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 - Popiela, Bartosz T1 - Non-Destructive Testing of Type 4 Composite Pressure Vessels N2 - Non-Destructive Testing (NDT) of type 4 composite pressure vessels can be seen as key to better understanding the behaviour of the composite structure and the impact of the manufacturing process on its quality. In this presentation, NDT methods used in the “Trustworthy Hydrogen” project are introduced. A brief discussion of the observed phenomena is provided. T2 - Visit of a delegation from Korea Fire Institute (KFI) CY - Berlin, Germany DA - 24.06.2024 KW - Composite KW - Pressure vessel KW - Non-destructive testing PY - 2024 AN - OPUS4-60401 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Popiela, Bartosz T1 - FEM-Analyse der Reparaturstellen an FKV-Sandwichplatten N2 - Untersuchung des Einflusses des Reparaturpatches auf das Verhalten der reparierten GFK-Sandwichproben unter Zug-, Druck- und Schubbeanspruchung. T2 - 25. Nationales SAMPE-Symposium CY - Kassel, Germany DA - 18.02.2020 KW - Rotorblätter KW - Glasfaserverstärkter Kunststoff KW - Sandwichstruktur PY - 2020 AN - OPUS4-50544 LA - deu 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 - Popiela, Bartosz T1 - Performance of Type 4 Composite Pressure Vessels: Impact of Residual Stress State N2 - This presentation summarizes the results of an experimental study on slow burst tests, involving two pressure vessel designs with different residual stress states. The significant performance differences between the two designs highlight the critical role of residual stress state in filament-wound structures T2 - Composites Research Seminar at the Innovative Design and Integrated Manufacturing Lab, Seoul National University CY - Seoul, South Korea DA - 22.11.2024 KW - Composite KW - Pressure vessel KW - Residual stresses KW - Burst test KW - Filament winding PY - 2024 AN - OPUS4-61734 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Popiela, Bartosz T1 - BAM 3.5 and Trustworthy Hydrogen: Experimental Investigation of Type 4 Composite Pressure Vessels N2 - The presentation provided a brief introduction to Division 3.5 at BAM and detailed an experimental study of composite pressure vessels as part of the 'Trustworthy Hydrogen' project. It included an in-depth analysis of slow burst test evaluations. T2 - Lab Seminar of IDIM SNU CY - Seoul, South Korea DA - 26.11.2024 KW - Composite KW - Pressure vessel KW - Residual stresses KW - Burst test PY - 2024 AN - OPUS4-61779 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wätzold, Florian A1 - Popiela, Bartosz A1 - Mayer, Jonas T1 - Methodology for AI-Based Search Strategy of Scientific Papers: Exemplary Search for Hybrid and Battery Electric Vehicles in the Semantic Scholar Database N2 - The rapid development of artificial intelligence (AI) has significantly enhanced productivity, particularly in repetitive tasks. In the scientific domain, literature review stands out as a key area where AI-based tools can be effectively applied. This study presents a methodology for developing a search strategy for systematic reviews using AI tools. The Semantic Scholar database served as the foundation for the search process. The methodology was tested by searching for scientific papers related to batteries and hydrogen vehicles with the aim of enabling an evaluation for their potential applications. An extensive list of vehicles and their operational environments based on international standards and literature reviews was defined and used as the main input for the exemplary search. The AI-supported search yielded approximately 60,000 results, which were subjected to an initial relevance assessment. For the relevant papers, a neighbourhood analysis based on citation and reference networks was conducted. The final selection of papers, covering the period from 2013 to 2023, included 713 papers assessed after the initial review. An extensive discussion of the results is provided, including their categorisation based on search terms, publication years, and cluster analysis of powertrains, as well as operational environments of the vehicles involved. This case study illustrates the effectiveness of the proposed methodology and serves as a starting point for future research. The results demonstrate the potential of AI-based tools to enhance productivity when searching for scientific papers. KW - Search strategy KW - Methodology KW - Artificial intelligence KW - Literature review KW - Battery electric vehicles KW - Hydrogen-powered vehicles PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-622012 DO - https://doi.org/10.3390/publications12040049 VL - 12 IS - 4 SP - 1 EP - 16 PB - MDPI CY - Basel, Switzerland AN - OPUS4-62201 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ghaznavi, Ali A1 - Kästle, Emanuel D. A1 - Popiela, Bartosz A1 - Duffner, Eric T1 - Damage monitoring of hydrogen composite pressure vessels using acoustic emission technique and machine learning N2 - A good understanding of the structural stability of hydrogen composite overwrapped pressure vessels (COPV) is important for the cost-effective design and safe operation of hydrogen storage systems. Acoustic emission (AE) monitoring is a non-destructive method sensitive to microstructural damages such as e.g. fiber breakage, and matrix cracking in COPVs. This study proposes a novel approach for damage monitoring by integrating acoustic emission techniques with machine learning (ML) algorithms to classify and predict damage types in COPVs. However, training accurate classification models requires extensive labeled datasets, which are very challenging to generate due to the nature of AE signal data and the lack of in-situ observations of microscopic failures in COPVs. Our research overcomes this limitation by automating the labeling process of AE signal data for different COPVs using unsupervised ML methods. The most representative features were extracted and then selected from recorded AE signals. Different unsupervised clustering algorithms were utilized based on various extracted feature combinations. The most stable clustering result was achieved and later used as appropriate labels for training classification algorithms. A deep neural network-based deep learning (DL) architecture was used to train discriminative models on AE data, identify patterns, and classify damage types into different classes with improved accuracy and speed for each COPV. Results demonstrate the potential of the proposed combined deep learning approach to train predictive models in identifying failure patterns. The trained models based on individual COPVs show high training, validation, and test accuracy for unseen datasets and offer enhanced predictive capabilities by following advanced DL techniques compared to traditional monitoring methods. The proposed method highlights its potential to improve the efficiency and safety of hydrogen storage systems. T2 - SCHALL 25 CY - Dresden, Germany DA - 26.03.2025 KW - Sequential Neural Network KW - Acoustic Emission KW - Composite Overwrapped Pressure Vessels KW - Damagemonitoring KW - Machine Learning KW - Deep Learning KW - Deep Neural Network PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-629040 DO - https://doi.org/10.58286/30958 SP - 1 EP - 12 AN - OPUS4-62904 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ghafafian, Carineh A1 - Popiela, Bartosz A1 - Trappe, Volker T1 - Failure Mechanisms of GFRP Scarf Joints under Tensile Load N2 - A potential repair alternative to restoring the mechanical properties of lightweight fiberreinforced polymer (FRP) structures is to locally patch these areas with scarf joints. The effects of such repair methods on the structural integrity, however, are still largely unknown. In this paper, the mechanical property restoration, failure mechanism, and influence of fiber orientation mismatch between parent and repair materials of 1:50 scarf joints are studied on monolithic glass fiber-reinforced polymer (GFRP) specimens under tensile load. Two different parent orientations of [-45/+45]2S and [0/90]2S are exemplarily examined, and control specimens are taken as a baseline for the tensile strength and stiffness property recovery assessment. Using a layer-wise stress analysis with finite element simulations conducted with ANSYS Composite PrepPost to support the experimental investigation, the fiber orientation with respect to load direction is shown to affect the critical regions and thereby failure mechanism of the scarf joint specimens. KW - Scarf joint KW - Glass fiber reinforced polymers KW - Failure mechanisms PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-523952 DO - https://doi.org/10.3390/ma14071806 VL - 14 IS - 7 SP - 1806 PB - MDPI CY - Basel, Switzerland AN - OPUS4-52395 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Popiela, Bartosz T1 - Influence of manufacturing process related residual stresses in wound composite material on the operational safety of H2 pressure vessels: PhD Topic Introduction N2 - Short introduction of the PhD Topic 5 in the BTU-BAM Graduate School "Trustworthy Hydrogen". Description of the objectives, deliverables and expected added value of the thesis. T2 - Introduction Week - BTU-BAM Graduate School "Trustworthy Hydrogen" CY - Berlin, Germany DA - 16.01.2023 KW - Residual stress KW - Composite KW - Pressure vessel KW - Hydrogen PY - 2023 AN - OPUS4-56882 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Popiela, Bartosz A1 - Günzel, Stephan A1 - Schukar, Marcus A1 - Mair, Georg W. A1 - Krebber, Katerina A1 - Seidlitz, Holger T1 - Impact of internal pressure control during manufacturing on residual stresses and safety performance of type 4 pressure vessels N2 - Composite pressure vessels are commonly manufactured using the wet filament winding process, where various process parameters can influence the performance of the finished component. In this study two designs of wet filament wound 6.8-liter type 4 composite pressure vessels were manufactured. Both differ only by the internal pressure used during the filament winding, which primarily influences the residual stress state in the composite structure. An extensive experimental study was carried out, including 10 slow burst tests and strain measurements with fiber optic sensors. Significant differences can be observed in the performance of the two designs even though the used stacking sequence, materials and other manufacturing parameters are the same for both designs. A discussion of the differences in the behavior of both cylinder types is provided, including the strain distribution in slow burst tests and failure mechanism. KW - Residual stresses KW - Slow burst tests KW - Filament winding KW - Type 4 composite pressure vessels KW - Hydrogen PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-626663 DO - https://doi.org/10.1016/j.jcomc.2025.100581 SN - 2666-6820 VL - 17 SP - 1 EP - 9 PB - Elsevier B.V. CY - Amsterdam, Netherlands AN - OPUS4-62666 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -