Image-based meshing is opening up exciting new possibilities for the application of computational continuum mechanics methods (finite-element and computational fluid dynamics) to a wide range of biomechanical and biomedical problems that were previously intractable owing to the difficulty in obtaining suitably realistic models. Innovative surface and volume mesh generation techniques have recently been developed, which convert three-dimensional imaging data, as obtained from magnetic resonance imaging, computed tomography, micro-CT and ultrasound, for example, directly into meshes suitable for use in physics-based simulations. These techniques have several key advantages, including the ability to robustly generate meshes for topologies of arbitrary complexity (such as bioscaffolds or composite micro-architectures) and with any number of constituent materials (multi-part modelling), providing meshes in which the geometric accuracy of mesh domains is only dependent on the image accuracy (image-based accuracy) and the ability for certain problems to model material inhomogeneity by assigning the properties based on image signal strength. Commonly used mesh generation techniques will be compared with the proposed enhanced volumetric marching cubes (EVoMaCs) approach and some issues specific to simulations based on threedimensional image data will be discussed. A number of case studies will be presented to illustrate how these techniques can be used effectively across a wide range of problems from characterization of micro-scaffolds through to head impact modelling.
Health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost, and durable products. In an effort to address technical issues concerning health monitoring, this article considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating turbine engine-like-disk to detect the disk faults and assess its structural integrity. The experimental results composed at a range of rotational speeds from tests conducted at the NASA Glenn Research Center's Rotordynamics Laboratory are evaluated and integrated into multiple data-driven anomaly detection techniques to identify faults and anomalies in the disk. In summary, this study presents a select evaluation of online health monitoring of a rotating disk using high caliber capacitive sensors and demonstrates the capability of the in-house spin system.
For SiC/SiC composites to replace metallic materials in future turbine engines, prime reliant environmental barrier coatings (EBCs) are required. However, due to the mismatch in thermal expansion and elastic modulus between the substrate and the coating, thermal residual stresses are generated in the coating after processing as well as during exposure to turbine engine operating conditions. The nature and magnitude of the thermal stresses will have a profound effect on the durability and reliability of the EBC. To estimate the magnitude of in-plane ( x- and y-directions) and through-the-thickness ( z-direction) thermal residual stresses in the coating, a finite element model (FEM) was developed. Using FEM, the residual stresses were predicted for three multilayered EBC systems considered for the SiC/SiC composites: (1) barium strontium aluminum silicate, (2) ytterbium disilicate, and (3) ytterbium monosilicate. Influence of thickness and modulus of the coating layer on the thermal residual stress were modeled. Results indicate that thermal residual stresses in the SiC/SiC composite substrate are compressive and in all the three coatings tensile. Further examination indicates that in the z-direction, tensile stresses in all three systems are negligible, but in-plane tensile stresses can be significant depending on the composition of the constituent layer and the distance from the substrate. Comparison of predicted thermal residual stresses in the three systems shows that the ytterbium monosilicate system has the highest stress (~395 MPa), while the other two systems averaged about 80 MPa in one of the coating layers. A parametric analysis conducted indicates that lowering the modulus of the coating can lower the thermal residual stresses.
This paper is a Part I of a literature review documentation describing the currently available and used techniques that are being explored by material scientists and researchers in the field of materials characterizations and testing for both thermal and environmental barrier coatings (TBCs and EBCs, respectively). This review contains relevant information regarding the most common coating applications and their impact on the durability and life of both the coatings and the substrate materials. It also includes a description of the methodologies of coating applications and their pros and cons. A discussion of the applicability, failure modes and modeling approaches that are presently available and utilized by active researchers in the field is also included. Part II will illustrate an in-depth assessment of various aspects of the available and developing life prediction models for both TBC and EBC and the influence of intrinsic and extrinsic factors on their thermal and mechanical stability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.