Engineering Archive
type: channel
description: engrXiv (Engineering Archive) is dedicated to the dissemination of engineering knowledge quickly and efficiently. The server is directed by Devin R. Berg and Open Engineering Inc., a 501(c)(3) non-profit. Follow us on Mastodon or Facebook or watch the engrXiv blog for updates.
language: en-US
publication name: Engineering Archive
items: Design of an IoT-Based Automatic Irrigation System for Chili Plants
items: Sustainable Off-Road Machinery Design: Reducing Soil Damage through Terrain–Machine Interaction Modeling
items: Digital Twin and Simulation-Based Design of Agricultural Processing Equipment
items: RGB versus Early-Fusion RGB-D Glass Segmentation
items: Development of an IOT-Based Smart Waste Management Web Application with a Spatial Monitoring Dashboard
items: Distributed Autonomous Snow-Clearing Systems for Public Roads
items: Discussion on "COMPARISON OF THE HYPERBOLIC AND ASAOKA OBSERVATIONAL METHODS OF MONITORING CONSOLIDATION WITH VERTICAL DRAINS"
items: General principles for modeling of thermal prebiotic synthesis and protocell self-organization in planetary environment simulators
items: Drowsiness Detection Based on Eye Aspect Ratio and Head Pose Estimation with IoT Integration
items: Coolant Intrusion in Mercedes EQ High-Voltage Battery Systems: Causes, Diagnostic Indicators, and the Risk of Unnecessary Battery Replacement
items: Stability of Structures: Kinematics, Equivalent Single-Layer Theories, and Energy-based Semi-Analytical Methods
items: Cross-consistency of system and characteristic-field models in a coupled liquid-rocket simulation (Merlin 1D–class case study)
items: Five-Year Trends in PFAS Contamination (2021-2025) in Maine Drinking Water Wells Around Sludge and Septage Sites Using Statewide Data from the Maine Department of Environmental Protection
items: Sustainable and Explainable Machine Learning for Risk-Based Maintenance Prioritization of Airport Stormwater Pipe Networks
items: Integrated Performance Assessment of the Gezira Irrigation Scheme
items: Numerical Investigation into Laminar-Flow-Sensitive Aerodynamic Behavior of the NACA 0012 Airfoil at Subsonic Mach Numbers
items: Quantum Dots Additized Lubricating Oils: A Review
items: Online-Causal Forecasting of Physics-Derived Lower-Limb Torque Proxies from Low-Cost Dual-View Motion Capture: A Subject-Specific Feasibility Study
items: Certification-Informed Analytical Preliminary Structural Design of a Box-Beam Engine Pylon for a Representative Wide-Body Civil Aircraft
items: The RopeComb: A Configurable Rope-and-Pulley Transmission for Impedance-Matched Mechanical Launch
items: Intelligent Smart Water Quality Monitoring and Autonomous Protection System Using Differential Evolution and EPANET Digital Twin
items: An Edge-Assisted IoT Framework for Intelligent Water Quality Anomaly Detection and Early Warning in Bangladesh Aquaculture
items: WLVocGenArg: Development of a Wireless Voice-Generating Arduino Gloves For The Deaf People Used For Virtual Communication
items: SPECTRA-CQ: Incipient Anomaly Detection in Bridge Health Monitoring via Capacity-Constrained Quantum and Classical Autoencoders
items: Edge AI-Driven Targeted Fertilizer Dispensing System for Mid-Sized Oil Palm Plantations Using Sensor Fusion

Design of an IoT-Based Automatic Irrigation System for Chili Plants
type: item
description: Manual watering of chili plants makes it difficult for farmers to monitor soil moisture levels and ensure consistent, periodic watering. This study aims to design an Internet of Things (IoT)-based automatic irrigation system capable of real-time soil moisture monitoring and automated watering based on soil conditions. The prototyping method was employed, comprising the stages of communication, quick planning, quick design modeling, prototype construction, and deployment and feedback. The system was built using a soil moisture sensor, ESP32, relay, water pump, Firebase Realtime Database, and an Android application. Black Box Testing was conducted to verify that the system functions according to requirements. The results demonstrate that the system can read soil moisture levels, automatically control the water pump based on predefined thresholds, and transmit and display data in real-time via Firebase and the Android application. Testing also confirmed that all core system functions—including sensor readings, pump control, data transmission, and monitoring—operated correctly as designed. Thus, the developed IoT-based automatic irrigation system can assist in monitoring soil conditions and watering chili plants.
subject: Preprints
  topic: section
subject: Internet of Things
  topic: keywords
subject: ESP32
  topic: keywords
subject: automatic irrigation
  topic: keywords
subject: soil moisture
  topic: keywords
subject: chili plants
  topic: keywords
creator: Kurniawan D. Irianto
creator: Muhammad Haris Rusnanda
rights: Copyright (c) 2026 Kurniawan D. Irianto, Muhammad Haris Rusnanda https://creativecommons.org/licenses/by/4.0
date: 2026-08-13
publication date: 2026-08-13
doi: 10.31224/7944

Sustainable Off-Road Machinery Design: Reducing Soil Damage through Terrain–Machine Interaction Modeling
type: item
description: Off-road machinery used in forestry, agriculture, land management, construction, and field logistics must operate across deformable, sloped, wet, rooted, and otherwise sensitive terrain. While such machines are essential for industrial productivity, they can also cause soil compaction, rutting, root damage, excessive slip, high contact pressure, increased fuel consumption, and long-term reduction of terrain productivity. Sustainable off-road machinery design therefore requires more than increased engine power, larger tires, or higher load capacity. It requires a systematic understanding of terrain–machine interaction. This article proposes an engineering framework for reducing soil damage through terrain–machine interaction modeling. The framework integrates soil bearing capacity, wheel–soil contact mechanics, root reinforcement, tire or track configuration, machine weight distribution, slip behavior, and mobility prediction into an applied design process for off-road machinery. Special attention is given to forestry machines operating on rooted soft soil and sloped terrain, where trafficability, productivity, operator safety, and environmental protection must be considered simultaneously. The article presents a practical modeling workflow, key engineering parameters, soil damage indicators, design strategies, an illustrative evaluation matrix, and future research directions. The proposed framework supports sustainable off-road machine development by connecting terramechanics, mechanical design, simulation-based engineering, sensor-assisted monitoring, and environmentally responsible machinery optimization.
subject: Preprints
  topic: section
subject: off-road machinery
  topic: keywords
subject: terramechanics
  topic: keywords
subject: forestry machines
  topic: keywords
subject: terrain–machine interaction
  topic: keywords
subject: rooted soil
  topic: keywords
subject: sustainable machinery
  topic: keywords
subject: Mechanical Engineering
  topic: disciplines
subject: Off-Road Vehicle Engineering
  topic: disciplines
subject: Agricultural Engineering
  topic: disciplines
subject: Forestry Engineering
  topic: disciplines
subject: Sustainable Engineering
  topic: disciplines
creator: Abdurasul Pirnazarov
rights: Copyright (c) 2026 Abdurasul Pirnazarov https://creativecommons.org/licenses/by/4.0
date: 2026-08-13
publication date: 2026-08-13
doi: 10.31224/7943

Digital Twin and Simulation-Based Design of Agricultural Processing Equipment
type: item
description: Agricultural processing equipment plays a critical role in transforming raw agricultural materials into usable industrial inputs. In cotton processing, grain handling, seed cleaning, fiber preparation, and other post-harvest operations, machinery must process biological materials that are variable in moisture, size, density, contamination level, mechanical strength, and flow behavior. This variability creates engineering challenges related to throughput, cleaning efficiency, energy consumption, material loss, machine wear, equipment reliability, and product quality. This article proposes a digital twin and simulation-based design framework for agricultural processing equipment, with particular emphasis on cotton cleaning, cotton separation, and raw material handling machinery. The proposed framework connects physical equipment, sensor data, simulation models, process optimization, and design feedback into an integrated engineering system. Instead of relying only on physical prototyping or trial-and-error modification, engineers can use digital twin models to evaluate machine geometry, operating speed, material flow, cleaning performance, energy demand, and failure risk before or during equipment operation. The article presents a conceptual digital twin architecture, a simulation-based design workflow, key input and output parameters, performance indicators, an illustrative evaluation matrix, and future research directions. The framework is designed to support agricultural processing machinery modernization, industrial automation, predictive maintenance, and sustainable manufacturing. It is especially relevant to cotton processing equipment, where improved machinery design can reduce processing losses, improve raw material quality, increase energy efficiency, and support more resilient agricultural manufacturing systems.
subject: Preprints
  topic: section
subject: digital twin
  topic: keywords
subject: cotton processing equipment
  topic: keywords
subject: simulation-based design
  topic: keywords
subject: industrial machinery
  topic: keywords
subject: mechanical engineering
  topic: keywords
subject: smart manufacturing
  topic: keywords
subject: Agricultural Machinery
  topic: disciplines
subject: Agricultural engineering
  topic: disciplines
subject: mechancial engineering
  topic: disciplines
subject: Simulation-Based Design
  topic: disciplines
subject: Digital Twin Systems
  topic: disciplines
subject: Smart Manufacturing
  topic: disciplines
creator: Abdurasul Pirnazarov
rights: Copyright (c) 2026 Abdurasul Pirnazarov https://creativecommons.org/licenses/by/4.0
date: 2026-08-13
publication date: 2026-08-13
doi: 10.31224/7942

RGB versus Early-Fusion RGB-D Glass Segmentation
type: item
description: Transparent glass is a persistent perception hazard for indoor mobile robots: RGB boundaries can be visually ambiguous, while commodity depth sensors often return missing or distorted measurements. This study isolates the effect of adding raw depth to a lightweight transformer segmenter. Two SegFormer B0 models were trained on identical partitions of the 3,009-image RGB-D Glass Surface Detection dataset using the same optimization and checkpoint-selection protocol: a three-channel RGB model and a four channel early-fusion RGB-D model. On the fixed 609-image test split, RGB outperformed RGB-D on seven of eight reported measures, reaching 0.9448 pixel accuracy, 0.8234 mean intersection over union, 0.7108 glass IoU, 0.8376 recall, and 0.8310 F1. RGB-D retained higher precision (0.8374 versus 0.8244). RGB also reduced mean inference latency by 10.7% (10.24 versus 11.47 ms) and increased throughput by 12.0% (97.63 versus 87.18 frames/s). The frozen checkpoints were then evaluated in 20 Pioneer P3-DX navigation runs. At the selected center-ratio threshold of 0.35, each model produced glass-triggered stops in both of its two glass runs (4/4 combined). Across all recorded thresholds, RGB triggered in 5/5 glass runs and RGB-D in 3/5; the independent distance safety stop terminated the remaining two RGB-D runs. Neither model produced a glass trigger in the ten non-glass runs. Under this controlled early-fusion design, raw depth did not improve unseen-test segmentation and reduced threshold robustness during robot deployment.
subject: Preprints
  topic: section
subject: Autonomous mobile robots
  topic: keywords
subject: Robotics Perception
  topic: keywords
subject: RGB-D perception
  topic: keywords
subject: semantic segmentation
  topic: keywords
subject: glass detection
  topic: keywords
subject: SegFormer
  topic: keywords
subject: Transparent Obstacles
  topic: keywords
subject: Computer Science
  topic: disciplines
subject: Artificial Intelligence and Robotics
  topic: disciplines
creator: Ebubechukwu Amasiatu
creator: Salem Ameen
rights: Copyright (c) 2026 Ebubechukwu Amasiatu, Salem Ameen https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7926

Development of an IOT-Based Smart Waste Management Web Application with a Spatial Monitoring Dashboard
type: item
description: Increasing urban waste volumes create logistical hurdles for the Regional Technical Implementation Unit (UPTD) of Waste Services in Sleman Regency. Currently, truck fleets operate on static schedules without real-time capacity data, causing severe fuel inefficiencies. To resolve this, the study designed an Internet of Things (IoT) smart waste management system integrated with a spatial dashboard using the Waterfall model. An ESP32 microcontroller and HC-SR04 ultrasonic sensor were wired to track available container space. This telemetry is transmitted to a cloud server and displayed instantly on a digital map. Testing involved 10 participants ranging from truck drivers to managers at UPTD Sleman. Evaluation results showed the sensor achieved 97.2% accuracy (2.8% error) with a rapid data transmission time of 7.46 seconds. User Acceptance Testing (UAT) and black-box assessments recorded a functional success rate exceeding 95%. During simulation, the smart routing feature successfully reduced the fleet’s daily travel distance from 25 kilometers to 12 kilometers. This logistical optimization directly lowered monthly diesel fuel consumption by 52 percent, dropping from 150 liters to 72 liters.
subject: Preprints
  topic: section
subject: Internet of Things
  topic: keywords
subject: Spatial Dashboard
  topic: keywords
subject: Smart Waste Management
  topic: keywords
subject: Route Optimization
  topic: keywords
subject: Fuel Efficiency
  topic: keywords
creator: Kurniawan D. Irianto
creator: Muhammad Ammar Fariz Baihaqi
rights: Copyright (c) 2026 Kurniawan D. Irianto, Muhammad Ammar Fariz Baihaqi https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7941

Distributed Autonomous Snow-Clearing Systems for Public Roads
type: item
description: Winter road conditions kill more than 1,300 people and injure over 116,800 annually in the United States on snowy, slushy, or icy pavement, while national winter-maintenance operations consume approximately $2.3 billion per year and roughly 20% of state Department of Transportation budgets. The prevailing operational model human-operated plow trucks working overnight storm shifts is capacity-constrained, fatigue-limited, and budget-fragile; documented state responses to cost pressure include deliberately leaving low-traffic highways unplowed overnight. This paper proposes a distributed autonomous snow-clearing system: compact autonomous plow units operating in coordinated convoys during low-traffic overnight windows, protected by an escort/signal vehicle following the beacon-signaling precedent established in active U.S. DOT truck-platooning pilots. The paper presents a quantified problem analysis from federal safety and cost data; a systems architecture with orthographic general-arrangement drawings; first-order sizing calculations covering blade forces, power, traction, stopping distance, battery capacity, and fleet sizing; an economic and nationwide-scaling analysis benchmarked against current DOT expenditure; and a phased deployment pathway grounded in three operating precedents commercial autonomous haulage in mining, winter-condition truck platooning on public highways, and a decade of academic autonomous-snowplow robotics. First-order results indicate per-unit blade power of order 14 kW, unit mass of order 1,200 kg, and a 12–15 unit fleet sufficient for a 500 priority-lane-mile city within a four-hour window physically plausible scales using present-day components.
subject: Preprints
  topic: section
subject: autonomous vehicles
  topic: keywords
subject: winter road maintenance
  topic: keywords
subject: snow removal
  topic: keywords
subject: physical AI
  topic: keywords
subject: V2X
  topic: keywords
subject: fleet robotics
  topic: keywords
subject: transportation safety
  topic: keywords
subject: autonomous snowplow
  topic: keywords
subject: DOT winter operations
  topic: keywords
subject:
  topic: subjects
  value: autonomous vehicles · autonomous snowplow · winter road maintenance · snow and ice control · robotics · physical AI · vehicle-to-everything (V2X) · fleet automation · road safety · transportation infrastructure · mechatronics · winter operations economics
subject: • Mechanical Systems Architecture
  topic: disciplines
subject: Artificial Intelligence (AI)
  topic: disciplines
subject: Road safety
  topic: disciplines
subject: Civil engineering
  topic: disciplines
subject: Robotics
  topic: disciplines
creator: Samuel Ayo Oyedemi
rights: Copyright (c) 2026 Samuel Ayo Oyedemi https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7939

Discussion on "COMPARISON OF THE HYPERBOLIC AND ASAOKA OBSERVATIONAL METHODS OF MONITORING CONSOLIDATION WITH VERTICAL DRAINS"
type: item
description: This paper presents a discussion on the hyperbolic and Asaoka observational methods for monitoring soil consolidation with vertical drains, specifically addressing their limitations in accounting for missing time problem & secondary consolidation. To overcome these constraints, the discussion introduces two alternative settlement-velocity methods: the settlement-velocity (δ-v) and settlement-log(velocity) (δ-log(v)) techniques. These methods allow for the evaluation of the true coefficient of consolidation (Cv) and ultimate primary settlement (δ_ult) by isolating the effects of secondary compression. Unlike traditional time-centric approaches, these velocity-based methods do not require instantaneous loading & initial conditions, known initial boundary timelines, or the clock time of the load increment. By mapping the settlement state directly against its rate of change, the proposed framework offers a more robust and mathematically simplified approach to extracting fundamental consolidation parameters from standard field data beyond the 60% consolidation stage.
subject: Preprints
  topic: section
subject: Consolidation
  topic: keywords
subject: Pore Pressure
  topic: keywords
subject: Field Monitoring
  topic: keywords
subject: XYY' Calculus
  topic: keywords
subject: YY' Calculus
  topic: keywords
subject: Civil Engineering
  topic: subjects
subject: Geotechnical Engineering
  topic: subjects
subject: applied mathematics
  topic: subjects
subject: Applied Physics
  topic: subjects
subject: Department of Structural, Geotechnical and Building Engineering
  topic: disciplines
subject: Geotechnical Earthquake Engineering
  topic: disciplines
creator: Sudhir Kumar Tewatia
rights: Copyright (c) 2026 Sudhir Kumar Tewatia https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7938

General principles for modeling of thermal prebiotic synthesis and protocell self-organization in planetary environment simulators
type: item
description: This paper considers the problem of achieving plausible and effective (leading to the formation of structures similar to biological ones) conditions for modeling thermally induced prebiotic processes from the perspective of thermodynamics, thermal physics, and thermal engineering. The article’s presentation is based on the principle of transition from thermal physics and thermodynamics to thermal engineering for constructing planetary environment simulators with controlled environmental conditions. Based on the physical premises from the first parts of this comprehensive review, a conclusion is made regarding the need to consider an additional set of controlled physical parameters or additional factors influencing the models of prebiotic synthesis and formation of precellular/protocell structures implemented in planetary environment simulators and hydrothermal synthesis reactors. Non-thermal heating sources are also considered, such as radiofrequency and microwave irradiation for dielectric heating, as well as radioisotope heating in the early Earth/protoplanet conditions. The coexistence of physical and chemical pathways for heating the prebiotic environment and the feasibility of modeling this separation in planetary environment simulators and controllable climate chamber facilities are highlighted. Exothermic reactions during hydrothermal serpentinization are considered as an example of chemical heating in prebiotic environments. This can lead to the abiotic synthesis of organic matter (which correlates well with the existing hypotheses of the origin of life in alkaline hydrothermal vents, with the mineral genesis of protocells and membrane potential generation on inorganic catalytic protomembranes). Thermal proteinoids and thermal proteinoid microspheres that form on their basis are considered an example of purely organic prebiotic structures obtained via hydrothermal heating. It is demonstrated that the application of thermophysical and thermal engineering appr…
subject: Preprints
  topic: section
subject: non-equilibrium thermodynamics
  topic: keywords
subject: thermal prebiotic synthesis
  topic: keywords
subject: geothermal conditions
  topic: keywords
subject: hydrothermal conditions
  topic: keywords
subject: planetary environment simulator
  topic: keywords
subject: hydrothermal synthesis reactor
  topic: keywords
subject: thermocycling
  topic: keywords
subject: PCR
  topic: keywords
subject: serpentinization
  topic: keywords
subject: thermal proteinoids
  topic: keywords
subject: thermal proteinoid microspheres
  topic: keywords
subject: thermal systems engineering
  topic: keywords
subject: thermophysics
  topic: disciplines
subject: thermal systems engineering
  topic: disciplines
subject: planetary simulator engineering
  topic: disciplines
subject: geothermal engineering
  topic: disciplines
subject: hydrothermal engineering
  topic: disciplines
subject: Microwave Engineering
  topic: disciplines
subject: thermochemistry
  topic: disciplines
subject: biomimetics
  topic: disciplines
subject: photocatalysis
  topic: disciplines
subject: Radio Engineering
  topic: disciplines
subject: radiophysics
  topic: disciplines
creator: Oleg Gradov
creator: Margaret Gradova
rights: Copyright (c) 2026 Oleg Gradov, Margaret Gradova https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7937

Drowsiness Detection Based on Eye Aspect Ratio and Head Pose Estimation with IoT Integration
type: item
description: This study proposes a real-time driver drowsiness detection system integrating computer vision with Internet of Things (IoT) technology on an affordable embedded platform. The system uses a Camera Module 3 Wide NoIR connected to a Raspberry Pi 3 Model B+ to capture driver facial images. Two visual indicators are computed in parallel from 68 facial landmarks extracted using dlib: Eye Aspect Ratio (EAR) for detecting prolonged eye closure, and Head Pose Estimation using solvePnP for detecting head nodding. An OR-logic decision mechanism triggers an audio alarm when EAR falls below 0.25 for five consecutive frames or Pitch angle exceeds 15 degrees for ten consecutive frames. Events are classified as KANTUK_MATA, KANTUK_KEPALA, or KEDUANYA and sent to firebase Realtime Database for remote monitoring. Black Box testing with 11 scenarios confirms all core functions operate correctly. Average response times of 2.00 seconds via EAR and 2.70 seconds via Head Pose are within acceptable ranges for early drowsiness warning. The multi-indicator approach demonstrates that head nodding is detected earlier than eye closure in gradual drowsiness scenarios, providing earlier warning than single-indicator systems.
subject: Preprints
  topic: section
subject: Driver Drowsiness Detection
  topic: keywords
subject: Eye Aspect Ratio
  topic: keywords
subject: Head Pose Estimation
  topic: keywords
subject: Raspberry Pi
  topic: keywords
subject: IoT
  topic: keywords
subject: Firebase
  topic: keywords
creator: Kurniawan D. Irianto
creator: Rama Amirul Ramadhan
rights: Copyright (c) 2026 Kurniawan D. Irianto, Rama Amirul Ramadhan https://creativecommons.org/licenses/by/4.0
date: 2026-08-12
publication date: 2026-08-12
doi: 10.31224/7935

Coolant Intrusion in Mercedes EQ High-Voltage Battery Systems: Causes, Diagnostic Indicators, and the Risk of Unnecessary Battery Replacement
type: item
description: The rapid expansion of the global electric vehicle market, which surpassed 17 million units sold in 2024 according to the International Energy Agency, has made the reliable diagnosis of high-voltage battery faults a critical competency for automotive dealerships worldwide. In Mercedes EQ vehicles, coolant intrusion into the battery enclosure represents a frequently underdiagnosed failure mode that shares its primary symptom with genuine cell-level degradation: a drop in isolation resistance triggering Battery Management System fault codes. The present study examines the technical causes of coolant ingress in EQ platform battery systems (EQA, EQB, EQC, EQS, and derivatives), characterizes the diagnostic indicators that distinguish this event from primary battery failure, and evaluates the downstream risk of unnecessary high-voltage battery replacement. Through systematic review of manufacturer recall documentation, technical service bulletins, peer-reviewed literature on battery thermal management and fault diagnosis, and documented dealer case studies, this paper shows that coolant intrusion can depress isolation resistance to levels that trigger emergency shutdowns without causing irreversible cell damage. A structured six-step diagnostic protocol and a replacement decision matrix are proposed to guide technicians. The findings are of direct relevance to Mercedes-Benz authorized dealers, independent EV specialists, and automotive service engineers seeking cost-effective, evidence-based diagnostic workflows.
subject: Preprints
  topic: section
subject: coolant intrusion
  topic: keywords
subject: high-voltage battery
  topic: keywords
subject: Mercedes EQ
  topic: keywords
subject: battery management system
  topic: keywords
subject: isolation resistance
  topic: keywords
subject: EV diagnostics
  topic: keywords
subject: thermal management
  topic: keywords
subject: dealership service
  topic: keywords
subject: fault code
  topic: keywords
subject: battery replacement risk
  topic: keywords
creator: Alexey Samoilov
rights: Copyright (c) 2026 Alexey Samoilov https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7933

Stability of Structures: Kinematics, Equivalent Single-Layer Theories, and Energy-based Semi-Analytical Methods
type: item
description: This part of the course details the fundamental principles of structural stability, focusing on kinematic relations and equivalent single-layer (ESL) theories for composite plates and shells. It derives three-dimensional strain-displacement equations for planar, cylindrical, conical, and spherical geometries. The formulations are systematically reduced to two-dimensional ESL models, specifically the Classical Laminated Plate Theory (CLPT), First-order Shear Deformation Theory (FSDT), and Third-order Shear Deformation Theory (TSDT). The limitations of ESL theories regarding interlaminar stress continuity are analysed, introducing Zig-Zag and Layerwise theories as advanced alternatives. Furthermore, the material covers energy-based formulation frameworks, deriving the principle of minimum potential energy, the semi-analytical Ritz method utilizing Legendre polynomials, and the neutral equilibrium criterion for extracting geometric stiffness matrices and linear buckling equations.
subject: Preprints
  topic: section
subject: Structural stability
  topic: keywords
subject: equivalent single-layer theories
  topic: keywords
subject: classical laminated plate theory
  topic: keywords
subject: CLPT
  topic: keywords
subject: first-order shear deformation theory
  topic: keywords
subject: FSDT
  topic: keywords
subject: third-order shear deformation theory
  topic: keywords
subject: TSDT
  topic: keywords
subject: buckling
  topic: keywords
subject: static analysis
  topic: keywords
subject: layerwise
  topic: keywords
subject: semi-analytical
  topic: keywords
subject: Ritz
  topic: keywords
subject: energy-based methods
  topic: keywords
creator: Saullo G. P. Castro
rights: Copyright (c) 2026 Saullo G. P. Castro https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7932

Cross-consistency of system and characteristic-field models in a coupled liquid-rocket simulation (Merlin 1D–class case study)
type: item
description: Coupled liquid-rocket system models and multidimensional nozzle solvers are usually developed separately; when they are made to share a chamber state, the mass-flow consistency between them is easy to leave unmeasured. We describe a transient LOX/RP-1 open-cycle gas-generator engine architecture - capacitance–inertance liquid feed networks, a compressible gas-flow network, shaft dynamics, multi-layer regenerative wall response, offline equilibrium thermochemistry tables, and orifice injector hydraulics- coupled at analysis stop to an axisymmetric method-of-characteristics (MOC) nozzle field evaluated at the shared chamber stagnation state. A headless extraction harness regenerates all tabulated results from frozen inputs and grades two mass residuals: conservation through the marched nozzle field, and agreement between field and system mass flow. The architecture is demonstrated on a Merlin 1D–class case assembled from public data. On the frozen case, field mass conservation closes to +0.92%, the field–system mass-flow residual is -1.78%, sea-level field thrust is ~831 kN, and engine specific impulse on total propellant flow (~305 kg/s) is ~277.7 s, consistent with the public Merlin-class bands that guided case authoring. The result is a documented, reproducible open-cycle composition in which system–field consistency is measured rather than assumed; the case study is a representative reconstruction, and all artefacts are archived on Zenodo.
subject: Preprints
  topic: section
subject: Rocket Propulsion
  topic: keywords
subject: Rocket engine
  topic: keywords
subject: Gas-Generator Cycle
  topic: keywords
subject: System Modelling
  topic: keywords
subject: Method of Characteristics
  topic: keywords
subject: Engineering Verification
  topic: keywords
subject: Nozzle Flow
  topic: keywords
subject: Turbomachinery
  topic: keywords
subject: Aerospace Engineering
  topic: disciplines
subject: Systems Modeling and Simulation
  topic: disciplines
creator: Daniel Sim
rights: Copyright (c) 2026 Daniel Sim https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7924

Five-Year Trends in PFAS Contamination (2021-2025) in Maine Drinking Water Wells Around Sludge and Septage Sites Using Statewide Data from the Maine Department of Environmental Protection
type: item
description: In 2016, the State of Maine became aware of PFAS contamination in a drinking water well in West Kennebunk1, Maine. Since then, significant PFAS contamination of drinking water wells in Maine has been discovered through the “PFAS Soil and Groundwater Investigation at Sludge and Septage Land Application Sites”3, completed by the Maine Department of Environmental Protection (MEDEP). The MEDEP has been taking PFAS samples in drinking water wells near sludge and septage sites since January of 20176. In the fall of 2025, I discussed with the MEDEP the possibility of evaluating statewide PFAS sample data to date, to look for PFAS contamination trends in PFAS contaminated drinking water wells. With thorough supportive assistance from the MEDEP, in late 2025 and early 2026 I received spreadsheet data of PFAS sample test results for all samples taken by the MEDEP or their contractors around sludge and septage land application sites (~220,000 PFAS parameter test results)4. All of the samples were taken from drinking water wells throughout Maine4. This report describes the methodology used to identify trends in PFAS concentration in drinking water wells throughout the State of Maine over a five-year period: 2021-2025. Results include: Trend graphs for PFAS 6 and PFOS independently, for 99 and 126 wells respectfully, that had sample results in each of those five years. The percentage of those wells with increasing trends of PFAS6 or PFOS concentration over the five-year period 2021-2025. Graphs showing PFAS trends for a subset of those wells with at least one sample over 1000 ppt (parts per trillion) PFAS 6 or PFOS, and for the subset of wells with at least one sample over 10,000 ppt PFAS 6 or PFOS. Conclusions and Recommendations are included.
subject: Preprints
  topic: section
subject: PFAS
  topic: keywords
subject: PFAS6
  topic: keywords
subject: PFOS
  topic: keywords
subject: Maine
  topic: keywords
subject: PFAS Contamination
  topic: keywords
subject: PFAS Contaminated Drinking Water Well
  topic: keywords
subject: Land-Spread Sludge
  topic: keywords
subject: Septage
  topic: keywords
subject: Maine Department of Environmental Protection
  topic: keywords
subject: ME DEP
  topic: keywords
subject: wastwater treatment sludge
  topic: keywords
subject: PFAS contaminated wastewater treatment sludge
  topic: keywords
subject: PFAS
  topic: subjects
subject: Per and Polyfuoroalkyl substances
  topic: subjects
subject: Drinking water contamination
  topic: subjects
subject: PFAS contamination of drinking water wells
  topic: subjects
subject: Environmental Engineering
  topic: disciplines
subject: Data Analysis
  topic: disciplines
subject: Research
  topic: disciplines
creator: Nathan Saunders
rights: Copyright (c) 2026 Nathan Saunders https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7929

Sustainable and Explainable Machine Learning for Risk-Based Maintenance Prioritization of Airport Stormwater Pipe Networks
type: item
description: Airport stormwater pipe networks operate under demanding conditions where infiltration, structural defects, debris accumulation, hydraulic inefficiencies, and water-quality concerns can gradually reduce system performance. Conventional inspection-based maintenance can identify these deficiencies, but reacting to large inspection datasets and determining which pipe segments require the earliest intervention remains challenging. This study proposes an explainable machine-learning framework for risk-based maintenance prioritization of airport stormwater infrastructure. An anonymized dataset containing pipe characteristics, inspection observations, hydraulic conditions, infiltration indicators, and water-quality measurements is used to develop and evaluate a proof-of-concept machine learning framework for identifying higher-priority maintenance locations. Random Forest and gradient-boosting algorithms are explored within the framework, while explainable-AI techniques are used to identify the factors influencing maintenance priority. The framework is intended to support faster engineering response, more targeted inspections and rehabilitation, reduced unnecessary intervention, and improved asset life-cycle management. The proposed approach provides a data-driven pathway toward more resilient and sustainable maintenance of underground drainage infrastructure in complex airport environments.
subject: Preprints
  topic: section
subject: asset management
  topic: keywords
subject: Sustainable construction
  topic: keywords
subject: Explainable AI
  topic: keywords
subject: Stormwater drainage
  topic: keywords
subject: Airport infrastructure
  topic: keywords
subject: AI adaptive learning
  topic: keywords
creator: Emanuel Muniez
creator: Mateo Fernando García
creator: Faustus Ricardo Sulla
rights: Copyright (c) 2026 Emanuel Muniez, Mateo Fernando García, Faustus Ricardo Sulla https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7927

Integrated Performance Assessment of the Gezira Irrigation Scheme
type: item
description: The Gezira Scheme (GS) is considered one of the oldest irrigation systems in Africa and the Arab region. Moreover, it is the largest scheme (0.9 million ha) in the world under a single management. The irrigation network is 11,000 km long with 29,000 field channels. This paper evaluates the performance of the GS irrigation system after a century of operation, particularly given the serious deterioration over the past two decades, during which the system has failed to meet crop water requirements. The assessment draws on MOIWR sediment monitoring and desilting records for 1987-2005, HR Wallingford field measurements, and published technical efficiency and hydro-economic studies. This issue may be primarily attributed to the significant amounts of sediment entering the scheme each year and the mismanagement of the irrigation system. Inflowing sediment concentration rose from about 700 ppm in the 1930s to about 8,000 ppm in the 1990s; desilting now consumes more than 60% of O&M expenditure; and the scheme's debt grew from USD 34 million in 1999 to over USD 150 million by 2005. The consequence of this situation is water shortage in many areas of the scheme, while others experience flooding, leading to inequitable water distribution. This disparity leads to a decline in crop production and returns from the scheme. In light of these issues, a critical review of the irrigation system is warranted. The concept and procedure for designing and remodelling the silted canals to restore the original section are highlighted, based on the rich experience and performance of this irrigation system. It is concluded that aquatic weeds increase sedimentation, and the deposited sediment enhances aquatic weeds' growth, thereby reducing canal capacity. The impact of this on the socio-economic development of the scheme inhabitants is explained. The paper finally examines the possibility of maintaining stable regime conditions in the canals. It also reports on the future of irrigation system…
subject: Preprints
  topic: section
subject: Sudan
  topic: keywords
subject: canal regime design
  topic: keywords
subject: irrigation
  topic: keywords
subject: sediment management
  topic: keywords
subject: performance
  topic: keywords
subject: night storage system
  topic: keywords
subject: aquatic weeds
  topic: keywords
subject: water governance
  topic: keywords
creator: Abdalla A. Ahmed
rights: Copyright (c) 2026 Abdalla A. Ahmed https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7923

Numerical Investigation into Laminar-Flow-Sensitive Aerodynamic Behavior of the NACA 0012 Airfoil at Subsonic Mach Numbers
type: item
description: Laminar flow behavior over airfoil surfaces plays a critical role in determining the aerodynamic efficiency in subsonic flight, particularly through its influence on viscous drag and boundary-layer development. The thickness of an airfoil affects the pressure-gradient distribution along the surface and can therefore influence laminar flow stability and aerodynamic performance. Quantitative investigations on isolating the thickness as an independent geometric parameter under consistent numerical conditions remain limited. This study presents a numerical investigation into the influence of airfoil thickness on laminar flow characteristics at subsonic Mach numbers. A symmetric NACA 0012 airfoil was adopted as the baseline geometry, and systematic thickness variations were introduced while maintaining a constant chord length and camber characteristics. The aerodynamic performance was analyzed using XFLR5 predictions combined with computational fluid dynamics (CFD) simulations performed using a Reynolds-averaged Navier–Stokes framework with transition-sensitive modeling. The analysis was conducted under subsonic operating conditions representative of low-speed aerodynamic applications. The results showed that increasing the airfoil thickness strengthened the adverse pressure gradients on the suction surface, leading to increased boundary-layer sensitivity and drag penalties. Thinner configurations exhibited delayed pressure recovery and improved aerodynamic efficiencies within the investigated operating range. CFD flow-field visualization further illustrated the relationship between pressure gradient development, wake growth, and aerodynamic performance trends. The findings provide insights into the sensitivity of laminar flow behavior to airfoil thickness and highlight the efficacy of the XFLR5 and CFD approaches in early-stage airfoil design and aerodynamic evaluations.
subject: Preprints
  topic: section
subject: Laminar Airfoil
  topic: keywords
subject: Subsonic
  topic: keywords
subject: Aerodynamic
  topic: keywords
subject: Airfoil
  topic: keywords
subject: CFD
  topic: keywords
subject: XFLR5
  topic: keywords
subject: ANSYS Fluent
  topic: keywords
subject: Aerodynamics
  topic: subjects
creator: Ayush Kamboj
rights: Copyright (c) 2026 Ayush Kamboj https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7922

Quantum Dots Additized Lubricating Oils: A Review
type: item
description: In this review, the studies pertaining to the quantum dots dispersed lubricating oils is systematically reviewed. Various aspects such as synthesis of the QDs additive, their dispersion method and stability, dispersion stability enhancement methods, and their tribological performance is presented. It is found that, such additized oils result in friction and wear reduction for steel tribopair by about 37.07 ± 17.25 % and 58.91 ± 23.77 % respectively.
subject: Preprints
  topic: section
subject: Nano lubricant
  topic: keywords
subject: lubrication
  topic: keywords
subject: Tribology
  topic: disciplines
creator: Prasad
rights: Copyright (c) 2026 Prasad https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7919

Online-Causal Forecasting of Physics-Derived Lower-Limb Torque Proxies from Low-Cost Dual-View Motion Capture: A Subject-Specific Feasibility Study
type: item
description: Low-cost motion capture may support anticipatory biomechanical surrogates, but causal deployability and target validity must be distinguished. We evaluated subject-specific 100-ms forecasting of physics-derived lower-limb torque proxies from dual-view marker video, with four-channel surface electromyography (sEMG) as an optional modality, using one 60-kg adult recording. Approximate 3D trajectories generated proxy targets through an engineering Lagrangian model; no force-plate or validated inverse-dynamics reference was available. Video-sEMG alignment was estimated on training data only and frozen at 559 frames (9.317 s). A six-channel causal gait-context receptive-field-matched temporal convolutional network (RF-TCN) achieved strict-test MAE 0.1326 Nm/kg, RMSE 0.2069, R² 0.4427, and r 0.6529 over 1564 windows; five-seed MAE was 0.1338 ± 0.0011 Nm/kg. Relative to the earlier causal-context reference, MAE decreased by 2.47%, while other metrics showed no supported improvement. A controlled K7-versus-K9 ablation showed only a small average MAE advantage for K9 and no statistically resolved overall effect. Sparse sEMG added no benefit beyond gait context. In stateful streaming replay, GPU complete-update p95/p99 latency was 21.78/25.03 ms with 0/6069 steady-state 50-ms deadline misses. These results support leakage-controlled, training-stable surrogate forecasting and GPU computational feasibility, not validated biological kinetics or hard-real-time exoskeleton control.
subject: Preprints
  topic: section
creator: Ange Tong
rights: Copyright (c) 2026 Ange Tong https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7918

Certification-Informed Analytical Preliminary Structural Design of a Box-Beam Engine Pylon for a Representative Wide-Body Civil Aircraft
type: item
description: Objectives: This study develops a certification-informed analytical framework for the preliminary structural design of an under-wing box-beam engine pylon representative of a twin-engine wide-body civil aircraft. The objective is to link airworthiness-derived loading requirements, engine–pylon reactions, structural architecture and geometry-based mass assessment within a traceable early-design workflow. Methods: Three aircraft mass states, five characteristic speeds and nine altitude conditions define the baseline design space. Gust, gyroscopic, engine failure, engine seizure, and emergency loading are evaluated to establish six-component reaction envelopes. These loads are transferred through an idealised closed box-beam representation to derive internal shear-force, bending-moment and torsional distributions and to support preliminary structural sizing of skins, ribs, stiffeners, spar caps and attachment lugs. Results: The final configuration contains 12 ribs and transitions from integral blade stiffeners in the central box to four L-section spar caps in geometrically constrained tapered regions. The CAD-based structural mass is approximately 596 kg per pylon, with the Ti-6Al-4V primary structure contributing approximately 85%. Conclusions: The methodology provides a transparent analytical route from certification-informed loading to preliminary structural architecture and mass assessment. No finite-element stress, displacement or buckling results are used as validation evidence; higher-fidelity numerical and experimental verification remains necessary.
subject: Preprints
  topic: section
subject: Aircraft Design
  topic: keywords
subject: Aerospace engineering
  topic: keywords
subject: Engine Design
  topic: keywords
subject: Engine Pylons
  topic: keywords
subject: Wide-Body Aircraft
  topic: keywords
creator: Ayush Kamboj
rights: Copyright (c) 2026 Ayush Kamboj https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7917

The RopeComb: A Configurable Rope-and-Pulley Transmission for Impedance-Matched Mechanical Launch
type: item
description: Transferring kinetic energy from a slow, high-force source, such as a descending mass, a ram or a spring, to a fast, light payload requires a transmission whose mechanical advantage rises continuously through the stroke. We introduce the RopeComb: a passive, configurable rope-and-pulley transmission in which a translating carriage progressively deflects a tension member into successive fixed spans. Two independent geometric freedoms per member (span width and engagement offset) make essentially any monotonically rising profile reachable, and because the resulting displacement ratio has a closed form, matching a target is a smooth least-squares fit rather than a search. By specifying a source deceleration rather than a payload force, and solving for the force that produces it, the geometry can be optimised for uniform payload force. Across mass ratios of 100:1, 1,000:1 and 10,000:1, arrays of eight to thirteen members track that target to within 1.5% and reach its exit velocity in arrays 1.9-2.8 m wide. Measured against the work needed to raise the source again, through the braking distance as well as the height that sets its entry speed, the transmission delivers 86.3% of the input to the payload; that figure is fixed by the entry and final speeds and the braking distance alone, and does not depend on mass ratio. The three simulated designs realise it to within 0.4%. It precedes a correction for the rotational inertia of sheaves in the fast path, which is first-order, scale-invariant, and costs a further 9 to 12% of exit velocity, leaving the payload 66 to 72% of cycle input rather than 86.3%. The stroke is terminated by a traction-loss instability, and the specified deceleration is the hardest that leaves the tension member continuously loaded throughout, with release occurring before the terminal transient. Pairing the RopeComb with a compliant, pre-tensioned output member absorbs the transients of discrete engagement, holding peak-to-mean payload force to 1.09-1.…
subject: Preprints
  topic: section
subject: rope-and-pulley transmission
  topic: keywords
subject: variable mechanical advantage
  topic: keywords
subject: impedance matching
  topic: keywords
subject: mechanical launch
  topic: keywords
subject: catapult
  topic: keywords
subject: UAV launch
  topic: keywords
subject: block and tackle
  topic: keywords
subject: least-squares design
  topic: keywords
subject: energy transfer
  topic: keywords
subject: passive mechanism
  topic: keywords
subject: kinematics
  topic: keywords
subject: passive transmission
  topic: keywords
subject: rope and pulley
  topic: keywords
subject: peak-to-mean force
  topic: keywords
subject: Mechanical Engineering
  topic: disciplines
subject: Aerospace Engineering
  topic: disciplines
subject: Engineering Mechanics
  topic: disciplines
subject: Applied Mechanics
  topic: disciplines
subject: Systems Engineering
  topic: disciplines
creator: Rami Mahdi
rights: Copyright (c) 2026 Rami Mahdi https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7913

Intelligent Smart Water Quality Monitoring and Autonomous Protection System Using Differential Evolution and EPANET Digital Twin
type: item
description: Modern urban water distribution systems require intelligent monitoring and autonomous protection mechanisms to prevent contamination and ensure public safety. This paper presents an intelligent decision-support framework integrating Differential Evolution (DE) optimization, EPANET hydraulic simulation, rule-based contamination risk assessment, and a real-time digital twin dashboard. The proposed system continuously monitors water quality parameters including chlorine concentration, turbidity, pressure, and temperature while performing rule-based contamination risk estimation and emergency response control. The developed framework can automatically isolate contaminated network zones using smart valve control and provide intelligent operational recommendations. Beyond the original single-function demonstration, this extended study validates the DE implementation against ten standard benchmark functions, benchmarks it against a particle swarm optimizer under a matched evaluation budget, quantifies the contamination-detection logic against twenty synthetic test scenarios spanning safe, boundary, and multi-fault conditions, and couples a second DE search directly to the EPANET hydraulic model to test pump-speed and valve-setpoint operating envelopes against real simulated pressure constraints rather than an abstract proxy objective. Experimental results demonstrate that the proposed system successfully improves contamination detection, visualization, and autonomous response capabilities for smart city water infrastructures; the EPANET-coupled search further shows that, within the physically reasonable pump-speed range tested, the network's surplus hydraulic capacity leaves no interior energy-pressure trade-off for the optimizer to find, a genuine, if modest, finding about the network's spare capacity. The study also surfaces implementation considerations, including a still-simplified default optimization objective and several software integration issues, that mark the cl…
subject: Preprints
  topic: section
subject: Differential Evolution
  topic: keywords
subject: EPANET
  topic: keywords
subject: Smart Water System
  topic: keywords
subject: Decision Support Systems
  topic: keywords
subject: Water Quality Monitoring
  topic: keywords
subject: Digital Twin
  topic: keywords
subject: Smart City
  topic: keywords
subject: Autonomous Protection
  topic: keywords
subject: Particle Swarm Optimization
  topic: keywords
subject: Computer Engineering
  topic: disciplines
subject: Civil and Environmental Engineering
  topic: disciplines
subject: Systems Engineering
  topic: disciplines
creator: Mathew Luv Christe
creator: Junior Charlie
rights: Copyright (c) 2026 Mathew Luv Christe, Junior Charlie https://creativecommons.org/licenses/by/4.0
date: 2026-08-11
publication date: 2026-08-11
doi: 10.31224/7916

An Edge-Assisted IoT Framework for Intelligent Water Quality Anomaly Detection and Early Warning in Bangladesh Aquaculture
type: item
description: In sustainable aquaculture, maintaining optimal water quality is essential, as sudden environmental changes can lead to disease outbreaks, reduced productivity, and significant fish mortality. This paper presents an edge-assisted Internet of Things (IoT)-Cyber Physical System (CPS) framework for intelligent water quality monitoring and real-time anomaly detection. The proposed framework integrates IoT-enabled water quality sensors, an ESP32 edge device, and a Raspberry Pi 4 Model B to perform real-time data acquisition, preprocessing, and anomaly detection using the Isolation Forest algorithm. While the ESP32 is responsible for collecting and transmitting sensor data, the Raspberry Pi executes the computationally intensive anomaly detection process and supports intelligent early-warning generation with low communication latency. Four critical water quality parameters, namely temperature, dissolved oxygen (DO), pH, and turbidity, were selected from the publicly available IoTMLCQ dataset. After data preprocessing and feature normalization, the proposed framework was evaluated using confusion matrix analysis, receiver operating characteristic (ROC) analysis, and standard classification metrics. Experimental results demonstrate that the proposed model achieved an accuracy of 97.25%, a precision of 66.67%, a recall of 66.45%, an F1-score of 66.56%, and an ROC-AUC of 98.44%, outperforming One-Class Support Vector Machine and Local Outlier Factor under identical experimental conditions. The proposed low-cost edge-assisted architecture provides timely anomaly detection and intelligent early warning, offering a practical solution to reduce fish losses, improve aquaculture farm management, and support sustainable smart aquaculture.
subject: Preprints
  topic: section
subject: Internet of Things (IoT)
  topic: keywords
subject: Cyber Physical Systems
  topic: keywords
subject: Isolation Forest
  topic: keywords
subject: Edge Computing
  topic: keywords
subject: Anomaly Detection
  topic: keywords
subject: Water Quality Monitoring
  topic: keywords
creator: Sunnymoon Rafi
creator: Md. Mahibullah
creator: Kazi Wakilur Rahman Rumman
creator: Shah Muhammad Azmat Ullah
creator: Gazi Muhammad Abdullah Mahfuz
creator: Toufik Ahmed
rights: Copyright (c) 2026 Sunnymoon Rafi, Md. Mahibullah, Kazi Wakilur Rahman Rumman, Shah Muhammad Azmat Ullah, Gazi Muhammad Abdullah Mahfuz, Toufik Ahmed https://creativecommons.org/licenses/by/4.0
date: 2026-08-10
publication date: 2026-08-10
doi: 10.31224/7914

WLVocGenArg: Development of a Wireless Voice-Generating Arduino Gloves For The Deaf People Used For Virtual Communication
type: item
description: Sign Language is the means for deaf people to communicate - they are more visually oriented people since most are deprived of the ability to hear and consequently, to speak in return. However, most non-deaf or ordinary people are incapable of communicating and understanding sign language. This study aims to develop wireless voice-generating gloves using Arduino that aid the deaf in communicating with normal people by translating signs and gestures into synthetic speech. In being able to do feedback, a normal person’s voice is transcribed into text as he/she presses the microphone button on the MIT App Inventor-developed mobile application named “FSL” before he/she speaks and then the text will display on the glove’s attached 20x4 LCD Screen for the deaf user to be able to receive the former’s response - two-way communication. The study envisions bridging the gaps in similar previous innovations for the beneficiary to benefit from the project fully. Through the quantitative method in the lens of the Technology Acceptance Model by Fred Davis (1989), a survey on Perceived Usefulness (PU) and Perceived Ease of Use (PEU) is administered to 20 respondents - Grade 7 and 8 deaf students of Parañaque National High School - Special Education Department (SPED), as well as Grades 5 and 6 deaf students of Las Piñas Elementary School Central - SPED. In the findings, to be able to perform in class better (e.g., assignments and projects) is the highlighted PU with the level of “Quite Likely,” while the PEU level is also “Quite Likely” due to the newness of the technology to the students, which underlines that there is still some perceived difficulty in using it. The core purpose of this intervention is to aid young deaf individuals in seeing the bigger horizons they ought to see and to make them feel that they are never isolated or treated as outcasts in today’s world equipped with technology.
subject: Preprints
  topic: section
subject: Arduino
  topic: keywords
subject: MIT App Inventor
  topic: keywords
subject: Deaf people
  topic: keywords
subject: Sign Language
  topic: keywords
subject: Two-way communication
  topic: keywords
subject: Information Technology
  topic: disciplines
subject: Computer Engineering
  topic: disciplines
subject: Assistive Technology
  topic: disciplines
subject: Human-Computer Interaction
  topic: disciplines
subject: Embedded Systems
  topic: disciplines
creator: John Syte Tiopes
creator: Jericho Gerald Baluyot
creator: Ericka Mae Rodillo
rights: Copyright (c) 2026 John Syte Tiopes, Jericho Gerald Baluyot, Ericka Mae Rodillo https://creativecommons.org/licenses/by/4.0
date: 2026-08-10
publication date: 2026-08-10
doi: 10.31224/7911

SPECTRA-CQ: Incipient Anomaly Detection in Bridge Health Monitoring via Capacity-Constrained Quantum and Classical Autoencoders
type: item
description: Detecting incipient structural damage in civil infrastructure requires isolating transient acoustic emissions that are heavily obscured by macroscopic environmental noise. This paper introduces SPECTRA-CQ (Spectrogram Pattern Evaluation via Classical and Quantum Architectures), a hybrid anomaly detection framework evaluated on continuous vibration telemetry from the operational openLAB reference bridge in Bautzen, Germany. Raw 1-dimensional accelerometer signals are mapped into 2-dimensional 64 × 1000 energy-density spectrograms via Continuous Wavelet Transform (CWT) to preserve critical time-frequency localization. A synthetic acoustic emission (AE) proxy is then injected into a target node to establish strict physical detection limits. This AE is bounded at an amplitude of 0.35 to mathematically simulate early-stage micro-cracking rather than obvious macroscopic failure. Initial unconstrained baseline ablations establish that both architectures are mathematically sound. Both Classical Convolutional Autoencoders (CAE) and Hybrid Quantum Autoencoders (HQAE) easily capture the structural variance at a latent space of 8 qubits on a single sensor and yield highly accurate reconstructions with a mean squared error of approximately 0.008. A fundamental bottleneck emerges when enforcing Noisy Intermediate-Scale Quantum (NISQ) capacity constraints. Aggressively compressing the latent space to just 2 qubits forces isolated single-sensor models to fail. Neither the classical nor the quantum architecture can effectively separate low-amplitude anomalies from standard reconstruction noise without a broader spatial context. This limitation, called “Single-Sensor Spatial Blindness” prevents reliable incipient damage detection. This barrier is overcome by expanding the architecture into a 6-sensor Siamese convolutional graph. It fuses spatial data from all six sensors while strictly maintaining the two-qubit bottleneck for each specific sensor. This setup allows the model to ancho…
subject: Preprints
  topic: section
subject: Bridge Health Monitoring
  topic: keywords
subject: Quantum Machine Learning
  topic: keywords
subject: Physics-Informed Neural Networks
  topic: keywords
subject: Anomaly Detection
  topic: keywords
subject: Structural Health Monitoring
  topic: keywords
subject: Autoencoders
  topic: keywords
subject: Multi-sensor Spatial Fusion
  topic: keywords
subject: Civil Engineering
  topic: disciplines
subject: Structural Engineering
  topic: disciplines
subject: Computer Science
  topic: disciplines
subject: Artificial Intelligence (AI)
  topic: disciplines
creator: Yesha Pandya
creator: S N Pandya
creator: N K Solanki
rights: Copyright (c) 2026 Yesha Pandya, S N Pandya, Dr. N K Solanki https://creativecommons.org/licenses/by/4.0
date: 2026-08-10
publication date: 2026-08-10
doi: 10.31224/7910

Edge AI-Driven Targeted Fertilizer Dispensing System for Mid-Sized Oil Palm Plantations Using Sensor Fusion
type: item
description: Nutrient management in commercial oil palm plantations presents a significant logistical challenge. Manual fertilizer application is labor-intensive and inefficient, while conventional tractor-mounted broadcast spreaders lead to substantial material wastage. These standard machines dispense fertilizer in a 360-degree pattern, causing much of the nutrient load to fall in inter-row spaces where it encourages weed growth rather than crop development. To address these inefficiencies for mid-sized operations, this paper proposes a low-cost, automated fertilizer dispensing system utilizing Edge AI and sensor fusion [4]. The architecture incorporates a Raspberry Pi 4B integrated with an HC-SR04 ultrasonic sensor for proximity measurement and a Pi Camera executing a lightweight YOLOv8 object detection model for real-time oil palm trunk identification [1]. Upon detection of a tree within a 2.5-meter threshold, the system activates a 12V linear actuator to open a targeted chute, delivering a precise dose of granular fertilizer directly to the weeded root basin. The design further includes a mechanical agitator within the hopper to prevent clumping of hygroscopic fertilizers. Initial benchtop evaluations indicate that affordable edge computing devices can achieve the requisite low-latency performance for precision agricultural applications. This system offers a scalable bridge between manual labor and high-cost commercial spreaders, significantly reducing fertilizer waste and operational overhead.
subject: Preprints
  topic: section
subject: Edge AI
  topic: keywords
subject: Sensor Fusion
  topic: keywords
subject: Precision Agriculture
  topic: keywords
subject: Oil Palm
  topic: keywords
subject: YOLOv8
  topic: keywords
subject: Raspberry Pi
  topic: keywords
subject: Agricultural engineering
  topic: disciplines
subject: Artificial Intelligence
  topic: disciplines
subject: Computer Engineering
  topic: disciplines
subject: Embedded Systems
  topic: disciplines
creator: Akhil Kommineni
rights: Copyright (c) 2026 Akhil Kommineni https://creativecommons.org/licenses/by/4.0
date: 2026-08-10
publication date: 2026-08-10
doi: 10.31224/7908