SPECIAL SESSIONS

Authors submitting an abstract in response to one of the special sessions can select the session directly at the Springer portal https://ocs.springer.com/misc/home/EWSHM2020

CONFIRMED SESSIONS

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Title

Organizer 1

Co-Organizers

Contact 1

Other Contacts

1 Seismic structural health monitoring for civil structures Dr. Maria Pina Limongelli Dr. Mehmet Celebi mariagiuseppina.limongelli@polimi.it celebi@usgs.gov
2 SHM in Wind Turbine Technology Dr. Wieslaw Ostachowicz  wieslaw@imp.gda.pl
3 Nonlinear Ultrasonic Guided Wave Methods for SHM Dr. Nitesh Yelve  niteshyelve@fcrit.ac.in
4 Utilization of the TU1402 benchmark towards enhancement of the Value of SHM Dr. Eleni Chatzi  Dr. Helder Sousa Dr. Daniel Straub Dr. Sebastian Thons chatzi@ibk.baug.ethz.ch sebt@byg.dtu.dk mail@hfmsousa.com straub@tum.de
5 Real time monitoring of built infrastructure Vikram Pakrashi and Basuraj Bhowmik  Dr. Eleni Chatzi  vikram.pakrashi@ucd.ie basuraj.bhowmik@ucd.ie chatzi@ibk.baug.ethz.ch
6 Nonlinear SHM methods for high sensitivity Cliff Lissenden    cjl9@psu.edu
7 Towards the next generation of Performance Indicators supported by SHM Helder Sousa Ana Mandic Alfred Strauss  mail@hfmsousa.com mandicka@grad.hr; alfred.strauss@boku.ac.at
8 Standardization and guidelines on SHM and NDT: needs and onging activities Dr. Maria Pina Limongelli S. Kessler A. Strauss H. Wenzel  mariagiuseppina.limongelli@polimi.it alfred.strauss@boku.ac.at sylvia.kessler@tum.de
9 Wireless Sensing Systems for Structural Health Monitoring Hailing Fu  Dr Zahra Sharif Khodaei  H.Fu@lboro.ac.uk  
10 Integrated approaches for SHM: models, data and experiments Dr. Alice Cicirello   a.cicirello@tudelft.nl
alice.cicirello@eng.ox.ac.uk
 
11 Diagnostics and Prognostics of Composite Structures towards a Condition-based Maintenance Framework Prof. Dimitrios Zarouchas Prof. Theodoros Loutas D.Zarouchas@tudelft.nl thloutas@upatras.gr
12 Vehicle-based Indirect SHM for Infrastructure Dr. Hae Young Noh Dr. Abdollah Malekjafarian Dr. Chul-Woo Kim Prof. Yongbin Yang noh@cmu.edu abdollah.malekjafarian@ucd.ie ; kim.chulwoo.5u@kyoto-u.ac.jp ; ybyang@ntu.edu.tw  
13 Guided Waves in Structures for SHM Dr. Wieslaw Ostachowicz Dr. Annamaria Pau wieslaw@imp.gda.pl annamaria.pau@uniroma1.it
14 Smart multifunctional materials and systems for SHM of large structures Antonella D’Alessandro, Filippo Ubertini  Simon Laflamme antonella.dalessandro@unipg.it; filippo.ubertini@unipg.it laflamme@iastate.edu
15 Human Performance Monitoring Prof. Ken Loh   kenloh@ucsd.edu
16 Structural health monitoring of cultural heritage structures Enrique García-Macías, Filippo Ubertini  enrique.garciamacias@unipg.it filippo.ubertini@unipg.it
17 New opportunities for structural health monitoring and artificial intelligence Yung-Bin Lin Tzu-Kang Lin yblin@narlabs.org.tw tklin@nctu.edu.tw
18 Acoustic Emission for Structural Health Monitoring of Civil Infrastructure Dr. Didem Ozevin   dozevin@uic.edu
19 Space-borne health monitoring for civil infrastructure Dr. Giorgia Giardina  Dr. Pietro Milillo  g.giardina@bath.ac.uk Pietro.Milillo@jpl.nasa.gov
20 Autonomous machine learning-enhanced SHM for aerostructures Dr. Abhishek Kundu Prof. Wiesław Ostachowicz Dr. Rhys Pullin KunduA2@cardiff.ac.uk wieslaw@imp.gda.pl; PullinR@cardiff.ac.uk
21 Digital twins for civil and industrial SHM applications Dr. Carlo Rainieri  carlo.rainieri@unimol.it
22 Electromagnetic Surface and Subsurface Sensing Methods for SHM Dr. Tzuyang Yu TzuYang_Yu@uml.edu
 23 Ultrasonic NDTs for the SHM of Train Wheel-Axle and Rail Prof. Donatella Cerniglia Dott. Nicola Montinaro Prof. Gabriella Epasto donatella.cerniglia@unipa.it nicola.montinaro@unipa.it  gabriella.epasto@unime.it
24 NEW TRENDS AND CHALLENGES OF SHM IN CIVIL ENGINEERING Prof Francesco Clementi Prof A. Formisano Prof. Nicola Cavalagni Prof. Gabriele Milani francesco.clementi@univpm.it antoform@unina.it nicola.cavalagli@unipg.it gabriele.milani@polimi.it
25 Infrared Thermography for Structural Health Monitoring Dr. Giuseppe Pitarresi and
Dott.ssa Rosa De Finis
giuseppe.pitarresi@unipa.it
rosa.definis@poliba.it
26 Fiber-optic sensors Branko Glisic Daniele Zonta bglisic@princeton.edu daniele.zonta@unitn.it
27 Robust Statistical and Probabilistic Methods for Structural Health Monitoring John Sakellariou Fotis Kopsaftopoulos Spilios Fassois   sakj@mech.upatras.gr kopsaf@rpi.edu fassois@mech.upatras.gr
28 Optical and computer-vision techniques for SHM & NDT Dr. Alessandro Sabato  Alessandro_Sabato@uml.edu
29 SHM Experiences within CleanSky2 project Prof. Fabrizio Ricci and Prof. Ernesto Monaco fabricci@unina.it ermonaco@unina.it
30 Carbon Nanotube and Graphene-based Sensors for SHM applications Prof. Alfredo Güemes Prof. Dr. Zhongqing Su alfredo.guemes@upm.es  zhongqing.su@polyu.edu.hk
31 Damage Identification Under Changing Environment and operational conditions Prof. Dr. Dongsheng Li Prof. Dr. Maosen Cao Prof. Dr. Peter Kraemer lids@stu.edu.cn cmszhy@hhu.edu.cn peter.kraemer@uni-siegen.de
32 Multifunctional Materials and Composites

Okenwa I. Okoli, Vincent O. Eze, Md Abu Shohag

  okoli@eng.famu.fsu.edu
33 Metamaterials for Autonomous and Sustainable Structural Systems Donghyeon Ryu, Kenneth J. Loh, and Nathan Salowitz donghyeon.ryu@nmt.edu kenloh@ucsd.edu salowitz@uwm.edu
34 Structural Health Monitoring of High-speed Rail and Maglev Systems Professor Yi-Qing Ni ceyqni@polyu.edu.hk
35 Defect imaging algorithms based on guided waves for BVIDs detection: a Round Robin test on a large-scale aeronautical composite structure Drs. Alessandro Marzani and Luca De Marchi alessandro.marzani@unibo.it
l.demarchi@unibo.it

# 1


Seismic structural health monitoring for civil structures

Dr. Maria Pina Limongelli (Politecnico di Milano, Italy)
Dr. Mehmet Celebi (Earthquake Science Center, USGS, Menlo Park, CA)

 

During the last two decades, due to a need and a growing interest by both researchers and professional, seismic structural health monitoring (SHM) has evolved. Numerous monitoring systems installed in structures in various seismic prone countries utilize real-time or near-real-time responses recorded during strong earthquakes to make informed decisions related to the health of their structures . These data have a strategic importance both for the advancement of knowledge on the behavior and performance of structures under strong seismic actions and for the calibration of realistic and reliable numerical models that are aimed to reproduce the structural behavior and to formulate a diagnosis about possible damages. Furthermore, the possibility to assess the seismic vulnerability based on data recorded on the monitored structure opens new avenues in maintenance policies, shifting from a traditional ‘scheduled maintenance’ to a ‘condition-based maintenance’, carried out ‘on demand’ or ‘automatically’, basing on the current structural condition. The aim of this Special Session is to report recent advances in this field and successful applications for civil structures and infrastructures: buildings, bridges, historical structures, dams, wind turbines, pipelines. The session deals with theoretical and computational issues and applications and welcomes contributions that cover, but are not limited to, seismic SHM algorithms for identification and damage detection, requisite strong motion arrays and real time monitoring systems and projects, instrumentation and measurements methods and tools, optimal sensors location, experimental tests, integration of seismic SHM in procedures for risk assessment and emergency management.

Such a session will provide a venue for exchange of information to ongoing developments and assess successes and limited successes of SHM.



# 2


SHM in Wind Turbine Technology

Prof. Wieslaw Ostachowicz

Keywords: wind turbines, sensors, sensing, SHM, damage detection, signal processing

The wind turbine industry has expanded significantly during the last 15 years, and the large offshore wind turbine farms represent important investments. On the other hand, small scale wind turbines represent a segment in the wind energy branch, which is affordable for private individuals and small to medium businesses. The session covers the main Structural Health Monitoring (SHM) topics which are focused on wind turbine structures. The research methodologies used here span a wide range of experimental and numerical approaches in complementary investigations of the rotor with blades, drive train and support structure. The crucial issue is to assess fibre reinforced polymer materials because they are widely used for wind turbine blades. The research methodologies should span a wide range of topics from piezoelectric transducers, elastic waves propagation phenomenon, fibre Bragg gratings, structural vibrations analysis, electro–mechanical impedance method, acoustic emission, damage mechanics, 3D laser vibrometry applications, vibration–based methods, and others. The aspects dedicated to operation, maintenance and the risks associated with damages leading to failure is the crucial issue and needs more advanced technologies. The combination of proposed techniques allows performing efficient both local and global SHM of the structure. It also includes a variety of techniques being related to diagnostics (damage size estimation and damage type recognition) and prognostics. A promising combination of selected techniques should lead to an innovative approach to ensure safe operation of the structure.



# 3


Nonlinear Ultrasonic Guided Wave Methods for SHM

Dr. Nitesh P. Yelve, PhD (Fr. C. Rodrigues Institute of Technology, Vashi Navi, Mumbai, India)

 

Ultrasonic guided waves can travel a long distance without much attenuation and thus, they can scan relatively larger area. Their interaction with small breathing damages, such as closed crack and delamination, produces different nonlinear effects based on the method of interrogating the specimen. These nonlinear effects include higher harmonics, subharmonics, mixed frequency response, and change in resonance frequency. Nonlinear ultrasonic guided wave methods are not only capable of detecting macro damages but also micro damages as small as grains in the material. These techniques can be effectively used for characterizing the materials in order to understand the quality of material produced or being used in an application. The range of application of these methods is large which include SHM of planar structures used in aircrafts, automobiles, power plants, etc. and elongated structures such as rails, pipes, ropes, etc.

A considerable pioneering laboratory work has happened in this domain. The researcher are now working in this domain with the practical perspectives. The objectives include development of:

  • Effective algorithms for damage localization,
  • Energy efficient transducers for actuating and sensing the waves,
  • Damage indices specific to the type of wave used,
  • Techniques for interrogating planar and elongated structures with extended projections/stiffeners,
  • Signal processors with integrated Internet of Things,
  • On-board/insitu damage detection kits, etc.


# 4


Utilization of the TU1402 benchmark towards enhancement of the Value of SHM

Dr. Eleni Chatzi (Swiss Federal Institute of Technology – ETH Zurich)
Dr. Helder Sousa (HS Consulting Ltd / BRISA Group, Portugal)
Dr. Daniel Straub (Technical University of Munich – TUM)
Dr. Sebastian Thons (Technical University of Denmark – DTU)

 

As part of COST Action TU1402 on Quantifying the Value of Structural Health Monitoring (SHM), a simulated benchmark has been established with the aim to serve as a reference case-study for validation of the SHM methods and decision-making tools relying on the Value of Information stemming from monitoring.

Available in https://github.com/ETH-WindMil/benchmarktu1402, the evolution and dissemination of the TU1402 benchmark has been set on the principle of joint-collaboration between partners of the TU1402 action, by assimilating both academic and industrial know-how. The considered system, which serves as a virtual monitored bridge, is modelled with an open access Finite Element code, which is supplemented with a Graphical User Interface (GUI). This enables extraction of modal properties and dynamic response (time-history) data for a number of predefined damage patterns and diverse operational as well as environmental scenarios.

Inspired from this initiative, this special session invites contributions adopting the COST TU1402 numerical benchmark study for:

  • Verification & Validation of methods and tools for system identification & damage detection
  • Reliability Analysis and Decision Support tools for Infrastructure Management
  • We further invite contributions for enhancement of the existing functionalities of this open-source tool with new features and potential applications.
  • We particularly welcome utilization of the benchmark in the context of the Value of Information from SHM


# 5


Special session: Real time monitoring of built infrastructure

Vikram Pakrashi, Basuraj Bhowmik (Dynamical Systems and Risk Laboratory University College Dublin, Ireland)
Eleni Chatzi (Structural Mechanics and Monitoring, ETH Zurich, Switzerland)
Emails: vikram.pakrashi@ucd.iebasuraj.bhowmik@ucd.ie; chatzi@ibk.baug.ethz.ch;

 

Summary: The aim of this special session is to report recent advancements and applications of real time structural health monitoring (SHM) for engineering structures. The session deals with the theoretical and computational issues related to online SHM algorithms for damage identification, stochastic simulation and techniques for recursive modal identification. Contributions are welcome, but are not limited to, real time damage detection algorithms and monitoring systems, recursive modal identification strategies, video and image based online monitoring of systems, strain based identification, energy harvesting techniques for online detection, numerical and computational investigation for online SHM, real time experimental SHM techniques, effect of operational conditions on real time SHM, integration of SHM in risk assessment, estimation of remaining useful life of existing structures based on real time outputs, optimal sensor location and online wireless sensing. The 10th edition of EWSHM will be the ideal forum for sharing and disseminating results of cutting-edge scientific research on real time SHM. The expected attendance of key players from both the development and application areas will offer a comprehensive review on the state-of-the-art view on online monitoring techniques for civil structures and mechanical systems.



# 6


Nonlinear SHM methods for high sensitivity

Cliff J Lissenden (Professor of Engineering Science and Mechanics, Pennsylvania State University)

Topic Description: early detection of material degradation is a key to a paradigm shift in life-cycle management in many industries; advances are sought in transducers, measurement techniques, signal processing, and correlating measurements with material microstructure.



# 7


Towards the next generation of Performance Indicators supported by SHM

Helder Sousa (HS Consulting Ltd / BRISA Group, Portugal)
Ana Mandic (University of Zagreb Faculty of Civil Engineering, Croatia)
Alfred Strauss (University of Natural Resources and Life Sciences, Austria)

Most roadway bridges belonging to the so-called core of the European transport infrastructure have been built as part of the post- World War II reconstruction effort. This means that society is progressively facing the beginning of the end of their designing lifetime, and, from a more technical point of view, bridge management is becoming more and more influenced by lifecycle multiobjective performance criteria. For an efficient approach, this needs to be wisely reflected on the selection and proper quantifying of so-called Performance Indicators to assist bridge management and mainly from a sustainability point of view. This is in line with the 2030 Agenda for Sustainable Development promoted by the UN in 2015 towards a sustainable planet.
In this context, and further to an up-to-date European review of Performance Indicators towards a sustainable road bridge management , this session welcomes to those with interest to give evidence on the effective utilization of SHM techniques (including NDT methods) towards a better quantification of the aforementioned Performance Indicators. In simple words, contributions that are able to show clearly the assessment of a specific Performance Indicator supported with and without the aforementioned technique(s) are ideally positioned to take part on the next generation of Performance Indicators supported by SHM.



# 8

 

Standardization and guidelines on SHM and NDT: needs and onging activities

M.P. Limongelli (Politecnico di Milano)
S. Kessler (Helmut Schmidt University / University of the Federal Armed Forces Hamburg)
A. Strauss (Boku University)
H. Wenzel (WENZEL Consulting Engineers GmbH)

Structural health monitoring (SHM) and non-destructive testing (NDT) are strategic tools for the non invasive assessment of the structural health state. Whilst research on these topics has seen important developments in the last 30years, their large scale application proceeds with a slower pace. The developement of standards and guidelines can provide an effective support to designers and managers and foster the practical implementation of these technologies to real world cases.

The aim of this Special Session is to bring together researchers and professionals to foster discussion and exchange of information about the ongoing activities related to the development of standards and guidelines on SHM and NDT.

Potential topics of the Session include, but are not limited to: sensors, structural and damage identification, SHM supported life-cycle performance assessment, design by testing, NDT testing, SHM supported decision making, uncertainties quantification, performance indicators, case studies.



# 9

 

Wireless Sensing Systems for Structural Health Monitoring

 Dr. Hailing Fu (Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK)

Dr. Zahra Sharif-Khodaei (Department of Aeronautics, Imperial College London, London, SW7 2AZ, UK)

 

Keywords: Wireless Sensor Networks, SHM, Low-Power Sensing, Energy Harvesting, Wireless Communication

 

Structural Health Monitoring has been one of the major technologies to detect, evaluate and guarantee structural integrity. This technology has also been investigated and applied in many fields, including aircraft, wind turbines, railway systems and bridges. One of the drawbacks of actual SHM systems for large-scale monitoring applications is wiring complexity and associated extra weight. This challenge can be solved through wireless sensors using specific sensors design, miniaturization and wireless technology. Power consumption would be another big concern in wireless sensing systems for SHM for long-term distributed operations. How to design energy efficient wireless sensing system is one of the challenges. Energy harvesting, as an alternative to conversion batteries, would be a solution to implement self-powered solutions. The aim of the special session is to bring experts in wireless sensing systems for SHM to exchange information and generate new ideas in novel wireless sensing systems for SHM. The scope, therefore, includes, but not limited to:

  • New Miniaturized Sensor Design
  • Low power sensing systems
  • Wireless sensors
  • Energy harvesting for self-powered systems
  • Wireless data acquisition system development
  • Applications of wireless systems in SHM


# 10

 

Integrated approaches for SHM: models, data and experiments

Dr. Alice Cicirello (Associate Professor at TU Delft, Netherlands – Visiting Fellow at University of Oxford)

 

There is the need for developing robust Structural Health Monitoring (SHM) tools for timely decision making and maintenance scheduling. Integrating operational data with mathematical models and laboratory experiments for developing effective structural health monitoring approaches is one of the current main research challenges in SHM. This is of particular importance for complex and critical engineering structures such as aerostructures, bridges, nuclear power plant and wind turbines to name a few. This special session invites contributions on techniques and industrial applications showcasing recent advances in the use of integrated approaches for SHM combining mathematical models of structures, recorded data (signals and/or reports) processing techniques and laboratory experiments.



# 11

 

Diagnostics and Prognostics of Composite Structures towards a Condition-based Maintenance Framework

Prof. Dimitrios Zarouchas (Delft University of Technology, The Netherlands)
Prof. Theodoros Loutas (Patras University, Greece)

 

Key words: Composites, diagnostics & prognostics, SHM, stochastic modelling, data-driven & physics-based models, feature extraction, fatigue & impact damage monitoring

Prognostics of the remaining useful service life, residual strength and residual stiffness of composite structures based on SHM measurements, is a new dynamically rising field towards a condition-based maintenance framework for light-weight composite structures.
This special session will gather the research community active in the area of damage diagnostics & prognostics, address the challenges, discuss the present as well as future trends and exchange ideas & experiences across different engineering applications. Studies in the area of prognostics of composite structures subjected to various types loading, i.e. fatigue, impact, using data-driven and physics-based models or a combination of those models, are expected to be presented in this session.
Emphasis is given in the utilization of various SHM techniques, different modeling philosophies (data-driven/physics based) and machine learning algorithms. Issues of optimized feature extraction towards multi-sensor data fusion and more effective diagnostic/prognostic schemes are also of potential interest.



# 12

 

Vehicle-based Indirect SHM for Infrastructure

Dr. Hae Young Noh (Civil and Environmental Engineering, Carnegie Mellon University, United States)

 

Advances in structural health monitoring (SHM) have enabled automated diagnosis of damage in infrastructure, but efficient and scalable solutions have been limited. Recently, vehicle-based indirect SHM approaches have received increasing attention as a practical solution due to their advantages in cost, low-maintenance, and scalability. These approaches assess infrastructure states and damage using the data collected from sensors on board. In this Special Session, we invite papers in the areas of vehicle-based indirect monitoring of infrastructure, including bridges, roadways, rail tracks, dams, pavement, etc. Hybrid approaches combining vehicle sensor data and other sensing modalities, as well as crowd-sourcing approaches fusing data from multiple vehicles are also welcomed.



# 13

 

Guided Waves in Structures for SHM

Prof. Wieslaw Ostachowicz (Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Poland)
Dr. Annamaria Pau (Sapienza University of Rome, Department of Structural and Geotechnical Engineering)

 

Key words: sensors, sensing, SHM, damage detection, signal processing

The session covers the main disciplines which are based on guided waves propagations in both isotropic and anisotropic materials. Authors are encouraged to submit papers that include the elastic waves propagation phenomenon which span a wide range from linear and non–linear, 1D, 2D and 3D, time or frequency, experimental and numerical approaches in complementary investigations of structures. The proposed novel techniques should allow to perform efficient both local and global SHM technologies. Considered above investigations are intended to develop variety of techniques being related to diagnostics (damage size estimation and damage type recognition) and prognostics. Promising combination of investigated techniques should lead to an innovative approach to ensure safety operation.



# 14

 

SMART MULTIFUNCTIONAL MATERIALS AND SYSTEMS FOR SHM OF LARGE STRUCTURES

Antonella D’Alessandro (1), Simon Laflamme (2), Filippo Ubertini (1)
(1) University of Perugia – Department of Civil and Environmental Engineering
(2) Iowa State University – Department of Civil, Construction, and Environmental Engineering

 

In recent years, the attention to safety and service performance of large civil engineering structures (such as bridges, dams, wind turbines, and energy systems) has increased dramatically as a result of alarming degradations due to ageing. For this reason, structural health monitoring (SHM) systems of various types and nature are under continuous development with the common objective to achieve a rapid and effective automated performance evaluation, including fault/damage identification and prognosis, to improve the efficiency of maintenance operation activities. Nevertheless, important difficulties in monitoring these large-scale structures are limiting the broad implementation of effective SHM systems, primarily due to costs, the localized nature of the measurements obtained leveraging off-the-shelf sensing technologies, and the inability of global analysis algorithms to detect local damage.

A solution that is currently attracting research attention is the integration of smart multifunctional materials and SHM systems. These technologies leverage state-of-the-art engineering advances, including new nano-/micro- structural composites (e.g. smart concretes, smart bricks, and smart pavements), real time vibration-based systems, novel methods for system identification and operational modal analysis, modern information and communication systems, machine learning and signal processing technologies, advanced structural analysis, and more. Despite the relevant scientific efforts in the field, several challenges in smart materials and smart SHM systems still need to be addressed, including the improvement of sensor systems, accuracy of data sampling, development of effective diagnostic methods, analysis and management of big data for structural performance evaluations, etc.
In this context, this special session will be a forum of discussion about recent results and applications of smart materials and systems for SHM of large scale structures.
The topics include, but not limited to, the following items:

  • Self-sensing structural composites for SHM applications
  • Skin-type sensors and large area electronics
  • Smart sensors
  • Advanced modeling
  • Intelligent damage identification systems and algorithms
  • New vibration-based SHM methods
  • Field applications


# 15

 

Human Performance Monitoring

Kenneth J. Loh (Department of Structural Engineering, University of California, San Diego)

 

Structural health monitoring and damage prognosis research has been targeted for ensuring structural integrity and safety. However, monitoring the “human structure” and how they interact with and control artificial structures is crucial for optimizing system performance and functionality. Often, both the human operator and structure need to be treated as a system and evaluated together, since failure of any one of these could result in mission failure or poor performance. Recently, there has been growing interests in developing new or adapting existing sensing technologies/methods for monitoring human performance. This special session is soliciting contributions focused on sensing the physiological and psychological conditions of human performance, as well as the interactions/interfaces between humans and artificial structural systems. Examples of specific topics of interest include: Bio-marker and bio-molecular sensing; Body sensor networks; Flexible electronics and sensors; Digital health; Human protective and enhancement systems; Human-machine interfaces and numerical modeling; Human-prosthetic interfaces; Human physiological monitoring; Human biomechanical modeling; Implantable sensors; In vivo and in vitro applications; Noninvasive and/or noncontact sensing; Textile-based sensors; and Wearable technologies.



# 16

 

Structural health monitoring of cultural heritage structures

Enrique García-Macías, Filippo Ubertini (University of Perugia – Department of Civil and Environmental Engineering)

 

 

The growing concern about the vulnerability of cultural heritage structures (CHS) to ageing deterioration, climate change, earthquakes and other extreme natural events, as well as their manifold cultural and economic values, has fostered the use of non-destructive testing and preventive conservation within the framework of structural health monitoring (SHM). Moreover, the particularities often related to the monitoring of historical buildings, including, among others, significant material uncertainty, complex geometry, access difficulties to certain parts of the structure, and low levels of excitation, make the SHM of CHS deserve special considerations. In particular, the strong dependence of the intrinsic stiffness of CHS to environmental conditions makes the deployment of long-term monitoring systems become imperative in most cases to achieve an effective structural assessment. The data collected by such systems allow for distinguishing between environment- and damage-induced alterations in the structural response, making it possible to attain an advanced knowledge on the integrity of CHS and to perform damage identification tasks. This Special Session is aimed at presenting and disseminating some of the most recent advances in the field of SHM of CHS. The session encompasses from theoretical/computational issues to practical applications, and specially welcomes contributions coping with:

  • SHM algorithms for system and/or damage identification of historic structures
  • advanced instrumentation and sensing techniques
  • data fusion of measurements from sensors of diverse physical nature
  • seismic interferometry
  • surrogate models for system identification
  • advanced modeling of historic structures for SHM including soil-structural interaction
  • optimal sensor placement techniques
  • monitoring applications and pilot case studies
  • SHM integration in risk and emergency management.


# 17

 

New opportunities for structural health monitoring and artificial intelligence

Yung-Bin Lin (National Center for Research on Earthquake Engineering, Taipei, Taiwan)
Tzu-Kang Lin (National Chiao Tung University, Hsinchu, Taiwan)

 

 

Artificial Intelligent (AI) Technology has been becoming more practical and important due to their enhanced accuracy and extended applications in recent years. This Special Session will bring together leading academics and practitioners from the fields of artificial intelligence relative learning technology, wireless sensor network, innovate sensor designed, smart infrastructure, structural health monitoring system, and multiple hazards monitoring assessment. The Special Session will reflect the advances and current challenges in structural health monitoring, sensor system, seismic effects, retrofit assessment, and asset management. Contributions on investigations related to the theoretical development, experimental studies and particularly practical applications of structural health monitoring techniques will be incorporated in the Special Session. This session aims to attract academics, researchers, students and professional engineers involved in the advancement of monitoring solutions for critical infrastructures.



# 18

 

Acoustic Emission for Structural Health Monitoring of Civil Infrastructure

Didem Ozevin (Department of Civil and Materials Engineering, University of Illinois at Chicago)

 

Acoustic Emission is capable of monitoring inaccessible areas, detecting hidden defects, pinpointing the defect location and severity. With the technological advancement of data transfer rate, wireless communication, on-chip decision making, and low cost instrumentation, AE has significant progress towards SHM with fast decision making. It is recognized by the AE community that SHM is one of the most critical AE topics to be studied and progressed towards standardization. The AE method has been applied to variety of civil infrastructure such as bridges, pipelines, dams and nuclear power plants. The objective of this special session is to discuss SHM-related AE challenges such as big data handling, in situ decision making, influence of materials and configurations to AE, sensor durability for long term monitoring and data throughput. In this special session, we invite papers on addressing those challenges, and AE case studies from laboratory scale experiments towards SHM and field implementations.



# 19

 

Space-borne health monitoring for civil infrastructure

Giorgia Giardina (BRE Centre for Innovative Construction Materials, Department of Architecture and Civil Engineering, University of Bath, UK)
Pietro Milillo (NASA Jet Propulsion Laboratory, United States)

 

 

In the last decade, the launch of second-generation Synthetic Aperture Radar (SAR) satellites and the parallel evolution of Interferometric SAR (InSAR) processing techniques have made available an unprecedented amount of high-quality measurements of earth surface displacements on large areas. Initially exploited for the evaluation of geophysical phenomena like earthquakes, landslides and volcanos, these measurements are increasingly applied to monitor buildings and infrastructure deformations. With a sensitivity to millimetre displacements, high-spatial density and weekly revisit time, SAR satellites are now a valuable tool in support to structural conditions assessment. This session aims at discussing the most recent challenges and development in InSAR applications to the health monitoring of structures. Topics cover and are not limited to advances in the processing algorithms and application case studies, including tunnels, bridges, dams, pipelines, etc.



# 20

 

Autonomous machine learning-enhanced SHM for aerostructures

Dr. Abhishek Kundu and Dr Rhys Pullin  (Cardiff School of Engineering, Cardiff University, UK)

Prof. Wiesław Ostachowicz (Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Poland)

 

Aerostructures operate in a safety-critical environment and the monitoring, damage detection and prognostics of such structures is of paramount importance. The futuristic vision of smart, self-monitoring aerostructures envisions autonomous SHM systems operating with high reliability and minimal human intervention. The development of such autonomous SHM systems hinges on developing a wide range of technologies within research themes ranging from a) advanced modelling to realize digital equivalents of the operational structures to b) integration of in-situ sensor data for mapping the measure signal features to structural health metrics and c) a robust identification and predictive framework for incipient damage characteristics and its evolution.
The special session aims to bring experts on such wide ranging themes to facilitate dialogue and communicate novel ideas into the potential and scope of such technologies being developed. The session focuses on, but is not limited to, the following topics.
• Machine learning in SHM
• Advanced modelling of composite structures
• Smart sensing and feature extraction
• Optimization of sensor placement
• Inverse problems for damage detection
• Uncertainty quantification in SHM



# 21

 

Digital twins for civil and industrial SHM applications

Carlo Rainieri (University of Molise, Campobasso, Italy)

 

Since the early applications of SHM to civil and industrial structures and infrastructures, the operational/environmental perturbations on the measurements have been recognized as critical factors affecting the ability to identify structural damage. As a consequence, the current structural condition as well as relevant historical data has to be taken into account to have an up-to-date representation, namely a model, of the actual physical system in operation. Digital twins can be therefore used to evaluate the current condition of the system, and more importantly, predict future behavior, detect anomalies, or optimize maintenance operation.

Building Information Modeling (BIM) is currently showing a potential to support maintenance (6D BIM); however, although BIM procedures are reasonably well established, their extension to the facility management stage still represents an open issue, in particular when the digital models have to be complemented with the information gathered by SHM systems.

This Special Sessions aims at exploring the opportunities related to the development of digital twins in the field of SHM and their applications to civil and industrial structures and infrastructures. They can also take advantage of the integration of advanced modeling approaches, either physics-based or statistical (or even a combination of the two), with effective construction management tools (6D BIM).

In this framework, strategies to discriminate environmental based effects from damage induced changes in the measurements, novel approaches to damage identification based on the digital twin concept, and, with the background of increasing affordability of sensing and computing technology, efforts aimed at increasing sensitivity, reliability and robustness of the above mentioned procedures will be the object of this special session.

The Special Session will provide a platform to introduce new concepts, new technology, and new method developments in civil and industrial engineering also through the integration of SHM with BIM technologies. Contributions and discussion should be fruitful not only for researchers but for industry, too, and they will increase the acceptance of SHM for early damage identification remarkably.



# 22

 

Electromagnetic Surface and Subsurface Sensing Methods for SHM

Prof. Tzuyang Yu (Department of Civil and Environmental Engineering, University of Massachusetts Lowell, USA, Yu)

 

Key words: Microwave, radar, ground penetrating radar, synthetic aperture radar, SHM, infrastructure, remote sensing, dielectric modeling

 

Ageing and deterioration of many engineering structures is usually a long-term process taking place from few years to few decades. To provide early-stage warning, effective and efficient applications of innovative sensors for surface and subsurface inspection for damage detection and condition assessment is indispensable. In recent years, advances in ground-coupled, air-coupled, and remote sensing electromagnetic sensors such as ground penetrating radar (GPR) and synthetic aperture radar (SAR) have enabled scientists and engineers to better detect subsurface damage and define structural deterioration. In this session, theoretical advances, numerical simulation, and experimental studies in radar imaging, signal processing, signal denoting, signal focusing, adaptive imaging, hardware design, algorithm development, and field applications are reported and discussed. Dielectric modeling work on multi-phase engineering materials for better damage detection and condition assessment using electromagnetic sensors is also encouraged.



# 23

 

Ultrasonic NDTs for the SHM of Train Wheel-Axle and Rail

Prof. Donatella Cerniglia and Dott. Nicola Montinaro (Engineering department, University of Palermo, Italy)
Prof. Gabriella Epasto (Engineering department, University of Messina, Italy)

 

Non Destructive Testings are used in transportation industries to evaluate abnormalities and/or defects in components and systems, without causing any damage.
In the railway field, human safety and service life of axles, wheels and rails are an important topic, taking also in consideration that such components have to bear severe static and dynamic loads deriving from their operative conditions. Indeed, in-situ conditions can lead to fatigue damage, rolling contact fatigue, impact damage due to railway ballast projection and corrosion. All these events can provoke cracks initiation and/or early failure.
Ultrasonic NDT methods rely upon the use of ultrasound waves to examine train wheel-axle and rail, without any alteration of materials and their geometry.
In Ultrasonic NDTs, high frequency sound waves are generated, propagated and received to detect and characterize internal and superficial defects in the tested part. There are several techniques that use the generation and reception of ultrasonic waves, even in complicated structures, where both waves generation and reception are a very difficult task.
The ultrasonic NDTs can be used both during the production of the Wheels, Axle and Rails (static analysis) and during the periodic services (i.e. in-situ – dynamic analysis).
Potential topics of the Session can be:

  • Use of contact transducers;
  • Phased array technique;
  • Non-contact detection using laser or other non-contact transducers;
  • Damage detection;
  • Fatigue life assessment;
  • NDT testing.


# 24

 

NEW TRENDS AND CHALLENGES OF SHM IN CIVIL ENGINEERING

Prof. Francesco Clementi (Department of Civil and Building Engineering, and Architecture, Polytechnic University of Marche, Ancona, Italy)
Prof A. Formisano (Department of Structures for Engineering and Architecture, University of Naples “Federico II”, Naples, Italy)
Prof. Nicola Cavalagli (Department of Civil and Environmental Engineering, University of Perugia, Perugia, Italy)
Prof Gabriele Milani (Department of Architecture, Built Environment and Construction Engineering, Technical University of Milan, Milan, Italy)

 

Structural Health Monitoring (SHM), often associated with robotic and drone systems (UAV) platforms, is becoming an increasingly frequent issue in Civil Engineering. Ordinary and historic constructions (e.g. churches, monuments, towers, bridges and infrastructures), are frequently struck and harmed by earthquakes, but also their structural capacity can be progressively reduced by several forms of degradation. In the framework of the early detection of the structural damages, SHM (involving the characterization strategy and the damage detection) are even more frequently applied, in order to reduce the monitoring costs and also to easily reach the less accessible parts of the constructions. Moreover, also the seismic, hydraulic and geotechnical risk can be studied and evaluated according to autonomous systems, remote sensing and UAV platforms. Aim of this Mini-Symposium is to encompass methodological aspects, recent developments and applications of structural health monitoring studies in all the different fields of the Civil Engineering, focusing on both the theoretical, computational, experimental and practical aspects and on the state-of-the-art review of the scientific literature. Topics to be covered, but not exclusive to, are:

  • SHM associated with UAVs Photogrammetry and Geocomputing for Hazards and Disaster Risk Monitoring
  • Contribution of contemporary sensors to the management of Earthquake Emergency Response
  • Drones and sensors to cope with the natural disasters: earthquakes, landslide and flood monitoring
  • Multi-disciplinary strategies of structural monitoring and preventive conservation
  • Vibration-based SHM strategies under changing environment and/or operational conditions
  • Detection, localization and/or quantification of damages in existing structures
  • Design, implementation and management of dynamic monitoring systems
  • Vibration-based tuning of FE model
  • Innovative sensing technologies for infrastructures and historic structures
  • Mechanical characterization of materials by ordinary and innovative methods


# 25

 

Infrared Thermography for Structural Health Monitoring

Dr. Giuseppe Pitarresi (Department of Engineering, University of Palermo)
Dott.ssa Rosa De Finis  (Politecnico di Bari – Italy)

 

The rise of anomalous thermal contrasts or temperature changes is a common indicator of an emerging or existing fault in materials and structures. State-of-the-art Infrared cameras are now able to detect and monitor such thermal signatures with high resolution and at high speeds. Moreover, IR cameras operate in real time, in a non-contact way, are easy to setup and can work in various environments, providing detailed full-field thermal maps over wide fields-of-view.

In the last two decades, many different methodologies have been proposed, trying to exploit the capabilities of modern IR camera systems to monitor or enquire the health of a structure/material under natural conditions (Passive Thermography) or induced heating/mechanical stimulation (Active Thermography). Such applications may have different focuses, e.g.: SHM, NDT, material characterisation, structural stress analysis, but their common approach lies on trying to correlate the natural or stimulated thermal response of the structure to its integrity.

Aim of this thematic session is to bring together different experiences, latest developments and case studies on NDT, SHM and Structural Characterisation via Infrared Thermography, in order to foster cross-fertilisation of good practises and ideas for further advances on the use of IR cameras in structural monitoring.

Some topics of special interest will comprise:

  • Material-based Thermography: material direct or indirect embedded heat sources;
  • Use of optical and electromagnetic heat sources for active IR NDT;
  • Evaluation of the Thermoelastic Signal as a damage indicator by means of economic and compact micro-bolometer cameras;
  • Adaptation of small size and low capital-cost micro-bolometer IR cameras into active IR NDT;
  • Detection and characterisation of fatigue cracks severity through Thermoelastic Stress Analysis;
  • Passive thermography for the early detection of equipment flaws and faulty industrial processes.


# 26

 

Fiber-optic sensors

Branko Glisic (CEE, Princeton University, E330 EQuad, Princeton, NJ 08544, USA)
Daniele Zonta (University of Trento -Italy)

 

Fiber-optic sensors (FOS) have been commercially available since 1990’s. Nevertheless, research and development activities related to FOS kept growing over the last two decades. Thus, on one hand, there is large variety of sensors installed in real structures worldwide and a large body of research regarding FOS applications have been generated; on the other hand, research on hardware (sensors and reading units) has also been carried out in pursuit of better performing monitoring systems. The aims of this special session are (1) to assess the state of the art of the FOS, (2) their applications in real-life settings, (3) the algorithms associated with their data analysis and management, and (4) to cross-fertilize the FOS research field through an exchange of ideas. Contributions on any of above topic are welcome, as well as any other topic involving FOS.



# 27

 

Robust Statistical and Probabilistic Methods for Structural Health Monitoring

Prof. John Sakellariou (Mechanical Engineering and Aeronautics, University of Patras, Patras, Greece)
Prof. Fotis Kopsaftopoulos (Mechanical and Aerospace Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA)
Spilios Fassois (Mechanical Engineering and Aeronautics, University of Patras, Patras, Greece)

 

Keywords: statistical methods, probabilistic methods, uncertainty modeling, data-based methods, vibration-based methods, stochastic systems

In recent years, we witness the development of novel and disruptive mechanical, aerospace and civil structural systems, while at the same time a large part of existing systems is reaching the end of its design life cycle. Therefore, our society is now met with the need for intelligent structural systems that possess robust and accurate structural health monitoring (SHM) capabilities within complex dynamic environments. The main challenge that has to be addressed for the successful development and deployment of such SHM systems is related to uncertainty: all systems are inherently characterized by uncertainty due to a number of factors, including lack of system knowledge and physical insight, limited data and information on operating and environmental conditions, complex dynamic nonlinear and/or time-varying behavior, manufacturing discrepancies, and aging effects.

 

In an effort to gather and summarize the relevant recent advances of the SHM community, this Special Session invites novel contributions in the areas of statistical and/or probabilistic SHM methods that may enable effective, robust, and accurate damage detection, identification (localization) and quantification for mechanical, aerospace and civil structural systems. Topics of interest include all modern SHM technologies integrated within a statistical and/or probabilistic framework. Indicative topics include:

  • Novel ideas on vibration-based SHM methods
  • Advanced statistical time-series methods for SHM
  • Experimental studies and applications of statistical/probabilistic SHM methods
  • Acoustic and ultrasonic wave-propagation-based methods for “local” diagnostics
  • Uncertainty modeling and quantification
  • SHM methods incorporating stochastic system identification techniques
  • Learning from data: statistical and machine learning approaches for SHM
  • Novel data-based methods for SHM; integration of data- with physics-based approaches
  • Probability of Detection (POD) for SHM


# 28

 

Optical and computer-vision techniques for SHM & NDT

Dr. Alessandro Sabato (Department of Mechanical Engineering – University of Massachusetts Lowell, USA)

 

Advancements in digital cameras and image-processing algorithms have made computer-vision methods attractive tools for structural health monitoring (SHM) and non-destructive evaluation (NDE) of aerospace, civil, and mechanical engineering systems. Because of their inherent advantages, optical and computer-vision-based inspections can overcome some of the limitations that characterize traditional and contact-type approaches (e.g., discrete number of measurement points, costs, installation challenges, the necessity for auxiliary instrumentations, interferences with the monitored structure, etc.). Thus, this technology has become a valid alternative for addressing the resilience, sustainability, and safety issues of aging structures and infrastructure systems.

This session aims to serve as a platform to explore recent theoretical and experimental efforts as well as future directions in computer-vision and optical techniques for SHM and NDE. Scholars are invited to contribute with original research, case studies, industrial applications, and advancements over the current state of the art. Potential topics include but are not limited to:

 

  • Digital Image Correlation SHM and NDE
  • Vision-based displacement and vibration measurement, modal analysis, and system identification
  • Integration vision-based techniques on autonomous and unmanned vehicles for remote inspection
  • Advancements in optical sensing and image-processing
  • Photogrammetric measure for structural systems assessment
  • Machine learning, deep learning, and convolutional neural networks for computer-vision SHM and NDE


# 29

 

SHM Experiences within CleanSky2 project

Prof. Fabrizio Ricci and Prof. Ernesto Monaco (University of Naples, Italy)

 

CleanSky2 (CS2) is a Joint Technology Initiative (JTI), a public-private partnership bringing together companies, universities, public laboratories, innovative SMEs and the European Commission. It develops and demonstrates break-through technologies for the civil aircraft market to cut aircraft emissions and noise, and secure the future international competitiveness of the European aviation industry.

CS2 JTI runs from 2014 to 2024. It brings together Europe’s aeronautics industrial leaders and public research organizations. The technologies developed under CS2 will reduce environmental pollution and noise levels and will therefore improve the quality of life. The close collaboration between the partners of CS2 will accelerate the pace of technological progress and create a mutual win-win situation.

Specific objectives include:

  • increasing aircraft fuel efficiency, thus reducing CO2 emissions by between 20 to 30%; and
  • reducing aircraft NOx and noise emissions by between 20 to 30% compared to “state-of-the-art” aircraft entering into service as from 2014

Among the other focuses, Structural Health Monitoring (SHM) methodologies and technologies are being developed with the final aim to minimize operative costs. Different kinds of SHM software and sensors systems are at the heart of verification and validation activities based on experimentation at different level from specimen to full scale demonstrator.

This special session invites contributions from all the CS2 partners that have been working in the area of Structural Health Monitoring.



# 30

 

Carbon Nanotube and Graphene-based Sensors for SHM applications

Prof. Alfredo Güemes  (Department Aeronautics, University Politecnica de Madrid, Spain)

Prof. Dr. Zhongqing Su (Dept. Mechanical Engineering, The Hong Kong Polytechnic University)

 

Carbon nanofillers are offering new and astonishing possibilities for advanced research and development.  Dispersed in polymers, nanofillers have demonstrated a high sensitivity and great easiness for usage in diverse applications, due to its piezoresistive behavior, very sensitive to strain and damage; basic principles have been well verified, with validations and applications being intensively explored. Different possibilities are opened, from doped resins to its usage as inks to be printed on adhesive films. It is a naturally distributed sensor, to be built with the structure without imposing any restriction nor additional weight, characteristics both very attractive for SHM applications.

By merging all the related papers into a Special Session, we hope the exchange of knowledge among the participants is stimulated, raising fruitful discussions.

 

  • Digital Image Correlation SHM and NDE
  • Vision-based displacement and vibration measurement, modal analysis, and system identification
  • Integration vision-based techniques on autonomous and unmanned vehicles for remote inspection
  • Advancements in optical sensing and image-processing
  • Photogrammetric measure for structural systems assessment
  • Machine learning, deep learning, and convolutional neural networks for computer-vision SHM and NDE


# 31

 

Damage Identification Under Changing Environment and operational conditions

Prof. Dr. Dongsheng Li (Shantou University, China)
Prof. Dr. Maosen Cao (Hohai University, China)
Prof. Dr. Peter Kraemer (University of Siegen, Germany)

 

Structural health monitoring (SHM) have received considerable attention for the last two decades. The problem is to be able to detect, locate and assess the extent of damage in a structure so that its remaining life can be known and possibly extended. However, a SHM system for in-service structures pose many significant technical challenges. One of the main obstacles is the environmental and operational variation of structures. In fact, these changes can often mask subtler structural changes caused by damage. Often the so-called damage-sensitive features employed in conventional damage detection techniques are also sensitive to changes in environmental and operational conditions of structures. Therefore, we solicit papers that develop new technologies to remove environmental effects from structural damage. At the same time, the damage-insensitive features extracted from motoring data under changing environment are welcomed in the conference. Other researches about data analysis and signal process techniques are also welcomed. We expect submissions addressing any of these challenges.

  • Techniques for separating environmental effects from structural damage
  • Feature extraction for structural health monitoring under changing environment
  • Data fusion-based structural damage detection under varying temperature conditions
  • Statistical damage detection considering environmental influences
  • Temperature and humidity effect on structural responses
  • Long-term monitoring and data analysis of bridges
  • Structural monitoring under operating conditions


# 32

 

Multifunctional Materials and Composites

Okenwa I. Okoli, Vincent O. Eze, Md Abu Shohag (High-Performance Materials Institute, FAMU-FSU College of Engineering, 2525 Pottsdamer St, Tallahassee)

 

Multi-functional composites have the ability to perform more than one principal function taking place at a time either sequentially or simultaneously. One primary function is to retain structural integrity, while other non-structural functions could be sensing, self-healing, energy harvesting/storage or thermal conductivity. The goal of this special session is to report recent findings on the application of multifunctional materials for the development of promising technologies for advanced energy harvesting and conversion devices, and sensors. Materials for energy harvesting, conversion and sensor application usually have low-efficiencies and mechanical or chemical properties that limit how they can be used. In addition, most materials in this class are expensive to be economically feasible as energy sources/sensors.

This session will accept contributions that offer approaches to the design and development of new materials manufacturing processes to produce efficient and low-cost energy harvesting, conversion materials, systems, sensors and devices. Energy harvesting and conversion can include light to electricity, heat to electricity, and chemical energy to electricity. This will be a great opportunity for sharing and disseminating results of cutting-edge research topics on multifunctional materials and composites.

Submissions may include but not limited to the following topics:

  • Self-healing, sensors (process sensor: in-situ curing sensors; operation sensors: damage and load sensors)
  • 3D printed multifunctional composites/additively manufactured sensor for SHM in composites
  • Multifunctional material architectures (metamaterials)
  • Characterization, modeling (numerical), validation and testing
  • Nanocomposites
  • Scalable manufacturing methods/processes

Keywords: energy harvesting, sensors, actuator, energy conversion, advanced composites, metamaterials, self-healing.



# 33

 

Metamaterials for Autonomous and Sustainable Structural Systems

Donghyeon Ryu (Department of Mechanical Engineering, New Mexico Tech, Socorro, NM, USA)
Kenneth J. Loh (Department of Structural Engineering, University of California, San Diego, CA, USA)
Nathan Salowitz (Department of Mechanical Engineering, University of Wisconsin, Milwaukee, WI, USA)

 

 

Advanced materials have made innovative progresses in structural health monitoring (SHM) by improving performance and efficiency of sensors and actuators. Nevertheless, as new industrial paradigms (e.g., autonomy, sustainability, and connectivity) demand structural systems to be fully autonomous and self-sustainable, researchers have sought solutions for designing novel sensors and actuators suitable for autonomous and sustainable structural systems. Metamaterials have been widely adopted in engineering communities for designing material systems exhibiting unprecedented characteristics. Also, in SHM community, there have been continuous effort to employ design concept of metamaterials for innovating sensors and actuators through hierarchical structural design at various length scales.

In this special session, researchers are invited to report recent research progresses in application of metamaterials for enhancing structural systems; exchange feedback on each other’s research; and brainstorm how to make persistent improvement in SHM and realize next-generation structural systems using advanced materials and engineering. Research topics for this special session can be, but not limited:

  • Advances in SHM by metamaterials
  • Novel design of sensors and actuators using metamaterials design concept
  • Innovative design concept of metamaterials
  • Multifunctional materials with metamaterials
  • Autonomous and sustainable structural systems enhanced by metamaterials


# 34

 

Structural Health Monitoring of High-speed Rail and Maglev Systems

Professor Yi-Qing Ni – National Engineering Research Center on Rail Transit Electrification and Automation (Hong Kong Branch), The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.

 

 

Key words: high-speed rail, maglev, online and onboard monitoring, non-destructive evaluation, predictive modelling tools, machine learning, health management

 

Scope of Session

High-speed rail (HSR) is being developed in Asian and European countries to satisfy the rapidly growing demand for intercity services and to shore up economic growth. The development of HSR has not only brought about convenience and comfort, but also aroused growing concern about safety and annually increasing budget for inspection and maintenance work to prevent potential accidents. Developing effective online structural health diagnosis and prognosis methods is a core focus for preventing catastrophic failure as well as prolonging the service life of HSR. Particularly, in the background of Industry 4.0, the provision of the whole gamut of access to digitization is a key directive, where a momentous mission is to develop smarter rail systems by integrating sensing, communication, computing and information technologies. This special session provides a platform for sharing state-of-the-art research and applications of structural health monitoring (SHM) technology for HSR and maglev systems. The scope of this session covers a broad range of research topics, including but not limited to:

  • On-board and online monitoring of rolling stock (coaches, bogies, and wheels);
  • Non-destructive and/or online monitoring of rail tracks;
  • Instrumentation for rail infrastructure monitoring (railway bridges, tunnels and subgrade);
  • Railway intrusion and obstacle detection techniques;
  • Earthquake early warning systems for HSR;
  • Advanced sensors and sensory networks for online/onboard monitoring of HSR and maglev;
  • Application of multi-functional materials, energy harvesting, wireless sensing, and cloud computing to HSR and maglev;
  • Monitoring-assisted prediction and control of vibration and noise induced by trains;
  • Condition-based maintenance strategy for rail infrastructure;
  • Machine learning tools for health management of HSR and maglev.


# 35

 

Defect imaging algorithms based on guided waves for BVIDs detection: a Round Robin test on a large-scale aeronautical composite structure

Drs. Alessandro Marzani and Luca De Marchi (University of Bologna, Italy)

 

 

Scope of Session

The special session aims at assessing and comparing imaging algorithms operating on guided wave signals for the detection of barely visible damages (BVIDs). To such purpose, a common dataset of piezo-actuated and piezo-received signals propagating in a composite panel of a full-scale wing demonstrator approximately 4.5 m long and from 1.2 to 2.3 m wide, is used by all the participants in the round robin test. The signals, freely available to download at http://shm.ing.unibo.it/, were acquired by a network of 133 piezoelectric transducers secondarily bonded on the composite panel at four different testing stages, namely before loading, before fatigue, before impacts, and after impacts. Such activity was carried out within the EU project “Smart Intelligent Aircraft Structures – SARISTU” (FP7-AAT-2011-RTD-1, GA 284562).

The round robin test will focus on the detection and eventual characterization of BVIDs in different bays of the composite panel. Such BVIDs were generated by air gun impacts and verified by means of ultrasonic C-scans.

As such, the round robin aims at comparing the work of several research groups operating in the area of guided waves based non-destructive testing and structural health monitoring. The goal of the special session is thus to discuss the state of art algorithms and discuss their pro and cons for damage detection, location and characterization.