Sustainability Enhancement of a Turbine Vane Manufacturing Cell through Digital Simulation based Design

Modern manufacturing systems should satisfy emerging needs related to sustainable development. The design of sustainable manufacturing systems can be valuably supported by simulation, traditionally employed mainly for time and cost reduction. In this paper, a multi-purpose digital simulation approach is proposed to deal with sustainable manufacturing systems design through Discrete Event Simulation (DES) and 3D digital human modelling. DES models integrated with data on power consumption of the manufacturing equipment are utilized to simulate different scenarios with the aim to improve productivity as well as energy efficiency, avoiding resource and energy waste. 3D simulation based on digital human modelling is employed to assess human factors issues related to ergonomics and safety of manufacturing systems. The approach is implemented for the sustainability enhancement of a real manufacturing cell of the aerospace industry, automated by robotic deburring. Alternative scenarios are proposed and simulated, obtaining a significant improvement in terms of energy efficiency (−87%) for the new deburring cell, and a reduction of energy consumption around −69% for the coordinate measuring machine, with high potential annual energy cost savings and increased energy efficiency. Moreover, the simulation-based ergonomic assessment of human operator postures allows 25% improvement of the workcell ergonomic index.

Chloride ingress into marine exposed concrete: A comparison of empirical- and physically- based models

In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.

Nurses' experiences of pain management for people with advanced dementia approaching the end of life: a qualitative study

AIMS AND OBJECTIVES: To explore hospice, acute care and nursing home nurses' experiences of pain management for people with advanced dementia in the final month of life. To identify the challenges, facilitators and practice areas requiring further support.

BACKGROUND: Pain management in end-stage dementia is a fundamental aspect of end of life care; however, it is unclear what challenges and facilitators nurses experience in practice, whether these differ across care settings, and whether training needs to be tailored to the context of care.

DESIGN: A qualitative study using semi-structured interviews and thematic analysis to examine data.

METHODS: 24 registered nurses caring for people dying with advanced dementia were recruited from ten nursing homes, three hospices, and two acute hospitals across a region of the United Kingdom. Interviews were conducted between June 2014 and September 2015.

RESULTS: Three core themes were identified: challenges administering analgesia, the nurse-physician relationship, and interactive learning and practice development. Patient-related challenges to pain management were universal across care settings; nurse- and organisation-related barriers differed between settings. A need for interactive learning and practice development, particularly in pharmacology, was identified.

CONCLUSIONS: Achieving pain management in practice was highly challenging. A number of barriers were identified; however, the manner and extent to which these impacted on nurses differed across hospice, nursing home and acute care settings. Needs-based training to support and promote practice development in pain management in end-stage dementia is required.

RELEVANCE TO CLINICAL PRACTICE: Nurses considered pain management fundamental to end of life care provision; however, nurses working in acute care and nursing home settings may be under-supported and under-resourced to adequately manage pain in people dying with advanced dementia. Nurse-to-nurse mentoring and ongoing needs-assessed interactive case-based learning could help promote practice development in this area. Nurses require continuing professional development in pharmacology. This article is protected by copyright. All rights reserved.

Linking Parametric CAD with Adjoint Surface Sensitivities

The goal of this work is to present an efficient CAD-based adjoint process chain for calculating parametric sensitivities (derivatives of the objective function with respect to the CAD parameters) in timescales acceptable for industrial design processes. The idea is based on linking parametric design velocities (geometric sensitivities computed from the CAD model) with adjoint surface sensitivities. A CAD-based design velocity computation method has been implemented based on distances between discrete representations of perturbed geometries. This approach differs from other methods due to the fact that it works with existing commercial CAD packages (unlike most analytical approaches) and it can cope with the changes in CAD model topology and face labeling. Use of the proposed method allows computation of parametric sensitivities using adjoint data at a computational cost which scales with the number of objective functions being considered, while it is essentially independent of the number of design variables. The gradient computation is demonstrated on test cases for a Nozzle Guide Vane (NGV) model and a Turbine Rotor Blade model. The results are validated against finite difference values and good agreement is shown. This gradient information can be passed to an optimization algorithm, which will use it to update the CAD model parameters.

Aerodynamic optimization using Adjoint methods and parametric CAD models

This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.

IMPLEMENTING BACK PAIN TREATMENT PATHWAYS IN CLINICAL PRACTICE: QUALITATATIVE ANALYSIS OF STAKEHOLDER PERCEPTIONS

Background
Evidence-based practice advocates utilising best current research evidence, while reflecting patient preference and clinical expertise in decision making. Successfully incorporating this evidence into practice is a complex process. Based on recommendations of existing guidelines and systematic evidence reviews conducted using the GRADE approach, treatment pathways for common spinal pain disorders were developed.

Aims
The aim of this study was to identify important potential facilitators to the integration of these pathways into routine clinical practice.

Methods
A 22 person stakeholder group consisting of patient representatives, clinicians, researchers and members of relevant clinical interest groups took part in a series of moderated focus groups, followed up with individual, semi-structured interviews. Data were analysed using content analysis.

Results
Participants identified a number of issues which were categorized into broad themes. Common facilitators to implementation included continual education and synthesis of research evidence which is reflective of everyday practice; as well as the use of clear, unambiguous messages in recommendations. Meeting additional training needs in new or extended areas of practice was also recognized as an important factor. Different stakeholders identified specific areas which could be associated with successful uptake. Patients frequently defined early involvement in a shared decision making process as important. Clinicians identified case based examples and information on important prognostic indicators as useful tools to aiding decisions.

Conclusion
A number of potential implementation strategies were identified. Further work will examine the impact of these and other important factors on the integration of evidence-based treatment recommendations into clinical practice.