Active thermography based on tensor rank decomposition
Thermosense: Thermal Infrared Applications XLIV
Thermography↗
Engineering topics
Joseph N Zalameda
Publications and source records attributed to Joseph N Zalameda.
In-situ Measurements using a Configurable Architecture Additive Testbed System
Explore the source record for details and available documents.
additive manufacturing↗
Towards Qualification and Certification of Laser Powder Bed Fusion Ti-6Al-4V with In-Situ Process Monitoring and Automated Defect Detection
Qualification and certification of laser powder bed fusion (LPBF) parts are two challenges that must be answered to ensure suitability for critical applications. In-situ monitoring using high frame rate thermal and conventional optical imaging sensors is applied to the LPBF build process. Currently, the large volume of data from such sensors becomes untenable for manual inspection in production environments. This presentation serves to address this in-situ monitoring deficiency in two ways. First, a framework for managing data streams from LPBF process monitoring sensors is described. Second, two candidate image analysis techniques are presented: one is a set of heuristics that are easily interpretable, and the other is an uninterpretable convolutional neural network. These strategies are compared in terms of performance, computational expense, and speed. These methodologies represent platforms for connecting processing conditions to process modeling efforts aligned with the qualification and certification mission for LPBF Ti-6Al-4V components.
Qualification↗
In-Situ Process Monitoring, Synchronization, and Mapping Laser Powder Bed Fusion Builds of Ti6Al4V
The use of in-situ process monitoring is of interest to lower the cost of inspection for the qualification of laser powder bed fusion (LPBF) parts. Precise monitoring of the LPBF-AM build process constitutes a multi-scale and multi-discipline task. There are several significant challenges to the in-situ approach: the synchronization of sensor signals to process steps, the physical interpretation and classification of sensor signals, managing very large datasets, and comparing the inputs with the observed monitoring signals. At NASA Langley Research Center, a configurable architecture additive testbed has been developed to monitor the build process with synchronized sensors. The philosophy and method adopted for the synchronization of the cameras with laser power & position Ti-6Al-4V LPBF are described. The synchronized in-situ monitoring signals are compared with ex-situ nondestructive inspection and optical microscopy observations. Such comparisons permit a better understanding of how the sequential process actions of LPBF-AM can affect build quality.
Laser Powder Bed Fusion↗
Additive Manufacturing Model-Based Process Metrics: Reduced Order Modeling of the Laser Powder Bed Fusion Process
The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.
Laser Powder Bed Fusion↗
Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques
Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of the subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography and ultrasound. The concept of the conflation of probability distributions is applied to combine the posterior distributions derived from thermography and ultrasound and the quality of the fused estimates are compared against the individual estimates against synthetic data that was created to mimic the inspection of a lap joint comprised of aluminum adherends.
thermal nondestructive evaluation↗
Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques
Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.
thermal nondestructive evaluation↗
Fabrication and Characterization of A Lunar Simulant-Based Sintered Construction Material
In-situ resource utilization (ISRU) is critical to enable future efforts to have a long-term human presence on the Moon as well as Mars. ISRU technologies are being developed for radiation protection, dust mitigation, thermal insulation, and other applications. One such ISRU technology for creating construction materials out of lunar and Martian regolith is sintering, which is a thermal-based construction process that bonds finely grained material together at temperatures below the melting point. However, the conditions employed during the sintering, such as temperature, atmospheric composition, duration of the process, and pressure, can have a significant impact on the quality and strength of the resulting materials. In parallel, the development of methods for characterizing the quality, porosity, density, and other properties of these materials is critical. X-ray computed tomography (X-ray CT) can image large changes in density within a material, such as the presence of pores throughout an otherwise uniform medium, with relatively high spatial resolution. Similarly, Terahertz time-domain spectroscopic (THz-TDS) imaging is sensitive to density variations within samples, but is restricted to non-conducting materials. Specifically, previous work has shown that the refractive index (n eff ) values obtained through the analysis of THz-TDS images increases with increasing density within plastic samples. Even further, this work showed that it is possible to create a calibration curve for a given material from samples of different, but known density, which can enable one to directly convert n eff to density for samples having the same composition, but unknown density. Here, we report on the fabrication of a lunar simulant-based sintered construction material using vacuum hot pressed (VHP) sintering, then show X-ray CT and THz-TDS imaging results of the sample, which show spatial variations in the material. This has important implications for efforts to improve these types of lunar construction material processes and verify the quality of these materials in terms of consolidation. To the best of our knowledge, there is no previous work utilizing VHP sintering to make lunar simulant-based construction materials or exploring the feasibility of THz imaging to spatially map the density variation through a lunar simulant-based construction material.
Terahertz time-domain spectroscopic imaging↗