Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


This content will become publicly available on January 8, 2027

Title: Thermal Conductivity Modeling and Optimization of Ceramic Matrix Composite Spinodoids
Spinodoids exhibit unique non-periodic architectures that offer distinct advantages in mechanical performance compared to conventional architected materials such as triply periodic minimal surfaces (TPMS) and lattice structures. In this study, spinodal topologies are optimized to enhance thermal conductivity, particularly for use in high-temperature aerospace applications. For this purpose, two-dimensional (2D) dual-phase spinodal structures are first generated and mapped into three-dimensional (3D) geometries, and their anisotropic thermal conductivities are evaluated along different spatial directions. A mathematical optimization framework is then implemented to perform topology optimization of spinodoids having a base material of SiC/SiC ceramic matrix composite (CMC). The spinodal structures are parameterized through orientation distributions constrained by conical angles. The steady-state thermal conduction is simulated numerically to compute elemental heat fluxes in three Cartesian directions, and effective thermal conductivities are extracted via the volume-averaging method. The optimization problem defines a composite objective function based on the anisotropic effective conductivities and is solved using a gradient-free heuristic algorithm. The resulting optimum design demonstrates the potential of spinodoid structures to improve thermal management in hot-section components of gas turbine engines.  more » « less
Award ID(s):
2236947
PAR ID:
10703237
Author(s) / Creator(s):
;
Publisher / Repository:
American Institute of Aeronautics and Astronautics
Date Published:
ISBN:
978-1-62410-765-8
Format(s):
Medium: X
Location:
Orlando, FL
Sponsoring Org:
National Science Foundation
More Like this
  1. ; (, Journal of Inverse and Ill-posed Problems)
    null (Ed.)
    Abstract This paper is concerned with the inverse scattering problem for the three-dimensional Maxwell equations in bi-anisotropic periodic structures.The inverse scattering problem aims to determine the shape of bi-anisotropic periodic scatterers from electromagnetic near-field data at a fixed frequency.The factorization method is studied as an analytical and numerical tool for solving the inverse problem.We provide a rigorous justification of the factorization method which results in the unique determination and a fast imaging algorithm for the periodic scatterer.Numerical examples for imaging three-dimensional periodic structures are presented to examine the efficiency of the method. 
    more » « less
  2. ; ; ; ; (, Advanced Engineering Materials)
    Macroporous ceramic materials are ubiquitous in numerous energy-conversion and thermal-management systems. The morphology and material composition influence the effective thermophysical properties of macroporous ceramic structures and interphase transport in interactions with the working fluid. Therefore, tailoring these properties can enable significant performance enhancements by modulating thermal transport, reactivity, and stability. However, conventional ceramic-matrix fabrication techniques limit the ability for tailoring the porous structure and optimizing the performance of these systems, such as by introducing anisotropic morphologies, pore-size gradations, and variations in pore connectivity and material properties. Herein, an integrated framework is proposed for enabling the design, optimization, and fabrication of tailored ceramic porous structures by combining computational modeling, mathematically defined surfaces, and lithography-based additive manufacturing. The benefits of pore-structure tailoring are illustrated experimentally for interstitial combustion in a porous-media burner operating with a smoothly graded matrix structure. In addition, a remarkable range of achievable thermal conductivities for a single material is demonstrated with tuning of the fabrication process, thus providing unique opportunities for modulating thermal transport properties of porous-ceramic structures. 
    more » « less
  3. ; ; (, Journal of Physics: Materials)
    Abstract Spinodal topologies (STs), inspired by material phase transition phenomena, exhibit complex geometries generated by Gaussian random fields (GRFs). These dual-phase structures feature smooth transitions and low-curvature designs, offering enhanced mechanical response compared to traditional surface- or strut-based metamaterials. Their flexible design spaces allow both periodic and non-periodic topologies, making them promising candidates for multiphysics applications. This work presents a computationally efficient data-driven framework for optimizing the mechanical and thermal properties of STs. A convolutional neural network (CNN) is trained on homogenized elastic and thermal properties obtained from finite element analyses. Next, the CNN model is coupled with an optimization solver to design dual-phase STs to improve multiphysics objectives. The inherent variations of STs introduced by the GRF formulation limit the ability of gradient-based optimizers to efficiently search for the design space. To overcome this challenge, a gradient-free global optimization algorithm is integrated into the surrogate model to find optimum designs with superior mechanical and thermal performance. 
    more » « less
  4. ; ; ; ; (, Extreme Mechanics Letters)
    Spinodal metamaterials, with architectures inspired by natural phase-separation processes, have presented a significant alternative to periodic and symmetric morphologies when designing mechanical metamaterials with extreme performance. While their elastic mechanical properties have been systematically determined, their large-deformation, nonlinear responses have been challenging to predict and design, in part due to limited data sets and the need for complex nonlinear simulations. This work presents a novel physics-enhanced machine learning (ML) and optimization framework tailored to address the challenges of designing intricate spinodal metamaterials with customized mechanical properties in large-deformation scenarios where computational modeling is restrictive and experimental data is sparse. By utilizing large-deformation experimental data directly, this approach facilitates the inverse design of spinodal structures with precise finite-strain mechanical responses. The framework sheds light on instability-induced pattern formation in spinodal metamaterialsobserved experimentally and in selected nonlinear simulations—leveraging physics-based inductive biases in the form of nonconvex energetic potentials. Altogether, this combined ML, experimental, and computational effort provides a route for efficient and accurate design of complex spinodal metamaterials for large-deformation scenarios where energy absorption and prediction of nonlinear failure mechanisms is essential. 
    more » « less
  5. ; ; ; ; ; ; ; (, Nanoscale)
    Self-assembled vertically aligned metal–oxide (Ni–CeO 2 ) nanocomposite thin films with novel multifunctionalities have been successfully deposited by a one-step growth method. The novel nanocomposite structures presents high-density Ni-nanopillars vertically aligned in a CeO 2 matrix. Strong and anisotropic magnetic properties have been demonstrated, with a saturation magnetization ( M s ) of ∼175 emu cm −3 and ∼135 emu cm −3 for out-of-plane and in-plane directions, respectively. Such unique vertically aligned ferromagnetic Ni nanopillars in the CeO 2 matrix have been successfully incorporated in high temperature superconductor YBa 2 Cu 3 O 7 (YBCO) coated conductors as effective magnetic flux pinning centers. The highly anisotropic nanostructures with high density vertical interfaces between the Ni nanopillars and CeO 2 matrix also promote the mixed electrical and ionic conductivities out-of-plane and thus demonstrate great potential as nanocomposite anode materials for solid oxide fuel cells and other potential applications requiring anisotropic ionic transport properties. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Text Encoded Conversion
  • XML
  • Save / Share this Record
  • Send to Email