Dynamic thermo-mechanical responses of road-soft ground system under vehicle load and daily temperature variation

A complete road-soft ground model is established in this paper to study the dynamic responses caused by vehicle loads and/or daily temperature variation.A dynamic thermo-elastic model is applied to capturing the behavior of the rigid pavement,the base course,and the subgrade,while the soft ground is characterized using a dynamic thermo-poroelastic model.Solutions to the road-soft ground system are derived in the Laplace-Hankel transform domain.The time domain solutions are obtained using an integration approach.The temperature,thermal stress,pore water pressure,and displacement responses caused by the vehicle load and the daily temperature variation are presented.Results show that obvious temperature change mainly exists within 0.3 m of the road when subjected to the daily temperature variation,whereas the stress responses can still be found in deeper places because of the thermal swelling/shrinkage deformation within the upper road structures.Moreover,it is important to consider the coupling effects of the vehicle load and the daily temperature variation when calculating the dynamic responses inside the road-soft ground system.

An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.

A Nonlinear Explicit Model of A Non-Circular Subsea Tunnel-Liner System with An FGM Inverted Arch Under Mechanical Loading and Fire Fields

This paper proposes an explicit scheme to analyze the failure of a subsea polyhedral tunnel-liner system with an inverted arch under mechanical loading and fire fields.The thin-walled liner is made of Functionally Graded Materials(FGMs),which may improve the stability behavior of the tunnel-liner system.Hydrostatic pressure is inevitable in the liner since underground water may penetrate the cracks of the tunnel,and reach the outer surface of the liner.In addition,an elevated temperature loading is taken into account,considering that fire may occur in the tunnel-liner system.Under the combination of mechanical loading and thermal loading,the liner deforms into a single-lobe shape,which is depicted by a trigonometric function.The total potential energy is expressed quantitatively after the energy approach and thin-walled shell theory are used.The minimum potential energy is obtained when the critical buckling occurs.The critical buckling pressure is calculated,which considers the effect of the thermal field.The present analytical prediction is subsequently compared precisely with other closed-form solutions.Finally,the effects of several parameters,such as the geometric shapes,temperature variations,and volume fraction indices,are discussed to further survey the buckling performance of the nonlinear buckling of an FGM polyhedral liner with an inverted arch.One may address a polyhedral liner with fewer polyhedral sides,and a lower volume fraction index is recommended to rehabilitate cracked tunnels in engineering applications.

Resilience-Oriented Load Restoration Method and Repair Strategies for Regional Integrated Electricity-Natural Gas System

The rising frequency of extreme disaster events seriously threatens the safe and secure operation of the regional integrated electricity-natural gas system(RIENGS).With the growing level of coupling between electric and natural gas systems,it is critical to enhance the load restoration capability of both systems.This paper proposes a coordinated optimization strategy for resilience-enhanced RIENGS load restoration and repair scheduling and transforms it into a mixed integer second-order cone programming(MISOCP)model.The proposed model considers the distribution network reconfiguration and the coordinated repair strategy between the two systems,minimizing the total system load loss cost and repair time.In addition,a bi-directional gas flow model is used to describe the natural gas system,which can provide the RIENGS with more flexibility for load restoration during natural gas system failure.Finally,the effectiveness of the proposed approach is verified by conducting case studies on the test systems RIENGS E13-G7 and RIENGS E123-G20.

Field Load Test Based SHM System Safety Standard Determination for Rigid Frame Bridge

The deteriorated continuous rigid frame bridge is strengthened by external prestressing. Static loading tests wereconducted before and after the bridge rehabilitation to verify the effectiveness of the rehabilitation process. Thestiffness of the repaired bridge is improved, and the maximum deflection of the load test is reduced from 37.9 to27.6 mm. A bridge health monitoring system is installed after the bridge is reinforced. To achieve an easy assessmentof the bridge’s safety status by directly using transferred data, a real-time safety warning system is createdbased on a five-level safety standard. The threshold for each safety level will be determined by theoretical calculationsand the outcomes of static loading tests. The highest risk threshold will be set at the ultimate limit statevalue. The remaining levels, namely middle risk, low risk, and very low risk, will be determined usingreduction coefficients of 0.95, 0.9, and 0.8, respectively.

Systematic Review:Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.

Seasonal Short-Term Load Forecasting for Power Systems Based onModal Decomposition and Feature-FusionMulti-Algorithm Hybrid Neural NetworkModel

To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance,this paper proposes a seasonal short-termload combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model.Specifically,the characteristics of load components are analyzed for different seasons,and the corresponding models are established.First,the improved complete ensemble empirical modal decomposition with adaptive noise(ICEEMDAN)method is employed to decompose the system load for all four seasons,and the new sequence is obtained through reconstruction based on the refined composite multiscale fuzzy entropy of each decomposition component.Second,the correlation between different decomposition components and different features is measured through the max-relevance and min-redundancy method to filter out the subset of features with strong correlation and low redundancy.Finally,different components of the load in different seasons are predicted separately using a bidirectional long-short-term memory network model based on a Bayesian optimization algorithm,with a prediction resolution of 15 min,and the predicted values are accumulated to obtain the final results.According to the experimental findings,the proposed method can successfully balance prediction accuracy and prediction time while offering a higher level of prediction accuracy than the current prediction methods.The results demonstrate that the proposedmethod can effectively address the load power variation induced by seasonal differences in different regions.

The loaded matrix:neurotrophin-enriched hydrogels for stem cell brain repair in Parkinson's disease

More than 200 years after Parkinson's disease was first described by the English surgeon whose name would eventually be given to the condition,available treatments remain purely symptomatic,leaving a critical unmet clinical need for a diseasemodifying therapy.

High Fe‑Loading Single‑Atom Catalyst Boosts ROS Production by Density Effect for Efficient Antibacterial Therapy

The current single-atom catalysts(SACs)for medicine still suffer from the limited active site density.Here,we develop a synthetic method capable of increasing both the metal loading and mass-specific activity of SACs by exchanging zinc with iron.The constructed iron SACs(h^(3)-FNC)with a high metal loading of 6.27 wt%and an optimized adjacent Fe distance of~4 A exhibit excellent oxidase-like catalytic performance without significant activity decay after being stored for six months and promising antibacterial effects.Attractively,a“density effect”has been found at a high-enough metal doping amount,at which individual active sites become close enough to interact with each other and alter the electronic structure,resulting in significantly boosted intrinsic activity of single-atomic iron sites in h^(3)-FNCs by 2.3 times compared to low-and medium-loading SACs.Consequently,the overall catalytic activity of h^(3)-FNC is highly improved,with mass activity and metal mass-specific activity that are,respectively,66 and 315 times higher than those of commercial Pt/C.In addition,h^(3)-FNCs demonstrate efficiently enhanced capability in catalyzing oxygen reduction into superoxide anion(O_(2)·^(−))and glutathione(GSH)depletion.Both in vitro and in vivo assays demonstrate the superior antibacterial efficacy of h^(3)-FNCs in promoting wound healing.This work presents an intriguing activity-enhancement effect in catalysts and exhibits impressive therapeutic efficacy in combating bacterial infections.

LOAD FLOW CALCULATION FOR FLEXIBLE AC TRANSMISSION SYSTEMS

In this paper, a synthetic mathematical model of load flow for flexible AC transmission systems (FACTS) with unified power flow controller (UPFC) is presented based on the analysis of basic principle and operation state of UPFC. The model can use the fast P Q decoupled load flow method. Examples of test systems show that the proposed model and method have good convergence. An effective tool is provided by the load flow computer program to analyze the load flow and initial valve calculation of the dynamic state of FACTS.

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.

A Greedy Algorithm for Task Offloading in Mobile Edge Computing System

Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless chan- nels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First （SMSEF） algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.

Research on Propeller Dynamic Load Simulation System of Electric Propulsion Ship

A dynamic marine propeller simulation system was developed, which is utilized for meeting the experimental requirement of theory research and engineering design of marine electric propulsion system. By applying an actual ship parameter and its accurate propeller J＇ -KT＇ and J＇ - Kp＇ curve data, functional experiments based on the simulation system were carried out. The experiment results showed that the system can correctly emulate the propeller characteristics, produce the dynamic and steady performances of the propeller under different navigation modes, and present actual load torque for electric propulsion motor.

Dynamic response of a three-beam system with intermediate elastic connections under a moving load/mass-spring

The objective of this research is to study the dynamic response characteristics of a three-beam system with intermediate elastic connections under a moving load/mass-spring.In this study,the finite Sine-Fourier transform was performed for the dynamic partial differential equations of a simply supported three-beam system(SSTBS)under a moving load and a moving mass-spring,respectively.The dynamic partial differential equations were transformed into dynamic ordinary differential equations relative to the time coordinates,and the equations were solved and the displacement Fourier amplitude spectral expressions were obtained.Finally,based on finite Sine-Fourier inverse transform,the expressions for dynamic response of SSTBS under the moving load and moving mass-spring were obtained.The proposed method,along with ANSYS,was used to calculate the dynamic response of the SSTBS under a moving load/mass-spring at different speeds.The results obtained herein were consistent with the ANSYS numerical calculation results,verifying the accuracy of the proposed method.The influence of the load/mass-spring’s moving speed on the dynamic deflections of SSTBS were analyzed.SSTBS has several critical speeds under a moving load/mass-spring.The vertical acceleration incurred by a change in the vertical speed of SSTBS due to the movement of mass-spring and the centrifugal acceleration produced by the movement of massspring on the vertical curve generated by SSTBS vibration could not be neglected.

An automatic loading system for rock core testing with an industrial CT scanner

A new type of a loading and measuring system was developed for testing failure and deformation of rock core samples with an industrial CT （ICT） scanner.The loading and measuring system consisted of a loading system and a computer control system.The maximum servo-controlled force was 2 tonnes.The new system was a high-stiffness system with a small size.During ICT tests,rock core samples could be easily loaded in the axial direction.So the initiation,propagation,and coalescence of cracks in core samples were observed on ICT images.

Rural Power System Load Forecast Based on Principal Component Analysis

Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.

Application of subsurface wastewater infiltration system to on-site treatment of domestic sewage under high hydraulic loading rate

In order to enhance the hydraulic loading rate （HLR） of a subsurface wastewater infiltration system （SWIS） used in treating domestic sewage, the intermittent operation mode was employed in the SWIS. The results show that the intermittent operation mode contributes to the improvement of the HLR and the pollutant removal rate. When the wetting-drying ratio （RwD） was 1.0, the pollutant removal rate increased by （13.6 ± 0.3）% for NH3-N, （20.7 ± 1.1）% for TN, （18.6± 0.4）% for TP, （12.2 ± 0.5）% for BOD, （10.1 ± 0.3）% for COD, and （36.2 ± 1.2）% for SS, compared with pollutant removal rates under the continuous operation mode. The pollutant removal rate declined with the increase of the HLR. The effluent quality met The Reuse of Urban Recycling Water - Water Quality Standard for Scenic Environment Use （GB/T 18921-2002） even when the HLR was as high as 10 cm/d. Hydraulic conductivity, oxidation reduction potential （ORP）, the quantity of nitrifying bacteria, and the pollutant removal rate of NH3-N increased with the decrease of the RWD. For the pollutant removal rates of TP, BOD, and COD, there were no significant difference （p 〈 0.05） under different RwDS. The suggested RWD was 1.0. Relative contribution of the pretreatment and SWlS to the pollutant removal was examined, and more than 80% removal of NH3-N, TN, TP, COD, and BOD occurred in the SWIS.

Resilient Fixed-Order Distributed Dynamic Output Feedback Load Frequency Control Design for Interconnected Multi-Area Power Systems

The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.

TOPOLOGY OPTIMIZATION OF TRUSS STRUCTURES WITH SYSTEMATIC RELIABILITY CONSTRAINTS UNDER MULTIPLE LOADING CASES

In this paper, a mathematical model for topology optimization oftruss structures with constraints of displacement and systemreliability under multiple loading cases is constructed. In order toavoid the difficulty of computing the structure's system reliability,a solving approach is presented in which the failure probability ofsystem is divided into the sum of a all bars' failures probability bymeans of reliability distribution. In addition, by drawing into thereliability safety factor and the fundamen- tal relationship instructural mechanics, all probability constraints of displacement andstress are equiv- alently displayed as conventional form and linearfunction of the design variables.