This study proposes a multilayer equivalent thermal analysis method, based on flow boundary layer theory, considering the computational problem of three-dimensional (3D) conjugate heat transfer analysis of a transmitting antenna cold plate. To cut down computational overhead, a stratification strategy is introduced to build an equivalent model, such that the 3D conjugate heat transfer problem can be transformed into a multilayer two-dimensional (2D) heat transfer (M2DHT) problem. For the iterative analysis of the M2DHT, the equivalent heat transfer coefficient was introduced as the link between layers. Based on the Prandtl boundary layer theory, convective heat transfer coefficients of the boundary layer with temperature-independent fluid properties were deduced, further improving the accuracy of the 2D conjugate heat transfer analysis. The multilayer equivalent analysis method addresses the shortcomings of the heat transfer coefficient calculation through tedious 3D analysis. With well-set proper convective heat boundaries configured, iterative computation via M2DHT is utilized to resolve the surface temperature field of the cold plate. Numerical simulations demonstrate that the presented approach accurately characterizes temperature distributions while substantially boosting computational efficiency in thermal evaluations of cold plates for transmitting antennas.

Manufacturing and environmental uncertainties can significantly affect the electromagnetic (EM) performance of antenna-radome systems, leading to degradation in key indicators such as reduced transmission coefficient, increased boresight error, and shortened radar detection range. To efficiently and accurately quantify these effects, this study proposes a combined strategy that integrates the Physical Optics-based Surface Integral (PO-SI) method with Interval Analysis (IA). The PO-SI method enables accurate modeling of complex radome structures, while IA estimates the upper and lower bounds of EM performance fluctuations by accounting for both manufacturing errors and environmental uncertainties. Compared to Geometric Optics-based methods, the proposed approach (PO-SI-IA) produces more accurate results that closely align with measured data, without reliance on extensive Monte Carlo sampling. Numerical simulations and microwave anechoic chamber experiments validate its accuracy and robustness. This work provides a reliable theoretical basis for uncertainty performance analysis and offers an efficient and flexible tool for EM performance evaluation and design of antenna-radome systems in complex operational environments.

Blister damage in plate-type fuel elements alters coolant channel geometry and deteriorates heat transfer, threatening reactor safety. Based on typical geometry and operating parameters of the JRR-3M research reactor, this study employs CFD to systematically investigate the effects of blister location, size, and number on flow and heat transfer. Results show that vortex structures generated between multiple blisters enhance local fluid mixing, leading to a slight reduction in maximum cladding temperature compared to a single blister. However, all blister conditions cause a significant increase in flow resistance. Sensitivity analysis indicates that blister size has the greatest impact, followed by the number of blisters, while the axial position has a negligible effect. In narrow rectangular channels with high flow velocities, the primary risk of blister damage shifts from the traditional “thermal crisis” to “increased flow resistance” and flow instability, providing a new quantitative perspective for the safety monitoring and assessment of research reactors.

For long-range and high-power microwave wireless power transmission systems, the end-to-end transmission efficiency is extremely important. To achieve this goal, high beam collection efficiency is required. And a flat-top beam is desired to improve the rectenna efficiency. In addition, the heat dissipation of the transmitting antenna must be considered, due to the high power transmission. These requirements pose significant challenges for antenna designers. To deal with these problems, a multiobjective optimization design method of transmitting antennas for Microwave wireless power transmission (MWPT) is developed. This method gives a set of compromise solutions, showing the potential tradeoffs. Then, an antenna engineer can select the best compromise solution based on the practical requirements.

To address the challenge of achieving a unified dynamic evaluation of in-service performance for reflector antennas subjected to coupled wind disturbances, structural flexibility, and servo control, an end-to-end performance evaluation method based on integrated modeling is proposed. A disturbance–structure–electromagnetic–control integrated modeling framework is constructed, in which the fluctuating wind load, structural dynamics model, cascaded servo control, and end-to-end performance mapping model are unified within a state-space closed-loop system, thereby enabling time-domain dynamic evaluation from environmental excitation inputs to performance index outputs. The Davenport spectrum and harmonic superposition method are adopted to establish a stochastic fluctuating wind model, and structural disturbance inputs are formed through wind pressure linearisation and modal projection. A low-order flexible dynamic model of the reflector antenna is developed using finite element modal condensation, and a main-axis closed-loop control model is formulated by incorporating fuzzy active disturbance rejection control and notch filtering. By combining the best-fit parabolic surface, the weighted half-path-length difference, and the Ruze formula, an end-to-end mapping model that relates structural nodal displacements to electromagnetic performance degradation is established. The research demonstrates that the proposed method can effectively reveal the influence of wind speed, elevation angle, and flexible mode coupling on antenna performance. Furthermore, a performance evaluation system developed based on this method integrates parameter input, simulation computation, and result output, providing an effective tool for antenna design optimization and performance assurance.

Recently, biomimetic porous structures have garnered significant attention due to promising application in thermal management systems. However, flexible design and performance optimization remain challenges to the in-depth investigation of cold plate heat transfer enhancement. Triply Periodic Minimal Surfaces (TPMS), mathematically defined as implicit surfaces with minimal mean curvature, exhibit superior structure interconnectivity and a high surface-area-to-volume ratio, making TPMS structures particularly promising for advanced fluid cooling applications. In cold plate design, the geometric configuration determines the fluid flow direction, which in turn strongly influences the heat transfer pathway. This study advances the design and optimization of TPMS cold plates, with particular attention to Gyroid and Diamond structures. A high-degree-of-freedom modelling framework is developed to generate TPMS variants with different periods and shell thicknesses using a small set of control parameters. The qualitative and quantitative relationships among geometric characteristics are systematically investigated. A material interpolation model is constructed to realize meshless numerical calculations and validated for accuracy. Subsequently, a multi-objective optimization problem is formulated based on the non-gradient NSGA-II algorithm, targeting both the average surface temperature of the heating source (overall thermal performance) and standard deviation of temperature (temperature uniformity). The adaptively optimized designs reveal that employing a small and uniform period along the mainstream direction enhances overall heat transfer performance, whereas a gradually decreasing period contributes to improved temperature uniformity. Besides, a gradually increasing shell thickness benefits both thermal metrics. Compared to the regular TPMS designs, the optimized Gyroid structure achieved a maximum reduction of 7.80 K (2.24%) in mean temperature and 3.78 K (32.98%) in standard deviation of temperature, whereas the optimized Diamond structures yielded respective reductions of 1.86 K (0.55%) and 5.09 K (46.53%). The proposed method effectively reduces the geometrical modelling and numerical analysis costs of flexible design and performance optimization for TPMS structures, and further extends their application potential.

To enhance the hydrothermal performance of cold plates, this study constructs a topology optimization framework that integrates conjugate heat transfer principles, aiming to maximize heat generation and minimize fluid flow dissipation. The robustness of the design is improved through the application of projection and density filtering techniques, with the projection intensity value incrementally increased via a parameter scanning method to bolster numerical convergence. The inlet and outlet distribution of the cold plate, aligned along its centerline, is determined through various target weight combinations, generating clear, continuous layouts. To further substantiate the effectiveness of the optimized configuration, a topology optimization design employing an objective function weighting factor of 0.7:0.3 is chosen to create the three-dimensional geometry of the cold plate. A parallel flow channel design, maintaining an identical fluid volume fraction and heat transfer boundary length, is introduced for comparative analysis. Moreover, performance indices such as surface temperature, pressure drop across the channel, average Nusselt number, and thermal resistance are assessed for two cold plates under varying inlet velocities. Both simulations and experiments indicate that the hydrothermal performance of the developed topological structure significantly surpasses that of the conventional parallel channel design, a disparity that amplifies with increasing inlet velocities.

With the continuous increase in the aperture of reflector antennas, their structural natural frequency decreases and damping becomes smaller, leading to a narrower servo bandwidth. Meanwhile, under the influence of external environmental disturbances, the traditional PID control algorithm can no longer meet the high pointing and tracking accuracy requirements of antenna servo systems. Accordingly, this paper presents a parameter self-tuning PID control algorithm based on an RBF neural network. By leveraging the adaptability and self-learning ability of the RBF neural network, the control parameters of the model are adjusted automatically. The structure of the RBF neural network is constructed, and the iterative formulas for updating both the neural network parameters and the PID parameters are derived using the gradient descent method. Simulation results indicate that the proposed algorithm not only significantly improves the dynamic performance of the antenna servo system but also exhibits strong disturbance rejection capability and robustness.

In this letter, we present a frequency-independent electromechanical coupling analysis method for terahertz dualreflector antennas, enabling efficient evaluation of electrical performances across multiple frequency bands while maintaining constant computation time. Initially, the phase function of the Physical Optics (PO) integral is linearized to overcome the complex integration forms. Subsequently, the oscillatory behavior inherent in the PO integral is eliminated using the Numerical Steepest Descent Path (NSDP) algorithm, from which a closedform expression for the Frequency-Independent Physical Optics (FI-PO) method is derived. Finally, the FI-PO method is integrated with the electromechanical coupling analysis to accurately compute the electrical performances of deformed antennas. This approach not only streamlines the electromechanical coupling analysis process but also dramatically reduces computation time in the terahertz band. In a representative example, a 97% reduction in computation time is achieved at 0.5 THz, while maintaining high accuracy in both the main and side lobes.

This article proposes a fast and effective method to analyze the scattering characteristics of large array structures based on the infinitesimal dipole model (IDM). Different from the traditional method of analyzing the entire array, this method uses the scattering field of isolated elements to obtain the scattering characteristics of the entire array structure. The characteristic weight coefficient (CWC) that characterizes the scattering characteristics of the isolated element is derived. Based on the IDM, the mutual coupling effect between elements is characterized, and the actual excitation coefficient of each element in the array environment is obtained. The proposed method can handle the scattering problem of large array structures. Due to using infinitesimal dipoles (IDs) instead of traditional mesh analysis, the computational complexity is significantly reduced and more suitable for analyzing large arrays. The correctness and effectiveness of the proposed method are verified through numerical examples and experiments.

A design of dual-linear-polarization microstrip phased array antenna with low cost is proposed in this paper. The antenna is based on the class of the aperture-coupled stacked patches. One antenna unit is fed by two H-shaped slots. The antenna is composed of one feeding network, one primary radiation path, one parasitic radiation path and two support structures. The antenna is low-cost and low profile, all the components of the antenna are processed with cheap material and are easy to assemble. An antenna working in X band is designed to verify the idea. When the standing wave ratio is less than 2, the proposed antenna can reach +/- 30 degrees scanning angle of horizontal plane and vertical plane within the working bandwidth of 4.0GHz. The gain in bandwidth is greater than 3.4 dB, and the isolation is above 16.0 dB. Based on the designed antenna unit, a 4x4 array is constructed and simulated; the simulated results show that the operating bandwidth is about 4.0GHz (8.0-12.0 GHz). At 10.0 GHz, the isolation between the ports is -24.5 dB, the cross-polarization level is less than -31.8 dB compared with the co-polarization level, and the realized gain can reach 15.7dBi.

Performance evaluation of liquid cooling plates is crucial for ensuring the reliable and stable operation of electronic devices. The evidential reasoning (ER) rule, an effective method for handling uncertain information, has been widely applied in this context. Traditional ER methods, however, face limitations in liquid cooling plate performance evaluation due to dynamic input variations and the challenges of integrating multisource, time-delay correlated indicators. In order to overcome these challenges, this article develops an ER rule with time-delay correlation (ER-TDC). A directed graph model of the liquid cooling system is first constructed to calculate the theoretical outlet flow rates and temperatures. Residuals are then obtained by comparing these with measured values, ensuring that the data used for performance evaluation remain unaffected by condition fluctuations. In order to enhance fusion stability and reduce uncertainty in evaluation results, a fusion sequence determination method that accounts for time delays is introduced. Additionally, the traditional ER rule is improved to refine the calculation of evidence parameters, incorporating the relative total dependence coefficient (RTDCD) as a discount factor to facilitate the effective fusion of time-delay correlated information sources, thereby generating belief distributions and expected utilities. Finally, some experiments on liquid cooling plates are performed to validate the effectiveness and feasibility of the proposed method. Experimental results show that the proposed method exhibits robust and practical performance under dynamic conditions and provides an efficient and reliable solution for performance evaluation of complex engineering systems.

To enhance the intelligence and digital management level of radio telescopes and ensure the safe and stable operation of antennas, this paper proposes a real-time state evaluation method for the antenna structure of radio telescopes based on digital twin (DT) technology. Firstly, based on the five-dimensional model of DT, a digital twin system (DTs) framework for radio telescopes is designed. Secondly, the quadric error metrics (QEM) mesh-simplification algorithm and mesh-reconstruction technology are employed to obtain a lightweight twin model of the antenna. Furthermore, a random forest (RF) regression surrogate model is established using finite element point cloud data samples. The K-nearest neighbor (KNN) algorithm and radial basis function (RBF) interpolation algorithm are utilized to construct the virtual–physical mapping model of the antenna, enabling rapid prediction and evaluation of the antenna structure state. Finally, a DT for real-time antenna structure state evaluation is developed using the Unity3D engine, with an experimental prototype of a reflector antenna as the object. Experimental results show that the average prediction accuracy of the physical field surrogate model of the system is 0.98, and the average computation time is 0.4 s. The system meets the precision and computational efficiency requirements for the real-time and accurate evaluation of the antenna structure state.

This letter proposes a method for rapid analysis of the scattering characteristics of large-scale arrays based on the regional decomposition strategy. To achieve array analysis, traditional infinitesimal dipole model methods use equivalent elements to characterize the mutual coupling effects between array elements. However, when the array is large, solving the mutual coupling matrix is often limited by hardware resources. This method utilizes the elements' electromagnetic periodicity and the diffracted waves' matching conditions, and derives the maximum subarray size based on the Floquet periodicity theorem. Treating the subarray as a new array element and reconstructing the mutual coupling matrix enable rapid array analysis within limited computing resources and are more suitable for scattering analysis of large-scale arrays. Numerical examples and comparisons with the literature verify the effectiveness and correctness of the proposed method.

Active adjustment technology is used to solve the problem of reduced electrical performance of large reflector antennas caused by environmental factors. This technology is crucial for the operation of antennas under high-frequency working conditions. This paper proposes a full-path active adjustment strategy for dual-reflector antennas. This strategy takes into account the working mode of the adjustment mechanism under comprehensive influencing factors and achieves the optimal receiving performance at the full elevation by changing different adjustment algorithms. First, the relationship between the displacement of reflector and the wavefront phase was established based on geometric optics. Second, three adjustment algorithms of the double reflector antenna were compared and analyzed: based on the standard, the fit and the optimal parabolic surface, the calculation process of the adjustment amount was derived. An adjustment strategy model for multiple working conditions was proposed by introducing the elevation and the complexity coefficient and combining three adjustment algorithms. Finally, a finite element analysis was conducted on the dual-reflector antenna with a diameter of 110 m, and the advantages and disadvantages of different adjustment algorithms were compared. The results show that strategy model not only achieves the optimal state of the antenna at the full elevation, but also shortens the adjustment amount of the adjustment mechanism and improves the working efficiency of the antenna under various working conditions.

Scattering analysis for flexible frequency selective surfaces (FSSs) is important. The infinitesimal dipole model (IDM) method can achieve high computational efficiency in scattering analysis. However, the complex preprocessing essentially limits the popularization and application of this method in large-scale computational problems. In this letter, an innovative method based on the IDM and backpropagation neural network (BPNN) is proposed to address the limitations of flexible FSS. First, the constrained infinitesimal dipole is solved by singular value decomposition, and the unit information in the FSS is restored by model reconstruction. Afterward, the BPNN was used to learn the dipole generation process, further improving efficiency. The simulation and measurement results demonstrate that the proposed method yields results comparable to those of the traditional method in terms of calculation accuracy. This letter presents a novel solution to the problem of FSSs in electromagnetic simulations and demonstrates the potential of deep learning technology in electromagnetism.

The infinitesimal dipole model (IDM) is a crucial method for analyzing the electromagnetic characteristics of antennas. This article proposes a new approach to analyzing the admittance matrix of an antenna array, incorporating high-order mutual coupling effect, based on the IDM. First, the radiating element is modeled as a group of infinitesimal dipoles. Second, the mutual admittance between two arbitrary radiating elements is calculated using the reaction theorem, considering only first-order coupling effect. Third, starting from the mechanism of multipole electromagnetic scattering in a typical two-element array, the admittance matrix that includes high-order coupling effect is derived in detail. Consequently, the admittance matrix for an N-element antenna array is obtained. Numerical and experimental cases are presented to validate the proposed method.

This letter proposes a method for analyzing the scattering characteristics of cylindrical conformal arrays with variable curvature based on the infinitesimal dipole model. This method uses osculating circles to fit the variable curvature array structure, controls the number of osculating circles, constructs feature elements by setting the fitting error threshold, and constrains the infinitesimal dipole in the cylindrical coordinate system to better match the feature elements. The proposed method considers the influence of array element structure deformation and mutual coupling effects, reduces the preprocessing time of equivalent elements one by one, and can accurately evaluate the scattering characteristics of variable-curvature conformal arrays. The measurement results of two examples verify the correctness of the proposed method.

Vibration isolation under low-frequency and large-amplitude conditions remains a significant challenge in engineering applications. Existing symmetric quasi-zero stiffness(S-QZS) or asymmetric quasi-zero stiffness(A-QZS) isolators often suffer from limited quasi-zero stiffness(QZS) regions and complex structural configurations. To address these issues, this paper proposes a novel metamaterial isolator design with A-QZS characteristics. The core innovation lies in generating a variable cross-section curved beam by rotating a trigonometric function curve about a spatial axis, enabling the structure to exhibit A-QZS behavior under vertical loading. This approach results in a structurally simple and easily manufacturable isolator. Based on comprehensive static and dynamic modeling, the stiffness characteristics and transmissibility performance of the A-QZS isolator are analyzed and compared with those of a conventional S-QZS isolator. Results show that the A-QZS design significantly broadens the QZS region. Under an excitation of 0.2g, the peak transmissibility and onset isolation frequency are reduced by 40.97 % and 42.01 %, respectively, compared to the S-QZS design, with enhanced dynamic stability. Furthermore, the advantages of A-QZS become more pronounced as the excitation amplitude increases.This study not only extends the application of QZS principles in metamaterial structural design but also provides a new design paradigm for achieving high-load, low-frequency, broadband vibration isolation, demonstrating strong potential for use in aerospace, precision instrumentation, and heavy machinery.

The application of data-driven fault diagnosis in structural health monitoring (SHM) encounters several challenges. One major obstacle is obtaining a large quantity of accurate fault samples in certain scenarios. Additionally, the complexity of working environments exacerbates the difficulty of diagnostics due to significant distribution disparities among samples from different environments. This paper proposes a manifold alignment method based on manifold distance features (MDFMA), aiming to address the issue of insufficient fault samples during the fault diagnosis process. Initially, a simulated physical model of the monitoring object is established to generate a large number of simulated fault samples. These are supplemented with a small number of actual fault samples and then merged into a training dataset. Subsequently, the training samples undergo reconstruction employing the shortest manifold distance feature. Then the cosine similarity (COS) measuring method is applied to calculate the similarity between simulated and actual samples, thereby facilitating cross-domain feature alignment. Finally, all sample points are projected into the labeled space, and the manifold alignment (MA) method is employed to predict the state of the monitoring subject. The experiments conducted on the liquid-cooled plate confirmed the effectiveness and feasibility of the proposed method. The results demonstrate that this approach exhibits superior robustness and applicability in practical applications compared to other manifold alignment methods.