Random Loading Research Articles

Study of the kurtoses transmission of linear structures under stationary non-Gaussian random loadings

Recent research has discovered that the kurtoses of non-Gaussian stress loadings can significantly impact the fatigue life of in-service structures. To predict potential damage, a fatigue life estimation method based on Gaussian damage and a kurtosis-related corrective coefficient has been developed. However, the transmission of kurtoses from excitations to responses has not been well studied, particularly in multi-input cases. This hinders efforts to accelerate fatigue damage by controlling input kurtoses. Therefore, this paper aims to establish a kurtoses transmission model for a linear structure under multiple uncorrelated stationary non-Gaussian excitations generated by zero-memory non-linear method. Firstly, a single-input kurtosis transmission equation is proposed to establish the relationship between excitation kurtosis and response kurtosis. Using this equation, the response kurtosis is formulated with input kurtosis and the system parameters of a linear structure. Secondly, the response kurtosis of multi-input cases is deduced, and the study shows that the response kurtosis is the weighted sum of the kurtosis induced by each excitation. Finally, numerical validation and experimental studies are conducted to verify the accuracy of both the single-input and multi-input kurtoses transmission models. The validations demonstrate that the proposed models can predict the response kurtoses with satisfactory precision, regardless of the input spectral shape and the number of uncorrelated input forces.

Time-varying reliability models for parallel systems consisting of beam structures with crack flaws

Abstract. Time-varying reliability assessment of parallel systems of beam structures with crack defects is of great importance for structural safety evaluation. In this paper, time-varying reliability models for parallel systems with cracked beams are proposed. In the modeling process, the statistical correlation between crack depth, random working load, random strength degradation, and random stress response as well as the complex failure correlation jointly caused by these factors are considered. Based on the finite element analysis of the cracked beams, the reliability models are constructed by combining the neural network and the response surface agent model. The validity of the model is verified by the Monte Carlo simulation method. The results show that crack depth and working load dispersion have important effects on reliability and failure correlation.

Deep-learning approach based on multi-data fusion for damage recognition of marine platforms under complex loads

This paper presents an innovative deep-learning network underpinned by advanced data-fusion techniques developed explicitly for detecting structural damage in marine platforms. This study commences with a rigorous validation of the proposed methodology employing detailed experimental procedures and subsequently applies this method to identify damage under specific random load conditions utilizing state-of-the-art finite element analysis software. This entails the meticulous construction of an extensive database mirroring the real-life conditions encountered by a deep-water jacket platform in the South China Sea. By conducting thorough simulations based on the characteristic environmental loads of this marine area, the study succeeds in closely replicating real-world conditions. The developed damage-identification model, which is specifically adapted to the distinctive requirements of non-Gaussian white-noise loads, exhibits notable accuracy. The experimental outcomes derived from the application of the proposed deep-learning algorithm for data fusion indicate an impressive accuracy rate of 92.01%. In simulated scenarios involving complexly loaded jacket platforms, the model attains an accuracy of 88.25%, highlighting the robustness of the method and its wide applicability in the field of marine structural health monitoring.

Numerical Analysis of Crack Propagation in an Aluminum Alloy under Random Load Spectra

This study develops a rapid algorithm coupled with the finite element method to predict the fatigue crack propagation process and select the enhancement factor for the equivalent random load spectrum of accelerated fatigue tests. The proposed algorithm is validated by several fatigue tests of an aluminum alloy under the accelerated random load spectra. In the validation process, two kinds of panels with different geometries and sizes are used to calculate the stress intensity factor, critical crack length, and crack propagation life. The simulated and experimental findings indicate that when the aluminum alloy is in a low plasticity state, the crack propagation life exhibits a linear relationship with the acceleration factor. When the aluminum alloy is in a high plasticity state, this study proposes an empirical formula to calculate the equivalent stress intensity factor and crack propagation life. The normalized empirical formula is independent of the geometry and size of different samples, although the fracture processes are different in the two kinds of panels used in our study. Overall, the numerical method proposed in this paper can be applied to predict the fatigue crack propagation life for the random spectrum of large samples based on the results of the simulated accelerated crack propagation process and the accelerated fatigue tests of small samples to reduce the cost and time of the testing.

Calculation of ship floating state by quasi-Newton iteration method for onboard loading computer

ABSTRACT Calculating the floating state of a ship is the basic function of onboard loading computer, which is crucial for ship safety. Aiming at the deficiencies in the existing algorithms, we used the quasi-Newton iteration method to calculate the floating state of a ship. Firstly, the section model database of ship's hull was established by cutting the stereolithographic (STL) 3D model which is created by ship design software. Then, Sutherland–Hodgma polygon clipping algorithm and Shoelace Formula were used to calculate the Jacobian matrix. Finally, We selected a 108,000 DWT bulk carrier, ADMIRAL SCHMIDT, as an example to verify the correctness of the algorithm. We performed 100,000 random loading numerical tests, the average number of iterations was 2–3, and the number of convergence failures was zero. We calculated 24 typical standard loading conditions. We found the maximum average absolute error of the draught and trim were 0.0081 and −0.0283 m, respectively. The calculation error was far less than the requirements of the classification society. The results showed that the Quasi-Newton iteration method is simple to implement and easy to program, and has high robustness and accuracy and appropriate convergence. The method is suitable for the real-time calculation of a ship's floating state and has considerable engineering application value.

Optimizing fatigue life prediction of high strength bolts in bolted spherical joints

Bolted spherical joints (BSJs) are integral to large-span space grid structures commonly used in expansive public and industrial buildings. BSJs are susceptible to fatigue damage in high strength bolts due to variable random loads. This study summarized findings from prior fatigue tests, detailing the fatigue failure patterns and S–N curves for grade 10.9 M20, M30 high strength bolts, and grade 9.8 M39 high strength bolts in BSJs. By employing finite element analysis, the study determined the stress concentration factors for these bolts, which were then utilized in fatigue life estimations using the Heywood model and the local strain approach (LSA). Both methods could yield satisfactory predictions, but when it came to the Heywood model, particularly when modifying it in areas of high stress, it demonstrated superior accuracy in predicting the performance of M20, M30, and M39 high strength bolts. Additionally, incorporating initial defect considerations, fatigue life was predicted using the damage tolerance design method (DTDM). Finally, when comparing the fatigue life prediction results obtained from various methods, it became evident that the modified Heywood model outperformed the other methods. This not only provided a superior solution but also demonstrated user-friendliness, thereby establishing itself as the preferred option for predicting the lifespan of high strength bolts in BSJs.

Multi-sensor data fusion reconstruction method for vibration dynamic responses of aerospace structures

The dynamic responses of key locations are important inputs for the life and reliability assessment of spacecraft structures. Due to the limited sensing resources, most critical responses are difficult to measure directly. A structural dynamic response reconstruction method is necessary. The responses of target locations can be reconstructed based on the empirical mode decomposition (EMD) of measured signals and the modal superposition. However, the structural modal information contained in the measured signal of a single sensor is limited, affecting the reconstruction accuracy. In this paper, a response reconstruction method based on multi-sensor data fusion is proposed. It is applied to a main load-bearing structure of a spacecraft and its typical components to verify its strain response reconstruction effect under random vibration loads. The experimental results show that multi-sensor data fusion improves the strain reconstruction accuracy. The maximum reduction in reconstruction error is from 8.7% to 1.3%. The reconstruction accuracy is further improved with the increase in the number of sensors. The optimal weighted fusion strategy for this problem is the weights defined by the Euclidean distance (EUC) or the dynamic time warping distance (DTW). The fusion results show a better performance with the increase in the power of the defined distance. The proposed multi-sensor fusion method improves the reconstruction accuracy via supplementing structural information to each other and eliminating the instability of single measured signals. More accurate dynamic responses via reconstruction reduce the large input uncertainty in life prediction and lay the foundation for building structural digital twins and managing structural health more effectively.

MODELING OF PROSUMER LOAD PROFILES BASED ON BEHAVIORAL APPROACH

The article analyzes various approaches to the modeling of daily electricity load schedules and proposes a methodology for improving the "bottom-up" behavioral model of the load of household consumers. The method is based on averaging generated random load schedules for a given type of household on a particular day of the year. Averaging is carried out by season and length of daylight. Next, working days and weekends are distinguished in each interval. Despite some differences, this work does not separate holidays, Saturdays, and Sundays to avoid unnecessary details. The selected parameters for dividing the averaging intervals allow you to obtain a relatively compact set of model data and, at the same time, preserve the features of the load on different days of the year and hours of the day. Household load profiles with varying steps of day distribution and the main difference of such distribution are considered. Models that more accurately convey the sporadic nature of prosumer consumption compared to typical load schedules are built for two types of households. A detailed analysis of the averaged load graphs was carried out in comparison with the typical graph and the generated load graphs. Averaged load schedules are suitable for modeling the operating modes and control algorithms of the prosumer energy generation and storage system.

Development of a novel model matching decentralized controller design algorithm and its experimental validation through load frequency controller implementation in restructured power system using TMS320F28379D controlCARD

A three-stage decentralized controller design algorithm is developed to achieve setpoint tracking and disturbance rejection in MIMO systems with communication time delay, and nonlinearities such as saturation and dead band. The first stage involves reference model formulation. The second stage comprises equating approximate generalized time moments/approximate generalized Markov parameters of closed-loop system model with reference model at certain expansion points in s-plane to obtain synthesis-like equation, concerning products of unknown controller numerator and denominator polynomials. This process yields simultaneous linear equations, whose solution provides the coefficients of the product polynomials. In the third stage, the controller parameters are extracted from the product polynomials using exact model matching. The proposed method is illustrated by designing load frequency controller in traditional and restructured power systems under scenarios like system parameter uncertainties, random load variation, and time-varying communication delays. Simulation studies reveal the efficacy of the proposed technique over existing techniques. Furthermore, the practical implementation feasibility of the decentralized controller designed for the restructured power system is validated using the TMS320F28379D controlCARD.

Estimating the optimal duration of random loading as part of machine part durability research

Aim. Making an informed decision regarding the durability of machine parts requires information on the operational load that needs to be measured on a representative section of the track. It should not be too long as well. Thus, it is required to determine the optimal duration of implementation. The duration of implementation that is optimal in terms of the reliability of load registration is defined for a process that is stationary in a special sense. Stationarity in a special sense is defined specifically for the task of assessing the durability of a specific part. Methods. The use of spectral theory for the study of random processes is probably not the best way of examining non-stationary loading processes in the context of durability assessment. We believe it would be optimal to use a cycle counting procedure (rain flow method) with subsequent calculation of durability. A lemma and a theorem were formulated on the sufficient duration of implementation for a process that is stationary in a special sense. A sufficient duration of implementation is defined as a limit past which its increase will not lead to a noticeable change in the calculated durability. Results. The matters of stationarity of a process in a narrow sense and the required duration of implementation will help in planning operational tests to measure and record random processes of machine part loading. Both matters were examined in terms of fatigue damage accumulation using Miner linear damage rule, as well as the adjusted linear damage summation hypothesis taking into account the fatigue curve slope parameter m. Some practical engineering problems were examined, including the problem of the optimal duration of implementation of a mining machine whose loading process is characterized by a high degree of irregularity and the problem of finding the required duration of implementation of load recording in a rolling stock component. Conclusion. A theorem on the required and sufficient duration of implementation was formulated. In order to test the method, Markov transition matrix-based model processes were used. In addition, the method and theorem were tested using examples of some experimental processes obtained from operational tests of vehicles and production machines.

Neural network based fatigue lifetime prediction of metals subjected to block loading

Fatigue lifetime predictions for variable amplitude loading are primarily based on the linear damage accumulation rule of Palmgren–Miner, which does not account for load sequence effects. Various nonlinear models have been developed, but their generalization capability is limited. Although neural network models have been used for prediction of the lifetime of metals subjected to constant amplitude loading, random loading and two-level block loading sequences before, they have never been used for multi-level block loading to the authors knowledge. The primary goal of this study is the development of neural network models for fatigue life estimation of metals subjected to block loading. To achieve this, a sufficient amount of qualitative data is required. Therefore a large number of rotating bending fatigue experiments with constant amplitude and block loading sequences are carried out. This new data is combined with data gathered from literature, leading to the most extensive open-access collection of variable amplitude fatigue data published to date. Neural network models are trained with the developed dataset and compared to four cumulative damage models including the linear Palmgren–Miner rule and three non-linear models. It is concluded that the neural network model for multi-level block loading outperforms all of the considered analytical models.

Life-cycle integrity design method considering load robustness of offshore oil and gas equipment: SCSSV as a case study

Components that are vulnerable to the external environment and harsh working conditions easily fail during their life cycle under variable loads of offshore oil and gas equipment. The reliability of the system in the life cycle is reduced, various risks are increased, and substantial maintenance costs are generated. However, the current reliability-based design optimization method has difficulty meeting the situation that the life cycle is taken as the time dimension of design considering reliability, risk, and maintenance. To solve the problem, a life cycle integrity design optimization method considering robustness is proposed. A simplified integrity model is established through random load sampling and global sensitivity analysis. A multiobjective particle swam hierarchical optimization algorithm is proposed, in which hierarchical optimization order is determined by the priority of objectives, and the optimization design with structural integrity as the optimization objective is completed. The method is applied in the design of pressure pipeline of all-electric surface-controlled subsurface safety valve system.

Study on the applicability of a modified strain approach to predict the fatigue life of HFMI-treated transverse stiffeners under variable amplitude loading

AbstractThis paper analyses the applicability of a modified strain approach to predict the fatigue life of HFMI-treated transverse stiffeners under variable amplitude loading (VAL) with random load sequences of a p(1/3) and linear shaped spectrum. Local stresses are determined using linear-elastic finite element analyses. The measured weld geometry and component imperfections are considered. From the hardness of the HFMI-treated zone and the base material, the elastic–plastic material behaviour and Coffin-Manson parameters to describe the damage parameter Woehler curve are estimated. Based on a hysteresis counting method (HCM), the damage for each closed hysteresis is calculated. The applied notch strain approach includes the impact of residual stresses and the influence of surface roughness. Thus far, the application of similar approaches has only been validated for welded components with comparatively low residual stresses and HFMI-treated welds subjected to constant amplitude loading. To validate the accuracy of the approach for HFMI-treated welds under variable amplitude loading, the approximated fatigue life is compared to the number of cycles derived from experimental investigations. In this study, it is shown in conjunction with experimental results that it is essential to consider the strength of the base material near the weld when assessing the service life. This area can be more critical than the HFMI-treated weld toe.

Research on data-driven power flow calculation method based on undirected-graph delooping-backtracking

As the scale of the power grid expands and distributed energy sources are integrated, along with the emergence of random loads, topological control of distribution networks has become a novel means of control. Therefore, data-driven power flow calculations must be capable of rapidly and accurately computing power flow results even when there are changes in the network’s topology. In this paper, a data-driven power flow calculation method is proposed to take topological changes into account. Based on initial loop data, we employ an undirected-graph delooping-backtracking method to generate a set of feasible topological samples. Using the Monte Carlo method on this basis, we generate feasible samples for the network’s topology and power injection, thereby establishing a training dataset. By training a deep neural network on these samples and adjusting network parameters, we effectively address power flow calculations in the presence of topological changes. Case study results demonstrate that the data-driven power flow calculation method, considering topological changes, can rapidly and accurately compute power flow results when topology alterations occur.

Fatigue crack growth properties of PMMA material used in underwater transparent structures

ABSTRACT Polymethyl methacrylate (PMMA) is an ideal material used in underwater transparent structures such as submersible windows and the fully-transparent pressure chamber of the sightseeing submersibles. The failure of PMMA structures usually come from small crack-like defects. In this paper, the fatigue crack growth experiments were carried out on PMMA materials with different thicknesses (B = 3, 6, 12 mm) and stress ratios (R = 0.1, 0.3) as well as plane strain fracture toughness test for unstable crack propagation conditions. Thickness effect and dwell time effect are experimentally investigated in addition to load ratio effect. The applicability of an improved crack growth rate model on PMMA material is validated by test results. The application of this model for prediction of crack growth rates can greatly save experimental time under different working conditions and can be applied in fatigue assessment of full-transparent structures under random loading.

Modeling and experiments on the vibro-acoustic analysis of ring stiffened cylindrical shells with internal bulkheads: A comparative study

The vibro-acoustic response of ring stiffened cylindrical shells with internal bulkheads under forced excitation is presented. The numerical analysis model is established using the Jacobi Ritz-Boundary element method. The first-order shear deformation theory, multi-segment technique and artificial spring technology are applied to establish the theoretical model, and the Jacobi orthogonal polynomials are introduced to represent the displacement functions. The Newmark-β integration method is used to obtain the vibration response of the structure, and the time-domain Kirchhoff boundary integral formulation is applied to describe the exterior acoustic field. The vibration and sound radiation of the ring stiffened cylindrical shell under impact and narrow band random loading were measured. The comparative study reveals that the results obtained from the proposed method agree well with the experimental results. The stiffeners and bulkheads have a significant effect on the vibration characteristics of the structure. Additionally, some physical insights into the resonant peaks and sound pressure directivity of the cylindrical shells are provided.

Design and analysis of optimal AGC regulator for multi‐area power systems with TCPS and energy storage unit in deregulated environment

AbstractIn today's electric power network, fast changes are the norm, and auxiliary services such as automatic generation control (AGC) play a crucial role in maintaining the quality of the power supply. AGC ensures a balance between power generation, demand, and losses to sustain frequency stability and variation in tie‐line power within a set limit, even when the load changes. To accomplish this, it is always beneficial to consider new approaches to controlling the situation. This paper introduces the design of new AGC regulators that consider deviation in DC tie‐line power as an extra control variable for the turbine controller. In this study, three different deregulated power systems (containing two control areas), namely three thermal generations, the combination of one thermal and two hydro generations, and three hydro generations, including two power distribution companies (DISCOs) in each control area. These optimal AGC regulators are implemented in the proposed thermal–thermal–thermal system to carry out the various power contracts. The results have shown that the dynamic outcomes meet the AGC standards. To improve further dynamic results and the proposed systems' stability margins by incorporating redox flow batteries (RFB). In actual operating conditions, the system parameters do not remain constant due to the aging effect, assumptions made in simplifying the mathematical model, etc. Thus, ±50% deviations in the nominal value of system parameters to assess how well the optimal AGC regulators perform in the system under investigation. The suggested realistic AGC system incorporates many parameter fluctuations and works well with the optimal AGC regulators developed for the proposed plans. This study expanded to include a two‐area, thermal‐hydro‐hydro (THH) system under a deregulated framework connected via an asynchronous transmission link with or without a thyristor‐controlled phase shifter (TCPS) and RFB. The genetic algorithm (GA) can solve many issues and has global search, flexibility to varied problem types, intrinsic parallelism, and the ability to handle massive, complex search spaces. Thus, a two‐area deregulated hydro‐hydro‐hydro system with parallel tie‐lines utilizes GA‐PID, GA‐FOPID, and GA‐(1 + PI)‐FOPID controllers. Moreover, a random load disturbance (RLD) is employed in each section of the offered approach to show the resilience and elite performance of the proposed control strategy. To produce various dynamic reactions in the plans, MATLAB software version R2013a is employed.

Molecular diagnosis of Cytomegalovirus infection: clinical performance of the Aptima transcription-mediated amplification assay toward conventional qPCR chemistry on whole blood samples.

In this paper, we describe the clinical performance of a novel transcription-mediated amplification (TMA) assay for the detection and quantification of human Cytomegalovirus (HCMV) DNA from whole blood samples. This is a pivotal analysis in immunocompromised patients [transplanted, HIV-positive, and Hematopoietic Stem Cell (HSC) recipients], and molecular tests with high sensitivity and specificity are necessary to evaluate the HCMV viral load in these patients. To our knowledge, this is the first in-depth evaluation of TMA chemistry for HCMV diagnosis on whole blood samples. Moreover, also technical aspects of this assay make it suitable for clinical diagnostics.

Optical Myography-Based Sensing Methodology of Application of Random Loads to Muscles during Hand-Gripping Training.

Hand-gripping training is important for improving the fundamental functions of human physical activity. Bernstein's idea of "repetition without repetition" suggests that motor control function should be trained under changing states. The randomness level of load should be visualized for self-administered screening when repeating various training tasks under changing states. This study aims to develop a sensing methodology of random loads applied to both the agonist and antagonist skeletal muscles when performing physical tasks. We assumed that the time-variability and periodicity of the applied load appear in the time-series feature of muscle deformation data. In the experiment, 14 participants conducted the gripping tasks with a gripper, ball, balloon, Palm clenching, and paper. Crumpling pieces of paper (paper exercise) involves randomness because the resistance force of the paper changes depending on the shape and layers of the paper. Optical myography during gripping tasks was measured, and time-series features were analyzed. As a result, our system could detect the random movement of muscles during training.

Parameter and Topology Optimization of Structures in the Frequency Domain under Nevanlinna–Pick Interpolation Constraints

The design optimization of structures can be conducted in either the time domain or the frequency domain. The frequency domain approach is advantageous compared to its time domain counterpart, especially if the degree of freedom is large, the objectives and/or constraints are formulated in the frequency domain, or the structure is subject to random loading. In this paper, an attempt is undertaken to obtain feasible optimal solutions by implementing the Nevanlinna–Pick (NP) interpolation theory across multi-objective structural optimization problems in the frequency domain. The NP equations introduce a trade-off that originates from the interpolation theory for complex variables. According to the NP theory, a complex function cannot have an independent amplitude from its derivative at a certain frequency. Consequently, the frequency response of a physical system cannot be shaped arbitrarily at discrete frequencies. Our objectives within this paper include calculating the weight, natural frequency, fatigue life, frequency domain response, and its derivative. To illustrate our claims, sample parameter and topology optimization problems were formulated and solved, both with and without the NP constraints. It was found that the inclusion of NP constraints induced a considerable improvement in the optimal solutions, while also causing the convergence to the optimal solution to become smoother.