Journal of Engineering Research and Reports

Design and Implementation of a Web-Based Automatic Grading Platform for Simulink Models

Licheng Fang — 2026-10-13

Background: Simulink is widely used in control engineering education for modelling and analysing dynamic systems. However, manual assessment of Simulink assignments can be time-consuming and inconsistent, particularly when submitted models contain complex differences in blocks, ports, parameters, and signal connections. A web-based, structure-aware automatic grading platform may therefore improve grading efficiency, consistency, and the traceability of model differences.

Aims: To design and implement a Web-based automatic grading platform for Simulink model assignments in control engineering education, addressing time-consuming manual grading, difficulty in locating complex structural differences, and inconsistent grading scales.

Study Design: Software system design and controlled experimental validation.

Place and Duration of Study: Huzhou College, Huzhou, China, during the platform development and controlled validation phase.

Methodology: The platform integrates a Web interface, backend task scheduling, MATLAB/Simulink model analysis, and database management. Each submitted model is compared with an instructor-provided reference model. Structural differences in blocks, input ports, output ports, signal connections, and model-level properties are classified and converted into scores across five dimensions. Twenty-one controlled model variants (M01-M21) were each submitted twice, yielding 42 grading records.

Results: Duplicate submissions produced identical total scores and identical scores across all five dimensions for all 21 variants. Parameter modifications, port additions/deletions, connection changes, and multiple structural changes were differentiated in the corresponding dimensions. As the number of added blocks increased from 26 to 101, the total score decreased from 94.2 to 85.6. The unchanged baseline and connection-rerouting cases did not fully match theoretical expectations, indicating that the reference-model version and difference-classification rules require further calibration.

Conclusion: The platform integrates Simulink structural comparison, automatic grading, result persistence, and online querying in a repeatable and interpretable workflow, providing a practical implementation for automated assessment of model-based coursework.

Carbon-Fibre-Reinforced Carbon–Silicon Carbide Composites for Extreme Environments: A Critical Narrative Review of Processing Strategies, Interface Engineering, Oxidation Resistance and Engineering Applications

Jie Chen — 2026-10-01

Carbon-fibre-reinforced carbon–silicon carbide (C/C–SiC) and carbon-fibre-reinforced silicon carbide (C/SiC) composites occupy a distinctive position among materials for extreme environments because they combine low density, damage tolerance and thermal-shock resistance with a matrix that forms protective silica at high temperature. Their use in re-entry thermal protection, rocket propulsion and high-energy friction systems has nevertheless remained constrained by an unresolved tension between the carbon reinforcement, which is required for toughness, and its vulnerability to oxidation. This critical narrative review examines how processing strategies, interface engineering and oxidation-protection approaches interact to determine the engineering performance of these composites. Literature was identified through structured searching of multidisciplinary scholarly indexes and specialised technical repositories, supplemented by backward and forward citation tracking, and was appraised for methodological adequacy, test realism and consistency with independent evidence. The synthesis indicates that chemical vapour infiltration, polymer infiltration and pyrolysis, and liquid or gaseous silicon infiltration yield materially different phase assemblies, residual-stress states and crack networks, so that properties reported for one route cannot be transferred uncritically to another. Interphase optimisation is supported by consistent evidence that intermediate pyrolytic carbon thicknesses maximise strength and reliability, but the optimum depends on the matrix route and residual stress rather than on a universal value. Oxidation behaviour follows temperature-dependent regimes governed by reaction control, diffusion through matrix microcracks and crack sealing by silica, yet most evidence derives from short, unstressed laboratory exposures. Protective coatings and ultra-high-temperature ceramic modifications improve short-term ablation resistance, whereas evidence for long-duration, multi-cycle durability under combined mechanical, thermal and chemical loading remains limited. Friction applications show the most mature translation, while reusable hot structures remain constrained by environmental durability and manufacturing cost. The review concludes that progress now depends less on incremental compositional modification than on standardised coupled-environment testing, validated life-prediction models and process routes that control residual silicon, porosity and interphase integrity simultaneously.

Ultra-Long-Span UHPC-Filled Steel Tube Truss Arch Bridges: A Critical Review of Structural Design, Optimisation, Construction, and Stability

Gao-Kaishuai — 2026-10-12

Concrete-filled steel tube (CFST) truss arch bridges, by virtue of their large spanning capacity, low self-weight, high load-carrying efficiency and strong construction adaptability, have become one of the dominant bridge types for major crossings such as deep valleys and wide rivers, and their spans are being extended from the 500 m scale to the 700 m scale and even to the kilometre scale. The continuous increase in span dramatically amplifies the self-weight effect of the arch ribs and significantly raises the proportion of dead-load internal forces, so that reducing the self-weight of the arch ribs has consequently become key to extending the span limit. Ultra-high performance concrete (UHPC) possesses a compressive strength of over 150 MPa, an elastic modulus of no less than 40 GPa and excellent durability. Using it as the core concrete in steel tubes to form ultra-high performance CFST members provides a material-level solution for improving the load-carrying efficiency of sections and achieving structural lightweighting. Focusing on the topic of “optimal design of ultra-long-span ultra-high performance CFST truss arch bridges”, this paper systematically reviews the relevant research status in China and abroad: first, research on the development history, structural type selection, construction technology and structural optimisation of ultra-long-span CFST truss arch bridges; second, research on the material properties and member mechanical behaviour of ultra-high performance CFST, on hollow sandwich and composite section forms, and on the trial design of steel-UHPC composite truss arches; third, research on key detailing parameters of CFST arch bridges such as the reasonable arch axis, global and local stability, and lateral bracing layout. On this basis, it is pointed out that existing research remains deficient in four aspects, namely the systematic comparison and selection of the span limit and section forms at the 800 m scale, the coupling mechanism between UHPC and steel tubes as well as truss structures, the dual-nonlinear stability analysis of ultra-long-span bridges, and the detailing measures for prefabricated construction; accordingly, the research scope of this paper is defined as the trial design, static parameter optimisation and stability analysis of an 800 m-scale ultra-high performance CFST truss arch bridge. This review can provide a fundamental reference for further research on ultra-long-span CFST truss arch bridges.

The Privacy-Personalization Paradox in AI-Driven Customer Experience Analytics: A Trust-Centred Integrative Review and Responsible Personalization Framework

Rahmat Kofoworola Sanusi — 2026-10-16

Artificial intelligence increasingly supports personalised customer experiences through predictive analytics, recommender systems, behavioural profiling and conversational interfaces. However, the data collection and inference required for personalisation can also heighten perceptions of surveillance, vulnerability and loss of control. This integrative conceptual review examines how AI-enabled personalisation, perceived privacy risk and consumer trust interact within customer experience analytics. The synthesis integrates privacy calculus, social exchange, psychological reactance and signalling perspectives to explain how consumers evaluate personalisation value against privacy-related costs. A trust-centred framework is developed in which personalisation intensity, data sensitivity, algorithmic inference and recommendation relevance jointly shape perceived value and privacy risk, with consumer trust linking these evaluations to engagement, disclosure willingness, satisfaction, loyalty and continued use. The review also distinguishes actual data practices from perceived privacy intrusion and identifies contextual conditions that may alter this balance. The review further proposes a context-dependent nonlinear relationship between personalisation intensity and trust: moderate personalisation may strengthen trust when relevance and value are proportionate to data use, whereas more intensive personalisation may reduce trust when intrusion, surveillance or loss of autonomy becomes salient. Responsible personalisation is therefore framed around proportionate data use, meaningful transparency, consumer control and privacy-by-design. The framework and proposed personalisation threshold remain conceptual and require empirical testing across AI applications, cultural settings and regulatory environments.

Study on the Influence of Leakage on the Mechanical Performance of High-pressure Water-conveyance Shield Tunnels

Jianing Wang — 2026-10-18

High-pressure water-conveyance shield tunnels operate at the intersection of pressurised hydraulic infrastructure, discontinuous segmental structures and deformable ground. Leakage can be a consequence of joint opening, cracking or interface separation, yet it may also alter pore-water pressure, effective ground support, structural forces and the subsequent progression of damage. This critical narrative review evaluates the reciprocal relationship between leakage and mechanical performance, distinguishing outward loss of conveyed water from inward groundwater ingress and from redistribution of pressure within composite linings. Peer-reviewed experimental, field, analytical and numerical investigations were evaluated thematically, with particular attention to evidence directly obtained from pressurised water-conveyance tunnels and to transferability from underwater transport and drainage tunnels. The synthesis identifies joint deformation and gasket contact conditions as relatively well-supported immediate controls of watertightness, whereas time-dependent soil–lining feedback and leakage-induced loss of global capacity remain less conclusively validated for internally pressurised tunnels. Full-scale tests indicate that internal pressure can reduce compressive ring forces, promote joint opening and redistribute loads among concrete segments, inner linings, steel shells and surrounding ground. Composite-lining experiments also show that cracking of self-compacting or reinforced concrete does not necessarily constitute complete hydraulic failure, provided alternative barriers remain intact. Conversely, the benefits of double gaskets, prestressing and fibre reinforcement depend on deformation compatibility and failure mode; improved strength alone cannot establish watertightness. An integrated performance framework is advanced in which hydraulic gradient, leakage pathway, joint and lining deformation, permeability evolution, external restraint and time-dependent degradation are assessed together. Priority needs are bidirectional pressure testing, repeated-load and ageing validation, monitoring capable of identifying leakage direction and location, and independently calibrated three-dimensional hydro-mechanical models. Design and maintenance should use explicit serviceability and ultimate limit states rather than treating a single leakage threshold as a universal measure of structural safety.

Crude Oil Price and Nigeria's Economy: An Empirical Test of the Resource Curse, 2010–2023

Edeh Mark Bekweri — 2026-09-30

Background and Aims: Nigeria’s substantial dependence on crude petroleum for export earnings and public revenue makes its economy particularly exposed to movements in global oil prices. This study examined whether Brent crude oil price is significantly associated with Nigeria’s gross domestic product (GDP) after accounting for exchange-rate and inflation dynamics, and to assess whether the evidence is consistent with a resource-curse interpretation.

Study Design: An ex postfacto annual time-series design was used.

Place and Duration of Study: Nigeria; national annual data for 2010–2023, analysed in 2026.

Methodology: Fourteen annual observations were assembled from the Federal Reserve Economic Data repository and the Central Bank of Nigeria. An ordinary least squares regression was estimated on log-transformed GDP and Brent crude oil price, with the exchange rate and inflation rate as controls. A real-GDP specification was estimated as a robustness check.

Results: The primary model was statistically significant, F(3, 10) = 30.35, p < .001, R² = .90. Brent crude oil price was not a significant predictor of GDP (B = −0.02, p = .899), whereas the exchange rate was significant (p < .001). Brent price also remained non-significant in the real-GDP robustness model (p = .463).

Conclusion: The short annual sample provides no evidence of a significant contemporaneous association between Brent crude oil price and GDP after the controls were included. The pattern is consistent with, but does not establish, an exchange-rate-mediated resource-curse mechanism.

Voltage Stability Improvement of Nigerian 330 KV Network in South Western Region Using UPFC and ANN

Ekemini E. Udofia — 2026-09-30

Voltage instability remains a critical operational concern in the Nigerian 330 kV transmission network, particularly under disturbances and increasing loading. This study evaluated voltage-stability improvement in selected substations within the south-western region using a unified power flow controller (UPFC) and an artificial neural network (ANN). A five-bus representation comprising Egbin GS, Okearo TS, Aja TS, Akangba TS, and Ikeja West TS was modelled in the Power System Analysis Toolbox (PSAT), while MATLAB/Simulink was used for the analysis of power-flow and dynamic-voltage responses. Newton-Raphson power-flow analysis was applied to determine line active power losses and identify the controller-placement location. Line 3, connecting bus 1 (Egbin GS) to bus 5 (Ikeja West TS), recorded the highest active power loss of 0.1084 pu and was selected for UPFC and ANN allocation. Following implementation, the bus voltage profiles were improved to the stated operating range of 0.95–1.05 pu. The dynamic responses also showed reduced oscillations and shorter settling behaviour under both control approaches. Using the voltage stability index reported in the study, the ANN achieved 97%, whereas the UPFC achieved 93%. Under the specific simulation conditions considered, the ANN therefore produced the higher reported VSI and a smoother voltage response. The findings are limited to the model configuration and operating conditions evaluated in this study.

Development and Evaluation of Recycled Plastic–sand Tiles for Sustainable Construction Applications

Thin Thin Hlaing — 2026-10-01

Aims: This study developed construction tiles from recycled polyethylene (PE) waste and sand and evaluated the effects of PE proportion and heating and mixing method on tile properties.

Study Design: A quantitative, laboratory-based experimental design was used.

Place and Duration of Study: The study was conducted at the Chemical Technology Research Center, Department of Research and Innovation, Yangon, Myanmar, between April 2023 and March 2024.

Methodology: Recycled PE waste was cleaned, dried, mechanically cut, and sieved to approximately 500 µm. Sand was dried and sieved before use. Four PE proportions, 25%, 30%, 33.33%, and 35% based on sand weight, and three heating and mixing methods were investigated. The produced tiles were evaluated for water absorption, density, compressive strength, flexural strength, and tensile strength, with measurements conducted in triplicate.

Results: In the PE-proportion comparison, the 33.33% PE tile recorded the highest compressive strength (8.27 N/mm²), flexural strength (2.01 N/mm²), and tensile strength (2220 psi). In the processing-method comparison, Method 3 produced the highest compressive strength (15.97 N/mm²) and flexural strength (2.80 N/mm²), while Method 2 produced the highest tensile strength (3040 psi). The Method 3 tile had a density of 2.55 g/cm³ and water absorption of 3.4%.

Conclusion: The 33.33% PE formulation processed using Method 3 provided the most favourable overall performance among the investigated conditions and represents a potential route for value-added use of recycled PE waste in construction tiles.

Analysis of Concrete Formwork Inspection and Distance Measurement based on YOLOv5

Gu Shuhao — 2026-10-01

The joint quality of prefabricated buildings directly determines structural performance. To realise the automatic positioning of concrete pouring equipment for small-size joints in prefabricated buildings, this paper develops an intelligent positioning system integrating YOLOv5 object detection and binocular vision ranging. For the screw-hole detection task in prefabricated components, a custom dataset was built using 2,000 on-site images collected under various viewing angles and illumination conditions. Five models, including YOLOv5n/s/m/l/x are compared in terms of recall, precision, mAP, and box regression loss. Considering detection accuracy, hardware cost, and inference speed collectively, YOLOv5l is selected as the object detection model. Zhang’s calibration method was adopted to calibrate the binocular camera and obtain its internal and external parameters. Using the SGBM semi-global stereo-matching algorithm, the depth and 3D positions of target screw holes were calculated based on the binocular triangulation principle. Data exchange between the host computer and PLC was achieved via the Modbus TCP protocol. The 3D coordinates of targets obtained through visual recognition are transmitted to the PLC to drive the end effector to complete positioning operations. A scaled-down indoor test platform was built for verification experiments. The effect of different shooting heights on screw-hole recognition was tested to determine the optimal working height. Experimental results showed that the average recognition accuracy of screw holes was 93.4% at a working distance of 600 mm. The measurement error of the target 3D coordinates was within the allowable engineering range, and the displacement values fed back by the encoder were generally consistent with the reference values measured using a laser rangefinder. The system achieves full-process automation of screw hole recognition, binocular ranging, positioning and operation. With moderate cost and practical applicability, the proposed scheme can provide technical support for intelligent pouring equipment for joints of prefabricated buildings.

Design and Analysis of Forced Drop Hammer Hydraulic Compactor for Soft Foundation Reinforcement of Large Dike Breach

Chen Yi — 2026-10-01

This study addresses the engineering challenges of high water content, low bearing capacity, poor equipment accessibility and unsatisfactory reinforcement performance in soft foundations following large-scale dike breaches. A forced-drop-hammer hydraulic compactor is designed for emergency foundation reinforcement at dike-breach sites. Based on the geotechnical characteristics of post-breach soft soil, the overall system configuration and hydraulic-circuit scheme are determined, and a constant-pressure, low-shock hydraulic circuit for forced-drop-hammer operation is optimised. Dynamic governing equations describing the complete hammer-lifting and compaction cycle are established. The AMESim platform is used to investigate system-pressure fluctuations, dynamic response and hammer-motion stability under multiple working conditions. Comparative laboratory-scale model tests are conducted to identify an appropriate compaction-parameter range for dike-breach soft ground, and a targeted emergency construction procedure is proposed for on-site rescue applications. The simulation and laboratory-test results show that the optimised hydraulic power supply maintains stable constant-pressure output with reduced hydraulic shock and reliable cyclic compaction performance. Within the recommended parameter range, the compactness of the simulated soft foundation increases by more than 12 %, improving compaction uniformity and reinforcement quality. The findings provide support for structural design and hydraulic-parameter matching of similar compaction equipment and offer a technical reference for rapid emergency reconstruction of breached dikes.

Experimental Characterization of Motor Fault Conditions Using Vibration, Gyroscope, and Acoustic Measurements with an Arduino-Based Monitoring System

Aarosh Srivastava — 2026-10-05

Background: Electric motors are widely used in industrial and electromechanical systems, making reliable condition monitoring important for detecting mechanical abnormalities before performance deterioration occurs. However, individual fault conditions may produce different responses depending on operating speed, fault geometry, mounting conditions, and sensor modality. Low-cost multisensor platforms integrating vibration, angular-motion, and acoustic measurements therefore provide a practical approach for experimentally characterising distinct motor fault signatures.

Aims: To develop and experimentally evaluate a multisensor platform that identifies controlled motor fault conditions using vibration, angular motion, and acoustic telemetry.

Study Design: A benchtop repeated-measures experiment was conducted to test a healthy baseline and six controlled mechanical conditions across four rotational speeds.

Methodology: A 12-V geared DC motor was controlled by an Arduino Mega 2560 and monitored with an Arduino Nano 33 BLE Sense Rev2, logging telemetry at 40, 80, 100, and 130 RPM. Six fault states were evaluated: four rotor mass-distribution configurations, a 15-degree shaft misalignment, and loosened motor-fixing screws, with three replicates per fault-speed combination. Trial-level features included AC resultant acceleration RMS, Dynamic-G variability, gyroscope motion, relative acoustic RMS, and packet-loss rate.

Results: Vibration magnitude depended on mass distribution rather than total added mass. Two adjacent eccentric masses produced the strongest vibration, three masses approached the one-mass response, and four symmetrically distributed masses reduced vibration despite the greatest attached mass. Configuration effects were strongest at 100 RPM (one-way ANOVA, F = 66.90, P < .001) and 130 RPM (F = 32.69, P < .001). The 15-degree misalignment produced a directional, non-monotonic vibration response, while loosened motor mounting produced a comparatively flat vibration response consistent with altered structural coupling. Acoustic RMS correlated with speed rather than fault type; packet loss remained at 13-14% regardless of mechanical state.

Conclusion: An embedded multisensor platform reliably identifies motor fault signatures when speed-specific and multidimensional features are considered. The results also show that a mechanical fault should not be interpreted simply as an increase in overall vibration amplitude.

Experimental Investigation of the Compressive Behavior of Hybrid Fiber-Reinforced Concrete and AI-Agent-Assisted Modeling

Hanbo Zhang — 2026-10-10

Hybrid fibre reinforcement is increasingly used to improve the mechanical performance and failure behaviour of concrete by combining the complementary characteristics of different fibre types. However, the effects of different hybrid fibre combinations on compressive behaviour and mesoscale failure mechanisms, particularly when integrated with AI-assisted discrete element modelling, remain insufficiently understood. This study investigated the compressive behaviour and mesoscale failure mechanisms of concrete reinforced with steel, macro-synthetic, and polypropylene fibres, individually and in hybrid combinations, and evaluated an AI-agent-assisted PFC3D modelling workflow. Thirteen mixture groups comprising 39 cubic specimens were subjected to uniaxial compression testing. Steel-fibre concrete achieved a compressive strength of 39.7 MPa compared with 35.0 MPa for plain concrete, whereas macro-synthetic fibre concrete reached 35.7 MPa and polypropylene fibre concrete decreased to 25.0 MPa. Fibre incorporation generally changed failure from localised crack coalescence to more distributed cracking and improved post-peak specimen integrity. Three representative mixtures were modelled using PFC3D with an AI agent supporting task generation, script execution, feedback-based correction, and result recording. Simulated peak strengths of 34.2, 37.3, and 26.5 MPa for the N0, SM, and MP models, respectively, were within 5% of the corresponding experimental values. AI-agent-assisted modelling reduced the reported total modelling time from 142 to 34 min, corresponding to an efficiency improvement of 76.1%. The first-run task success rate was 61.1%, while all staged tasks were completed after correction. Repeated simulations produced low coefficients of variation for peak stress and crack number. The findings indicate that steel-macro-synthetic hybridisation provided comparatively favourable compressive performance, while the AI-assisted workflow supported efficient and reproducible discrete element modelling.

Securing Enterprise AI Supply Chains: A Framework for Model Provenance, Third-Party Risk, and Compromised AI Components

Favour Amarachi Ezeugwa — 2026-10-14

Enterprises assemble AI systems from externally sourced models, datasets, libraries, agents and serving components whose origin and integrity they cannot directly observe. This study asks how provenance assurance, third-party dependency exposure and supply-chain governance relate to the disclosed-vulnerability record of such components, and argues that this record measures security observability as much as security risk. Drawing on resource dependence, information asymmetry and signalling theory, we assemble a cross-sectional secondary dataset of 1,321 widely used open-source AI/ML components (GitHub, deps.dev, OpenSSF Scorecard, OSV, PyPI statistics, CISA KEV) and the 1,000 most-downloaded Hugging Face models, and estimate negative binomial, logistic, hurdle and zero-inflated models with robust standard errors and influence and selection diagnostics. Disclosed advisories are rare but concentrated: 8.9% of components carry one yet attract 39.4% of monthly downloads, and advisory publication rose from 54 in 2023 to 486 in the first nine months of 2026. Advisory counts rise with ecosystem reach (incidence rate ratio 2.49 per log unit of stars), release activity and, in the Scorecard subsample, detection and disclosure practices (IRR 1.48 per index point), whereas hardening and provenance controls show no negative association. Disclosure therefore tracks scrutiny and transparency rather than the absence of defects, motivating a six-pillar framework in which continuous observability, not silence, is the basis for trusting AI components. We recommend that enterprises assess AI suppliers on verifiable provenance, safe serialisation and disclosure capacity rather than on advisory counts and embed AI bills of materials and exploitation-aware monitoring in continuous engineering controls, and that standards bodies distinguish disclosure capacity from vulnerability prevalence in AI risk frameworks.

Multiscale Meteorological Drought Dynamics Using Penman-Monteith SPEI in a Humid Tropical Environment, Owerri, Nigeria

Iheukwumere P. Onyemachi — 2026-10-16

This study investigated multiscale (1-, 3-, 6-, and 12-month) meteorological drought dynamics in Owerri, southeastern Nigeria, using the Standardized Precipitation Evapotranspiration Index (SPEI) derived from FAO-56 Penman-Monteith reference evapotranspiration (PET). Monthly hydroclimatic records (1992-2022) retrieved from the Nigerian Meteorological Agency (NiMet) were analysed to evaluate climatic water balance, drought variability, temporal trends, and the influence of evapotranspiration using non-parametric and comparative statistical techniques. The three-parameter log-logistic distribution did not provide an adequate representation of the climatic water balance series for Owerri; therefore, alternative probability models were evaluated to identify the most appropriate distribution for each accumulation scale. Mean PET and climatic water balance were 109.38 mm and 85.34 mm, respectively. PET exhibited a significant decreasing trend (MK-Z = −2.525, p = 0.0116) with a change point in March 2007; climatic water balance showed no significant long-term trend. Agreement between SPEI and SPI increased with accumulation timescale, while significant differences were confined to the 1- and 3-month timescales. These findings demonstrate that atmospheric evaporative demand primarily influences short-term drought characterisation, whereas precipitation dominates longer-term drought variability. One significance of the study was to provide a station-based multiscale drought assessment for Owerri, Nigeria, in the literature. However, the major constraint of this study is its reliance on data from a single NiMet station to represent the entire Imo State.

Simulation Study on Bypass Bleed-off Synchronization Control of a Dual-cylinder Hydraulic Hoist Based on AMESim

Yuanhang Zhou — 2026-10-17

Synchronised displacement of dual hydraulic cylinders is important for the controlled operation of lifting gates, particularly when flow distribution and loading differ between actuators. This study evaluates a bypass bleed-off synchronisation arrangement for a dual-cylinder hydraulic hoist using AMESim simulation. A single proportional directional valve supplies both cylinders in parallel, while an individual proportional bleed-off valve, connected through a four-check-valve rectifier bridge, regulates the corrective flow for each cylinder. A proportional–integral–derivative controller uses the measured displacement difference to select and actuate the appropriate bleed-off valve, with separate branch gains accommodating the extension and retraction directions. The simulated model includes hydraulic components, cylinder friction, displacement measurement dynamics and the specified operating parameters. Five cases examine an uncontrolled baseline, closed-loop regulation, unequal cylinder loads, proportional-gain sensitivity and a complete extension–retraction cycle. In the reported simulations, the uncontrolled displacement difference increases to approximately 21 mm over a 2 m stroke. With the tuned controller, the steady-state synchronisation error remains within ±1.5 mm under equal loading and below 1.5 mm with a load increase of up to 30% on one cylinder. The results also show that controller tuning affects oscillatory behaviour and that correction is possible in both stroke directions. These simulation findings indicate the potential of bypass bleed-off regulation as a comparatively simple synchronisation approach for existing gate-hoist circuits. Experimental verification remains necessary before practical performance can be established.