Engineering

Abstract: Conventional valve-controlled hydraulic excavator boom drive systems suffer from low energy conversion efficiency and severe throttling losses. To address this issue, this paper proposes a pump-controlled digital hydraulic drive system based on a Direct Energy Recovery Digital Pump (DERDP). The DERDP integrates hydraulic pumping and boom potential energy recovery within a single unit, enabling both energy recuperation and precise flow regulation. An AMESim simulation model of the system is developed and validated against experimental measurements from a dedicated hardware-in-the-loop test bench. Using the validated model, the operational characteristics are investigated under varying boom load pressures, pump displacement fractions, and motor displacement fractions; the drive and energy recovery efficiencies are systematically evaluated across different operating conditions. Simulation results show that the boom energy recovery efficiency reaches 50%–60%. These findings offer practical guidance for implementing digital hydraulic solutions in construction machinery.

Abstract: The current pattern of energy utilization relies primarily on fossil fuels, and countries around the world are faced with the dual pressures of resource scarcity and environmental pollution. The development of series-connected hydraulic hybrid vehicles represents one of the key approaches to reducing energy consumption and emissions in the automotive industry today. In this paper, aiming at a certain type of series-connected hydraulic hybrid vehicle, the models are developed for the vehicle’s power and transmission systems as well as its driving dynamics, and also a forward simulation model is created for the entire vehicle using Matlab/Simulink. An energy management strategy based on rules for engine multi-point control is proposed. The simulation results show that, compared with conventional vehicles before any modifications, this control strategy improves the fuel efficiency of the hydraulic hybrid vehicle by 26.46%. In comparison with an energy management strategy based on rule-based engine single-point control, it increases the vehicle’s fuel efficiency by 8.48%. The study finds that, for series-connected hydraulic hybrid vehicles, using the coordinated operation of the engine and the accumulator instead of relying solely on the accumulator for propulsion not only eliminates unnecessary engine idling but also helps to improve fuel efficiency.

Abstract: The diversity of modern structural glasses is immense, and their mechanical properties vary significantly. Reliable evaluation of glass fracture toughness enables the rational design of structural elements, accurate prediction of their service life, and guaranteed operational safety. This study introduces a novel specimen configuration for determining the static fracture toughness of glass. The specimen design incorporates a stabilizing zone, which reduces its sensitivity to loading device stiffness and ensures straight crack propagation. Specimen preparation is simple and requires no specialized, expensive equipment. Utilizing this approach, static fracture toughness testing of glass can be performed on a standard tensile testing machine. This specimen configuration enables the analysis of crack deceleration and arrest stages. At these stages, the crack tip is fully formed, and the crack front exhibits a natural, rectilinear profile. Consequently, the quality of initial crack preparation in the specimen becomes non-critical. The application of numerical simulation in experimental data processing yielded the dependence of the critical stress intensity factor on the crack propagation velocity. The developed specimen was successfully tested on silicate glass. The advantages of the proposed approach are demonstrated by comparing the results with data obtained using a traditional compact tension specimen.

Abstract: Infrared thermography provides non-contact access to spatially resolved wall-temperature information, but large flow-boiling archives require traceable separation of physically meaningful variations from measurement artefacts. This study develops a physics-guided workflow for quality assessment of longitudinal infrared temperature profiles extracted from the central line of an externally observed heated foil in rectangular minichannels. The frozen dataset comprised 143,821 complete profiles, 35,666,447 spatial points, 447 source files, and 20 grid families. Leakage-safe source-file-level partitioning was used. Controlled evaluation covered eight local synthetic anomaly morphologies at three intensities and a separate global-offset challenge. A Random Forest using 64 engineered profile descriptors was compared with a five-channel masked residual one-dimensional convolutional neural network operating directly on complete profiles. On the locked test set, the Random Forest achieved an area under the precision-recall curve of 0.915, sensitivity of 0.731, and false-positive rate of 0.082, compared with 0.871, 0.452, and 0.063 for the neural model. Both models deteriorated under external grid-family transfer and remained near chance for uniform temperature offsets. The Random Forest is retained as the preferred supervised benchmark; geometry and grid-family transfer remain the principal unresolved limitation.

Abstract: The curing state of polyolefin elastomer (POE) encapsulants affects the mechanical interaction between constituent layers of laminated photovoltaic (PV) structures and is therefore relevant to their manufacturing quality and long-term structural performance. Gel content (GC), commonly used as an indicator of encapsulant crosslinking, is conventionally determined using destructive laboratory procedures. This study investigates the feasibility of vibration-based modal characterization as a non-destructive approach for distinguishing different POE curing states in simplified glass–POE–glass laminate specimens relevant to photovoltaic module structures. Specimens with POE gel contents of 25%, 35%, 49%, 68%, and 75% were experimentally investigated. Modal parameters were identified from acceleration responses using Frequency Domain Decomposition (FDD) and Enhanced Frequency Domain Decomposition (EFDD), and the first six vibration modes were evaluated. The results revealed a measurable but non-monotonic dependence of natural frequency on gel content. For most modes, the frequencies decreased as GC increased from 25% to approximately 68%, followed by a partial recovery at 75% GC. Higher-order modes exhibited larger absolute frequency variations than the first global bending mode, indicating greater sensitivity to changes in the effective mechanical state of the POE interlayer. Finite element analysis supported the correspondence between the experimentally identified and numerically predicted modal characteristics, while a calibrated partial-composite-action model provided a structural interpretation of incomplete shear coupling between the glass layers. The results demonstrate the potential of modal characterization as a rapid and non-destructive screening approach for differentiating POE curing states, while quantitative prediction of unknown gel content requires further validation using larger independent datasets.

Abstract: This work introduces PCREM, a Principal Component Analysis/Artificial Neural Network-guided methodology for identifying candidate reduced ethanol-combustion mechanism topologies from high-fidelity two-dimensional OpenFOAM pool-fire simulations. The high-fidelity database is generated using The San Diego Mechanism, while the reduced-state analysis is organized around the modified Millán-Merino retained-species set containing 17 chemical species, including dynamically retained CH₃CHOH. Principal Component Analysis (PCA) is applied to the pool-fire thermochemical state, and the first 10 principal components (PCs) are retained, capturing 99.9390% of the cumulative variance and yielding reconstruction errors of approximately 2% for the selected thermochemical scalars. Artificial neural networks (ANN) are then trained to reconstruct temperature and species mass fractions from the retained principal components, with validation losses of 3.4716e-06 for temperature, 2.0333E-06 for major species (avg of CO₂, H₂O, C₂H₅OH), and 2.4943E-6 for selected radicals/intermediates (avg of CH₃, CO, H). A PCA-ANN-based sensitivity and species-ranking framework is subsequently developed to quantify the influence of each retained thermochemical scalar on key quantities of interest, including temperature, fuel, O₂, CO₂, H₂O, CO, and principal-component source terms. Using unity-weighted quantities of interest, the cumulative species-importance analysis indicates that the top 13, 15, and 16 species retain approximately 91.91%, 97.83%, and 99.40% of the total importance, respectively. Based on these thresholds, three candidate reduced mechanism topologies are proposed: PCREM-16, a conservative candidate that removes only CH₃ CH₂O; PCREM-15, an intermediate candidate that removes CH₃CH₂O and CH₃CHOH; and PCREM-13, an aggressive candidate that additionally removes HO₂ and C₂H₂. Reaction-consistency analysis is used to identify which pathways remain directly closed and which require ANN reconstruction, QSS treatment, or future reduced-rate re-derivation.The proposed PCREM framework is not intended as an arbitrary truncation of the Millán-Merino mechanism. Rather, it provides a data-informed, pool-fire-specific, a priori methodology for identifying compact candidate reduced mechanisms suitable for future ANN-closed principal-component transport simulations. The results establish the foundation for subsequent a posteriori OpenFOAM implementation and validation of PCREM-16, PCREM-15, and PCREM-13.

Abstract: Particle–fluid flow in fluid catalytic cracking (FCC) standpipes depends on solids throughput, aeration, and valve throttling, which can redistribute pressure loading. This study combined a cold-flow experiment, an Eulerian–Eulerian gas–solid model, and structural finite-element analyses for a 150 mm regenerated-catalyst standpipe with a bend and butterfly valve at 30% opening. Sixteen cases combined solids mass flow rates of 5–20 kg s−1 and aeration velocities of 0–0.42 m s−1. At four matched conditions, the model overpredicted valve-upstream pressure (mean bias error, 0.802 kPa; root-mean-square error, 0.869 kPa; mean absolute percentage error, 32.5%) but reproduced the normalized response (r = 0.976; R²1:1 = 0.907; normalized root-mean-square error = 0.115). At 5 kg s−1, aeration decreased the valve-upstream-to-inlet pressure difference by 36.8% but increased the valve-upstream-to-outlet difference by 87.3%. At 10 kg s−1, the former reached a discrete minimum at 0.28 m s−1. At 15–20 kg s−1, both differences increased as valve restriction dominated. The first six natural frequencies were 22.766–158.390 Hz, and the bend–transition–valve assembly was structurally sensitive. These results identify operating-dependent pressure-load redistribution and priority monitoring locations for this standpipe geometry.

Abstract: Diabetic Foot Ulcers (DFUs) pose a serious health risk to people with diabetes, with a high risk of recurrence following the first DFU and a risk of foot amputation or death. It greatly impacts patient quality of life and costs the NHS up to 1% of its annual budget. Over the last 20 years, work has highlighted the link between DFU formation and normal forces. More recently, work has highlighted the importance of strain/shear forces, which are inherently coupled with normal forces. While limited lab-based in-shoe systems have been produced to detect shear, they alter the shoe-foot interface and are not commercially available. Additionally, consultation with people with diabetes highlighted that they may not wear shoes around the house, leaving long periods where in-shoe solutions cannot track forces. We, therefore, present the development of a novel plantar shear measuring system, the Shear Tracking for Enhanced Prevention Sock (STEPS), an instrumented garment to provide an accessible tool for people at risk with DFU. Integrating sensors within the sock provides a solution that seamlessly integrates within the foot-shoe environment, is suitable for shoeless use, and helps mitigate adherence issues. A prototype STEPS was produced, successfully integrating printed resistive strain sensors (proxy for shear) within custom-designed socks using conductive embroidery for flexible connectivity. The strain sensor has a low profile (<0.5 mm thickness) and remains unobtrusive. Preliminary testing shows the capacity for strain measurement of 12+%, with a resolution of 0.013 Ω across a 20 Ω range, demonstrating good sensitivity over 90 cycles. Proof-of-concept testing characterised the system’s ability to measure plantar strain. A single-participant pilot study demonstrated that STEPS captures repeatable, gait-synchronised strain signals during walking, with a signal-to-noise ratio exceeding 30 dB and between-repeat correlations of up to R=0.77, supporting its potential to detect strain (as proxy for shear) during daily activity.

Abstract: This study develops a fractional boundary element framework for the numerical analysis of nonlinear three temperature behavior in functionally graded magnetic thermoelectric materials. The formulation incorporates the coupled interactions among electron, ion, and phonon temperature fields together with magnetic, electric, and mechanical effects. A boundary element discretization is combined with fractional time modeling to provide an efficient computational strategy for problems involving complex geometries and strongly coupled material behavior. The proposed approach reduces the need for extensive domain discretization and therefore offers advantages in computational storage and solution efficiency. Numerical investigations demonstrate that the fractional order and material gradation significantly influence the magnitude and spatial distribution of thermal stresses. The computed results are also compared with established numerical approaches for representative limiting cases, showing close agreement and supporting the reliability of the proposed formulation. The developed methodology provides an effective computational tool for investigating coupled thermal, electromagnetic, and mechanical responses in advanced functionally graded thermoelectric structures.

Abstract: Post-harvest peeling of yam tubers is labor-intensive and can cause substantial edible-matter loss, particularly when tubers have irregular geometries. This study developed and evaluated an adaptive spring-loaded peeling machine designed to follow local yam surface profiles during processing. The machine combines a reciprocating cutting head, independently compliant spring-loaded knives, a two-chuck holding arrangement, and controlled angular indexing. It was designed for tubers 50–200 mm in diameter and 100–600 mm in length, with a target capacity of 240–300 kg h⁻¹. Engineering development included cutting-force analysis, power-transmission design, spring-rate selection, structural verification, prototype fabrication, and performance testing using ten dry yam tubers. Peeling efficiency ranged from 89.9% to 99.9% (mean 94.65±3.61 %), peeling loss ranged from 2.67% to 5.91% (mean 3.92±0.98 %), and peeling rate ranged from 41.76 to 51.92 mm s⁻¹ (mean 44.94±3.04 mm s⁻¹). The estimated machine capacity was approximately 270 kg h⁻¹. Relative to previously reported yam peelers, the prototype combined high peel removal with comparatively low edible-matter loss. The results demonstrate the potential of localized mechanical compliance and controlled indexing to improve small- and medium-scale yam processing, while replicated trials are still required to establish performance across cultivars, moisture conditions, and operating settings.

Abstract: Intelligent seedbed preparation requires more than an optimized soil-engaging component: field condition must be diagnosed, a controllable setting must be adjusted, and the resulting soil zone must be verified. This critical review synthesizes 133 sources across soil mechanics, component design, numerical modeling, field validation, and sensing-control research for water-limited cropping systems. Evidence was compared as bounded within-study contrasts rather than pooled effects because outcome definitions, soils, operating regimes, and validation scales differ. Four recurring conflicts organize the synthesis: fracture versus draft, tilth versus evaporative exposure, residue retention versus blockage, and immediate loosening versus persistence. Reported examples include an increase in the <50-mm aggregate fraction from 76.1% to 88.0%, a study-specific fragmentation index increase from 83.0% to 94.54%, a 43–47% reduction in penetration resistance after geometry-optimized loosening, and rainfall-dependent water-use-efficiency gains of 6.0–11.7% after subsoiling. These values are retained as study-specific anchors, not universal settings. The proposed framework adds value by linking four decision stages—field diagnosis, component design, controlled operation, and post-pass verification—while explicitly separating conventional optimization, monitored operation, and closed-loop intelligent control.

Abstract: Embedding a trained sheet-metal localisation surrogate inside a finite element (FEM) solver requires consistent predictions irrespective of the solver's strain-increment count, which is difficult to control in non-linear explicit codes. We re-implement in Fortran a trained recurrent neural network (RNN) damage criterion, previously validated only in Python/TensorFlow, and embed it as a live fracture criterion inside an Abaqus/Explicit user material subroutine (VUMAT). Two architectures are compared: a SimpleRNN and the proposed Consistent RNN (ConsRNN), whose transition function is designed so that predictions converge under path refinement rather than drifting with the increment count. Both are trained on bilinear strain paths and evaluated under varying discretisations and nonlinear histories. ConsRNN converges under refinement, at a substantial fixed-resolution accuracy cost on multilinear paths, whereas SimpleRNN predictions drift, disqualifying it for embedding. Deployed at structural scale, the embedded ConsRNN governs element deletion in a clamped steel plate and reaches the same peak force and displacement as an established two-parameter fracture criterion, an agreement expected by construction, with responses diverging only on the post-peak softening branch. The results establish discretisation consistency as the decisive property for embedding recurrent surrogates, and report, to the best of our knowledge, the first such embedding of a customised, non-standard-transition recurrent cell.

Abstract: Wind-turbine blades and hydrofoil sailcraft operate through the same fundamental inter-action between free-stream wind and system motion. For a horizontal-axis wind turbine (HAWT), aerodynamic lift is resolved into a tangential force that produces rotor torque; correspondingly, in sailing, the forward component of sail lift provides the driving force that propels the craft. This paper develops a comparative apparent-wind framework for these rotating and translating aerodynamic systems. Velocity and force-vector analysis re-lates apparent-wind velocity, apparent-wind angle, angle of attack (AoA), lift-to-drag ratio (L/D), and useful-force production. For hydrofoil sailing, a force balance gives the speed ra-tio U/V = (L/D) sin θ − cos θ – K, where U is craft speed, V is true-wind speed, θ is the true-wind angle relative to the course, and K represents normalized aerodynamic and hy-drodynamic losses, and the associated velocity made good, VMG = U cos θ. For vertical-axis wind turbines (VAWTs), the corresponding relative-wind angle varies cyclically with blade azimuth and tip-speed ratio, requiring rapid pitch adjustment to control AoA, dynamic stall, torque, and fatigue loading. Sail trim performs an analogous function by adjusting sail angle, twist, and camber to maintain favorable AoA and L/D, although its objective is maximum speed or VMG rather than maximum power coefficient. The comparison shows that apparent-wind velocity and angle provide a common basis for understanding tangen-tial-force generation, pitch or trim control, and system-level aerodynamic optimization. The results show that sailing faster than the true wind arises from the combined high lift-to-drag performance of the sail and the low-drag lift and lateral resistance provided by the hydrofoil. Finally, the potential for apparent-wind power generation aboard a high-performance sailing craft, scaling approximately as ½ ρ Asail V³ (L/D)², is also explored.

Abstract: This paper gives a numerical analysis of MHD hybrid nanofluid flow through a stretching sheet in the presence of electric and rotation effects. The objectives of the research include investigating the effects of the mass flow rate of the hybrid nanofluid, the magnetic field, and the electrical as well as rotational forces on the flow velocity, temperature distribution, and thermal conductivity of the system. Thus, the continuity, momentum and energy equations are obtained, and then transformed using similarity variables. A Finite Difference Method (FDM) is augmented with the shooting method to solve the resulting ODEs of the mathematical model. Parameters consist of the Hartmann number, rotation parameter, electric field strength, nanoparticle volume fraction; the fluid flow and thermal characteristics are explored in the study. From the performed analysis, it can be concluded that the magnetic field decreases the fluid velocity, while the electric field increases the value of velocity and heat transfer rate. Rotational effects bring about very large changes in the structure of the boundary layer and the temperature profiles. These results are significant for heat exchange and flow control in numerous engineering applications containing magnet and electric current. Examples of practical applications include enhanced cooling systems like air conditioning, heat pumps, evaporative cooling, and rotating equipment such as pumps, turbines, gas compressors, blowers, gearboxes, and different types of fans among others.

Abstract: Triply periodic minimal surface (TPMS) shell lattices combine high mechanical efficiency with an open-cell topology, yet their stiffness and strength remain well below theoretical upper bounds. This study develops a stress-feedback-driven continuous variable-thickness method for simultaneous stiffness and strength enhancement of TPMS shell lattices. Finite-element analyses provide nodal von Mises stresses that are mapped into relaxed thickness updates; spatial filtering and target-volume normalization preserve a smooth thickness field and constant material volume. The method thickens highly loaded regions and thins underutilized regions while keeping the mid-surface geometry unchanged. Across a relative density (RD) range of 5%–20% and a maximum-to-minimum thickness-ratio limit of 100, the effective Young's modulus and yield strength of N14 shell lattices increase by up to 46.39% and 58.82%, respectively. With the thickness ratio restricted to 10, the corresponding maximum gains remain 30.90% and 46.75%. The improvement results from transferring materials toward existing load paths and increasing the fraction of the shell that participates effectively in load transfer. The proposed method provides a numerically efficient route for designing high-performance lightweight shell lattices and identifies moderate-contrast thickness fields for subsequent manufacturing-oriented development.

Abstract: Additive Manufacturing (AM) has revolutionized modern production. However, its integration with conventional or subtractive manufacturing is still underexplored. Therefore, this study investigates the machinability of 316L stainless steel (SS) produced with rolling or Powder Bed Fusion – Laser Beam (PBF-LB) technologies under dry turning. Compared with rolled specimens, the AM samples exhibit greater variability in machining performance and higher sensitivity to cutting conditions. It is demonstrated from the results that sample with the highest feed shows the least favorable machinability. In particular, the PBF-LB specimen machined at the highest feed rate exhibits the highest cutting force and tool vibration, produces the roughest machined surface, and generates the highest cutting-zone temperature. It also shows relatively high flank wear and has the shortest tool life. Although the measured temperatures remain well below the melting point of 316L SS, optical microscopy reveals pronounced built-up edge formation, indicating that adhesive wear rather than thermal melting is the dominant wear mechanism. These findings demonstrate that rolled 316L provides more stable machining behavior and offer practical guidance for optimizing the dry turning of AM 316L SS.

Abstract: Flexible manufacturing systems are prone to deadlocks caused by shared resource competition, which may interrupt production flow and reduce system reliability. This study proposes a Random Forest-Assisted Critical Deadlock Discovery and Recovery Recommendation Method (RF-GCAM) for flexible manufacturing systems modeled by S³PR Petri nets. The proposed framework integrates reachability graph generation, representative critical deadlock discovery, Random Forest-based deadlock classification, feature importance analysis, and recovery recommendation. In the case study, 364 reachable markings were generated, among which 4 deadlock states were identified. To reduce redundant analysis, 2 representative critical deadlocks were selected for recovery evaluation. The Random Forest classifier achieved an accuracy of 98.86%, precision of 94.12%, recall of 100.00%, and F1-score of 96.97%. Feature importance analysis further identified influential Petri net places associated with deadlock classification, including p₁₄, p₁₀, p₀, and p₁₇. Based on the nearest legal state search and feature importance ranking, the proposed method recommended p0 and p10 as primary recovery places for CD1 and CD2, respectively. The results show that RF-GCAM can provide accurate, interpretable, and deadlock-specific recovery recommendations for flexible manufacturing systems.

Abstract: The increasing generation of heavy petroleum residues has created significant environmental and energy-related challenges, while simultaneously providing an abundant potential feedstock for thermochemical energy conversion. Gasification offers a promising pathway for converting carbon-rich petroleum residues into a combustible synthesis gas (syngas) containing hydrogen (H₂), carbon monoxide (CO), and light hydrocarbons. In the present study, the gasification characteristics of heavy petroleum residues in an entrained-flow reactor were investigated using a combination of thermodynamic analysis and detailed chemical-kinetic modeling in CHEMKIN. An equilibrium-based approach was initially employed to establish a fundamental understanding of the pyrolysis and gasification behavior of the reference fuel. Subsequently, a kinetic model was developed in CHEMKIN to investigate the effects of key operating parameters on product-gas composition and energy content. Parametric analyses were performed to evaluate the influence of temperature, fuel moisture content, and gasifying-agent conditions on the formation of major gaseous products. The results demonstrate that operating temperature plays a critical role in determining the product distribution and significantly affects the formation of combustible species. Changes in fuel moisture content also modify the reaction environment and consequently influence the composition and energetic characteristics of the produced gas. The gasification stage was further investigated by examining the effects of different gasifying-agent conditions on the formation of H₂, CO, and CH₄. The results demonstrate a strong dependence of syngas composition on the operating conditions, reflecting the competition among pyrolysis, oxidation, water–gas, water–gas shift, methanation, and related gas-phase reactions. Based on the parametric analysis, an operating condition providing a favorable balance among hydrogen, carbon monoxide, and methane production was identified. The results demonstrate the capability of CHEMKIN-based kinetic modeling to provide insight into the governing chemical mechanisms of heavy petroleum residue conversion and to identify suitable operating conditions for syngas production.

Abstract: As the core interception component of flexible rockfall barriers, the accurate characterization of the mechanical behavior of metal ring nets is essential for the safety assessment of the whole system. To overcome the limitations of existing computational models in reflecting the large-deformation states of the nets and the activation of energy dissipators, systematic uniaxial tension tests and puncture tests were first carried out on five specifications of ring nets (R8 to R19, 30 specimens in total). The results reveal a two-stage deformation feature (an initial low-force tensioning stage followed by a stiffness-hardening rapid-rise stage) and a parallel-superposition load-carrying mechanism under both loading cases. The experimental data were then normalized by dividing the force by the number of steel wires and non-dimensionalizing the dis-placement, on the basis of which a unified piecewise two-stage constitutive model, consisting of a linear tensioning segment and a power-hardening segment, was estab-lished to describe the response up to the peak point; the tensile and puncture cases share the same model form and are distinguished only by different parameters (fitting coefficient of determination R2 not lower than 0.97, with mean values of 0.98 and 0.983, respectively). A full-scale numerical model of the overall structure was subsequently established using LS-DYNA, in which the two side spans adopt the tensile constitutive model and the middle impact span adopts the puncture constitutive model. The model was verified against a 1500 kJ full-scale impact test. The computed time histories of the support-rope forces, the activation states of the energy dissipators (pressure-relief rings), the maximum interception deformation (computed 8.23 m versus measured 8.8 m, with a relative error of about 6.5%) and the energy-dissipation distribution of the pressure-relief rings (average relative error of about 5.2%) all agreed well with the experimental results. The proposed two-stage computational model can therefore accurately reflect the force and deformation states of the ring nets in the actual structure and correctly describe the transmission of the impact force and the activation of the energy dissipators, providing a reliable theoretical basis for the refined design of flexible rockfall barriers.

Abstract: Milling cutters are subjected to variable mechanical loads during machining, which can affect their structural integrity and thermal condition. This study aims to evaluate the effect of external cutting force on the stress–strain and thermal responses of a mushroom-shaped slot milling cutter. A three-dimensional model of a six-tooth cutter with a 14 mm cutting diameter and an 8 mm shank diameter was developed in SolidWorks Simulation. The cutter was modeled using AISI M2 high-speed steel, while an AISI 4340 steel workpiece was included to represent the cutter–workpiece contact. Static analyses were performed under forces of 500, 750, and 1000 N, and the von Mises stress, resultant displacement, and equivalent strain were determined. Thermal analyses were additionally conducted using corresponding heat inputs. The maximum von Mises stresses were 158.8, 238.4, and 326.9 MPa, while the corresponding displacements were 0.04529, 0.05818, and 0.09097 mm for 500, 750, and 1000 N, respectively. The maximum temperatures increased from 380.15 to 561.95 and 748.85 °C with increasing load. The results demonstrate a systematic increase in both mechanical and thermal responses with increasing cutting force, providing a basis for identifying critical regions and assessing cutter operating conditions.