This paper presents an innovative model-driven architecture enabling 3D web-based design processes in the field of large complex building (LBC) projects, such as power plant construction. This work was motivated by proposing new ways of achieving 3D CAD tasks not only for highly complex and temporary organization in the design stages but also for the whole lifecycle of such installations, which may last several decades. in this particular scenario, it is very important to share the right information with the right stakeholder at the right time, to maintain a high level of knowledge sharing. Taking into account these challenges, we propose a first implementation of interactive 3D CAD editing tools, based on the X3DOM technology and driven by a knowledge layer which utilizes a complete reference data and rules management system. To store the CAD models, a Macro-Parametric Approach has been investigated and a 3D server has been added to the traditional PDM (Product or Plant Data Management) to execute remotely complex CAD operations. This is a very promising start to deploy lightweight and smart web3D CAD editing services for the AEC (Architecture Engineering Construction) and power industries

a) Standard webVis UI elements with Instance Graph (IG) struct-tree views (b) Interactive high quality and secure visualisation via server-based ray-tracing and streaming (c) AR application with client-based composition of multi-buffer views Figure 1: Application examples using webVis / instant3DHub. The platform is able to deliver different kinds of browser-based visualisation applications, such as high-quality large model visualisation, CAD inspection, or augmented reality, while providing a straightforward and expressive tag set and API. AbstractThis paper presents the webVis / instant3DHub platform, which combines a novel Web-Components based framework and a Visual Computing as a Service infrastructure to deliver an interactive 3D data visualisation solution. The system focuses on minimising resource consumption, while maximising the end-user experience. It utilises an adaptive and automated combination of client, server and hybrid visualisation techniques, while orchestrating transmission, caching and rendering services to deliver structural and semantically complex data sets on any device class and network architecture. The API and Web Component framework allow the application developer to compose and manipulate complex data setups with a simple set of commands inside the browser, without requiring knowledge about the underlying service infrastructure, interfaces and the fully automated processes. This results in a new class of interactive applications, built around a canvas for real-time visualisation of massive data sets.

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The long term management of a production asset raises several major issues among which rank the technical management of the plant, its economics and the fleet level perspective one has to adopt. Decision makers are therefore faced with the need to define long term policies (up to the end of asset operation) which take into account multiple criteria including safety (which is paramount) and performance. In this paper we first remind the reader of the EDF three-level methodology for asset management. We then focus on the knowledge model and on the software tools that implement this methodology in order to gather, preserve, share, maintain and exploit the expert knowledge needed for asset management and to allow decision makers to define, evaluate and analyze long term plant operation and maintenance policies. Lastly, as the quality of the processed plant level evaluations (operation & maintenance strategies are evaluated, at a plantlevel, through a set of technical and economic indicators) and their interpretation relies on the quality of the knowledge captured in the tools, we focus on the definition of a “adaptative” user interface — based on Electronic Structured Documents — that allows technical/strategic experts and decision makers to consult the useful pieces of knowledge in a context dependent way. Such an interface, which, in a near future, should be fully implemented in the tools will facilitate the validation of the knowledge-base content and the analysis of the processed results.

The long term management of a production asset raises several major issues among which rank the technical management of the plant, its economics and the fleet level perspective one has to adopt. Decision makers are therefore faced with the need to define long term policies (up to the end of asset operation) which take into account multiple criteria including safety (which is paramount) and performance. In this context, EDF “PWR Durability I & II” research projects have consecutively been launched, since 2001, at EDF – Research & Development in order to develop methods and tools for EDF fleet. The aim of this paper is: • to summarize and analyze the research work that has been performed by EDF – R&D in the field of decision making for nuclear power plant maintenance and operation during the past seven year; • to highlight the strong and weak points of the developed methodology and tools and to identify the research work needed in order to ensure their use by EDF decision makers; • to introduce and illustrate our last development based on the use of an “adaptative” man/machine user interface in order to allows technical/strategic experts and decision makers to consult the useful pieces of knowledge in a context dependent way and, thus, facilitate the validation of the knowledge-base content and the analysis of the processed results. As a result, in this paper, we first remind the reader of the EDF overall methodology for asset management and its adaptations to plant-level life cycle management and to fleet-level component major replacement or capital investment management. We then focus on the three software tools that implement this methodology in order to allow decision makers, in several different contexts to define, evaluate and analyze long term plant operation and maintenance policies, major component replacement policies and capital investment strategies. We also show how the methodology and the software tools were used, from 2003 to 2007, on several pilot case studies. Examples of technical and economic results obtained for plant level pilot case study is quickly described as well as the kinds of conclusions one can draw from them in order to help decision makers evaluate and analyze long term asset management strategies or compare different plants. We then present the opinion of EDF’s decision makers about the developedmethodology and tools — and their use — and our understanding of their feedback. Lastly, we illustrate, using examples of technical and economic knowledge, data and results obtained from our previous pilot case studies, how the concept of an “adaptative” man/machine user interface could be used in order to facilitate the mastering of the methodology and tools’ complexity and to support decision makers’ evaluation and analysis of long term asset management strategies.