Transactions of Nanjing University of Aeronautics & Astronautics
Issue S,2025 Table of Contents
2025(S):1-11.
DOI: 10.16356/j.1005-1120.2025.S.001
Abstract:
In response to the need for a supportive on-orbit platform for future Mars exploration missions， this paper proposes the design and implementation of an autonomous spacecraft formation flying system near the Martian synchronous orbit using fuzzy learning-based intelligent control. A detailed analysis of spacecraft relative motion in the Mars environment is conducted， deducing the necessary conditions to reach the Martian synchronous orbit constraints. The modified Clohessy-Wiltshire （C-W） equation with Martian J2 （Oblateness index） perturbation is used as a reference to design a fuzzy learning-based intelligent and robust nonlinear control approach， which helps to autonomously track the desired formation configuration and stabilizes it. An introduction to spacecraft propulsion mechanisms is provided to analyze the feasibility of using electrical thrusters for spacecraft formation configuration tracking and stabilization in Martian synchronous orbits. The simulations show the effectiveness of the proposed control system for long-term on-orbit operations and reveal its reliability for designing intelligent deep-space formation flying configurations， such as an autonomous Mars observatory， a Martian telescope， or an interferometer.
In response to the need for a supportive on-orbit platform for future Mars exploration missions， this paper proposes the design and implementation of an autonomous spacecraft formation flying system near the Martian synchronous orbit using fuzzy learning-based intelligent control. A detailed analysis of spacecraft relative motion in the Mars environment is conducted， deducing the necessary conditions to reach the Martian synchronous orbit constraints. The modified Clohessy-Wiltshire （C-W） equation with Martian J2 （Oblateness index） perturbation is used as a reference to design a fuzzy learning-based intelligent and robust nonlinear control approach， which helps to autonomously track the desired formation configuration and stabilizes it. An introduction to spacecraft propulsion mechanisms is provided to analyze the feasibility of using electrical thrusters for spacecraft formation configuration tracking and stabilization in Martian synchronous orbits. The simulations show the effectiveness of the proposed control system for long-term on-orbit operations and reveal its reliability for designing intelligent deep-space formation flying configurations， such as an autonomous Mars observatory， a Martian telescope， or an interferometer.
2025(S):12-25.
DOI: 10.16356/j.1005-1120.2025.S.002
Abstract:
This paper presents an analysis of an equilateral triangular array formation initialization for space-based gravitational wave observatory （GWO） near Lagrange points in the circular-restricted three-body problem. A stable configuration is essential for the continuous observation of gravitational waves （GWs）. However， the motion near the collinear libration points is highly unstable. This problem is examined by output regulation theory. Using the tracking aspect， the equilateral triangular array formation is established in two periods and the fuel consumption is calculated. Furthermore， the natural evolution of the formation without control input is analyzed， and the effective stability duration is quantified to determine the timing of control interventions. Finally， to observe the GWs in same direction with different frequency bands， scale reconfiguration is employed.
This paper presents an analysis of an equilateral triangular array formation initialization for space-based gravitational wave observatory （GWO） near Lagrange points in the circular-restricted three-body problem. A stable configuration is essential for the continuous observation of gravitational waves （GWs）. However， the motion near the collinear libration points is highly unstable. This problem is examined by output regulation theory. Using the tracking aspect， the equilateral triangular array formation is established in two periods and the fuel consumption is calculated. Furthermore， the natural evolution of the formation without control input is analyzed， and the effective stability duration is quantified to determine the timing of control interventions. Finally， to observe the GWs in same direction with different frequency bands， scale reconfiguration is employed.
2025(S):26-37.
DOI: 10.16356/j.1005-1120.2025.S.003
Abstract:
To overcome external environmental disturbances， inertial parameter uncertainties and vibration of flexible modes in the process of attitude tracking， a comprehensively effective predefined-time guaranteed performance controller based on multi-observers for flexible spacecraft is proposed. First， to prevent unwinding phenomenon in attitude description， the rotation matrix is used to represent the spacecraft’s attitude. Second， the flexible modes observer which can guarantee predefined-time convergence is designed， for the case where flexible vibrations are unmeasurable in practice. What’s more， the disturbance observer is applied to estimate and compensate the lumped disturbances to improve the robustness of attitude control. A predefined-time controller is proposed to satisfy the prescribed performance and stabilize the attitude tracking system via barrier Lyapunov function. Finally， through comparative numerical simulations， the proposed controller can achieve high-precision convergence compared with the existing finite-time attitude tracking controller. This paper provides certain references for the high-precision predefined-time prescribed performance attitude tracking of flexible spacecraft with multi-disturbance.
To overcome external environmental disturbances， inertial parameter uncertainties and vibration of flexible modes in the process of attitude tracking， a comprehensively effective predefined-time guaranteed performance controller based on multi-observers for flexible spacecraft is proposed. First， to prevent unwinding phenomenon in attitude description， the rotation matrix is used to represent the spacecraft’s attitude. Second， the flexible modes observer which can guarantee predefined-time convergence is designed， for the case where flexible vibrations are unmeasurable in practice. What’s more， the disturbance observer is applied to estimate and compensate the lumped disturbances to improve the robustness of attitude control. A predefined-time controller is proposed to satisfy the prescribed performance and stabilize the attitude tracking system via barrier Lyapunov function. Finally， through comparative numerical simulations， the proposed controller can achieve high-precision convergence compared with the existing finite-time attitude tracking controller. This paper provides certain references for the high-precision predefined-time prescribed performance attitude tracking of flexible spacecraft with multi-disturbance.
2025(S):38-50.
DOI: 10.16356/j.1005-1120.2025.S.004
Abstract:
In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform， a distributed cooperative positioning method based on confidence evaluation is proposed. Firstly， the impact of ranging error， priori information， spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually. Secondly， a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle， which comprehensively considers the coupling relationship between influencing factors. Finally， a distributed cooperative navigation filter based on inter-vehicle ranging is designed. Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results， and positioning accuracy under the proposed method is improved by more than 15% compared with the traditional screening methods based on optimal geometric configuration and closest distance.
In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform， a distributed cooperative positioning method based on confidence evaluation is proposed. Firstly， the impact of ranging error， priori information， spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually. Secondly， a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle， which comprehensively considers the coupling relationship between influencing factors. Finally， a distributed cooperative navigation filter based on inter-vehicle ranging is designed. Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results， and positioning accuracy under the proposed method is improved by more than 15% compared with the traditional screening methods based on optimal geometric configuration and closest distance.
2025(S):51-63.
DOI: 10.16356/j.1005-1120.2025.S.005
Abstract:
Multi-layer riveted structures are widely applied to aircraft. During the service， cracks may appear within these structures due to stress concentration of the riveted holes. The guided wave monitoring has been proved to be an effective tool to deal with this problem. However， there is a lack of understanding of the wave propagation process across such kinds of structures. This study proposes a piezoelectric guided wave simulation method to reveal the propagation of guided waves in multi-layer riveted structures. Effects of pretension force， friction coefficient， and cracks that might influence wave characteristics are studied. The guided wave simulation data is compared with the experimental results and the results verify the simulation model. Then the guided wave propagation in a more complex long-beam butt joint structure is further simulated.
Multi-layer riveted structures are widely applied to aircraft. During the service， cracks may appear within these structures due to stress concentration of the riveted holes. The guided wave monitoring has been proved to be an effective tool to deal with this problem. However， there is a lack of understanding of the wave propagation process across such kinds of structures. This study proposes a piezoelectric guided wave simulation method to reveal the propagation of guided waves in multi-layer riveted structures. Effects of pretension force， friction coefficient， and cracks that might influence wave characteristics are studied. The guided wave simulation data is compared with the experimental results and the results verify the simulation model. Then the guided wave propagation in a more complex long-beam butt joint structure is further simulated.
2025(S):64-77.
DOI: 10.16356/j.1005-1120.2025.S.006
Abstract:
Current aero-engine life prediction areas typically focus on single-scale degradation features， and the existing methods are not comprehensive enough to capture the relationship within time series data. To address this problem， we propose a novel remaining useful life （RUL） estimation method based on the attention mechanism. Our approach designs a two-layer multi-scale feature extraction module that integrates degradation features at different scales. These features are then processed in parallel by a self-attention module and a three-layer long short-term memory （LSTM） network， which together capture long-term dependencies and adaptively weigh important feature. The integration of degradation patterns from both components into the attention module enhances the model’s ability to capture long-term dependencies. Visualizing the attention module’s weight matrices further improves model interpretability. Experimental results on the C-MAPSS dataset demonstrate that our approach outperforms the existing state-of-the-art methods.
Current aero-engine life prediction areas typically focus on single-scale degradation features， and the existing methods are not comprehensive enough to capture the relationship within time series data. To address this problem， we propose a novel remaining useful life （RUL） estimation method based on the attention mechanism. Our approach designs a two-layer multi-scale feature extraction module that integrates degradation features at different scales. These features are then processed in parallel by a self-attention module and a three-layer long short-term memory （LSTM） network， which together capture long-term dependencies and adaptively weigh important feature. The integration of degradation patterns from both components into the attention module enhances the model’s ability to capture long-term dependencies. Visualizing the attention module’s weight matrices further improves model interpretability. Experimental results on the C-MAPSS dataset demonstrate that our approach outperforms the existing state-of-the-art methods.
2025(S):78-90.
DOI: 10.16356/j.1005-1120.2025.S.007
Abstract:
Morphing aircraft are designed to adaptively adjust their shape for changing flight missions， which enables them to improve their flight performance significantly for future applications. The folding wingtips represent a key research aspect for morphing aircraft， since they can lead to potential improvements in flight range， maneuverability， load alleviation and airport compatibility. This paper proposes a hinge mechanism design for folding wingtips based on the shape memory alloy torsion tube， aiming to achieve successful folding using the actuation effect of the shape memory alloy. The proposed design employs a shape memory alloy torsion tube as the actuator for the active folding of the wingtip， which is motivated by the characteristics of the tube， enabling a simplified structure for the integration with high energy density. Through numerical simulation and testing of the folding wingtip structure， the concept is verified， which shows its potential as an actuator for folding wingtips.
Morphing aircraft are designed to adaptively adjust their shape for changing flight missions， which enables them to improve their flight performance significantly for future applications. The folding wingtips represent a key research aspect for morphing aircraft， since they can lead to potential improvements in flight range， maneuverability， load alleviation and airport compatibility. This paper proposes a hinge mechanism design for folding wingtips based on the shape memory alloy torsion tube， aiming to achieve successful folding using the actuation effect of the shape memory alloy. The proposed design employs a shape memory alloy torsion tube as the actuator for the active folding of the wingtip， which is motivated by the characteristics of the tube， enabling a simplified structure for the integration with high energy density. Through numerical simulation and testing of the folding wingtip structure， the concept is verified， which shows its potential as an actuator for folding wingtips.
2025(S):91-101.
DOI: 10.16356/j.1005-1120.2025.S.008
Abstract:
Conflict resolution （CR） is a fundamental component of air traffic management， where recent progress in artificial intelligence has led to the effective application of deep reinforcement learning （DRL） techniques to enhance CR strategies. However， existing DRL models applied to CR are often limited to simple scenarios. This approach frequently leads to the neglect of the high risks associated with multiple intersections in the high-density and multi-airport system terminal area （MAS-TMA）， and suffers from poor interpretability. This paper addresses the aforementioned gap by introducing an improved multi-agent DRL model that adopted to autonomous CR （AutoCR） within MAS-TMA. Specifically， dynamic weather conditions are incorporated into the state space to enhance adaptability. In the action space， the flight intent is considered and transformed into optimal maneuvers according to overload， thus improving interpretability. On these bases， the deep Q-network （DQN） algorithm is further improved to address the AutoCR problem in MAS-TMA. Simulation experiments conducted in the “Guangdong-Hong Kong-Macao” greater bay area （GBA） MAS-TMA demonstrate the effectiveness of the proposed method， successfully resolving over eight potential conflicts and performing robustly across various air traffic densities.
Conflict resolution （CR） is a fundamental component of air traffic management， where recent progress in artificial intelligence has led to the effective application of deep reinforcement learning （DRL） techniques to enhance CR strategies. However， existing DRL models applied to CR are often limited to simple scenarios. This approach frequently leads to the neglect of the high risks associated with multiple intersections in the high-density and multi-airport system terminal area （MAS-TMA）， and suffers from poor interpretability. This paper addresses the aforementioned gap by introducing an improved multi-agent DRL model that adopted to autonomous CR （AutoCR） within MAS-TMA. Specifically， dynamic weather conditions are incorporated into the state space to enhance adaptability. In the action space， the flight intent is considered and transformed into optimal maneuvers according to overload， thus improving interpretability. On these bases， the deep Q-network （DQN） algorithm is further improved to address the AutoCR problem in MAS-TMA. Simulation experiments conducted in the “Guangdong-Hong Kong-Macao” greater bay area （GBA） MAS-TMA demonstrate the effectiveness of the proposed method， successfully resolving over eight potential conflicts and performing robustly across various air traffic densities.
2025(S):102-120.
DOI: 10.16356/j.1005-1120.2025.S.009
Abstract:
Hyperspectral image （HSI） classification is crucial for numerous remote sensing applications. Traditional deep learning methods may miss pixel relationships and context， leading to inefficiencies. This paper introduces the spectral band graph convolutional and attention-enhanced CNN joint network （SGCCN）， a novel approach that harnesses the power of spectral band graph convolutions for capturing long-range relationships， utilizes local perception of attention-enhanced multi-level convolutions for local spatial feature and employs a dynamic attention mechanism to enhance feature extraction. The SGCCN integrates spectral and spatial features through a self-attention fusion network， significantly improving classification accuracy and efficiency. The proposed method outperforms existing techniques， demonstrating its effectiveness in handling the challenges associated with HSI data.
Hyperspectral image （HSI） classification is crucial for numerous remote sensing applications. Traditional deep learning methods may miss pixel relationships and context， leading to inefficiencies. This paper introduces the spectral band graph convolutional and attention-enhanced CNN joint network （SGCCN）， a novel approach that harnesses the power of spectral band graph convolutions for capturing long-range relationships， utilizes local perception of attention-enhanced multi-level convolutions for local spatial feature and employs a dynamic attention mechanism to enhance feature extraction. The SGCCN integrates spectral and spatial features through a self-attention fusion network， significantly improving classification accuracy and efficiency. The proposed method outperforms existing techniques， demonstrating its effectiveness in handling the challenges associated with HSI data.
2025(S):121-130.
DOI: 10.16356/j.1005-1120.2025.S.010
Abstract:
Devices on aircraft are subjected to complex environmental excitations that pose risks to their operational safety. Passive vibration isolation techniques are extensively employed due to their advantage of not requiring additional energy sources. This paper introduces a novel metallic vibration isolator based on zigzag structures. The proposed isolator features a compact design and can be manufactured using additive manufacturing techniques， allowing for the integration of structural and functional elements. Firstly， the vibration response of the single-degree-of-freedom （SDOF） system is analyzed. To achieve effective vibration reduction， it is crucial for the isolator's stiffness to be sufficiently low. Secondly， to obtain a structure with high compliance， the traversal algorithm and the finite element method（FEM） are applied. The results confirm that the zigzag structure is a reliable high-compliance configuration. Thirdly， the parametric geometric model of the zigzag structure is developed and its stiffness is calculated. Quasi-static compression experiments validate the accuracy of the calculations. Finally， a specific engineering example is considered， where a zigzag vibration isolator is designed and fabricated. Vibration experiments demonstrate that the zigzag isolator effectively reduces both the stiffness and the fundamental frequency of the vibration system， achieving a vibration isolation efficiency exceeding 60%.
Devices on aircraft are subjected to complex environmental excitations that pose risks to their operational safety. Passive vibration isolation techniques are extensively employed due to their advantage of not requiring additional energy sources. This paper introduces a novel metallic vibration isolator based on zigzag structures. The proposed isolator features a compact design and can be manufactured using additive manufacturing techniques， allowing for the integration of structural and functional elements. Firstly， the vibration response of the single-degree-of-freedom （SDOF） system is analyzed. To achieve effective vibration reduction， it is crucial for the isolator's stiffness to be sufficiently low. Secondly， to obtain a structure with high compliance， the traversal algorithm and the finite element method（FEM） are applied. The results confirm that the zigzag structure is a reliable high-compliance configuration. Thirdly， the parametric geometric model of the zigzag structure is developed and its stiffness is calculated. Quasi-static compression experiments validate the accuracy of the calculations. Finally， a specific engineering example is considered， where a zigzag vibration isolator is designed and fabricated. Vibration experiments demonstrate that the zigzag isolator effectively reduces both the stiffness and the fundamental frequency of the vibration system， achieving a vibration isolation efficiency exceeding 60%.
2025(S):131-140.
DOI: 10.16356/j.1005-1120.2025.S.011
Abstract:
This study presents a novel analytical algorithm for solving the forward position problem of a triangular platform Stewart-type parallel robot （STPR）. By introducing a virtual chain and leveraging tetrahedral geometric principles， the proposed method derives analytical solutions for the position and orientation of the moving platform. The algorithm systematically addresses the nonlinearity inherent in the kinematic equations of parallel mechanisms， providing explicit expressions for the coordinates of key moving attachment points. Furthermore， the methodology is extended to general triangular platform STPRs with non-coplanar fixed attachments. Numerical validation through virtual experiments confirms the accuracy of the solutions， demonstrating that the mechanism admits eight distinct configurations for a given set of limb lengths. The results align with established kinematic principles and offer a computationally efficient alternative to iterative analytical approaches， contributing to the advancement of precision control in parallel robotic systems.
This study presents a novel analytical algorithm for solving the forward position problem of a triangular platform Stewart-type parallel robot （STPR）. By introducing a virtual chain and leveraging tetrahedral geometric principles， the proposed method derives analytical solutions for the position and orientation of the moving platform. The algorithm systematically addresses the nonlinearity inherent in the kinematic equations of parallel mechanisms， providing explicit expressions for the coordinates of key moving attachment points. Furthermore， the methodology is extended to general triangular platform STPRs with non-coplanar fixed attachments. Numerical validation through virtual experiments confirms the accuracy of the solutions， demonstrating that the mechanism admits eight distinct configurations for a given set of limb lengths. The results align with established kinematic principles and offer a computationally efficient alternative to iterative analytical approaches， contributing to the advancement of precision control in parallel robotic systems.
2025(S):141-149.
DOI: 10.16356/j.1005-1120.2025.S.012
Abstract:
To address the issues of low solving efficiency and poor decoupling accuracy in existing six-axis acceleration decoupling algorithms， a new decoupling algorithm is proposed along with a corresponding auto-compensation algorithm. Firstly， based on Kane’s method， the dynamics model of the six-axis acceleration sensing mechanism is formed to determine the relationship between accelerations and branch forces. Then， with the trapezoidal rule， a solution algorithm for the dynamics model is developed. The virtual prototype tests show that the computation of this algorithm is five times more efficient than that of the ADAMS core algorithm. Besides， this solution algorithm is applied to the “12-6” configuration and “9-3” configuration. The results show that the efficiency of the former is nearly 3.3 times that of the latter. Finally， based on vibration theory， an auto-compensation algorithm for the solution algorithm is established. Virtual prototype tests indicate that with 40% noise interference， the auto-compensation algorithm achieves misjudgement rate and omission rate of only 4.0% and 4.5%， respectively， and the errors in the solving process converge.
To address the issues of low solving efficiency and poor decoupling accuracy in existing six-axis acceleration decoupling algorithms， a new decoupling algorithm is proposed along with a corresponding auto-compensation algorithm. Firstly， based on Kane’s method， the dynamics model of the six-axis acceleration sensing mechanism is formed to determine the relationship between accelerations and branch forces. Then， with the trapezoidal rule， a solution algorithm for the dynamics model is developed. The virtual prototype tests show that the computation of this algorithm is five times more efficient than that of the ADAMS core algorithm. Besides， this solution algorithm is applied to the “12-6” configuration and “9-3” configuration. The results show that the efficiency of the former is nearly 3.3 times that of the latter. Finally， based on vibration theory， an auto-compensation algorithm for the solution algorithm is established. Virtual prototype tests indicate that with 40% noise interference， the auto-compensation algorithm achieves misjudgement rate and omission rate of only 4.0% and 4.5%， respectively， and the errors in the solving process converge.
2025(S):150-155.
DOI: 10.16356/j.1005-1120.2025.S.013
Abstract:
An analysis is conducted on the hydrodynamic response law of a single module maritime airport， considering the atmospheric variables of the wind and wave field. The analysis is based on hydroelastic theory and focuses on the typhoon-driven very large floating structures （VLFS） configuration of the maritime airport. The findings indicate that the proposed method enables efficient information exchange between the fluid and structure domains through the coupling interface. The displacement of the maritime airport affected by the typhoon’s wave field is mostly determined by the direction of the flow. The wave loads acting on the floating body also influence the wave profile of the irregular wave and the deformation of the floating body. The von Mises stress distribution is not significant in all parts of the floating body.
An analysis is conducted on the hydrodynamic response law of a single module maritime airport， considering the atmospheric variables of the wind and wave field. The analysis is based on hydroelastic theory and focuses on the typhoon-driven very large floating structures （VLFS） configuration of the maritime airport. The findings indicate that the proposed method enables efficient information exchange between the fluid and structure domains through the coupling interface. The displacement of the maritime airport affected by the typhoon’s wave field is mostly determined by the direction of the flow. The wave loads acting on the floating body also influence the wave profile of the irregular wave and the deformation of the floating body. The von Mises stress distribution is not significant in all parts of the floating body.
2025(S):156-166.
DOI: 10.16356/j.1005-1120.2025.S.014
Abstract:
Studies on coral aggregate concrete （CAC） mainly focus on uniaxial stress conditions. However， concrete structures often experience complex stress conditions in practical engineering. It is essential to investigate the mechanical behavior and failure mechanisms of CAC under multiaxial stress conditions. This paper employs a 3D mesoscale model that considers the actual size， shape， and spatial distribution of aggregates. The reliability of the model and material parameters is verified through comparison with existing experimental data. Subsequently， the model is used to systematically study the mechanical properties， failure modes， and failure processes of C40 CAC under the biaxial compression. The numerical results are compared with the experimental results of CAC and ordinary portland concrete （OPC）. The results indicate that the failure modes of CAC under the biaxial compression are diagonal shear failure. The biaxial compressive strength and elastic modulus of CAC are greater than those under uniaxial stress and exhibit a significant intermediate principal stress effect. The biaxial compressive strength reaches its maximum value when the stress ratio is 0.5， which is consistent with the conclusions for OPC. Finally， failure criteria and strength envelopes for CAC under the biaxial compression are established in order to provide a reference for analyzing the strength characteristics and structural design of CAC.
Studies on coral aggregate concrete （CAC） mainly focus on uniaxial stress conditions. However， concrete structures often experience complex stress conditions in practical engineering. It is essential to investigate the mechanical behavior and failure mechanisms of CAC under multiaxial stress conditions. This paper employs a 3D mesoscale model that considers the actual size， shape， and spatial distribution of aggregates. The reliability of the model and material parameters is verified through comparison with existing experimental data. Subsequently， the model is used to systematically study the mechanical properties， failure modes， and failure processes of C40 CAC under the biaxial compression. The numerical results are compared with the experimental results of CAC and ordinary portland concrete （OPC）. The results indicate that the failure modes of CAC under the biaxial compression are diagonal shear failure. The biaxial compressive strength and elastic modulus of CAC are greater than those under uniaxial stress and exhibit a significant intermediate principal stress effect. The biaxial compressive strength reaches its maximum value when the stress ratio is 0.5， which is consistent with the conclusions for OPC. Finally， failure criteria and strength envelopes for CAC under the biaxial compression are established in order to provide a reference for analyzing the strength characteristics and structural design of CAC.
2025(S):167-179.
DOI: 10.16356/j.1005-1120.2025.S.015
Abstract:
The development and utilization of marine resources by human beings is gradually moving towards the deep sea， and deep-sea aquaculture platforms have emerged to meet the needs of aquaculture and food security. To better understand the motion response characteristics of the main structure of the full-submersible deep-sea aquaculture platform under the action of water waves， Fluent software is used to numerically simulate regular waves， irregular waves， and strong nonlinear waves， and their effects on the six degrees of freedom motion response of the main structure of the full-submersible deep-sea aquaculture platform are analyzed. The study found that under the towing condition， the smaller the wave direction angle， the more intense the movement. Under the platform’s working conditions， the larger the wave direction angle， the more intense the movement.
The development and utilization of marine resources by human beings is gradually moving towards the deep sea， and deep-sea aquaculture platforms have emerged to meet the needs of aquaculture and food security. To better understand the motion response characteristics of the main structure of the full-submersible deep-sea aquaculture platform under the action of water waves， Fluent software is used to numerically simulate regular waves， irregular waves， and strong nonlinear waves， and their effects on the six degrees of freedom motion response of the main structure of the full-submersible deep-sea aquaculture platform are analyzed. The study found that under the towing condition， the smaller the wave direction angle， the more intense the movement. Under the platform’s working conditions， the larger the wave direction angle， the more intense the movement.
2025(S):180-194.
DOI: 10.16356/j.1005-1120.2025.S.016
Abstract:
The rapid development of the industrial internet of things （IIoT） has brought huge benefits to factories equipped with IIoT technology， each of which represents an IIoT domain. More and more domains are choosing to cooperate with each other to produce better products for greater profits. Therefore， in order to protect the security and privacy of IIoT devices in cross-domain communication， lots of cross-domain authentication schemes have been proposed. However， most schemes expose the domain to which the IIoT device belongs， or introduce a single point of failure in multi-domain cooperation， thus introducing unpredictable risks to each domain. We propose a more secure and efficient domain-level anonymous cross-domain authentication （DLCA） scheme based on alliance blockchain. The proposed scheme uses group signatures with decentralized tracing technology to provide domain-level anonymity to each IIoT device and allow the public to trace the real identity of the malicious pseudonym. In addition， DLCA takes into account the limited resource characteristics of IIoT devices to design an efficient cross-domain authentication protocol. Security analysis and performance evaluation show that the proposed scheme can be effectively used in the cross-domain authentication scenario of industrial internet of things.
The rapid development of the industrial internet of things （IIoT） has brought huge benefits to factories equipped with IIoT technology， each of which represents an IIoT domain. More and more domains are choosing to cooperate with each other to produce better products for greater profits. Therefore， in order to protect the security and privacy of IIoT devices in cross-domain communication， lots of cross-domain authentication schemes have been proposed. However， most schemes expose the domain to which the IIoT device belongs， or introduce a single point of failure in multi-domain cooperation， thus introducing unpredictable risks to each domain. We propose a more secure and efficient domain-level anonymous cross-domain authentication （DLCA） scheme based on alliance blockchain. The proposed scheme uses group signatures with decentralized tracing technology to provide domain-level anonymity to each IIoT device and allow the public to trace the real identity of the malicious pseudonym. In addition， DLCA takes into account the limited resource characteristics of IIoT devices to design an efficient cross-domain authentication protocol. Security analysis and performance evaluation show that the proposed scheme can be effectively used in the cross-domain authentication scenario of industrial internet of things.
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