Not to be confused with 3D SystemsDassault Systèmes S.A. is a French software company that specializes in the production of 3D design software, 3D digital mock-up and product lifecycle management solutions. The company also offers social and collaboration and information and intelligence products. Wikipedia.
Dassault Systemes | Date: 2015-08-24
Current real-time rendering techniques of virtual representations of jewelry with gemstones do not address the shimmer and sparkle of real gemstones. Embodiments of the present invention use real-time rendering methods and systems that enable flash scintillation and fiery scintillation on the facets of virtual representations of gemstones as they are manipulated online by the customer. A 3D representation of a gemstone is displayed. In response to user input corresponding to the manipulation of the displayed 3D representation of the gemstone, scintillations at facets of the 3D representation of the gemstone are determined. The scintillations are determined by loading a scintillation factor from a look-up table corresponding to an angle of incidence of a light source to a facet of the gemstone. The determined scintillations at the facets of the gemstone are displayed for the user in real-time.
Dassault Systemes | Date: 2016-12-09
It is proposed a computer-implemented method for compressing a three-dimensional modeled object. The method comprises: providing a mesh of the three-dimensional modeled object; parameterizing (u,v) the mesh in a two-dimensional plane, the parameterization of the mesh resulting in a set of vertices having two-dimensional coordinates; providing a grid on the two-dimensional plane; and modifying the two-dimensional coordinates of each vertex by assigning one vertex to one intersection of the grid. Such compression method is lossless, completely reversible, suitable to efficiently reduce the storage size of a CAD file.
Dassault Systemes | Date: 2017-03-01
The present disclosure is directed to a method and corresponding system that improves accuracy of a computer simulation of an original posture of a digital human model (DHM) relative to a target object. The method and system may obtain information associated with the original DHM posture. The obtained DHM posture information may include a position of a head of the DHM. The method and system may obtain information associated with the target object. The obtained target object information may include a size of the target object and an orientation of the target object. The method and system method may obtain a distance from the head of the DHM to the target object. In some embodiments, the system and method may generate a measure of vision (i.e., vision measure) of the DHM of the target object that the DHM is visually targeting. The system and method may generate the measure of vision based on one or more parameters which may include any of the obtained DHM posture information, the obtained target object information, and the obtained head-target (HT) distance. Based on the measure of vision, the system and method may generate a constraint of vision (i.e., vision constraint) of the DHM to the target object. Based on the vision constraint, the system and method may generate an updated DHM posture.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: NMP-29-2015 | Award Amount: 8.00M | Year: 2016
A definitive conclusion about the dangers associated with human or animal exposure to a particular nanomaterial can currently be made upon complex and costly procedures including complete NM characterisation with consequent careful and well-controlled in vivo experiments. A significant progress in the ability of the robust nanotoxicity prediction can be achieved using modern approaches based on one hand on systems biology, on another hand on statistical and other computational methods of analysis. In this project, using a comprehensive self-consistent study, which includes in-vivo, in-vitro and in-silico research, we address main respiratory toxicity pathways for representative set of nanomaterials, identify the mechanistic key events of the pathways, and relate them to interactions at bionano interface via careful post-uptake nanoparticle characterisation and molecular modelling. This approach will allow us to formulate novel set of toxicological mechanism-aware end-points that can be assessed in by means of economic and straightforward tests. Using the exhaustive list of end-points and pathways for the selected nanomaterials and exposure routs, we will enable clear discrimination between different pathways and relate the toxicity pathway to the properties of the material via intelligent QSARs. If successful, this approach will allow grouping of materials based on their ability to produce the pathway-relevant key events, identification of properties of concern for new materials, and will help to reduce the need for blanket toxicity testing and animal testing in the future.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: SC5-11a-2014 | Award Amount: 6.57M | Year: 2015
The overall aim of Real-Time-Mining is to develop a real-time framework to decrease environmental impact and increase resource efficiency in the European raw material extraction industry. The key concept of the proposed research promotes the change in paradigm from discontinuous intermittent process monitoring to a continuous process and quality management system in highly selective mining operations. Real-Time Mining will develop a real-time process-feedback control loop linking online data acquired during extraction at the mining face rapidly with an sequentially up-datable resource model associated with real-time optimization of long-term planning, short-term sequencing and production control decisions. The project will include research and demonstration activities integrating automated sensor based material characterization, online machine performance measurements, underground navigation and positioning, underground mining system simulation and optimization of planning decisions, state-of-the art updating techniques for resource/reserve models. The impact of the project is expected on the environment through a reduction in CO2-emissions, increased energy efficiency and production of zero waste by maximizing process efficiency and resource utilization. Currently economically marginal deposits or difficult to access deposits will be become industrial viable. This will result in a sustainable increase in the competitiveness of the European raw material extraction through a reduced dependency on raw materials from non-EU sources.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: FOF-03-2016 | Award Amount: 4.12M | Year: 2016
In the aerospace industry very high quality standards have to be met. For the manufacturing of carbon fibre parts this is currently solved through extended end-of-line inspection in combination with re-work processes to deal with defective parts. Also, in-situ visual inspection is used for quality control, which is currently causing huge productivity losses (30%-50%) during lay-up and has become a real bottleneck in carbon fibre parts manufacturing. The project will provide a solution by developing inline quality control methods for the key process steps: automatic lay-up (dry fibre placement and automatic dry material placement) and curing. At the system level decision support systems will be developed that assist human decision-making when assessing defects and when planning the part flow through the production line. These will be supported by simulation tools for part verification and logistical planning. The future manufacturing of the A320neo wing covers will be provide the background for the developments. Each such wing cover consists of two parts, that each cost several hundred thousand Euros in manufacturing. Assuming the planned production rates of 60 planes per month from 2025, savings of 150 MEUR in production costs can be obtained per year. The consortium consists of all key players that will play a future role in the manufacturing of such large carbon fibre parts. Airbus with its research centers Airbus Group Innovations and FIDAMC will play a leading role in the consortium as far as the multi-stage manufacturing process is concerned. Machine builders (MTorres, Danobat) and research centers will develop the inline quality control, while Dassault Systmes will provide simulation support.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: FoF-08-2015 | Award Amount: 7.01M | Year: 2015
OPTIMISED aims to develop novel methods and tools for deployment of highly optimised and reactive planning systems that incorporate extensive factory modelling and simulation based on empirical data captured using smart embedded sensors and pro-active human-machine interfaces. The impact of energy management on factory planning and optimisation will be specifically assessed and demonstrated to reduce energy waste and address peak demand so that operations that require or use less energy, can allow this excess energy to be re-routed to local communities. The OPTIMISED environment will use semantically enriched process modelling, big-data generation, capture and perform analytics to effectively support planning specialists, manufacturing engineers, team leaders and shopfloor operatives throughout the systems lifecycle. These next generation manufacturing systems supported by data rich manufacturing execution systems with OPTIMISED technology will support a dramatic improvement in system performance, improved operational efficiency and equipment utilisation, real-time equipment and station performance monitoring, adaptation and resource optimisation. The OPTIMISED vision will be achieved by developing systems which are able to: 1. Monitor system performance through an integrated sensor network, automatically detecting bottlenecks, faults and performance drop-off 2. Continuously evolve to respond to disruptive events, supply chain disruptions and non-quality issues through factory simulation modelling 3. Improve understanding and monitoring of energy demand curve and energy usage per industrial process and globally improve efficiency of production line through reduced energy waste 4. Understand potential benefits, added value and impacts of participating in Demand Side Response (DSR) processes and becoming an active player in the changing energy industry, instead of remaining a conventional passive element that simply acquires a service from energy providers
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: FoF-05-2014 | Award Amount: 4.82M | Year: 2015
Manutelligence targets the product-service emerging trend; aiming at providing to EU manufacturing companies: - Efficiency in the design process, through ubiquitous cross-disciplinary collaborative management of P-S engineering knowledge across the entire life-cycle phases; - Complete integration of Product Lifecycle Management and Service Lifecycle Management, using methodologies and tools to support cross development; - Involvement of all the key partakers in the supply chain, including customers; - The ability to Search, retrieve and reuse data from heterogeneous data sources during design, manufacturing, testing and usage; - To manage, reuse and optimize designs, promoting modularity and Engineering Design Codified Knowledge, through KBE and design automation; - Close knowledge loop cycles between design, manufacturing, testing and use of products; - To extend and improve the use of Simulation and optimize it through comparison with test bench and real usage data; - Precise and quick measures and simulations of Cost and Sustainability issues, through Life Cycle Cost (LCC), Life Cycle Analysis (LCA) and CO2 footprint. To achieve these needs, ManuTelligence aims to integrate best in class methodology and tools from research and industry, resulting in a secure, cross disciplinary collaborative Product/Service Design and Manufacturing Engineering Platform. This platform will enable designers and engineers to access through natural 3D experiences to data from both the traditional enterprise IT systems (CAD, CAX, PLM, MES, etc.) and IoT enabled systems for physical products information and knowledge management. Such a platform, to have success on the market, needs to be inclusive, facilitating the cooperation and collaboration of enterprises. For this reason, it has been decided from the draft architecture, that it will have interfaces based on Open Standard (e.g. STEP and the OpenGroup QLM.
Agency: GTR | Branch: EPSRC | Program: | Phase: Fellowship | Award Amount: 866.29K | Year: 2015
Composite materials and advanced structures are predicted to be major drivers for the growth and competitiveness of UKs value-added manufacturing economy. Maintaining and further enhancing the current national competitive advantage has been identified as a government strategic priority. This fellowship will contribute toward this goal by considering engineering structural design and composite materials in a different light. When conceiving structures, it is common practice to rely on well-established design principles and robust analysis tools. This may be for several reasons, but the lack of experience with different approaches is probably the most important. Exploring the opportunities that are available outside the designer comfort zone is a risky, expensive and time-consuming gamble that engineering companies can rarely afford to take. History shows several examples of structural designs that, despite being at the forefront of current material technologies, missed out on remarkable engineering opportunities. The Iron Bridge, across the river Severn near Coalbrookdale, is probably the most famous case in point in Britain. Completed in 1779, the bridge was the worlds first to be made of cast iron and is renowned for being substantially overdesigned, having been conceived following rules for wood rather than metal constructions. Composite materials are a modern example. One of their most remarkable features is the versatility that allows engineers to design not only a structure but also its constituent materials. However, partly due to their excellent specific stiffness, there is often the tendency to use them to replicate the well-known behaviour of isotropic materials, thus missing the opportunity to exploit many of the benefits that they could potentially provide. Owing to the colour of carbon fibre composites, this modus operandi is known as the black metal approach. In a similar way, structural design is normally limited to linear regimes. In other words, structures are often designed to be stiff and exhibit small displacements, i.e. to respond linearly to the applied loads. Under these circumstances design methods are well established and based on decades of experience. This is indeed the engineers comfort zone. Designers usually avoid large displacements because they may cause unwanted shape changes and trigger the transition to nonlinear regimes, potentially leading to catastrophic and often sudden, uncontrolled failure. However, if we could learn to control such behaviour, it could actually be exploited for a benefit. The aim of this proposal is to explore the possibilities given by nonlinear responses in structural design. The principal objectives are the development of a new generation of adaptive/multifunctional structures working in elastically nonlinear regimes and the creation of novel paradigms for structural efficiency. The ambition is to harness the possibilities presented by composite materials and to deliver new design principles by removing the barriers imposed by the current practice of restricting structures to behave linearly. Imagine aircraft wings or wind turbine blades tailored to be lighter and still meet the requirements imposed at different operating conditions, thanks to nonlinear stiffness characteristics; buildings whose structural response is compliant only if subjected to extreme earthquake loads, so as to prevent catastrophic failure; or a bridge whose stiffness increases in case of strong winds preventing detrimental aeroelastic instabilities. This is my vision. This is what the elastic properties of composite materials can offer, if we move away from the black metal approach.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: NMP-35-2014 | Award Amount: 7.44M | Year: 2015
The overall objective for iBUS is to develop and demonstrate by 2018 an innovative internet based business model for the sustainable supply of traditional toy and furniture products that is demand driven, manufactured locally and sustainably, meeting all product safety guidelines, within the EU. The iBUS model focuses on the capture, creation and delivery of value for all stakeholders consumers, suppliers, manufacturers, distributors and retailers. The main focus of iBUS is to drive sales for EU traditional toy and furniture manufacturers by leveraging internet based technologies, focusing on safe products, quality, design and innovation. In this new iBUS model consumers become designers, designing, customising and placing orders for their own products online in the iBUS cloud. They will be supported by embedded services in iBUS, developed in the main by SME Technology providers. These services include augmented reality design assistants, design verification tools for compliance with EU product safety guidelines, analysis of environmental footprint and prototyping with additive layer / 3D printing. Subsequently, parametric engineering design principles will take the design from concept to demand. This demand will then be synchronised and optimised across the supply chain, supported by the embedded supply chain optimisation tools, to produce sustainable demand driven production and supply plans. Manufacturers will then produce the furniture and toys in small scale series production driven by the actual customer demand. Suppliers will have visibility of, and make decisions based on, end-customer demand. Likewise customers will have visibility of their orders through all stages of production and delivery. The infrastructure will be cloud based using internet and social media technologies, allowing interaction and collaboration, but also accessible to home-based or small business users, promoting social inclusion.