Quantification of the value of monitoring information for deteriorated structures
An efficient structural integrity management of deteriorated structures is of high societal value. Monitoring can be very beneficial as it is well developed with diverse technologies, algorithms and systems. However, the value or the utility of monitoring is seldom quantified and infrastructure owners and operators may be reluctant to invest in large systems for which the benefit is not clearly specified. In order to overcome this issue, recent research efforts (such as e.g. the COST Action TU1402) focus on utilising the Bayesian pre-posterior decision theory (1) to quantify the value of monitoring information and (2) to perform the quantification before implementation of the monitoring system.
This PhD focusses on deteriorated structures such as bridges and wind turbines and the development of monitoring strategies to most efficiently plan the structural integrity management throughout and prolonging the service life. The expected results comprise the documentation of efficient monitoring strategies for deteriorated structures and the quantification of their utility in terms of risk reduction, expected cost reduction and service life benefits for industrial application and for the value of society.
Approaches, methods and tools are developed, applied and disseminated for the quantification of the value of monitoring information for highly deteriorated structures.
The objective of this PhD is the identification of monitoring strategies to efficiently manage and to enlarge the service life of deteriorated structures.
- Extensive literature study on Value of Information (VoI), decision theory, Structural Health Monitoring (SHM), structural integrity management and deteriorated structures.
- Further development of approaches and methods for the quantification of monitoring information on the basis of utility and decision theory.
- Development of tools for the quantification of the value of monitoring information.
- Application of the tools in case studies.
- Dissemination of research results and thesis writing.
The expected results comprise the documentation of efficient strategies for monitoring deteriorated structures and the quantification of their utility in terms of risk reduction, expected cost reduction and service life benefits.
The research results are to be disseminated at international conferences and in reviewed scientific journals.
- AAU (Aalborg, Denmark)
April & May 2017
The aim of this secondment is to obtain additional scientific input on risk and decision analysis and wind turbine modelling.
- COWI (Kongens Lyngby, Denmark)
October 2018 to January 2019
The aim of this secondment is the performance of case studies in the environment of the consulting company COWI.
- Thöns S., Schneider R., Faber M.H.
Quantification of the Value of Structural Health Monitoring Information for Fatigue Deteriorating Structural Systems
12th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP12), Vancouver, Canada, 2015
- Schneider R., Fischer J., Straub D., Thöns S., Bügler M., Borrmann A.
Intelligent Structures - Prototype for the Condition Assessment and Damage Development Prognosis for Elements of the Bridge Model
Carl Schünemann Verlag GmbH, 2015. ISBN: 978-3-95606-190-5
- Thöns S., Faber M.H., Rücker W.
Life Cycle Cost Optimized Monitoring Systems for Offshore Wind Turbine Structures
IRIS Industrial Safety and Life Cycle Engineering: Technologies / Standards / Applications, VCE Vienna Consulting Engineers Zt GmbH, Vienna, Austria, 2013. ISBN: 978-3-200-03179-1
- Long L., Farreras Alcover I., Thöns S.
Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
IWSHM 2019, The 12th International Workshop on Structural Health Monitoring, Stanford, California, USA, 10-12 September 2019
- Long L., Mai A.Q., Thöns S., Sørensen J.D.
On the value of SHM information for the offshore wind turbines
WESC 2019 - Wind Energy Science Conference,Cork, Ireland, 17-20 June 2019
- Bayane I., Long L., Thöns S., Brühwiler E.
Quantification of the conditional value of SHM data for the fatigue safety evaluation of a road viaduct
ICASP13, The 13th International Conference on Applications of Statistics and Probability in Civil Engineering, Seoul, South Korea, 26-30 May 2019
- Long L., Thöns S., Döhler M.
The effects of deterioration models on the value of damage detection information
IALCCE 2018, The Sixth International Symposium on Life-Cycle Civil Engineering, Ghent, Belgium, 28-31 October 2018
- Long L., Thöns S., Döhler M.
The effects of SHM system parameters on the value of damage detection information
EWSHM 2018, The 9th European Workshop on Structural Health Monitoring Series, Manchester, UK, 10-13 July 2018
- Long L., Thöns S., Döhler M.
Damage detection and deteriorating structural systems
IWSHM 2017, The 11th International Workshop on Structural Health Monitoring, Stanford, California, USA, 12-14 September 2017
- Long L., Alcover F. I., Thöns S.
Utility-based decision of optimal SHM campaign and service life extension on an orthotropic steel bridge deck
Submitted to Structure & Infrastructure Engineering journal (April 2020)
- Long L., Mai A. Quang., Morato G. P., Sørensen D. J., Thöns S.
On the conditional value of structural and environmental information for offshore wind turbines
Submitted to Renewable Energy Journal (March 2020)
- Long L., Döhler M., Thöns S.
Determination of structural and damage detection system influencing parameters on the value of information
Structural Health Monitoring Journal, January 2020
- Rastayesh S., Long L., Sørensen J.D., Thöns S.
Risk Assessment and Value of Action Analysis for Icing Conditions of Wind Turbines Close to Highways
Energies, Volume 12, Issue 14, 2019
- Thöns S., Döhler M., Long L.
On Damage Detection System Information for Structural Systems
Structural Engineering International, Volume 28, Issue 3, pages 255-268, 2018
- Maintains and updates an individual blog on a regular basis. Read her posts.
- Participated in the "PhD retreat".
- Participated in the BAM PhD day in 2017 and 2018.
- Participated in the "Marie Skłodowska-Curie Actions Falling Walls Lab".
- Recorded a video as done within the so-called Three Minute Thesis (3MT®). Watch the video.
ESR12: Lijia Long (BAM)
Local academic supervisor: Assoc. Prof. Sebastian Thöns (DTU)
Industrial co-supervisor: Dr. Isaac Farreras Alcover (COWI)
PhD director: Prof. John Dalsgaard Sørensen (AAU)