To address the problem of neglecting load uncertainties and structural deformation in conventional support reaction calculations for full-scale aircraft static tests,this paper proposes a novel approach based on modu-lar transfer learning for accurately predicting high-load support reactions.The proposed method introduces a modular transfer learning framework in which separate models are developed to account for loading uncertainties.A primary prediction model is first established using historical test data to extract general static testing characteristics.Subse-quently,a residual correction model trained with low-load data from the current test condition is integrated,enab-ling adaptation and correction of prediction errors specific to the present testing scenario.Additionally,to explicitly consider structural deformation effects,a binomial regression technique is employed to estimate loading-point coor-dinates at high-load levels,facilitating accurate determination of loading directions.By combining these coordinates with spatial force equilibrium equations,precise prediction of support reactions is achieved.The effectiveness and accuracy of the proposed method are validated through a full-scale static test case involving a representative verifica-tion aircraft.Comparative analyses demonstrate that,compared with traditional rigid-body assumptions,the devel-oped method significantly enhances the prediction accuracy for high-load stages,thereby providing robust theoretical and technical support for support reaction estimation in large-scale and complex testing environments.
To reduce the mass and manufacturing cost of phased array antennas while ensuring stable radiation per-formance under harsh operating conditions,this paper proposes a multi-objective surrogate optimization algorithm based on the Kriging model—MOAK.The algorithm integrates a feasible-region exploration criterion with a TCF-SMOTE criterion to form a hybrid infill strategy.The feasible-region exploration criterion enables effective identifica-tion of the global feasible space,after which the innovative TCF-SMOTE criterion is employed to construct a com-plete Pareto front,thereby achieving high-accuracy Pareto-optimal solution sets.Specifically,the TCF-SMOTE cri-terion suppresses extreme constraint violations in Kriging model construction through a truncated constraint function(TCF),mitigating model distortion near feasible-domain boundaries.In addition,the SMOTE algorithm is applied to generate synthetic sample points,increasing the number of Pareto solutions(PS)and improving the completeness of the Pareto front(PF).Comparative experiments on three standard benchmark functions demonstrate that the MOAK algorithm significantly outperforms conventional surrogate-model-based optimization al-gorithms,alleviating the problems of sparse PS distribution and incomplete PF characterization.When applied to the optimization design of the pre-skeleton of a phased array antenna,MOAK provides diverse solutions for balan-cing structural lightweighting,cost,and radiation performance,thereby meeting different design preference require-ments.In a representative optimized design,MOAK achieved a 35.4%reduction in mass,an 80.2%reduction in cost,and an 84.91%reduction in computation time,while maintaining stable radiation performance.
Studying the dynamic characteristics of the vehicle during the water-exit process through ice-breaking has significant scientific value and engineering significance for improving its performance and ensuring the safety of polar missions.Focusing on the dynamic characteristics of ice fragmentation and impact loads during the water-exit process of a vehicle breaking through ice,this paper establishes a numerical simulation method for the ice-vehicle-water coupling interaction based on the ALE algorithm and the penalty function contact algorithm.The dynamic characteristics under different launch velocities and dual-vehicle launch conditions are investigated,and the ice fragmentation characteristics and vehicle load characteristics during the water-exit process are obtained.The research results show that the water-exit process of the vehicle breaking through ice can be divided into three stages.The load on the vehicle mainly consists of fluid force and contact force,with the peak contact force reaching 2 600 kN and the peak fluid force reaching 1 400 kN.The fluid force on the dual-vehicle configuration is reduced by 50%compared with that on the single-vehicle configuration during ice-breaking.As the launch velocity increa-ses,the velocity decay rate of the vehicle gradually decreases.When the launch velocity is 50 m/s,the velocity de-cay rate is 5.98%.The research results can provide theoretical basis and technical support for underwater launch engineering of vehicles in polar environments.
Single-cell culture has long posed a significant challenge and remained a hot topic in biomedical engi-neering.To address the limitations in existing microfluidic single-cell chips,where cell culture space is constrained by the capture zones——impeding long-term cultivation.This study presents a capture-culture dual-zone integrated microfluidic chip,which integrates cell capture and culture functional region within a single unit.Through optimized chip layout design,the device achieves a microsphere capture rate of 91.93%and a cell capture rate of 60.1%.This study employs mouse fibroblast L929 cells(average diameter:10 μm)as the model system,establishing a hydro-dynamic flow model of cell suspension within the chip through theoretical calculations and computational simulations.To ensure cell viability,a microchannel width of 60 μm achieves optimal capture efficiency.To validate the chip performance,under conditions of a cell(or microsphere)input density of 1×105 cell/mL and a flow velocity of 300 μm/s,the cells exhibited stable post-entry conditions.With a microchannel width of 60 μm,the chip achieved both high capture efficiency and single-cell isolation rates,yielding a robust single-cell microflu-idic device with stable bonding.This chip demonstrates a simple structure and straightforward fabrication process,serving as a novel tool for single-cell analysis and research.
A light helicopter is widely used in low-altitude transportation.How to improve gear transmission effi-ciency and enhance the smoothness,durability and reliability of the traditional face gear transmission system are ur-gent problems to be solved.To carry out the weight reduction and dynamic characteristic analysis of the face gear body structure,the paper proposes a face gear body structural lightweight optimization design method that combines topological optimization and parametric optimization.The 3D model of the face gear was established with the finite element method.The solid isotropic material with penalization topological optimization and the sensitivity analysis of the face gear body structure were carried out to select the key design parameters.The multi-objective genetic algo-rithm was used to realize the multi-objective parametric optimization.The optimization results show that after topolo-gical optimization,the mass of the face gear body is reduced by 35.34%,that the maximum equivalent stress de-creases by 15.44%and that the maximum axial displacement of the face gear rim decreases by 29.19%.The trave-ling wave resonance analysis indicates that no-nodal diameter resonance points are within the working rotational speed range of the face gear body,significantly enhancing its strength and axial stiffness.
