Load Distribution Research Articles

An optimal configuration strategy of multi-chiller system based on overlap analysis and improved GA

For design of the multi-chiller system, the configuration can be optimized that the system is high efficiency when it is operated under frequent load and operation condition in one year. Base on this idea, the paper presents a novel strategy of optimal configuration of multi-chiller system. The high hour-density range of annual load distribution and the high-efficiency region of combination of chillers are presented respectively, and their obtaining methods are developed. The overlap index is defined to evaluate the overlap between the high-efficiency region and high hour-density range, and it is maximized for the proposed optimal configuration strategy. GA is improved and employed for optimization. The proposed optimal configuration strategy is validated in a real multi-chiller system. The results show that the optimal configuration configured by the proposed strategy can improve annual Energy Efficiency Ratio (EER) about 5 % comparing with the original configuration of the real system. The configurations using equivalent strategy and typical non-equivalent strategy are compared, and the results show that both of hourly COP and annual EER of the configuration of the proposed strategy are better than them. 50 random configurations enumerated from chiller candidates are also compared. The results show that the overlap index is strongly correlated to annual EER, and it can be taken as optimization object for optimal configuration. Improved GA is compared with original GA, and the results show that of computation time cost can be reduced more than 60 % by use of Improved GA. The validation results show that the proposed strategy can obtain the optimal configuration of multi-chiller system directly from chiller candidates.

Extrapolation Framework and Characteristic Analysis of Load Spectrum for Agriculture General Power Machinery

As a crucial step in food production, tillage and land preparation play a pivotal role in achieving sustainable crop production and improving the soil environment. However, accurate assessment of the load that agricultural machinery implements during the operation process has always been a vexing problem that needs urgent solutions. In this paper, an extrapolation and reconstruction framework for the time-domain load is constructed based on the probability-weighted moments (PWM) estimation and the peaks-over-threshold function, and the load spectrum is obtained for agriculture general power machinery. Firstly, the load acquisition system was developed, the traction resistance and output torque of the tractor were measured, and the collected load signals were preprocessed. Next, the mean excess function and PWM estimation are introduced to select the optimal threshold and generalized Pareto distribution (GPD) fitting parameters and the extreme load distribution that exceeds the threshold range is fitted. The extreme points in the original data are replaced by generating new extreme points that follow the GPD distribution, and the extrapolation of the load spectrum is achieved. Finally, the real extrapolated load spectrum was validated based on statistical characteristics and rainflow counting analysis, and the correlation coefficient between the fitting data and the extreme load samples was greater than 0.99. It can retain the load sequence characteristics of the original load to a great extent, truly reflecting the load state during the operation of agricultural machinery. Meanwhile, the characteristics of the load spectrum can be accurately obtained, such as extreme, mean, and amplitude values, and the real load during deep loosening and rotary tillage are accurately described. The values provide more authentic and reliable data support for the subsequent selection of optimal operating parameters, reliability design of the power transmission system, and the life assessment of the agricultural implements.

Reliability of Girder Bridge System under Lateral Uneven Vehicular Overloads

Truck presence on bridges is random. Trucks may centrically or eccentrically appear on a bridge span in one or more lanes, which will cause extra load effects on girder components and eventually influence structural performance. Especially when trucks are heavily loaded, their eccentric passage is possible to induce damage in components, and, thus, the prescribed load- delivery path will be changed among components within the system. Therefore, component- and system-level structural performance of bridges subjected to aggressive vehicular overloads need to be thoroughly addressed. In this study, a WIM-based 5-axle overloaded truck model is chosen, and it is gradually applied to the finite element models of two girder bridges with different eccentric distance, considering two loading scenarios of single truck and multiple trucks. In detail, trucks are transversely loaded with an incremental eccentric distance, to investigate the impacts of eccentric loadings on structural performance, including failure sequences of components, load distribution factors among components, as well as system redundancy, as structures entering nonlinear stage. Finally, the reliability indices of the two bridges under uneven overloads are assessed at the component level and system level, respectively. The results of this study were beneficial to structural evaluation bridges subjected to overloads to ensure their serviceability and integrity.

Enhancing fiber/matrix interface adhesion in polymer composites: Mechanical characterization methods and progress in interface modification

The interface between the fiber and polymer matrix is a crucial region that plays a major role in the mechanical performance of fiber reinforced polymer composites (FRPCs) materials. The properties of this zone are recognized to have a significant influence on the fracture and failure of FRPCs. As a result, strong adhesion at the interface is required for effective stress transfer and load distribution within the composite material. In light of this, the aim of this work is to provide an up-to-date review of test methods for assessing fiber/matrix interface adhesion in FRPCs under static and dynamic loadings, along with advancements in interface modification techniques. At the outset, we give an overview of the different modification treatments used thus far, alongside interface testing methods, in order to optimize fiber/matrix compatibility, improve interfacial bonding and scrutinize their impact on interfacial adhesion properties. Particular attention is then focused on the description of the main mechanical characterization techniques used to assess the fiber/matrix interfacial properties. In the final outlook, we highlight the key findings and discuss potential directions for characterization of the fiber/matrix interface.

Deep learning-based post-disaster energy management and faster network reconfiguration method for improvement of restoration time

Natural disasters in the world often cause power outages. To improve post-disaster response and restoration time, a method for energy management and network reconfiguration in emergencies has been proposed, where energy storages systems (ESSs) in distribution networks are used to support the system balance immediately and then the network reconfiguration is accelerated based on deep learning techniques. First, when power failures occur, the outputs of ESSs are calculated optimally in terms of the proposed optimization model under the constraints of minimizing line losses. After the injections of ESSs in emergencies, the network reconfiguration is still needed due to the limitation of ESS capacities. To avoid calculations of power flow repeatedly, a deep-learning based reconfiguration method for distribution networks has been proposed, where the deep-learning model is trained offline and can output the parameters of power flow immediately when a state combination of distribution generators (DGs), loads and power lines, which is an effective way to accelerate the network reconfiguration. If many reconfiguration schemes are found, a decision-making method with preferences are used to select one according to different situations. Finally, cases are designed, and simulation results show that the calculation time of a reconfiguration schemes are reduced significantly by almost one hundred multiples.

Assessing the risks arising from a trailer connected behind a passenger car

Article pays attention to the impact of using the trailer on driving performances of a studied vehicle combination.The research was performed via extensive experimental measurements. A new methodology of determining a technical condition of the trailer’ brakes was proposed and verified, which can be also applied during the regular technical inspection. Various load distributions in the trailer caused the centre of gravity’s position of the vehicle was changed, which may increase the risk of skidding or disconnection of the trailer from the towing vehicle. Also, the vehicle’s ability to accelerate and decelerate decreased considerably due to the loading up. There were assessed the braking characteristics of the combination of vehicles as well, depending on the technical condition of the trailer’s brakes. The importance of this article lies in the quantification of selected factors on road safety in relation to driving with a combination of vehicles.

A low voltage load balancing distribution method considering street information and V2G technology application

The low-voltage distribution network (LVDN) is the final stage in delivering electric energy from power plants to consumers, and its operational condition greatly impacts many power users. While medium-voltage and high-voltage distribution networks can be managed through intelligent digital systems, load imbalance issues in LVDNs often rely on planners’ experience, leading to significant limitations. With advancements in electric vehicle (EV) charging technology and vehicle-to-grid (V2G) technology, where EVs act as distributed energy storage units, bidirectional energy exchange between vehicles and the grid can now contribute to LVDN operation. This paper proposes a low-voltage load distribution planning method that integrates street information and V2G technology. A two-stage stochastic programming mixed-integer model is developed to tackle load imbalance in LVDNs, with the planning scheme derived from solving this model. A case study is presented to verify the effectiveness of the method, demonstrating that incorporating V2G technology enhances load distribution accuracy and reduces reliance on manual planning, improving network stability and operational efficiency.

Comparative static analysis of functionally graded porous curved beams: Deterministic versus stochastic approaches

This study presents a comprehensive exploration of the comparative static analysis of functionally graded porous curved beams, examining deterministic versus stochastic approaches. The material randomness is incorporated using a stochastic finite element model. The formulation employed in this study utilizes three-noded elements and combines a higher-order shear deformation theory (HSDT) with the probabilistic first-order perturbation technique. The investigation focuses on an FGM curved beams incorporating various porosity models, including even, uneven, and sinusoidal distributions. The FGM porous curved beam is subjected to a uniform distributed load, and the study aims to determine the stochastic bending responses under these conditions. Additionally, various parameters influencing bending response, such as boundary conditions, geometric configurations, volume fraction indices, and porosity distributions, are examined. The uncertain bending responses are assessed in terms of material stochasticity using a stochastic finite element model, with validation through Monte Carlo simulation. Subsequent research endeavors within this field may investigate the impact of random fluctuations on both geometry and boundary conditions.

Simulation Framework for Substation Siting Integrating Load, Land Use, Neighborhood, and Cost Analysis

This study presents a comprehensive framework for substation siting to address power demand and urbanization challenges. It integrates economic, social, and environmental dimensions to ensure reliable power supply systems. Using simulation techniques, the paper evaluates substation placement by analyzing load distribution, land use, neighborhood satisfaction, and construction costs. The Analytical Hierarchy Process (AHP) assesses load distribution, while a hierarchical clustering algorithm maximizes land use efficiency. Neighborhood satisfaction is measured using hierarchical analysis and fuzzy logic. Construction costs are optimized via a genetic algorithm. These simulations formulate a multi-criteria decision-making tool, proposing an optimized siting strategy balancing technical, socio-economic, and environmental considerations. The framework enhances the accuracy of substation siting studies and provides practical implementation guidance, offering new insights and refined methodologies for modern power system planning and development.

DUAL LOOP VOLTAGE DROOP REGULATED CONTROLLER FOR DC MICROGRID USING HYBRID PSO AND GGO ALGORITHMS

Abstract DC microgrids are effectively employed in distribution network integration with renewable energy sources. The droop control technique is commonly utilized for DC microgrid regulation during load sharing. It minimizes the potential instability caused by disturbances such as input voltage changes, uncertainty parameters, and constant power load (CPL). Nevertheless, conventional droop control is inadequate in achieving precise current and satisfactory voltage regulation distribution for load sharing. The proposed approach comprises two separate loops for the DC bus voltage regulation and load current distribution, delivering a CVL and CPL to overcome the single optimization voltage controller technique. The primary loop uses the PSO algorithm to precisely manage the current load sharing among two parallel converters. Due to this the instability problems arising from disturbances, and it mitigated by the proposed topology. The multiobjective optimization technique provides notable resilience, rapid dynamic response, and robust stability over considerable variations in load. The secondary loop utilises the GGO algorithm to optimize the parameter to minimize the DC bus voltage regulation, voltage management, reasonable distribution of load power, and suitable reliability. The performance of the voltage regulation enhance & settling time for output voltage has been mitigated more than 31ms times through the proposed controller compared to conventional controller under the variation of CVL, CPL, and input voltage disturbance demonstrated in simulation results.

Research on the measurement mechanism of a six-axis force sensor based on a flexible hinge series–parallel hybrid

Abstract Addressing the common limitations of current six-axis force sensors, including the degradation of strain gauge accuracy due to environmental influences and the necessity for a complete replacement when damaged, this paper proposes an innovative six-axis force sensor that integrates a hybrid serial–parallel structure featuring flexible hinges. The sensor’s bracket is designed using a combination of serial–parallel flexible hinges, which confer load distribution capabilities, are lightweight, have high strength, and facilitate replacement. The static force model and the overall stiffness model of the sensor were developed based on the 3-universal–prismatic–universal parallel mechanism theory, providing a theoretical foundation for evaluating the sensor’s performance. To validate the accuracy of the stiffness model, finite element software is utilized for simulation-based verification. Subsequently, a calibration experiment is performed on the sensor, yielding results that conclusively show an error margin of less than 5% between experimental and theoretical values, satisfying the design criteria for sensor measurement.

Radiological and Anthropometrical Analysis of the Hip Joint Using Computed Tomography Scan in North Indian Population

Abstract Background: Anthropometric research on the hip joint has significant clinical implications, including (1) implant design and (2) avoiding implant mismatch complications, such as aseptic loosening and incorrect load distribution, which are mainly unknown in North India. The aim of this research is to ascertain the anatomical differences in the normal hip joint across individuals in North India and to statistically compare the results with global data. Materials and Methods: We used one hip topogram and one axial segment of the femoral head to analyze 100 people (35 females and 65 males) with normal hips between the ages of 20 and 65. In both sexes and on both sides, we determined the means of the following measurements: femoral head diameter (HD), femoral neck width (NW), femoral neck length, acetabular angle of sharp, femoral version, horizontal offset, acetabular version, and vertical offset. Results: The following are the mean parameters that were observed: (a) neck shaft angle (NSA) - 128.93°, (b) femoral HD = 4.29 cm, (c) femoral NW = 2.97 cm, (d) femoral neck length = 3.61 cm, (e) Acetabular angle of Sharp - 33.01°, (f) Acetabular version = 20.44°, (g) femoral Version = 21.57°, (h) horizontal offset = 3.62 cm, and (i) Vertical offset = 4.43 cm. Conclusion: The NSA and acetabular angle of sharp were 5°–6° more when compared to the western population while horizontal and vertical offset is comparatively less than Western population and in the Indian NSA was higher for North Eastern population than the North Indian population. The residual parameters were comparable to those found in Western literature.

Intricate DG and EV Planning Impact Assessment with Seasonal Variation in a Three-Phase Distribution System

Modern power systems present opportunities and challenges when integrating distributed generation and electric vehicle charging stations into unbalanced distribution networks. The performance and efficiency of both Distributed Generation (DG) and Electric Vehicle (EV) infrastructure are significantly affected by global temperature variation characteristics, which are taken into consideration in this study as it investigates the effects of these integrations. This scenario is further complicated by the unbalanced structure of distribution networks, which introduces inequalities that can enhance complexity and adverse effects. This paper analyzes the manner in which temperature changes influence the network operational voltage profile, power quality, energy losses, greenhouse harmful emissions, cost factor, and active and reactive power losses using analytical and heuristic techniques in the IEEE 69 bus network in both three-phase balance and modified unbalanced load conditions. In order to maximize adaptability and efficiency while minimizing the adverse impacts on the unbalanced distribution system, the findings demonstrate significant variables to take into account while locating the optimal location and size of DG and EV charging stations. To figure out the objective, three-phase distribution load flow is utilized by the particle swarm optimization technique. Greenhouse gas emissions dropped by 61.4%, 64.5%, and 60.98% in each of the three temperature case circumstances, while in the modified unbalanced condition, they dropped by 57.55%, 60.39%, and 62.79%. In balanced conditions, energy loss costs are reduced by 95.96%, 96.01%, and 96.05%, but in unbalanced conditions, they are reduced by 91.79%, 92.06%, and 92.46%. The outcomes provide valuable facts that electricity companies, decision-makers, along with other energy sector stakeholders may utilize to formulate strategies that adapt to the fluctuating patterns of electricity distribution during fluctuations in global temperature under balanced and unbalanced conditions of network.

Study on the effect of shape parameters and initiation points of rectangular high explosive on the spatial distribution of blast loads

Study on the effect of shape parameters and initiation points of rectangular high explosive on the spatial distribution of blast loads

Deriving Ritz formulation for the Static Flexural Solutions of Sinusoidal Shear Deformable Beams

This paper presents the Ritz variational method for the static bending analysis of sinusoidal shear deformable beams. The theory accounts for transverse shear deformation and satisfies transverse shear stress-free conditions at the top and bottom surfaces of the beam. The total potential energy functional for the thick beam bending problem is formulated and minimized using a Ritz procedure. The problem considered simply supported boundary conditions and two cases of loading – uniformly distributed load over the span and point load at the center. The function is a function of two unknown displacement functions constructed in terms of unknown generalized displacement parameters and shape functions that satisfy the boundary conditions. Ritz minimization of the functional is used to find the generalized displacement parameters and then the displacements w(x) and The displacements and stresses are found for the loading distributions considered. It is found that the results obtained agree remarkably well with the exact results obtained using the theory of elasticity. The differences between the present results and the exact solutions are less than 0.3% for maximum transverse displacement for both cases of loading considered. For uniform load over the beam, the result for l/t = 10 is 0.112% greater than the exact solution. For the point load at the center, the result for l/t = 10 is 4.468% greater than the exact solution. The increased difference in the point load case is due to the singular nature of the point load problem.

Optimal load distribution control for airport terminal chiller units based on deep reinforcement learning

The building sector consumes substantial energy, with HVAC systems accounting for nearly half of the total energy use. Optimizing chiller unit operations is crucial for reducing energy consumption. This research introduces a novel model-free control method for optimizing central chiller load distribution using deep reinforcement learning (DRL). The aim is to address the challenges posed by the high-dimensional complexity and parameter tuning in traditional meta-heuristic algorithms. The proposed method leverages deep neural networks combined with reinforcement learning to optimize chiller control based on real-world data. Case studies conducted in a large airport terminal demonstrate that this approach achieves a 7.71 % energy savings, closely matching the performance of model-based control methods with only a 0.26 % difference. The results indicate that the DRL method not only outperforms traditional expert control systems but also offers a feasible alternative for optimal control in complex, variable environments with limited data. This study contributes to the field by filling a research gap in applying DRL for optimal chiller load (OCL) control and demonstrates its potential for large-scale public building applications. The novelty of this research lies in its model-free approach, which provides a robust solution for energy optimization in dynamic and uncertain environments.

A novel real-time hybrid testing method for Twin-Rotor Floating Wind Turbines with Single-Point Mooring systems

The Floating Wind Turbines (FWT) are at the forefront of innovation, aiming to enhance power capacity and reduce costs. Among these innovations, the Twin-Rotor Single-Point Mooring Floating Wind Turbines (TR-SPM FWT) stands out. However, the unique structural design and dynamic characteristics of TR-SPM FWT pose challenges for traditional FWT model testing methods. To address this, a real-time hybrid testing (RTHT) method is proposed, employing the Multi-drive Aerodynamic Loading Simulator (MALS), specifically tailored for TR-SPM FWT model tests. MALS incorporates load distribution rules to accurately simulate aerodynamic loads, with its precision and response speed comprehensively evaluated. Furthermore, to enable multiple MALS units to replicate complicated aerodynamic behaviors concurrently, interference between channels and synchronization of units are examined. A load correction model is introduced and a RTHT system is devised, considering the floater yaw feedback of TR-SPM FWT. Ultimately, the proposed method is successfully applied to investigate the dynamic response of a TR-SPM FWT under diverse wind and wave conditions, demonstrating the reliability of the proposed test method and system.

Investigation on Tensile Properties of Polylactide-Nanoclay (PLA/ MMT) Surface Modification Nanocomposites

Polylactic acid (PLA) has gained significant attention as an environmentally friendly biopolymer, but its limited mechanical properties have hindered broader applications. Nanoparticles such as montmorillonite (MMT) offer a promising approach to address this limitation. The intercalation of MMT with polymer chains can significantly impact the mechanical properties of the nanocomposites. Hence, this paper investigated the effect of surface-modified montmorillonite (MMT) nanoparticles on the mechanical properties of polylactic acid (PLA) nanocomposites. The acetylation process of MMT was carried out followed by neutralisation process with NaOH. PLA granules and acetylated-modified MMT were mixed, crushed into granular form, and moulded. The effect of varying concentrations of modified MMTs on the tensile strength, elongation at break, and maximum force of PLA/MMT nanocomposites was evaluated using the ASTM D638 standard. FTIR results showed shifts in peak intensities in regions 2750 cm-1- 2810 cm-1 led to changes in the aliphatic and aromatic regions, which confirmed the presence of acetylation. Controlled surface modification improved interfacial interactions and load distribution, enhancing overall mechanical performance. The incorporation of surface-modified MMT in PLA/MMT nanocomposite increased the maximum force, Young's modulus, elongation at breaks and tensile strength. PLA/1wt% MMT and the PLA/7wt% MMT compositions exhibited good mechanical properties. However, the PLA/5 wt% MMT blendis deemed more suitable for food applications, such as disposable cups, plates, and cutleries, due to its lower elongation point. In conclusion, the hydrophilic properties of MMT and the hydrophobic properties of PLA are compatible due to the synergistic effects during surface modification which enhance the overall performance of the nanocomposites.

Elasticity solutions for functionally graded beams with arbitrary distributed loads

This paper derives the exact general elasticity solution for functionally graded rectangular beams subjected to arbitrary normal and tangential loads and with arbitrary end constraints. The general solution consists of bending moments and their integrals and derivatives, along with load-independent function sequences of the longitudinal coordinate. The method for determining function sequences has been established based on the stress function method. General solution formulas for stresses, strains and displacements have been derived and used to solve explicit special solutions for six cases involving concentrated forces, uniformly loads, and quadratically distributed loads with different displacement constraints scenarios. The results obtained are compared with existing exact solutions and those of Euler–Bernoulli and Timoshenko beams, and the errors of the latter two are analysed.

Dynamic Modeling and Behavior of Cylindrical Roller Bearings Considering Roller Skew and the Influence of Eccentric Load

At high speeds, skew and skid may frequently occur for the rollers in cylindrical roller bearings, especially when under eccentric load, as the uneven load distribution along the generatrix of the roller further aggravates this phenomenon. In this paper, a dynamic model of a cylindrical roller bearing was established, taking into account roller skewing and interactions with the cage. Firstly, the interaction between the roller and the raceway was calculated by slicing the roller along its generatrix. Furthermore, the computation of the interaction between the roller and the cage is based on elastic theory, taking into account pocket clearance. Subsequently, the dynamic equations for both rollers and cage were derived. Based on this foundation, an investigation was conducted to reveal how rotational speed, radial loads, and moment loads affect roller slipping, skewing characteristics, and interactions with the cage under uneven load conditions. The findings indicate a direct proportionality between roller slipping and bearing speed while exhibiting an inverse relationship with load magnitude. Additionally, it was observed that both bearing speed and load have a direct influence on roller skewing angle. Moreover, normal interaction force between the roller and cage demonstrates a direct proportionality to bearing speed while inversely correlating with load magnitude.