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        <title>Frontiers in Mechanical Engineering | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/mechanical-engineering</link>
        <description>RSS Feed for Frontiers in Mechanical Engineering | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-10-25T19:54:01.954+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1987261</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1987261</link>
        <title><![CDATA[From electrode swelling to structural integration: a quantitative electro-chemo-mechanical framework for electric-vehicle batteries]]></title>
        <pubdate>2026-10-23T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Feng Li</author><author>Xiaoxi Liu</author><author>Yunda Liu</author><author>Jiayi Li</author><author>Shengnan Li</author><author>Yueyue Yu</author>
        <description><![CDATA[Electro-chemo-mechanical coupling is well established in electric-vehicle batteries, yet its translation from electrode behavior to pack- and vehicle-level performance remains difficult. This mini-review organizes the evidence around five transferable descriptors: electrode/cell swelling, contact or stack pressure, stiffness and strength, mechanical-abuse tolerance, and inactive structural mass or volume. Recent studies are examined to show how silicon-rich electrode deformation, pressure-dependent solid-state interfaces, and structural integration influence practical energy density and safety. Building on established mechanisms, we propose a mechanical penalty ledger that defines consistent accounting boundaries and connects cell-level specific energy with the mass and volume of constraint, protection, interconnection, and thermal-management components. An illustrative 60 kWh case study compares conventional, structurally optimized, and higher-specific-energy battery architectures. Under the stated hypothetical assumptions, a 12% improvement in cell-level specific energy yields only an approximately 3.3% improvement in pack-level specific energy when additional compression hardware is included. A break-even calculation identifies an illustrative maximum allowable compression-hardware mass of approximately 33.7 kg for the higher-energy configuration to outperform the conventional reference. The worked example is a sensitivity demonstration rather than experimental validation or a universal design threshold. This review therefore provides a transparent basis for evaluating when electrochemical improvements survive mechanical integration penalties, while emphasizing the need for experimentally validated load paths, ageing-conditioned safety limits, and complete component-level inventories.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1958346</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1958346</link>
        <title><![CDATA[Hypergraph-informed cascading risk control for low-carbon manufacturing: a simulation study for digital-twin development]]></title>
        <pubdate>2026-10-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Haipin Li</author><author>Jifa Lu</author>
        <description><![CDATA[Manufacturing operators must maintain production while limiting emissions when disturbances spread through shared resources. This simulation-only study examines that trade-off in a reduced-order, five-layer manufacturing network; no physical-plant calibration or live digital-twin connection is available. The prototype combines sparse hypergraph risk features, temporal damage memory and a soft actor-critic controller with carbon and tail-excess penalties. Trained policies are evaluated on four held-out synthetic networks using 50 paired disturbance seeds and three initialization seeds. The proposed controller achieves mean resilience 0.875, compared with 0.442 without intervention and 0.947 for HG-SAC. Its emissions are 24.0% lower than HG-SAC, but it exceeds the allowance in 87.5% of trajectories. Paired effect sizes, multiplicity corrections, retrained ablations and shifted-disturbance tests clarify the trade-offs and limitations. The results show a trade-off between emissions and resilience under the simulated conditions. Prospective plant calibration and shadow validation remain necessary.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1980739</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1980739</link>
        <title><![CDATA[A transformer-based correction factor for critical heat flux prediction under non-uniform axial heating]]></title>
        <pubdate>2026-10-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Reece Bourisaw</author><author>Arsen S. Iskhakov</author>
        <description><![CDATA[Critical heat flux (CHF) prediction under non-uniform axial heating remains challenging because the local thermal margin can depend on both local thermodynamic conditions and the upstream heating history. Traditional non-uniform CHF methods account for thermal-history effects through empirical correction factors, whereas the present work uses a transformer to learn this correction while retaining the conventional formulation. A neural network previously trained on a large uniform-heating CHF database is frozen and used to provide the baseline uniform-heating CHF prediction. A causal transformer model is then trained on non-uniform CHF data to predict a local correction factor from ordered axial sequences containing normalized axial position, equilibrium quality, and normalized heat-flux shape, with mass flux used as a global conditioning variable. The causal attention mask prevents downstream locations from contributing to the correction at each axial location. The model is evaluated using a benchmark non-uniform CHF database containing inlet-peaked, middle-peaked, outlet-peaked, and spike-like axial power profiles. The proposed correction is compared against the frozen uniform-heating neural network without correction, the same neural network with K5 or Tong F corrections, and LUT-based predictions. Additional studies examine input ablation, axial-resolution transfer, training-seed robustness, and profile-family-held-out generalization. On the primary held-out test set, the transformer-based correction reduces prediction scatter relative to the classical correction-factor baselines; additional seed and profile-family-held-out tests indicate remaining sensitivity to training initialization and unseen profile families. Attention profiles at the transformer-selected minimum departure from nucleate boiling ratio (MDNBR) locations are analyzed as qualitative diagnostics of the learned sequence representation.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1987465</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1987465</link>
        <title><![CDATA[Comparative aerodynamic analysis of NACA 24-series airfoils at low Reynolds number using computational fluid dynamics and wind-tunnel experiments]]></title>
        <pubdate>2026-10-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shaik Irfan Sadaq</author><author>Pankaj Kumar</author><author>Abhishek Agarwal</author><author>Michel Kalenga Wa Kalenga</author><author>Balram Yelamasetti</author><author>Samera Saniya</author><author>V. Dharam Singh</author>
        <description><![CDATA[IntroductionThis study compares five NACA four-digit airfoils under identical CFD conditions and examines the selected profile experimentally using a scaled wind-tunnel model.MethodsNACA 2408, 2412, 2415, 2418 and 2421 were analysed at 35 m/s and an angle of attack of 0°. Lift, drag, static pressure and lift-to-drag (L/D) ratio were evaluated. The selected profile was fabricated as a 1:20-scaled model and tested in a low-speed wind tunnel.ResultsNACA 2412 achieved the highest reported CFD L/D ratio of 35.64. The scaled CFD and experimental results differed by 3.87% in lift, 1.55% in drag and 2.36% in L/D ratio.DiscussionNACA 2412 showed the highest aerodynamic efficiency among the investigated profiles under the selected CFD conditions. Because the scaled experimental model operated at a different Reynolds number, the experimental results provide complementary evidence rather than strict Reynolds-number-matched validation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1915019</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1915019</link>
        <title><![CDATA[Design and analysis of a double-helical folding-deploying mechanism for a land-air amphibious vehicle]]></title>
        <pubdate>2026-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Meng Gao</author><author>Mengjie Zhang</author><author>Meijing Wang</author><author>Pengfei Xu</author><author>Xiaoming Sun</author>
        <description><![CDATA[Existing rotor deployment mechanisms for land-air amphibious vehicles, such as fixed, telescopic, and conventional folding arms, remain limited in coupled motion capability, compactness, and load-bearing performance. To achieve rotor attitude switching within a constrained installation space, this paper proposes a double-helical folding-deploying mechanism. The mechanism couples screw-driven vertical lifting with helical-guide-induced horizontal rotation, enabling the rotor arm to switch between ground-driving and flight-operation configurations through coordinated translation and rotation. A nested structure consisting of a lead screw, lifting platform, rotating sleeve, guide body, and helical guide is designed to improve integration and motion coordination. Static mechanical models are established for key load-bearing and contact components, and the load transmission relationship, non-uniform contact pressure distribution, and frictional resistance torque are derived for structural design and strength verification. An ADAMS dynamic model is then developed to validate the motion process and force characteristics. The simulated lead-screw forces agree well with theoretical results, with errors of 2.0% and 3.2%, while the guide-body force error is about 10% due to contact nonlinearity and friction-induced oscillation. Finally, a one-way fluid-structure interaction analysis under multirotor flight conditions shows maximum stresses of 165–195 MPa and maximum deformations of 67–68 mm, indicating feasible load-bearing performance.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.2001438</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.2001438</link>
        <title><![CDATA[Nonlinear vortex-induced vibration of cantilever fluid-conveying pipes under internal flow-induced modal interaction and post-flutter]]></title>
        <pubdate>2026-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chenyi Wang</author><author>Yiru Ren</author>
        <description><![CDATA[The vibration behavior analysis of cantilever fluid-conveying pipes under the coupling of internal and external flow is essential for the safety design of offshore mining pipes. This paper explores the nonlinear vortex induced vibration (VIV) behavior of a cantilever fluid-conveying pipe, taking into account the coupling effects of internal flow-induced modal interaction and post-flutter. A nonlinear model of the pipe is established that fully considers nonlinear stiffness and nonlinear inertia. The nonlinear stiffness is introduced by considering nonlinear curvature in the displacement field, while the nonlinear inertia is introduced through the inextensible pipe model. The vortex-induced force caused by external flow is characterized using a wake-oscillator model. The governing equation is derived via the Hamiltonian variational principle, and numerical solutions are obtained by Galerkin truncation combined with the fourth-order Runge-Kutta method (RKM), which are validated through a specific harmonic balance method (HBM). The results present the amplitude-flow velocity bifurcation curve, as well as vibration modes and spectra at specific flow velocities. It is indicated that nonlinear bimodal coupled vibration behavior exists under both of the two types of internal and external flow coupling, which may not change the response the periodicity, but significantly change the amplitude and vibration mode.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1991577</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1991577</link>
        <title><![CDATA[Changes in operational availability following a structured preventive-maintenance program for industrial rolling doors: a before-and-after case study in lima, Peru]]></title>
        <pubdate>2026-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Roberto Carlos Calero Obregón</author><author>Karen Esteincin Cuba Vargas</author><author>Jorge Epifanio Gamarra Tolentino</author><author>Eluard Alexander Mendoza Zenozain</author><author>Nestor Bernardo Corpus Vergara</author>
        <description><![CDATA[IntroductionIndustrial rolling doors are operationally relevant auxiliary assets whose failures can disrupt material flow, safety, and service continuity, yet empirical maintenance evidence for these systems remains limited. This uncontrolled before-and-after case study evaluated changes in reliability following implementation of a structured maintenance-management program centered on quarterly preventive maintenance in a manufacturing plant in Lima, Peru.MethodsTen rolling doors with complete paired records were analyzed over two standardized six-month observation windows, each comprising 4,320 nominal scheduled hours per door. Failure records and technical inspections informed cause prioritization, asset-criticality assessment, failure-mode analysis, maintenance tasks, task-specific training, and standardized record keeping. Mean time between failures (MTBF), mean time to repair (MTTR), operational availability, failure count, and downtime were compared at door level.ResultsMTBF increased from 359.61 to 2,338.45 h (mean paired difference 1,978.84 h; 95% bootstrap CI 1,199.74–2,868.94), MTTR decreased from 48.89 to 1.55 h (difference −47.34 h; 95% CI −57.05 to −39.92), and availability increased from 85.21% to 99.91% (difference 14.70 percentage points; 95% CI 10.83–18.75). Exact paired Wilcoxon tests yielded p = 0.002 for all three outcomes. Total recorded failures decreased from 137 to 25 and downtime from 6,390 to 38 h.DiscussionThe changes were associated with implementation of the structured program. However, the absence of a concurrent control group, the use of nominal calendar exposure rather than recorded opening/closing cycles, incomplete intervention-fidelity records, and the short observation horizon preclude definitive causal attribution.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.2004324</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.2004324</link>
        <title><![CDATA[Physics-guided digital-twin-oriented energy-state estimation with meta-domain generalization for electric vehicle mechatronic systems]]></title>
        <pubdate>2026-10-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wei Xiao</author>
        <description><![CDATA[BackgroundElectric-vehicle energy estimators are often judged by average error on data drawn from the same distribution used for model development. Much less is known about how these estimators behave when the route, operating regime, or individual vehicle changes, although such shifts are unavoidable in a practical mechatronic digital twin.MethodsThe analysis included 4,114 eligible 1-min windows from 503 eVED trips recorded by three 2013 Nissan Leaf vehicles. We fitted a sign-constrained electromechanical prior within each training fold and linked it to a compact latent state-space encoder. PGMD-Twin combined episodic training over four data-derived operating archetypes, three softly gated experts, a weak worst-domain penalty, and trip-grouped split-conformal calibration. Performance was examined with five-fold trip-grouped validation, route-family holdouts, leave-one-archetype-out testing, leave-one-vehicle-out testing, and four vehicle-archetype compound holdouts. Imputation and scaling were estimated from training data only.ResultsIn trip-grouped testing, PGMD-Twin reached a mean MAE of 0.0196 kWh and R2 of 0.825. Mean MAE was 0.0208 kWh under route shift, 0.0211 kWh when an operating archetype was withheld, 0.0255 kWh in same-model inter-vehicle transfer, and 0.0205 kWh across the compound holdouts. Empirical coverage of the nominal 90% intervals ranged from 91.5% to 97.9%. A simpler physics-data Hybrid retained lower mean point error in several matched protocols, and adding the meta-domain term did not improve every ablation.ConclusionPGMD-Twin should be interpreted as an offline, digital-twin-oriented energy-state estimation framework rather than as a validated online digital twin or a universally superior predictor. Its value is in combining a physical prior, short-horizon state dynamics, structured domain-shift testing, and uncertainty auditing in one workflow. Relative error degradation was smaller than for the matched MLP and Hybrid under route, condition, and vehicle shifts, but absolute point error remained higher and vehicle-level transfer remained unresolved. Cross-platform validation, continuous synchronization, and hardware- or vehicle-in-the-loop testing are therefore required before broader digital-twin deployment claims can be supported.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1831065</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1831065</link>
        <title><![CDATA[Comprehensive numerical investigation of ambient temperature and discharge rate effects on thermal performance of a 104-cell Li-ion battery pack with zig-zag arrangement and hybrid TEC–forced convection cooling]]></title>
        <pubdate>2026-10-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Siva Krishnam Raju Rallabandi</author><author>I. S. Rajay Vedaraj</author>
        <description><![CDATA[Effective battery thermal management must remain reliable under changing ambient temperature, discharge demand, and airflow availability. This study investigates a 104-cell (13S8P) NCR18650BD lithium-ion battery pack in a Zig-zag (staggered) arrangement using a Python/SciPy lumped-parameter thermal model that combines Joule heat, SOC-dependent reversible entropic heat, temperature-dependent internal resistance, radiation, forced convection, and thermoelectric-cooler (TEC) physics. A full factorial design was evaluated over 108 operating conditions (four ambient temperatures, nine discharge currents, and three airflow velocities), with five seeded Monte Carlo repetitions per condition, yielding 540 simulated measurements. The SOC-dependent entropic coefficient was propagated through the solver by SOC-window averaging for steady-state cases and by Coulomb-counted SOC updates for transient discharge. The rerun showed that the 45 °C natural-convection safe-current limit decreases from 40.3 A at 20 °C to 22.5 A at 35 °C. With ambient-dependent TEC hot-side derating, the corresponding natural-convection TEC-assisted extended limits decrease from 70.8 A to 57.0 A, demonstrating that TEC expands the operating envelope but does not eliminate ambient-temperature sensitivity. At v = 7 m/s, all tested currents up to 60 A remain safe except the 35 °C case, where the no-TEC threshold is 52.4 A. Two-way ANOVA at v = 7 m/s identified ambient temperature as the dominant factor (η2 = 0.6348), followed by discharge current (η2 = 0.3585), with a small interaction contribution (η2 = 0.0016). A physics-enhanced Ridge model achieved R2 = 0.9858 and RMSE = 0.630 °C on a condition-level holdout split, while a closed-form no-TEC BMS equation achieved R2 = 0.9279 and RMSE = 1.419 °C. The revised results provide corrected isotherm coordinates, an updated safe-current table, clearer operating-envelope figures, and an explicit TEC activation map for battery-management implementation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1900959</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1900959</link>
        <title><![CDATA[Multi-objective optimization of lane-changing trajectories for autonomous vehicles based on deep reinforcement learning]]></title>
        <pubdate>2026-10-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuexiang Hu</author><author>Qin Li</author>
        <description><![CDATA[IntroductionThe viability of autonomous driving technology largely depends on driving efficiency and driving safety, in which the accuracy of lane-changing trajectory planning is particularly important. Existing methods still suffer from low prediction accuracy and insufficient multi-objective collaborative optimization.MethodsA multi-objective optimized lane-changing trajectory planning method for autonomous vehicles based on the improved deep deterministic policy gradient is proposed. A trajectory prediction module is constructed by combining the temporal convolution network, the spatial multi-head attention mechanism, and a Transformer encoder–decoder, and the driving risk field is integrated into the multi-objective reward function.ResultsA performance comparison analysis was conducted between the trajectory prediction module and other methods, and the prediction root mean square errors for going straight, turning left, and turning right were 1.59, 1.19, and 1.27 m, respectively. The proposed method achieved obstacle avoidance and target advancement success rates of 98.92% and 98.26%, respectively, both of which outperformed the comparison method. In the lane-changing overtaking and lane-changing obstacle avoidance scenarios, the vehicle lane-changing correction was more timely, the vehicle speed fluctuation was smaller, and the front wheel angle control was smoother, all of which were better than those of the comparison method.DiscussionThe proposed lane-changing trajectory planning method effectively improves the trajectory prediction accuracy and planning performance, and can provide a theoretical basis for related research fields.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.2005334</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.2005334</link>
        <title><![CDATA[Regenerative braking control for electric vehicles with battery and safety constraints]]></title>
        <pubdate>2026-10-16T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Sun Changyong</author><author>Zhang Wenfeng</author><author>Mengqi Zhu</author>
        <description><![CDATA[Regenerative braking recovers energy while slowing an electric vehicle. Its contribution is limited by battery charge acceptance, motor capability, and tire grip. When the battery charging limit falls, friction braking may need to replace the lost regenerative torque. Different actuator response times can then cause a shortfall in total braking torque. This mini-review examines how battery limits and brake control are coordinated. It compares rule-based, fuzzy, predictive, and learning-based methods, with attention to actuator response and validation. It also examines dual-motor torque allocation and one-pedal control, using documented production functions as examples. Immediate battery protection is distinguished from long-term battery aging. The reviewed studies show why lower charging current alone does not establish a battery-life benefit. A key control task is to manage changes in regenerative capability during braking. Predicting these changes may help prepare the friction brakes, but the current battery and tire limits must still be respected. The review proposes combined battery and road test cases. It also defines torque-deficit measures for assessing brake transitions. Future studies should report recovered energy alongside deceleration, wheel slip, actuator delay, and battery response under matched test conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1957641</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1957641</link>
        <title><![CDATA[Design challenges and enabling technologies for ultra-high-speed electric drive systems]]></title>
        <pubdate>2026-10-16T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Yingshuai Liu</author><author>Dongdong Li</author><author>Hua Li</author><author>Xintong Li</author>
        <description><![CDATA[Ultra-high-speed electric drive systems are a key route toward higher power density in electric vehicles, aerospace propulsion, and industrial applications, with series-production traction machines now exceeding 20,000 r/min and laboratory prototypes approaching or exceeding 100,000 r/min. This mini-review examines the design challenges and enabling technologies of ultra-high-speed machines, organized around five engineering questions: how high electrical frequency reshapes loss mechanisms and winding design, how centrifugal and fatigue loading constrain rotor structures, which bearing technologies remain viable at extreme speeds, how windage and cooling limit thermal management, and how power electronics and control must adapt. Findings are synthesized from peer-reviewed journal literature, with particular attention to retaining-sleeve material selection, rotor stress and balancing, active magnetic bearing systems, windage loss scaling, and direct oil cooling trade-offs. Because rotational speed alone does not define the operational limits—tip speed, electrical frequency, bearing DN values, and rated power are equally decisive—the review frames each topic around its underlying physical constraint rather than a nominal speed threshold. By identifying the conflicts among electromagnetic performance, mechanical integrity, and thermal stability, and by separating mature industrial practice from laboratory demonstrations, this review aims to provide a focused reference for researchers and engineers developing next-generation high-speed electric propulsion systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1904437</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1904437</link>
        <title><![CDATA[Interpretable surrogate modeling for load-aware thermal risk assessment of bolted switchgear busbar joints using electro-thermal simulation]]></title>
        <pubdate>2026-10-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kuineng Chen</author><author>Huan Liu</author><author>Fenglu Li</author>
        <description><![CDATA[Thermal-risk assessment of bolted busbar joints is complicated by the coupled effects of electrical loading, contact condition, and heat dissipation. This study develops an interpretable forward-surrogate framework based on three-dimensional electro-thermal finite-element simulation. Physics enters through finite-element generation of the training data, physically defined input variables, and post hoc consistency checks, rather than through constraints embedded in the learning algorithm. Five prescribed inputs were considered: load current, contact resistance, effective contact ratio, ambient temperature, and convective heat-transfer coefficient. The effective-contact heating power was checked against P≈I2Rc, with a maximum relative deviation of 0.173% across 400 simulated cases; 382 cases were retained within the intended applicability domain. Four candidate models were compared using 5×10 repeated cross-validation. The XGBoost regressor achieved R2=0.990±0.005, RMSE=1.877±0.542, and MAE=1.042±0.198K, with performance comparable to random forest. For four-class simulation-oriented thermal-risk classification, XGBoost achieved an accuracy of 0.938±0.026 and a macro F1-score of 0.941±0.033. SHapley Additive exPlanations (SHAP) analysis identified load current and prescribed contact resistance as the dominant contributors, while convection, ambient temperature, and effective contact ratio produced smaller, condition-dependent effects. The lower global importance of effective contact ratio reflects the area-averaged temperature-rise target and does not imply that current constriction is physically unimportant. Across three threshold schemes, all out-of-fold errors were between adjacent classes. The framework is geometry-specific and has not been experimentally validated. It predicts internal effective-contact temperature rise; relating this quantity to infrared surface measurements requires further validation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1989288</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1989288</link>
        <title><![CDATA[Friction properties of boundary film formed by polymer additives in wide-area contacts with nanoscale gap]]></title>
        <pubdate>2026-10-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wataru Yagi</author><author>Toshiyuki Tsuchiya</author><author>Naoki Yamashita</author><author>Tomoko Hirayama</author>
        <description><![CDATA[Polymer additives, originally used as viscosity index improvers, have attracted increasing attention as friction-reducing lubricant additives because of their ability to adsorb onto surfaces through polar groups. Although adsorbed polymer films are known to play an important role in friction under boundary lubrication conditions, how their interfacial properties change during sliding and how these changes affect tribological behavior remain unclear. To elucidate the relationship between the interfacial behavior of polymer additives and friction characteristics, we investigated changes in the coefficient of friction and oil film thickness using lubricating oils containing polymethyl methacrylate (PMA). A custom-built friction tester capable of applying unidirectional sliding over a contact area of approximately 1 mm2 was used to evaluate PMA additives with different numbers of polar groups and molecular weights, with a base oil and an olefin copolymer (OCP) used for comparison. The base oil and OCP-containing oil exhibited a nearly constant dynamic coefficient of friction, whereas all PMA-containing oils exhibited lower friction accompanied by stick-slip behavior at low shear velocities. No clear difference in the coefficient of friction was observed between PMA additives with different numbers of polar groups. However, the oil film thickness of the PMA additive with fewer polar groups decreased with increasing load. Although the coefficient of friction was nearly the same for high- and low-molecular-weight PMAs, the oil film thickness of the high-molecular-weight PMA decreased after friction compared with that before friction. These results suggest that the number of polar groups affects the stiffness of the adsorbed polymer film in the load direction, whereas molecular weight affects the oil film thickness. For high-molecular-weight PMA, shear-induced desorption or rearrangement of a weakly formed topmost layer may reduce the thickness of the remaining strongly adsorbed film. These findings clarify the relationship between the interfacial behavior of polymer additives and friction characteristics and provide insights into the design of polymer additives for friction reduction.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1976511</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1976511</link>
        <title><![CDATA[Data-driven multi-criteria evaluation of intelligent cockpit configuration strategies in Chinese battery electric vehicles]]></title>
        <pubdate>2026-10-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Weixin Zhu</author><author>Xue Xiong</author>
        <description><![CDATA[IntroductionIn this study, we examine how documented cockpit equipment differentiates selected Chinese-brand battery electric vehicles (BEVs). We compare configuration richness with and without a price criterion and identify recurring equipment arrangements, rather than using specifications as a proxy for tested cockpit performance.MethodsThe dataset comprises 36 purposively selected model–trim combinations from 13 brands. Two CRITIC–TOPSIS models score four configuration criteria, with guide price included as a cost in the second model. Gower dissimilarity and partitioning around medoids (PAM) describe eight mixed-type attributes. Sensitivity checks vary weights, aggregation, criteria, coding, and case composition. Each model also uses 5,000 vehicle resamples and 5,000 brand-block resamples to assess conditional weighting uncertainty.ResultsThe head‐up display (HUD) level receives the largest weight in the price‐free model (0.3557). Baseline rankings correlate at ρ = 0.964. Five clusters yield a mean silhouette width of 0.519, only slightly above 0.514 for six clusters. Removing HUD reduces ranking correlations to 0.678 and 0.750. The leading price-adjusted scores for ZEEKR 001 and XPeng P7+ differ by 0.000285; their first-place frequencies under brand-block resampling are 50.30% and 49.06%.DiscussionThe comparison distinguishes equipment patterns within the recorded sample, but its resolution depends on the criteria and their representation. Broad ranking agreement does not guarantee a stable first-place choice. The clusters describe configurations, not market shares, and neither index establishes superior usability, safety, or overall cockpit capability.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1967578</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1967578</link>
        <title><![CDATA[A model for timing anomaly detection and prediction of CNC machine tools based on multi-scale feature fusion and self-attention]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tengda Chen</author>
        <description><![CDATA[In order to solve the bottleneck problem of existing deep learning models being easily affected by feature interference and overfitting under strong noise, this paper proposes a Multi-scale Feature Fusion and Self-Attention based Time-Series Anomaly Detection and Prediction Network(MSFF-SATADPN). This paper first uses progressive dilated convolution to truncate local transient features in multiple frequency bands, and then dynamically maps global degradation dependencies through self attention mechanism. In addition, this paper applies orthogonal projection regularization of singular value decomposition to the hidden layer space, thereby decoupling steady-state principal components and anomalous disturbances at the physical representation level. Finally, independent blind testing across tools showed that within the range of structural mutations, compared to the Informer model exhibiting residual oscillations of −0.058–0.059 mm, the model predicted residual convergence to −0.015–0.018 mm. The global average absolute error of all test samples reached 0.062 mm, and the average absolute error distribution of each sample was 0.08 mm. The global average absolute error directly aggregated the absolute errors of all time steps, and each sample value averaged the absolute errors within each sample before sample aggregation. Both values were lower than the corresponding values of PatchTST in paired t-test (p < 0.01). In the abnormal classification under natural noise cutting conditions, the overall F1 score converged to 0.938 (± 0.008). This study overcomes the confusion of multi frequency features through a clear orthogonal decoupling mechanism, providing a reliable sequence analysis method for practical industrial operation and maintenance decisions.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1906456</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1906456</link>
        <title><![CDATA[IMU- and LSTM-CNN-based multi-gait recognition for a lower limb exoskeleton]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Liancheng Zheng</author><author>Rizauddin Ramli</author><author>Xinru Li</author><author>Mohamad Hazwan Mohd Ghazali</author><author>Mingya Wang</author>
        <description><![CDATA[This study presents a platform-specific and subject-independent validation of an IMU-based LSTM-CNN gait-recognition pipeline on a self-developed lower-limb exoskeleton. Ten healthy participants performed five locomotion modes, including level walking, stair ascent, stair descent, standing up, and sitting down. Each participant completed five level-walking trials and ten trials for each of the remaining four locomotion modes, resulting in 450 original recording trials. IMU signals collected from the thigh, shank, and foot were segmented using a 128-sample sliding window with a 64-sample step. To prevent information leakage from overlapping windows and to evaluate inter-subject generalization, the dataset was partitioned at the participant level before window segmentation. The LSTM layers modeled temporal dependencies in the IMU sequences, while Conv1D and pooling layers extracted local discriminative features. Under the subject-independent evaluation protocol, the model achieved an overall accuracy of 94.08%, a macro-F1 score of 93.73%, and a balanced accuracy of 93.62%. These results support the preliminary feasibility of the implemented IMU-based LSTM-CNN workflow for offline gait-mode recognition on the tested lower-limb exoskeleton platform. Further validation under larger participant cohorts and online closed-loop conditions is still required.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1968060</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1968060</link>
        <title><![CDATA[Process optimization and machining performance of ultrasonic vibration-assisted milling of hardened internal keyways]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Liang Zhang</author><author>Xuemin Li</author><author>Xiaoming Han</author>
        <description><![CDATA[IntroductionHardened internal keyways are widely used in aerospace transmission components, where machining quality directly affects assembly accuracy, load-carrying capability, and service reliability. Conventional wire electrical discharge machining (WEDM) can produce recast layers, micro-cracks, and other thermally induced defects, while subsequent manual finishing may compromise dimensional consistency. This study investigates ultrasonic vibration-assisted milling (UVAM) as a non-electrical machining process for precision machining of hardened internal keyways.MethodsAn axial UVAM system was integrated with a vertical machining center, and a series of experiments were conducted to examine the effects of vibration parameters, cutting parameters, and cooling conditions on machining performance. Single-factor experiments were used to determine suitable parameter ranges, followed by orthogonal optimization and response surface analysis to evaluate the relationships between key process parameters and machining quality.ResultsA vibration frequency of 30 kHz, vibration amplitude of 2.0 µm, spindle speed of 5000 r/min, feed per tooth of 25 µm/tooth, and oil-mist lubrication provided a favorable combination of surface quality, dimensional accuracy, and tool life. Under these conditions, the machined keyways exhibited a surface roughness of 0.32–0.49 µm, a keyway width of 3.01–3.04 mm, and a twin-slot symmetry error below 0.02 mm. No apparent recast layer or thermally induced surface damage was observed on the machined surfaces. Continuous machining tests showed that abrasive wear was the primary tool wear mechanism, with flank wear increasing gradually from 0.001 to 0.009 mm after six consecutive workpieces. Sensitivity analysis identified feed per tooth and vibration amplitude as the dominant process variables affecting machining quality. A response surface model was developed to predict surface roughness, and the predicted values showed good agreement with the experimental measurements.DiscussionThe results demonstrate that UVAM enables stable and damage-free machining of hardened internal keyways with high surface quality, consistent dimensional accuracy, and controllable tool wear, providing a practical non-electrical alternative to conventional thermal machining processes for precision transmission components.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1978898</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1978898</link>
        <title><![CDATA[Additive manufacturing of metallic implants: a comprehensive review of material selection, porous architecture, and hybrid surface engineering]]></title>
        <pubdate>2026-10-13T00:00:00Z</pubdate>
        <category>Review</category>
        <author>M Mutharasu</author><author>J Joel</author>
        <description><![CDATA[Additive manufacturing (AM) of metallic implants is shifting from geometry replication toward integrated control of load transfer, tissue interaction, and surface stability. Nevertheless, the literature remains fragmented, often optimizing biomaterials, architectures, AM processes, and bioactive coatings as separate components despite their coupled performance. This review proposes an integrated design framework that connects patient anatomy, material selection, architected porosity, AM technology, and hybrid surface engineering into a unified development pathway. CT/MRI-based design and topology optimization are presented for a lattice topology, with the aim of achieving precise volumetric porosity levels between 50% and 85% to bring effective stiffness into the physiological range of human bone, approximately 0.01–20 GPa. Titanium, Co-Cr alloys, and 316L stainless steel, as well as magnesium alloys, are critically compared with hydroxyapatite, bioactive glass, and hierarchical hybrid coatings to demonstrate how multilayer functionality can overcome limitations of metallic substrates. Coating performance correlates with adhesion, degradation, and cellular response, which treats biological evaluation as an interconnected metric rather than an isolated endpoint. It discusses critical trade-offs where increased porosity improves mechanical compatibility, but retention of fatigue strength above cortical bone thresholds of 40–60 MPa remains a profound manufacturing challenge; increased coating complexity increases the risk of interfacial failure, and accelerated degradation compromises retention of structural integrity. The review concludes by identifying manufacturing reproducibility, coating durability on complex lattices, and regulatory qualification as the leading barriers to clinical translation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1963772</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1963772</link>
        <title><![CDATA[Friction and interfacial mechanics of surgical suturing: needle–tissue penetration, suture drag and friction-control strategies]]></title>
        <pubdate>2026-10-09T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Shubham Gupta</author><author>Varatharajan Prasannavenkadesan</author>
        <description><![CDATA[Surgical suturing involves a sequence of tribological contacts that begins with needle penetration, continues through suture pull-through, and culminates in knot tightening and locking. Uncontrolled friction at these interfaces can cause tissue trauma, coating delamination, or knot slippage. This narrative review synthesises the biomechanics and tribology of the needle–tissue, suture–tissue, and suture–suture interfaces. PubMed, Scopus and Web of Science were searched for studies published from January 2000 to July 2026, and studies were selected for mechanical relevance and synthesised by tribological interface. Needle insertion force is a combined response of tissue deformation, cutting and shaft friction, with attention to needle geometry, trajectory, velocity, tissue properties and force sensing. Suture drag is examined in relation to material, diameter, surface roughness, monofilament or multifilament construction, hydration, loading and pulling speed. Surface-engineering approaches, including lubricants, silicone and polymeric treatments, antimicrobial coatings, dopamine-, chitosan- and graphene-based modifications, and tissue-integrating sutures, are evaluated for friction reduction, durability, handling and knot performance. The review also discusses the transition from low resistance during passage to sufficient suture–suture friction after tightening, together with experimental apparatus, biological tissue models, finite-element methods and robotic force feedback. Evidence shows that friction is stage-dependent and should be controlled rather than uniformly minimised. Future progress will depend on standardised wet-tissue testing, clearer separation of force components, repeated-passage evaluation of coatings, tissue-specific needle–suture selection, and stronger links between mechanical measurements, tissue response and adaptive robotic control.]]></description>
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