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Enhancing load frequency control and automatic voltage regulation in Interconnected power systems using the Walrus optimization algorithm.

This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations.

Fatigue Life Based Study of Electronic Package Mounting Locations on Printed Circuit Boards Subjected to Random Vibration Loads

Fatigue Life Based Study of Electronic Package Mounting Locations on Printed Circuit Boards Subjected to Random Vibration Loads

Advanced Sliding Mode Design for Optimal Automatic Generation Control in Multi-Area Multi-Source Power System Considering HVDC Link

The multi-area multi-source power system (MAMSPS), which uses a variety of power sources including gas, hydro, thermal, and renewable energy, has recently been implemented to balance the growing demand for electricity and the overall capacity for power generation. In this paper, an integral sliding mode control with a single-phase technique (ISMCSP) is applied to two areas, with each area including gas–wind–thermal power systems with HVDC system. Firstly, a two-area gas–wind–thermal power system with HVDC (TAGWTPSH) is the first model in this scheme to consider the parameter uncertainties of a MAMSPS. Secondly, sliding mode design law with a single-phase technique is introduced to alleviate chattering and oscillation problems. Then, power system stability is ensured by the Lyapunov control theory based on the new LMIs technique. Thirdly, the ISMCSP’s effectiveness in a MAMSPS is also assessed under random load patterns and parameter variations regarding settling time and over-/undershoot. The ISMCSP was created to alter the fundamental sliding mode control, and therefore the suggested approach performs better than recently published approaches. This is demonstrated by the frequency overshoot deviation value in frequency deviations: 0.7 × 10−3 to 2.8 × 10−3 for the TAGWTPSH with the suggested ISMCSP. In the last case, for random changes in load from −0.4 to +0.5 p. u, the proposed ISMCSP method still stabilizes the frequency of the areas meeting the standard requirements for AGC.

Low-resource dynamic loading identification of nonlinear system using pretraining

To address the challenge of load identification in nonlinear systems, an audio neural network-based method called WaveNet is proposed that leverages its capability to capture long-term dependencies in mechanical systems, enabling accurate load identification. Unlike traditional dynamic load identification methods that often encounter difficulties with matrix solutions, this approach takes advantage of WaveNet’s capabilities, enhancing both accuracy and efficiency. We integrate pre-training and transfer learning techniques to address the data scarcity challenges often encountered in real-world engineering applications. By transferring features across distributed datasets, this method reduces the dependency on single-task data, thereby improving model robustness. The performance of the WaveNet method is rigorously evaluated against traditional benchmarks such as Multilayer Perceptron (MLP) and Convolutional Neural Network (CNN) benchmarks under random load conditions applied to a complex structural framework. The proposed method achieves a root mean squared error (RMSE) of 1.521 and a determination coefficient (R²) of 0.996 in the random load case, demonstrating superior accuracy compared to other approaches. Moreover, its applicability is verified through simulations of both impact load and harmonic load scenarios, showcasing the effectiveness of transfer learning in overcoming domain discrepancies. Finally, the method is tested in random experiments to validate its engineering applicability. The results highlight the significant accuracy improvement in low-resource tasks achieved through pre-training, showcasing the potential and value of the proposed method.

Vibration response of nanobeams subjected to random reactions

Nanobeams composed of materials exhibiting flexoelectric properties have been successfully used in advanced technological equipment, including electronic circuits and very sensitive sensors, owing to their remarkable unique effects. Therefore, it is essential to determine their mechanical behavior as a practical need. This study employs an analytical methodology to provide a precise solution to the vibration issue of nanobeams under random stationary loads. Under such circumstances, the nanobeam is influenced by both the temperature and moisture conditions simultaneously. Additionally, the beam is supported by a viscoelastic foundation that considers both the viscous resistance parameter and the elastic parameter. Analytical formulations are derived by integrating classical beam theory with nonlocal strain gradient theory in order to elucidate the impact of size effects on nanobeams. This research also demonstrates the reliability verification, which clearly validates the accuracy of the calculation formula used in this work. This study examines the impact of material parameters, viscoelastic foundation, temperature, and moisture on the displacement spectrum at the middle and entire length of the beam. The study also explores how the flexoelectric effect decreases the displacement in the nanobeam. Subsequently, we provide scientifically derived findings that have significant relevance for building practical nanobeam specifications.

Localized Stochastic Dynamic Solution for Laminated Coupled Open Conical-Cylindrical Cabin System Based on the Condensation Method

This paper proposed a technical solution for quickly and accurately solving the stochastic dynamic characteristics of laminated coupled open conical-cylindrical cabin system. On the basic of first-order shear deformation theory (FSDT), the two-dimensional spectral Chebyshev method was introduced to obtain a unified dynamic matrix that included laminated conical and cylindrical panels. The middle part of the cabin was selected as the target substructure, while the precise dynamic condensation theory was used as a tool to establish a local dynamic analysis model of the cabin system based on comprehensive consideration of complex boundary conditions, coupling conditions, random load excitation and other factors. From a numerical analysis perspective, the local-level dynamic responses obtained from the model were validated to match well with the global-level results from the finite element method. Based on this numerical validation, a dynamic parametric analysis scheme was proposed, focusing on the local dynamic characteristics of the target substructure. This scheme analyzed the impact of the structural parameters of the middle part of cabin on the dynamic behaviors of the cabin system, providing technical guidance for the design optimization of the cabin system in engineering applications.

Experimental research on nonlinear vibration characteristics of double-layer mining string for deep-sea hydrate extraction under internal and external flow excitation

The vibration mechanism of the deep-sea hydrate mining string is extremely complex due to the combined effects of internal gas–liquid solid multiphase flow, structural contact collision, soil creep effect, and external ocean random load. Based on this, using the principle of similarity, a simulation experimental platform for the vibration of double-layer mining riser in deep-sea hydrate wells under internal and external flow excitation is developed, considering the vortex-induced effect of external flow field on the mining riser in the ocean section (which can simulate a maximum ocean flow velocity of 0.5 m/s), the three-phase flow-induced effect of gas–liquid–solid inside (which can simulate a maximum flow velocity of 2.0 m/s), and the coupling effect of mining string–conductor anchor node (CAN)–seabed. The influence of particle size, phase ratio, three-phase flow, and external flow velocity on the vibration response characteristics and nonlinear behavior of mining string are investigated. It is found that the vibration of vertical string is significantly affected by external ocean currents and internal three-phase currents. The vibration displacement amplitude of the horizontal section (average 0.08 mm) is significantly smaller than those of the vertical section (average 70 mm). The strong vibration positions of the vertical and horizontal sections of the mining string are different, in that the vertical section is mostly located below the middle section (just at 1800–2400 mm), while the horizontal section is mostly located at the three-phase inlet (just at 500 mm). The vertical section of the mining string presents a motion trajectory of oblique straight line, wide oblique straight line, or approximately wide oblique straight line, while the horizontal section is mostly a chaotic trajectory or an “8”-shaped chaotic trajectory. The decrease in particle mesh size and the increase in solid-phase proportion are reflected in the difficulty and accumulation of particle transport, leading to an increase in vibration displacement, as well as a decrease in vibration displacement amplitude and vibration energy. When the particle size set as 50 mesh, the displacement of mining string is largest, just for 110 mm of vertical section and 0.08 mm of horizontal section. The increase in the proportion of gas phase will lead to changes in the flow state of multiphase flow, which will affect the vibration displacement amplitude of the mining string to varying degrees. The increase in three-phase flow velocity further induces vibration of the mining string, and when the flow velocity is between 1.5 and 1.75 m/s, it will resonate with the string system, resulting in a sudden increase in the amplitude of vibration displacement. The research results can effectively guide operations and improve the service life of deep-sea hydrate mining riser.

Coupled critical plane-pseudo excitation method for multiaxial fatigue analysis of structures under random vibration

This study proposes a coupled critical plane–pseudo excitation method for assessing multiaxial fatigue damage in mechanical structures subjected to random loads. Within the modal coordinate framework, we derive an expression for the spectral moment of the structural stress response using the pseudo excitation method, which facilitates the decoupling of spatial characteristics from frequency domain properties. For the input power spectral density, represented as an integer power function, we employ eigenvalue decomposition and the residue theorem to derive an analytical expression for the spectral moment of the modal displacement response. By constructing equivalent stress modes based on the maximum shear stress and normal stress criteria, we obtain an expression for the equivalent stress variance. Intelligent optimization algorithms are utilized to determine the critical plane position and the corresponding equivalent stress spectral moments, followed by the application of the Dirlik method for fatigue assessment. A numerical example involving random vibration multiaxial fatigue analysis of an L-shaped thin-walled plate demonstrates the effectiveness of the proposed coupled critical plane–pseudo excitation method in comparison to the traditional critical plane method that relies on the stress covariance matrix for calculating equivalent variance. The results confirm the accuracy and efficiency of our approach, and we further explore the impact of different forms of the excitation power spectral density and the damping ratios on the computational outcomes.

Toward Limited Durability of Load-Bearing Beams of Metal Bridge Spans

The paper considers the limited durability as a structural property which continuously maintains operability during certain time under random loading of beam elements and proposes the definition for durability as the main criterion of failure and destruction of beam elements or beam as a whole.Methodology: Structural analysis; cumulative model of quasi-monotonic damage accumulation and failure of beam elements.Purpose: To develop methods to determine the durability based on damages representing a random, non-stationary loading process.Research findings: The damage accumulation is calculated for beams. The process is considered as quasi-monotonic. Stress-strain curves are obtained, including changes in probabilistic characteristics of not only structural materials, but also loading modes from the damage growth. The durability limitations of span girders are estimated both by nominal stresses and total damage in the more dangerous section.

Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration

Concerns over fossil fuel emissions and their hazardous effects have led to a shift away from conventional power plants and focus more on the expansion of renewable energy sources. This shift has resulted in reduced inertia and resulted in poor frequency control within electrical power systems. Hybrid Energy Storage Systems (HESS) have been proposed as an effective solution to enhance frequency stability and address the reduced inertia issue. This research evaluates three distinct control models for HESS, Incorporating Supercapacitor Energy Storage (SCES) and Battery Energy Storage Systems (BESS). To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. The performances of the three control models are evaluated based on three test scenarios incorporating uncertainties, reduced inertia, and uniform and random load disturbances. The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. Conversely, the Simultaneously Optimized Virtual Inertia And Virtual Synchronous Generator Controlled HESS (SO VI-VSG-HESS) excel in mitigating small frequency fluctuations with an average improvement in frequency standard deviation of 87.65 %. The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.

A New Stochastic Controller for Efficient Power Extraction from Small-Scale Wind Energy Conversion Systems under Random Load Consumption

This paper presents an innovative scheme to enhance the efficiency of power extraction from wind energy conversion systems (WECSs) under random loads. The study investigates how stochastic load consumption, modeled and predicted using a Markov chain process, impacts WECS efficiency. The suggested approach regulates the rectifier voltage rather than the rotor speed, making it a sensorless and reliable method for small-scale WECSs. Nonlinear WECS dynamics are represented using Takagi–Sugeno (TS) fuzzy modeling. Furthermore, the closed-loop system’s stochastic stability and recursive feasibility are guaranteed regardless of random load changes. The performance of the suggested controller is compared with the traditional perturb-and-observe (P&O) algorithm under varying wind speeds and random load variations. Simulation results show that the proposed approach outperforms the traditional P&O algorithm, demonstrating higher tracking efficiency, rapid convergence to the maximum power point (MPP), reduced steady-state oscillations, and lower error indices. Enhancing WECS efficiency under unpredictable load conditions is the primary contribution, with simulation results indicating that the tracking efficiency increases to 99.93%.

Ratcheting-fatigue behavior and fracture mechanism of 316H ASS under cyclic random loading block

In this study, a set of programmed random factors with non-zero mean were designed. Then various stress levels (15, 18 and 22 KN) were multiple superimposed to factors to form one random loading block (RLB), the blocks were repeated to failure to investigate the synergistic damage of 316H ASS under low-cycle fatigue (LCF), high-cycle fatigue (HCF) and ratcheting effect. The lifetime of cyclic RLB tests decreased with the increase of block-mean stresses σmBlock (208、255 and 311.5 MPa). The normalized strain amplitudes indicate that when the σmBlock amplitude below the yield strength (208 and 255 MPa), a stable ratchet accumulation phase allows the specimens to exhibit cyclic hardening behavior. When σmBlock exceeds the yield strength (311.5 MPa), the ratcheting strain increases significantly and the specimens exhibit cyclic softening behavior. Especially, the transgranular cleavage fracture, quasi-cleavage fracture and intergranular secondary cracks were identified when the failure of cyclic RLB tests were induced by LCF, HCF and ratcheting. With the increase of σmBlock amplitude, the decrease of LAGB proportion and the increase of dislocation density further reduce the fatigue resistance. In addition to dislocation motion, the α’-martensite phase transformation induced by ratcheting-fatigue has been further demonstrated as a mechanism for coordinated deformation. The percentage of stresses (within one block) that exceeds the diverge critical stress (375.6 MPa) of stacking faults (SFs) determines the α’-martensite nucleation mechanism.

Fatigue Crack Propagation Life of Metallic Materials Under Random Loading: A Coupling Analysis Method in the Frequency Domain

ABSTRACTThis paper proposes an equivalent spectrum method to predict the fatigue crack propagation (FCP) life of metallic materials subjected to random loading. To adequately account for the coupling effects between crack propagation and the random response of structures, a coupling analysis model is introduced. The stress intensity factor (SIF) can be estimated based on the power spectral density (PSD) of an equivalent displacement. Random vibration fatigue tests were conducted to evaluate the proposed model on aluminum alloy specimens. Results indicate significant variations in natural frequency with crack length. The predicted results are compared with the experimental values, demonstrating satisfactory prediction accuracy of the proposed coupling analysis model. This model enables the assessment of coupling effects between crack length and random response, facilitating more precise predictions of FCP life in metallic materials and guiding the expanded application of damage tolerance criteria in structural engineering.

Dynamic Response Analysis of Asphalt Pavement under Pavement-Unevenness Excitation

This paper investigates and analyzes the dynamic response of asphalt pavement under pavement-unevenness excitation based on an orthogonal vector function system and efficient DVP (dual variable and position) method. Firstly, starting from the pavement unevenness of the vehicle excitation source, the pavement-unevenness excitation is established by using the filtered white-noise method, and the random load of the vehicle model is obtained by simulation. Then, based on the basic governing equation of the road-surface problem under the random load, the analytical solution of the road-surface mechanical response is obtained by using the orthogonal vector function system and DVP method. The effects of pavement-unevenness grade, vehicle speed, vehicle load, interlayer contact condition, and transverse isotropy on the mechanical response of the road surface are analyzed via the analytical results. The results show that DVP can effectively solve the dynamic response of pavements under the excitation of pavement unevenness; in addition, it can also be applied to certain situations, such as transverse isotropy of materials and interface conditions. The results show that the pavement unevenness does not affect the average stress and strain of each layer but has a significant effect on the peak value and dispersion degree. An increase in vehicle speed causes a peak in strain and a larger coefficient of variation. Poor bonding between interfaces can lead to increased stress and strain at the bottom of the surface layer.

A novel bidirectional LSTM network model for very high cycle random fatigue performance of CFRP composite thin plates

This study proposes a novel Double-layer Bidirectional Long Short-Term Memory (BiLSTM) neural network model, shorted as TDA-BiLSTM, which integrates Transfer learning and Attention mechanisms. The model aims to predict the fatigue life of carbon fiber reinforced polymer (CFRP) thin plate structures subjected to very high cycle random vibration fatigue loads. Distinct from conventional servo-hydraulic and ultrasonic fatigue testing methods, this research pioneers the use of a vibration table for very high cycle fatigue (VHCF) testing to fill the gap in the field. By training and validating data across various life ranges, the TDA-BiLSTM model demonstrates significant advantages in training speed and predicting accuracy. Its bidirectional structure and attention mechanism effectively capture complex patterns and long-term dependencies in sequence data. Experimental results indicate that the TDA-BiLSTM model achieves significantly lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) compared to Long Short-Term Memory (LSTM) and Long Short-Term Memory with Transfer learning (Tr-LSTM) models across different life ranges on the ε-N curve, indicating higher accuracy and stability in strain life prediction tasks. Additionally, an analysis of typical damage areas using Scanning Electron Microscopy (SEM) reveals the failure mechanisms of CFRP plates under very high cycle vibration fatigue loads.

Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications

This study investigates the application of a PID controller with a fractional derivative component (PIDDμ), optimized using the stochastic fractional search (SFS) technique, for load frequency control (LFC) in power systems. Additionally, solar PV and battery energy storage systems (BESS) and flywheel energy storage systems (FESS) are integrated as backup sources to enhance the LFC performance. To assess the effectiveness of the proposed approach, three error metrics—Integral Time Absolute Error (ITAE), Integral Time Multiplied Square Error (ITSE), and Integral of Absolute Error (IAE)—are evaluated. The results are compared with recent optimization-based LFC techniques across various scenarios. It is found that the SFS-PIDDμ achieves IAE=0.006786, ITSE=1.07e-05, and ITAE=0.01853, which are significantly lower than the error values produced by other LFC techniques. Furthermore, integrating solar PV, along with BESS and FESS, further reduces these error values. The graphical LFC responses of the SFS-PIDDμ outperform other optimization-based LFC techniques. The robustness of the approach is also validated against random load changes of varying magnitudes and for broader parametric variations.

A numerical procedure for calculating ice-induced fatigue damage for ship hulls in level ice

Ship hulls advancing in level ice are exposed to considerable cyclic ice loadings, which might cause fatigue damage, threatening the structural integrity and endangering the crews’ lives. Ice-induced fatigue problem is of significance to ice-going ships. In this paper, a fatigue analysis for ship structures in level ice is performed based on a dedicated 6-degree-of-freedom (6-DOF) numerical model of ice-ship interaction, founded on a circumferential crack assumption. The numerical procedure considers the time-varying instantaneous waterline and the couplings between ship motions and external forces. The local ice loads used for fatigue assessment can be obtained from numerical simulations, and the random load peaks are represented by Weibull distribution. A case study of fatigue calculation for designated transverse frames is carried out, of which the applied stress is converted from ice loads by means of structural beam theory. Eventually, according to a proper S-N curve, the fatigue damages are evaluated on the basis of Palmgren–Miner rule, respectively under the operational scenarios of laterally symmetrical and asymmetrical initial ice edges.

Cyclic bond behavior and bond stress – slip model of steel strands in steel fiber reinforced concrete

To study the bond performance of steel strands in steel fiber reinforced concrete (SFRC), bonding tests under monotonic and cyclic loads were performed on the specimens with different steel fiber volume fractions (SFVFs), bond lengths, nominal diameters of steel strands and SFRC strengths. The results showed that the relative rotation between the steel strand and SFRC occurred when the steel strands were vertically pulled out from SFRC due to the smooth and continuous helical shape of the steel strands. For the specimens with the same parameters, the maximum bond stress under cyclic load decreased by 1.67–22.88 % than that under monotonic load. The maximum bond stress under cyclic load increased with the increasing SFVFs or SFRC strength. Notably, the maximum bond stress under cyclic load also increased with the increasing bond length or diameter of steel strands, significantly different from that of ordinary ribbed steel bars and FRP bars. The cumulative energy dissipation (CED) of bond specimens increased with the diameter of steel strands and SFRC strength. Besides, the SFVFs had a positive effect on the CED, but simultaneously increasing diameter of steel strands would weaken the positive effect of SFVFs, and simultaneously increasing bond length had no obvious on the CED. Finally, a bond stress – slip model of steel strands in SFRC was established, suitable for calculating bond stress – slip curves under random and complicated loading schemes. By comparing the calculation and test results of bond stress – slip curves, it was proved that the proposed model had an acceptable accuracy and could describe the influence laws of SFVF, bond length, nominal diameter of steel strand and SFRC strength well.

Method for assessing the durability of structures under stationary and non-stationary random loading using variational mode decomposition (VMD)

In the era of digital transformation, most devices are equipped with a variety of sensors, which provide information to be used in developing intelligent models for predicting the fatigue life. The development of digital models of real objects for fatigue life estimation faces the lack of algorithms for performing such an estimation. The problem arises in the adaptive and automatic analysis of signals from real sensors installed on the object and their subsequent processing to estimate the fatigue life of the object. We propose a new method for assessing the fatigue life of structures based on application of the adaptive method of variational mode decomposition to signals gained from sensors, including non-stationary ones. Variational mode decomposition involves decomposition of an initial complex random process into simpler random processes (modes) that are stationary and narrowband. An original method of summarizing damage resulted from the action of the modes obtained as a result of the decomposition is used. The developed method can be used as an algorithmic support for the generation of digital doubles of the residual lifetimes of natural products. The proposed method is compared with the «rainflow» method in the time domain. Different realizations of random stationary and non-stationary signals with different bandwidths are compared numerically. In addition, the traditional frequency methods of Dirlik and Benasciutti have been compared with the «rainflow» method. The analysis showed good results for the proposed method, i.e., the error was smaller compared to traditional frequency methods, especially for non-stationary processes.

Vibration response analysis of multilayer functionally graded graphene platelets reinforced composite cylindrical shell under moving random loads

Vibration response analysis of multilayer functionally graded graphene platelets reinforced composite cylindrical shell under moving random loads