Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

L'abstract è presente nell'allegato / the abstract is in the attachmen

Virtual testing of multifunctional moveable actuation systems

This work presents the current state of the virtual testing activities performed within the Virtual Product House (VPH) start-up project. In this project a multidisciplinary, collaborative end-to-end process for virtual product design is developed. On the basis of preliminary design and concept studies on aircraft level, the process focusses on design, manufacturing and testing of aircraft systems and structural components with special attention to certification aspects. The initial use case considers the trailing edge flap of a long-range aircraft and its actuation system. Design and analysis tools are integrated in a remote workflow execution environment to automatically generate designs and evaluate them by virtual test means. Virtual tests facilitate knowledge on properties and behavior of the virtual product in early development phases and allow to optimize design flaws in consecutive design iterations to hence reduce the risk of costly corrections later in the development process. The testing is setup in multiple stages. Currently, domain-specific tests are carried out for the moveable structure and its actuation system, with the latter being in focus for the current text. These tests address the functional verification of the actuation system in nominal and failure cases. A SysML model comprising system requirements and architecture is used to model test cases and trace test results. On the basis of these test cases, simulation configurations for virtual tests are automatically built, executed and evaluated. With this method, a continuous evaluation of designs in terms of functional verification of the moveable actuation system is possible. Moreover, the automated execution of all steps allows to determine the effects of design changes quickly without a large amount of labor-intensive and error-prone work

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Foundations of Multi-Paradigm Modelling for Cyber-Physical Systems

This open access book coherently gathers well-founded information on the fundamentals of and formalisms for modelling cyber-physical systems (CPS). Highlighting the cross-disciplinary nature of CPS modelling, it also serves as a bridge for anyone entering CPS from related areas of computer science or engineering. Truly complex, engineered systems—known as cyber-physical systems—that integrate physical, software, and network aspects are now on the rise. However, there is no unifying theory nor systematic design methods, techniques or tools for these systems. Individual (mechanical, electrical, network or software) engineering disciplines only offer partial solutions. A technique known as Multi-Paradigm Modelling has recently emerged suggesting to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s), and then weaving the results together to form a representation of the system. If properly applied, it enables, among other global aspects, performance analysis, exhaustive simulation, and verification. This book is the first systematic attempt to bring together these formalisms for anyone starting in the field of CPS who seeks solid modelling foundations and a comprehensive introduction to the distinct existing techniques that are multi-paradigmatic. Though chiefly intended for master and post-graduate level students in computer science and engineering, it can also be used as a reference text for practitioners

Compendium in Vehicle Motion Engineering

This compendium is written for the course “MMF062 Vehicle Motion Engineering” at Chalmers University of Technology. The compendium covers more than included in that course; both in terms of subsystem designs and in terms of some teasers for more advanced studies of vehicle dynamics. Therefore, it is also useful for the more advanced course “TME102 Vehicle Modelling and Control”.The overall objective of the compendium is to educate vehicle dynamists, i.e., engineers that understand and can contribute to development of good motion and energy functionality of vehicles. The compendium focuses on road vehicles, primarily passenger cars and commercial vehicles. Smaller road vehicles, such as bicycles and single-person cars, are only very briefly addressed. It should be mentioned that there exist a lot of ground-vehicle types not covered at all, such as: off-road/construction vehicles, tracked vehicles, horse wagons, hovercrafts, or railway vehicles.Functions are needed for requirement setting, design and verification. The overall order within the compendium is that models/methods/tools needed to understand each function are placed before the functions. Chapters 3-5 describes (complete vehicle) “functions”, organised after vehicle motion directions:\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 3:\ua0Longitudinal\ua0dynamics\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 4:\ua0Lateral\ua0dynamics\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 5:\ua0Vertical\ua0dynamicsChapter 1 introduces automotive industry and the overall way of working there and defines required pre-knowledge from “product-generic” engineering, e.g. modelling of dynamic systems.Chapter 2 also describes the subsystems relevant for vehicle dynamics:• Wheels and Tyre\ua0• Suspension\ua0• Propulsion\ua0• Braking System\ua0• Steering System\ua0• Environment Sensing Syste

Digital twin and its implementations in the civil engineering sector

Digital Twin (DT) concept has recently emerged in civil engineering; however, some problems still need to be addressed. First, DT can be easily confused with Building Information Modelling (BIM) and Cyber-Physical Systems (CPS). Second, the constituents of DT applications in this sector are not well-defined. Also, what the DT can bring to the civil engineering industry is still ambiguous. To address these problems, we reviewed 468 articles related to DT, BIM and CPS, proposed a DT definition and its constituents in civil engineering and compared DT with BIM and CPS. Then we reviewed 134 papers related to DT in the civil engineering sector out of 468 papers in detail. We extracted DT research clusters based on the co-occurrence analysis of paper keywords' and the relevant DT constituents. This research helps establish the state-of-the-art of DT in the civil engineering sector and suggests future DT development

A new framework for supporting and managing multi-disciplinary system-simulation in a PLM environment

In order to keep products and systems attractive to consumers, developers have to do what they can to meet growing customers’ requirements. These requirements could be direct demands of customers but could also be the consequence of other influences such as globalization, customer fragmentation, product portfolio, regulations and so on. In the manufacturing industry, most companies are able to meet these growing requirements with mechatronic and interdisciplinary designed and developed products, which demand the collaboration between different disciplines. For example, the generation of a virtual prototype and its simulation tools of a mechatronic and multi-disciplinary product or system could require the cooperation of multiple departments within a company or between business partners. In a simulation, a virtual prototype is used for testing a product or a system. This virtual prototype and test approach could be used from the early stages of the development process to the end of the product or system lifecycle. Over years, different approaches/systems to generating virtual prototypes and testing have been designed and developed. But these systems have not been properly integrated, although some efforts have been made with limited success. Therefore, the requirement exists to propose and develop new technologies, methods and methodologies for achieving this integration. In addition, the use of simulation tools requires special expertise for the generation of simulation models, plus the formats of product prototypes and simulation data are different for each system. This adds to the requirements of a guideline or framework for implementing the integration of a multi- and inter- disciplinary product design, simulation software and data management during the entire product lifecycle. The main functionality and metadata structures of the new framework have been identified and optimised. The multi-disciplinary simulation data and their collection processes, the existing PLM (product lifecycle management) software and their applications have been analysed. In addition, the inter-disciplinary collaboration between a variety of simulation software has been analysed and evaluated. The new framework integrates the identified and optimised functionality and metadata structures to support and manage multi- and inter-disciplinary simulation in a PLM system environment. It is believed that this project has made 6 contributions to new knowledge generation: (1) the New Conceptual Framework to Enhance the Support and Management of Multi-Disciplinary System-Simulation, (2) the New System-Simulation Oriented and Process Oriented Data Handling Approach, (3) the Enhanced Traceability of System-Simulation to Sources and Represented Products and Functions, (4) the New System-Simulation Derivation Approach, (5) the New Approach for the Synchronisation of System Describing Structures and (6) the Enhanced System-Simulation Result Data Handling Approach. In addition, the new framework would bring significant benefits to each industry it is applied to. They are: (1) the more effective re-use of individual simulation models in system-simulation context, (2) the effective pre-defining and preparing of individual simulation models, (3) the easy and native reviewable system-simulation structures in relation to input-sources, such as products and / or functions, (4) the easy authoring-software independent update of system-simulation-structures, product-structures and function-structures, (5) the effective, distributed and cohesive post-process and interpretation of system-simulation-results, (6) the effective, easy and unique traceability of the data which means cost reductions in documentation and data security, and (7) the greater openness and flexibility in simulation software interactions with the data holding system. Although the proposed and developed conceptual framework has not been implemented (that would require vast resources), it can be expected that the benefits in 7 above will lead to significant advances in the simulation of new product design and development over the whole lifecycle, offering enormous practical value to the manufacturing industry. Due to time and resource constraints as well as the effort that would be involved in the implementation of the proposed new framework, it is clear there are some limitations to this PhD thesis. Five areas have been identified where further work is needed to improve the quality of this project: (1) an expanded industrial sector and product design and development processes, (2) parameter oriented system and production description in the new framework, (3) the improved user interface design of the new framework, (4) the automatic generation of simulation processes and (5) enhancement of the individual simulation models