A novel approach to the dynamic response analysis of Euler-Bernoulli beams resting on a Winkler soil model and subjected to impact loads

This work presents a novel approach to the dynamic response analysis of a Euler-Bernoulli beam resting on a Winkler soil model and subjected to an impact loading.The approach considers that damping has much less importance in controlling the maximum response to impulsive loadings because the maximum response is reached in a very short time,before the damping forces can dissipate a significant portion of the energy input into the system.The development of two sine series solutions,relating to different types of impulsive loadings,one involving a single concentrated force and the other a distributed line load,are presented.This study revealed that when a simply supported Euler-Bernoulli beam,resting on a Winkler soil model,is subject to an impact load,the resulting vertical displacements,bending moments and shear forces produced along the span of the beam are considerably affected.In particular,the quantification of this effect is best observed,relative to the corresponding static solution,via an amplification factor.The computed impact amplification factors,for the sub-grade moduli used in this study,were in magnitude greater than 2,thus confirming the multiple-degree-of-freedom nature of the problem.

A discussion about the limitations of the Eurocode’s high-speed load model for railway bridges

High-speed railway bridges are subjected to normative limitations concerning maximum permissible deck accelerations.For the design of these structures,the European norm EN 1991-2 introduces the high-speed load model(HSLM)—a set of point loads intended to include the effects of existing high-speed trains.Yet,the evolution of current trains and the recent development of new load models motivate a discussion regarding the limits of validity of the HSLM.For this study,a large number of randomly generated load models of articulated,conventional,and regular trains are tested and compared with the envelope of HSLM effects.For each type of train,two sets of 100,000 load models are considered:one abiding by the limits of the EN 1991-2 and another considering wider limits.This comparison is achieved using both a bridge-independent metric(train signatures)and dynamic analyses on a case study bridge(the Canelas bridge of the Portuguese Railway Network).For the latter,a methodology to decrease the computational cost of moving loads analysis is introduced.Results show that some theoretical load models constructed within the stipulated limits of the norm can lead to effects not covered by the HSLM.This is especially noted in conventional trains,where there is a relation with larger distances between centres of adjacent vehicle bogies.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Accuracy assessment of global vertical displacement loading tide models for the equatorial and Indian Ocean

The three-dimensional displacements caused by ocean loading effects are significant enough to impact spatial geodetic measurements on sub-daily or longer timescales,particularly in the vertical direction.Currently,most tide models incorporate the distribution of vertical displacement loading tides;however,their accuracy has not been assessed for the equatorial and Indian Ocean regions.Global Positioning System(GPS)observations provide high-precision data on sea-level changes,enabling the assessment of the accuracy and reliability of vertical displacement tide models.However,because the tidal period of the K_(2) constituent is almost identical to the orbital period of GPS constellations,the estimation of the K_(2) tidal constituent from GPS observations is not satisfactory.In this study,the principle of smoothness is employed to correct the systematic error in K_(2) estimates in GPS observations through quadratic fitting.Using the adjusted harmonic constants from 31 GPS stations for the equatorial and Indian Ocean,the accuracy of eight major constituents from five global vertical displacement tide models(FES2014,EOT11a,GOT4.10c,GOT4.8,and NAO.99b)is evaluated for the equatorial and Indian Ocean.The results indicate that the EOT11a and FES2014 models exhibit higher accuracy in the vertical displacement tide models for the equatorial and Indian Ocean,with root sum squares errors of 2.29 mm and 2.34 mm,res-pectively.Furthermore,a brief analysis of the vertical displacement tide distribution characteristics of the eight major constituents for the equatorial and Indian Ocean was conducted using the EOT11a model.

Data-Driven Modeling for Wind Turbine Blade Loads Based on Deep Neural Network

Blades are essential components of wind turbines.Reducing their fatigue loads during operation helps to extend their lifespan,but it is difficult to quickly and accurately calculate the fatigue loads of blades.To solve this problem,this paper innovatively designs a data-driven blade load modeling method based on a deep learning framework through mechanism analysis,feature selection,and model construction.In the mechanism analysis part,the generation mechanism of blade loads and the load theoretical calculationmethod based on material damage theory are analyzed,and four measurable operating state parameters related to blade loads are screened;in the feature extraction part,15 characteristic indicators of each screened parameter are extracted in the time and frequency domain,and feature selection is completed through correlation analysis with blade loads to determine the input parameters of data-driven modeling;in the model construction part,a deep neural network based on feedforward and feedback propagation is designed to construct the nonlinear coupling relationship between the unit operating parameter characteristics and blade loads.The results show that the proposed method mines the wind turbine operating state characteristics highly correlated with the blade load,such as the standard deviation of wind speed.The model built using these characteristics has reasonable calculation and fitting capabilities for the blade load and shows a better fitting level for untrained out-of-sample data than the traditional scheme.Based on the mean absolute percentage error calculation,the modeling accuracy of the two blade loads can reach more than 90%and 80%,respectively,providing a good foundation for the subsequent optimization control to suppress the blade load.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Modeling the blast load induced by a close-in explosion considering cylindrical charge parameters

Structural damage is significantly influenced by the various parameters of a close-in explosion.To establish a close-in blast loading model for cylindrical charges according to these parameters,a series of field experiments and a systematic numerical analysis were conducted.A high-fidelity finite element model developed using AUTODYN was first validated using blast data collected from field tests conducted in this and previous studies.A quantitative analysis was then performed to determine the influence of the charge shape,aspect ratio(length to diameter),orientation,and detonation configuration on the characteristics and distributions of the blast loading(incident peak overpressure and impulse)according to scaled distance.The results revealed that the secondary peak overpressure generated by a cylindrical charge was mainly distributed along the axial direction and was smaller than the overpressure generated by an equivalent spherical charge.The effects of charge shape on the blast loading at 45°and 67.5°in the axial plane could be neglected at scaled distances greater than 2 m/kg^(1/3);the effect of aspect ratios greater than 2 on the peak overpressure in the 90°(radial)direction could be neglected at all scaled distances;and double-end detonation increased the radial blast loading by up to 60%compared to singleend detonation.Finally,an empirical cylindrical charge blast loading model was developed considering the influences of charge aspect ratio,orientation,and detonation configuration.The results obtained in this study can serve as a reference for the design of blast tests using cylindrical charges and aid engineers in the design of blast-resistant structures.

A robust optimization model for demand response management with source-grid-load collaboration to consume wind-power

To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.

Finite-difference model of land subsidence caused by cluster loads in Zhengzhou,China

Groundwater exploitation has been regarded as the main reason for land subsidence in China and thus receives considerable attention from the government and the academic community.Recently,building loads have been identified as another important factor of land subsidence,but researches in this sector have lagged.The effect of a single building load on land subsidence was neglected in many cases owing to the narrow scope and the limited depth of the additional stress in stratum.However,due to the superposition of stresses between buildings,the additional stress of cluster loads is greater than that of a single building load under the same condition,so that the land subsidence caused by cluster loads cannot be neglected.Taking Shamen village in the north of Zhengzhou,China,as an example,a finite-difference model based on the Biot consolidation theory to calculate the land subsidence caused by cluster loads was established in this paper.Cluster loads present the characteristics of large-area loads,and the land subsidence caused by cluster loads can have multiple primary consolidation processes due to the stress superposition of different buildings was shown by the simulation results.Pore water migration distances are longer when the cluster loads with high plot ratio are imposed,so that consolidation takes longer time.The higher the plot ratio is,the deeper the effective deformation is,and thus the greater the land subsidence is.A higher plot ratio also increases the contribution that the deeper stratigraphic layers make to land subsidence.Contrary to the calculated results of land subsidence caused by cluster loads and groundwater recession,the percentage of settlement caused by cluster loads in the total settlement was 49.43%and 55.06%at two simulated monitoring points,respectively.These data suggest that the cluster loads can be one of the main causes of land subsidence.

Dynamic stability analysis of porous functionally graded beams under hygro-thermal loading using nonlocal strain gradient integral model

We present a study on the dynamic stability of porous functionally graded(PFG)beams under hygro-thermal loading.The variations of the properties of the beams across the beam thicknesses are described by the power-law model.Unlike most studies on this topic,we consider both the bending deformation of the beams and the hygro-thermal load as size-dependent,simultaneously,by adopting the equivalent differential forms of the well-posed nonlocal strain gradient integral theory(NSGIT)which are strictly equipped with a set of constitutive boundary conditions(CBCs),and through which both the stiffness-hardening and stiffness-softening effects of the structures can be observed with the length-scale parameters changed.All the variables presented in the differential problem formulation are discretized.The numerical solution of the dynamic instability region(DIR)of various bounded beams is then developed via the generalized differential quadrature method(GDQM).After verifying the present formulation and results,we examine the effects of different parameters such as the nonlocal/gradient length-scale parameters,the static force factor,the functionally graded(FG)parameter,and the porosity parameter on the DIR.Furthermore,the influence of considering the size-dependent hygro-thermal load is also presented.

Mesoscopic modelling of UHPCC material under dynamic tensile loadings

This paper presents a new 3D mesoscopic model of ultra-high performance cement-based composite(UHPCC)to investigate its dynamic tensile behavior.In this model,the UHPCC is regarded as a two-phase material composed of cementitious matrix and randomly distributed fibers.The model is established using the commercial software LS-DYNA and involves generating the randomly distributed fiber elements with considerations of diameter,length,orientation and volume fraction,and then fully constraining them with the matrix.In particular,to capture the slipping effect between fibers and matrix that has a strong influence on the dynamic tensile behavior,the fibers are modelled by a fictitious material represented by the load-slip relation.The strain-rate effect of slipping force neglected in most of previous studies is considered by calibrating constitutive parameters of the fictitious material under different strain-rates based on the single fiber pullout tests.Finally,the 3D mesoscopic model is validated against three sets of tension-dominated experiments covered a wide range of loading intensity.Numerical predictions demonstrate that strain-rate effect of slipping force must be considered,and the neglect of it may lead to a great underestimation of the dynamic tensile strength of UHPCC material and would unavoidably underestimate the blast resistance of UHPCC components.

Finite-time economic model predictive control for optimal load dispatch and frequency regulation in interconnected power systems

This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.

Mechanical responses and acoustic emission behaviors of coal under compressive differential cyclic loading(DCL):a numerical study via 3D heterogeneous particle model

The stability of coal walls(pillars)can be seriously undermined by diverse in-situ dynamic disturbances.Based on a 3D par-ticle model,this work strives to numerically replicate the major mechanical responses and acoustic emission(AE)behaviors of coal samples under multi-stage compressive cyclic loading with different loading and unloading rates,which is termed differential cyclic loading(DCL).A Weibull-distribution-based model with heterogeneous bond strengths is constructed by both considering the stress-strain relations and AE parameters.Six previously loaded samples were respectively grouped to indicate two DCL regimes,the damage mechanisms for the two groups are explicitly characterized via the time-stress-dependent variation of bond size multiplier,and it is found the two regimes correlate with distinct damage patterns,which involves the competition between stiffness hardening and softening.The numerical b-value is calculated based on the mag-nitudes of AE energy,the results show that both stress level and bond radius multiplier can impact the numerical b-value.The proposed numerical model succeeds in replicating the stress-strain relations of lab data as well as the elastic-after effect in DCL tests.The effect of damping on energy dissipation and phase shift in numerical model is summarized.

Applications of AnnAGNPS Model for Sediment and Nutrient Loadings for Funiu Mountain Area, China

The main goal of this study was to evaluate the performance of AnnAGNPS(Annualized AGricultural NonPoint Source)pollution model,in calculating runoff,sediment loading and nutrient loadings for Funiu Mountain area.Most of the model input parameters were sourced from Luanchuan Forest Ecology Station(LFES)in Funiu Mountain area.The data on 23 storms in 2018 was used to calibrate the model and the data on 33 storms in 2019 for validation.The whole evaluation consisted of determining the coefficient of determination(R^(2)),Nash-Sutcliffe coefficient of efficiency(E),and the percentage volume error(VE).Results showed that the runoff volumes were underpredicted by 5.0%with R^(2) of 0.93(P<0.05)during calibration and underpredicted by 5.3%with R^(2) of 0.90(P<0.05)during validation.But sediment loading was able to produce a moderate result.The model underpredicted the daily sediment loading by 15.1%with R^(2) of 0.63(P<0.05)during calibration and 13.5%with R^(2) of 0.66(P<0.05)during validation.Nitrogen loading was overpredicted by 20.3%with R^(2)=0.68(P<0.05),and phosphorus loading performance was slightly poor with R^(2)=0.65(P<0.05)during validation.In general,the model performed well in simulating runoff compared to sediment loading and nutrient loadings.

Research on AC Electronic Load with Energy Recovery Based on Finite Control Set Model Predictive Control

Nowadays,AC electronic loads with energy recovery are widely used in the testing of uninterruptible power supplies and power supply equipment.To tackle the problems of control difficulty,strategy complexity,and poor dynamic performance of AC electronic load with energy recovery of the conventional control strategy,a control strategy of AC electronic load with energy recovery based on Finite Control Set Model Predictive Control(FCSMPC)is developed.To further reduce the computation burden of the FCS-MPC,a simplified FCS-MPC with transforming the predicted variables and using sector to select expected state is proposed.Through simplified model and equivalent approximation analysis,the transfer function of the system is obtained,and the stability and robustness of the system are analyzed.The performance of the simplified FCS-MPC is compared with space vector control(SVPWM)and conventional FCS-MPC.The results show that the FCS-MPC method performs better dynamic response and this advantage is more obvious when simulating high power loads.The simplified FCS-MPC shows similar control performance to conventional FCS-MPC at less computation burden.The control performance of the system also shows better simulation results.

Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

In the conventional technique,in the evaluation of the severity index,clustering and loading suffer from more iteration leading to more com-putational delay.Hence this research article identifies,a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects.The polynomial load modelling or ZIP(constant impedances(Z),Constant Current(I)and Constant active power(P))is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security.The process of finding the severity of the line using a Hybrid Line Stability Ranking Index(HLSRI)is used for assisting the concepts of machine learning with J48 algorithm,infers the superior affected lines by adopting the IEEE standards in concern to be compensated in maintaining the power system stability.The simulation is performed in the WEKA environment and deals with the supervisor learning in order based on severity to ensure the safety of power system.The Unified Power Flow Controller(UPFC),facts devices for the purpose of compensating the losses by maintaining the voltage characteristics.The finite element analysis findings are compared with the existing procedures and numerical equations for authentications.

A Study on the Load Modeling of Railway Vehicles Using PSCAD/EMTDC Based on MVDC

This paper,the kinetic equation,traction force,and braking force for railway trains are reviewed.In addition,the driving characteristics are interpreted as to how the power of the electric vehicle relates to the weight,speed,track curve,and track gradient of the electric vehicle.The driving characteristics of these trains are analyzed through PSCAD/EMTDC(power systems computer aided design/electromagnetic transients including DC)modeling.

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.

Study of Load Modeling Technology on Hardware-in-the-Loop Simulator of Gun Servo System

A hardware-in-the-loop (HWIL) simulator for gun servo system is described in this paper, and its load modeling technologies,such as road spectrum model,sea wave model are studied. The simulation results show that the models can be used in HWIL and satisfy the requirements of hardware-in-the-loop simulator of gun servo system.

A Joint Model of Device Load and User Intention in Load Monitoring

In this paper, a concept for the joint modeling of the device load and user intention is presented. It consists of two coupled models, a device load model to characterize the power consumption of an electric device of interest, and a user intention model for describing the user intentions which cause the energy consumption. The advantage of this joint model is the ability to predict the device load from the user intention and to reconstruct the user intention from the measured device load. This opens a new way for load monitoring, simulation and prediction from the perspective of users instead of devices.