Zone Partitioning Research Articles

Zoning strategy of zonal modeling for thermally stratified large spaces

Large space buildings play a significant role in modern society because of their environmental advantages and market value. While the zonal model is promising for the efficient and rapid evaluation of the stratified thermal environment, there is a lack of a reasonable and convenient zoning strategy with the advent of modern computing. This paper presents a universal and practical zonal model, in which a simplified momentum equation is applied to consider air momentum preservation, transformation, and dissipation. Hence, the zoning structure is generalized and flexible. Moreover, limiting the dimensionless temperature constraint between adjacent zones establishes the connection between thermal nonuniformity and zoning results automatically. Simultaneously, the dimension and number of zones should be restricted within reasonable ranges to satisfy the characteristics of zonal simulation and reach the criteria of convergence. To further explore and validate the zonal model, a reduced-scale experimental model was constructed to replicate the thermal stratification in a mechanically ventilated large space by considering many crucial realistic factors. A particle image velocimetry (PIV) measurement was then conducted to visualize the airflow pattern and support the partition of zones. The results showed that the zonal simulation with adaptive zoning method can realize a similar accuracy with fewer zones and exhibit a better tolerance for zoning results compared to the conventional empirical zoning method. Furthermore, a case study of an atrium was performed to demonstrate the practicality and efficiency of the method for long-term dynamic simulations of complex thermal environments and building energy use.

A novel integrated rotary reactor for NO reduction by CO and air preheating: Reactor design and heat transfer modelling

Abstract An integrated reactor for NOx reduction by CO (iNA reactor) was proposed, integrating a rotary air preheater with a decoupled NOx adsorption-reduction reactor. Three zones were created in this reactor: a flue gas zone, a reducing gas zone, and an air zone. It was expected that NOx reduction efficiency could be enhanced by independently controlled temperature and oxygen content. In this paper, heat transfer was investigated for the proposed iNA reactor to understand the temperature evolution. A heat transfer model was first developed for an air preheater for verification. Energy balance equations were proposed for both the gas and the matrix phase. The modelling results showed that the design can meet the targeted temperatures. The developed heat transfer model was further applied to simulate the temperature profiles in the iNA reactor with three zones. The influences of several design and operating parameters on the heat transfer performance were investigated: flow direction of reducing gas, inlet temperature of flue gas, rotating speed of the reactor, inlet temperature and flow rate of reducing gas, and different zone partitions. It was concluded that a slower rotating speed was preferred to maintain large temperature differences between different zones, which benefited the temperature-dependent NOx adsorption-reduction process. For the reducing gas, downward flow direction, higher temperature and flow rates were preferred. The heat transfer performance was not very sensitive to zone partition ratio, although it may have an important effect on the reaction efficiencies.

A Case Study on Urban Ventilation Assessment with Local Climate Zone (LCZ) Parameters

The local climate zone (LCZ) partitions are widely used in urban climate investigations. Parameters characterizing LCZ types could be used in investigations about urban heat island (UHI) intensity and air ventilation modelling and assessment. In the current work, modelling methods of UHI intensity and wind environment are investigated based on the LCZ parameters. A drag source term with a porous media model of the urban canopy layer was proposed to simulate the urban scale wind environment with the CFD method. Vertical and horizontal airflow in the urban canopy layer was analysed. The upward and downward wind was found in the urban canopy model influenced by the variations of building height and density. On the other hand, the heat balance models could also be conducted on LCZ. Results showed the potential capabilities in urban wind assessment. A summary of models and the requirement on LCZ parameters were proposed.

Frequency Stability of the European Interconnected Power System Under Grid Splitting in Market Zones

This paper proposes a graph theory-based approach to define the possible separation of the market zones in large power systems. The market zone partitioning is used to assess the frequency stability based on a set of parameters, including the inertia, the running capacity of the separated areas, and the power exchanged on the interconnection lines. A system split indicator is finally used to rank the worst split lines. The methodology has been tested on real scenarios of the interconnected Continental Europe power system.

Nursing management at a Chinese fever clinic during the COVID‐19 pandemic

BackgroundThe rampant spread of the novel coronavirus disease (COVID‐19) has assumed pandemic proportions across the world. Attempts to contain its spread have entailed varying early screening and triage strategies implemented in different countries and regions.AimTo share the experience of scientific and standardized management of fever clinics in China, which provide the first effective checkpoint for the prevention and control of COVID‐19.IntroductionA fever clinic was established at our hospital in Tianjin, China, for initially identifying suspected cases of COVID‐19 and controlling the spread of the disease.MethodsThe management system covered the following aspects: spatial layout; partitioning of functional zones; a work management system and associated processes; management of personnel, materials and equipment; and patient education.ResultsWithin two months of introducing these measures, there was a comprehensive reduction in the number of new COVID‐19 cases in Tianjin, and zero infections occurred among medical staff at the fever clinic.DiscussionThe fever clinic plays an important role in the early detection, isolation and referral of patients presenting with fevers of unknown origin. Broad screening criteria, an adequate warning mechanism, manpower reserves and staff training at the clinic are essential for the early management of epidemics.ConclusionThe spread of COVID‐19 has been effectively curbed through the establishment of the fever clinic, which merits widespread promotion and application.Implications for nursing and health policiesHealth managers should be made aware of the important role of fever clinics in the early detection, isolation and referral of patients, and in the treatment of infectious diseases to prevent and control their spread. In the early stage of an epidemic, fever clinics should be established in key areas with concentrated clusters of cases. Simultaneously, the health and safety of health professionals require attention.

Dynamic Reserve and Transmission Capacity Allocation in Wind-Dominated Power Systems

The large shares of wind power generation in electricity markets motivate higher levels of operating reserves. However, current reserve sizing practices fail to account for important topological aspects that might hinder their deployment, thus resulting in high operating costs. Zonal reserve procurement mitigates such inefficiencies, however, the way the zones are defined is still open to interpretation. This paper challenges the efficiency of predetermined zonal setups that neglect the location of stochastic power production in the system, as well as the availability, cost and accessibility of flexible generating units. To this end, we propose a novel reserve procurement approach, formulated as a two-stage stochastic bilevel model, in which the upper level identifies a number of contiguous reserve zones using dynamic grid partitioning and sets zonal requirements based on the total expected operating costs. Using two standard IEEE reliability test cases, we show how the efficient partitioning of reserve zones can reduce expected system cost and promote the integration of stochastic renewables.

大型核动力船舶应急计划区分区策略研究

大型核动力船舶应急计划区分区策略研究

Gray Zone Partitioning Functions and Parameterization of Turbulence Fluxes in the Convective Atmospheric Boundary Layer

AbstractHere, we present the first attempt to fully represent three‐dimensional turbulence fluxes in the “Terra Incognita” or the gray zone in other words. In order to derive partitioning functions, representing the partitioning between subgrid and total fluxes, we make use of high‐resolution large‐eddy simulations (LES), which are performed with the Weather Research and Forecasting (WRF) model. LES computations are performed for various levels of convective instability, ranging from pure buoyant to strongly sheared convection. Then, the resulting reference‐LES fields are successively coarse grained from its original microscale grid spacing ( m) up to typical mesoscale grid spacings ( km). The given process is applied by means of an advanced filter, that is, the Butterworth filter. It enables a clear scale‐specific filtering that results in a more controlled energy transition from lower to higher wavenumbers, unlike the drawbacks of current filters in use. Finally, we parameterize the subgrid scale (SGS) partitioning functions of 10 SGS turbulence quantities: momentum fluxes (τij, six terms), heat fluxes (qj, three terms), and turbulence kinetic energy (k). Turbulence partitioning relations are parameterized in a scale‐aware, stability‐dependent, and height‐dependent form, using the sigmoidal Gompertz function. Thus, the new gray zone model provides a framework that bridges the mesoscale and microscale limits and that is suitable for the development of next generation three‐dimensional, multiscale turbulence parameterization methods or planetary boundary layer schemes.

An adversarial model for attack vector vulnerability analysis on power and gas delivery operations

Power systems often rely on natural gas pipeline networks to supply fuel for gas-fired generation. Market inefficiencies and a lack of formal coordination between the wholesale power and gas delivery infrastructures may magnify the broader impact of a cyber-attack on a natural gas pipeline. In this study we present a model that can be used to quantify the impact of cyber-attacks on electricity and gas delivery operations. We model activation of cyber-attack vectors that attempt to gain access to pipeline gas compressor controls using a continuous-time Markov chain over a state space based on the gas operator Industrial Control System firewall zone partition. Our approach evaluates the operating states and decision-making in the networks using physically realistic and operationally representative models. We summarize these models, the sequence of analyses used to quantify the impacts of a cyber-incident, and propose a Monte Carlo simulation approach to quantify the resulting effect on the reliability of the bulk power system by the increase in operational cost. The methodology is applied to a case study of interacting power, gas, and cyber test networks.

Numerical Insights Into the Effects of Model Geometric Distortion in Laboratory Experiments of Urban Flooding

AbstractGeometrically distorted scale models have been a valuable tool for physical modeling of urban flooding in a network of streets. However, little is known so far about the bias induced in such cases by the model geometric distortion. Here, we use 2‐D computational modeling to provide a first systematic quantification of this bias in the case of a synthetic urban layout. The bias is found to be generally small, with the maximum deviations of the upscaled flow depth and discharge partition from the corresponding values of the undistorted model being around 10% in the case of relatively rapid and shallow flow conditions. When the geometric distortion is increased, the computations reveal a nonmonotonous pattern of the flow variables (depth, discharge partition, and size of flow separation zones), which results from a competition between declining frictional losses and growing local losses in the model. These findings may guide the design of distorted scale models of urban flooding and assist the interpretation of laboratory observations for assessing flood protection measures, for process understanding or for validating computational modeling.

Infection control measures of a Taiwanese hospital to confront the COVID-19 pandemic.

The World Health Organization announced the coronavirus disease 2019 (COVID‐19) outbreak a pandemic on 12 March 2020. Although being in proximity to China, the original epicenter of the COVID‐19 outbreak, Taiwan has maintained a low number of COVID‐19 cases despite its close social ties and heavy traffic between Taiwan and China. Containment strategies executed by the Taiwanese government have attracted global attention. Similarly, in‐hospital settings, high alertness and swift responses to the changing outbreak situation are necessary to ensure hospital staff members' safety so they can continue to save patients' lives. Herein, we present infection control measures that can be adopted in hospital settings that were executed in a Taiwanese hospital to confront the COVID‐19 pandemic, including emergency preparedness and responses from the hospital administration, education, surveillance, patient flow arrangement, the partition of hospital zones, and the prevention of a systemic shutdown by using the “divided cabin, divided flow” strategy. The measures implemented by a Taiwan hospital during the COVID‐19 pandemic may not be universally applicable in every hospital. Nonetheless, the presented infection control methods have been practically executed and can be referenced or modified to fit each hospital's unique condition.

Extreme Photovoltaic Power Analytics for Electric Utilities

Obtaining high-fidelity information on extreme photovoltaic (PV) power is critical for electric utility system planning and operations. However, a scarcity of extreme data has previously made achieving an accurate estimate of extreme PV power an intractable challenge. In response to this challenge, this paper presents Extreme PV Power Analytics (EPVA). It utilizes k-means clustering to determine which PV systems have similar behaviors in their extreme capacity factors (ECFs) in order to incorporate more extreme data in an extreme value analysis. This extreme value analysis is subsequently applied to obtain the distribution of ECFs. Zone partitioning results and ECF distribution results for The United Illuminating Company service territory are presented to validate the effectiveness and efficacy of EPVA.

Research on traffic zone partition method based on two-level partition theory

As an important part of traffic planning, traffic zone division has drawn much attention for decades. Better than traditional methods of traffic zone division based on traffic surveys and road network structures, this paper proposes a two-level framework for dividing traffic zones by using massive car-hailing data from a big data perspective. Firstly, the grid model is established within the study area and massive travel data are matched into grids. Secondly, the Louvain community detection algorithm is used to divide the research area into different traffic medium zones (TMZs). Further, a K-prototype clustering algorithm based on partition is used to divide each TMZ into several traffic small zones (TSZs). Taking the Beijing Fifth Ring as an example, the study area is divided into 16 TMZs and 302 TSZs by using two-level partition theory. The proposed method of dividing traffic zones is proved to be efficient and accurate and can be easily applied to other areas, which helps planners to make more smarter traffic planning and city management.

Enabling Sequential-write-constrained B + -tree Index Scheme to Upgrade Shingled Magnetic Recording Storage Performance

When a shingle magnetic recording (SMR) drive has been widely applied to modern computer systems (e.g., archive file systems, big data computing systems, and large-scale database systems), storage system developers should thoroughly review whether current designs (e.g., index schemes and data placements) are appropriate for an SMR drive because of its sequential write constraint. Through many prior works excellently manage data in an SMR drive by integrating their proposed solutions into the driver layer, an index scheme over an SMR drive has never been optimized by any previous works because managing index over the SMR drive needs to jointly consider the properties of B + -tree and SMR natures (e.g., sequential write constraint and zone partitions) in a host storage system. Moreover, poor index management will result in terrible storage performance because an index manager is extensively used in file systems and database applications. For optimizing the B + -tree index structure over an SMR storage, this work identifies performance overheads caused by the B + -tree index structure in an SMR drive. By such observation, this study proposes a sequential-write-constrained B + -tree index scheme, namely SW-B + tree, which consists of an address redirection data structure, an SMR-aware node allocation mechanism, and a frequency-aware garbage collection strategy. According to our experiments, the SW-B + tree can improve the SMR storage performance 55% on average.

WKNN indoor location algorithm based on zone partition by spatial features and restriction of former location

High-precision indoor location algorithm using fingerprint highly relies on the accuracy of database. This paper proposes a WKNN indoor location algorithm based on spatial characteristics partition and former location restriction. In this proposed system, target space of large area is divided into multiple partitions by its spatial characteristics, solving the problem that one fingerprint database cannot achieve total coverage. Also, the restricted relationship between the former and the present position are introduced to increase the quality of chosen candidate reference points, and thus improve the smoothness of the estimation results obviously. A large number of indoor positioning experiments show that this algorithm could effectively improve the indoor positioning accuracy when compared with the traditional WKNN.

An ArcGIS add-in for spatiotemporal data mining in climate data

Spatiotemporal data mining has many important applications in environmental modelling. This paper introduces a modified algorithm for spatiotemporal data mining based on density-based spatial clustering of applications with noise (DBSCAN). Based on the modified algorithm, a geographic information system (GIS) add-in was developed using ArcObjects and C#, and is freely available for download. Compared with some existing methods, the new method can perform automated detection of spatiotemporal clusters using limited user input parameters. The application of the add-in was demonstrated using summer temperature data collected from 104 weather stations in southwest China from 1961 to 2011. The results suggest that the modified algorithm can provide more detailed partition of temperature zones compared with some existing methods.

Weighted Rendezvous Planning on Q-Learning Based Adaptive Zone Partition with PSO Based Optimal Path Selection

Nowadays, wireless sensor network (WSN) has emerged as the most developed research area. Different research have been demonstrated for reducing the sensor nodes’ energy consumption with mobile sink in WSN. But, such approaches were dependent on the path selected by the mobile sink since all sensed data should be gathered within the given time constraint. Therefore, in this article, the issue of an optimal path selection is solved when multiple mobile sinks are considered in WSN. In the initial stage, Q-learning based Adaptive Zone Partition method is applied to split the network into smaller zones. In each zone, the location and residual energy of nodes are transmitted to the mobile sinks through Mobile Anchor. Moreover, Weighted Rendezvous Planning is proposed to assign a weight to every node according to its hop distance. The collected data packets are transmitted to the mobile sink node within the given delay bound by means of a designated set of rendezvous points (RP). Then, an optimal path from RP to mobile sink is selected utilizing the particle swarm optimization algorithm which is applied during routing process. Experimental results demonstrated the effectiveness of the proposed approach where the network lifetime is increased by the reduction of energy consumption in multihop transmission.

Tectonic evolution of the hinterland of the Zagros Orogen revealed from the deformation of the Golpaygan Metamorphic Complex, Iran

In the southwestern part of the Central Iran zone, the Golpaygan Metamorphic Complex (GMC) was evolved during the Zagros orogeny. This complex is composed of different metamorphic rocks including schist, marble, slate, gneiss and amphibolite. The metamorphic complex is overlain by a cover sequence including Permian carbonates, Jurassic clastic rocks, Cretaceous carbonates and Eocene clastic rocks. The internal structure of the GMC is characterized by four deformational stages. The first stage (D1) developed contemporaneously with the prograde regional metamorphism and resulted in formation of the first generation folds and prevailing axial plane foliation. The second stage of deformation (D2) was accompanied by deformation partitioning and formation of contractional shear zones. These structures were overprinted by different scale folds of the third stage (D3). The fourth stage of deformation (D4) is characterized by generation of the extensional shear zones which gradually transformed into normal faults. D1 and accompanied metamorphism may have resulted from steep subduction of the Neotethys Ocean beneath the active margin of the Central Iran zone during Jurassic times. D2–D3 structures and retrograde metamorphism may have been formed by a regional shortening and transpression deformation event which resulted in exposure of the metamorphic rocks in shallower levels during Cretaceous flat slab subduction. This condition lasted until Paleocene time when the slab roll-back caused extension and thinning of the overriding Central Iran plate. The subsequent decompression and regional extension resulted in intrusion of magmatic rocks and generation of D4 which formed the GMC and related magmatism in Paleocene-Eocene time.

Predicting the Upcoming Services of Vacant Taxis near Fixed Locations Using Taxi Trajectories

Emerging on-line reservation services and special car services have greatly affected the development of the taxi industry. Surprisingly, taking a taxi is still a significant problem in many large cities. In this paper, we present an effective solution based on the Hidden Markov Model to predict the upcoming services of vacant taxis that appear at some fixed locations and at specific times. The model introduces a weighted confusion matrix and a modified Viterbi algorithm, combining the factors of time of day and traffic conditions. In our framework, the hotspot or hidden states extraction is implemented through kernel density estimation (KDE) and fuzzy partitioning of traffic zones is done via a Fuzzy C Means (FCM) algorithm. We implement the proposed model on a large-scale dataset of taxi trajectories in Beijing. In this use case, tests demonstrate the high accuracy of the modeling framework in predicting the upcoming services of vacant taxis. We further analyze the factors affecting the predictive accuracy via a prediction accuracy analysis and prediction location evaluation. The findings of this paper can provide intelligence for the improvement of taxi services, to increase the passenger capacity of taxis and also to improve the probability of passengers finding taxis.

Global optimisation model and algorithm for unit restarting sequence considering black‐start zone partitioning

Unit restarting after a blackout is the basis of the overall restoration process for a power system. A reasonable restarting sequence of units may speed up the restoration process and reduce economic loss. In view of the situation that there are usually several black-start sources in a large-scale power system, a global optimisation method for unit restarting considering black-start zone partitioning is proposed in this study. On the basis of the multiple time-step modelling framework, the optimisation problem is formulated as a mixed integer linear programming model, with the objective functions to maximise the total-weighted MWh output and minimise the links between the subsystems under various operational constraints. The hierarchical method based on generalised Benders decomposition is applied to decompose the optimisation problem into one master problem and two sub-problems: (i) determination of the unit restarting sequence considering only the grouping of units and (ii) rationality check of unit grouping and check of operational constraints based on power flow calculation. The master problem and sub-problems are alternately and iteratively solved until the optimal solution is obtained. The results of New England 10-unit 39-bus system and a practical power system in southwest China verify the validity of the proposed method.