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The hemispherical resonant gyroscope is the highest-precision solid-state vibration gyroscope, widely applied in aviation, aerospace, marine, and other navigation fields. As the core component of the hemispherical resonant gyroscope, the design of its structural parameters directly influences the key performance parameters of the resonator—specifically, the thermoelastic damping quality factor and the minimum frequency difference from interference modes—affecting the operational accuracy and lifespan of the gyroscope. However, existing research, both domestic and international, has not clarified the effect of structural parameters on performance laws. Thus, studying the mapping relationship between the resonator’s performance and structural parameters is essential for optimization. In this study, a hemispherical resonator with a midplane radius of 10 mm serves as the research object. Based on a high-precision finite element simulation model of an ideal hemispherical resonator, the mechanism of thermoelastic damping and the influence of structural parameters on performance are analyzed. A PSO-BP neural network mapping model is then developed to relate the resonator’s structural and performance parameters. Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. The comprehensive, performance-oriented multi-objective optimization method for the structural parameters of hemispherical resonators proposed in this paper offers a cost-effective approach to high-performance design and optimization, and it can also be applied to other manufacturing processes under specific conditions.

Human sweat serves as a viable signal source for continuous monitoring of physiological indicators. Sweat sensors with flexible microfluidic structures offer the advantages of operational convenience and quantifiability, making them suitable for integration with electrochemical detection. The utilization of flexible polymer materials as substrates enhances the ability to manipulate sweat, necessitating exploration into highly integrated and controllable structural designs for fluid chambers in microfluidic structures. This study presents simulations and designs aimed at optimizing the layout of microfluidic structures and two-dimensional channel shapes. A flexible polyethylene glycol terephthalate substrate is employed to fabricate the microfluidic sensing device using laser cutting, screen printing, and layer-by-layer assembly techniques. The resulting microfluidic structure enables precise control over artificial sweat flow velocities and facilitates verification of Na + detection. The optimal parameters of the length of 7 mm, width of 110 μm, and diffusion angle of 15°, ensure stable flow velocity under precise control. The response of the Na + sensor exhibits near-Nernstian behavior that varies with the flow velocity. The integration of an electrochemical sensor with flexible microfluidic structures demonstrates high sensitivity and accuracy, and on-body quantitative analysis in human sweat is achieved.

Modern manufacturing places increasing demands on assembly accuracy, revealing the limitations of conventional tolerance-based methods and studies that oversimplify multi-surface constraints into single-surface problems. To address this challenge, it is crucial to account for geometric distribution errors on multiple surfaces and constraints from multiple mating surfaces, analyzing their coupling effects in assembly. This paper presents a model that incorporates the effects of machining-induced geometric distribution errors and the constraints arising from multiple mating surfaces. The model determines contact points between two pairs of mating surfaces and calculates the spatial pose of the assembled part to predict assembly accuracy. The model validation was conducted in two stages: initial verification of fundamental principles through a two-dimensional simulation, followed by experimental validation. The experimental study involved mating surfaces with distinct geometric distribution errors manufactured by different machine tools. Assembly tests were performed under two distinct orientations of applied external forces. Results show close agreement between predicted and measured values, with a root mean square error (RMSE) below 2%, confirming the method’s effectiveness. The proposed method offers a solution to the assembly registration problem involving coupled multi-constraints and geometric distribution errors.

In tolerance design for complex mechanical systems, 3D dimension chain analyses are crucial for assembly accuracy. The current methods (e.g., worst-case analysis, statistical tolerance analysis) face limitations from oversimplified assumptions—treating datum features as ideal geometries while ignoring manufacturing-induced spatial distribution of form errors and failing to characterize 3D coupled error constraints. This study proposes a six-dimensional spatial dimension chain (SDC) model based on transfer matrix theory. The key innovations include (1) a six-dimensional model integrating position and orientation vectors, incorporating geometric error propagation constraints for high-fidelity error prediction and tolerance optimization, (2) the characterization of spatially distributed form errors and 3D coupled errors of spatial dimension chain-based multiple mating-surface constraint (SDC-MMSC) using six-degree-of-freedom (6-DoF) geometric error components, reducing the assembly topology complexity while improving the efficiency, and (3) a 6-DoF error characterization method for non-mating-constrained data, providing the theoretical basis for SDC modeling. The experimental validation on an aero-engine casing assembly shows that the SDC model captures multidimensional closed-loop spatial errors, with absolute errors of max–min closed-loop distances below 9.3 μm and coaxiality prediction errors under 8.3%. The SDC-MMSC method demonstrates superiority, yielding normal vector angular errors <0.008° and envelope surface RMSE values <0.006 mm. This method overcomes traditional simplified assumptions, establishing a high-precision, multidimensional distributed-form-error-driven SDC model for complex mechanical systems.

The rotor overtemperature caused by losses is one of the important issues for the high-speed electrical machine. This paper focuses on the rotor loss analysis and CFD-thermal coupling evaluation for 105 kW, 36,000 r/min HSPMSM. Three types of sleeve materials as carbon-fiber, Titanium alloy, and stainless steel are introduced in this paper, researching the effects of sleeve conductivity, thickness and rotational speed on rotor eddy current loss, balancing rotor mechanical strength. The sleeve made of titanium alloy material with a thickness of 3.5 mm is chosen to effectively suppress the rotor eddy current loss in high-speed motors in the paper. The air friction loss becomes significant based on the PM motor at high rotational speed. The roundness error of the rotor sleeve has the important impact on the air friction loss of the rotor and the rotor temperature of the motor, which leads to the over temperature of the rotor. Therefore, based on the CFD fluid model, the influence of roundness error, cooling parameters, rotational speed and temperature boundary on the air friction loss is studied in detail, and the expression is summarized to provide reference for estimating the air friction loss. According to the rotor structure in this paper, the optimal cooling air inlet velocity is 10 m/s. Finally, the loss separation method is used to obtain the air friction loss measurement results. The accuracy of the finite element calculation results of air friction loss is verified through the experimental data. The temperature rise of the HSPMSM was also measured with 5.5% error. In this paper, the conclusion and analysis method could provide some reference for the research of the rotor structure and the improvement of the efficiency of HSPMMs.

The key indicator of a grazing incidence focusing mirror’s imaging quality is its angular resolution, which is significantly influenced by its surface shape distribution error. In this paper, we propose a method for the prediction of grazing incidence focusing mirror imaging quality based on accurate modelling of the surface shape accuracy for the whole assembly process. Firstly, the three-dimensional surface shape distribution error of the inner surface of the focusing mirror is reconstructed based on measured point cloud data, and the changes in the surface shape induced by suspension gravity and the adhesive curing shrinkage force are obtained through simulation, and then an accurate geometric digital twin model based on the characterisation of its surface shape accuracy is established. Finally, a study on the quantitative prediction of the angular resolution of its imaging quality is performed. The results show that the surface shape error before assembly has the greatest influence on the imaging quality; the difference in angular resolution between the two suspension methods under the influence of gravity is approximately 2.1″, and the angular resolution decreases by about 4.2″ due to adhesive curing. This method can provide effective support for the prediction of the imaging quality of grazing incidence focusing mirrors.

In this study, hierarchical copper nano-dendrites (CuNDs) are fabricated via the electrodeposition method. The electrochemical behaviors of the as-obtained hierarchical CuNDs in 0.1 M NaOH aqueous solution are subsequently studied. The CuNDs experience a non-equilibrium oxidation process when subjected to cyclic voltammetry (CV) measurements. The first oxidation peak O1 in CV is attributed to the formation of an epitaxial Cu 2 O layer over the surface of the hierarchical CuNDs. However, the second oxidation peak O 2 in CV appears unusually broad across a wide potential range. In this region, the reaction process starts with the nucleation and growth of Cu(OH) 2 nanoneedles, followed by the oxidation of Cu 2 O. Upon the increase of potential, Cu 2 O is gradually transformed to CuO and Cu(OH) 2 , forming a dual-layer structure with high productivity of Cu(OH) 2 nanoneedles.

Thin-walled structures comprised of fiber-reinforced polymer (FRP) composites and metal excel in achieving a balanced design in terms of material cost, weight savings, and mechanical performance. This study aims to explore the crushing characteristics and failure mechanism of square hollow aluminum tubes wrapped with glass FRP (GFRP) fabricated by vacuum-assisted resin infusion with six types of lay-up directions. Axial quasi-static compression and single/repeated low-velocity impact (LVI) are conducted to investigate their failure evolution and energy absorption properties, such as the specific energy absorption (SEA), mean crushing force (MCF), peak crushing force (PCF), and crushing force efficiency (CFE). The synergy among oblique, axial, and circumferential GFRP ply, which enhances strength and reduces out-of-plane deformation in the structure, is maximized by using the antisymmetric angle ply rather than the single angle ply. Under these three loading modes, the cases with a [0°/90°] lay-up have excellent crashworthiness indicators, including PCF, SEA, and MCF. Meanwhile, compared with the pure aluminum tube, both the SEA and CFE are improved simultaneously by up to 158% and 121% during the single LVI test. The study focuses on the influence of stacking configurations on crashworthiness and further explores the potential and application of such hybrid structures.

Transition-metal oxides （TMOs） have gradually attracted attention from resear- chers as anode materials for lithium-ion batteries （LIBs） and sodium-ion batteries （SIBs） because of their high theoretical capacity. However, their poor cycling stability and inferior rate capability resulting from the large volume variation during the lithiation/sodiation process and their low intrinsic electronic con- ductivity limit their applications. To solve the problems of TMOs, carbon-based metal-oxide composites with complex structures derived from metal-organic frameworks （MOFs） have emerged as promising electrode materials for LIBs and SIBs. In this study, we adopted a facile interface-modulated method to synthesize yolk-shell carbon-based Co3O4 dodecahedrons derived from ZIF-67 zeolitic imida- zolate frameworks. This strategy is based on the interface separation between the ZIF-67 core and the carbon-based shell during the pyrolysis process. The unique yolk-shell structure effectively accommodates the volume expansion during lithiation or sodiation, and the carbon matrix improves the electrical conductivity of the electrode. As an anode for LIBs, the yolk-shell Co3O4/C dodecahedrons exhibit a high specific capacity and excellent cycling stability （1,100 mAh.g-1 after 120 cycles at 200 mA-g-1）. As an anode for S1Bs, the composites exhibit an outstand- ing rate capability （307 mAh-g-1 at 1,000 mA-g-1 and 269 mAh.g-1 at 2,000 mA-g-1）. Detailed electrochemical kinetic analysis indicates that the energy storage for Li＋ and Na＋ in yolk-sheU Co3O4/C dodecahedrons shows a dominant capacitive behavior. This work introduces an effective approach for fabricating carbon- based metal-oxide composites by using MOFs as ideal precursors and as electrode materials to enhance the electrochemical performance of LIBs and SIBs.

Brushless direct current (BLDC) permanent magnet (PM) synchronous motors are in high demand for ventilator applications owing to their high speed, high efficiency, and other significant features. However, it has become an important problem in eddy current loss calculations with high-speed motors, which leads to low motor (ventilator) life and PM demagnetization. This paper focuses on the eddy current loss calculation and the structure improvement design for the two-pole 90 W, 47,000 r/min toothless BLDC motor. First, the influencing factors of eddy current loss are comprehensively investigated, and a multiparameter improvement methodology is proposed accordingly. Second, by finite element analysis (FEA), the effective winding length ratio and the number of parallel wires were mainly researched for the winding, and the influence on the eddy current loss and the efficiency was determined, providing a reference for BLDC high-speed motors. This study has resulted in a 34.75% reduction in the winding losses, and a 4.6% increase in the efficiency of the improved model compared with the original design. Third, the new rotor structure is proposed, saving PM volume 15% more than original. THD of gap flux density is decreased 20.97%; the eddy current loss in the new rotor is decreased 22% more than original. Furthermore, by coupling simulation of the magnetic–thermal field, the maximum temperature of winding of the improved model is 13.4% lower than that of the original model at the thermal steady state. Finally, the electromagnetic and thermal properties simulation results were verified by testing the prototype. It is of great significance to the structure design and efficiency improvement of the BLDC high-speed motor.