Large-Scale Stabilized Multi-physics Earthquake Simulation for Digital Twin

2021 ◽  
pp. 3-15
Author(s):  
Ryota Kusakabe ◽  
Tsuyoshi Ichimura ◽  
Kohei Fujita ◽  
Muneo Hori ◽  
Lalith Wijerathne
Keyword(s):  
Large Scale ◽  
Earthquake Simulation ◽  
Digital Twin

Dynamic Experimental Investigation on the Self-Vibration Characteristics of Liquid Storage Tanks Under Seismic Excitations

2013 ◽  
Author(s):  
Zhou Fang ◽  
Zhiping Chen ◽  
Guodong Jia ◽  
Hui Wang ◽  
Xiang Li
Keyword(s):  
Large Scale ◽  
Vibration Characteristics ◽  
The Self ◽  
Earthquake Simulation ◽  
Seismic Excitations ◽  
Storage Model ◽  
Design Standard ◽  
Finite Element Software ◽  
Liquid Storage ◽  
Cylindrical Steel

A large-scale earthquake simulation experiment about the unanchored cylindrical steel liquid storage model tanks has been completed. The self-vibration characteristics of the model tanks with liquid inside were investigated based on the experimental data of the acceleration dynamic response. The seismic table test, the analysis methods are designed and conducted, and experimental results of the model tanks were carefully measured. Furthermore, ANSYS finite element software was used to simulate and calculate the low order natural frequency and fundamental frequency of the model tank systems according to the national design standard. The reasons for the existence of consistency and differences among the results obtained from experiments, numerical simulation and national design standard were discussed.

scholarly journals Understanding design change propagation in complex engineering systems using a digital twin and design structure matrix

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Long Chen ◽  
Jennifer Whyte
Keyword(s):  
Large Scale ◽  
Load Capacity ◽  
Prediction Method ◽  
Change Propagation ◽  
Engineering Systems ◽  
Content Type ◽  
Design Change ◽  
Digital Twin ◽  
Complex Engineering ◽  
Complex Engineering Systems

PurposeAs the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).Design/methodology/approachThe paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.FindingsThe digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.Originality/valueThis research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

scholarly journals Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1717
Author(s):  
Lei Wu ◽  
Jiewu Leng ◽  
Bingfeng Ju
Keyword(s):  
Information Asymmetry ◽  
Large Scale ◽  
Planning Process ◽  
Design Stage ◽  
Precision Machining ◽  
Digital Twin ◽  
Module Design ◽  
Digital Twins ◽  
Ultra Precision ◽  
And Control

Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

A fiber optics enriched Digital Twin for assessment of reinforced concrete structures

2021 ◽  
Author(s):  
Carlos G. Berrocal ◽  
Ignasi Fernandez ◽  
Rasmus Rempling
Keyword(s):  
Reinforced Concrete ◽  
Fiber Optics ◽  
Asset Management ◽  
Web Application ◽  
Large Scale ◽  
Management Strategies ◽  
Reinforced Concrete Beam ◽  
Structural Condition ◽  
Ongoing Research ◽  
Digital Twin

<p>This paper presents the results of <i>SensIT</i>, an ongoing research initiative at Chalmers University of Technology aimed at developing a digital twin concept to improve the asset management strategies of reinforced concrete infrastructure. The developed concept relies on data collected from distributed optical fiber sensors (DOFS), which are then analysed to extract relevant features, such as deflections and crack widths, that can be used as indicators of the structural performance. Thereafter, intuitive contour plots are generated to deliver critical information about the element’s structural condition in a clear and straightforward manner. Last, both raw and analysed data are integrated into a collaborative web application where information can be readily accessed, and results can be visualized directly onto a 3D model of the element. The concept has been tested on a large-scale reinforced concrete beam subjected to flexural loading in laboratory conditions.</p>

scholarly journals Digital Twin-Based Safety Risk Coupling of Prefabricated Building Hoisting

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3583
Author(s):  
Zhansheng Liu ◽  
Xintong Meng ◽  
Zezhong Xing ◽  
Antong Jiang
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Information Integration ◽  
Large Scale ◽  
Security Management ◽  
Information Modeling ◽  
Security Risk ◽  
Safety Risk ◽  
Digital Twin ◽  
Prefabricated Building

Safety management in hoisting is the key issue to determine the development of prefabricated building construction. However, the security management in the hoisting stage lacks a truly effective method of information physical fusion, and the safety risk analysis of hoisting does not consider the interaction of risk factors. In this paper, a hoisting safety risk management framework based on digital twin (DT) is presented. The digital twin hoisting safety risk coupling model is built. The proposed model integrates the Internet of Things (IoT), Building Information Modeling (BIM), and a security risk analysis method combining the Apriori algorithm and complex network. The real-time perception and virtual–real interaction of multi-source information in the hoisting process are realized, the association rules and coupling relationship among hoisting safety risk factors are mined, and the time-varying data information is visualized. Demonstration in the construction of a large-scale prefabricated building shows that with the proposed framework, it is possible to complete the information fusion between the hoisting site and the virtual model and realize the visual management. The correlative relationship among hoisting construction safety risk factors is analyzed, and the key control factors are found. Moreover, the efficiency of information integration and sharing is improved, the gap of coupling analysis of security risk factors is filled, and effective security management and decision-making are achieved with the proposed approach.

A Digital Twin Method for Automated Behavior Analysis of Large-Scale Distributed IoT Systems

2019 ◽  
Author(s):  
Jack Sleuters ◽  
Yonghui Li ◽  
Jacques Verriet ◽  
Marina Velikova ◽  
Richard Doornbos
Keyword(s):  
Behavior Analysis ◽  
Large Scale ◽  
Digital Twin ◽  
Twin Method

scholarly journals Intelligent Logistics for Intelligent Production Systems

2018 ◽  
Vol 20 (4) ◽  
pp. 16-23 ◽  
Author(s):  
Martin Krajcovic ◽  
Patrik Grznar ◽  
Miroslav Fusko ◽  
Radovan Skokan
Keyword(s):  
Large Scale ◽  
Production Systems ◽  
Internal State ◽  
Logistics System ◽  
Digital Twin ◽  
Logistics Systems ◽  
Inadequate Knowledge ◽  
Different Types ◽  
Intelligent Logistics ◽  
In The Beginning

The main topic of the submitted paper is intelligent logistics and its integration into production systems. In the beginning, the problem that lies in the inadequate knowledge of the internal state has been defined. The new society-wide trends that will originate in a few years are also outlined. Those trends will affect factories and their logistics systems on a large scale. Therefore, it is necessary to have a strategy that takes these new trends into consideration. In this manuscript, is described a strategy for intelligent production systems, as well as technologies for different types of production-logistic strategies. Many of these technologies can be applied together with the Digital Twin. The Digital Twin is a new concept in the field of designing production and logistics systems in the factory. Finally, we provide a description of the implementation of the Digital Twin into the production and logistics system.

scholarly journals Context awareness in process monitoring of additive manufacturing using a digital twin

2022 ◽  
Author(s):  
Raven T. Reisch ◽  
Tobias Hauser ◽  
Benjamin Lutz ◽  
Alexandros Tsakpinis ◽  
Dominik Winter ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Process Monitoring ◽  
Context Awareness ◽  
Large Scale ◽  
Spatial Context ◽  
Context Aware ◽  
Cold Metal Transfer ◽  
Digital Twin ◽  
Local Anomaly ◽  
Wire Arc Additive Manufacturing

AbstractWire Arc Additive Manufacturing allows the cost-effective manufacturing of customized, large-scale metal parts. As the post-process quality assurance of large parts is costly and time-consuming, process monitoring is inevitable. In the present study, a context-aware monitoring solution was investigated by integrating machine, temporal, and spatial context in the data analysis. By analyzing the voltage patterns of each cycle in the oscillating cold metal transfer process with a deep neural network, temporal context was included. Spatial context awareness was enabled by building a digital twin of the manufactured part using an Octree as spatial indexing data structure. By means of the spatial context awareness, two quality metrics—the defect expansion and the local anomaly density—were introduced. The defect expansion was tracked in-process by assigning detected defects to the same defect cluster in case of spatial correlation. The local anomaly density was derived by defining a spherical region of interest which enabled the detection of aggregations of anomalies. By means of the context aware monitoring system, defects were detected in-process with a higher sensitivity as common defect detectors for welding applications, showing less false-positives and false-negatives. A quantitative evaluation of defect expansion and densities of various defect types such as pore nests was enabled.

Digital Thread Enabled Manufacturing Automation Towards Mass Personalization

2020 ◽  
Author(s):  
Akhilnandh Ramesh ◽  
Zhaojun Qin ◽  
Yuqian Lu
Keyword(s):  
Information Flow ◽  
Data Exchange ◽  
Large Scale ◽  
Field Performance ◽  
Manufacturing Automation ◽  
Digital Twin ◽  
Digital Twins ◽  
Type Mass ◽  
Mass Personalization ◽  
Self Organizing

Abstract Manufacturing industries are moving towards mass personalization, which refers to the rapid production of individualized products, with large scale efficiencies. This shift from push-type mass customization to pull-type mass personalization will pose critical operational challenges to manufacturing businesses, with complexities ranging from effective requirements elicitation to design, manufacturing, commissioning and after-sales support. Aiming at addressing these challenges, a feasible operational framework for enabling efficient manufacturing automation for mass personalization is proposed in this paper. A key element of this operational framework is the Digital Thread, which streamlines information flow associated with design, manufacturing, maintenance and servicing of a personalized product, each of which are represented as Digital Twins. An As-Designed Digital Twin is created from the beginning of the product co-design process, which then evolves into the subsequent design and manufacturing process and systems resulting in As-Designed Digital Twin evolving to As-Planned Digital Twin and then to As-Built Digital Twin. The personalized product, after it’s commissioning and installation constitutes the As-Maintained Digital Twin of the product, which stores product data related to field performance. The data exchange and communications between these Digital Twins that reside in the various departments of the organization and the management systems create a seamless Digital Thread, capturing the lifecycle information of each personalized product. Personalized product is proposed to be developed through a self-organizing shopfloor, working on a multi-agent mechanism and controlled by a central agent control algorithm, which can coordinate and provide individualized process plans. The Digital Twins, interlinked by a Digital Thread and realized by a self-organizing shopfloor, thus result in increased level of automated control in engineering and manufacturing. To validate the feasibility of this proposed framework, we tested the information flow in the Digital Thread with a case study in the construction industry. Finally the challenges faced by such an automation framework and the area of future work are also discussed.

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