eess papers | Gist.Science

Cavitation Behavior of Water–Ethanol Blends in Representative Injector Geometry: Experimental and Numerical Investigation

This study validates a multi-component Euler–Euler cavitation model against experimental data for water–ethanol blends in an injector geometry, revealing that while mass flow predictions are similar for single- and multi-component approaches, the latter is essential for accurately capturing the ethanol-dominated vapor composition and specific water/ethanol enrichment patterns within the flow.

Dionysios Stefanitsis, Gavin Dober, Cyrille Lesieur, Stephan Leyer2026-09-09

⚡ electrical engineering

Effect of Alkali Activators on Mechanical and Durability Properties of Fly Ash based Geopolymer Concrete

This study demonstrates that fly ash-based geopolymer concrete, particularly when optimized with specific alkali activator ratios and oven curing, achieves mechanical strength comparable to ordinary Portland cement while offering superior durability and a significantly lower carbon footprint.

Abhishek V. Jadhav, V. M. Bogar2026-09-09

⚡ electrical engineering

A Control-Oriented Quasi-Steady Aerodynamic Model for a Low- Frequency Rigid–Flexible Multi-Segment Ornithopter

This paper presents a computationally efficient, control-oriented quasi-steady aerodynamic model for low-frequency rigid–flexible multi-segment ornithopters that accurately predicts dominant lift and thrust trends for flight dynamics and controller design, despite limitations in capturing complex unsteady wake interactions.

Mingyang HUANG2026-09-09

⚡ electrical engineering

Critical Gypsum Content in Leaching of Gypseous Soil

This study introduces the concept of Critical Gypsum Content (CGC) as a residual threshold in gypseous soils beyond which dissolution ceases, demonstrating that reaching this limit significantly reduces cohesion, increases compressibility and permeability, and accelerates soil deterioration through a positive feedback mechanism.

Qutayba Al-Saffar, Mohammed Jaro, Muwafaq Awad, Zeena AlKazzaz, Abdulnasser Ali2026-09-09

⚡ electrical engineering

Fabrication and Optimization of M2 High-Speed Steel via PBF–LB/M: A Machine Learning-Driven Approach

This study demonstrates that a machine learning-driven strategy, utilizing Random Forest and Gradient Boosting algorithms to optimize laser processing parameters without baseplate preheating, successfully enables the crack-free fabrication of M2 high-speed steel via PBF–LB/M with near-full density and high hardness.

Sumit Sahu, Anish Upadhyaya, Felix Oppermann, Ulrich Krupp2026-09-09

⚡ electrical engineering

Nanostructured Battery Technology for Unmanned Aerial Vehicles (UAVs): Development, Performance and Prospects

This study demonstrates that integrating nanostructured electrode materials with auxiliary energy storage components and solid-state electrolytes significantly enhances the efficiency, safety, and flight endurance of unmanned aerial vehicles by an estimated 15–20% through improved voltage regulation, specific capacity, and thermal stability.

Đức Hoàn Vũ, Oanh Bùi2026-09-09✓ Author reviewed ⓘ

⚡ electrical engineering

High-Efficiency MEMS Synthetic Jet Cooler for Mobile Thermal Management

This study presents a compact, high-efficiency MEMS synthetic jet cooler utilizing a silicon-based piezoelectric actuator operating at ultrasonic frequencies to deliver significant thermal management performance for mobile devices while meeting strict size and power constraints.

Junya Wang, Kaiwei Yang, Hexiang Guo, Guodong Wang, Shaotang Wei, Zheng You2026-09-09

⚡ electrical engineering

Mechanical response and precursor characteristics of catastrophic failure in deep coal mass with through-openings : Insights from experiments

This study utilizes constrained uniaxial compression tests combined with acoustic emission and digital image correlation to demonstrate that opening geometry significantly influences the precursory characteristics of catastrophic failure in deep coal, leading to a proposed dual-timescale prediction strategy that integrates variance-based early risk identification with power-law acceleration for imminent failure confirmation.

Ji Ma, Zhouyang Jiang, Housheng Jia, Ruifu Yuan, Zhiqiang Hou, Lifang Feng, Zhengxuan Yang, Xiao Li2026-09-09

⚡ electrical engineering

Bio-Digital Convergence and Sustainable Artificial Intelligence: Evaluating the Tools of the Jach'a Qh’anax Model in the Andean-Amazonian and Mesoamerican Bioeconomy

This study demonstrates that integrating the Andean-Amazonian Jach'a Qh'anax model with deep learning and edge-computing tools enables smallholder communities in the Global South to significantly reduce chemical dependencies, stabilize household revenues, and achieve technological sovereignty by harmonizing ancestral biocultural knowledge with predictive bio-digital systems.

Jorge León Quiroga-Canaviri, Carlos Alberto Zuniga-Gonzalez, Henry Antonio Osorto-Ruiz2026-09-09

⚡ electrical engineering

Predictive Quality Control And Yield Improvement In Roll-To-Roll Manufacturing Using Machine Learning

This paper synthesizes existing literature to propose a conceptual framework that leverages machine learning, inline sensing, and automated feedback control to transition roll-to-roll manufacturing from reactive inspection to predictive quality control, thereby improving yield and process stability.

Deborah Gyang2026-09-09

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