Deep learning for full-field ultrasonic characterization

This study takes advantage of recent advances in machine learning to establish a physics-based data analytic platform for distributed reconstruction of mechanical properties in layered components from full waveform data. In this vein, two logics, namely the direct inversion and physics-informed neural networks (PINNs), are explored. The direct inversion entails three steps: (i) spectral denoising and differentiation of the full-field data, (ii) building appropriate neural maps to approximate the profile of unknown physical and regularization parameters on their respective domains, and (iii) simultaneous training of the neural networks by minimizing the Tikhonov-regularized PDE loss using data from (i). PINNs furnish efficient surrogate models of complex systems with predictive capabilities via multitask learning where the field variables are modeled by neural maps endowed with (scaler or distributed) auxiliary parameters such as physical unknowns and loss function weights. PINNs are then trained by minimizing a measure of data misfit subject to the underlying physical laws as constraints. In this study, to facilitate learning from ultrasonic data, the PINNs loss adopts (a) wavenumber-dependent Sobolev norms to compute the data misfit, and (b) non-adaptive weights in a specific scaling framework to naturally balance the loss objectives by leveraging the form of PDEs germane to elastic-wave propagation. Both paradigms are examined via synthetic and laboratory test data. In the latter case, the reconstructions are performed at multiple frequencies and the results are verified by a set of complementary experiments highlighting the importance of verification and validation in data-driven modeling

The effects of physical decontamination methods on zirconia implant surfaces: a systematic review

Purpose: Peri-implantitis therapy and implant maintenance are fundamental practices to enhance the longevity of zirconia implants. However, the use of physical decontamination methods, including hand instruments, polishing devices, ultrasonic scalers, and laser systems, might damage the implant surfaces. The aim of this systematic review was to evaluate the effects of physical decontamination methods on zirconia implant surfaces. Methods: A systematic search was conducted using 5 electronic databases: Ovid MEDLINE, PubMed, Scopus, Web of Science, and Cochrane. Hand searching of the OpenGrey database, reference lists, and 6 selected dental journals was also performed to identify relevant studies satisfying the eligibility criteria. Results: Overall, 1049 unique studies were identified, of which 11 studies were deemed suitable for final review. Air-abrasive devices with glycine powder, prophylaxis cups, and ultrasonic scalers with non-metal tips were found to cause minimal to no damage to implant-grade zirconia surfaces. However, hand instruments and ultrasonic scalers with metal tips have the potential to cause major damage to zirconia surfaces. In terms of laser systems, diode lasers appear to be the most promising, as no surface alterations were reported following their use. Conclusion: Air-abrasive devices and prophylaxis cups are safe for zirconia implant decontamination due to preservation of the implant surface integrity. In contrast, hand instruments and ultrasonic scalers with metal tips should be used with caution. Recommendations for the use of laser systems could not be fully established due to significant heterogeneity among included studies, but diode lasers may be the best-suited system. Further research—specifically, randomised controlled trials—would further confirm the effects of physical decontamination methods in a clinical setting

Verified partial eigenvalue computations using contour integrals for Hermitian generalized eigenproblems

We propose a verified computation method for partial eigenvalues of a Hermitian generalized eigenproblem. The block Sakurai-Sugiura Hankel method, a contour integral-type eigensolver, can reduce a given eigenproblem into a generalized eigenproblem of block Hankel matrices whose entries consist of complex moments. In this study, we evaluate all errors in computing the complex moments. We derive a truncation error bound of the quadrature. Then, we take numerical errors of the quadrature into account and rigorously enclose the entries of the block Hankel matrices. Each quadrature point gives rise to a linear system, and its structure enables us to develop an efficient technique to verify the approximate solution. Numerical experiments show that the proposed method outperforms a standard method and infer that the proposed method is potentially efficient in parallel.Comment: 15 pages, 4 figures, 1 tabl

A Smoothing Newton-BICGStab Method for Least Squares Matrix Nuclear Norm Problems

Master'sMASTER OF SCIENC

A Comparative Performance of Discrete Wavelet Transform Implementations Using Multiplierless

Using discrete wavelet transform (DWT) in high-speed signal-processing applications imposes a high degree of care to hardware resource availability, latency, and power consumption. In this chapter, the design aspects and performance of multiplierless DWT is analyzed. We presented the two key multiplierless approaches, namely the distributed arithmetic algorithm (DAA) and the residue number system (RNS). We aim to estimate the performance requirements and hardware resources for each approach, allowing for the selection of proper algorithm and implementation of multi-level DAA- and RNS-based DWT. The design has been implemented and synthesized in Xilinx Virtex 6 ML605, taking advantage of Virtex 6’s embedded block RAMs (BRAMs)

Pionic Fusion of ⁴He + ¹²C

Pionic fusion is the process by which two nuclei collide, undergo complete fusion, and then de-excite solely by the emission of a pion. Previously measured pionic fusion cross sections are inconsistent with known mechanisms for pion production and suggest unknown collective processes might dominate production at low energies in heavy ion collisions. In this work, an experiment was developed to make the first coincident measurement of pionic fusion for a charged pion channel of a reaction for which there are no previous measurements. The pionic fusion reaction ⁴He (55 MeV/u) + ¹²C → ¹⁶N + π⁺ was studied at the Texas A&M University Cyclotron Institute. The ¹⁶N fusion residues were detected using a dE-E silicon telescope at the focal plane of the MARS spectrometer and the newly designed ParTI phoswich detector array was used to detect the charged pions. Fast-sampling digitizers recorded the waveform responses of the phoswiches which were used to identify the pions through fast vs. slow (dEE) pulse shape discrimination and through the characteristic decay of the muon daughters of the implanted pions. An energy calibration method for light charged particles including charged pions is developed for the ParTI phoswich detectors and the geometrical and particle identification efficiencies of the array are explored. The "muon decay trigger" which was implemented in the firmware of the onboard FPGA in the digitizers is discussed and its ability to increase the pion event selectivity is characterized. A detailed characterization of the transmission efficiency and particle identification capabilities at the focal plane of MARS is also given. Cross sections are reported for all species detected at the focal plane of MARS and upper limits for the cross section of pionic fusion based on the measurement of ¹⁶N in MARS and charged pions in the ParTI array are reported

Strapdown inertial measurement unit computer, volume 1 Final report

Strapdown inertial measurement unit design, calculations, and operating instruction