Multi-disciplinary Optimization with Standard Co-simulation Interfaces

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Grid-enabled Workflows for Industrial Product Design

This paper presents a generic approach for developing and using Grid-based workflow technology for enabling cross-organizational engineering applications. Using industrial product design examples from the automotive and aerospace industries we highlight the main requirements and challenges addressed by our approach and describe how it can be used for enabling interoperability between heterogeneous workflow engines

Holistic simulation for integrated vehicle design

A holistic vehicle simulation capability is necessary for front-loading component, subsystem, and controller design, for the early detection of component and subsystem design flaws, as well as for the model-based calibration of powertrain control modules. The current document explores the concept of holistic vehicle simulation by means of reviewing the current trends automotive system design and available solutions in terms of model interfaces and neutral modelling environments. The review is followed by the presentation of a Simulink-based Multi- disciplinary Modelling Environment (MME) developed by the authors to accommodate simulation work across the vehicle development cycle

Virtue integrated platform : holistic support for distributed ship hydrodynamic design

Ship hydrodynamic design today is often still done in a sequential approach. Tools used for the different aspects of CFD (Computational Fluid Dynamics) simulation (e.g. wave resistance, cavitation, seakeeping, and manoeuvring), and even for the different levels of detail within a single aspect, are often poorly integrated. VIRTUE (the VIRtual Tank Utility in Europe) project has the objective to develop a platform that will enable various distributed CFD and design applications to be integrated so that they may operate in a unified and holistic manner. This paper presents an overview of the VIRTUE Integrated Platform (VIP), e.g. research background, objectives, current work, user requirements, system architecture, its implementation, evaluation, and current development and future work

Numerical propulsion system simulation: An interdisciplinary approach

The tremendous progress being made in computational engineering and the rapid growth in computing power that is resulting from parallel processing now make it feasible to consider the use of computer simulations to gain insights into the complex interactions in aerospace propulsion systems and to evaluate new concepts early in the design process before a commitment to hardware is made. Described here is a NASA initiative to develop a Numerical Propulsion System Simulation (NPSS) capability

Co-Simulation Methods for Holistic Vehicle Design: A Comparison

Vehicle development involves the design and integration of subsystems of different domains to meet performance, efficiency, and emissions targets set during the initial developmental stages. Before a physical prototype of a vehicle or vehicle powertrain is tested, engineers build and test virtual prototypes of the design(s) on multiple stages throughout the development cycle. In addition, controllers and physical prototypes of subsystems are tested under simulated signals before a physical prototype of the vehicle is available. Different departments within an automotive company tend to use different modelling and simulation tools specific to the needs of their specific engineering discipline. While this makes sense considering the development of the said system, subsystem, or component, modern holistic vehicle engineering requires the constituent parts to operate in synergy with one-another in order to ensure vehicle-level optimal performance. Due to the above, integrated simulation of the models developed in different environments is necessary. While a large volume of existing co-simulation related publications aimed towards engineering software developers, user-oriented publications on the characteristics of integration methods are very limited. This paper reviews the current trends in model integration methods applied within the automotive industry. The reviewed model integration methods are evaluated and compared with respect to an array of criteria such as required workflow, software requirements, numerical results, and simulation speed by means of setting up and carrying out simulations on a set of different model integration case studies. The results of this evaluation constitute a comparative analysis of the suitability of each integration method for different automotive design applications. This comparison is aimed towards the end-users of simulation tools, who in the process of setting up a holistic high-level vehicle model, may have to select the most suitable among an array of available model integration techniques, given the application and the set of selection criteria

Modelling environment for holistic vehicle simulation

As the complexity of road vehicles increases with time, the importance of CAE tools to the product development cycle increases as well. A holistic vehicle simulation capability is necessary for front-loading component, subsystem, and controller design, for the early detection of component and subsystem design flaws, as well as for the model-based calibration of powertrain control modules. The current document explores the concept of holistic vehicle simulation by means of developing and testing a Simulink-based multidisciplinary modelling environment (MME), modular in nature and capable of connecting to subsystem models developed in different environments, thus supporting holistic vehicle simulation on a company-wide scale. The developed environment is tested via the integration of subsystem models built in different commercial software packages within the environment. The simulation results generated from equivalent vehicle models developed in three competing platforms are compared and the advantages and limitations of the different methods of model integration to the master holistic vehicle simulation are discussed

ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)

Systems Engineering for Cyber-Physical Products

International audienceThis paper will present how the Dassault Systèmes PLM solution introduces a new paradigm to address the systems engineering challenges of developing cyber-physical systems. V6 unified modeling architecture has extensive support for cross discipline systems engineering based tools, enabling a collaborative Platform and Model Based Engineering environment

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie