Loading Problem Research Articles

A Loadability Study of 30 kV Misurata Distribution Network

Due to the expansion of power distribution networks, the power delivered to the loads might get through corridors which limits their capability of transmitting the power. This concept is termed as the loadability. An unplanned increase in power consumption in the Libyan network, especially after 2011, led to major problems at different levels of the power network. For instance, these issues are addressed at the generation level as power shortages and load shedding while at the distribution level presented as under voltages and loadability issues. In this paper, a study of the loadability of 30 kV Misurata electrical distribution network (MDN) is carried out using the NEPLAN software. Even though the MDN is considered one of the largest distribution networks in Libya, a lack of data is found which makes an ambiguous vision about this network and the necessary developments required in the future as well as adds some difficulties to making studies. The work presents the steady state operation of MDN under the existence of the current and estimated loads up to the year 2026. The results show significant loading problems in Misurata distribution network which should be considered to avoid the anticipated future power transfer limitations. Some visible solutions are proposed toensure the optimal operation of the distribution network.

Minimization of the Buckling Load of a Clamped Plate with Perimeter Constraint

We look for minimizers of the buckling load problem with perimeter constraint in any dimension. In dimension 2, we show that the minimizing plates are convex; in higher dimension, by passing through a weaker formulation of the problem, we show that any optimal set is open and connected. For the higher eigenvalues, we prove that minimizers exist among convex sets with prescribed perimeter.

How to load your auto carrier. A hybrid packing approach for the auto-carrier loading problem

The distribution of new vehicles is a critical cost factor for automotive original equipment manufacturers (OEMs). While trains are the ideal mode for overland transport, OEMs often opt for road transport via auto carriers due to flexibility reasons or unavailability of rail networks. Auto carriers are specialized trucks equipped with flexible loading platforms. Finding the optimal configuration of platforms can be a difficult task due to passenger vehicles varying in size, shape, and weight. This problem is known as the auto-carrier loading problem (ACLP). The current literature deals with the ACLP on a strategic level with the goal to maximize transport capacities. However, it neglects the resulting increase in operational complexity.In this paper, we present a hybrid packing approach to solve the ACLP on an operational level. Our approach considers the shapes of the vehicles as polygons and incorporates an approximation of continuous rotation by combining a geometric algorithm with a mixed integer model formulation. We aim not only to maximize loading capacities but also to provide instructions for truck drivers on how to arrange the vehicles on the truck. We conduct a proof of concept (POC) with actual auto carriers to verify the feasibility of our approach and to quantify potential benefits for our industry partner. The POC confirms that our approach reliably generates feasible and comprehensive loading instructions. Not only could the implementation of our approach reduce lead times and transportation damages, but in addition, could completely automate the manual load creation process in distribution centers.

Research on Image Detection Algorithm of Rail Traffic Congestion Degree Based on Convolutional Neural Networks

With the sustainable development of the social economy and the continuous maturity of science and technology, urban rail transit has developed rapidly. It solved the problems of urban road load and people’s travel and brought about the problem of rail transit passenger congestion. The image detection algorithm for rail transit congestion is established based on the convolutional neural networks (CNN) structure to realize intelligent video image monitoring. The CNN structure is optimized through the backpropagation (BP) algorithm so that the model can detect and analyze the riding environment through the monitoring camera and extract the relevant motion characteristics of passengers from the image. Furthermore, the crowding situation of the riding environment is analyzed to warn the rail transit operators. In practical application, the detection accuracy of the algorithm reached 91.73%, and the image processing speed met the second-level processing. In the performance test, the proposed algorithm had the lowest mean absolute error (MAE) and mean square error (MSE). In Part B, the MAE and MSE values of the model were 16.3 and 24.9, respectively. The error values were small, so the performance was excellent. The purpose of this study is to reduce the possibility of abnormal crowd accidents at stations and provide new ideas for intelligent management of rail transit.

The status and challenging perspectives of 3D-printed micro-batteries.

In the era of the Internet of Things and wearable electronics, 3D-printed micro-batteries with miniaturization, aesthetic diversity and high aspect ratio, have emerged as a recent innovation that solves the problems of limited design diversity, poor flexibility and low mass loading of materials associated with traditional power sources restricted by the slurry-casting method. Thus, a comprehensive understanding of the rational design of 3D-printed materials, inks, methods, configurations and systems is critical to optimize the electrochemical performance of customizable 3D-printed micro-batteries. In this review, we offer a key overview and systematic discussion on 3D-printed micro-batteries, emphasizing the close relationship between printable materials and printing technology, as well as the reasonable design of inks. Initially, we compare the distinct characteristics of various printing technologies, and subsequently emphatically expound the printable components of micro-batteries and general approaches to prepare printable inks. After that, we focus on the outstanding role played by 3D printing design in the device architecture, battery configuration, performance improvement, and system integration. Finally, the future challenges and perspectives concerning high-performance 3D-printed micro-batteries are adequately highlighted and discussed. This comprehensive discussion aims at providing a blueprint for the design and construction of next-generation 3D-printed micro-batteries.

Combined system of automatic flow stabilization bread mass at the entry of the thresher of the grain harvester

The research conducted in this article is devoted to solving the actual problem of loading the grain harvester with bread mass at the entrance of the thresher. It is possible to achieve the minimum level of fluctuations in the flow of bread mass at the entrance of the threshing-separating device only in appropriately designed optimal multidimensional stabilization systems. At the same time, the methods of dynamic design and analytical design should be used for the construction of similar systems. We proposed to extend the experimental and analytical approach to the design of optimal stabilization systems to the case when minimal fluctuations in the flow of bread mass occur at the entrance to the thresher of the grain harvester. As a result, we developed and implemented an optimal combined system of automatic stabilization with feedback on the deviation from the average value of the flow of bread mass and correction according to the change in output. To carry out the above studies, the method of analyzing the quality of stabilization under random steady-state effects was used, and this made it possible to calculate normalized indicators of the quality of stabilization.

Research on wind turbine variable pitch control based on wind speed estimation

With the continuous promotion of the “double carbon” strategy, the capacity of wind turbines is increasing, and the dimensions of key parts such as the diameter of the wind turbine wheel, the height of the tower, and the radius of the tower tube are also increasing. Large wind turbines have a large inertia, so the execution time of the pitch actuator and the response time of the pitch action are usually longer, which leads to large fluctuations in the output power of the wind turbine when the wind speed changes rapidly under the working conditions above the rated wind speed and leads to complex loading problems. Therefore, in this paper, the design of pitch control is carried out by estimating the effective wind speed at the wind turbine surface and using the inverse system method to transform the nonlinear wind turbine system into a linear decoupled form. This method improves the pitch response speed, reduces the output power fluctuation, and better suppresses the load of the turbine to ensure the safe and stable operation of the turbine

Coupled poroelastic and gravitational deformation of a layered spherical Earth – I: load Love numbers

SUMMARY In this paper, we propose a fully coupled two-phase poroelastic deformation theory for a spherically layered and self-gravitating Earth. The earth model consists of a solid inner core, a fluid outer core and poroelastic mantle and crust. The boundary-value problems are posed in the Laplace-transformed domain using the spherical system of vector functions, and analytical solutions are obtained in each layer using the dual-variable and position matrix method. As an application, the surface loading problem is considered. The undrained and drained limits are discussed with the corresponding governing equations, which are different from the conventional ones where body force is ignored. Numerical examples show that the poroelastic effect can be significant since the difference between the results for undrained and drained limits are large with obvious time-dependent deformation. This newly derived theory for the coupled boundary-value problem will have broad applications, such as displacement and gravity change due to groundwater depletion, poroelastic rebound after an earthquake and risk evaluation of earthquakes induced by water injection.

Heat transfer performance of RP-3 aviation kerosene at supercritical pressure within a rotating U-shaped channel

The combined cycle engine based on turbine is typical in the field of cycle engines. However, the problem of high temperature heat load of turbine blades is serious. In order to solve this kind of problem, the method of using hydrocarbon fuel as cooling medium to improve the cooling efficiency of turbine blades are proposed. In this paper, the flow and heat transfer characteristics of RP-3 aviation kerosene in a rotating U-shaped channel under supercritical pressure were studied by numerical simulation. The flow and heat transfer characteristics of RP-3 aviation kerosene under supercritical pressure at different rotational speeds were numerically simulated by SST k-ω model. The results show that the centrifugal section and the horizontal section show obvious fluid stratification, and the mainstream distribution in the centripetal section is relatively uniform due to the bending effect and rotational buoyancy. Compared with the heat transfer capacity in the static state of the centrifugal section, the heat transfer of the fluid in the rotating state deteriorates, recovers and strengthens with the increase in the rotational speed. Moreover, compared with the centripetal section, the rotational speed has a particularly significant effect on the heat transfer performance in the centrifugal section and the horizontal section. When the rotational speed exceeds 300 rpm, the deterioration trend of heat transfer is weakened and the overall heat transfer performance is greatly improved.

A multistart biased‐randomized algorithm for solving a three‐dimensional case picking problem with real‐life constraints

AbstractThis paper introduces the three‐dimensional case picking problem (3D‐CPP) and proposes a multistart biased‐randomized algorithm (BRA) to solve it. The 3D‐CPP combines two important topics in modern warehouse logistics: the pallet loading problem and the routing of pickers in manual warehouses. The proposed optimization procedure aims at minimizing the overall distance traveled by the pickers, and is achieved by combining a routing problem (i.e., the order in which picking positions are visited) with a loading problem (i.e., the way in which cases are placed onto the pallet). We also consider additional constraints regarding the weight, vertical support, and strength of the cases. In order to solve this problem, we first propose a constructive heuristic which combines routing and packing procedures. This initial heuristic is then extended into a multistart BRA by employing a skewed probability distribution to introduce a certain degree of randomness during the solution‐construction process. A series of computational experiments allow us to assess the quality of the proposed approach, through a comparison with other algorithms as well as using real‐life data provided by an industrial partner.

The Correlation Of Excessive Assignment Between Student’s Mental Health

This research investigated the correlation of excessive assignments on the mental health of fifth-year English language students at State Islamic Religious Institution in Central Kalimantan. The research hypothesized a strong positive correlation between perceived assignment load and mental health problems. The method of this research used quantitative approach using a questionnaire. The Data was collected from 20 participants. The researchers, analyzed the data using pearson's correlation coefficient JASP to examine the relationship between excessive assignment and mental health condition. Based on the findings, the result showed a significant positive correlation (r = 0.900, p <.001) between excessive assignment and mental health condition, indicating that 81.0% of the variance in students' mental health could be attributed to their perceived workload. Educational institutions should take proactive steps to manage student workloads and provide mental health support services, such as counseling, time management training, and flexible deadlines. Promoting a balanced approach to academic assessment that prioritizes both academic excellence and student well-being is crucial for fostering the success and well-being of English language students. This research limited due to the small sample size and focus on a specific student population. Future research with larger and more diverse samples is needed to further explore the complex relationship between academic demands and student mental health. The findings highlight the urgent need for universities and educators to prioritize student mental health alongside academic achievement. Implementing practical strategies to manage workloads and provide mental health support can promote a more holistic and student-centered educational environment.

Mixed reality-based online 3D pallet loading problem to achieve augmented intelligence in e-fulfilment processes

Mixed reality-based online 3D pallet loading problem to achieve augmented intelligence in e-fulfilment processes

An exploration of the super-critical speed dynamic behaviours of the pantograph-catenary system

The train operating speed is traditionally limited to lower than 0.7 times the critical speed of the catenary. The material’s strength limits the tensile forces of the tension wires, preventing the further improvement of the train speed. A novel super-critical speed operating strategy of the pantograph catenary system (PCS) is proposed, using the relatively low tensile values of the catenary to make the pantograph run at a speed ratio larger than 1. The analytical results of a string under a moving load show the theoretical possibility of the super-critical speed operating strategy in moving load problems. The finite element method (FEM) is adopted for the model of the catenary. The differences between the simple catenary and the stitched catenary running at the super-critical speed regime are compared. Then, the tensile forces designation of the stitched catenary with different speed ratio values beyond 400 km/h is studied. Finally, the dynamic behaviours of the PCS reaching the super-critical speed regime are discussed, consisting of the continuous acceleration process and the transition process from the high-tension section to the low-tension section. The proposed super-critical speed operating strategy may be promising for the next-generation high-speed PCS.

Pallets delivery: Two matheuristics for combined loading and routing

The implementation of novel regulatory and technical requirements for the distribution of vehicle axle weights in road freight transport introduces a new set of constraints on vehicle routing. Until now, axle weight distribution in determining the load plan for freight transport units has been overlooked in the vehicle routing process. Compliance with these axle weight constraints has become paramount for road freight transport companies, since noncompliance with the axle weight distribution legislation translates into heavy fines. This work aims to provide a tool capable of generating cargo loading plans and routing sequences for a palletised cargo distribution problem. The problem addressed integrates the capacitated vehicle routing problem with time window and the two-dimensional loading problem with load balance constraints. Two integrative solution approaches are proposed, one giving greater importance to the routing and the other prioritising the loading. In addition, a novel MILP model is proposed for the 2D pallet loading problem with load-balance constraints that take advantage of the standard dimension of the pallets. Extensive computational experiments were performed with a set of well-known literature benchmark instances, extended to incorporate additional features. The computational results show the effectiveness of the proposed approaches.

Start Up And Operation Of A UASB Rector With Molasses As A Preferred Substrate – A Case Study

Anaerobic digestion followed by aerobic treatment has gained wide acceptability for many of the wastewater treatment. Several novel bio-reactors have been developed. All these reactors pose a problem of shock loading, when the high COD organic industrial waste is fed in to the reactor. Further, the normal substrates like glucose, sewage, citric acid may result in addition of a large volume of the substrate solution for a given organic loading. Both these problems are solved by adopting molasses, a typical by-product from the sugar industry. Among the bio-reactors to treat high strength waste waters, the Up-flow Anaerobic Sludge Blanket Reactor (UASBR), has received wide popularity for the treatment of domestic waste waters as well as for a variety of industrial wastewaters. This paper is to present a cogent and a clear picture of the startup and steady state operation of an UASB Reactor with molasses as the initial startup substrate for the development of well settleable sludge granules, the major feature of an UASB Reactor. The UASB reactor was fabricated in transparent Plexiglas. The reactor had a working volume of 9.75 liters with provision of ports for input, output, collection of samples, and collection of gas. Inside the settler, a gas-liquid-solid separation system using a glass funnel and a gas pressurizing plexiglass tube was provided. The aim was to granulate the sludge and acclimatizing it completely to take high organic loading. The feed was supplemented with a fixed COD: N: P ratio by adding urea for nitrogen and KH2PO4 for phosphorous. The HRT was fixed to be 8 hours. The reactor temperature was maintained at 35 ± 20oC. In about 55 days, the buttery seed sludge got granulated at an OLR of 8 g COD/l.day. The SEM of the granules exhibited a mixed morphology on the surface of the granules while filamentous Methanothrix proliferation could be clearly seen in the interior of the granule. Methanoceata and Methanothrix are the two dominant species found in the granules.

A chameleon and remora search optimization algorithm for handling task scheduling uncertainty problem in cloud computing

Task scheduling in cloud computing is responsible for serving the user requirements. The scheduling strategy must handle the problems of high load over virtual machines (VMs), high-cost consumption and lengthier scheduling time effectively. The greatest challenge in the cloud computing environment is achieving the intended outcome of task scheduling under the uncertain user request demands as it is responsible for assigning specific resources to requests for achieving effective task completion. However, most of the task scheduling approaches contributed to the literature mainly focused on the design and development of scheduling algorithms but ignored to explore the impact of uncertain factors such as millions of instructions per second (MIPS) and network bandwidth during the scheduling process. In this paper, A Chameleon and Remora Search Optimization Algorithm (CRSOA) is proposed for achieving efficient scheduling process by exploring the impact of MIPS and network bandwidth which directly affects the virtual machine (VM) performance. Further the work includes the uncertainty factors of task completion rate, load balance, scheduling cost and makespan in a simultaneous manner during the process of scheduling. It is formulated a multi-objective cloud task scheduling optimization model by integrating the merits of Chameleon Search Algorithm (CSA) and Remora Search Optimization Algorithm (RSOA) using a greedy methodology for simulating the real cloud computing task scheduling process. The simulation results evidently confirmed that the proposed CRSOA approach is minimizing the completion time and effective in handling the load balancing between the available VMs against other competitive metaheuristic task scheduling algorithms. The experimental investigation of this CRSOA confirmed its predominance in minimizing the makespan by 18.96%, cost by 22.18%, and degree of imbalance by 20.54%, compared to the baseline approaches with different number of tasks and VMs.

Computing minimal solutions to the ring loading problem

Given a cycle graph of n nodes and a non-negative demand di,j for each pair of nodes i,j, the ring loading problem with demand splitting (RLPW) asks to determine a routing of these demands such that the maximum load on any edge is minimal. In this work, we present an algorithm for computing minimal solutions to RLPW in O(n2) time. This algorithm, when employed as a subroutine, also improves the runtimes for several other ring loading algorithms by a factor of up to O(n2).

The Moving Element Method for the Dynamic Responses of Floating Double-Plate Structures on the Shallow Water

In this paper, the dynamic behavior of floating double-plate structures under a moving load is investigated in great detail with different factors utilizing the moving element method (MEM). The structures in this study are very large floating structures (VLFSs). The Kirchhoff–Love theory is used to model two floating plates connected by a Winkler-type elastic core, whilst the water surrounding the structure is simulated by the shallow linear water wave theory. In order to improve the computational efficiency of moving load problems, the MEM is adopted. Since the MEM uses fewer discrete elements than those of the traditional finite element method (FEM), the computational cost is reduced. The proposed two-plate model helps to reduce the influence of the surrounding water on the upper plate. Several numerical results are presented to investigate the influence of the ratio of thickness between layers as well as core stiffness on the displacements with different water depths, and load speeds.

Tactical unit algorithm: A novel metaheuristic algorithm for optimal loading distribution of chillers in energy optimization

Metaheuristic algorithms have gained increasing popularity in practical problems of engineering optimization. Aim to address the optimal chiller loading (OCL) problem in parallel chiller systems and other energy system optimization problems more efficiently, with the aim of reducing energy consumption and carbon emissions, this paper proposes a novel metaheuristic algorithm named the Tactical Unit Algorithm (TUA). The search process of this algorithm can be divided into three stages: searchers action search phase, executors action execution phase, and assessors action evaluation phase. In this paper, we use MATLAB to conduct simulation tests of benchmark functions and OCL problems. To evaluate the performance of TUA, we conduct experiments using 24 benchmark functions and compare the results with those obtained from nine commonly used metaheuristic algorithms. The findings demonstrate that TUA exhibits more accurate search accuracy, faster convergence, and better stability. Furthermore, we apply TUA to optimal chillers loading in energy optimization, and the results of three classic case tests provide preliminary evidence of the feasibility of TUA in addressing the OCL problem.

Out-Plane Buckling of Arches with Variable Cross-Section

The variable cross-section arch is widely used in practical engineering because of its beautiful arc and excellent mechanical properties. However, there is still no systematic and comprehensive study on the out-plane buckling of variable cross-section arches. In view of this, this paper is focused on the elastic analytical research of out-plane buckling of arches with variable cross-sections under a uniformly distributed radial local load. The pre-buckling and out-plane buckling behavior of a variable cross-sectional arch under an external load is quite different from that of an arch with a uniform cross-section. Castigliano’s second theorem is used to establish pre-buckling force method equilibrium equations for variable cross-sectional arches under a uniformly distributed radial local load, and corresponding analytical solutions of normal stress, axial compression, and the bending moments are obtained. Based on the energy method and the Ritz method, analytical solutions of the critical load for the elastic out-plane buckling of arches with variable cross-sections are derived. Comparisons with ANSYS results indicated that the analytical solutions are able to accurately predict the pre-buckling internal forces and critical out-plane buckling load of variable cross-section arches subjected to a uniformly distributed radial local load. It is found that the internal forces and the out-plane buckling load of an arch are significantly affected by the variation of cross-sectional height. As the ratio of the arch’s cross-sectional height increases, the bending moment decreases, and the axial force and critical out-plane buckling load increase. Analytical solutions of pre-buckling internal force and critical out-plane buckling load problems for arches with variable cross-sections have a wider significance since they can provide an effective explicit analytic method for the optimal design of arch structures.