A hardening load transfer function for rock bolts and its calibration using distributed fiber optic sensing

Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most of which are based on the global rock bolt response evaluated in pull-out tests.This paper presents a laboratory experimental setup aiming to capture the rock formation effect,while using distributed fiber optic sensing to quantify the effect of the confinement and the reinforcement pull-out behavior on a more local level.It is shown that the behavior along the sample itself varies,with certain points exhibiting stress drops with crack formation.Some edge effects related to the kinematic freedom of the grout to dilate are also observed.Regardless,it was found that the mid-level response is quite similar to the average response along the sample.The ability to characterize the variation of the response along the sample is one of the many advantages high-resolution fiber optic sensing allows in such investigations.The paper also offers a plasticity-based hardening load transfer function,representing a"slice"of the anchor.The paper describes in detail the development of the model and the calibration/determination of its parameters.The suggested model captures well the coupled behavior in which the pull-out process leads to an increase in the confining stress due to dilative behavior.

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.

Adaptive Load Balancing for Parameter Servers in Distributed Machine Learning over Heterogeneous Networks

In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.

Electric Vehicle Charging Capacity of Distribution Network Considering Conventional Load Composition

At present,the large-scale access to electric vehicles(EVs)is exerting considerable pressure on the distribution network.Hence,it is particularly important to analyze the capacity of the distribution network to accommodate EVs.To this end,we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load.First,the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed.Second,the charging behavior of an EVis simulated by combining the Monte Carlo method and the trip chain theory.After obtaining the temporal and spatial distribution of the EV charging load,themethod of distribution according to the proportion of the same type of conventional load among the nodes is adopted to integrate the EV charging load with the conventional load of the distribution network.By adjusting the EV ownership,the EV capacity in the distribution network is analyzed and solved on the basis of the following indices:node voltage,branch current,and transformer capacity.Finally,by considering the 10-kV distribution network in some areas of an actual city as an example,we show that the proposed analysis method can obtain a more reasonable number of EVs to be accommodated in the distribution network.

Green's functions for uniformly distributed loads acting on an inclined line in a poroelastic layered site

Based on one type of practical Biot＇s equation and the dynamic-stiffness matrices ofa poroelastic soil layer and half-space, Green＇s functions were derived for unitformly distributed loads acting on an inclined line in a poroelastie layered site. This analysis overcomes significant problems in wave scattering due to local soil conditions and dynamic soil-structure interaction. The Green＇s functions can be reduced to the case of an elastic layered site developed by Wolf in 1985. Parametric studies are then carried out through two example problems.

A Distributed Decision Mechanism for Controller Load Balancing Based on Switch Migration in SDN

Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism(DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.

Analytical solution for functionally graded anisotropic cantilever beam subjected to linearly distributed load

The bending problem of a functionally graded anisotropic cantilever beam subjected to a linearly distributed load is investigated. The analysis is based on the exact elasticity equations for the plane stress problem. The stress function is introduced and assumed in the form of a polynomial of the longitudinal coordinate. The expressions for stress components are then educed from the stress function by simple differentiation. The stress function is determined from the compatibility equation as well as the boundary conditions by a skilful deduction. The analytical solution is compared with FEM calculation, indicating a good agreement.

Load Distribution of Base Stations in User-Centric Heterogeneous UDN

In ultra-dense networks(UDN),multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations(BSs).The data rate and quality of service can be improved.However,BSs in user-centric paradigm are required to serve more users due to this multiple association scheme.The improvement of system performance may be limited by the improving load of BSs.In this letter,we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN.Based on open loop power control(OLPC),a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio(SINR)for any typical user.As for any BS in different tiers,by leveraging stochastic geometry,we derive the Probability Mass Function(PMF)of the number of the served users,the Cumulative Distribution Function(CDF)of total power consumption,and the CDF bounds of downlink sum data rate.The accuracy of the theoretical analysis is validated by numerical simulations,and the effect the system parameters on the load of BSs is also presented.

Research on Short-Term Load Forecasting of Distribution Stations Based on the Clustering Improvement Fuzzy Time Series Algorithm

An improved fuzzy time series algorithmbased on clustering is designed in this paper.The algorithm is successfully applied to short-term load forecasting in the distribution stations.Firstly,the K-means clustering method is used to cluster the data,and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division.On this basis,the data is fuzzed to form a fuzzy time series.Secondly,a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load,which is used to predict the short-term trend change of load in the distribution stations.Matlab/Simulink simulation results show that the load forecasting errors of the typical fuzzy time series on the time scale of one day and one week are[−50,20]and[−50,30],while the load forecasting errors of the improved fuzzy time series on the time scale of one day and one week are[−20,15]and[−20,25].It shows that the fuzzy time series algorithm improved by clustering improves the prediction accuracy and can effectively predict the short-term load trend of distribution stations.

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.

Effect of dynamic loading orientation on fracture properties of surrounding rocks in twin tunnels

For expedited transportation,vehicular tunnels are often designed as two adjacent tunnels,which frequently experience dynamic stress waves from various orientations during blasting excavation.To analyze the impact of dynamic loading orientation on the stability of the twin-tunnel,a split Hopkinson pressure bar(SHPB)apparatus was used to conduct a dynamic test on the twin-tunnel specimens.The two tunnels were rotated around the specimen’s center to consider the effect of dynamic loading orientation.LS-DYNA software was used for numerical simulation to reveal the failure properties and stress wave propagation law of the twin-tunnel specimens.The findings indicate that,for a twin-tunnel exposed to a dynamic load from different orientations,the crack initiation position appears most often at the tunnel corner,tunnel spandrel,and tunnel floor.As the impact direction is created by a certain angle(30°,45°,60°,120°,135°,and 150°),the fractures are produced in the middle of the line between the left tunnel corner and the right tunnel spandrel.As the impact loading angle(a)is 90°,the tunnel sustains minimal damage,and only tensile fractures form in the surrounding rocks.The orientation of the impact load could change the stress distribution in the twin-tunnel,and major fractures are more likely to form in areas where the tensile stress is concentrated.

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presents a distributed model predictive control DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints GRCs, load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints. © 2014 Chinese Association of Automation.

Natural Frequency of the Bridge—Vehicle Coupled System Considering Uniform Distributed Moving Load

Natural frequencies of the bridge—vehicle coupling system considering uniform distributed load varying with position is investigated in this work.An analytic model of a simply supported beam bridge with constant section is introduced to establish the frequency equations of the coupled system.Comparisons with the results between analytic model and FEM indicate that the present research is correct and reasonable.In view of an example bridge,natural frequencies are studied on the bridge subjected to uniform distributed moving loads in cases of different weight and span,by which some regular phenomenon are obtained.The present study can apply in the engineering problem of interaction between bridges and moving loads such as trains and tracked vehicles.

The Response of Viscously Damped Euler-Bernoulli Beam to Uniform Partially Distributed Moving Loads

The paper investigates the response of non-initially stressed Euler-Bernoulli beam to uniform partially distributed moving loads. The governing partial differential equations were analyzed for both moving force and moving mass problem in order to determine the behaviour of the system under consideration. The analytical method in terms of series solution and numerical method were used for the governing equation. The effect of various beam observed that the response amplitude due to the moving force is greater than that due to moving mass. It was also found that the response amplitude of the moving force problem with non-initial stress increase as mass of the mass of the load M increases.

A Load Balancing Policy for Distributed Web Service

The proliferation of web services;and users appeal for high scalability, availability and reliability of web servers to provide rapid response and high throughput for the Clients’ requests occurring at anytime. Distributed Web Servers (DWSs) provide an effective solution for improving the quality of web services. This paper addresses un-regulated jobs/tasks migration among the servers. Considering distributed web services with several servers running, a lot of bandwidth is wasted due to unnecessary job migration. Having considered bandwidth optimization, it is important to develop a policy that will address the bandwidth consumption while loads/tasks are being transferred among the servers. The goal of this work is to regulate this movement to minimize bandwidth consumption. From literatures, little or no attention was given to this problem, making it difficult to implement some of these policies/schemes in bandwidth scarce environment. Our policy “Cooperative Adaptive Symmetrical Initiated Dynamic/Diffusion (CASID)” was developed using Java Development Environment (JADE) a middle ware service oriented environment which is agent-based. The software was used to simulate events (jobs distribution) on the servers. With no job transfer allowed when all servers are busy, any over loaded server process jobs internally to completion. We achieved this by having two different agents;static cognitive agents and dynamic cognitive agents. The results were compared with the existing schemes. CASID policy outperforms PLB scheme in terms of response time and system throughput.

Load Profile Analysis for Mitigating Load-Shedding in Central Africa: Case of Kinshasa

Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.

Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply.Despite the complexity of their protection,as well as the operation of distributed generation resources in the distribution network,factors such as improving reliability,increasing production capacity of the distribution network,stabilizing the voltage of the distribution network,reducing peak clipping losses,as well as economic and environmental considerations,have expanded the influence of distributed generation(DG)resources in the distribution network.The location of DG sources and their capacity are the key factors in the effectiveness of distributed generation in the voltage stability of distribution systems.Nowadays,along with the scattered production sources of electric vehicles with the ability to connect to the network,due to having an energy storage system,they are known as valuable resources that can provide various services to the power system.These vehicles can empower the grid or be used as a storage supply source when parked and connected to the grid.This paper introduces and studies a two-stage planning framework for the concurrent management of many electric vehicles and distributed generation resources with private ownership.In the first stage,the aim is to increase the profit of electric vehicles and distributed generation sources;finally,the purpose is to reduce operating costs.The proposed scheduling framework is tested on a distribution network connected to bus 5 of the RBTS sample network.Besides distributed generation sources and electric vehicles,we integrate time-consistent load management into the system.Due to distributed generation sources such as photovoltaic systems and wind turbines and the studied design in the modeling,we use the Taguchi TOAT algorithm to generate and reduce the scenario to ensure the uncertainty in renewable energy.MATLAB software is used to solve the problem and select the optimal answer.

Analytical Load Balancing Model in Distributed Open Flow Controller System

The Software Defined Network (SDN) is a concept based on a decoupling between the control plan and the data plan of a network. Thus, the network becomes programmable and can be coupled to the business applications of the users. The study that is discussed in this article looks at load planning and balancing in distributed controllers. To do this, a model and theoretical methods of performance evaluation related to appropriate software tools, to predict and control the quality of service offered to users is exposed. This paper exposed also a distributed architecture of controllers and then a module based on an adaptive load balancing algorithm that is fault tolerant and fluctuates controller loads. The experiments show a significant gain in efficiency of our solution.

Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement

This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. The tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Dynamic-Distributed Load Balancing for Highly-Performance and Responsiveness Distributed-GIS (D-GIS)

In recent years, several results have been introduced to enhance distributed GIS performance. While much more efforts have focused on tile map and simple symbologies on dynamic map, load balancing GIS servers have not been addressed by the GIS community so far. This paper, therefore, proposed dynamic distributed load balancing for D-GIS in order to quickly render information to client interface by involving a set of GIS servers which process clients’ requests depending of an algorithm. In the model, several concepts were introduced and defined: Virtual Server within physical machine which constitutes a setup environment for a single GIS server, Load Hash Table which contains information about virtual server’s capacity, real-time load and other mandatory elements, Request Split Table which splits requests depending of the input area’s Quantity of Information and stores request tasks composition for later reconstitution. At last we have Distributed Failover Callback Function Table level one (respectively level two) which determines whether or not the request had been successfully processed by the chosen virtual server (respectively physical machine). This table allows sending back the same request to another virtual server (respectively physical node). Two load handlers (primary and secondary) are defined in case of failure. Our Model achieves efficient load balancing by: providing efficient node selection;optimizing request routing;managing node failover;involving client’s request partitioning and introducing method type decomposition. A simulation of the algorithm shows a low response time when performing GIS operations.