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IMPROVING KNOWLEDGE CAPTURE, ACCESS, AND REUSE BY A MODEL-BASED AND DATA-DRIVEN MANAGEMENT USING THE EXAMPLE OF AVIATION’S RETROFIT

IMPROVING KNOWLEDGE CAPTURE, ACCESS, AND REUSE BY A MODEL-BA...

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ASME 2024 International design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2024

作者： Laukotka, Fabian N. Krause, Dieter Institute of Product Development and Mechanical Engineering Design Hamburg University of Technology Hamburg Germany

ISBN: (纸本)9780791888353

The retrofit of aircraft - the design and installation of new cabins into existing planes, comes with challenges, particularly regarding access to the necessary information. Although aircraft are generally similar, each single one becomes unique over time due to its individual usage and maintenance. While certification requires the changes made to be documented, this is typically done through numerous individual documents that are differentiated by domain, area within the aircraft, revision, and other factors that lead to a fragmentation of information. Engineers rely on implicit knowledge gained from years of experience and common knowledge as well as established structures like the ATA-Chapters, to tediously re-join these fragments and gain an overview of the current state of the aircraft and the relevant documents. This work presents an approach that utilizes ontologies to capture implicit knowledge and combines it with system models defining generic information as well as the definitions of standards that are identical for certain types of aircraft. A web application that functions as an access system is introduced to help engineers filter and identify required information and documents more easily when planning a new cabin. Finally, together with a partner from the industry, this approach is applied to a case study. Copyright © 2024 by ASME.

关键词： Retrofitting

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Controllable self-transport of bouncing droplets on ultraslippery surfaces with wedge-shaped grooves

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Droplet 2024年第2期3卷 138-145页

作者： Chuchen Yue Qingwen Dai Xiaolong Yang Carsten Gachot Wei Huang Xiaolei Wang College of Mechanical and Electrical Engineering Nanjing University of Aeronautics&AstronauticsNanjingChina Institute of Engineering Design and Product Development Tribology Research GroupTU WienViennaAustria

Preventing the accretion of droplets on surfaces is vital and slippery liquid-infused porous surfaces(SLIPS)have promising application prospects,such as surface self-cleaning and droplet *** this work,controllable self-transport of bouncing droplets on ultraslippery surfaces with wedge-shaped grooves is *** impact behaviors of droplets on SLIPS under various impact velocities and diameters are explored,which can be classified as hover,total bounce,partial bounce,Worthington jet,and *** with wedge-shaped grooves were designed to transport accreted *** energy and transport model is established to explain the impact and self-transport mechanism,where the Laplace pressure and moving resistance between droplets play a key ***,SLIPS with branched wedge-shaped grooves were designed for droplet self-transport and demonstrated *** work provides a general reference for spontaneous motion control of sessile droplets,droplets with initial impacting velocity,or even liquid films.

关键词： wedge shaped droplets

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A Reinforcement-Learning-based Parameter Tuning Methodology for Traction Control in the Holistic Railway Digital Twin System 34

A Reinforcement-Learning-based Parameter Tuning Methodology ...

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34th CIRP design Conference, CIRP 2024

作者： Zhou, Shiyang Kugu, Ozan Wurth, Lukas Grafinger, Manfred TU Wien Institute of Engineering Design and Product Development Lehargasse 6/307 Vienna1060 Austria

Holistic railway digital twin systems can optimize railway performance by merging diverse models and data for monitoring, diagnostics, and prognostics. In such systems, traction control is critical to safe and efficient train operations. However, due to the dynamic and non-linear railway operations, achieving the optimal parameter configuration for traction control algorithms remains complex. Conventional approaches to parameter tuning often rely on experience-based manual adjustments or simple optimization algorithms, failing to capture the intricate interplay between various parameters and their impact on overall system performance. To address this, we present a novel methodology that leverages deep rein- forcement learning (RL) techniques to autonomously fine-tune traction control parameters within the holistic railway digital twin system. The core idea involves modeling the traction control in a co-simulation of a well-built multibody dynamic model and a traction controller. Through iterative learning, the RL agent refines its policy, converging toward parameter configurations that enhance both operational efficiency and safety. The RL- based tuning methodology shows significant traction control improvement over conventional methods. The RL-based methodology showcases its adaptability to varying conditions, which is essential for modern railway systems that operate in dynamic and unpredictable environments. © 2024 The Authors. Published by Elsevier B.V.

关键词： Traction control

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COMPONENT TESTING OF SANDWICH STRUCTURES WITH MORE REALISTIC BOUNDARY CONDITIONS 23

COMPONENT TESTING OF SANDWICH STRUCTURES WITH MORE REALISTIC...

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23rd International Conference on Composite Materials, ICCM 2023

作者： Schwan, Lukas Schellhorn, Johann Krause, Dieter Institute of Product Development and Mechanical Engineering Design Hamburg University of Technology Germany

As part of the design process for aircraft cabin monuments, the loads on the fasteners, like inserts are determined using global FEM and are compared with allowables of the fasteners. The allowables are determined in component tests, which currently have highly idealized boundary conditions, resulting in high safety factors being added. In this paper, application-oriented component tests with realistic boundary conditions for insert systems are proposed, experimental investigations are performed on them, and virtual models are implemented. The studies show that the boundary conditions have a great influence on the structural behavior and the failure mechanisms of the sandwich structure and the insert system. The results further prove that tests with application-oriented loading situations should be used to validate detailed virtual models, e.g. to ensure their use as submodels in the global FEM analysis of large sandwich structures. In addition, an example is given to show how such a component test with realistic boundary conditions can be used in the design optimization of the load introduction. © 2023 International Committee on Composite Materials. All rights reserved.

关键词： Boundary conditions

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Integrating Variety, Assembly, and Lightweight design in product Architecture of Cabin Monument 34

Integrating Variety, Assembly, and Lightweight Design in Pro...

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34th CIRP design Conference, CIRP 2024

作者： Sankowski, Olga Heyden, Emil Krause, Dieter Hamburg University of Technology Institute of Product Development and Mechanical Engineering Design Denickestrasse 17 Hamburg20173 Germany

In aircraft cabin design, particularly in the design of aircraft monuments such as galleys, there are specific conflicting objectives that needs to be balanced. The key objectives are to meet customer requirements, optimise assembly processes for increased production and achieve lightweight design for efficient operations. The paper presents a methodical approach that integrates variety, assembly efficiency and lightweight design considerations into the early stages of product architecture design. Using the after monument of the Airbus A320 family as an example, the paper proposes specific module drivers such as 'common unit', 'different specification' and 'load path compatible modules' to guide the design process. These module drivers aim to harmonise the different objectives of stakeholders, including aircraft manufacturers, cabin manufacturers and airlines. The method is illustrated using a geometric representation of product architecture alternatives optimised for each of the variety, assembly and lightweighting objectives. Overall, the paper contributes to the advancement of a stakeholder-oriented modularisation approach and provides a starting point for future developments. It highlights the importance of defining module drivers and visualising the trade-offs to achieve a balanced product architecture in the aviation industry. © 2024 Elsevier B.V.. All rights reserved.

关键词： Cabins (aircraft)

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Structural color prints combined with microlens arrays for sustainable autostereoscopic displays

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Materials Today: Proceedings 2022年 70卷 283-288页

作者： You En Chan, John Ruan, Qifeng Yang, Joel K.W. Engineering Product Development Singapore University of Technology and Design 487372 Singapore Institute of Materials Research and Engineering 138634 Singapore

Structural colour printing is a sustainable printing technology that avoids the use of environmentally harmful dyes or pigments. Structural colours are produced from the interaction of light with nanostructures through physical mechanisms such as scattering, instead of selective absorption caused by chemical properties. Because of these physical mechanisms, structural colours are durable and non-fading, which find them potential applications in artworks and security prints. However, structural colour prints have a fixed two-dimensional image appearance that limits the perception of three-dimensional information. An effective solution is to combine structural colour prints with microlens arrays. This solution enables three-dimensional information to be perceived by the naked eyes under white light illumination without the use of specialized optics. As microlens arrays are compact and lightweight, they can be easily integrated with structural colour prints. Here, we demonstrate that the combination of structural colour prints with microlens arrays produces dynamic moiré and autostereoscopic effects that can be used to display-three-dimensional information. To achieve these effects, we fabricate polymer structures on glass substrate using straightforward fabrication methods (primarily, two-photon polymerization lithography). Furthermore, these structures can be dissolved using organic solvents for recycling the substrate. We believe that this work contributes towards displaying a colourful and three-dimensional world with a sustainable future. © 2022

关键词： Microlenses

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Artificial Intelligence in Cardiology 17

Artificial Intelligence in Cardiology

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Kok, Chiang Liang Koh, Yit Yan Ho, Chee Kit Thanh, Nguyen To Cong Teo, Tee Hui The University of Newcastle College of Engineering Australia Singapore Institute of Technology Engineering Cluster Singapore Singapore University of Technology and Design Engineering Product Development Singapore

ISBN: (纸本)9798331530471

This research explores the integration of artificial intelligence (AI) in cardiovascular medicine, highlighting its potential to revolutionize the diagnosis, treatment, and management of cardiovascular diseases, offering the potential for improved patient outcomes and more efficient healthcare delivery. This paper explores the multifaceted applications of AI in cardiology, including early diagnosis and risk assessment, personalized treatment plans, predictive analytics, and drug development. AI algorithms leverage vast amounts of data from various sources, such as electronic health records, imaging studies, and wearable devices, to provide insights that enhance clinical decision-making. However, the widespread adoption of AI in cardiology faces significant challenges, including data quality and interoperability, ethical concerns surrounding patient privacy, algorithm transparency, and regulatory hurdles. This review emphasizes how collaboration among clinicians, researchers, and policymakers can help overcome challenges to fully leverage AI in cardiovascular care, ultimately enhancing patient outcomes. © 2024 IEEE.

关键词： Electronic health record

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Integration of AI in Smart Electric Drivetrains 17

Integration of AI in Smart Electric Drivetrains

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Kok, Chiang Liang Ho, Chee Kit Lee, Charles Thanh, Nguyen To Cong Teo, Tee Hui The University of Newcastle College of Engineering Australia Singapore Institute of Technology Engineering Cluster Singapore Singapore University of Technology and Design Engineering Product Development Singapore

ISBN: (纸本)9798331530471

This research explores the integration of artificial intelligence (AI) in smart electric drivetrains, highlighting its potential to revolutionize the performance and efficiency of electric vehicles (EVs). By leveraging AI technologies, manufacturers can optimize energy management, enhance predictive maintenance, and improve overall driving experiences, thereby contributing to sustainable transportation solutions. The study addresses the multifaceted benefits of AI integration, including increased range, improved vehicle handling, and reduced operational costs, while also acknowledging the significant challenges that accompany this transformation. These challenges include the complexity of developing reliable algorithms, ensuring cybersecurity, managing data privacy, and overcoming consumer skepticism. Through a comprehensive analysis of the current landscape, the findings suggest that by effectively navigating the challenges and harnessing the power of AI, the automotive sector can significantly advance toward a more efficient, safe, and environmentally friendly future in transportation. © 2024 IEEE.

关键词： Predictive maintenance

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Optimization Strategies for Thermal Management in Electric Drivetrains: Enhancing Performance and Longevity 17

Optimization Strategies for Thermal Management in Electric D...

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Kok, Chiang Liang Kit Ho, Chee Koh, Yit Yan Cong Thanh, Nguyen To Teo, Tee Hui The University of Newcastle College of Engineering Australia Singapore Institute of Technology Engineering Cluster Singapore Singapore University of Technology and Design Engineering Product Development Singapore

ISBN: (纸本)9798331530471

This research investigates how thermal management optimization for electric drivetrains is essential for enhancing the performance, efficiency, and longevity of electric vehicles (EVs). Effective thermal management not only prevents overheating and extends component lifespan but also improves overall vehicle efficiency by optimizing energy usage and extending driving range. The study not only examines various cooling technologies, such as liquid cooling systems, heat pumps, and integrated cooling modules, but also highlights their benefits and associated challenges, including integration complexity, cost, weight, and energy consumption. © 2024 IEEE.

关键词： Electric Drivetrains Electrical Vehicles (EVs) Thermal Management

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Artificial Intelligence in Healthcare Systems 17

Artificial Intelligence in Healthcare Systems

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Siradanai, Thanasitsomboon Kok, Chiang Liang Ho, Chee Kit Koh, Yit Yan Teo, Tee Hui The University of Newcastle College of Engineering Australia Singapore Institute of Technology Engineering Cluster Singapore Singapore University of Technology and Design Engineering Product Development Singapore

ISBN: (纸本)9798331530471

Artificial intelligence (AI) is transforming the healthcare systems by introducing cutting-edge solutions that enhance diagnostic accuracy, optimize clinical workflows, and personalize patient care. This report explores the current and potential applications of AI in healthcare, with a focus on its role in medical imaging, personalized medicine, surgery, drug discovery, workflow management, and virtual healthcare. Using AI's ability to process vast datasets, detect patterns, and assist in decision-making, healthcare systems can achieve improved efficiency and patient outcomes. Despite its benefits, the integration of AI into healthcare faces challenges related to data privacy, algorithmic transparency, biasness, and ethical concerns. Additionally, this report discusses on the future of AI, highlighting its potential in healthcare industries. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Healthcare

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