Predicting the Near Field Underwater Explosion Response of Coated Composite Cylinders using Multiscale Simulations, Experiments, and Machine Learning

Direct measurement of the wall pressure loading subjected to the near-field underwater explosion is of great difficulty. In this article, an improved methodology and a lab-scale experimental system are proposed and manufactured to assess the wall pressure loading. In the methodology, a Hopkinson bar (HPB), used as the sensing element, is inserted through the hole drilled on the target plate and the bar’s end face lies flush with the loaded face of the target plate to detect and record the pressure loading. Furthermore, two improvements have been made on this methodology to measure the wall pressure loading from a near-field underwater explosion. The first one is some waterproof units added to make it suitable for the underwater environment. The second one is a hard rubber cylinder placed at the distal end, and a pair of ropes taped on the HPB is used to pull the HPB against the cylinder hard to ensure the HPB’s end face flushes with loaded face of the target plate during the bubble collapse. To validate the pressure measurement technique based on the HPB, an underwater explosion between two parallelly mounted circular target plates is used as the validating system. Based on the assumption that the shock wave pressure profiles at the two points on the two plates which are symmetrical to each other about the middle plane of symmetry are the same, it was found that the pressure obtained by the HPB was in excellent agreement with pressure transducer measurements, thus validating the proposed technique. To verify the capability of this improved methodology and experimental system, a series of minicharge underwater explosion experiments are conducted. From the recorded pressure-time profiles coupled with the underwater explosion evolution images captured by the HSV camera, the shock wave pressure loading and bubble-jet pressure loadings are captured in detail at 5 mm, 10 mm, …, 30 mm stand-off distances. Part of the pressure loading of the experiment at 35 mm stand-off distance is recorded, which is still of great help and significance for engineers. Especially, the peak pressure of the shock wave is captured.

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Near Field Breast Tumor Detection Using Ultra-Narrow Band Probe with Machine Learning Techniques

Scientific Reports ◽

10.1038/s41598-018-31046-9 ◽

2018 ◽

Vol 8 (1) ◽

Cited By ~ 3

Author(s):

Maged A. Aldhaeebi ◽

Thamer S. Almoneef ◽

Abdulbaset Ali ◽

Zhao Ren ◽

Omar M. Ramahi

Keyword(s):

Machine Learning ◽

Breast Tumor ◽

Narrow Band ◽

Near Field ◽

Tumor Detection ◽

Machine Learning Techniques ◽

Learning Techniques

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Fast and Accurate Near-Field to Far-Field Transformation Using an Adaptive Sampling Algorithm and Machine Learning

2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting ◽

10.1109/apusncursinrsm.2019.8888868 ◽

2019 ◽

Cited By ~ 1

Author(s):

Rezvan Rafiee Alavi ◽

Rashid Mirzavand ◽

Pedram Mousavi

Keyword(s):

Machine Learning ◽

Adaptive Sampling ◽

Near Field ◽

Far Field ◽

Sampling Algorithm ◽

Field Transformation

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Fast extreme ultraviolet lithography mask near-field calculation method based on machine learning

Applied Optics ◽

10.1364/ao.384407 ◽

2020 ◽

Vol 59 (9) ◽

pp. 2829

Author(s):

Jiaxin Lin ◽

Lisong Dong ◽

Taian Fan ◽

Xu Ma ◽

Rui Chen ◽

...

Keyword(s):

Machine Learning ◽

Calculation Method ◽

Extreme Ultraviolet ◽

Near Field ◽

Field Calculation ◽

Extreme Ultraviolet Lithography ◽

Ultraviolet Lithography

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Numerical Simulation on Response of Foam Core Sandwich Panels Subjected to Underwater Explosion

Volume 9: Prof. Norman Jones Honoring Symposium on Impact Engineering; Prof. Yukio Ueda Honoring Symposium on Idealized Nonlinear Mechanics for Welding and Strength of Structures ◽

10.1115/omae2016-55149 ◽

2016 ◽

Author(s):

Dongjie Ai ◽

Yuansheng Cheng ◽

Jun Liu ◽

Jianhu Liu ◽

Haikun Wang ◽

...

Keyword(s):

Energy Absorption ◽

Sandwich Structures ◽

Near Field ◽

Sandwich Panels ◽

Underwater Explosion ◽

Core Material ◽

Design Parameters ◽

Equal Weight ◽

Core Height ◽

Panel Thickness

Sandwich panel structures, which consist of two thin faces and low relative density cores, can significantly mitigate the possibilities of panel fractures. In the present paper, numerical simulations are conducted to study the deformation and fracture modes of sandwich structures under near-field underwater blasts and contact underwater blasts. Two different core materials are employed, namely aluminum foam and PVC foam. Main focus of this paper was placed to (i) study the failure mechanisms and energy absorption characteristics of sandwich structures in typical conditions, (ii) to demonstrate the benefits of such structures compared with solid plates of equal weight, and (iii) to obtain the properties of withstanding underwater explosion for single core material sandwich panels. In addition, the effects of panel thickness configuration and core height on deformation and energy absorption of the plates were explored. Results indicated that sandwich structures showed an effective reduction in the maximum panel deflection compared with a monolithic plate of same mass. The design parameters have great impacts on the results.

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The Fluid-Solid Interaction Dynamics between Underwater Explosion Bubble and Corrugated Sandwich Plate

Shock and Vibration ◽

10.1155/2016/6057437 ◽

2016 ◽

Vol 2016 ◽

pp. 1-21

Author(s):

Hao Wang ◽

Yuan Sheng Cheng ◽

Jun Liu ◽

Lin Gan

Keyword(s):

Shock Wave ◽

Failure Modes ◽

Sandwich Structures ◽

Numerical Models ◽

Near Field ◽

Three Dimensional ◽

Underwater Explosion ◽

Bubble Collapse ◽

Fe Model ◽

Wave Load

Lightweight sandwich structures with highly porous 2D cores or 3D (three-dimensional) periodic cores can effectively withstand underwater explosion load. In most of the previous studies of sandwich structure antiblast dynamics, the underwater explosion (UNDEX) bubble phase was neglected. As the UNDEX bubble load is one of the severest damage sources that may lead to structure large plastic deformation and crevasses failure, the failure mechanisms of sandwich structures might not be accurate if only shock wave is considered. In this paper, detailed 3D finite element (FE) numerical models of UNDEX bubble-LCSP (lightweight corrugated sandwich plates) interaction are developed by using MSC.Dytran. Upon the validated FE model, the bubble shape, impact pressure, and fluid field velocities for different stand-off distances are studied. Based on numerical results, the failure modes of LCSP and the whole damage process are obtained. It is demonstrated that the UNDEX bubble collapse jet local load plays a more significant role than the UNDEX shock wave load especially in near-field underwater explosion.

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Near-field Sensors with Machine Learning for Breast Tumor Detection

Journal of Computational Vision and Imaging Systems ◽

10.15353/jcvis.v4i1.328 ◽

2018 ◽

Vol 4 (1) ◽

pp. 3

Author(s):

Maged A. Aldhaeebi ◽

Thamer S. Almoneef ◽

Omar M. Ramahi

Keyword(s):

Machine Learning ◽

Feature Extraction ◽

Breast Tumor ◽

Extraction Method ◽

Near Field ◽

Tumor Detection ◽

Electromagnetic Properties ◽

Feature Extraction Method ◽

The Difference ◽

Breast Tissues

In this work, we propose the use of an electrically small novel antenna as a probe combined with a classification algorithm for nearfield microwave breast tumor detection. The resonant probe ishighly sensitive to the changes in the electromagnetic properties of the breast tissues such that the presence of the tumor is estimatedby determining the changes in the magnitude and phase responseof the reflection coefficient of the sensor. The Principle Component placed at the middle of the probe as shown in Fig. 1. The mainAnalysis (PCA) feature extraction method is applied to emphasize the difference in the probe responses for both the healthy and thetumourous cases . We show that when a numerical realistic breast with and without tumor cells is placed in the near field of the probe, the probe is capable of distinguishing between healthy and tumorous tissue. In addition, the probe is able to identify tumors with various sizes placed in single locations.

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