⚡ Category

eess

1710 papers

⚡ electrical engineering

Multi-Horizon, Multi-Depth Forecasting of Pavement Temperature in a Continental Climate: Machine Learning Methods Benchmarked Against a Persistence Baseline

This study demonstrates that while a naive persistence baseline outperforms six machine learning algorithms for short-term pavement temperature forecasting across all depths in a continental climate, machine learning methods offer limited but real value at longer horizons and greater depths where thermal inertia dampens high-frequency variability.

Assel Nugmanova, Bagdat Teltayev, Ulan Alipov2026-07-08
⚡ electrical engineering

Physics-Informed Machine Learning for Radiation-Free Water Liquid Ratio Estimation Using Coriolis Flow Measurements

This study introduces a radiation-free, physics-informed machine learning framework that accurately estimates the Water Liquid Ratio in three-phase oil–gas–water flows using only Coriolis mass flow measurements and a novel Harmonic Mixture Density Mean Factor (HMDMF), achieving high predictive performance (R² = 0.8943) and offering a cost-effective alternative to traditional gamma-based systems.

Hamza Zidoum, Majid Al Yaroubi2026-07-08
⚡ electrical engineering

Thermodynamic Stratification of Dual-Working-Fluid ORC-Driven Vapor Compression Refrigeration Systems Based on Critical Property Compatibility

This study introduces a thermodynamic stratification framework based on critical temperature differences to classify dual-working-fluid ORC-VCC systems, revealing that lower critical temperature differences yield higher efficiency at the cost of increased mass flow rates while identifying condenser temperature as the dominant factor influencing overall system performance.

Aryan Nafis, Afia Mahmuda Momtaz, Tajwar Razib, Anup Saha2026-07-08
⚡ electrical engineering

PINN-Flow: A Unified Physics-Informed Optical Flow Framework for Joint Fluid–Wall Motion Estimation in Abdominal Aortic Aneurysms

PINN-Flow is a unified physics-informed deep learning framework that jointly estimates blood flow velocity and aortic wall displacement in abdominal aortic aneurysms by integrating Navier-Stokes and linear-elastic constraints, thereby significantly outperforming data-driven baselines in noise robustness and accuracy for rupture risk stratification.

hanae hanae2026-07-08
⚡ electrical engineering

Water-Spray Cooling of Turbine Wakes: a Pathway to Enhance Wind Farm Power Generation

This study demonstrates that spraying fine water droplets into turbine wakes to induce evaporation-driven negative buoyancy accelerates wake recovery and significantly increases net power generation in wind farms, as validated by large-eddy simulations and wind tunnel experiments.

Xuefeng Yang, Mou Lin, Shengli Chen, Kun Lin, Xinwei Shen, Zhen-Zhong Hu, Daoyi Chen, Yunfei Du, Jiantao Shi, Chongbo Su (…)2026-07-08
⚡ electrical engineering

From European Modular Housing to Ichu-Insulated Andean Dwellings: A Comparative Technology-Transfer Framework for Frost-Resilient Thermal Conditioning in Southern Peru

This paper proposes a low-cost, locally-sourced thermal retrofit framework for frost-prone Andean dwellings in southern Peru by systematically comparing international cold-climate housing strategies to derive a wall and roof specification using indigenous materials like ichu grass and camelid wool that theoretically reduces thermal transmittance by 55–65%.

PAUL RICARDO PRUDENCIO GALVEZ2026-07-08
⚡ electrical engineering

Introducing Friction Stir Spot Additive Manufacturing process for producing aluminum parts

This study introduces a cost-effective Friction Stir Spot Additive Manufacturing process for aluminum parts, demonstrating through experimental and finite element analysis that increasing welding points per layer can achieve approximately 80% of the flexural strength of an ideal part while successfully fabricating geometrically complex components.

Abolfazl Masoumi, Pouriya Barghmadi, Amirhossein Mohammadzad2026-07-08
⚡ electrical engineering

Forward Kinematics Accuracy Enhancement of a Force-Torque Decoupled Spherical Parallel Manipulator near Singular Configurations within a Tripodal Robot

This paper presents an enhanced mechanical design for a force-torque decoupled spherical parallel manipulator that integrates an internal serial structure with a fourth joint sensor to significantly improve forward kinematics accuracy near singular configurations, validated through analytical derivation, simulation, and real-time prototype testing within a tripodal robot.

David Feller2026-07-08