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Adaptive wavelet compression of large additive manufacturing experimental and simulation datasets

Computational Mechanics

Salloum, Maher S.; Johnson, Kyle J.; Bishop, Joseph E.; Aytac, Jon M.; Dagel, Daryl D.; van Bloemen Waanders, Bart G.

New manufacturing technologies such as additive manufacturing require research and development to minimize the uncertainties in the produced parts. The research involves experimental measurements and large simulations, which result in huge quantities of data to store and analyze. We address this challenge by alleviating the data storage requirements using lossy data compression. We select wavelet bases as the mathematical tool for compression. Unlike images, additive manufacturing data is often represented on irregular geometries and unstructured meshes. Thus, we use Alpert tree-wavelets as bases for our data compression method. We first analyze different basis functions for the wavelets and find the one that results in maximal compression and miminal error in the reconstructed data. We then devise a new adaptive thresholding method that is data-agnostic and allows a priori estimation of the reconstruction error. Finally, we propose metrics to quantify the global and local errors in the reconstructed data. One of the error metrics addresses the preservation of physical constraints in reconstructed data fields, such as divergence-free stress field in structural simulations. While our compression and decompression method is general, we apply it to both experimental and computational data obtained from measurements and thermal/structural modeling of the sintering of a hollow cylinder from metal powders using a Laser Engineered Net Shape process. The results show that monomials achieve optimal compression performance when used as wavelet bases. The new thresholding method results in compression ratios that are two to seven times larger than the ones obtained with commonly used thresholds. Overall, adaptive Alpert tree-wavelets can achieve compression ratios between one and three orders of magnitude depending on the features in the data that are required to preserve. These results show that Alpert tree-wavelet compression is a viable and promising technique to reduce the size of large data structures found in both experiments and simulations.

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TYPE Journal Article YEAR 2019
ScopusOSTIDOI

On the convergence of the Neumann series for electrostatic fracture response

Geophysics

Weiss, Chester J.; van Bloemen Waanders, Bart G.

The feasibility of Neumann-series expansion of Maxwell's equations in the electrostatic limit is investigated for potentially rapid and approximate subsurface imaging of geologic features proximal to metallic infrastructure in an oilfield environment. Although generally useful for efficient modeling of mild conductivity perturbations in uncluttered settings, we have raised the question of its suitability for situations such as oilfields, in which metallic artifacts are pervasive and, in some cases, in direct electrical contact with the conductivity perturbation on which the Neumann series is computed. Convergence of the Neumann series and its residual error are computed using the hierarchical finite-element framework for a canonical oilfield model consisting of an L-shaped, steel-cased well, energized by a steady-state electrode, and penetrating a small set of mildly conducting fractures near the heel of the well. For a given node spacing h in the finite-element mesh, we find that the Neumann series is ultimately convergent if the conductivity is small enough - a result consistent with previous presumptions on the necessity of small conductivity perturbations. However, we also determine that the spectral radius of the Neumann series operator grows as approximately 1/h, thus suggesting that in the limit of the continuous problem h→0, the Neumann series is intrinsically divergent for all conductivity perturbations, regardless of their smallness. The hierarchical finite-element methodology itself is critically analyzed and shown to possess the h2 error convergence of traditional linear finite elements, thereby supporting the conclusion of an inescapably divergent Neumann series for this benchmark example. Application of the Neumann series to oilfield problems with metallic clutter should therefore be done with careful consideration to the coupling between infrastructure and geology. The methods used here are demonstrably useful in such circumstances.

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TYPE Journal Article YEAR 2019
ScopusOSTIDOI

Wireless Temperature Sensing Using Permanent Magnets for Nonlinear Feedback Control of Exothermic Polymers

IEEE Sensors Journal

Mazumdar, Anirban; Chen, Yi; van Bloemen Waanders, Bart G.; Brooks, Carlton F.; Kuehl, Michael K.; Nemer, Martin N.

Epoxies and resins can require careful temperature sensing and control in order to monitor and prevent degradation. To sense the temperature inside a mold, it is desirable to utilize a small, wireless sensing element. In this paper, we describe a new architecture for wireless temperature sensing and closed-loop temperature control of exothermic polymers. This architecture is the first to utilize magnetic field estimates of the temperature of permanent magnets within a temperature feedback control loop. We further improve performance and applicability by demonstrating sensing performance at relevant temperatures, incorporating a cure estimator, and implementing a nonlinear temperature controller. This novel architecture enables unique experimental results featuring closed-loop control of an exothermic resin without any physical connection to the inside of the mold. In this paper, we describe each of the unique features of this approach, including magnetic field-based temperature sensing, extended Kalman filtering for cure state estimation, and nonlinear feedback control over time-varying temperature trajectories. We use experimental results to demonstrate how low-cost permanent magnets can provide wireless temperature sensing up to ∼ 90°C. In addition, we use a polymer cure-control testbed to illustrate how internal temperature sensing can provide improved temperature control over both short and long time-scales. This wireless temperature sensing and control architecture holds value for a range of manufacturing applications.

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI

Data Analysis for the Born Qualified Grand LDRD Project

Swiler, Laura P.; van Bloemen Waanders, Bart G.; Jared, Bradley H.; Koepke, Joshua R.; Whetten, Shaun R.; Madison, Jonathan D.; Ivanoff, Thomas I.; Jackson, Olivia D.; Cook, Adam W.; Brown-Shaklee, Harlan J.; Kammler, Daniel K.; Johnson, Kyle J.; Ford, Kurtis R.; Bishop, Joseph E.; Roach, R.A.

This report summarizes the data analysis activities that were performed under the Born Qualified Grand Challenge Project from 2016 - 2018. It is meant to document the characterization of additively manufactured parts and processe s for this project as well as demonstrate and identify further analyses and data science that could be done relating material processes to microstructure to properties to performance.

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TYPE SAND Report YEAR 2018
OSTIDOI

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

IEEE Transactions on Magnetics

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.; van Bloemen Waanders, Bart G.; Bond, Stephen D.; Nemer, Martin N.

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. In this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results show that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μ m when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Last, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI

Changing the Engineering Design & Qualification Paradigm in Component Design & Manufacturing (Born Qualified)

Roach, R.A.; Bishop, Joseph E.; Jared, Bradley H.; Keicher, David M.; Cook, Adam W.; Whetten, Shaun R.; Forrest, Eric C.; Stanford, Joshua S.; Boyce, Brad B.; Johnson, Kyle J.; Rodgers, Theron R.; Ford, Kurtis R.; Martinez, Mario J.; Moser, Daniel M.; van Bloemen Waanders, Bart G.; Chandross, M.; Abdeljawad, Fadi F.; Allen, Kyle M.; Stender, Michael S.; Beghini, Lauren L.; Swiler, Laura P.; Lester, Brian T.; Argibay, Nicolas A.; Brown-Shaklee, Harlan J.; Kustas, Andrew K.; Sugar, Joshua D.; Kammler, Daniel K.; Wilson, Mark A.

Abstract not provided.

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TYPE Presentation YEAR 2018
OSTI
Results 26–50 of 159
Results 26–50 of 159