Quasi-implicit alternating-direction splitting combined with isogeometric analysis produces wildfire temperature simulations with 10 times higher accuracy and linear computational cost.
Computer Methods in Applied Mechanics and Engineering194(39–41), 4135–4195 (2005) https://doi
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UNVERDICTED 6representative citing papers
Non-conformal immersed and union-based isogeometric methods with boundary-conformal quadrature reduce patch count and preprocessing for magnetostatics while union variants maintain accuracy on benchmarks.
A neural network with periodic activations parameterizes thin-shell mid-surfaces so that network weights can be optimized to minimize structural compliance subject to a volume limit.
Bio-PINNs with a near-to-far curriculum and deformation-uncertainty proxy recover cell-induced densified phases and tether morphologies more reliably than standard adaptive PINN baselines in single-cell and multicellular settings.
ALL-FEM fine-tunes LLMs on a corpus of verified FEniCS scripts and uses multi-agent workflows to automate finite element code generation, achieving 71.79% success on 39 benchmarks across elasticity, flow, and coupled problems.
An isogeometric topology optimization approach using topological derivatives and level-set methods in an immersed framework enables seamless geometry updates without remeshing and benefits from higher-order basis functions for solution accuracy.
citing papers explorer
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Wildfires Quasi-Implicit Alternative-Direction Simulations using Isogeometric Finite Element Method
Quasi-implicit alternating-direction splitting combined with isogeometric analysis produces wildfire temperature simulations with 10 times higher accuracy and linear computational cost.
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Immersed boundary-conformal isogeometric methods for magnetostatics
Non-conformal immersed and union-based isogeometric methods with boundary-conformal quadrature reduce patch count and preprocessing for magnetostatics while union variants maintain accuracy on benchmarks.
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Neural parametric representations for thin-shell shape optimisation
A neural network with periodic activations parameterizes thin-shell mid-surfaces so that network weights can be optimized to minimize structural compliance subject to a volume limit.
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Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks
Bio-PINNs with a near-to-far curriculum and deformation-uncertainty proxy recover cell-induced densified phases and tether morphologies more reliably than standard adaptive PINN baselines in single-cell and multicellular settings.
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ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods
ALL-FEM fine-tunes LLMs on a corpus of verified FEniCS scripts and uses multi-agent workflows to automate finite element code generation, achieving 71.79% success on 39 benchmarks across elasticity, flow, and coupled problems.
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Isogeometric Topology Optimization Based on Topological Derivatives
An isogeometric topology optimization approach using topological derivatives and level-set methods in an immersed framework enables seamless geometry updates without remeshing and benefits from higher-order basis functions for solution accuracy.