, high expectations and respect for diverse learning styles (Chickering and Gamson, 1987).

Method
Undergraduate student nurses from Queen’s University, Belfast, enrolled in the year one ‘Health and Wellbeing’ model were invited to participate in the project. Over a six week period the student volunteers worked in partnership with teaching staff to construct individual, unique, three dimensional felt models of the upper body. Students researched the agreed topic for each week in terms of anatomical structure, location, tissue composition and vascular access. Creativity was encouraged in relation to the colour and texture of materials used. The evaluation of the project was based on the four level model detailed by Kirkpatrick and Kirkpatrick (2006) and included both quantitative and qualitative analysis:• pre and post knowledge scores• self-rated confidence• student reflections on the application of learning to practice.

Results
At the end of the project students had created felt pieces reflective of their learning throughout the project and ‘memorable’ three dimensional mental maps of the human anatomy. Evaluation revealed not only acquisition of anatomical knowledge, but the wider benefits of actively engaging in creative learning with other students and faculty teaching staff.

The project has enabled nurse educators to assess the impact of innovative methods for delivery of these important topics.