Documents published in Scipedia

• A Numerical Study of the Impact of Bending and Torsional Stiffness on the Static Aeroelastic Characteristics of a Large Aspect Ratio Composite Wing

  S. qiao, F. Wang, P. Wang

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (2), 26

  
  

  Abstract

  The bending and torsional stiffness influence structural deformation to varying degrees. Utilizing the coupled numerical method of Computational Fluid Dynamics and Computational Structural Dynamics (CFD/CSD), a comprehensive study was conducted on the impact of bending and torsional stiffness on the static aeroelastic behavior of a high-aspect-ratio wing, employing FLUENT software across diverse flight conditions. The study summarized this influence by comparing the computational outcomes. The results indicate that as the angle of attack rises, the lift increment diminishes gradually until the angle reaches 14 degrees, rendering the strategy of enhancing bending and torsional stiffness to gain more lift ineffective. Between 2 and 14 degrees of angle of attack, the lift difference between the scenarios decreases from 23.98% to 7.31%. At higher Mach numbers and lower angles of attack, augmenting wing stiffness significantly boosts wing lift. Optimal lift-to-drag characteristics are achieved at approximately 6 degrees of angle of attack. By averagely increasing the wing’s bending and torsional stiffness by 8.28% and 5.22%, respectively, the lift-to-drag characteristics can be enhanced by 5.27% at a low angle of attack of 0.75 Mach. The disparity in maximum deflection between the two stiffness wings is most pronounced at higher flight speeds and smaller angles of attack, with the opposite trend observed for the difference in maximum torsion angle. The key findings presented in this paper can expedite the integrated design of stiffness for this type of wing structure by providing vital technical insights.OPEN ACCESS Received: 24/07/2024 Accepted: 22/10/2024

  Abstract
  The bending and torsional stiffness influence structural deformation to varying degrees. Utilizing the coupled numerical method of Computational Fluid Dynamics and Computational [...]

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• Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China_prova_word

  Z. Wu, K. Xu, Y. Chen, J. Sánchez Pinedo

  Colección de pruebas Jesús Sánchez (2024). 3

  
  

  Abstract

  The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was {| class="formulaSCP" style="width: 100%; text-align: center;" |- | 12\% |} . Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m , inlet and outlet air velocities of 1.5 and {| class="formulaSCP" style="width: 100%; text-align: center;" |- | 2.0\, m/s |} , respectively, and an air supply angle of {| class="formulaSCP" style="width: 100%; text-align: center;" |- | {45}^{\circ } |} . These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.

  Abstract
  The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]

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• Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China

  Z. Wu, K. Xu, Y. Chen, Y. Liu, M. Liu

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 39

  
  

  Abstract

  The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was 12%. Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m, inlet and outlet air velocities of 1.5 and 2.0 m/s, respectively, and an air supply angle of 45°. These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.OPEN ACCESS Received: 19/07/2024 Accepted: 10/10/2024

  Abstract
  The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]

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• Word de prueba

  J. Sánchez Pinedo

  Colección de pruebas Jesús Sánchez (2024). 1

  
  

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• Research on the Effects of Pit Excavation on Adjacent Existing Subway Tunnel Structures Based on the FEM-DEM Coupling Method

  D. Meng, W. Lei, J. Han, H. Li, Y. Huang

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 43

  
  

  Abstract

  With the swift advancement of underground space development, large deep excavation projects above subway stations are becoming more common. This study employs the Finite element method-Discrete element method (FEM-DEM) coupling method to examine the effects of excavation on the structure of nearby subway tunnels. First, the f lexible triaxial compression test was conducted using the FEM-DEM coupling method to acquire the macroscopic mechanical characteristics of various soil layers. Based on this, the ground particle model was developed using the particle size scaling method, the underground continuous wall support was constructed via the FEM-DEM coupling method, and the tunnel model was established using particles arranged circularly. The study shows that with the excavation, the particles at the bottom of the foundation start to heave upward, with the maximum uplift displacement being approximately 10 mm. Throughout the excavation process, substantial changes occur in the contact force chain within the pit, with notable stress release at the pit bottom. Moreover, the porosity at the pit bottom gradually increases, and the vertical stress decreases; the stress decreased by 75% compared to before excavation, primarily due to stress release during excavation. Lastly, a focused analysis was conducted on the tunnel deformation during excavation. Throughout the foundation pit excavation, the tunnel’s displacement mainly took place within the excavation area, and its vertical displacement increased as the excavation depth increased, with a maximum displacement of approximately 0.5 mm. Analysis of particle displacement at various locations in the tunnel revealed that particles closest to the foundation pit bottom experienced the greatest displacement, whereas those farther away had relatively smaller displacements. The findings offer crucial theoretical support for the design and implementation of excavation projects.

  Abstract
  With the swift advancement of underground space development, large deep excavation projects above subway stations are becoming more common. This study employs the Finite element [...]

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• Control-Relevant Identification of the Unstable Inertial Systems

  I. Cojuhari

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 40

  
  

  Abstract

  Nowadays, with the rise of computing power, control-relevant identification methods have gained attention in various industrial applications, incorporating the requirements for control design into the process of system identification. Mathematical identification of stable linear dynamical systems is a widely studied problem in the literature, and it is prevalently performed in open-loop structures that may lead to high-order models suitable for control system design with imposed control objectives. However, in the case of unstable systems identification can become a challenge task, and usually is performed using closed-loop identification techniques. This paper presents the control-relevant identification approach for two kinds of unstable processes. The contribution focuses on establishing a well-fitted identified model by using a strategy that involves collecting data from the closed-loop system’s operation with a proportional controller when the system achieves an underdamped step response. In addition, a proportional-integral-derivative (PID) controller for each process was synthesized using maximal stability degree method. Concerning identification, the simulation results were compared with those of the genetic algorithm and offered better model estimation than the genetic algorithm. On the other hand, it is also demonstrated that the designed control algorithm offered a high degree of stability to the system and is more reliable in stabilizing the behavior of the unstable system than the genetic algorithm and the parametric optimization method.

  Abstract
  Nowadays, with the rise of computing power, control-relevant identification methods have gained attention in various industrial applications, incorporating the requirements [...]

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• Effects of radar absorption materials application on stealth performance of inlet based on risk theory

  S. Liu, Z. Guo, L. Chen

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 42

  
  

  Abstract

  One significant technical measure to reduce the forward radar cross section (RCS) of the aircraft was to design the inlet into an S-shape. Additionally, the application of radar-absorbing material (RAM) can further decrease the RCS of the air intake which approach enhances the stealth capabilities of the aircraft. Nevertheless, the use of RAM will simultaneously increase the inherent weight of the air intake. The electromagnetic scattering characteristics of Sshaped inlets without RAM coating and seven coating schemes are calculated by numerical simulation. The risk theory was employed to assess the impact of the coating RAM on the radar cross-section. The simulation results indicate that coating RAM can further reduce the forward average RCS value. Compared to the full coating scheme the S-shaped inlets with RAM on the intake region can achieve 90% of the RCS reduction effect and cut down approximately forty percent of the coating.

  Abstract
  One significant technical measure to reduce the forward radar cross section (RCS) of the aircraft was to design the inlet into an S-shape. Additionally, the application of [...]

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• Detection of small rod-end joint bearings via deep feature fusion and confidence propagation clustering

  J. Peng, R. Ye, S. Lan, T. Xiao, C. Xu, Y. Song

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 41

  
  

  Abstract

  Machine vision is used to detect dense, small rod-end joint bearings in sliding ball surfaces with little feature information and high variability. However, this leads to inaccurate identification, affecting production efficiency. This study proposes a deeplearning object-detection algorithm model that allows the network to retain more semantic information. We introduced the space-to-depth convolution (SPD-Conv) step-free convolution module to improve the backbone network and developed a multi-level feature fused SPD (MFSPD) deep feature fusion module to redesign the neck network to improve the feature extraction ability and detection accuracy for small targets. Furthermore, we added a small P4 detection head in the head network (i.e., prior box acquisition on the dataset using the weighted k-means algorithm), increased the matching degree of the prior box and feature layer, and accelerated the model convergence. To improve the confidence propagation clustering (CP-Cluster) analysis algorithm for post-processing, we optimized the prediction box confidence degree and detection speed. The algorithm performance was evaluated on homemade, T-LESS, and COCO datasets. The mAP@.5 values of the target detection algorithm for the homemade and T-LESS datasets were 96.9% and 93.8%, respectively, and the mAP was 55.9% for the COCO dataset. The experimental results indicate that the algorithm has a high detection accuracy and good feature extraction ability. Thus, it has considerable advantages for small-object detection and provides a reference for the detection of small parts.

  Abstract
  Machine vision is used to detect dense, small rod-end joint bearings in sliding ball surfaces with little feature information and high variability. However, this leads to [...]

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• The Segmentation of Debris Flow Fans Based on Spatial Coordinate Attention Mechanism

  X. Song, B. Wang

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 44

  
  

  Abstract

  In response to the low accuracy and poor performance of traditional machine learning methods in identifying debris flow fans. This paper proposes an optimized Simple, Parameter-Free Attention Module (SimAM) attention mechanism named Spatial Coordinate Attention Module. It combines with convolutional neural networks to achieve precise segmentation of debris flow fans. Firstly, the energy function of the SimAm is improved to retain the spatial coordinate information of features. Secondly, the closed-form solution of the module is obtained through optimization theory to ensure lightweightness, resulting in the Spatial Coordinate Attention Module. Finally, the Spatial Coordinate Attention Module is embedded into classic segmentation network models to compare with mainstream attention mechanisms. Experimental results demonstrate that the proposed method outperforms mainstream attention mechanisms in various classic models, yielding more complete segmentation results. This approach effectively enhances the segmentation performance of the network models in the task of debris flow fans segmentation

  Abstract
  In response to the low accuracy and poor performance of traditional machine learning methods in identifying debris flow fans. This paper proposes an optimized Simple, Parameter-Free [...]

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• Validation of VSPAERO for Basic Wing Simulation

  J. Rosas-Cordova, C. Santana-Delgado, D. Hernadez-Alcantara, L. Amezquita-Brooks

  Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 45

  
  

  Abstract

  Potential flow theory-based numerical solvers have gained popularity for rapid and straightforward aerodynamic modeling across various applications, particularly in the early stages of design and in resource-limited projects such as small unmanned aerial vehicles (UAVs). These solvers offer a cost-effective solution for analyzing aerodynamic performance, and several well-established methods have demonstrated strong alignment with experimental data. Among these solvers is VSPAERO, a relatively recent addition integrated within the National Aeronautics and Space Administration’s (NASA) OpenVSP aircraft design software. Despite its growing use, a comprehensive validation of the VSPAERO solver remains necessary to ensure its reliability in diverse scenarios. This article presents a validation of the VSPAERO solver by conducting a series of case studies. The assessment includes comparisons against reference values obtained through empirical relationships, results from other established aerodynamic solvers and experimental data from wind tunnel testing. The assessment covers a range of geometries and flow conditions, highlighting areas where the solver performs well and identifying any limitations in its application. The findings provide insights into the meshing parameters required for accurate simulations, as well as the types of geometries and flow conditions for which VSPAERO can be considered a reliable tool. As a conclusion, the article presents a series of best practices and guidelines that are recommended to improve the accuracy and efficiency of future erodynamic simulations conducted using this software. These recommendations are intended to serve as a valuable reference for both researchers and engineers involved in aerodynamic modeling, particularly those working on projects with tight budgets or in the preliminary stages of aircraft design.

  Abstract
  Potential flow theory-based numerical solvers have gained popularity for rapid and straightforward aerodynamic modeling across various applications, particularly in the early [...]

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