TY - CONF A1 - Karapanagiotis, Christos T1 - Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data fusion and digital twin modeling N2 - Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Hydrogen KW - Ultrasonic guided waves KW - Fiber optic sensors KW - Acoustic emission KW - Machine learning KW - Pressure vessels KW - Structural health monitoring PY - 2024 AN - OPUS4-60277 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing N2 - We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future. T2 - 11th European Workshop on Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Hydrogen KW - Composites KW - Pressure vessels KW - Fiber optic sensors KW - Machine learning KW - Structural health monitoring PY - 2024 AN - OPUS4-60275 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Heimann, Jan A1 - Yilmaz, Bengisu A1 - Charmi, Amir A1 - Duffner, Eric A1 - Schukar, Marcus A1 - Prager, Jens T1 - Structural Health Monitoring (SHM) for continuous monitoring of hydrogen pressure vessels N2 - While hydrogen is one of the most promising energy carriers, the safety of hydrogen storage technology remains one of the most important factors for technological and societal approval. While the engineering safety factors of the pressure vessels are kept high, the periodic inspection and the limited lifetime are making the application very costly considering manpower, time, money, and material waste. The development of an integrated structural health monitoring system can allow an easy transition from the current situation to cost-effective predictive maintenance. Hence, we propose to integrate three different SHM systems into hydrogen pressure vessels, namely guided wave ultrasonics, acoustic emission, and fibre optic sensing, to continuously monitor the condition and integrity. In this work, we evaluated the condition of a Type IV composite overwrapped pressure vessel using ultrasonic guided wave propagation. We mounted fifteen piezo-electric wafers on the composite cylinder by shaping three rings containing five sensors each. We acquired data from the sensor network following different boundary conditions with artificial damages on the selected locations. The data were evaluated with guided wave tomography techniques using ultrasonic features (amplitude, frequency, etc.) as well as artificial intelligence (AI). The results suggest that both traditional guided wave fusion techniques and AI-based characterization methods can detect artificial damages. In future work, it is planned to integrate acoustic emission and fibre optic sensing. Moreover, the measurement and the test results will be implemented into a digital twin to derive trends and make predictions on the damage propagation as well as the remaining useful lifetime. This work has received funding from German Ministry of Economic Affairs and Climate Actions within the QI-Digital initiative (www.qi-digital.de). T2 - SCHALL 23 CY - Wetzlar, Germany DA - 21.03.2023 KW - Structural Health Monitoring KW - Ultrasonic Guided Waves KW - Composite Overwrapped Pressure Vessel KW - Hydrogen PY - 2023 AN - OPUS4-58026 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Popiela, Bartosz T1 - PhD Topic 5: Summer School Update. Influence of manufacturing process related residual stresses in wound composite material on the operational safety of H2 pressure vessels N2 - The presentation is an update on the progress of the PhD Project. It focuses on the residual stress induction during the winding process of type 4 composite pressure vessels. Moreover, an overview of the experimental study is given, with focus on the manufacturing of composite pressure vessels. T2 - Summer School 2023 - BTU-BAM Graduate School "Trustworthy Hydrogen" CY - Berlin, Germany DA - 04.09.2023 KW - Residual stress KW - Composite KW - Pressure vessel KW - Hydrogen PY - 2023 AN - OPUS4-58239 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos A1 - Schukar, Marcus A1 - Breithaupt, Mathias A1 - Krebber, Katerina T1 - Monitoring of composite pressure vessels using surface applied distributed fiber optic sensors N2 - In this paper, we report on surface-applied distributed fibre optic sensors for monitoring composite pressure vessels designed for hydrogen storage. Previous reports have revealed that integrating optical fibres within vessel composite structures effectively enables the monitoring of structural behavior throughout their lifetime. However, integrating optical fibres during the manufacturing process is complex and time-consuming. Therefore, we aim to simplify this process by attaching the optical fibres to the vessel’s surface. This method is significantly more timeefficient than the integration process and can be applied to any vessel. Our results demonstrate that surface-applied fibre optic sensors can detect and precisely localise damage. Additionally, signs of damage can be recognised even before the damage occurs. Predictive maintenance using fibre optic sensors could reduce premature maintenance costs and periodic inspections while increasing safety and extending the vessel’s useful service life. The role of machine learning in predictive maintenance is also discussed. T2 - 20th Sensors & their Applications Conference CY - Limerick, Ireland DA - 11.08.2024 KW - Hydrogen KW - Fiber optic sensors KW - Composites KW - Machine learning KW - Structural health monitoring PY - 2024 SP - 1 EP - 4 AN - OPUS4-60911 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Monitoring hydrogen composite pressure vessels using surface applied distributed fiber optic sensors N2 - We report on surface-applied distributed fibre optic sensors for monitoring composite pressure vessels designed for hydrogen storage. Previous reports have revealed that integrating optical fibres within vessel composite structures effectively enables the monitoring of structural behavior throughout their lifetime. However, integrating optical fibres during the manufacturing process is complex and time-consuming. Therefore, we aim to simplify this process by attaching the optical fibres to the vessel’s surface. This method is significantly more timeefficient than the integration process and can be applied to any vessel. Our results demonstrate that surface-applied fibre optic sensors can detect and precisely localise damage. Additionally, signs of damage can be recognised even before the damage occurs. Predictive maintenance using fibre optic sensors could reduce premature maintenance costs and periodic inspections while increasing safety and extending the vessel’s useful service life. The role of machine learning in predictive maintenance is also discussed. T2 - 20th Sensors & their Applications Conference CY - Limerick, Ireland DA - 11.08.2024 KW - Hydrogen KW - Fiber optic sensors KW - Composites KW - Machine learning KW - Structural health monitoring PY - 2024 AN - OPUS4-60831 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bernardy, Christopher A1 - Konert, Florian A1 - Popiela, Bartosz A1 - Sarif, Raduan T1 - H2Safety@BAM: Competence Center for safe hydrogen technologies N2 - Presentation of the competence center H2Safety@BAM at the European PhD Hydrogen Conference 2024 in Ghent, Belgium. T2 - European PhD Hydrogen Conference 2024 (EPHyC2024) CY - Ghent, Belgium DA - 20.03.2024 KW - H2safety KW - Hydrogen KW - Safety KW - Competence center PY - 2024 AN - OPUS4-59756 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mair, Georg W. A1 - Becker, Ben A1 - Duffner, Eric A1 - John, Sebastian T1 - Composite storage systems for CGH2- systematic improvement of RC&S N2 - Conventional approval requirements exclusively ask for minimum strength values, which have to be met. The probabilistic approach estimates how likely none of the comparatively manufactured units fails during operation. Both questions are juxtaposed and compared here with respect to the load cycle tests. The influence of the sample sizes is discussed additionally. T2 - 10th INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY & ENVIRONMENTAL PROTECTION CY - Bled, Slovenia DA - 27.06.2017 KW - Probabilistic KW - Hydrogen KW - Composite KW - Cylinder KW - Regulations KW - Load cycles KW - GTR 13 PY - 2017 AN - OPUS4-41677 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mair, Georg W. A1 - Becker, Ben T1 - Monte-Carlo-analysis of minimum load cycle requirements for composite cylinders for hydrogen N2 - Existing regulations and standards for the approval of composite cylinders in hydrogen service are currently based on deterministic criteria (ISO 11119-3, UN GTR No. 13). This paper provides a systematic analysis of the load cycle properties resulting from these regulations and standards. Their characteristics are compared with the probabilistic approach of the BAM. Based on Monte-Carlo simulations the available design range of all concepts is compared. In addition, the probability of acceptance for potentially unsafe design types is determined. T2 - ICHS 2017 CY - Hamburg, Germany DA - 11.09.2017 KW - Monte-Carlo KW - Hydrogen KW - Regulations KW - Probabilitic approach PY - 2017 SP - ID 202, 1 EP - 11 PB - HySafe CY - Hamburg AN - OPUS4-41944 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Erxleben, Kjell T1 - Component test for the assessment of in-service welding on/onto pressurized hydrogen pipelines N2 - Hydrogen is seen as the energy carrier of the future. Therefore a reliable infrastructure to transport hydrogen in a large scale is needed. A so called European hydrogen backbone out of long distance transmission pipelines is planned by European countries to create a hydrogen transport infrastructure. Due to economic reasons this will be achieved by new build pipelines such as repurposed natural Gas (NG) pipelines, converted to hydrogen useage. A general suitability for hydrogen service of low alloyed pipeline steel, as it is used for NG service today, is given. But in case of necessary in-service welding procedures in terms of e.g. hot-tapping and stoppling, the risk of a critical hydrogen uptake into the pipe materials due to much higher temeperatures while welding and the possibility of hydrogen embrittlement (HE) needs to be closely investigated. The presentation gives an overview of the current H2-SuD project, investigating the feasability of in-service welding on future hydrogen pipelines. Therefore, component-like demonstrators were developed to test (I) the additional hydrogen uptake due to in-service welding under hydrogen pressure and (II) to measure the temperature field due to different welding parameters and demonstrator geometries, especially on the inner pipe wall surface. Collected data will be used to validate a numerical simulation of the thermal field and additionally the hydrogen diffusion in the pipeline material. T2 - Presentation at The University of Manchester CY - Manchester, United Kingdom DA - 12.09.2025 KW - In-service KW - Hydrogen KW - Pipeline KW - Welding PY - 2025 AN - OPUS4-64129 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Rhode, Michael T1 - Hydrogen trap characterization in 200 and 1,000 bar charged CoCrNi medium entropy alloy compared to steel AISI 316L N2 - Multiple principal element alloys (MPEAs) represent a new class of metallic materials. MPEAs, such as the CoCrNi medium entropy alloy (MEA), have attracted considerable research attention as potential materials to replace, for example, austenitic steels in high-pressure hydrogen environments. Due to the relatively new alloy concept, studies on the specific hydrogen diffusion and trapping behavior of high-pressure hydrogen-charged CoCrNi MEAs are rare so far. For this reason, a CoCrNi-MEA was investigated and compared to an austenitic stainless steel, AISI 316L. Both materials were subjected to high pressure hydrogen loading for two different pressures: 200 bar and 1,000 bar. After charging, thermal desorption analysis (TDA) was used with three heating rates from 0.125 K/s to 0.500 K/s to clarify the specific hydrogen desorption and trapping behavior. To the best of our knowledge, this study is the first to characterize hydrogen diffusion and trapping in 1,000 bar high-pressure charged CoCrNi. For this purpose, the underlying TDA spectra were analyzed in terms of peak deconvolution into a metallurgically justifiable number of defined peaks. The individual peak temperatures and activation energies “EA” were calculated. The following conclusions can be drawn from the results obtained: (1) Exposure to 200 bar or 1,000 bar leads to an increase in hydrogen absorption, regardless of the material investigated, expressed by a significantly increased desorption rate at 1,000 bar. However, the effusion peaks typically occur only at high temperatures. The (2) TDA showed that a four-peak deconvolution scenario was sufficient to describe the trapping behavior and the "EA" indicated the dominance of irreversible traps. In addition, the average trapping energy is higher than in the 316L. The (3) charge pressure related hydrogen solubility was in the order of: CoCrNi-MEA < 316L for both pressures and (4) charging at 1000 bar results in an average concentration of 49 wt.ppm (CoCrNi-MEA) and > 75 wt.ppm (316L). In summary, the CoCrNi-MEA was characterized by a reduced solubility, but very deep entrapment compared to the 316L. For this reason, further application potentials of the MEA may arise. T2 - FEMS Euromat 2025 - 18th European Congress and Exhibition on Advanced Materials and Processes CY - Granada, Spain DA - 15.09.2025 KW - Medium entropy alloy KW - Hydrogen KW - Trapping KW - Diffusion KW - High-pressure charging PY - 2025 AN - OPUS4-64160 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -