Dynamic Behavior of Hybrid APM (Advanced Pore Morphology Foam) and Aluminum Foam Filled Structures
The aim of this work is to evaluate the effect of different densities of hybrid aluminum polymer foam on the frequency behavior of a foam filled steel structure with different ratios between steel and foam masses. The foam filled structure is composed of three steel tubes with a welded flange at both ends bolted together to form a portal grounded by its free ends. Structure, internal and ground constraints have been designed and manufactured in order to minimize nonlinear effects and to guarantee optimal constraint conditions. Mode shapes and frequencies were verified with finite elements models (FEM) to be in the range of experimental modal analysis, considering the frequency measurement range limits for instrumented hammer and accelerometer. Selected modes have been identified with suitable modal parameters extraction techniques. Each structure has been tested before and after filling, in order to compute the percentage variation of modal parameters. Two different densities of hybrid aluminum polymer foam have been tested and compared with structures filled with aluminum foams produced using the powder compact melting technique. All the foam fillings were able to suppress high frequency membrane modes which results in a reduction of environmental noise and an increase in performance of the components. Low frequency modes show an increase in damping ratio only when small thickness steel frames are filled with either Hybrid APM or Alulight foam.
Endurance of Damping Properties of Foam-Filled Tubes
The favorable energy-absorption properties of metal foams have been frequently proposed for damping or anti-crash applications. The aim of this paper is to investigate the endurance of these properties for composite structures, made by a metal or a hybrid metal-polymeric foam used as the core filling of a tubular metal case. The results of experimental tests are shown, run with two types of structures: 1) square steel tubes filled with aluminum or with hybrid aluminum-polymer foams; 2) round titanium tubes filled with aluminum foams. The paper shows that the damping properties of a foam-filled tube change (improve) with the number of cycles, while all other dynamic properties are nearly constant. This result is very important for several potential applications where damping is crucial, e.g., for machine tools.
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.