Process Parameter Prediction and Modeling of Laser Percussion Drilling by Artificial Neural Networks.

Finding process parameters for laser-drilled blind holes often relies on an engineer's experience and the trial-and-error method. However, determining such parameters should be possible using methodical calculations. Studies have already begun to examine the use of neural networks to improve the efficiency of this situation. This study extends the field of research by applying artificial neural networks (ANNs) to predict the required parameters for drilling stainless steel with a certain depth and diameter of blind holes, and it also pre-simulates the drilling result of these predicted parameters before actual laser processing. The pre-simulated drilling results were also compared with real-world observations after drilling the stainless steel. These experimental findings confirmed that the proposed method can be used to accurately select laser drilling parameters and predict results in advance. Being able to make these predictions successfully reduces time spent, manpower, and the number of trial-and-error shots required in the pre-processing phase. In addition to providing specific data for engineers to use, this method could also be used to develop a set of reference parameters, greatly simplifying the laser drilling process.

Impact damage visualization in a honeycomb composite panel through laser inspection using zero-lag cross-correlation imaging condition.

A fully non-contact laser-based nondestructive inspection (NDI) system is developed to detect and visualize damage in structures. The study focuses on the size quantification and characterization of a barely visible impact damage (BVID) in a honeycomb composite panel. The hardware consists of a Q-switched Nd:YAG pulse laser that probes the panel by generating broadband guided waves via thermo-elastic expansion. The laser, in combination with a set of galvano-mirrors is used to raster scan over a two-dimensional surface covering the damaged region of an impacted quasi-isotropic [60/0/-60]s honeycomb composite panel. The out-of-plane velocities are measured at a fixed location normal to the surface by a laser Doppler vibrometer (LDV). An ultrasonic full wavefield assembled from the three-dimensional space-time data matrix in the interrogated area is first acquired and then processed for imaging the impacted damage area. A wavenumber filtering technique in terms of wave vectors is applied to distinguish the forward and backward wavefields in the wavenumber-frequency domain. A zero-lag cross correlation (ZLCC) imaging condition is then employed in the space-frequency domain for damage imaging. The ZLCC imaging condition consists of cross correlating the incident and reflected wavefields in the entire scanned region. The condition not only images the damage boundary between incident and reflected waves outside the damage region but also, for longer time windows, enables to capture the momentary standing waves formed within the damaged region. The ZLCC imaging condition imaged two delaminated region: a main delamination, which was a skewed elliptic with major and minor axis lengths roughly 17 mm and 10 mm respectively, and a secondary delamination region approximately 6 mm by 4 mm, however, which can only be shown at higher frequency range around 80-95 kHz. To conclude, the ZLCC results were in very good agreement with ultrasonic C-scan and X-ray computed tomographic (X-ray CT) scan results. Since the imaging condition is performed in the space-frequency domain, the imaging from ZLCC can also reveal resonance modes which are shown in the main delaminated area by windowing a narrow frequency band sequentially.

Theranostic mesoporous silica nanoparticles biodegrade after pro-survival drug delivery and ultrasound/magnetic resonance imaging of stem cells.

Increasing cell survival in stem cell therapy is an important challenge for the field of regenerative medicine. Here, we report theranostic mesoporous silica nanoparticles that can increase cell survival through both diagnostic and therapeutic approaches. First, the nanoparticle offers ultrasound and MRI signal to guide implantation into the peri-infarct zone and away from the most necrotic tissue. Second, the nanoparticle serves as a slow release reservoir of insulin-like growth factor (IGF)-a protein shown to increase cell survival. Mesenchymal stem cells labeled with these nanoparticles had detection limits near 9000 cells with no cytotoxicity at the 250 µg/mL concentration required for labeling. We also studied the degradation of the nanoparticles and showed that they clear from cells in approximately 3 weeks. The presence of IGF increased cell survival up to 40% (p<0.05) versus unlabeled cells under in vitro serum-free culture conditions.