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Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a nondestructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. We study our proposed testing method along experiments carried out on a custom research PBF-LB/M machine using infrared (IR) cameras.
Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
For industrial applications dealing with hydrogen, the definition of safety distances and the assessment of possible hazards emanating from releases is mandatory. Since hydrogen is usually stored and transported under pressure, one scenario to be considered is the momentum driven release of hydrogen from a leakage with subsequent ignition. In this scenario, the emitted heat radiation from the resulting jet flame to the surroundings has to be determined to define adequate safety distances. For hydrocarbon flames, different jet flame models are available to assess the hazards resulting from an ignited jet release. Since hydrogen flames differ from hydrocarbon flames in their combustion behavior, it has to be checked if these models are also applicable for hydrogen. To evaluate the accuracy of these models for hydrogen jet flames, tests at real-scale are carried out at the BAM Test Site for Technical Safety (BAM-TTS). Herein, the flame geometry and the heat radiation at defined locations in the surroundings are recorded for varying release parameters such as leakage diameter (currently up to 30 mm), release pressure (currently up to max. 250 bar) and mass flow (up to max. 0.5 kg/s). The challenge here is the characterization of the flame geometry in an open environment and its impact on the thermal radiation. Existing heat radiation data from the literature are mostly based on unsteady outflow conditions. For a better comparability with the steady state jet flame models, the experiments presented here are focused on ensuring a constant mass flow over the release duration to obtain a (quasi) stationary jet flame. In addition, stationary outflow tests with hydrocarbons (methane) were also carried out, which are intended to serve as reference tests for checking flame models based on hydrocarbon data.
The design of bridges often overlooks the vertical component of earthquakes or considers it of secondary importance, despite compelling evidence indicating specific structural damage caused by primary earthquake waves. Conversely, during the operational phase, the combined influence of ground motion and moving loads from vehicles can significantly impact the structural health monitoring (SHM) of bridges. This study aims to evaluate the simultaneous effect of vertical earthquake vibrations and moving vehicle loads on simply supported bridges. The research employs a practical methodology based on the eigenfunction expansion method to analyze change of deflection due to the effect of these concurrent forces under seven different earthquake records. It is shown that within a realistic range of vehicle mass and velocity, the average of changing the maximum deflection at the mid-span of the main beam (denoted as M_n) reaches up to 163% under various scenarios. Subsequently, the seismic parameters influencing this phenomenon are identified through a statistical analysis of set of 100 different earthquake records with unique features. A linear regression equation is presented to predict the M_n based on the earthquake specific properties. Additionally, to control the vertical vibration of bridge systems, a novel vibration suppression system utilizing steel pipe dampers is introduced, and its reliability is examined across a broad spectrum of bridge flexural rigidity. The results indicate that the system's efficiency depends on M_n and the soil type of the bridge construction, enabling a reduction in structural sections (up to 27%) while achieving the same maximum target deflection in the initial state. This efficiency leads to a more economical design solution, emphasizing the potential benefits of the proposed system for practical application.
NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
(2024)
Non-destructive Testing (NDT) provides valuable data about structural elements, supporting the assessment of existing infrastructures without incurring additional structural damage from inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has already been considered for non-destructive concrete testing. Regarding that, extensive measurements with sophisticated scopes need to be conducted by experts as an obligatory process.
This study illustrates how NDT results describing the inner structure of a concrete element can effectively support the reassessment of bridges in operation. To achieve this, the study considers the various measurable positions of the resisting longitudinal tendons of a bridge structure to investigate the displacement change under dynamic service loads.
Furthermore, this study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. This regression analysis yields a modifier for determining the correct depth of an object within the structural element. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. As a result, it provides unbiased and accurately measured results, while ensuring that the measurement data can remain uncorrelated. Major advantages include efficient computation, a wider scope, and avoiding redundant information about the measuring process.
The findings demonstrate that employing the proposed NDT analysis method, with its enhanced practicability, can significantly augment the efficiency of NDT data-supported structural reassessments across various scenarios.
Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC) offers several advantages compared to concrete, notably due to the strain hardening behavior under tensile actions. Structures made of this composite material are lightweight and highly durable, thanks to the UHPFRC waterproofing quality. Nonetheless, the tensile behavior leads to a different cracking pattern than conventional concrete and is not fully understood yet. This paper presents a combined approach using both passive ultrasonic (US) stress wave (or acoustic emission) and active US stress wave monitoring to localize and quantify damage progression in a full-scale UHPFRC beam during experimental load testing. The proposed monitoring approach involves 24 US transducers that are embedded randomly throughout a 4.2- meter-long laboratory UHPFRC T-beam. Continuous monitoring enabled accurate localization of US stress sources caused by loading-induced cracking as well as from pulses generated by the embedded US transducers. This study shows that it is possible to predict the location and shape of the macro-crack that is linked to structural failure early on, i.e., just after the end of the elastic domain. This combined approach opens new possibilities to monitor the structural behavior and detect damage on UHPFRC structures before they affect the structural behavior in terms of deflection and strain.
To safely dispose of nuclear waste in underground facilities, engineered barrier systems are needed to seal shafts and galleries. The material used in these barriers must be adapted to the host rock parameters. Shrinking and cracking must be avoided to provide a barrier with almost zero permeability. For repositories in salt rock environments, several types of salt concrete (SC) are possible construction materials. Within the project SealWasteSafe, we compared the behavior of an innovative alkali-activated material (AAM) with standard SC in their hydration and hardening phase. To monitor the microstructural changes within the two materials SC and AAM, acoustic emission (AE) signals have been recorded for up to ~250 days on 340-litercubic specimens. The phenomenon of AE is defined as the emission of elastic waves in materials due to the release of localized internal energy. Such energy release can be caused by the nucleation of micro-fracture, e.g., in concrete while curing or when exposed to load. The occurrence of AE events gives first rough indications of microstructural changes and potentially occurring cracking and thus, provides insights for structural health monitoring (SHM). The results show, that for the first 28 days after casting, less AE activity was detected in the AAM compared to SC. After 61 days, in the AAM material, the number of AE events exceeded those observed in the SC. However, the majority of the AE detected and located in AAM was related to surface effects, and not to microstructural changes or occurring cracks within the bulk volume. Additionally, the source location analysis indicated, that despite lower activity in SC, we observed some clustering of the events. In contrast, in AAM, the activity inside the specimen is randomly distributed over the whole volume. The monitoring results help to estimate the material’s sealing properties which are crucial to assess their applicability as sealing material for engineered barriers.
Combined passive ultrasonic (US) stress wave [better known as acoustic emission (AE)] and active US stress wave monitoring has been shown to provide a more holistic picture of ongoing fracture processes, damage progression, as well as slowly occurring aging and degradation mechanisms in concrete structures. Traditionally, different data analysis techniques have been used to analyze the data generated from these two monitoring techniques. For passive US stress wave monitoring, waveform amplitudes, hit rates, source localization, and b-value analysis, among others, have been used to detect and locate cracking. On the other hand, amplitude tracking, magnitude squared coherence (MSC), and coda wave interferometry (CWI) are examples of analyses that have been employed for active US stress wave monitoring. In this paper, we explore some of these data analysis techniques and show where their respective applications and limitations might be. After providing an overview of the monitoring approach and the different data analysis techniques, results and observations from selected laboratory experiments are discussed. Finally, suggestions for further work are proposed.
Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels
(2024)
We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for automotive use. The paper deals with the condition monitoring of such composite pressure vessels (CPVs) using the optical backscatter reflectometry (OBR) applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the polymer liner during the manufacturing process of the carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors can be an opportunity for monitoring the material degradation of CPVs under static and cyclic loading.
We present a distributed polymer optical fiber sensor system for deformation monitoring of geotechnical infrastructure. The sensor system is based on the digital incoherent optical frequency domain reflectometry (I-OFDR) for the detection of local strain events along a perfluorinated polymer optical fiber (PF-POF) used as a sensing fiber. For the best possible load transfer, the PF-POFs were integrated onto geosynthetics which pose a sensor carrier for the sensing fiber. By using elastic PF-POF instead of a standard glass fiber as a sensing fiber the strain range of geosynthetics-integrated fiber optic sensors could be extended up to 10 % in accordance with the end-user requirements.
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.