Network Layout Research Articles

Collaborative optimization design for district distributed energy system based on energy station and pipeline network interactions

District distributed energy systems (DDESs) are widely used worldwide due to their environmentally-friendly and energy-saving characteristics. The strong correlation and coupling of energy stations and pipeline networks lead to difficulties in the collaborative optimization design of the DDES. To minimize the total annual cost of the system, this research proposed a collaborative optimization model to realize the integrated design of the DDES. The energy distance method is combined with the K-means cluster method to solve the problem of locating and sizing energy stations. The pipelines planning algorithm based on “Dijkstra algorithm (DA) + genetic algorithm (GA)” is used to optimize the pipeline layout and diameter simultaneously. The improved DA method continuously updates the cost full adjacency matrix and pipe diameter matrix of each pipe segment by optimizing the access sequence of user nodes, and finally obtains the optimal layout and pipe diameter of the pipe network at the same time. Moreover, this paper reveals the influence factors that should be considered in the planning of DDES, such as the number of energy station and flow velocity. The results indicate that compared to traditional optimization processes, the collaborative method proposed in this paper reduced the total annual cost of the pipeline network by 20.5 %. The improved DA method solves the problem of pipeline sharing while preventing the system from falling into local optima. Moreover, optimizing the number of energy stations and flow velocity can reduce annual cost of pipelines by 0–14 % and 0–20 %, respectively. This study provides theoretical guidance and technical support for researchers in the planning and designing of DDES.

Assessment of the integrated benefits of highway infrastructure and analysis of the spatiotemporal variation: Evidence from 29 provinces in China

While China has made great achievements in highway infrastructure construction, there are still problems with the quality of development and layout balance. This paper uses the technique for order preference by similarity to ideal solution (TOPSIS) and the entropy weight method to measure the integrated benefits of highway infrastructure (IBHIs) in 29 provinces in China from 2015 to 2020. The measurement is carried out by constructing an assessment system for the IBHIs, and the regional differences and dynamic evolutionary trends of China's IBHIs are revealed using methods such as kernel density estimation and Dagum Gini ratio decomposition. The study finds that (1) there is more potential to improve the development level of China's IBHIs. The problem of economic benefits is more prominent, while social and environmental benefits are steady to favorable in terms of their state. (2) The IBHIs in China continue to improve, with the absolute differences within regions widening and producing polarization or multicollinearity. (3) The relative differences in China's IBHIs are narrowing, and the major factor in the uneven development across regions is the intergroup differences. This study explores the current development status, dynamic change characteristics and different causes of IBHIs in China, providing a theoretical basis and empirical support for further optimizing the layout of highway networks and promoting high-quality development in the highway transport sector.

Investigating the Spatiotemporal Relationship between the Built Environment and COVID-19 Transmission

Earlier studies have examined various factors that may contribute to the contagion rate of COVID-19, such as urban climatic and socioeconomic characteristics. However, there is a lack of studies at the township level detailing the spatiotemporal settings of built environment attributes, especially in the context of lockdown as a response to the global Omicron outbreak. In this study, we extended the existing literature by relating the initial-stage Omicron pandemic conditions with more comprehensive measures of the built environment, including density, diversity, design, distance to transit, and destination accessibility. The variations from the confirmed clusters of COVID-19 and asymptomatic infected cases before, during, and after the lockdown throughout the Omicron outbreak were identified geographically using GIS methods in 218 township-level divisions across Shanghai during the lockdown period. We also compared the regression results of the ordinary least-squares regression, geographically weighted regression, and geographically and temporally weighted regression. Our results show that (1) among all the built environment variables, metro line length, walking accessibility, hotel and inn density, and population exhibited positive significance in influencing pandemic prevalence; (2) spatial and temporal variations were evident in the association between accessibility, mobility, density-related built environment variables, and COVID-19 transmission across three phases: pre-lockdown, during lockdown, and post-lockdown. This study highlights the importance of targeted public health interventions in densely populated areas with high demand for public transit. It emphasizes the significance of transportation network layout and walking accessibility in controlling the spread of infectious diseases in specific urban contexts. By considering these factors, policymakers and stakeholders can foster urban resilience and effectively mitigate the impact of outbreaks, aligning with the objectives of the 2030 UN Sustainable Development Goals.

A fast and differentiable optimization model for finding the minimum dominating set in large-scale graphs

The minimum dominating set is an important NP-hard problem in graph theory, widely used in various fields such as computer network layout and social networks. Although linear programming algorithms can obtain a global optimal solution on small graphs, they are not suitable for large graphs. To find a local optimal solution, many heuristic algorithms have been proposed. These algorithms require strong techniques and programming, and most of them still need improvement in performance on large graphs. This paper presents a cooperative–competitive model that transforms the discrete problem into a continuously differentiable problem. By using the gradient descent method, this approach can handle all vertices simultaneously, and its time complexity is linear. Compared to existing search algorithms, this method is based on a straightforward principle and is fast. For small graphs, it can achieve performance almost comparable to linear programming methods. For large graphs, this method can explore more diverse local optimal solutions in the same amount of time, making it easier to obtain better performance. In this paper, a comparison and analysis of this gradient-based algorithm and graph theory-based search algorithms are conducted on the minimum dominating set, allowing researchers to have a clearer understanding of the advantages and disadvantages of search algorithms and gradient methods in complex problems. The referenced search algorithms may potentially improve the gradient descent algorithm, leading to better solutions in other fields. At the same time, gradient-based methods can be used to solve many similar NP-hard problems in graph theory.

Hierarchical framework for demand prediction and iterative optimization of EV charging network infrastructure under uncertainty with cost and quality-of-service consideration

As electric vehicles (EVs) continue to grow in popularity, the demand for efficient and effective EV charging infrastructure is rapidly increasing. However, the design and deployment of such infrastructure faces numerous challenges, some of which include demand uncertainty, EV network layout, maintenance cost, and quality of service (QoS), and have proven to be particularly challenging in cases where all objectives need to be addressed simultaneously. To address these challenges, this study proposes a hierarchical iterative optimization approach that aims to minimize the demand–supply mismatch at a higher level and considers both cost and QoS under uncertainty at a lower level in a dynamic EV charging network. Specifically, the proposed approach uses a time-series linear regression ensemble to accurately predict future demand at demand points, which is then used to match demand at demand points with supply at supply points. We then model the infrastructure allocation problem as a knapsack problem and use an allocation algorithm to determine the optimal number of charging stations at each supply point. The infrastructure is allocated to minimize total cost and maximize QoS. A framework for EV infrastructure optimization is designed and can be applied to any type of network. The effectiveness of our proposed approach is demonstrated through extensive experimentation on various datasets by comparing with existing state-of-the-art approaches. Simulation results show that the proposed approach is robust to different EV networks, handles uncertainty well, can effectively address the challenges associated with EV infrastructure optimization, and can provide policy makers and infrastructure planners with a practical and efficient tool for designing and deploying charging infrastructure. This study contributes to the field of EV infrastructure network optimization by modeling QoS and proposing a hierarchical optimization framework that effectively addresses the challenges associated with the design and deployment of charging infrastructure.

Application of Artificial Intelligence Technology in the Optimal Deployment of Wireless Sensor Network Nodes

WSN (Wireless Sensor Network) is a network composed of a large number of sensor nodes self-organizing through wireless communication technology. Nodes are prone to failures due to environmental impact and energy depletion, and environmental interference and node failures can easily cause changes in the network topology. This article conducts research on the application of AI (Artificial Intelligence) technology in the optimal deployment of WSN nodes. Using AI technology to optimize the deployment of hybrid WSN mobile nodes, ensuring that the node density of each sub target area reaches its expected node density to ensure effective coverage of the entire target monitoring area. Given the target area range, the number and position of sensor nodes are determined through AI technology, which is the network layout for a given target area. Effectively reducing the data flow of the entire network. Due to the limited energy of sensor nodes, minimizing energy consumption and maximizing network lifespan are the main goals of designing WSN. Deployment strategies must optimize the deployment strategies of sensor nodes, intermediate nodes, and base stations to ensure coverage, connectivity, and robustness.

Water Distribution Network Optimization Model with Reliability Considerations in Water Flow (Debit)

Water distribution networks (WDNs) are defined as the planning for the development, distribution, and utilization of water resources. The main challenge of WDNs is to preserve limited water resources while providing effective benefits from these resources in accordance with environmental considerations. Water distribution networks use hydraulic components to connect water resources to consumers. The diameter of each pipe, the layout of the pipe network, and the total length of pipes all contribute to the most effective layout for a water distribution system. This study considers the assurance that the flow (discharge) of water is in accordance with what is expected, with such aspects apt to be described as a particular form of reliability. As a result, this study proposes a stochastic optimization model with non-linear probability constraints for overcoming the challenges of water distribution networks while taking water flow reliability into account. The pressure drop equation causes the non-linear shape. The stochastic model of the opportunity constraint is changed to a deterministic multi-objective model using an approach based on integer programming and sample averaging to solve the resulting model. The direct search approach (neighbourhood search) is then applied to tackle the integer part.

Well-Drilling and Groundwater Monitoring Network Construction Taking Changde City as an Example

Entrusted by the Environmental Protection Bureau of Changde City we conducted drilling sampling survey and constructed a monitoring network for groundwater in several counties and districts of Changde City. This article introduces the drilling technology detection method and detection network layout plan adopted in the project and expounds the problems that occurred while executing the project in order to provide reference for similar groundwater capacity supervision and construction projects.

Research on Tobacco Retail Point Layout in Guanshanhu District, Guizhou Province Based on Transportation Accessibility

Guizhou tobacco planting has a long history, thanks to Guizhou's superior climate, soil and other ecological conditions and rich planting experience, laid an important position of Guizhou tobacco in China's tobacco industry, tobacco industry is Guizhou's traditional advantageous industry, but also an important pillar industry, in the economic and social development of Guizhou Province plays an irreplaceable important role, Guanshanhu District is the key work area of Guizhou Tobacco Company to arrange tobacco sales related service configuration, so for the existing tobacco network layout system in Guanshanhu District. Through the spatial layout, traffic accessibility analysis under the conditions of surrounding basic transportation facilities, and the construction of traffic time isochronous circles, the following optimization suggestions are given for the traffic layout: 1. Adjust the density of outlets to improve the efficiency of services; 2 Considering a variety of factors to help increase tobacco sales; 3.Regularly evaluate and adjust the layout; 4 Consider regional characteristics.

Research on Public Air Route Network Planning of Urban Low-Altitude Logistics Unmanned Aerial Vehicles

As urban populations continue to grow and road traffic congestion worsens, traditional ground logistics has become less efficient. This has led to longer logistics times and increased costs. Therefore, unmanned aerial vehicle (UAV) logistics has become increasingly popular. However, free-planned routes cannot meet the safety and efficiency requirements of urban airspace mobility. To address this issue, a public air route network for low-altitude logistics UAVs needs to be established in urban areas. This paper proposes a public route network planning method based on the obstacle-based Voronoi diagram and A* algorithm, as follows: Firstly, construct a city airspace grid model in which the characteristics of the airspace are mapped onto the grid map. Introduce an obstacle clustering algorithm based on DBSCAN to generate representative obstacle points as the Voronoi seed nodes. Utilize the Voronoi diagram to establish the initial route network. Then, conduct an improved path planning by employing the A* algorithm for obstacle avoidance in route edges that pass through obstacles. To ensure the safe operation of drones, set constraints on the route safety interval. This process will generate a low-altitude public air route network for urban areas. After considering the flight costs of logistics UAVs at different altitudes, the height for the route network layout is determined. Finally, the route network evaluation indicators are established. The simulation results demonstrate that compared with the city road network planning method and the central radial network planning method, the total route length is shortened by 7.1% and 9%, respectively, the airspace coverage is increased by 9.8% and 35%, respectively, the average network degree is reduced by 52.6% and 212%, respectively, and the average flight time is reduced by 19.4s and 3.7s, respectively. In addition, by solving the network model using the Dijkstra algorithm, when the energy cost and risk cost weights are 0.6 and 0.4, respectively, and the safety interval is taken as 15 m, the total path cost value of the planned trajectory is minimized.

Exploratory Analysis of Surrogate Metrics to Assess the Resilience of Water Distribution Networks

AbstractThis study compares and discusses the adequacy of surrogate resilience metrics proposed in the literature for resilience assessment of drinking water systems concerning demand increase and network redundancy. A sensitivity analysis is carried out for increasing flow rates using a conceptual case study with different layouts and demand scenarios, selecting several metrics to assess the resilience of two real network areas. Resilience metrics based on surplus energy are sensitive to network layout and demand scenarios. The network resilience index considers hydraulic reliability and network diameter uniformity. In contrast, the weighted resilience index also considers the network topology and gives importance to pipes with higher flow rates. Entropy‐based resilience metrics mainly rely on the network flows' uniformity and are sensitive to pipe redundancy. The entropy metric most adequate to assess the hydraulic capacity is the diameter‐sensitive flow entropy, since it is sensitive to the velocity inside the pipes. Topology metrics cannot assess the hydraulic capacity though evaluate the system redundancy (meshed‐ness coefficient), robustness (central‐point dominance) and water transportation efficiency (average‐path length). Surrogate resilience metrics do not assess the system performance during a failure. They indicate systems which are better prepared to overcome failure events and increased demand events, providing vital information to drinking water systems management.

Creating an Innovative Blueprint for Barangay Development

This study is focused on the augmentation, extension, and enrichment of knowledge pertaining to the design of a new development plan for Barangay Babuyan in Carrascal, Surigao Del Sur. The central emphasis is placed on the intricate interplay between person-environment relationships, particularly concerning the innovative facilities being designed, notably housing. Through a comprehensive approach, the researchers executed a survey in line with the guidelines established by the Municipal Planning and Development Council (MPDC) of Carrascal. As per the MPDC, the designated relocation site encompasses a total area of 100,000 square meters, with each unit boasting a floor space of 48 square meters and an accompanying lot area of 100 square meters. The proposed project involves multifaceted considerations encompassing critical elements such as road network layout, housing design, electrical and water storage tank plans, drainage systems, and provisions for open spaces. This endeavor integrates a range of methodologies including surveying, on-site investigation, data collection, formulation of a novel barangay development plan, and comprehensive cost estimations. The development of a meticulously designed plan stands as a pivotal solution that addresses various aspects of community growth. This design, projected to efficiently accommodate the entire barangay, is rooted in the observation of a positive 2.33% average population growth rate from 1990 to 2015. Furthermore, the chosen relocation site holds the advantage of being hazard-free, exhibiting low susceptibility to landslides. The newly conceptualized barangay development plan is characterized by an easily accessible road network featuring a width of 6 meters. This network is illuminated by energy-efficient 100W solar LED street lights. In tandem, the plan includes a 3.50m x 3.50m water storage tank and an 8m x 6m house design encompassing a bedroom, living area, kitchen, and shared bathroom. The culmination of this proposed study is marked by its high level of acceptance, as it fulfills the requisites set forth by the Local Government Unit (LGU) and is aligned with the aspirations of the residents

Geological Hazards of Housing Development of a Pliocene Terrace Land Plot in the City of Rostov-on-Don

Introduction. In Rostov-on-Don the industrial and civil construction is carried out under a number of geological hazards: soils subsiding deformations, landslides, underfloodings, suffusions. Building up the new urban districts has always led to the groundwater surge. The Pliocene terrace building conditions in the eastern part of the city are characterised by the high risk of underflooding due to the shallow groundwater, low hydraulic gradients and water permeability of soils. The data on the present state of the groundwater level is not published in the media. Based on the materials on the territory geological structure and hydrogeological conditions, as well as on the numerical hydrogeological modeling, the present paper aims to investigate the groundwater balance determining factors and to develop the geofiltration monitoring recommendations for constraining the underflooding.Materials and methods. The geological structure and hydrogeological conditions of the territory were analysed using the published reading and graphical materials, as well as the engineering and geological survey results. The aquifers’ geometrical parameters analysis and the spatial data visualisation were made by means of the QGIS geographic information system. For creating and analysing the numerical geofiltration models, the Visual Modflow software product of Aquaveo company was used.Research results. The natural and technogenic geofiltration state of the territory under investigation had been forming for many years. The study of the designed numerical hydrogeological model indicates on the high risk of local underflooding as well as defines the conditions of its spreading throughout the entire territory. The role of the ravine-gully system that drains the aquifer and constrains the underflooding has been assessed. To control the territory groundwater balance and to specify the aquifers’ parameters, the layout of the observational hydrogeological wells network has been developed. Discussion and conclusion. The existing groundwater balance is vulnerable. Building up the territory is highly likely to cause additional infiltration of technogenic water and to lead to underflooding. The territory development project should envisage the geofiltration process monitoring and groundwater draining solutions.

Software Defined Networking Architecture for Energy Transaction in Smart Microgrid Systems

A decentralized power distribution network consisting of smart microgrids introduces opportunities to trade with energy called transactive energy. However, research studies in the existing literature suggest that several standardized information models for TE do not meet the network architecture’s reliability, flexibility, and security requirements. This limitation is mainly due to the static nature of traditional IP infrastructure. To achieve these requirements in the network architecture, this study investigates the optimized application of software-defined network architecture for transactive energy in smart microgrid systems. Through literature research, unique design approaches in an SDN architecture are identified that improve the reliability, flexibility, and security of the SDN architecture. These design approaches include a decentralized controller network layout, redundant link configuration, a mesh network topology, and data encryption. The proposed solution uniquely combines these design approaches into a single optimized SDN solution for TESMS. To validate the improvements of the findings from the literature research, each design approach is simulated in this study using Mininet SDN emulator and AnyLogic system simulation software. The proposed solution is then applied to a use-case scenario that shows the improvements required for TESMS. The use-case scenario shows significant improvement in the data path uptime. An improvement of 0.27% is achieved, which equates to a 2 h per month increase in the data path uptime. The results of the simulation show that the proposed SDN architecture improves the reliability and flexibility of a traditional SDN network. Furthermore, enabling encryption between the nodes improves the security of the SDN architecture.

THE EFFECTS STREET-NETWORK CONFIGURATION IN MODELLING WALKABILITY THROUGH SPACE SYNTAX

This study investigates street network connectivity in an informal settlement, Kampong Taman Sari, Bandung. It generally refers to the informal residential area with minimum facilities and urban services. The majority of these settlements depict irregular patterns and narrow paths or alleys. Thus, kampong inhabitants mainly rely on walking, biking, and riding motorcycles to access vital urban features and functions. This purpose study is to examine the potential connectivity not only for accessibility but also for evacuation movement in an informal settlement. This investigation also aims to understand an associative relation between street-network configuration and informal settlement patterns with the probability distribution of pedestrian movement. This study utilizes computational street network analysis through the space syntax method that consists of two distinctive evaluations, such as axial analysis and visual graph analysis. The following result depicts the spatial accessibility, integration, permeability, walkability, and connectivity based on this relation. Experimenting in modelling a walkable kampong in the urban environment will conduce to urban design qualities of the street environment and street network layout for pedestrians or users.

Connected-closeness: A Visual Quantification of Distances in Network Layouts

This paper proposes a network-visualization metric, connected-closeness, designed to provide a quantified statement about the mediation of the topology by the node placement. It allows stating the percentage of connected nodes that are closer than a certain characteristic distance, computed on the basis of the layout, and pictured in the visualization. This statement, and others it provides, are intended to help non-experts interpreting network visualizations visually. Connected-closeness allows assessing a layout's validity from the specific angle of bringing connected nodes closer. A benchmark finds that force-directed layouts are indeed good at bringing connected nodes closer, but the metric also detects situations and layouts where it fails. It allows comparing different layouts for a given network and different networks for a given layout, and provides quantified evidence that force-driven placements consistently capture an aspect of the topological structure of networks. The calculations allow assessing visual distances as a statistical measure of edge presence in terms or precision and recall, and show that in practice, layout algorithms prioritize recall over precision. The paper provides the definition of different indicators, their underlying rationale, visual examples, a simple optimization, implementation remarks, and a benchmark of 14 network generators and 7 node-placement algorithms rendered 100 times each, for a total of 9800 network visualizations.

Effect of skew angle on bridge deck behavior with different cross girder patterns

ABSTRACT Bridges are common and important constructions to overcome different obstacles in any transportation network. Variations in bridge types include variation in span length, statical system, construction material, construction methods and sustained loads. Choosing the suitable statical system is affected with several factors such as construction time, availability of materials, available budget, contractors’ background and one of the most important factors is the layout of the road network or obstacles outline beneath the bridge. Skew bridges result from inclined intersection between bridge axis and the below road or water stream. The famous problems that result from this inclination are distribution of loads among the main girders and variation in bearings` reactions. Stiffness of cross girders especially near the skew edge affects noticeably the distribution of loads in main girders. In this paper, analysis of medium span skew RC girder bridge deck will be proposed using different skew angles (α) measured from horizontal axis that are 20̊, 30̊, 40̊ and 50̊ and different cross girder patterns. Analysis will be performed using grillage model in FEM software package. Analysis includes different skew angles, different cross girder patterns and different distributed gravity load patterns. The observed outputs in the analysis are reactions at bearings and bending moment values in main girders. In this paper, effect of skew angles and different cross girders patterns on reactions at bearings will be introduced. The effect of these variables on main girders BM values will be discussed in extended paper work.

Grounding force-directed network layouts with latent space models

Force-directed layout algorithms are ubiquitously used tools for network visualization. However, existing algorithms either lack clear interpretation, or they are based on techniques of dimensionality reduction which simply seek to preserve network-immanent topological features, such as geodesic distance. We propose an alternative layout algorithm. The forces of the algorithm are derived from latent space models, which assume that the probability of nodes forming a tie depends on their distance in an unobserved latent space. As opposed to previous approaches, this grounds the algorithm in a plausible interaction mechanism. The forces infer positions which maximise the likelihood of the given network under the latent space model. We implement these forces for unweighted, multi-tie, and weighted networks. We then showcase the algorithm by applying it to Facebook friendship, and Twitter follower and retweet networks; we also explore the possibility of visualizing data traditionally not seen as network data, such as survey data. Comparison to existing layout algorithms reveals that node groups are placed in similar configurations, while said algorithms show a stronger intra-cluster separation of nodes, as well as a tendency to separate clusters more strongly in multi-tie networks, such as Twitter retweet networks.

Ensemble‐based estimates of the impact of potential observations

AbstractIn order to conduct observation‐network design experiments for a forecast system, methods are needed to estimate the benefit of potential observations. Ideally, these methods are flexible enough to accommodate multiple observation types and forecast lead times while being computationally fast enough to evaluate many potential observational network layouts. For ensemble forecasts, this can be achieved by assuming that analysis and forecast errors are represented by the respective ensemble variance and by assuming a linear ensemble sensitivity between the background state and a forecast quantity of choice. These assumptions enable estimating how much the forecast error of a forecast quantity would be reduced for an arbitrary combination of observation locations and types without the need to run additional forecasts. An aspect that has received little attention is that to apply these variance‐reduction estimates to a specific ensemble‐forecast system consistently, the system's localization needs to be taken into account. We introduce and compare three methods to take localization into account when estimating the benefit of potential observations. One method requires explicitly inverting the background ensemble covariance matrix, one method avoids the inversion but needs to be provided with estimates of signal propagation over time, and the third method requires both the inversion and the signal propagation estimate. We introduce a simple linear‐advection toy model to perform various observing‐system simulation experiments to test the three methods with point and indirect observations. Our results indicate that the methods requiring signal propagation to be provided are best suited to short lead times, whereas the remaining method is more accurate if signal propagation is not known well; for example, for longer lead times.

In-band full-duplex MIMO PLC systems for relaying networks

In Power Line Communications (PLC), there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons, which creates coverage issues despite the not too long distances. Hence, PLC networks often employ repeaters/relays, especially in smart grid neighborhood area networks. Even in broadband indoor PLC systems that offer a notable data rate, relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things paradigm. In this paper, we study Multiple-Input Multiple-Output (MIMO) PLC systems that incorporate in-band full-duplex functionality in relaying networks. We present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC systems. To reach this analysis, we get channel realizations from random network layouts for indoor and outdoor scenarios. We adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC standards. The concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput: smart grids with enhanced communications in outdoor scenarios, and “last meter” systems for high-speed connections everywhere in indoor ones.