An even-load-distribution design for composite bolted joints using a novel circuit model and neural network

Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning

(2020) Chun‐Teh Chen et al.   Advanced Science

Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework

(2020) Chunping Ma et al.   npj Computational Materials

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

(2020) Anh Tran et al.   ACTA MATERIALIA

Theory-guided machine learning for damage characterization of composites

(2020) Navid Zobeiry et al.   COMPOSITE STRUCTURES

Revealing the competitive fatigue failure behaviour of CFRP-aluminum two-bolt, double-lap joints

(2020) Meijuan Shan et al.   COMPOSITE STRUCTURES

An improved 2D finite element model for bolt load distribution analysis of composite multi-bolt single-lap joints

(2020) Fengrui Liu et al.   COMPOSITE STRUCTURES

Theoretical definition of a new custom finite element for structural modeling of composite bolted joints

(2020) Valerio G. Belardi et al.   COMPOSITE STRUCTURES

Machine learning for composite materials

(2019) Chun-Teh Chen et al.   MRS Communications

A modified stiffness method considering effects of hole tensile deformation on bolt load distribution in multi-bolt composite joints

(2019) Libin Zhao et al.   COMPOSITES PART B-ENGINEERING

Recent advances and applications of machine learning in solid-state materials science

(2019) Jonathan Schmidt et al.   npj Computational Materials

An enhanced spring-mass model for stiffness prediction in single-lap composite joints with considering assembly gap and gap shimming

(2018) Yuxing Yang et al.   COMPOSITE STRUCTURES

An interpretation of the load distributions in highly torqued single-lap composite bolted joints with bolt-hole clearances

(2018) Fengrui Liu et al.   COMPOSITES PART B-ENGINEERING

Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

(2018) Zijiang Yang et al.   COMPUTATIONAL MATERIALS SCIENCE

Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment

(2018) Grace X. Gu et al.   Materials Horizons

A machine learning approach to model solute grain boundary segregation

(2018) Liam Huber et al.   npj Computational Materials

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials

Improving load sharing in hybrid bonded/bolted composite joints using an interference-fit bolt

(2016) Karthik Prasanna Raju et al.   COMPOSITE STRUCTURES

A general-purpose machine learning framework for predicting properties of inorganic materials

(2016) Logan Ward et al.   npj Computational Materials

An analytical model for the prediction of load distribution in multi-bolt composite joints including hole-location errors

(2014) J. Lecomte et al.   COMPOSITE STRUCTURES

Prediction of impact damage tolerance of drop impacted WGFRP composite by artificial neural network using acoustic emission parameters

(2014) P. Ramasamy et al.   COMPOSITES PART B-ENGINEERING

A modified failure envelope method for failure prediction of multi-bolt composite joints

(2013) Fengrui Liu et al.   COMPOSITES SCIENCE AND TECHNOLOGY

Bonded repair of composite aircraft structures: A review of scientific challenges and opportunities

(2013) K.B. Katnam et al.   PROGRESS IN AEROSPACE SCIENCES

An analytical model for the prediction of load distribution in highly torqued multi-bolt composite joints

(2010) C.T. McCarthy et al.   COMPOSITE STRUCTURES

Mechanics of mechanically fastened joints in polymer–matrix composite structures – A review

(2008) Srinivasa D. Thoppul et al.   COMPOSITES SCIENCE AND TECHNOLOGY