Engineering Proceedings

9 pages, 3496 KB

Open AccessProceeding Paper

A Multi-Disciplinary Approach to Concurrent Aero-Structural and On-Board System Design for a Distributed Propulsion HER Configuration

by Simone Mancini, Tim Klaproth, Reinhold Maierl, Ögmundur Petersson, Jean-Christophe Giret and Sylvain Béchet

Eng. Proc. 2026, 133(1), 198; https://doi.org/10.3390/engproc2026133198 (registering DOI) - 12 Jun 2026

Abstract

This study investigates the integration of hybrid-electric distributed propulsion (DEP) systems in aviation to improve environmental sustainability. It aims to develop practical and integrated aircraft solutions by addressing the architectural complexity of hybrid-electric systems through a concurrent design approach. This approach is crucial [...] Read more.

This study investigates the integration of hybrid-electric distributed propulsion (DEP) systems in aviation to improve environmental sustainability. It aims to develop practical and integrated aircraft solutions by addressing the architectural complexity of hybrid-electric systems through a concurrent design approach. This approach is crucial due to the strong interdependence between aircraft performance and the size of the hybridized propulsion system. The research utilizes a multi-disciplinary Design and Optimisation (MDO) framework, built around GEMSEO, to support aero-structural and system design for a hybrid-electric regional aircraft configuration. The framework combines aerodynamics, structural, and on-board system design using a multi-fidelity approach, facilitating the integration of different design disciplines. Key findings highlight the sensitivity of overall aircraft design to on-board system sizing. We conclude that a concurrent MDO design approach effectively captures the sensitivity of the design to on-board systems sizing. Full article

(This article belongs to the Proceedings of The 15th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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7 pages, 195 KB

Open AccessProceeding Paper

A Review of Emerging Dielectric Fluids for Sustainable and Resilient Power Transformers

by Vusumuzi Sibeko

Eng. Proc. 2026, 140(1), 64; https://doi.org/10.3390/engproc2026140064 (registering DOI) - 12 Jun 2026

Abstract

This paper reviews emerging dielectric fluids for power transformers, including natural and synthetic esters, silicone oils, gas-to-liquid oils, and nanofluids, driven by environmental regulations, fire safety concerns, and the need for extended asset life. The review synthesizes technical data from standards and field [...] Read more.

This paper reviews emerging dielectric fluids for power transformers, including natural and synthetic esters, silicone oils, gas-to-liquid oils, and nanofluids, driven by environmental regulations, fire safety concerns, and the need for extended asset life. The review synthesizes technical data from standards and field experience, including a case study of an Eskom transformer energized in 2016 with natural ester fluid. Analysis confirms these fluids offer significant benefits in fire safety, biodegradability, and dielectric performance, with the case study demonstrating natural esters’ effectiveness in preserving solid insulation. However, trade-offs involving cost, material compatibility, and operational protocols require careful management. Full article

8 pages, 1018 KB

Open AccessProceeding Paper

Frequency Enhancement for Distributed Wind Generators Using Energy Storage Systems

by Sydeny Madenga, Thapelo Mosetlhe and Adedayo Ademola Yusuff

Eng. Proc. 2026, 140(1), 63; https://doi.org/10.3390/engproc2026140063 (registering DOI) - 12 Jun 2026

Abstract

Power system operators globally face an ongoing challenge of maintaining a balance between electricity supply and load demand. This is a task which has been made increasingly complex by variability inherent in both generation sources and consumer loads. The balancing act is resource [...] Read more.

Power system operators globally face an ongoing challenge of maintaining a balance between electricity supply and load demand. This is a task which has been made increasingly complex by variability inherent in both generation sources and consumer loads. The balancing act is resource intensive, costly, and is critical for preventing frequency deviations that could destabilize the entire network, which can lead to blackouts and equipment damage. The intermittent nature caused by unpredictable wind speeds adds more challenges by introducing rapid fluctuations that system operators may struggle to mitigate. Energy storage systems (ESSs) have shown potential in addressing these challenges by offering flexible buffering capabilities to smooth out imbalances and enhance frequency stability. In this research, the impact of fluctuating wind speeds on power system frequency stability was analyzed. Subsequently, a hybrid energy storage system that integrates batteries for sustained energy discharge and super capacitors for rapid high-power responses was added. This enabled the system to handle mismatches effectively. The results show a 66% reduction in frequency deviations during wind fluctuations compared to baseline scenarios without storage. This improvement facilitates improved integration of renewable energy sources by allowing higher penetration levels without compromising stability. Full article

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10 pages, 1161 KB

Open AccessProceeding Paper

Evaluation of Abaca Fiber-Reinforced Polymer Composites for Fiber-Optic Cable Strengthening: Advancing Experiential Learning for Industrial Technology Learners

by Vicardo J. Aroy, John O. Estillore, Romnick J. Labastida, Marlon A. Filipino and Junrey V. Quitorio

Eng. Proc. 2026, 143(1), 10; https://doi.org/10.3390/engproc2026143010 (registering DOI) - 12 Jun 2026

Abstract

The study investigated the tensile strength and elongation properties of abaca fiber-reinforced polymer (AFRP) composites after varying durations of seawater soaking, with a focus on their potential for reinforcing fiber-optic cables. It aims to bridge industrial technology education, experiential learning, and green technology [...] Read more.

The study investigated the tensile strength and elongation properties of abaca fiber-reinforced polymer (AFRP) composites after varying durations of seawater soaking, with a focus on their potential for reinforcing fiber-optic cables. It aims to bridge industrial technology education, experiential learning, and green technology by evaluating abaca fiber as a sustainable alternative to synthetic aramid yarn. Conducted at Caraga State University, Cabadbaran Campus (CSUCC), the research utilized a quasi-experimental product development design involving industrial technology students and instructors. Tensile strength testing and comparative analysis were performed on abaca fiber samples (A, B, and C) subjected to different seawater soaking durations. Results show that soaking time significantly affects the fiber strength, with Sample A achieving the highest tensile strength (5631.5 MPa) and Sample C the lowest (1679.8 MPa). Findings indicate that prolonged exposure to seawater weakens abaca fiber, emphasizing the need for controlled treatment to optimize its industrial applications. This study emphasizes the importance of hands-on learning in industrial technology education, promoting critical thinking and technical skills while underscoring sustainability. The research advocates for eco-friendly materials in industrial applications and highlights the potential of abaca fiber composites. Future studies should investigate pre-treatment methods to enhance fiber durability, assess the long-term environmental performance, and conduct large-scale pilot testing to evaluate commercial viability. By integrating sustainable innovations into industrial technology education, this study contributes to advancing natural fiber composites for manufacturing and telecommunications infrastructure. Full article

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11 pages, 385 KB

Open AccessProceeding Paper

Electronically Controlled Root Crop Processor: A Laboratory Simulator for Outcome-Based TVET Learners

by Cerelo T. Tabat, Jr., Jesson S. Lunio, Chris John L. Papa and Jemery D. Noces

Eng. Proc. 2026, 143(1), 9; https://doi.org/10.3390/engproc2026143009 (registering DOI) - 12 Jun 2026

Abstract

This study introduces an Electronically Controlled Root Crop Processor, a compact, Arduino-powered simulator designed to transform hands-on learning for TVET students. Built with locally available materials, it seamlessly integrates grating and juice extraction while prioritizing safety, ergonomics, and user-friendly operation. Experts rated the [...] Read more.

This study introduces an Electronically Controlled Root Crop Processor, a compact, Arduino-powered simulator designed to transform hands-on learning for TVET students. Built with locally available materials, it seamlessly integrates grating and juice extraction while prioritizing safety, ergonomics, and user-friendly operation. Experts rated the prototype highly for functionality and usability, with ergonomics scoring 3.96, while aesthetics and modularity scored 3.83, highlighting areas for refinement. By bridging classroom theory and practical skills, the processor offers an interactive, real-world food processing experience, empowering learners to develop technical competencies efficiently in laboratory settings. Full article

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8 pages, 800 KB

Open AccessProceeding Paper

Modeling and Simulation of a Distributed-Electric Propulsion System with PROOSIS

by Maria Aranda Rosales and Luis Sánchez de León

Eng. Proc. 2026, 133(1), 197; https://doi.org/10.3390/engproc2026133197 - 11 Jun 2026

Abstract

This paper presents a concise modeling and simulation study of a turboelectric distributed propulsion (TeDP) system for a hybrid wing body (HWB) aircraft. A whole-system 0D model has been implemented in PROOSIS that includes the thermodynamic model of the turboshaft and fan array, [...] Read more.

This paper presents a concise modeling and simulation study of a turboelectric distributed propulsion (TeDP) system for a hybrid wing body (HWB) aircraft. A whole-system 0D model has been implemented in PROOSIS that includes the thermodynamic model of the turboshaft and fan array, as well as an electrical subsystem model addressing generators, motors, and cryogenic cooling for high-temperature superconducting (HTS) machines. Boundary layer ingestion (BLI) was explicitly modeled in the inlet–fan interaction. Parametric studies explored control strategies that minimized fuel consumption across the flight envelope. The design and off-design analyses demonstrated that coupling BLI with distributed fans can deliver significant aerodynamic benefits, while the integrated mission simulation highlighted the system-level implications of electrical conversion and control and quantified potential fuel savings. Full article

(This article belongs to the Proceedings of The 15th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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9 pages, 2078 KB

Open AccessProceeding Paper

Traceable Intercorporation Data Exchange and Processing Using a Graph-Based Infrastructure

by Paula Ruß, Gerald Schegk, Deoclécio Valente, Jonas Jepsen, Malte Christian Struck, Oliver Bertram, Frank Dressel and Arthur Zamfir

Eng. Proc. 2026, 133(1), 196; https://doi.org/10.3390/engproc2026133196 - 11 Jun 2026

Abstract

Designing an aircraft requires multidisciplinary analysis and data processing abilities, which are often spread over various partners. Effective collaboration across organisational boundaries is difficult, but essential. As the aerospace industry becomes increasingly digitalised, ever larger volumes of data and models must be exchanged. [...] Read more.

Designing an aircraft requires multidisciplinary analysis and data processing abilities, which are often spread over various partners. Effective collaboration across organisational boundaries is difficult, but essential. As the aerospace industry becomes increasingly digitalised, ever larger volumes of data and models must be exchanged. Heterogeneous tools, data formats, and infrastructures make it difficult to exchange data and to trace it. We propose using semantic graphs for data exchange to ensure interoperability, while semantic links between data models facilitate multidisciplinary and cross-organisational collaboration. Furthermore, our approach captures comprehensive metadata that describes the creation and modification of each dataset, thereby establishing a fully traceable data provenance chain. We demonstrate its functionality via a design process for an electromechanical actuator (EMA) given requirements from a different stakeholder (simulated). Having the requirements and the EMA models translated in Resource Description Framework (RDF) graphs, we are able to create links between them. This then enables the EMA model to be automatically re-evaluated when requirements change, ensuring that it complies with them. For the data exchange, we use the DLR SemanticHub, which utilises a graph database. By providing traceability of the data results provided in different data formats and the data origins, we enable transparency and accountability across organisational boundaries, which is important for trusted collaboration and compliance in intercorporational data exchange. Full article

(This article belongs to the Proceedings of The 15th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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11 pages, 5539 KB

Open AccessProceeding Paper

Electrical Properties of Old Gold Mine Tailings and Their Suitability as Conductive Backfill for Earthing Applications

by Sithole Lungelo Phinda and Chandima Gomes

Eng. Proc. 2026, 140(1), 62; https://doi.org/10.3390/engproc2026140062 - 11 Jun 2026

Abstract

This study investigates the electrical properties of gold mine tailings from the Soweto mining region to assess their potential as a low-cost and sustainable backfill material for grounding systems. Samples were collected from historical mine dumps, oven-dried at 70 °C for 24 h [...] Read more.

This study investigates the electrical properties of gold mine tailings from the Soweto mining region to assess their potential as a low-cost and sustainable backfill material for grounding systems. Samples were collected from historical mine dumps, oven-dried at 70 °C for 24 h to determine dry density and baseline moisture content, and reconstituted to controlled moisture levels of 5–25% by mass. Bulk electrical resistivity was measured using the Wenner four-electrode method in accordance with ASTM G57-06. The results reveal a strong inverse correlation between moisture content and resistivity. At low moisture content (≈5%), resistivity exceeded measurable limits, indicating poor ionic conduction, whereas increasing moisture content led to a substantial reduction in resistivity, reaching an average value of approximately 10 Ω at 25% moisture due to improved pore water continuity and ionic mobility. These findings demonstrate that moisture-conditioned gold mine tailings can achieve electrical performance comparable to that of conventional grounding enhancement materials while offering notable economic and environmental benefits. Owing to their local availability and waste re-utilisation potential, the tailings present a technically feasible and environmentally responsible solution for improving earthing performance in high-resistivity soils. Further work should examine long-term field performance, corrosion effects, and leaching behaviour. Full article

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13 pages, 3323 KB

Open AccessProceeding Paper

Medium Voltage Underground Cables ANN Real-Time Detection and Classification Technique

by Sifiso Zikhali, Nomihla Ndlela, Ntombenhle Mazibuko and Kabulo Loji

Eng. Proc. 2026, 140(1), 61; https://doi.org/10.3390/engproc2026140061 - 11 Jun 2026

Abstract

This paper introduces a cutting-edge, real-time fault detection and classification method powered by artificial neural networks (ANNs), designed to significantly boost the reliability and sustainability of medium voltage (MV) underground cable distribution systems. The research analyzes the electrical and physical properties of MV [...] Read more.

This paper introduces a cutting-edge, real-time fault detection and classification method powered by artificial neural networks (ANNs), designed to significantly boost the reliability and sustainability of medium voltage (MV) underground cable distribution systems. The research analyzes the electrical and physical properties of MV underground cables and common fault types, including line-to-line, line-to-ground, and double line-to-ground faults. A simulation model is developed using MATLAB/Simulink R2025b to generate fault scenarios under various operating conditions. Raw data in the form of Voltage and current signals are generated and processed to extract significant features, which are then fed into the ANN model. The ANN is trained using a supervised learning approach, using a dataset of labeled fault instances. Key parameters like hidden layers, activation functions, and learning rates are optimized to improve the model’s performance. The results show that the proposed ANN-based fault detection technique achieves over 95% accuracy in detecting and classifying faults in real-time, with minimal computational delay. Comparative analysis with conventional fault classification techniques demonstrates the superiority of the ANN model in handling noisy and non-linear data. Full article

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9 pages, 2207 KB

Open AccessProceeding Paper

Intelligent Prediction of Blast Furnace Permeability by Integrating Extreme Gradient Boosting and Light Gradient Boosting Machine

by Bo Xu, Haiqi Nie, Hongda Li and Xinmin Shi

Eng. Proc. 2026, 141(1), 15; https://doi.org/10.3390/engproc2026141015 - 11 Jun 2026

Abstract

We developed an ensemble model based on the fusion of Extreme Gradient Boosting and Light Gradient Boosting Machine. 20 key parameters, including hourly charging rate, blast volume, and blast pressure, are selected as input features to construct and train the ensemble model for [...] Read more.

We developed an ensemble model based on the fusion of Extreme Gradient Boosting and Light Gradient Boosting Machine. 20 key parameters, including hourly charging rate, blast volume, and blast pressure, are selected as input features to construct and train the ensemble model for predicting the blast furnace permeability index. The results show that the model achieves a root mean squared error of 0.0868, a mean absolute error of 0.0708, and a coefficient of determination of 0.9602, confirming its excellent predictive accuracy. Full article

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8 pages, 760 KB

Open AccessProceeding Paper

Field-Programmable Gate Array Implementation of Fast Detection Method for Power Grid Faults

by Zihong Lin, Kengyu Lien and Qiaofei Xie

Eng. Proc. 2026, 141(1), 14; https://doi.org/10.3390/engproc2026141014 - 11 Jun 2026

Abstract

We implemented a power grid fault detection scheme based on adaptive frequency tracking and an iterative discrete Fourier transform. We designed and verified the scheme on a Field-Programmable Gate Array (FPGA) development board, leveraging the inherent advantages of hardware parallel processing to overcome [...] Read more.

We implemented a power grid fault detection scheme based on adaptive frequency tracking and an iterative discrete Fourier transform. We designed and verified the scheme on a Field-Programmable Gate Array (FPGA) development board, leveraging the inherent advantages of hardware parallel processing to overcome the speed and real-time limitations of traditional general-purpose processor-based solutions. The simulation results demonstrate that the FPGA implementation validates the effectiveness of the algorithm, achieving excellent performance in terms of resource utilization and power consumption. These findings provide a solid technical foundation for the development of specialized and miniaturized power grid protection devices. Full article

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14 pages, 2063 KB

Open AccessProceeding Paper

Development and Simulation of a Portable Solar Food Dehydrator: A Sustainable Learning Tool for Food Technology Education in Mindanao, Philippines

by John O. Estillore, Raffy V. Cosicol, Renissa S. Cosicol, Jeramel Rodaje, Rea Dumas and Gleciel Biñan Cabriana

Eng. Proc. 2026, 143(1), 8; https://doi.org/10.3390/engproc2026143008 - 11 Jun 2026

Abstract

Sustainability in higher education plays a crucial role in shaping future professionals with an eco-conscious mindset. This study focuses on developing and simulating a portable solar food dehydrator as a practical application of sustainability principles in technology education. By integrating sustainability into the [...] Read more.

Sustainability in higher education plays a crucial role in shaping future professionals with an eco-conscious mindset. This study focuses on developing and simulating a portable solar food dehydrator as a practical application of sustainability principles in technology education. By integrating sustainability into the curriculum, this research enhances students’ technical skills while promoting the use of renewable energy and effective food preservation methods. Furthermore, the project aligns with green campus initiatives by encouraging energy-efficient practices and reducing food waste. This study emphasizes the significance of education for sustainable development by offering learners hands-on experience in designing eco-friendly solutions, promoting innovation, and equipping them to contribute to a more sustainable future. A food dehydrator is a device that removes moisture from food to aid in its preservation, utilizing a heat source and airflow to reduce its water content. The researchers used two methods to dehydrate food: direct sunlight (sun drying) and indirect sunlight (solar drying). The study used a developmental research design. Simulations revealed that, with solar-powered electricity, the longer the drying time, the greater the reduction in the moisture content. This was evident in the eighth experiment, which was conducted on fruits and vegetables. While drying with direct sunlight, the same trends, albeit to a lesser extent, were observed in the reduction in the moisture content of the fruits and vegetables. These insights can inform future design improvements, making the products more visually appealing and distinctive, thereby enhancing their attractiveness and novelty. Full article

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9 pages, 813 KB

Open AccessProceeding Paper

Needs and Challenges of Industrial Technology Education Learners in a Mindanao Higher Education Institution: Implications for Curriculum Enhancement

by John O. Estillore, Ramil B. Arante and Jona J. Biongcog

Eng. Proc. 2026, 143(1), 7; https://doi.org/10.3390/engproc2026143007 - 11 Jun 2026

Abstract

Technical higher education in the Philippines is a government priority, as it equips learners with the technical knowledge and practical skills necessary to develop industry and technology-ready human capital. In parts of Mindanao, the Philippines, where socio-economic and technological challenges are significant, Industrial [...] Read more.

Technical higher education in the Philippines is a government priority, as it equips learners with the technical knowledge and practical skills necessary to develop industry and technology-ready human capital. In parts of Mindanao, the Philippines, where socio-economic and technological challenges are significant, Industrial Technology Education (ITE) learners must be equipped with relevant, comprehensive knowledge of industry trends. A sequential explanatory mixed-methods design was employed in this research, combining quantitative surveys with qualitative interviews to provide a comprehensive analysis. Five hundred twenty-six learners participated in the survey, and six were selected for in-depth interviews. The findings highlight the significant impact of familial and peer support on fostering confidence, encouraging academic perseverance, and improving mental health. However, financial hardships and inadequate emotional support remain significant obstacles. The study emphasizes the importance of cultivating an inclusive campus atmosphere via awareness efforts, accessible services, and mentorship programs to guarantee fair educational opportunities. For this reason, the implementation of personalized education plans, flexible learning, digital access, academic and educational support, and an institutional support system is highly encouraged to address learners’ essential needs. The research findings also suggest integrating mentorship programs, adopting inclusive learning practices, developing an adaptable curriculum, and providing mental health support services for learners, particularly those with disabilities. By aligning the curriculum with industry specifications and standards and providing well-planned support frameworks, higher education institutions in Mindanao can produce graduates who are professionally qualified, highly skilled, well-mannered, and career-prepared, fully equipped to meet the demands of the dynamic workforce. Full article

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11 pages, 2988 KB

Open AccessProceeding Paper

Real-Time Detection of Underground Intrusions via Vibration Sensors and Dual-Band GSM Cellular Notifications Using SIM900A Module for Electrical Laboratory Simulation

by John Estillore, Jovanie Banate, Dan Rosel Galla, Dexter Rollorata and Joseph S. Yatan

Eng. Proc. 2026, 143(1), 6; https://doi.org/10.3390/engproc2026143006 - 11 Jun 2026

Abstract

Microfinance institutions (MFIs) are vital in promoting financial inclusion for underserved populations. However, these institutions face growing security threats, including sophisticated burglary tactics like underground tunneling. In the Philippines, notable incidents, such as the “Termite Gang” heist in Marikina City and a mall [...] Read more.

Microfinance institutions (MFIs) are vital in promoting financial inclusion for underserved populations. However, these institutions face growing security threats, including sophisticated burglary tactics like underground tunneling. In the Philippines, notable incidents, such as the “Termite Gang” heist in Marikina City and a mall robbery in Ozamiz, highlight the limitations of conventional security systems in addressing subterranean intrusions. This study addresses the gap in existing security technologies by developing a real-time detection system that integrates a vibration sensor, a Global System for Mobile Communications (GSM) module for sending real-time SMS alerts, an audible alarm, and a solar-powered backup system for continuous operation. The system was simulated in the electrical technology laboratory to enhance classroom learning. The system’s core is an Arduino Uno microcontroller that processes inputs from the SW-420 vibration sensor, activating alarms and triggering SMS notifications via the SIM900A module when it detects unusual vibrations. Simulations A, B, and C were conducted to evaluate the system’s response time, with results showing a progressive reduction in detection time from five seconds to one second, indicating improved calibration and system efficiency. These findings also support the existing literature on user interaction with vibration alerts, demonstrating high accuracy in interpreting haptic notifications and the cognitive trade-offs involved. The proposed solution offers a proactive, energy-resilient, and cost-effective security system specifically designed to address underground burglary attempts. It applies to MFIs, pawnshops, and other high-risk financial environments. Future research should explore the application of machine learning for adaptive threat detection, expand the system’s scalability, and integrate mobile applications to enable user customization and enhance alert management. Full article

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12 pages, 2233 KB

Open AccessProceeding Paper

Structural Assessment of a Compact Offset Strip Fin Heat Exchanger for Hydrogen Fuel Cell Electric Aircraft

by Sahil Bhapkar, Siddharth Patkar, Markus Kober and Stefan Kazula

Eng. Proc. 2026, 133(1), 195; https://doi.org/10.3390/engproc2026133195 - 10 Jun 2026

Abstract

Hydrogen fuel cells offer strong potential for decarbonizing aviation, yet their megawatt-scale integration is limited by thermal management system (TMS) challenges. In low-temperature Proton Exchange Membrane Fuel Cell (PEMFC) systems, the heat exchanger (HEX) is the key TMS component influencing thermal efficiency, mass, [...] Read more.

Hydrogen fuel cells offer strong potential for decarbonizing aviation, yet their megawatt-scale integration is limited by thermal management system (TMS) challenges. In low-temperature Proton Exchange Membrane Fuel Cell (PEMFC) systems, the heat exchanger (HEX) is the key TMS component influencing thermal efficiency, mass, and reliability. While prior work has focused on thermo-hydraulic optimization, structural behavior under flight conditions remains insufficiently addressed. This study introduces a coupled CFD–FEA methodology for a nacelle-integrated, megawatt-class plate–fin HEX. The model captures the effects of non-uniform thermal loads, constrained thermal expansion, and dynamic excitation. Local flow-induced vibrations are assessed through pre-stressed modal analysis, and global dynamic behavior is predicted using a homogenized approach. Results show that thermally induced stresses dominate over pressure loads, and the introduction of coolant-fin geometries with suitable expansion tolerances mitigates stress and resonance risks. The approach provides design guidance for structurally robust, vibration-tolerant, and aero-thermally efficient HEXs for next-generation PEMFC-powered aircraft. Full article

(This article belongs to the Proceedings of The 15th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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4 pages, 575 KB

Open AccessProceeding Paper

ISOD@M: A New Module for Predictive Analytics in Asset Management—A Case Study in Northern Italy

by Fabio Veronesi and Luca Scansetti

Eng. Proc. 2026, 135(1), 32; https://doi.org/10.3390/engproc2026135032 - 10 Jun 2026

Abstract

This paper presents an innovative asset management system developed by ISOIL to predict pipe failures and reduce non-revenue water losses in distribution networks. The system combines advanced risk assessment algorithms with mobile data collection tools to identify critical pipeline sections and optimize replacement [...] Read more.

This paper presents an innovative asset management system developed by ISOIL to predict pipe failures and reduce non-revenue water losses in distribution networks. The system combines advanced risk assessment algorithms with mobile data collection tools to identify critical pipeline sections and optimize replacement strategies. Applied to a medium-sized utility in Northern Italy, the approach successfully identified 2.36% of the network (~38 km) with the highest vulnerability levels. The predictive model demonstrated 68% accuracy in identifying locations where new leaks subsequently occurred, validating its effectiveness for proactive maintenance planning and leak detection optimization. Full article

(This article belongs to the Proceedings of II International Conference on Challenges and Perspectives in Urban Water Management Systems (CSDU-CSSI DAYS 25))

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15 pages, 5931 KB

Open AccessProceeding Paper

Evaluation of the Effectiveness of Maleic Anhydride Polypropylene in Improving Interfacial Adhesion in Untreated Palm Fiber-Reinforced Polypropylene Composites

by Bibit Sugito Suryo Suparto, Supriyono and Rois Fathoni

Eng. Proc. 2026, 137(1), 19; https://doi.org/10.3390/engproc2026137019 - 10 Jun 2026

Abstract

This study evaluated the effectiveness of maleic anhydride polypropylene (MAPP) in improving the mechanical performance and interfacial adhesion of lignocellulosic fiber-reinforced polypropylene (PP) composites. Based on Scanning Electron Microscopy (SEM) investigations, the relationship between fiber fraction, MAPP content, mechanical characteristics, and fracture morphology [...] Read more.

This study evaluated the effectiveness of maleic anhydride polypropylene (MAPP) in improving the mechanical performance and interfacial adhesion of lignocellulosic fiber-reinforced polypropylene (PP) composites. Based on Scanning Electron Microscopy (SEM) investigations, the relationship between fiber fraction, MAPP content, mechanical characteristics, and fracture morphology was the main focus. The test results showed that the stiffness and tensile strength of the composites increased with the addition of MAPP. The esterification reaction between the anhydride groups of MAPP and the hydroxyl groups of the fibers strengthened the interphase covalent bond, with the 46:50:4 composition producing the highest elastic modulus of 79.67 MPa and maximum tensile stress of 11.01 MPa. The dense interphase zone, few gaps, and no dominant fiber tension were all confirmed by SEM morphology, and also indicated effective stress transfer from the PP matrix to the fibers. However, the toughness of the material decreased significantly with increasing stiffness. Due to strong plastic deformation in the PP matrix that is not tightly attached to the fibers, the composition without MAPP (30:70:0) shows high impact energy and breaking strain, reaching 25.39 kJ/m² and 121.26%, respectively. The increase in chemical bonding at 4% MAPP content limits the mobility of the polymer chains, making it more brittle. In addition, even though MAPP is still present in the system, increasing the fiber fraction above 60% causes agglomeration, decreased homogeneity, and increased voids due to limited matrix wetting, ultimately deteriorating the mechanical properties. Tensile stress and elastic modulus have a very strong positive correlation (R² = 0.93), while impact energy and strain have a good correlation (R² = 0.89). The results overall showed that the ideal MAPP dosage is in the range of 4% before interface saturation occurs and confirmed that MAPP efficiency is determined by the balance between fiber composition, MAPP quantity, and dispersion homogeneity. Full article

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7 pages, 745 KB

Open AccessProceeding Paper

Intelligent Particulate Matter 2.5 Forecasting for Real-Time Air Quality Intelligence

by Chia-Hui Liu and Chen-Chuan Cheng

Eng. Proc. 2026, 141(1), 12; https://doi.org/10.3390/engproc2026141012 - 10 Jun 2026

Abstract

An intelligent particulate matter 2.5 forecasting system was established to enhance real-time air quality monitoring in Taiwan. Utilizing hourly data from 2024 to late 2025, the system employs deep time-series learning to capture short-term fluctuations and seasonal transitions, generating 1–2 h ahead predictions. [...] Read more.

An intelligent particulate matter 2.5 forecasting system was established to enhance real-time air quality monitoring in Taiwan. Utilizing hourly data from 2024 to late 2025, the system employs deep time-series learning to capture short-term fluctuations and seasonal transitions, generating 1–2 h ahead predictions. Specifically optimized for edge computing, the system ensures low-latency, on-site inference for practical deployment. By categorizing pollution risk levels, the framework enables early warnings for high-pollution events. Evaluation using root mean square error, mean absolute error, and the coefficient of determination confirms high predictive precision, demonstrating its potential to shift air quality management from reactive monitoring to proactive, AI-driven intelligence for sustainable urban governance. Full article

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9 pages, 1632 KB

Open AccessProceeding Paper

Hardware Implementation of an Autoencoder on a Field Programmable Gate Array

by Minh-Hieu Vo, Thien-Van Nguyen, Trong-Nhan Huynh, Tan-Phat Dang and Huu-Thuan Huynh

Eng. Proc. 2026, 141(1), 11; https://doi.org/10.3390/engproc2026141011 - 10 Jun 2026

Abstract

An autoencoder is an unsupervised deep learning architecture designed to compress input data, extract meaningful features, and reconstruct the original input for applications such as anomaly detection and data compression. However, CPU-based implementations often suffer from limited performance and high power consumption. To [...] Read more.

An autoencoder is an unsupervised deep learning architecture designed to compress input data, extract meaningful features, and reconstruct the original input for applications such as anomaly detection and data compression. However, CPU-based implementations often suffer from limited performance and high power consumption. To address these challenges, this paper presents an FPGA-based autoencoder with a hardware-friendly neural network architecture optimized for both resource utilization and processing performance. In addition, optimization techniques such as network size reduction, quantization, and pipelining are applied to improve efficiency in real-time applications. The proposed autoencoder accelerator is integrated into a Nios II system to evaluate its effectiveness. Implemented on a Cyclone V 5CSXFC6D6F31C6 FPGA (Intel Corporation, San Jose, California, United States) at 50 MHz, the system occupies 81% of logic resources, 3% of memory blocks, and 3% of digital signal processing blocks. Experimental results show that, while an Intel Xeon CPU at 2.2 GHz requires more than 0.2 s to process a single handwritten digit from the Modified National Institute of Standards and Technology dataset, the proposed system performs the same task in approximately 4.5 milliseconds, providing a 44× speedup. This demonstrates the effectiveness of the proposed FPGA-based autoencoder accelerator. Full article

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Engineering Proceedings

Vol. 136

ICACEH 2025

Vol. 135

CSDU-CSSI DAYS 25

Vol. 134

ECICE 2025

Vol. 133

EASN 2025

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