Computer Methods in Applied Mechanics and Engineering最新文献

{"title":"Simulating fluid-fluid displacement in a soft capillary tube: How compliance delays interfacial instability and bubble pinch-off","authors":"Sthavishtha R. Bhopalam, Ruben Juanes, Hector Gomez","doi":"10.1016/j.cma.2025.118430","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118430","url":null,"abstract":"The displacement of a more viscous fluid by a less viscous immiscible fluid in confined geometries is a fundamental problem in multiphase flows. Recent experiments have shown that such fluid-fluid displacement in micro-capillary tubes can lead to interfacial instabilities and, eventually bubble pinch-off. A critical yet often overlooked aspect of this system is the effect of tube’s deformability on the onset of interfacial instability and bubble pinch-off. Here, we present a computational fluid-structure interaction model and an algorithm to simulate this fluid-fluid displacement problem in a soft capillary tube. We use a phase-field model for the fluids and a nonlinear hyperelastic model for the solid. Our fluid-structure interaction formulation uses a boundary-fitted approach and we use Isogeometric Analysis for the spatial discretization. Using this computational framework, we study the effects of inlet capillary number and the tube stiffness on the control of interfacial instabilities in a soft capillary tube for both imbibition and drainage. We find that the tube compliance delays or even suppresses the interfacial instability and bubble pinch-off—a finding that has important implications for flow in soft porous media, bio-microfluidics, and manufacturing processes.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"115 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enforcing mesh quality constraints in shape optimization with a gradient projection method","authors":"Sebastian Blauth, Christian Leithäuser","doi":"10.1016/j.cma.2025.118451","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118451","url":null,"abstract":"For the numerical solution of shape optimization problems, particularly those constrained by partial differential equations (PDEs), the quality of the underlying mesh is of utmost importance. Particularly when investigating complex geometries, the mesh quality tends to deteriorate over the course of a shape optimization so that either the optimization comes to a halt or an expensive remeshing operation must be performed before the optimization can be continued. In this paper, we present a novel, semi-discrete approach for enforcing a minimum mesh quality in shape optimization. Our approach is based on Rosen’s gradient projection method, which incorporates mesh quality constraints into the shape optimization problem. The proposed constraints bound the angles of triangular and solid angles of tetrahedral mesh cells and, thus, also bound the quality of these mesh cells. The method treats these constraints by projecting the search direction to the linear subspace of the currently active constraints. Additionally, only slight modifications to the usual line search procedure are required to ensure the feasibility of the method. We present our method for two- and three-dimensional simplicial meshes. We investigate the proposed approach numerically for the drag minimization of an obstacle in a two-dimensional Stokes flow, the optimization of the flow in a pipe governed by the Navier–Stokes equations, and for the large-scale, three-dimensional optimization of a structured packing used in a distillation column. Our results show that the proposed method is indeed capable of guaranteeing a minimum mesh quality for both academic examples and challenging industrial applications. Particularly, our approach allows the shape optimization of complex structures while ensuring that the mesh quality does not deteriorate.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"18 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Bayesian multi-fidelity inverse analysis for expensive and non-differentiable physics-based simulations in high stochastic dimensions","authors":"Jonas Nitzler, Buğrahan Z. Temür, Phaedon-S. Koutsourelakis, Wolfgang A. Wall","doi":"10.1016/j.cma.2025.118442","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118442","url":null,"abstract":"High-dimensional Bayesian inverse analysis (<mml:math altimg=\"si63.svg\"><mml:mrow><mml:mi>dim</mml:mi><mml:mo>≫</mml:mo><mml:mn>100</mml:mn></mml:mrow></mml:math>) is mostly unfeasible for computationally demanding, nonlinear physics-based high-fidelity (HF) models. Usually, the use of more efficient gradient-based inference schemes is impeded if the multi-physics models are provided by complex legacy codes. Adjoint-based derivatives are either exceedingly cumbersome to derive or nonexistent for practically relevant large-scale nonlinear and coupled multi-physics problems. Similarly, holistic automated differentiation w. r. t. primary variables of multi-physics codes is usually not yet an option and requires extensive code restructuring if not considered from the outset in the software design. This absence of differentiability further exacerbates the already present computational challenges. To overcome the existing limitations, we propose a novel inference approach called <ce:italic>Bayesian multi-fidelity inverse analysis (BMFIA)</ce:italic>, which leverages simpler and computationally cheaper lower-fidelity (LF) models that are designed to provide model derivatives. BMFIA learns a simple, probabilistic dependence of the LF and HF models, which is then employed in an altered likelihood formulation to statistically correct the inaccurate LF response. From a Bayesian viewpoint, this dependence represents a multi-fidelity (MF) conditional density (discriminative model). We demonstrate how this MF conditional density can be learned robustly in the <ce:italic>small data regime</ce:italic> from only a few HF and LF simulations (50 to 300), which would not be sufficient for naive surrogate approaches. The formulation is fully differentiable and allows the flexible design of a wide range of LF models. We demonstrate that BMFIA solves Bayesian inverse problems for scenarios that used to be prohibitive, such as finely-resolved and hence high-dimensional spatial reconstruction problems in two-dimensional Euclidean domains with static posteriors, given nonlinear and transient coupled poro-elastic media physics. We show that the resulting static MF posteriors are in excellent agreement with the (usually inaccessible) HF posteriors or ground-truth data and note that extending the framework to arbitrary three-dimensional domains is a natural and important direction for future work.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"24 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A block preconditioner for thermo-poromechanics with frictional deformation of fractures","authors":"Yury Zabegaev, Inga Berre, Eirik Keilegavlen","doi":"10.1016/j.cma.2025.118440","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118440","url":null,"abstract":"The numerical modeling of fracture contact thermo-poromechanics is crucial for advancing subsurface engineering applications, including CO<ce:inf loc=\"post\">2</ce:inf> sequestration, production of geo-energy resources, energy storage and wastewater disposal operations. Accurately modeling this problem presents substantial challenges due to the complex physics involved in strongly coupled thermo-poromechanical processes and the frictional contact mechanics of fractures. To resolve process couplings in the resulting mathematical model, it is common to apply fully implicit time stepping. This necessitates the use of an iterative linear solver to run the model. The solver’s efficiency primarily depends on a robust preconditioner, which is particularly challenging to develop because it must handle the mutual couplings between linearized contact mechanics and energy, momentum, and mass balance. In this work, we introduce a preconditioner for the problem based on the nested approximations of Schur complements. To decouple the momentum balance, we utilize the fixed-stress approximation, extended to account for both the porous media and fracture subdomains. The singularity of the contact mechanics submatrix is resolved by a linear transformation. Two variations of the algorithm are proposed to address the coupled mass and energy balance submatrix: either the Constrained Pressure Residual (CPR) or the algebraic multigrid method (AMG) for systems of equations. The preconditioner is evaluated through numerical experiments of fluid injection into fractured porous media, which causes thermal contraction and subsequent sliding and opening of fractures. The experiments show that the preconditioner performs robustly for a wide range of simulation regimes governed by various fracture states, friction coefficients and Peclétnumber. The grid refinement experiments demonstrate that the preconditioner scales well in terms of GMRES iterations, in both two and three dimensions.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"40 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Neo-Yeoh hyperelastic interpolation model for stable multi-material topology optimization under geometric nonlinearity","authors":"Longlong Song, Fengwen Wang, Tong Gao, Weihong Zhang","doi":"10.1016/j.cma.2025.118467","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118467","url":null,"abstract":"Current mainstream methods for addressing numerical instability in geometrically nonlinear topology optimization typically require mesh duplication and manual manipulation of the tangent stiffness matrix. Mesh duplication significantly hinders computing efficiency, while manual manipulation restricts their applicability in commercial solvers. To address these limitations, this study proposes a Neo-Yeoh hyperelastic interpolation (NYHI) material model to address numerical instability in geometrically nonlinear topology optimization. Integrating Neo-Hookean and second-order Yeoh hyperelastic materials with a Heaviside function, the model selectively enhances shear resistance in low-density regions while maintaining accurate deformation modeling in solid elements. The topology optimization framework for multi-material problems considering geometric nonlinearity is proposed. Numerical tests on single- and multi-material structures, including cantilever and two-side clamped beams, demonstrate the model’s efficacy in suppressing distortion in low-density regions and enabling stable optimization under large deformations. Key parameters in the NYHI material model are systematically analyzed, revealing their critical roles in balancing optimization stability and structural performance. The proposed model successfully addresses numerical instability issues with a single mesh, leading to a significant simplification of the topology optimization formulation.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"122 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diff-FlowFSI: A GPU-optimized differentiable CFD platform for high-fidelity turbulence and FSI simulations","authors":"Xiantao Fan, Xin-Yang Liu, Meng Wang, Jian-Xun Wang","doi":"10.1016/j.cma.2025.118455","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118455","url":null,"abstract":"Turbulent flows and fluid-structure interactions (FSI) are ubiquitous in scientific and engineering applications, but their accurate and efficient simulation remains a major challenge due to strong nonlinearities, multiscale interactions, and high computational demands. Traditional CFD solvers, though effective, struggle with scalability and adaptability for tasks such as inverse modeling, optimization, and data assimilation. Recent advances in machine learning (ML) have inspired hybrid modeling approaches that integrate neural networks with physics-based solvers to enhance generality and capture unresolved dynamics. However, realizing this integration requires solvers that are not only physically accurate but also differentiable and GPU-efficient. In this work, we introduce Diff-FlowFSI, a GPU-accelerated, fully differentiable CFD platform designed for high-fidelity turbulence and FSI simulations. Implemented in JAX, Diff-FlowFSI features a vectorized finite volume solver combined with the immersed boundary method to handle complex geometries and fluid-structure coupling. The platform enables GPU-enabled fast forward simulations, supports automatic differentiation for gradient-based inverse problems, and integrates seamlessly with deep learning components for hybrid neural-CFD modeling. We validate Diff-FlowFSI across a series of benchmark turbulence and FSI problems, demonstrating its capability to accelerate scientific computing at the intersection of physics and machine learning.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"120 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nine circles of elastic brittle fracture: A series of challenge problems to assess fracture models","authors":"Farhad Kamarei, Bo Zeng, John E. Dolbow, Oscar Lopez-Pamies","doi":"10.1016/j.cma.2025.118449","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118449","url":null,"abstract":"Since the turn of the millennium, capitalizing on modern advances in mathematics and computation, a slew of computational models have been proposed in the literature with the objective of describing the nucleation and propagation of fracture in materials subjected to mechanical, thermal, and/or other types of loads. By and large, each new proposal focuses on a particular aspect of the problem, while ignoring others that have been well-established. This approach has resulted in a plethora of models that are, at best, descriptors of fracture only under a restricted set of conditions, while they may predict grossly incorrect and even non-physical behaviors in general. In an attempt to address this predicament, this paper introduces a vetting process in the form of nine challenge problems that any computational model of fracture must convincingly handle if it is to potentially describe fracture nucleation and propagation in general. The focus is on the most basic of settings, that of isotropic elastic brittle materials subjected to quasi-static mechanical loads. The challenge problems have been carefully selected so that: <mml:math altimg=\"si61.svg\"><mml:mi>i</mml:mi></mml:math>) they can be carried out experimentally with standard testing equipment; <mml:math altimg=\"si62.svg\"><mml:mrow><mml:mi>i</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:math>) they can be unambiguously analyzed with a sharp description of fracture; and, most critically, <mml:math altimg=\"si63.svg\"><mml:mrow><mml:mi>i</mml:mi><mml:mi>i</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:math>) in aggregate they span the entire range of well settled experimental knowledge on fracture nucleation and propagation that has been amassed for over a century. For demonstration purposes, after their introduction, each challenge problem is solved with two phase-field models of fracture, a classical variational phase-field model and the phase-field model initiated by Kumar, Francfort, and Lopez-Pamies (<ce:italic>J. Mech. Phys. Solids</ce:italic> 112 (2018), 523–551), this both for a prototypical elastic brittle hard material (soda-lime glass) and a prototypical elastic brittle soft material (a polyurethane elastomer).","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"37 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-iterative method for reliability-based topology optimization of static and dynamic problems with uncertain-but-bounded parameters","authors":"Gang Yang, Zeng Meng, Peng Hao, Changting Zhong","doi":"10.1016/j.cma.2025.118456","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118456","url":null,"abstract":"The non-probabilistic reliability-based topology optimization (NRBTO) method offers a powerful tool for achieving high-performance and high-safety layout designs under uncertain-but-bounded (UBB) parameters. However, the practical application of NRBTO is limited by unaffordable computational burden associated with repeated non-probabilistic reliability iterations. To address this issue, a new non-iterative reliability-based topology optimization method for static and dynamic problems with UBB parameters is established to avoid the non-probabilistic reliability iteration, in which a novel non-iterative method (NIM) is proposed by strict proving the monotonicity conditions with respect to UBB parameters. The complex NRBTO model is transformed into an equivalent deterministic topology optimization model, thereby reducing computational costs. Moreover, the sensitivities with respect to design variables are derived using the adjoint method. The effectiveness of proposed NIM for NRBTO is validated through two static and two dynamic examples, where the compliance, displacement, stress, frequency, and frequency-band problems are addressed.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"40 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inverse scattering without phase: Carleman convexification and phase retrieval via the Wentzel–Kramers–Brillouin approximation","authors":"Thuy T. Le, Phuong M. Nguyen, Loc H. Nguyen","doi":"10.1016/j.cma.2025.118439","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118439","url":null,"abstract":"This paper addresses the challenging and interesting inverse problem of reconstructing the spatially varying dielectric constant of a medium from phaseless backscattering measurements generated by single-point illumination. The underlying mathematical model is governed by the three-dimensional Helmholtz equation, and the available data consist solely of the magnitude of the scattered wave field. To address the nonlinearity and servere ill-posedness of this phaseless inverse scattering problem, we introduce a robust, globally convergent numerical framework combining several key regularization strategies. Our method first employs a phase retrieval step based on the Wentzel–Kramers–Brillouin (WKB) ansatz, where the lost phase information is reconstructed by solving a nonlinear optimization problem. Subsequently, we implement a Fourier-based dimension reduction technique, transforming the original problem into a more stable system of elliptic equations with Cauchy boundary conditions. To solve this resulting system reliably, we apply the Carleman convexification approach, constructing a strictly convex weighted cost functional whose global minimizer provides an accurate approximation of the true solution. Numerical simulations using synthetic data with high noise levels demonstrate the effectiveness and robustness of the proposed method, confirming its capability to accurately recover both the geometric location and contrast of hidden scatterers.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"209 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aerodynamics-driven topology optimization of compliant airfoils considering stability","authors":"Qingdi Wang, Lucas Oliveira Siqueira, Tao Xu, Guanzhe Cui, Zhi Li, Anderson Soares da Costa Azevêdo, Renato Picelli, Yi Min Xie","doi":"10.1016/j.cma.2025.118454","DOIUrl":"https://doi.org/10.1016/j.cma.2025.118454","url":null,"abstract":"Airfoil structures optimized solely for stiffness can suffer from buckling instabilities under realistic aerodynamic loads. We present the first topology optimization framework to improve the stability of aerodynamic structures. For a clear representation of structure, this work employs the topology optimization of binary structures with geometry trimming. Reynolds-averaged Navier-Stokes turbulence model is employed to accurately predict the turbulent aerodynamic loading under realistic flight conditions. Fluid–structure interaction and buckling analysis are conducted using an elastic formulation with geometrical nonlinearities to allow for large deformations. The numerical model system is solved through the finite element method and the Arbitrary Lagrangian-Eulerian method is applied. The sensitivities are calculated using semi-automatic differentiation and interpolated to the optimization mesh. Kreisselmeier-Steinhauser aggregation function is used and augmented Lagrangian multipliers are developed for buckling constraints. Numerical examples demonstrate that the proposed method can effectively improve the airfoil stability to different constraint levels across various configurations with minimal parameter tuning. Additionally, the algorithm produces designs that are conducive to manufacturing.","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"115 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}