⚡ electrical engineering

A Stabilized Mixed Hybrid Finite Element Framework for Large-Deformation Poromechanics with Torsion: Application to Transmural Perfusion and Vascular Hemodynamics

This paper presents a stabilized mixed hybrid finite element framework that effectively resolves volumetric locking and pressure oscillations in large-deformation poromechanics under torsion, demonstrating through analytical and numerical validation that torsional twist significantly reduces endocardial fiber stress and improves perfusion modeling accuracy in hypertensive hearts compared to standard formulations.

Kamyar Malakpoor2026-10-22
⚡ electrical engineering

From spatial attribution to mesh decisions in nonlinear moisture-threshold calculations

This study establishes a cost-accounted, interpretable procedure for linking local flux sensitivity to optimal mesh selection in nonlinear moisture-threshold calculations by validating coupled tangent and adjoint methods, comparing spatial grading strategies against goal-oriented approaches, and quantifying the impact of constitutive laws and latent cooling on numerical drying endpoints.

Songde You, Yihong Chen, Jin Chen2026-10-22
⚡ electrical engineering

Sulphate and chloride durability of metakaolin-blended palm kernel shell concrete masonry units: separating the contributions of the pozzolan and the agro-waste aggregate

This study demonstrates that while metakaolin significantly enhances the sulphate and chloride durability of palm kernel shell concrete masonry units by refining pore structure, the inclusion of the lightweight agro-waste aggregate partially offsets these gains, resulting in a net durability improvement that correlates weakly with water-accessible porosity and is characterized by matrix softening rather than mass loss.

Nova John, Vincent Sam Jebadurai S, Hemalatha G2026-10-22
⚡ electrical engineering

C³M-OMMT Twin: A Causal Process–Structure–Property Digital Twin for Morphology-Aware Mechanical Optimization of OMMT-Modified PLA in Fused-Filament Fabrications

This paper introduces C³M-OMMT Twin, a comprehensive causal process–structure–property digital twin pipeline that integrates multi-modal characterization and physics-informed learning to optimize OMMT-reinforced PLA printing parameters, thereby significantly enhancing mechanical performance and reducing void formation while minimizing reliance on trial-and-error experimentation.

Mangesh Deshmukh, Prashant Thorat, Nishant Bhore2026-10-22
⚡ electrical engineering

SAC-enhanced iterative learning control with two-layer barrier mapping for nonlinear MIMO systems with asymmetric input constraints

This paper proposes a Soft Actor-Critic augmented Proportional-Derivative Iterative Learning Control scheme with a two-layer barrier mapping strategy to achieve uniform ultimate boundedness and improved tracking performance for nonlinear MIMO systems under asymmetric input constraints and nonrepetitive disturbances.

Hongfeng Tao, Fei Shao, Zhihe Zhuang, Wojciech Paszke2026-10-22
⚡ electrical engineering

A Fault Current Limiter Coordinated with a Hybrid DC Circuit Breaker for HVDC Applications

This paper proposes a coordinated Fault Current Limiter and Hybrid DC Circuit Breaker system for ±500 kV HVDC applications that significantly reduces transient overvoltage stress on IGBTs by 86.96% and enhances fault protection through a simple, low-cost design that eliminates reliance on capacitor charging and discharging.

Ossama E Gouda, Mohamed Salah Abu Al-Ala, Mohammed Shams2026-10-22
⚡ electrical engineering

Overhead Transmission Line Fragility, Climate-Induced Risks and Geospatial Artificial Intelligence: A Systematic Bibliometric Review

This systematic bibliometric review reveals that while research on overhead transmission line fragility has increasingly incorporated artificial intelligence and machine learning, it remains fragmented with weak integration of climate and geospatial perspectives, significant regional biases, and a lack of comprehensive frameworks to address cumulative multi-hazard climate impacts.

Tshisikhawe Mphaphuli, Abel Ramoelo, Philemon Tsele2026-10-22
⚡ electrical engineering

A data-driven framework to inform extreme flood warning: Evaluating dual-tier weighting in contrasting catchments

This study demonstrates that a data-driven framework employing dual-tier residual weighting significantly improves extreme flood detection in low-yield, attenuated catchments without compromising continuous streamflow simulation, provided that the weighting strategy is tailored to the catchment's specific hydrological characteristics and paired with an appropriate objective function.

Ali akbar Eatesam, Khosrow Hoseini, Hojat Karami2026-10-22