Grid Layer Research Articles

Evaluation of carbon grid reinforcement in asphalt pavement

• Carbon grid reinforcement mixtures exhibited a higher performance on fatigue cracking resistance. • Both grid reinforced mixtures met the minimum shear bonding strength requirement of 225 kPa. • The grid efficiency factor of the G17 mixture outperforms the G20 mixture, which was 2.5 compared to 1.16. • The performance year of grid mixtures was 2–4 times higher than the control mixture. • G17 and G20 alternatives reduced 43% and 13% total cost compared to C00 alternative through 20-year service. This study aims to analyze the advantages of carbon grid reinforcement in asphalt pavement based on performance tests, pavement design, and life cycle cost analysis (LCCA). The improvement in mechanical property was examined by overlay tester (OT), four-point bending, Hamburg wheel tracking, and shear bond strength test. Grid efficiency factor (GEF) was computed to evaluate the enhancement of cracking resistance. Based on the OT results, the performance year was quantified by a mechanical-empirical model of reflective cracking rate. Then, the outcomes from the performance year analysis were used to determine the economic effect through 20-year service by life cycle cost analysis (LCCA). Overall, carbon grid reinforcement not only enhances the performance of asphalt mixture but also prolongs service life, thus beneficial in cost-effectiveness. For instance, the resistance to reflection cracking was improved; deformation and rutting velocity was reduced due to the presence of a grid layer; GEFs of grid reinforced mixtures ranged from 1.5 to 2.5. Finally, the asphalt mixture containing grid would increase performance year by 2–4 times than that of conventional asphalt mixture. Therefore, the total cost of the grid reinforced alternative was reduced by approximately 43% through a 20-year service.

Grid Adaptive Bucketing Algorithm Based on Differential Privacy

With the popularity of location-based services, the restricted relationship between the availability of big location data and user’s privacy security has become a challenging issue. The spatial division is an effective measure for statistical location data characteristics. This paper proposes a grid adaptive bucketing algorithm based on differential privacy (GAB) to solve the problem that the existing differential privacy location data division method does not fully consider the distribution characteristics of spatial data points and noise superimposition. The algorithm first divides the mobile app location spatial data set into two layers of grids. It then performs adaptive binning judgment according to the square sum error value in the divided area. It puts areas with similar distributions into the same bucket, reducing the uniform assumption error and the noise error caused by many blank areas. Finally, a noise allocation strategy based on Hopkins statistic is adopted to achieve a reasonable noise allocation. The experimental results on two real large-scale location data sets, Checkin and Beijing, show that, compared with other classical algorithms based on differential privacy space partitioning, the GAB algorithm performs better in common evaluation indicators such as relative error and absolute error, which means GAB can obtain better range query effects and privacy protection effects.

Irradiation-dependent topology optimization of metallization grid patterns and variation of contact layer thickness used for latitude-based yield gain of thin-film solar modules

We show that the concept of topology optimization for metallization grid patterns of thin-film solar devices can be applied to monolithically integrated solar cells. Different irradiation intensities favor different topological grid designs as well as a different thickness of the transparent conductive oxide (TCO) layer. For standard laboratory efficiency determination, an irradiation power of 1000,mathrm {W/m}^2 is generally applied. However, this power rarely occurs for real-world solar modules operating at mid-latitude locations. Therefore, contact layer thicknesses and also lateral grid patterns should be optimized for lower irradiation intensities. This results in material production savings for the grid and TCO layer of up to 50 % and simultaneously a significant gain in yield of over 1,% for regions with a low annual mean irradiation.Graphical

A Framework for Optimization of Double Layer Grids with Supporting Cables

Space structures are used when it is required to cover a large unpaved area such as sports stadiums, aircraft factories, bridges, etc. Weight minimization is important in optimizing space structures, having various advantages such as cost reduction, reduction of the deterioration, increasing the possibility of using larger spans, and easy transportation and installation process. The use of meta-heuristic algorithms, inspired by the physics laws of nature, allows us to optimize a variety of complex problems. In this paper, four structures with different spans with and without cables are examined. Optimization is performed using Enhanced Colliding Bodies Optimization (ECBO) and Vibrating Particles System (VPS) optimization algorithms. The optimization is aimed to minimize the weight and the mid-span deflection of the structures. The utilized methods are based on the optimization algorithms in MATLAB (MATrix LABoratory) programming and the SAP2000 (Structural Analysis Program 2000) finite element software. In this way, the results, obtained from the structural analysis in finite element software, are utilized by the optimization algorithms and the operation is repeated until the optimal weight is achieved. In all the investigated examples, the ECBO performed better than the VPS algorithm. The findings indicate that the addition of the cables, in addition of reducing the weight of the structures can reduce the mid-span deflection.

Nonuniform 3D finite-difference elastic wave simulation on staggered grids

We have developed develop an approach to simulate the 3D isotropic elastic wave propagation using nonuniform finite-difference discretization on staggered grids. Specifically, we consider simulation domains composed of layers of uniform grids with different grid spacings, separated by nonconforming interfaces. We determine that this layer-wise finite-difference discretization has the potential to significantly reduce the simulation cost, compared to its fully uniform counterpart. Stability of such a discretization is achieved by using specially designed difference operators, which are variants of the standard difference operators with adaptations near boundaries or interfaces, and penalty terms, which are appended to the discretized wave system to weakly impose boundary or interface conditions. Combined with specially designed interpolation operators, the discretized wave system is shown to preserve the energy-conserving property of the continuous elastic wave equation, and a fortiori ensures the stability of the simulation. Numerical examples are presented to demonstrate the efficacy of the proposed simulation approach.

Development progress of power prediction robot and platform: Its world level very long term prototyping example

Global Power Prediction Systems prototype version 2021 is presented with its system decomposition, scope, geographical/administrative/power grid decompositions, and similar. “Welcome”, “sign-up”, “log-in”, and “non-registered user main” web-interfaces are designed as draft on Quant UX. Map canvas is given as world political map with/without world power grid layers on QGIS 3.16.7-Hannover. Data input file is prepared based on several sources (1971-2018). It includes minimum and maximum values due to source value differences. 70/30 principle is applied for train/test splitting (training/testing sets: 1971-2003/2004-2018). 10 models are prepared on R version 4.1.1 with RStudio 2021.09.0+351. These are R::base(lm), R::base(glm), R::tidymodels::parsnip(engine("lm")), R::tidymodels::parsnip(engine("glmnet")) with lasso regularization, R::tidymodels::parsnip(engine("glmnet")) with ridge regularization, R::forecast(auto.arima) auto autoregressive integrated moving average (ARIMA), R::forecast(arima) ARIMA(1,1,2), and ARIMA(1,1,8). Electricity demand in kilowatt-hours at the World level zone for up to 500-years (2019-2519) prediction period with only 1-year interval is forecasted. The best model is the auto ARIMA (mean absolute percentage error MAPE and symmetric mean absolute percentage error SMAPE for minimum and maximum electricity consumption respectively 1,1652; 6,6471; 1,1622; 6,9043). Ex-post and ex-ante plots with 80%-95% confidence intervals are prepared in R::tidyverse::ggplot2. There are 3 alternative scripts (long, short, RStudio Cloud). Their respective runtimes are 41,45; 25,44; and 43,33 seconds. Ex-ante 500-year period (2019-2519) is indicative and informative.

Research on grid‐dependence of neural network turbulence model

AbstractTurbulence machine learning based on deep neural network has become a research hotspot in turbulence modeling. Although most turbulence models have strict requirements on grid dependence, there are few analyses on grid dependence on the coupling of models and equations. In this article, a neural network turbulence model is constructed for the flow around airfoil with high Reynolds number, and the effects of wall‐normal grid spacing on the calculation accuracy are studied. The results show that compared with the traditional differential equation turbulence model, the neural network turbulence model can break through the limitation of y+ < 1 and relax the requirement of the normal density of the boundary layer grid while ensuring the accuracy.

HEXAGONAL GRIDS APPLIED TO CLUSTERING LOCATIONS IN WEB MAPS

Abstract. One of the popular ways to clutter reduction techniques is to combine neighboring points into one marker that somehow shows that it contains multiple entities – this way is called clustering. In this paper, we present a JavaScript library to define optimal size of clusters and render them. Moreover, markers have to present heterogeneous data inside of clusters.The presented library relies on server side clustering, no matter if is it a real-time clustering or a static bunch of hexagonal grids. For the library, a server provides the bunch of grid layers by different cell sizes – from smaller to larger. The library relies on data fetching provided by external library, such as Mapbox/Maplibre, so it can work with both GeoJSON and vector tiles. Using the HTML Canvas to render the marker allows to full customizing the marker image: manage the colors and proportions of cluster fractions and the size.

Discretization Analysis of Fluid Mechanical Flow Field Grid

The design basis of the performance of special industrial fluid machinery is to obtain the distribution of air flow parameters through the solution of flow field. In the numerical solution of flow field, the discretization of computational domain grid is the key factor affecting the calculation results. In this paper, the two-dimensional axisymmetric flow field analysis model were adopted. By establishing the software interface and automatic execution script file, the grid discreteness analysis process was established. The Richardson extrapolation method was used to infer the accurate solution of the flow field, and the grid independence and convergence analysis and the grid spacing analysis of the first layer of the wall were carried out. The results showed that the numerical results gradually approached the exact solution with the increase of the total number of grids, but the correlation between the numerical results and the total number of grids decreased in this process; By changing the normal spacing of the first layer of grid on each wall and making mathematical statistical analysis, the sensitive area of grid spacing could be determined. The method established in this paper could significantly improve the overall efficiency of the fluid mechanical mesh discreteness analysis and flow field analysis, and recommended the configuration of the optimal mesh discretization mode for the subsequent simulation calculation, which was conducive to further improve the calculation accuracy and efficiency of the flow field.

Tsunami impact assessment for low-lying cities along the Northern Atlantic coast of Morocco using MIRONE software

The Northern Atlantic coastline of Morocco is potentially exposed to tsunamis, like that triggered by the large Lisbon event (November 1st, 1755), also known as the most destructive event in Moroccan history. In this work, we used MIRONE software to simulate tsunami phenomenon in the Southwest Iberian Margin region, combining a series of bathymetric and topographic grid layers with an initial water elevation generated using Mansinha's formulations and assuming an instantaneous seabed movement. For this investigation, we considered four scenarios, associated with four potential seismic sources for the 1755 earthquake located in the Gulf of Cadiz. Thus, for each scenario, we obtained a map showing the results of the simulation (distance traveled, wave displacement speed, evolution of wave heights from offshore to coastal areas and arrival travel times). These maps showed that cities like Mohammedia, Casablanca and El-Jadida, were important stakes that could be impacted by a tsunami originating from these sources. For these cities, we thus determined the traveling water columns and the inland distances that could be reached by this inundation. The results show that these cities are potentially threaten by maximum water elevation exceeding 20 m in some locations, with a worse scenario characterized by flow depth and inundation distance ranging from 6 m to 10, and 1.8 km–4.6 km, respectively. These results should also be useful for the authorities, emergency, and decision planners to develop tsunami protection and risk awareness among the coastal communities of Morocco.

Triboresistive Touch Sensing: Grid‐Free Touch‐Point Recognition Based on Monolayered Ionic Power Generators (Adv. Mater. 19/2022)

Triboresistive Touch Sensing In article number 2108586, Jeong-Yun Sun and co-workers report a novel type of touch sensing, termed triboresistive touch sensing, which is developed for self-powered gridless touch recognition. An ionic poly(dimethylsiloxane) exhibiting high transmittance (96.5%), stretchability (539.1%), resilience (99.0%), and ionic conductivity (0.25 mS m−1) is designed to generate power based on the electric field generated by touch. The generated voltages ensure recognition of the touch positions without electrode grid layers and external power sources.

An Energy Aware Multi Slot Scheduling with Two-Layer Hexagonal Based Integrated Aggregation Approach for Underwater Wireless Sensor Networks (UWSN)

In the present era, Underwater Wireless Sensor Network (UWSN) is an emerging technology that involves a huge amount of sensor nodes to collect and monitor information from the underwater environment. However, the data transmission process is constrained due to the collision and energy consumption which can adversely affect the performance. Hence, there is an essential need to develop a suitable mechanism that addresses these challenges using a data aggregation-based routing mechanism in UWSN. In this paper, a Multi-Slot Scheduling with a Two-Layer Hexagonal based Integrated Aggregation model (MSS-TLHIA) is proposed that offers a prolonged lifetime with less energy consumption and collision avoidance. In this model, data aggregation is performed using the aggregator node selection process. Initially, the entire network is partitioned into several hexagonal grids using the golden ratio. This partitioning offers an improved coverage area for every node which are participating in the network. Once the network is partitioned into coverage areas called clusters, a Cluster Head (CH) is selected using the ranking-based fuzzy mechanism. Then, an aggregator node is selected in common for both the layers of the hexagonal grids. In order to prevent the energy drain of the aggregator node completely and to prolong their lifetime, the aggregator node is re-selected for every time slot. Furthermore, the occurrence of collision is avoided by the multi-slot scheduling process. Experimental results demonstrate that the performance of the proposed model is compared with other existing protocols and achieves better results in terms of network lifetime, energy consumption, collision rate, packet dropped rate, packet delivery, and data forwarding measures.

Downscaling Switzerland Land Use/Land Cover Data Using Nearest Neighbors and an Expert System

High spatial and thematic resolution of Land Use/Cover (LU/LC) maps are central for accurate watershed analyses, improved species, and habitat distribution modeling as well as ecosystem services assessment, robust assessments of LU/LC changes, and calculation of indices. Downscaled LU/LC maps for Switzerland were obtained for three time periods by blending two inputs: the Swiss topographic base map at a 1:25,000 scale and the national LU/LC statistics obtained from aerial photointerpretation on a 100 m regular lattice of points. The spatial resolution of the resulting LU/LC map was improved by a factor of 16 to reach a resolution of 25 m, while the thematic resolution was increased from 29 (in the base map) to 62 land use categories. The method combines a simple inverse distance spatial weighting of 36 nearest neighbors’ information and an expert system of correspondence between input base map categories and possible output LU/LC types. The developed algorithm, written in Python, reads and writes gridded layers of more than 64 million pixels. Given the size of the analyzed area, a High-Performance Computing (HPC) cluster was used to parallelize the data and the analysis and to obtain results more efficiently. The method presented in this study is a generalizable approach that can be used to downscale different types of geographic information.

Effectiveness of buckling restrained braces for upgrading earthquake resistant capacity of single layer grid dome

This study investigates the effectiveness of buckling restrained braces (BRBs) adopted for reducing dynamic responses of a grid dome to severe earthquakes. The diameter of the dome is 120 m of a circular plan. The dome is supported by a ductile substructure composed of BRBs, and the substructure is proportioned so as to initially yield under a base shear coefficient of approximately 0.30 and to bear a base shear coefficient of 0.40 against earthquake motions of the ultimate limit state. Artificial seismic accelerations based on a design spectrum specified in a Japanese code are applied in the present analysis. The intensity of the applied accelerations ranges from the serviceability limit level to the ultimate limit level. The results of responses have provided us with valuable information indicating that the ductile substructure of the dome absorbs seismic energy with a stable hysteresis loop, significantly decreasing the responses of the dome. The responses also show that the dynamic amplification within the dome is greatly suppressed in comparison with those in domes supported by elastic substructures. A formulation for the response reduction rate is proposed. The present paper clearly indicates the feasibility of constructing large reticulated domes of this type in regions prone to severe seismicity using such BRBs.

Triboresistive Touch Sensing: Grid-Free Touch-Point Recognition Based on Monolayered Ionic Power Generators.

Recent growing pursuit of skin-mountable devices has been impeded by the complicated structures of most sensing systems, containing electrode grids, stacked multilayers, and even external power sources. Here, a type of touch sensing, termed "triboresistive touch sensing", is introduced for gridless touch recognition based on monolayered ionic power generators. A homogeneous monolayer, i.e., ionic poly(dimethylsiloxane) (PDMS), generates electricity based on the electric field generated by touch. Voltages generated at each corner of the ionic PDMS rely on resistance between touch points and each corner, ensuring recognition of the touch positions without the need for electrode grid layers and external power sources. With notable advantages of high transparency (96.5%), stretchability (539.1%), and resilience (99.0%) of the ionic PDMS, epidermal triboresistive sensing is demonstrated to express touch position and readily play a musical instrument. A gridless system of triboresistive sensing allows rearrangement of the touch sections according to a given situation without any physical modification, and thus easily completes consecutive missions of controlling position, orientation, and gripping functions of a robot.

Construction of novel cluster-based MOF as multifunctional platform for CO2 catalytic transformation and dye selective adsorption

Synthetic conditions and ligands are the key structural defining factors of metal–organic frameworks (MOFs). Therefore, reasonable optimization of these aspects is considered to be an effective means for designing materials with novel structures and target functions. Herein, two novel Co(II)-based MOFs, namely [Co(HL)(dibp)]n (HL-8) and {[Co2(L)(OH)(dibp)]·DMA}n (HL-9) (H3L = 2′,6′-dimethyl-[1,1′-biphenyl]-3,4′,5-tricarboxylic acid; dibp = 4,4′-di(1H-imidazol-1-yl)-1,1′-biphenyl]), have been hydrothermally synthesized and structurally characterized. HL-8 crystallizes in the orthorhombic system (Pna21) with a grid layer structure, while HL-9 crystallizes in the monoclinic P21/n space group assembled through Co4(OH)2 clusters with organic ligands. Remarkably, benefiting from the finite cage-like structure, HL-9 exhibited enhanced performance in carbon dioxide (CO2) adsorption/catalytic transformation and excellent size selectivity during dye molecular adsorption process.

Preference based multi-objective reinforcement learning for multi-microgrid system optimization problem in smart grid

Grid-connected microgrids comprising renewable energy, energy storage systems and local load, play a vital role in decreasing the energy consumption of fossil diesel and greenhouse gas emissions. A distribution power network connecting several microgrids can promote more potent and reliable operations to enhance the security and privacy of the power system. However, the operation control for a multi-microgrid system is a big challenge. To design a multi-microgrid power system, an intelligent multi-microgrids energy management method is proposed based on the preference-based multi-objective reinforcement learning (PMORL) techniques. The power system model can be divided into three layers: the consumer layer, the independent system operator layer, and the power grid layer. Each layer intends to maximize its benefit. The PMORL is proposed to lead to a Pareto optimal set for each object to achieve these objectives. A non-dominated solution is decided to execute a balanced plan not to favor any particular participant. The preference-based results show that the proposed method can effectively learn different preferences. The simulation outcomes confirm the performance of the PMORL and verify the viability of the proposed method.

Cracking behaviour of tunnel lining under bias pressure strengthened using FRP Grid-PCM method

During operational stage, lining cracking is a common anomaly for road tunnels, which seriously affects the integrity and service-life of tunnels. Bias pressure is one of the most important factors that cause lining cracking. In order to provide a novel and effective control method for lining cracking, a series of scale tests regarding the strengthening of tunnel lining using fiber reinforced plastic grid with polymer-cement-mortar (FRP grid - PCM) were carried out, and the effects of various parameters on the control of lining cracking, such as the acting range of bias pressure, the layout range of the FRP grid layer and the number of FRP grid layers were studied. The scale tests were composed of seven specimens, including two reference specimens under different acting ranges of the bias pressure and five strengthened specimens with different strengthening parameters. The inhibitory mechanism of FRP grid layer for lining cracking was also discussed. The results show that the FRP grid layer could effectively bear tensile stress, so that the propagation of the tensile crack was effectively suppressed, and the bearing capacity of the lining was significantly improved. When the acting range of the bias pressure was small, that is, the internal force of the lining section was dominated by the bending moment, the FRP grid layer could improve the rigidity of the lining. More specifically, the gain increased with a concurrent increase in both the number and the layout range of FRP grid layers, whereas it worsened with an increase in the acting range of the bias pressure. The results showed that the FRP grid - PCM method is a potential control method for the tensile crack of the lining.

Clustering of Marine Vessel Trajectory Data for Routes Planning through Water Areas with Heavy Traffic

The article is devoted to the problem of ensuring the safety of vessel traffic. One of the elements of the traffic organization in areas with heavy navigation is the system of establishing the routes of vessels. This system is a set of restrictions imposed by a certain traffic pattern and rules adopted in a particular water area. The paper considers the problem of planning a transition route for water areas with heavy marine traffic. The planning of the vessels transition route during the movement of the water area with established routes must be carried out taking into account the specified restrictions. A possible way to identify these restrictions is to isolate the movement patterns of a particular sea area from the retrospective information about its traffic. Model representations of such a problem can be formulated on the basis of the idea of clustering the parameters of traffic. The route planning problem model is based on finding the shortest path on a weighted graph. Several ways of constructing such a graph are proposed: a regular grid of vertices and edges; a layered ore random grid of vertices and edges; vertices and edges based on retrospective data. The weight of the edges is proposed to be set as a function of the “desirability” of a particular course of the vessel for each point of the water area, taking into account the identified movement patterns. The paper discusses possible clustering methods and makes a choice in favor of subtractive clustering.

ЧИСЛЕННО-ЭКСПЕРИМЕНТАЛЬНОЕ ИССЛЕДОВАНИЕ НЕЛИНЕЙНОГО СЖАТИЯ ПАКЕТОВ МЕТАЛЛИЧЕСКИХ ПЛЕТЕНЫХ СЕТОК

The results of numerical simulation of elastoplastic compression of symmetrical fragments of a package of woven steel meshes are presented. The thickness of the symmetrical fragment is one and two layers. The study was carried out under dynamic loading conditions in the ANSYS LS-DYNA computer system. The mesh package is formed by superimposing layers on top of each other while maintaining the direction of the wires. The packet has a quasi-periodic structure; therefore, symmetrical fragments can be distinguished. For two mesh layers, a fragment is accepted, taking into account the shift of the layer in the lateral directions by half the size of the cell. The compression was carried out by a pair of absolutely rigid plates moving symmetrically towards each other at a constant speed for a given time interval. A multilinear plasticity model with isotropic hardening was used to describe the behavior of the material. If the maximum specified deformation is exceeded in the calculation, the diagram automatically continues with a small linear hardening modulus. A comparative analysis of numerical solutions for the compression of symmetrical fragments from one and two layers of a woven mesh is carried out. When the fragments are compressed, a strongly uneven stress-strain state arises in the wires, especially large irreversible deformations occur in the knots of weaving. The deformation curves of the fragments have characteristic inflections associated with the fact that the deformation process includes not only knots of weaving, but also deformations of wire compression along its entire length. The numerical results are compared with the experimental dynamic compression curve of a multilayer mesh package. The compression curves are different for one and two layers. For two layers of grids, the deformation curve at low pressure is more consistent with the experimental data. Two stages of behavior of the deformation diagram are observed at low and high degrees of compression, the characteristic inflection is formed somewhat earlier than in the numerical solution for one layer. Numerical dependences of the relative area of the normal and lateral passage sections of a symmetrical fragment of a mesh package on the compression strain are obtained. These data can be used to simulate the propagation of shock waves through multilayer woven mesh packages.