An integrated framework for solid modeling and structural analysis of layered composites with defects

Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

doi:10.1016/j.cad.2018.07.006

Cited by 11 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our toolkit, known as "Delamo" [2] provides the means to execute these scripts including creation of layer-by-layer solid models and generating instructions to the finite element package to apply the desired boundary conditions. The current im- Figure 3.…”

Section: Center For Nondestructive Evaluationmentioning

confidence: 99%

Automated Construction and Insertion of Layer-by-Layer Finite Element Sub-Models of Damaged Composites

Holland¹,

Krishnamurthy²,

Bingol³

et al. 2018

American Society for Composites 2018

Self Cite

View full text Add to dashboard Cite

Finite element models of composite structures are generally shell-based and modeled at the laminate level. More detailed layer-by-layer lamina-level models are sometimes needed for representing joints or for modeling defect growth processes. We describe a method and toolkit for automating the creation and insertion of layerby-layer finite element sub-models of composite laminate. We focus in particular on representing damage captured from nondestructive evaluation (NDE) measurements. The method is based on scripting existing simulation and solid modeling tools (ABAQUS and ACIS). It works even on complicated, curved CAD models. The submodel location is identified by the intersection of a cylinder with the structure. We then execute a series of instructions to generate a new shell with the submodel region removed, generate the layer-by-layer submodel, and bond together the layers and models with desired boundary conditions and defects. The instructions represent the steps of lamination and bonding for creating the composite. The output of the method includes CAD models of the new shell and each lamina within the submodel, and a Python script for ABAQUS that will load the CAD models, bond them together, and apply the specified boundary conditions. Disciplines Disciplines Materials Science and Engineering | Structures and Materials Comments Comments

show abstract

Section: Center For Nondestructive Evaluationmentioning

confidence: 99%

Automated Construction and Insertion of Layer-by-Layer Finite Element Sub-Models of Damaged Composites

Holland¹,

Krishnamurthy²,

Bingol³

et al. 2018

American Society for Composites 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Layered defects are a common problem in building structures, primarily manifesting as poor adhesion, incomplete integration, or misalignment between the building surface and the internal structure (Lourenço et al, 2016;Lublasser et al, 2017;Bingol et al, 2019). Such defects can lead to further deterioration of the building's surface coating, such as crack formation and component detachment, posing a potential threat to the normal use and 10.…”

Section: Introductionmentioning

confidence: 99%

Semi-real-time infrared thermography for detecting layering defects in plasters solidification within indoor environments

Wan,

Zhao,

Zhang

et al. 2024

Front. Mater.

View full text Add to dashboard Cite

In the solidification of plasters, promptly identifying layering defects is vital to reduce later inspection and maintenance expenses. Traditional tapping methods for defect detection, while widespread, are inefficient and can damage walls. This study proposes an innovative method utilizing Infrared Thermal Imaging (IRT) for semi real-time detection of layering defects during the solidification phase. The method was applied within the first 48 h following the application of two different plasters (Cement and Gypsum, mixed on-site as needed, not pre-dosed, and applied in a single layer), systematically examining the effects of plaster composition and environmental temperature conditions. The results showed that all preset defects were successfully identified. It was observed that larger defects are more readily detectable at a given thickness, and conversely, thicker defects are more discernible at a fixed size, with the dimension of the defect having a more pronounced impact on absolute contrast than its thickness. Notably, cement plaster exhibited two distinct temporal windows for defect detection, primarily influenced by environmental temperatures. In contrast, gypsum mortar presented two detection phases, with the initial phase being predominantly governed by the heat of hydration and the latter by ambient temperature conditions. The application of IRT technology in this research demonstrates its efficacy in accurately detecting layering defects during the solidification of plasters. This method offers valuable insights and guidance for the application of plaster layers in real-world engineering scenarios, potentially reducing maintenance costs and improving construction quality.

show abstract

“…The development of machine learning tools for computer-aided design in chemistry is a dynamic area of research [1][2][3][4]. In the last decades, among many other artificial intelligence approaches, the use of quantitative structure-property relationship (QSPR) models has increased noticeably [5].…”

Section: Introductionmentioning

confidence: 99%

Computer-aided design of polymeric materials: Computational study for characterization of databases for prediction of mechanical properties under polydispersity

Cravero

Schustik

Martínez

et al. 2019

Chemometrics and Intelligent Laboratory Systems

View full text Add to dashboard Cite

In Polymer Informatics, quantitative structure-property relationship (QSPR) modeling is an emerging approach for predicting relevant properties of polymers in the context of computer-aided design of industrial materials. Nevertheless, most QSPR models available in the literature use simplistic computational representations of polymers based on their structural repetitive unit. The aim of this work is to evaluate the effect of this simplification and to analyze new strategies to achieve alternative characterizations that capture the phenomenon of polydispersity. In particular, the experiments reported in this work are focused on three mechanical properties derived from the tensile test. The reported results revealed the disadvantages of using these simplified representations. Besides, we contributed with alternative representations for the databases of polymer molecular descriptors that achieved more realistic and accurate QSPR models.

show abstract

An integrated framework for solid modeling and structural analysis of layered composites with defects

Cited by 11 publications

References 18 publications

Automated Construction and Insertion of Layer-by-Layer Finite Element Sub-Models of Damaged Composites

Automated Construction and Insertion of Layer-by-Layer Finite Element Sub-Models of Damaged Composites

Semi-real-time infrared thermography for detecting layering defects in plasters solidification within indoor environments

Computer-aided design of polymeric materials: Computational study for characterization of databases for prediction of mechanical properties under polydispersity

Contact Info

Product

Resources

About