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.

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.

Numerical modeling of centrifuge cyclic lateral pile load experiments

To gain insight into the inelastic behavior of piles, the response of a vertical pile embedded in dry sand and subjected to cyclic lateral loading was studied experimentally in centrifuge tests conducted in Laboratoire Central des Ponts et Chaussees. Three types of cyclic loading were applied, two asymmetric and one symmetric with respect to the unloaded pile. An approximately square-root variation of soil stiffness with depth was obtained from indirect in-flight density measurements, laboratory tests on reconstituted samples, and well-established empirical correlations. The tests were simulated using a cyclic nonlinear Winkler spring model, which describes the full range of inelastic phenomena, including separation and re-attachment of the pile from and to the soil. The model consists of three mathematical expressions capable of reproducing a wide variety of monotonic and cyclic experimentalp-y curves. The physical meaning of key model parameters is graphically explained and related to soil behavior. Comparisons with the centrifuge test results demonstrate the general validity of the model and its ability to capture several features of pile-soil interaction, including： soil plastification at an early stage of loading, ＂pinching＂ behavior due to the formation of a relaxation zone around the upper part of the pile, and stiffness and strength changes due to cyclic loading. A comparison of the p-y curves derived from the test results and the proposed model, as well as those from the classical curves of Reese et al. （1974） for sand, is also presented.

Testing and modeling of cyclically loaded rock anchors

The Norwegian Public Roads Administration(NPRA) is planning for an upgrade of the E39 highway route at the westcoast of Norway. Fixed links shall replace ferries at seven fjord crossings. Wide spans and large depths at the crossings combined with challenging subsea topography and environmental loads call for an extension of existing practice. A variety of bridge concepts are evaluated in the feasibility study. The structures will experience significant loads from deadweight, traffic and environment. Anchoring of these forces is thus one of the challenges met in the project. Large-size subsea rock anchors are considered a viable alternative. These can be used for anchoring of floating structures but also with the purpose of increasing capacity of fixed structures. This paper presents first a thorough study of factors affecting rock anchor bond capacity. Laboratory testing of rock anchors subjected to cyclic loading is thereafter presented. Finally, the paper presents a model predicting the capacity of a rock anchor segment, in terms of a ribbed bar, subjected to a cyclic load history. The research assumes a failure mode occurring in the interface between the rock anchor and the surrounding grout. The constitutive behavior of the bonding interface is investigated for anchors subjected to cyclic one-way tensile loads. The model utilizes the static bond capacity curve as a basis, defining the ultimate bond sbuand the slip s1 at τ. A limited number of input parameters are required to apply the model. The model defines the bond-slip behavior with the belonging rock anchor capacity depending on the cyclic load level(τcy/τ), the cyclic load ratio(R= τcy/τcy), and the number of load cycles(N). The constitutive model is intended to model short anchor lengths representing an incremental length of a complete rock anchor.

Numerical Modeling of Response and Damage of Masonry Walls to Blast Loading

To model the damage process of masonry walls under blast loading, a dynamic continuum damage material model is constructed for brick and mortar separately. The degradation of both the stiffness and strength are governed by a damage variable. By using the proposed material model, damage and fragmentation of a typical masonry wall under blast loading at different scaled distances is calculated. The hazard level of the masonry wall to blast loading is evaluated by analyzing the numerical results.

Acid deposition critical loads modeling for the simulation of sulfur exceedance and reduction in Guangdong, China

The current acid deposition critical loads in Guangdong, China were calculated using the PROFILE model with a 3 km × 3 km resolution. Calculations were carded out for critical loads of potential acidity, actual acidity, sulfur and nitrogen, with values in extents of 0-3.5, 0-14.0, 0-26.0 and 0-3.5 kmol/（hrnE.year）, respectively. These values were comparable to previously reported results and reflected the influences of vegetation and soil characteristics on the soil acid buffering capacity. Simulations of SO2 emission and sulfur deposition in this study showed that sulfur deposition core areas mirrored SO2 emission centers. The prediction of sulfur deposition after 20% and 40% reduction of SO2 emission suggested that the reduction of area sources contributed greatly to the decrease of sulfur deposition. Thus, abatement of area source emissions could be the primary way to mitigate sulfur deposition in Guangdong to meet both the provincial and national regulations of air pollution control.

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.

Modeling on Flash Flood Disaster Induced by Bed Load

Flash floods result from a complex interaction among hydro-meteorological, hydrological, and hydraulic processes across various spatial and temporal scales. Sichuan Province suffers flash floods frequently owing to mountain weather and topography. A flash flood and gravel bed load transport are two key relative problems in mountain river engineering. Bed materials are often encountered in alternate scouring and deposition in mountain fluvial processes during a flash flood. In this circumstance, CRS-1 bed load numerical model jointly with scale physical model is employed to predict water level and gravel bed scour and deposition for design of flood control dykes and flash flood disaster mitigation. A case study on the mechanism of a flash flood disaster induced by bed load transport for a hydropower station in Sichuan Province is conducted. Finally, suggestions to protect the hydropower station are proposed.

Mesoscopic Modeling Approach and Application for Steel Fiber Reinforced Concrete under Dynamic Loading:A Review

Steel fiber reinforced concrete(SFRC)has drawn extensive attention in recent years for its superior mechanical response to dynamic and impact loadings.Based on the existing test results,the highstrength steel fibers embedded in a concrete matrix usually play a strong bridging effect to enhance the bonding force between fiber and the matrix,and directly contribute to the improvement of the post-cracking behavior and residual strength of SFRC.To gain a better understanding of the action behavior of steel fibers in matrix and further capture the failure mechanism of SFRC under dynamic loads,the mesoscopic modeling approach that assumes SFRC to be composed of different mesoscale phases(i.e.,steel fibers,coarse aggregates,mortar matrix,and interfacial transition zone(ITZ))has been widely employed to simulate the dynamic responses of SFRC material and structural members.This paper presents a comprehensive review of the state-of-the-art mesoscopic models and simulations for SFRC under dynamic loading.Generation approaches for the SFRC mesoscale model in the simulation works,including steel fiber,coarse aggregate,and the ITZ between them,are reviewed and compared systematically.The material models for different phases and the interaction relationship between fiber and concrete matrix are summarized comprehensively.Additionally,some example applications for SFRC under dynamic loads(i.e.,compression,tension,and contact blast)simulated using the general mesoscale models are given.Finally,some critical analysis on the current shortcomings of the mesoscale modeling of SFRC is highlighted,which is of great significance for the future investigation and development of SFRC.

Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A Numerical Modeling Study

Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast loading.Initially centered on high-profile facilities such as embassies and petrochemical plants,this concern now extends to a wider array of infrastructures and facilities.Engineers and scholars increasingly prioritize structural safety against explosions,particularly to prevent disproportionate collapse and damage to nearby structures.Urbanization has further amplified the reliance on oil and gas pipelines,making them vital for urban life and prime targets for terrorist activities.Consequently,there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert disasters.In this study,an empty pipe model was successfully validated under contact blast conditions using Abaqus software,a powerful tool in mechanical engineering for simulating blast effects on buried pipelines.Employing a Eulerian-Lagrangian computational fluid dynamics approach,the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 mm.Material descriptions in the numerical model relied on Abaqus’default mechanical models.Comparative analysis revealed varying pipe performance,with deformation decreasing as explosion-to-pipe distance increased.The explosion’s location relative to the pipe surface notably influenced deformation levels,a key finding highlighted in the study.Moreover,quantitative findings indicated varying ratios of plastic dissipation energy(PDE)for different blast scenarios compared to the contact blast(P0).Specifically,P1(25 mm subsurface blast)and P2(50 mm subsurface blast)showed approximately 24.07%and 14.77%of P0’s PDE,respectively,while P3(25 mm above-surface blast)and P4(50 mm above-surface blast)exhibited lower PDE values,accounting for about 18.08%and 9.67%of P0’s PDE,respectively.Utilising energy-absorbing materials such as thin coatings of ultra-high-strength concrete,metallic foams,carbon fiber-reinforced polymer wraps,and others on the pipeline to effectively mitigate blast damage is recommended.This research contributes to the advancement of mechanical engineering by providing insights and solutions crucial for enhancing the resilience and safety of underground pipelines in the face of blast events.

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 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.

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.

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.

Evaluation of Nitrogen Loads from Anthropogenic and Natural Sources by an integrated Biogeochemical Modeling Frame

This study proposed an integrated biogeochemical modeling of nitrogen load from anthropogenic and natural sources in Japan.Firstly,the nitrogen load(NL) from different sources such as crop,livestock,industrial plant,urban and rural resident was calculated by using datasets of fertilizer utilization,population distribution, land use map,and social census.Then,the nitrate leaching from soil layers in farmland,grassland and natural conditions was calculated by using a

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.

In-Depth Study on Synthesis Load Modeling

Detailed procedures for the modeling of synthesis load models (SLM) of actual power network are presented, then the classification indices based on 1oad characteristics and the principle of load classification are expounded. Based on the results of general investigation of 220 kV and 330kV substations in China’s power grid, the load characteristics are classified, and detailed load characteristic investigation of selected different kinds of typical substations are carried out. By use of statistical synthesis, the SLM for typical substations, in which the distribution networks are taken into account, are built;and the modeling results are disseminated and applied to whole Chinese power grid. Besides, the load model parameters are evaluated and verified via post-disturbance simulation method. The effectiveness of the built SLM is validated by the fitting of some disturbance incidents.

How does Mechanical Loading Make Bone Microstructure: Modeling vs. Remodeling

Bone modeling and remodeling are governed by distinct biochemical processes that may hold unique opportunities for optimizing bone mass[1,2].Remodeling refers to the coupled resorption and subsequent formation on the bone surface,while modeling represents uncoupled formation or resorption.Mechanical loading is known to improve bone mass,though whether this occurs through modeling or remodeling(or by some combination)is unclear.Dynamic in vivo morphometry utilizing high resolution micro-CT and image registration has only recently become feasible and thus holds an untapped and expanding potential for understanding bone metabolism by quantifying and localizing formation/resorption and modeling/remodeling events.16-week-old mice were given 2 baseline weekly micro-CT scans of both tibiae prior to the initiation of daily unilateral loading(contralateral limb for nonloaded control).Weekly scanning and daily loading continued for 5 weeks.Registered images for each mouse in a global coordinate system revealed the time course of each voxel,and changes in bone mass were quantified as modeling or remodeling starting at the onset of loading.In cortical bone,after an initial response to loading in both regimes,modeling emerged as the dominant response.Loading effects were largest in areas of mechanical significance.For example,anabolic modeling on the periosteal surface of the half of the tibia in compression under axial load presented a strong effect of loading,whereas the same measure on the endosteal surface in the area in tension showed no difference.Similarly,in trabecular bone anabolic modeling was significantly increased with loading on trabecular plates but not rods(plates have been shown to be the major contributor to overall bone strength).The catabolic modeling response on the endosteal surface showed an interesting transition over time.Loading initially led to a significant suppression of catabolic modeling,but over time increased it to levels significantly beyond that of nonloaded controls.

Wavelet time series MPARIMA modeling for power system short term load forecasting

The wavelet power system short term load forecasting(STLF) uses a mulriple periodical autoregressive integrated moving average(MPARIMA) model to model the mulriple near periodicity, nonstationarity and nonlinearity existed in power system short term quarter hour load time series, and can therefore accurately forecast the quarter hour loads of weekdays and weekends, and provide more accurate results than the conventional techniques, such as artificial neural networks and autoregressive moving average(ARMA) models test results. Obtained with a power system networks in a city in Northeastern part of China confirm the validity of the approach proposed.

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.