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We introduce the concept of physics-guided transfer learning to predict the thermal conductivity of an additively manufactured short-fiber reinforced polymer (SFRP) using micro-structural characteristics extracted from tensile tests. Developing composite manufacturing digital twins for SFRP composite processes like extrusion deposition additive manufacturing (EDAM) require extensive experimental material characterization. Even the same material system printed on different EDAM systems can result in significant changes to the printed micro-structure, affecting the mechanical and transport properties. This, in turn, makes characterization efforts expensive and time-consuming. Therefore, the objective of the paper is to address this experimental bottleneck and use prior information about the material manufactured in one extrusion system to predict its properties when manufactured in another system. To enable this framework, we assume that changes in properties of the same material when manufactured in different systems arise solely due to microstructural changes. To that end, we present a Bayesian framework that can transfer thermal conductivity properties across extrusion deposition additive manufacturing systems. While we discuss the transfer of thermal conductivity properties, the development is such that the framework can be used for the transfer of other properties that depend on microstructural characteristics defined in the manufacturing process. These include the coefficient of thermal expansion, viscoelastic properties, etc. The framework begins by using thermal conductivity data of the composite printed in one extrusion system to probabilistically infer the constituent thermal properties of the fiber and the polymer. Next, by conducting limited tensile tests of the same material printed in another extrusion system, we infer its orientation tensor. Finally, the inferred constituent thermal conductivity properties and the inferred orientation tensor are coupled using a micromechanics model to predict the thermal conductivity properties of the composite printed in the second extrusion system. We experimentally verify the predictions and show that our method provides a reliable framework for transferring material properties while accounting for epistemic and aleatory uncertainties. • A probabilistic framework to transfer material information across manufacturing systems. • A framework to account for surrogate uncertainty in parameter inference. • Demonstrate transfer of thermal conductivity across additive manufacturing systems. • Applications to transfer other properties including coefficient of thermal expansion. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the large amplitude vibration behavior of nanocomposite cylindrical shells reinforced by single-walled carbon nanotubes (SWCNTs) in thermal environments. The SWCNTs are assumed to be aligned and straight with a uniform layout. Two kinds of carbon nanotube-reinforced composite (CNTRC) shells, namely, uniformly distributed (UD) and functionally graded (FG) reinforcements, are considered. The material properties of FG-CNTRC shells are assumed to be graded in the thickness direction, and are estimated through a micromechanical model. The motion equations are based on a higher-order shear deformation theory with a von Kármán-type of kinematic nonlinearity. The thermal effects are also included and the material properties of CNTRCs are assumed to be temperature-dependent. The equations of motion are solved by an improved perturbation technique to determine the nonlinear frequencies of the CNTRC shells. Numerical results demonstrate that in most cases the natural frequencies of the CNTRC shells are reduced but the nonlinear to linear frequency ratios of the CNTRC shells are increased as the temperature rises. It is found that the natural frequencies are increased by increasing the CNT volume fraction, whereas the CNTRC shells with intermediate CNT volume fraction do not have intermediate nonlinear to linear frequency ratios. [Copyright &y& Elsevier]

Abstract: A general multiscale computational framework that concurrently couples the quantum-mechanical model with the continuum model is developed. This approach is then used to study the electronic properties of single-walled carbon nanotubes (CNTs) influenced by geometry and deformation. The electronic properties of the CNT, such as the band structure and band gap, are intimately connected to its electrical and thermal properties, mechanical stiffness, failure strength, chemical reactivities and many others. The CNT geometry is featured by a cylindrical-shaped structure, which leads to a mixture of the electronic structures that were originally present in graphite. These important effects are incorporated in a coarse-grained tight-binding model based on an extension to the Bloch theorem and the virtual atom cluster model developed previously by the authors. With this approach, we study the correlation among the electronic structures/properties, CNT geometry and applied deformation for a wide variety of tubes. The major technical ingredients and findings are [(1)] Compared with the computational cost of of the full-scale tight-binding calculation with n e being the electronic base functions used, we have developed an efficient concurrent approach as it scales with O(N G ) with N G being the number of quadrature points; [(2)] We have established a new coarse-grained cluster model that provides a direct way of coupling deformation mapping with the quantum-mechanical model. A unique feature of this coarse-grained model is that it does not use any stress and strain concepts as in a standard continuum approach; [(3)] We report strong influences of CNT geometry on its electronic properties. For zigzag tubes with chiral index of (n,0) and radius r, the band gap E g ∝ r −0.695 when the remainder of n divided by 3 (mod(n,3)) is 1 and E g ∝ r −1.109 when mod(n,3)=2; [(4)] We report significant changes in the band gap and electrical conductance as functions of the applied tensile strain and twist. Transitions from metal to semiconductor and vice versa are observed; [(5)] There is a weak coupling between the band gap, electrical conductance and applied bending angle. Based on extensive studies, we conclude that the electron–mechanical coupling relations obtained in this work are more robust than the previous analytical studies in that it takes into account the important effects of curvature and relaxation. The simulation results highlight the importance of the concurrent coupling among the electronic properties, CNT geometry and mechanical deformation. [Copyright &y& Elsevier]

Abstract: This paper summarizes the approaches used to address the thermal validation challenge problem. The approaches differ in their characterization of the thermal properties and uncertainty, the definitions and use of validation metrics, the use of validation experimental data to characterize or improve the model predictions, and the assessment of regulatory compliance. All approaches estimated regulatory failure with the resulting estimated probabilities varying by an order of magnitude. [Copyright &y& Elsevier]

Abstract: In this paper, a consistent integration procedure for the thermoviscoplastic version of the complete Gurson model is proposed. With adiabatic conditions considered and with the use of the backward Euler integration scheme, a numerical algorithm implicit in all variables as well as the corresponding algorithmic operator have been developed. The proposed algorithm was implemented in a finite element code and its performance is demonstrated with the numerical simulation of different examples. [Copyright &y& Elsevier]

The conjugate heat transfer problem is found in non-isothermal physical systems that involve thermodynamic processes between materials that are thermally coupled through non-adiabatic contacts. A very high-order accurate finite volume scheme in general polygonal meshes is proposed to solve conjugate heat transfer problems with arbitrary curved interfaces and imperfect thermal contacts. Besides the discontinuous thermal properties, imperfect thermal contacts are challenging to address since the obtained temperature is also discontinuous on the interface as a consequence of the interfacial thermal resistance. Moreover, the arbitrary curved interfaces are discretized with polygonal meshes to avoid the shortcomings of classical curved mesh approaches, but a specific treatment is required to overcome the geometrical mismatch and properly fulfill the prescribed interface conditions. The proposed method is based on a partitioned formulation of the conjugate heat transfer problem with the appropriate thermal coupling. A generic polynomial reconstruction method is used to provide local approximations of the temperature complemented with the reconstruction for off-site data method to properly fulfill the prescribed interface conditions. A comprehensive numerical benchmark is provided to verify the proposed method and assess its capability in terms of accuracy, convergence order, stability, and robustness. The results provide the optimal very high-order of convergence and prove the capability of the method to handle arbitrary curved interfaces and imperfect thermal contacts. This contribution represents a significant step towards more efficient and versatile numerical methods for complex conjugate heat transfer problems in engineering applications. [ABSTRACT FROM AUTHOR]