High Dynamic Conditions Research Articles

Magnetic and mechanical hardening of nano-lamellar magnets using thermo-magnetic fields

High-performance magnetic materials based on rare-earth intermetallic compounds are critical for energy conversion technologies. However, the high cost and supply risks of rare-earth elements necessitate the development of affordable alternatives. Another challenge lies in the inherent brittleness of current magnets, which limits their applications for high dynamic mechanical loading conditions during service and complex shape design during manufacturing towards high efficiency and sustainability. Here, we propose a strategy to simultaneously enhance the magnetic and mechanical performance of a rare-earth-free multicomponent magnet. We achieve this by introducing nano-lamellar structures with high shape anisotropy into a cobalt–iron–nickel–aluminum material system through eutectoid decomposition under externally applied thermo-magnetic fields. Compared to the conventional thermally activated processing, the thermo-magnetic field accelerates phase decomposition kinetics, producing finer lamellae spacings and smaller eutectoid colonies. The well-tailored size, density, interface, and chemistry of the nano-lamellae enhance their pinning effect against the motion of both magnetic domain walls and dislocations, resulting in concurrent gains in coercivity and mechanical strength. Our work demonstrates a rational pathway to designing multifunctional rare-earth-free magnets for energy conversion devices such as high-speed motors and generators operating under harsh service conditions.

Технологические решения для создания многоагентных систем в сфере инновационной деятельности

Abstract. In the context of the rapid development of science and technology, traditional methods are no longer effective, which requires more intelligent and adaptive solutions for information management and processing. The article explores and analyzes multi-agent systems (MAS), their role and importance in the field of innovation. Objective: systematization of technological solutions used in the development of multi-agent systems in innovation activities, as well as assessment of their impact on the effectiveness of innovation processes. Result and novelty: an analysis of architectural and algorithmic approaches to MAC development was carried out, modern software and hardware solutions, including the Internet of Things (IoT) and cloud platforms, were studied. Innovative aspects in the integration of MAC with physical devices are highlighted, which expands their functionality. Practical significance: the considered technological solutions support the practical application of MAC in various fields: from project management to optimization of research processes. The implementation of the IAU contributes to improved coordination and allocation of resources, which is especially important in conditions of high dynamics and uncertainty of the innovation environment. Discussion: It is emphasized that MAC development faces the challenges of complex architecture and computational costs. The importance of choosing a suitable development platform (for example, JADE, SPADE, NetLogo) is highlighted, depending on the needs of the project. The role of cloud technologies and IoT in the future development of multi-agent systems is emphasized.

Multimedia Transmission Technique for Smart Ambulance with multi-carrier OFDM in a V2V and V2I Channel model using Software Defined Radio Technology

This research explores the implementation of a cutting-edge Software Defined Radio (SDR) framework to transmit multimedia files that can be assumed to be medical data in smart ambulances. The system utilizes multi-carrier Orthogonal Frequency-Division Multiplexing (OFDM) across V2V and V2I channels. The research is based on the notion that adaptive real-time communication is essential for the uninterrupted supply of key patient data to medical facilities and vehicles in transit, in order to address the problems posed by high mobility and dynamic environmental conditions. A comprehensive SDR system has been constructed and assessed in comparison to conventional communication mechanisms, demonstrating notable advancements in data accuracy and uninterrupted transmission. Our system successfully established stable connections in V2I channels, even in the presence of environmental obstacles. It maintained average power levels of approximately 32.074 dBm and a Peak-to-Average Power Ratio (PAPR) of 1.037 dB. These results indicate a constant signal envelope that promotes optimal signal transmission with excellent fidelity. In V2V scenarios, we successfully maintained data integrity with a low Peak-to-Average Power Ratio (PAPR) of 3.316 dB, even while vehicles were moving at a speed of 20 km/h. Additionally, we secured a high likelihood (94.5%) that the signal power remained close to the average, showing the robustness of our system against Doppler effects and signal dispersion. Text transmissions experienced errors when subjected to a Doppler shift of 20 km/h, which impacted the decoding of the received text. Similarly, image transmissions revealed limitations in bandwidth, as a transmitted image of 3640 KB was received with a degraded 4 KB. This emphasizes the importance of implementing effective error handling and recovery mechanisms. The results illustrate the efficacy of the suggested system in maintaining a high Quality of Service (QoS), offering proof of the effectiveness of contemporary wireless communication technologies in improving emergency medical services and setting new standards in smart ambulance capabilities.

The strapdown shipborne gravimetry for ocean based on SINS/GNSS: comparison and optimization

Abstract The strapdown inertial scalar gravimetry (SISG) has become one of the main methods for measuring marine gravity. SIGS requires specific force, attitude, velocity, and position information for gravimetry. The attitude can be obtained by the strapdown inertial navigation system/global navigation satellite system (SINS/GNSS) integration, and the displacement information comes from GNSS or SINS/GNSS. Therefore, based on the different sources of displacement information, shipborne SISG can be divided into two modes. Namely, the gravimetry method of different parameter sources (DPGM) based on displacement information of GNSS and the attitude of SINS/GNSS, as well as the full parameter gravimetry method (FPGM) based on the attitude and displacement information of SINS/GNSS. Since the accuracy of GNSS can meet the requirements for gravimetry, the theoretical studies and applications of DPGM are more common. For FPGM, this idea is more often used in underwater applications (SINS/ doppler velocity log (SINS/DVL), etc.). However, it rarely appears in shipborne applications. Moreover, there is relatively little theoretical analysis on FPGM. In fact, FPGM also has certain application prospects due to the high accuracy. Based on this, this article first provides the measurement model and steps of FPGM, and conducts the theoretical analysis of FPGM. The comparison is made with DPGM from the perspective of error terms. And it is pointed out that FPGM has better potential for anti-interference improvement than DPGM. Then, from the perspective of application, we propose the investigated linear robust Kalman filter (LRKF) based on Huber-M estimation without traversing all dimensions and introduce the horizontal acceleration and bias corrections to improve FPGM. Finally, the optimized FPGM (OFPGM) is obtained. The results of lake and sea tests show that FPGM has certain research value. And OFPGM has higher performance in high dynamic condition and when GNSS occurs interference, which is more suitable for offshore measurement.

Enhancing Direction-of-Arrival Estimation with Multi-Task Learning.

There are numerous methods in the literature for Direction-of-Arrival (DOA) estimation, including both classical and machine learning-based approaches that jointly estimate the Number of Sources (NOS) and DOA. However, most of these methods do not fully leverage the potential synergies between these two tasks, which could yield valuable shared information. To address this limitation, in this article, we present a multi-task Convolutional Neural Network (CNN) capable of simultaneously estimating both the NOS and the DOA of the signal. Through experiments on simulated data, we demonstrate that our proposed model surpasses the performance of state-of-the-art methods, especially in challenging environments characterized by high noise levels and dynamic conditions.

Adaptive range gating based on variational Bayesian inference for space debris ranging with spaceborne single-photon LiDAR.

To enhance the accuracy of space debris localization, spaceborne single-photon LiDAR (SSPL) presents a promising technique for accurate target ranging. Extended Kalman filtering (EKF) plays a crucial role in range gating under high dynamic and nonlinear motion conditions of space debris, ensuring accurate state estimation and prior distance data. However, unknown and time-varying statistics of process and measurement noise significantly degrade state estimation accuracy, posing risks of filter divergence and reduced photon reception, ultimately rendering range gating ineffective. To address this challenge, we propose an adaptive range gating method based on variational Bayesian adaptive extended Kalman filtering (ARG-VBAEKF). This method leverages variational Bayesian (VB) posterior approximation to estimate the joint distribution of state and noise. Simulation results demonstrate that ARG-VBAEKF achieves accurate state and noise estimation, thereby effectively enhancing range gating performance in SSPL-based space debris ranging.

Star Spot Extraction for Multi-FOV Star Sensors Under Extremely High Dynamic Conditions

Star Spot Extraction for Multi-FOV Star Sensors Under Extremely High Dynamic Conditions

Irreversible failure characteristics and microscopic mechanism of lithium-ion battery under high dynamic strong mechanical impacts

Irreversible failure characteristics and microscopic mechanism of lithium-ion battery under high dynamic strong mechanical impacts

Методологические принципы управления риском на горнодобывающих предприятиях в условиях неопределенности среды

In conditions of uncertainty and high dynamics of the operating environment of a mining enterprise, the operation of its mine engineering system must ensure timely response (reactions) adequate to the impact of the internal and external environments. At the same time, the most crucial characteristics of a mine engineering system in a turbulent external environment are efficiency, safety, and environmental friendliness, whose conflict constantly intensifies. The article considers two characteristics of the system, i.e., efficiency and production safety, and the tasks to ensure them may often contradict each other. It is possible to reduce or mitigate the impact of this conflict on the production activities of an enterprise using production risk management. Based on the analysis of the operation of mining enterprises in the sphere of accident and injury risk management and methods applied within the framework of production safety system functioning, the main tendencies, specifics, and regularities of risk management have been determined. This allowed for the substantiation of principles necessary and sufficient for risk management under uncertainty of the environment of operation of mining enterprises: production conditions are always changeable, therefore, the parameters of the mine engineering system deviate from the design values and the scheduled operation mode; the object of control at risk management is a production situation; a production emergency as a manifestation of dual nature of risk reveals both profits and losses. The implementation of the suggested principles is possible on the condition of control over production risk including all factors affecting employees of different occupations during their work and uniting both economic (non-compliance with production program, accidents, production downtime) and social risks (injuries, temporary disabilities). The account of the established regularity of the occurrence of production emergencies at design, planning, and production activities at a mining enterprise will ensure an acceptable level of production risk for mining operations.

Construction and Analysis of Battery Equivalent Circuit Model Considering Liquid Phase Lithium Ion Diffusion Under High-Rate Conditions

In order to obtain the internal state of lithium-ion battery quickly and accurately, the problem that the internal state of the battery is difficult to estimate quickly and accurately is solved. The discharge performance of lithium ion is affected by the electrode current during the charge and discharge process. This paper analyzes the key factors of the electrochemical model at high rate, considers the change of lithium ion concentration in the liquid phase of the battery, integrates the electrochemical mechanism and the equivalent circuit, and establishes a mechanism equivalent circuit model with more computational advantages through circuit elements. The equivalent circuit model can describe the physical characteristics of the lithium battery. Under high rate constant current and dynamic conditions, the model shows good electrical characteristics. Compared with the traditional empirical equivalent circuit model, the accuracy of the model is improved, and the state quantity is reduced by 15 compared with the electrochemical model. The model is of great significance in practical application.

A Moderated Mediation Model of Entrepreneurship Education, Competence, and Environmental Dynamics on Entrepreneurial Performance

This study explores the relationship between entrepreneurship education, entrepreneurial competence, and entrepreneurial performance, focusing on the moderating role of environmental dynamics under conditions of high and low environmental dynamics. Using SPSS 21.0 and Smart PLS 4.0 software, this quantitative research analyzed survey data from 424 college students in China who have started their own businesses. The results indicate that entrepreneurship education has a significant positive impact on entrepreneurial performance. Furthermore, environmental dynamics moderate the indirect effect of entrepreneurship education on entrepreneurial performance through entrepreneurial competence, with the indirect effect being stronger when environmental dynamics are high. The study also underscores the need for the sustainable development of entrepreneurship education, ensuring that educational programs evolve continuously to meet the changing demands of entrepreneurial environments. The findings highlight the importance of entrepreneurship education in fostering entrepreneurial competence and enhancing entrepreneurial performance. However, due to the cross-sectional design and self-reported nature of the data, the ability to draw causal inferences is limited. Future research should adopt longitudinal designs and objective performance measures to further investigate these relationships.

Experimental study on dynamic response of hard rock blasting under in-situ stress

Experimental study on dynamic response of hard rock blasting under in-situ stress

A High Dynamic Velocity Locked Loop for the Carrier Tracking of a Wide-Band Hybrid Direct Sequence/Frequency Hopping Spread-Spectrum Signal

For hybrid direct sequence/frequency hopping (DS/FH) spread spectrum signals, even if the relative motion speed between the transmitter and receiver remains constant, the Doppler frequency will vary due to the continuous hopping of the carrier frequency. Under high dynamic conditions, the first-order and second-order change rates of the Doppler frequency attached to the received signal further increase the Doppler frequency agility, making it difficult for the carrier tracking loop to maintain steady-state tracking. To address these issues, a high dynamic velocity locked loop (HD-VLL) is proposed in this paper. Specifically, the accumulated phase tracking error caused by acceleration and jerk is first analyzed. Subsequently, to compensate for this phase tracking error with the system clock, the proposed loop adds an acceleration compensation module and a jerk compensation module. However, this results in the output of the high dynamic loop filter being updated with the system clock, which contradicts the multiplexing design of a traditional loop filter for parallel signal processing, making the hardware implementation of an HD-VLL impractical. Therefore, this contradiction leads us to design an HD-VLL-based multi-carrier NCO (HD-VLL-NCO). The HD-VLL and HD-VLL-NCO are simulated, revealing the HD-VLL’s superior dynamic adaptability and steady-state tracking, while the HD-VLL-NCO achieves comparable accuracy with the appropriate truncation bit width.

Effects of structural geometric nonlinearities on the transonic aeroelastic characteristics of wing

Effects of structural geometric nonlinearities on the transonic aeroelastic characteristics of wing

An undrained dynamic strain-pore pressure model for deep-water soft clays from the South China Sea

With the increasing use of oceans for engineering purposes, such as the installation of suction anchors and pipelines, the stability of seabed structures has become a pivotal concern and is intricately linked to the characteristics of seabed soils. This study focuses specifically on deep-sea soft clay, a predominant seabed soil type distinguished by its high water content, thixotropy, and low permeability. These clays are vulnerable to destabilization and damage when disturbed, thereby posing threats to seabed installations. While the existing literature extensively examines the cyclic behavior of clay, considering factors such as the pore pressure response and strain and deformation characteristics, there is a notable gap in research addressing the behavior of deep-sea soft clay under comprehensive stress levels and prolonged cyclic loading. In this study, cyclic shear tests of the natural marine clay of the South China Sea were conducted, and the cyclic stress ratio (CSR), overpressure consolidation ratio (OCR), consolidation ratio (Kc), and loading frequency were varied. It was found that the CSR, OCR, and Kc significantly impact the cumulative dynamic strain in deep-sea soft clay during undrained cyclic dynamic tests. Higher CSR values lead to increased dynamic strain and structural failure risk. Subsequently, a dynamic strain-dynamic pore pressure development model was proposed. This model effectively captures the cumulative plastic deformation and dynamic pore pressure development, showing correlations with the CSR, OCR, and Kc, thus providing insights into the deformation and pore pressure trends in deep-sea clay under high cyclic dynamic loading conditions. This research not only furnishes essential background information but also addresses a critical gap in understanding the behavior of deep-sea soft clay under cyclic loading, thereby enhancing the safety and stability of seabed structures.

Kalman Filter with Adaptive Covariance Estimation for Carrier Tracking under Weak Signals and Dynamic Conditions

Kalman filtering (KF)-based tracking has been commonly employed in global navigation satellite system (GNSS) receivers to achieve robust tracking. However, under more serious conditions, such as severe strength attenuation and abrupt dynamic coexisting environments, it is difficult for KF-based tracking to keep tracking well due to the fixed noise statistics. To further enhance the carrier tracking performance, this paper proposes an adaptive KF carrier tracking method for resisting signal strength fading and high dynamic environments. The proposed method introduces the adaptive factor to adjust the process noise covariance to accommodate the noise statistics in actual variable situations. Moreover, we apply the chi-square hypothesis test to detect system stability. The adaptive factor is only applied when the system is not stable, which can enhance computational efficiency. The proposed method is conducted in the GPS L1 software receivers. According to the results, the proposed algorithm can improve the robustness in tracking performance compared with other tracking methods under signal serious fading and high dynamic conditions. Using the proposed method, GNSS receivers’ navigation performance can be improved under complex conditions.

INS aided spoofing detection of high dynamic GNSS receiver for launch vehicle applications: A loosely coupled approach

INS aided spoofing detection of high dynamic GNSS receiver for launch vehicle applications: A loosely coupled approach

MODERN APPROACHES TO FORECASTING CORPORATE INCOME TAX REVENUES IN THE RUSSIAN FEDERATION

The purpose of the study. The purpose of the study is to determine the optimal model for forecasting corporate income tax revenues. The subject of the study is modern methods of forecasting income tax revenues to the budgets of the subjects of the Russian Federation, based on mathematical and statistical, regression and autoregressive models with a moving average. The article identifies the advantages and disadvantages of existing approaches to forecasting tax revenues, as well as defines the conditions for the applicability of the considered models in conditions of high dynamics of changes in market conditions and macroeconomic uncertainty. The results of the study are presented, which make it possible to establish the optimal methodology for forecasting corporate income tax receipts, taking into account the statistical limitations of the planning horizon, as well as to identify a forecasting mechanism available for use in long-term planning. Conclusions. Based on the results of the study, it was concluded that it is advisable to combine tax forecasting models to achieve optimal predictive and analytical indicators, as well as to apply this approach only within the framework of short-term planning. The final forecast indicator can be identified on the basis of expert assessments, the average value of the indicators obtained, or through a combination of these approaches: an expert assessment of the weighting coefficients to calculate the weighted average value of the forecast indicator.

Magnetically Suspended Control Sensitive Gyroscope Rotor High-Precision Deflection Decoupling Method using Quantum Neural Network and Fractional-Order Terminal Sliding Mode Control

To achieve high-precision deflection control of a Magnetically Suspended Control and Sensitive Gyroscope rotor under high dynamic conditions, a deflection decoupling method using Quantum Radial Basis Function Neural Network and fractional-order terminal sliding mode control is proposed. The convergence speed and time complexity of the neural network controller limit the control accuracy and stability of rotor deflection under high-bandwidth conditions. To solve the problem, a quantum-computing-based structure optimization method for the Radial Basis Function Neural Network is proposed for the first time, where the input and the center of hidden layer basis function of the neural network are quantum-coded, and quantum rotation gates are designed to replace the Gaussian function. The parallel characteristic of quantum computing is utilized to reduce the time complexity and improve the convergence speed of the neural network. On top of that, in order to further address the issue of input jitter, a fractional-order terminal sliding mode controller based on the Quantum Radial Basis Function Neural Network is designed, the fractional-order differential sliding mode surface and the fractional-order convergence law are proposed to reduce the input jitter and achieve finite-time convergence of the controller, and the Quantum Radial Basis Function Neural Network is used to approximate the residual coupling and external disturbances of the system, resulting in improving the rotor deflection control accuracy. The semi-physical simulation experiments demonstrate the effectiveness and superiority of the proposed method.

Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law

In order to improve the accuracy and convergence speed of the steering law under the conditions of high dynamics, high bandwidth, and a small deflection angle, and in an effort to improve attitude measurement and control accuracy of the spacecraft, a spacecraft attitude measurement and control method based on variable speed magnetically suspended control sensitive gyroscopes (VSMSCSGs) and the fractional-order zeroing neural network (FO-ZNN) steering law is proposed. First, a VSMSCSG configuration is designed to realize attitude measurement and control integration in which the VSMSCSGs are employed as both actuators and attitude-rate sensors. Second, a novel adaptive steering law using FO-ZNN is designed. The matrix pseudoinverses are replaced by FO-ZNN outputs, which solves the problem of accuracy degradation in the traditional pseudoinverse steering laws due to the complexity of matrix pseudoinverse operations under high dynamics conditions. In addition, the convergence and robustness of the FO-ZNN are proven. The results show that the proposed FO-ZNN converges faster than the traditional zeroing neural network under external disturbances. Finally, a new weighting function containing rotor deflection angles is added to the steering law to ensure that the saturation of the rotor deflection angles can be avoided. Semi-physical simulation results demonstrate the correctness and superiority of the proposed method.