To achieve intelligent optimization of cavitation characteristics in fuel centrifugal impeller, this study proposes a novel multi-stage Kriging-Based approach. The core innovation lies in establishing a three-stage adaptive sampling strategy based Kriging model utilizing Mean Squared Error (MSE), Expected Improvement (EI), and Cross-Validation (CV) strategy, with clearly defined transition thresholds between stages. The approach is preliminarily validated through comprehensive testing on one-dimensional and multi-dimensional mathematical functions, demonstrating superior performance compared to conventional single-stage approaches. The benchmark results demonstrate that the proposed multi-stage sampling strategy significantly outperforms existing single-stage counterparts, achieving superior convergence speed and enhanced prediction accuracy across comparative evaluations. The practical application to an aviation fuel centrifugal impeller design demonstrates significant improvements in cavitation performance, including a 13.19% reduction in the net positive suction head required, a 13.78% decrease in the Thoma cavitation number, and a 12.53% increase in cavitation specific speed. Moreover, flow field simulation demonstrates that the optimization impeller flow characteristic is more excellent, in which the pressure loss including back-flow and leakage vortex at the inlet is reduced and the pressure distribution in the volute is more uniform. These results conclusively demonstrate the effectiveness of the proposed approach in enhancing the cavitation characteristic of centrifugal impeller.

To overcome the prohibitive computational cost of high-fidelity CFD simulations and the inefficiency of traditional methods in the cavitation reliability assessment of fuel centrifugal pumps, this paper presents an efficient reliability analysis framework named AK-IEI-MCS. The core innovation lies in a novel Improved Expected Improvement (IEI) learning function that adaptively concentrates sampling efforts near the limit state surface (LSS) to minimize high-fidelity model evaluations. Application to the cavitation reliability assessment of a fuel centrifugal pump demonstrates a quantified failure probability of 5.6308×10-4 with superior efficiency. The results confirm that the framework significantly reduces computational costs while supporting the reliable design of aerospace fuel systems.

Natural language-based control commands for large-scale UAVs hold promise in applications such as voice-centric air traffic control (ATC) environments, single-operator management of multiple UAVs, and eVTOL taxi services. Large language models (LLMs) can enable command translation, knowledge base queries, and contextual understanding of diverse phrasings, while providing operational recommendations. However, challenges including speech recognition errors, harmful command inputs, and timeout issues hinder practical deployment. This paper proposes an LLM-based UAV interaction agent designed to parse commands from both UAV cockpits and ATC systems, while generating actionable operational advice. We evaluated multiple LLM variants and implemented engineering optimizations to improve recognition accuracy and response speed. Surveys with UAV stakeholders indicate that LLM-driven systems partially meet operational requirements but underscore the need for improvements in training methodologies and accuracy. These findings highlight the potential of LLMs in onboard UAV communication while emphasizing unresolved technical challenges requiring further refinement.

A Monte Carlo reliability analysis method based on generalized stress-interference was proposed in order to determine the influence of wear characteristics on the reliability of sliding valves in the fuel system of an aero-engine. The influence of key parameters on the reliability of sliding valves was analysed based on the establishment of wear depth model. The mapping relationship between wear depth and wear volume of sliding valve was determined by Archard wear model and spool stress analysis results. The limit state equation was established based on generalized stress-interference theory, and the basic random variables affecting wear depth were clarified. The wear reliability of sliding valves for a certain engine type was simulated and analysed by the proposed Monte Carlo reliability analysis method. Simulation results show that: the iterative error of the coefficient of variation of the reliability calculation is less than 10(-7), and the calculation results converge; the wear reliability is basically unaffected by the spool diameter; the wear reliability decreases slightly with the increase of the wear coefficient K; in addition, with the increase of the hardness of the material, the wear reliability is improved, but the influence decreases to a certain value.

To overcome the high computational cost and low iteration efficiency in optimizing fuel centrifugal pumps, this paper presents a parallel adaptive optimization framework based on an adaptive Kriging surrogate model.The core innovation lies in a Two-layer Search Strategy (TSS) that combines local error analysis and a global sample-density criterion for adaptive sampling and parallel model updating.Implemented in a self-developed CFD-optimization integrated platform, the proposed approach significantly reduces computation time in multi-core environments.Application to a fuel centrifugal pump demonstrates efficiency improvements of 6.47%, 6.17%, and 4.97% under low, design, and high flow conditions, respectively, confirming that TSS enhances both accuracy and efficiency for complex turbomachinery optimization.

Cavitation in aviation fuel centrifugal pumps can lead to impeller erosion and performance degradation, posing significant reliability risks. To efficiently assess low-probability cavitation failures under multidimensional uncertainty, this study proposes a surrogate-based reliability analysis framework named AK-IEI-SSIS, which integrates Kriging modeling, an Improved Expected Improvement (IEI) learning function, and Subset Simulation Importance Sampling (SSIS). The framework adaptively refines sampling near failure boundaries to enhance accuracy and computational efficiency. Its performance is validated through multiple benchmark cases involving nonlinear and high-dimensional systems. A Python-based parametric platform is also developed to orchestrate parametric modeling, meshing, CFD simulation, and reliability analysis. Applied to an aviation fuel centrifugal pump, the framework accurately quantifies cavitation-induced failure probabilities as low as 5.63 x 10-4 using only 202 CFD evaluations, achieving a 99 % reduction in computational cost compared to Monte Carlo methods. Although demonstrated on a specific pump, the framework is applicable to reliability assessment of rotating fluid machinery under uncertainty, supporting reliability analysis and maintenance planning for next-generation aerospace propulsion systems.

In order to clarify the performance degradation problem of fuel centrifugal pumps, a stochastic process-based performance degradation model modeling method is given with an aero-engine fuel centrifugal pump as the object of study, and the reliability assessment is carried out. First, the degradation modeling method based on stochastic process is given. Secondly, PumpLinx is utilized to obtain the performance degradation data of the centrifugal pump and perform data processing. Gamma and Wiener stochastic process models are given based on MATLAB. Finally, based on the centrifugal pump performance degradation data for centrifugal pump reliability assessment, and compare and analyze the advantages and disadvantages of the two modeling methods, and found that the degradation modeling method based on the Gamma process is more suitable for centrifugal pump reliability assessment.

Leveraging distributed data from various clients to tackle target issues has become a prominent trend in fault diagnosis. However, the growing concerns about data privacy have gained significant attention in the research community. Addressing this, a self-paced decentralized federated transfer framework is developed for diagnosing faults in rotating machinery across diverse domains. To improve efficiency and enhance security in data privacy protection, a decentralized federated optimization strategy is formulated to address communication challenges across varied data domains. Initially, pre-trained source models extract self-supervised information from the target client data and utilize the self-paced mechanism to integrate this information into auxiliary models. At the same time, this paper employs a nonlinear hashing mapping scheme to encode features from the target client. Subsequently, contributions of different source models are assessed to determine their respective weights. The federated source models, along with auxiliary models, are then weighted appropriately to integrate the final target model. Finally, the obtained target model and encoded target features are transmitted back to the source clients for updates and feature alignment, with iterations continuing until convergence is reached. Thus, the proposed framework effectively addresses the gap in data distribution while ensuring data privacy protection. Comprehensive experiments validate the effectiveness and security of the proposed framework for fault diagnosis.

In the fuel system of an aircraft engine, aero-fuel centrifugal pumps are widely utilized as boost pumps. In this research, we propose the integration of an inlet injector with an aero-fuel centrifugal pump to optimize its flow characteristics and enhance performance. The key geometric parameters of the impeller, volute, and injector are meticulously designed. The effectiveness of our approach is validated through a combination of experimental and numerical analysis, which involves comparing simulation results with experimental data. The findings demonstrate that the presence of the injector significantly impacts the flow characteristics and hydraulic performance of the pump. Specifically, it effectively reduces flow losses in the specific channels of the impeller and volute. Furthermore, the injector enhances the regulation of the inlet flow fields by adjusting the inlet pressure and controlling the suction flow direction. Consequently, the pump's efficiency is enhanced when equipped with the injector compared to its performance without it. Therefore, incorporating an injector in an aero-fuel centrifugal pump has a positive effect on regulating flow characteristics and improving hydraulic efficiency.

为了研究长中短复合叶片对小流量工况下燃油离心泵非定常特性的影响规律,基于CFD技术对某型燃油离心泵进行了非定常数值模拟.首先,分别建立原型方案和带有长中短复合叶片的优化方案的离心泵三维模型和网格模型.其次,基于RNG k-ε湍流模型,对两个方案中泵内流动非定常特性进行数值计算.仿真结果表明:长中短复合叶片减弱了叶轮流道内的大尺度漩涡,降低了叶轮的出口滑移,使得压力分布更加均匀.同时,叶轮与隔舌的动静干涉造成了蜗壳内一定程度的压力脉动产生,且长中短复合叶片的压力脉动幅值相对较低.另一方面,小流量工况下,优化方案中离心泵的增压值为12.9MPa,效率为26.9％,比原型方案中离心泵的增压值和效率分别提高了3.5％和2.6％.

To clarify the transient flow characteristics of a high-speed aero-fuel centrifugal pump in variable gas-liquid ratio conditions, numerical simulations for the internal flow field in design flow rate and small flow rate conditions are conducted, focusing on the transient flow characteristics and time-frequency performance of pressure pulsation in the impeller channel. The conversion relationship between gas-liquid ratio and inlet pressure is given to determine the inlet simulation boundary, and then the grid model and length of time step are checked for relevant test. The prediction results between simulations and test are given to verify the effectiveness of the adopted simulation method. Then, the transient characteristics are analyzed through the results of pressure contour and turbulent kinetic energy, and the time-frequency performances of pressure pulsations at impeller inlet and outlet are conducted by fast Fourier transform(FFT). The results show that the flow in the impeller channel is relatively stable under the fuel saturation condition, and the main frequency of pressure amplitude is rotation frequency. With the increase of gas-liquid ratio, the impeller inlet produces a low-pressure zone whose area is significantly enlarged. Besides, a certain wake flow zone is generated at impeller outlet, where the turbulent energy dissipation rate is also demonstrated to be the strongest at these zones. Moreover, the inlet pressure is generally decreased with the increase of gas-liquid ratio, and the main frequency at the design flow rate is rotation frequency, but other frequency multiplication appears at the small flow rate. Meanwhile, the wake flow at the impeller outlet does not seriously affect the main frequencies at the monitoring points, where the main frequency is still rotation frequency.

IntroductionLignin is a complex aromatic polymer plays major biological roles in maintaining the structure of plants and in defending them against biotic and abiotic stresses. Cinnamoyl-CoA reductase (CCR) is the first enzyme in the lignin-specific biosynthetic pathway, catalyzing the conversion of hydroxycinnamoyl-CoA into hydroxy cinnamaldehyde. Dalbergia odorifera T. Chen is a rare rosewood species for furniture, crafts and medicine. However, the CCR family genes in D. odorifera have not been identified, and their function in lignin biosynthesis remain uncertain.Methods and ResultsHere, a total of 24 genes, with their complete domains were identified. Detailed sequence characterization and multiple sequence alignment revealed that the DoCCR protein sequences were relatively conserved. They were divided into three subfamilies and were unevenly distributed on 10 chromosomes. Phylogenetic analysis showed that seven DoCCRs were grouped together with functionally characterized CCRs of dicotyledons involved in developmental lignification. Synteny analysis showed that segmental and tandem duplications were crucial in the expansion of CCR family in D. odorifera, and purifying selection emerged as the main force driving these genes evolution. Cis-acting elements in the putative promoter regions of DoCCRs were mainly associated with stress, light, hormones, and growth/development. Further, analysis of expression profiles from the RNA-seq data showed distinct expression patterns of DoCCRs among different tissues and organs, as well as in response to stem wounding. Additionally, 74 simple sequence repeats (SSRs) were identified within 19 DoCCRs, located in the intron or untranslated regions (UTRs), and mononucleotide predominated. A pair of primers with high polymorphism and good interspecific generality was successfully developed from these SSRs, and 7 alleles were amplified in 105 wild D. odorifera trees from 17 areas covering its whole native distribution.DiscussionOverall, this study provides a basis for further functional dissection of CCR gene families, as well as breeding improvement for wood properties and stress resistance in D. odorifera.

针对复合叶轮式燃油离心泵在设计中的叶轮型线复杂、难以实现快速迭代的问题,提出一种基于改进Bezier曲线的叶轮参数化设计方法,并进行了试验验证及性能仿真分析研究.引入比例系数来约束五点四次贝塞尔样条曲线的控制点参数,并采用该方法设计叶轮轴面轮廓型线.结合辅助叶片偏置设计方法,完成复合叶轮的参数化设计,并对某型燃油离心泵进行设计及三维建模.最后,通过外特性试验验证设计方法和仿真方法的有效性,并将改进Bezier曲线和未改进Bezier曲线设计的复合叶轮结果进行对比.结果表明:仿真与试验结果预测的扬程和效率误差均在5％以内,所提出的设计方法和采用的仿真方法是有效的.相比未改进的Bezier曲线,采用改进Bezier曲线设计的复合叶轮其内部流动更加平稳且水力损失更少.

In order to study the complex transient flow characteristics of a high-pressure aero-fuel centrifugal pump within its full working envelope, a certain type of centrifugal pump is numerically simulated, in which the simulation results are compared with the experiment results to verify the effectiveness of the present simulation method. Then, the verified simulation method is selected to analyze the transient flow characteristics, in which the time-frequency characteristic of pressure pulsation at monitored positions is analyzed by using fast fourier transform. In addition, the unsteady flow structures are studied by focusing on the relative speed, turbulent kinetic energy and so on. The results show that the main frequency of pressure pulsation in the impeller and volute is rotation frequency and blade frequency, respectively, where different monitoring points show similar trend. Meanwhile, the flow is relatively stable under design flow rate condition. However, a certain large-scale vortex appears in the impeller channel under small flow rate conditions, which mainly exists at the exit of the impeller channel near the tongue. In addition, turbulent kinetic energy at the exit of the impeller and the tongue has a large distribution range and changes seriously, where a certain hydraulic loss is produced.

Non-probabilistic reliability analysis is of great importance in both reliability measure and reliability based design, the efficiency and precision of non-probabilistic reliability analysis, as well as uncertainty quantification, have attracted great attention currently. In this study, considering the coexistence of correlated and independent uncertain-but-bounded variables in engineering applications, a multi-super-ellipsoidal model is used to quantify the uncertainties. Furthermore, inspired by both "norm" based reliability index and "volume-ratio" based reliability index, a hybrid non-probabilistic reliability index is derived to measure the reliability extent more accurately and intuitively. To improve the accuracy and efficiency of solving the hybrid non-probabilistic reliability index, an effective Kriging based hybrid active learning method (HALM) is further developed. Finally, four examples are used to verify the effectiveness and robustness of the proposed HALM. The results show that the selection of multi-super-ellipsoidal model has a certain effect on the estimation of reliability index. Compared with the sampling-based analysis method, HALM presents better performance in terms of the trade-of between in computational efficiency and accuracy.

This paper presents a model reference robust adaptive control method modified by projection theory for a variable cycle engine subject to modeling uncertainties and external disturbances. A new adaptive compensation control method is developed to improve the control performance of multivariable system which affected by uncertainty. A basic optimal LQR control law is compensated by the augmented model reference adaptive method under the framework of feedback control structure, to improve the dynamic and anti-interference performance of the system which affected by uncertainty. The simulation of the method is carried out with a turbo-fan engine model. The simulation results showed that: the controller designed by the new adaptive compensation control method effectively realizes the compensation of the system uncertainty and the tracking of the control command, and improves the control performance of the original LQR controller when the system is uncertain.

针对燃油离心泵高效、高抗汽蚀的优化设计问题,进行了基于损失模型和SQP(Sequen?tial Quadratic Programming)算法的多目标优化设计及仿真研究.建立表征叶轮和蜗壳等水力、容积和机械各效率的综合损失模型,并利用必需汽蚀余量来表征汽蚀特性.利用SQP算法构造合理的适应度函数,建立离心泵多目标优化数学模型.对燃油离心泵进行优化设计并与其它优化算法进行了对比,各优化算法的优化结果相似,但SQP算法优化求解的迭代步数相对较少.基于CFD技术进行仿真及外特性预测,验证燃油离心泵多目标优化设计方法的有效性.结果表明:相比传统方法,基于损失模型和SQP算法优化的离心泵流动损失更低,其进口流动更利于抗汽蚀性能;同时,优化的离心泵高效工作区域相对宽广,必需汽蚀余量相对较低,抗汽蚀性能有所改善.

This paper presents a high-speed aero-fuel centrifugal pump with an active inlet injector for an aero-engine aiming at regulating the internal flow field and improving overall hydraulic performance. Unlike most of the existing centrifugal pumps for aero-engines, an injector is designed and integrated with the pump to accomplish the active flow control. Firstly, by employing the energy equation in the pump, reasonable geometrical parameters of the injector are calculated. Then, a validation study is conducted with three known turbulence models, showing that simulations with the RNG κ-ε turbulence model can accurately predict the head and efficiency of the experimental pump. Finally, simulation results with the determined turbulence model are discussed. The results show that the static pressure is uniformly distributed inside the impeller, the volute and the injector. The flow field is significantly ameliorated by improving the pressure inside the suction pipe and controlling the flow direction via the injector. Furthermore, the head and efficiency of the designed pump with an active inlet injector are improved compared to the one without an injector.

以某型外啮合高压航空燃油齿轮泵为研究对象,推导齿轮理论强度校核计算公式及校核流程,对其齿轮进行强度校核;通过计算机CAD技术建立齿轮泵三维模型,基于ANSYS进行齿轮的动态啮合过程、静态接触应力、静态弯曲应力仿真;将3种仿真结果与理论校核结果进行对比,表明该仿真技术能够有效实现该型泵的应力仿真分析.应力分布结果表明:齿轮动态啮合过程中,最大应力发生在中心距中点位置和啮合线末端,且通过对2个位置的静态接触应力和弯曲应力仿真获取相应的齿面接触应力和齿根弯曲应力的啮合性能参数,再次验证齿轮的受力规律,对新一代航空发动机主供油泵的设计及仿真研究具有一定的工程实践意义.

针对齿轮泵的困油问题,给出一种齿轮泵卸荷槽的综合设计方法,并基于计算流体技术完成其内流场特性的仿真分析研究.首先,在某型外啮合齿轮泵基本结构基础上,对卸荷槽进行综合设计,提出具体的设计方法并给出设计结果;进而通过计算机CAD技术建立齿轮泵三维模型和流道模型,并利用Pumplinx进行该型齿轮泵的内流场特性模拟仿真,对比仿真结果与试验数据,误差在5％以内,验证了采用的仿真技术能够有效实现该型泵的特性分析;最后,将综合设计的卸荷槽与3种典型卸荷槽进行特性预测及对比,可以表明:相比其他3种典型卸荷槽结构,综合设计的卸荷槽可以有效地缓解齿轮泵啮合区域的困油压力,并减小齿轮泵的流量脉动,有效地改善了齿轮泵的困油现象.所得出的结论对高性能齿轮泵的设计及仿真研究具有一定的工程实践意义.