Occurrence Point Research Articles

Evaluation of Fire and Evacuation Safety in School Dormitories

This study aims to prepare an optimal plan to secure evacuation safety in the event of a fire in a school dormitory. Accordingly, the available safe egress time (ASET) was calculated by applying human safety standards, such as an indoor temperature of 60 ℃, a visual distance of 5 m, CO at 1,400 ppm, O2 at 15% and CO2 at 5%. Additionally, in the event of a fire, the required safe egress time (RSET) was calculated by applying factors such as detection, alarm, recognition, interpretation, the evacuation start of the occupants, training status, and the alarm facilities. An analysis of the ASET and RSET showed that in the event of a fire, it is necessary to secure various evacuation routes, in addition to the usual access route, to evacuate quickly by bypassing the fire occurrence point. Moreover, it was found that the ASET varied at each point inside the building, owing to the influences of toxic gases, oxygen, heat, visibility, and smoke resulting from the fire. In addition, in the event of a fire, evacuating along a planned evacuation route designed to minimize confusion and bottlenecks among students was effective for evacuation safety. Finally, it was found that evacuation safety can be secured by designating evacuation routes that are suitable for use in situations in which the location of the fire is unknown.

Analysis of Landslide Susceptibility Using Frequency Ratio Methods in the Lisu Watershed, Barru Regency

Barru Regency is an area with a relatively high frequency of landslides according to BNPB data for 2015. This can be seen in several incidents from 2017 to 2021. The purpose of this research is to identify and determine the level of vulnerability of landslides that occur in an area by utilizing the method Frequency Ratio. The Lisu watershed study area is a research study because it is included in the largest local watershed in Barru Regency. This study uses landslide occurrence point data by including nine factors that cause landslides such as land cover, slope, slope aspect, elevation, rainfall, curvature, distance from river, distance from fault, and lithology. These nine factors are divided into five classes, namely very low, low, medium, high, and very high. The results of the analysis show that the AUC model success rate and prediction accuracy are 0.80 and 0.83. The very high vulnerability to landslides is spread over the Tanete Riaja and Pujananting Districts. This indicates that the frequency ratio method is appropriate as a basis for analyzing the level of landslide vulnerability in the Lisu watershed.

38ft급 HDPE 파워보트 구조해석을 통한 선급별 하중 기준에 대한 비교 고찰

According to the government policy of environmental regulations, interest of ship, which made with High-Density Polyethylene (HDPE) as a low-carbon and eco-friendly material, is growing as a substitute for the existing fishery boat hull materials such as FRP, aluminum, steel etc. However, regulations related to the production of HDPE ship are still quite incomplete. Even there are no regulations related to structural analysis. Therefore, in this study, structural analysis is carried out by applying different design loads for each international classification for 38ft class HDPE power boats, and the results are compared and analyzed. According to this study, although there is a correlation between the based pressure value and the analysis result value of each class regulation, it is not necessarily proportional. Also, This analysis result shows a difference not only depending on the size of design load, but also application range of the load, the pressure adjustment factor and section shape. However, the occurrence point and trend of the maximum stress values were quite consistent. It is hoped that the results of this study will be used when establishing HDPE ship structure analysis procedures and standards in the future.

Spatial dynamic simulation of important cash crops based on phenology with Scutellaria baicalensis Georgi as an example

Substantial differences in the niche and quality of plants, especially in cash crops, are clearly observed in different phenological phases. Many plants have distinct phenological characteristics, yet the distribution patterns and secondary metabolites in plants at different growth stages are poorly understood. We examined the importance of environmental variables in phenological phases for plant niches and quality using 30 years of species spatial occurrence point data combined with phenological data and other environmental factors. First, we developed niche models for Scutellaria baicalensis Georgi to estimate the distributions of habitat suitability and spatial dynamics for five developmental stages. Our results suggested that some populations were lost when environmental factors in specific phenological stages were involved in modeling and that these environmental variables contributed more than 30 % of the total to species distribution modeling. The results of independent phenological niche modeling illustrated the spatial variation dynamics of S. baicalensis, and 22.88 % of the potential distribution areas were consistent among the five phenological periods. Additionally, we considered the impact of environmental variables in five growth stages on quality. Six environmental variables (maximum temperature during the flowering period, maximum temperature during the blooming period, maximum temperature during the fruiting period, phenological precipitation during the fruiting period, precipitation standard deviation during the fruiting period, and phenological precipitation during the withering period) played pivotal roles in the formation of secondary metabolites and affected the spatial distribution of plant quality. Our study demonstrates the importance of phenological phases and highlights that they should be considered if plants have distinct phenological signatures. In regard to cultivation and management, our results provide decision-makers with an integrative approach for planning the rational allocation of resources used to obtain medicinal plants.

Development of An Automatic Calculation Algorithm for Rainfall Thresholds of Debris Flow in Korea

Climate change has increased the amount and intensity of rainfall, increasing debris flow risk. Debris flow damage has become a social issue in Korea, and the need for research related to rainfall thresholds for debris flow has increased. In this study, an automatic calculation algorithm was developed to derive criteria suitable for the Korean region for the rainfall thresholds of debris flow. The study area selected was Gangwon-do, where a significant amount of debris flow occurred recently, and information on rainfall and the occurrence of debris flow were collected. As a result of applying an algorithm based on the R programming language, an equation for the relationship between the rainfall intensity and duration in Gangwon-do was automatically derived using debris flow occurrence point information and meteorological rainfall information.

Prediction of Critical Heat Flux for Subcooled Flow Boiling in Annulus and Transient Surface Temperature Change at CHF

The ability to predict critical heat flux (CHF) is of considerable interest for high-heat equipment, including nuclear reactors. CHF prediction from a mechanistic model for subcooled flow boiling in rod bundles still remains unsolved. In this paper, we try to predict the CHF in an annulus, which is the most basic flow geometry simplified from a fuel bundle, using a liquid sublayer dryout model. The prediction is validated with both water and R113 data, showing an accuracy within ±30%. After the CHF in an annulus is calculated successfully, a near-wall vapor–liquid structure is proposed on the basis of the liquid sublayer dryout model. Modeling of heat transfer modes over the heating surface at CHF is performed, and predictions of the changes in liquid sublayer thickness and heater surface temperature at the CHF occurrence point are carried out by solving the heat conduction equation in cylindrical coordinates with a convective boundary condition, which changes with the change in flow pattern over the heating surface. Transient changes in the liquid sublayer thickness and surface temperature at the CHF occurrence point are reported.

Predicting the Geographical Distribution of Malaria-Associated Anopheles dirus in the South-East Asia and Western Pacific Regions Under Climate Change Scenarios

Malaria occurrence is highly related to the geographical distribution of Anopheles dirus (An. dirus) in the South-East Asia Region and Western Pacific Region (SEAR/WPR). Future climate change has been shown to alter the geographical distribution of malaria vectors. However, few studies have investigated the impact of climate change on the potential distribution of An. dirus in the SEAR/WPR. We considered future climate and land-use data under two climate change scenarios for Representative Concentration Pathways (RCP 4.5 and RCP 8.5) and population data from five Shared Socioeconomic Pathways (SSPs), by using three machine learning models, namely, Random Forest (RF), Boosted Regression Trees (BRT), and Maximum entropy (Maxent) to project the geographical distribution of An. Dirus and to estimate the exposed population. A pseudo-absence dataset was generated based on the relationships between model performance and the distance from the pseudo-absence point to the occurrence point in order to improve model accuracy for projection of the Environmentally Suitable Area (ESA) and exposed human population. The results show that the pseudo-absence data corresponding to the distance of 250 km are appropriate for modeling. The RF method ultimately proved to have the highest accuracy. The predicted ESA of An. dirus would mainly be distributed across Myanmar, Thailand, the southern and eastern part of India, Vietnam, the northern part of Cambodia, and the southern part of Laos. The future ESA is estimated to be reduced under the RCP 4.5 climate change scenario. In the 2070s under RCP 8.5, the reduction of ESA is even greater, especially in Thailand (loss of 35.49 10,000 square kilometers), Myanmar (26.24), Vietnam (17.52), and India (15), which may prevent around 282.6 million people from the risk of malaria under the SSP3 scenarios in the SEAR/WPR. Our predicted areas and potential impact groups for An. dirus under future climate change may provide new insights into regional malaria transmission mechanisms and deployment of malaria control measures based on local conditions in the SEAR/WPR’s.

Lightning Performance of Unshielded 220 kV Transmission Lines Equipped With Metal Oxide Arresters

Overhead ground wires installed on transmission lines have been proved to be effective to protect conductors from direct lightning strokes, but ground wire breakouts due to icing are frequently reported. In order to prevent electric failure accidents caused by ground wire breakouts under icing conditions, unshielded transmission lines equipped with metal oxide arresters (MOAs) whole line have been proposed in high mountainous areas. Compared with ordinary transmission lines, lightning stroke risk of unshielded lines is much higher. In order to improve the lightning performance of unshielded lines, it is necessary to obtain the essential lightning energy absorption ability of the MOAs installed on unshielded lines. In this article, simulation model of unshielded 220 kV transmission lines equipped with MOAs is built, the influences of lightning parameters, striking occurrence point and grounding resistance on the absorbed energy of MOAs are analyzed. Based on Monte Carlo method, lightning trip-out rate of unshielded transmission lines are calculated, and suggested energy absorption ability of MOAs is proposed, which can give references for the improvement of power supply reliability of transmission lines.

Displacement Mapping of Point Clouds for Retaining Structure Considering Shape of Sheet Pile and Soil Fall Effects during Excavation

An entire large-scale retaining structure can be monitored by simulating a three-dimensional point cloud obtained by laser scanning. The behavior of a retaining structure composed of sheet piles according to excavation was analyzed by the displacement mapping method in this paper. The displacement errors can be generated due to inclined sections, U-shaped protrusions of sheet piles and cutting point clouds, and the fall and deposition of soil adhering to the sheet pile. Therefore, the analysis error was minimized by pretreatment of the point cloud considering the shape of the sheet pile before displacement mapping. For displacement mapping, the cloud to mesh (C2M) distance was calculated by segmenting the point cloud of the retaining structure into 5 rows and 20 columns, which have about 100 elements. Analysis of seven monitoring results from Day 0 to Day 35 was performed, and the maximum displacement occurrence point and the expansion of displacement with time were evaluated by displacement mapping. In an in-depth analysis after displacement mapping, it was possible to estimate the displacement variation in the vertical direction of a pile in which the excessive displacement occurred as well as the change pattern of the displacement in the horizontal direction of the entire pile head. A crack found at the top of a sheet pile occurred due to excessive displacement, which was verified by visual inspection.

Intelligent Anomaly Identification of Uplift Pressure Monitoring Data and Structural Diagnosis of Concrete Dam

As an essential load of the concrete dam, the abnormal change of uplift pressure directly threatens the safety and stability of the concrete dam. Therefore, it is of great significance to accurately and efficiently excavate the hidden information of the uplift pressure monitoring data to clarify the safety state of the concrete dam. Therefore, in this paper, density-based spatial clustering of applications with noise (DBSCAN) method is used to intelligently identify the abnormal occurrence point and abnormal stable stage in the monitoring data. Then, an application method of measured uplift pressure is put forward to accurately reflect the spatial distribution and abnormal position of uplift pressure in the dam foundation. It is easy to calculate and connect with the finite element method through self-written software. Finally, the measured uplift pressure is applied to the finite element model of the concrete dam. By comparing the structural behavior of the concrete dam under the design and measured uplift pressure, the influence of abnormal uplift pressure on the safety state of the concrete dam is clarified, which can guide the project operation. Taking a 98.5 m concrete arch dam in western China as an example, the above analysis ideas and calculation methods have been verified. The abnormal identification method and uplift pressure applying method can provide ideas and tools for the structural diagnosis of a concrete dam.

Mapping distribution and identifying gaps in protected area coverage of vulnerable clouded leopard (Neofelis nebulosa) in Nepal: Implications for conservation management

Clouded leopard (Neofelis nebulosa) is listed as vulnerable by the IUCN red list and is a protected species in Nepal. However, there is limited information on its status and distribution, which is a critical first step in conservation planning and management. To address this knowledge gap, this study attempts to: (a) predict the potential suitable habitat for the clouded leopard in Nepal with available occurrence point, (b) determine important variables (bioclimatic and environmental) responsible for its distribution and range limits, and (c) evaluate coverage of existing protected areas (PAs) in Nepal using MaxEnt modeling. The current model with a high discriminative ability (AUC = 0.945, TSS = 0.780) predicts 11,794 km2 suitable habitat for clouded leopard in Nepal, of which 72% of the area is distributed outside the current protected areas network of Nepal. Most of these habitats lie in the Middle mountain and Hilly regions, distributed from the Pachthar Ilam Taplejung corridor in the east to Annapurna Conservation Area in the mid-central part of Nepal. The most important variables responsible for its distribution were the mean Normalized Difference Vegetation Index (NDVI), Isothermality, and the precipitation of the coldest quarter associated with the forest cover landscape and climate. Deforestation and fragmentation of habitat and climate change in the Middle mountain and Hilly region, and occasional poaching are significant concerns, and may pose threats for the long-term conservation of this species. We recommend establishing community-based conservation areas in the Middle mountain and Hilly regions and investigating species distribution, status, and ecology, including its prey and habitat, across the Nepalese landscape. Identification of habitats and conservation opportunities is crucial for species' long-term conservation. Hence, the map produced here can serve as a reference for future investigations into clouded leopard distribution and could be a significant tool for formulating and implementing conservation strategies in Nepal.

Data Analysis of the Risks of Type 2 Diabetes Mellitus Complications before Death Using a Data-Driven Modelling Approach: Methodologies and Challenges in Prolonged Diseases

(1) Background: A disease prediction model derived from real-world data is an important tool for managing type 2 diabetes mellitus (T2D). However, an appropriate prediction model for the Asian T2D population has not yet been developed. Hence, this study described construction details of the T2D Holistic Care model via estimating the probability of diabetes-related complications and the time-to-occurrence from a population-based database. (2) Methods: The model was based on the database of a Taiwan pay-for-performance reimbursement scheme for T2D between November 2002 and July 2017. A nonhomogeneous Markov model was applied to simulate multistate (7 main complications and death) transition probability after considering the sequential and repeated difficulties. (3) Results: The Markov model was constructed based on clinical care information from 163,452 patients with T2D, with a mean follow-up time of 5.5 years. After simulating a cohort of 100,000 hypothetical patients over a 10-year time horizon based on selected patient characteristics at baseline, a good predicted complication and mortality rates with a small range of absolute error (0.3–3.2%) were validated in the original cohort. Better and optimal predictabilities were further confirmed compared to the UKPDS Outcomes model and applied the model to other Asian populations, respectively. (4) Contribution: The study provides well-elucidated evidence to apply real-world data to the estimation of the occurrence and time point of major diabetes-related complications over a patient’s lifetime. Further applications in health decision science are encouraged.

Rolling bearing fault feature extraction using non-convex periodic group sparse method

The detection and evaluation of early faults is currently an important issue in the condition assessment of machinery and has been a challenging problem. In this paper, a novel index and a periodic enhancement group sparse (PEGS) model are sequentially proposed for early fault feature extraction of rolling bearings. Firstly, an index is defined based on the energy operator Gini index to determine the early fault occurrence from the whole-lifecycle vibration signal of the rolling bearing. Second, PEGS is proposed by appendinga period estimating approach and a novel non-convex penalty to the non-convexgroup sparse optimization. It can promote the sparsity of fault signals and itsability to extract fault features. Moreover, the adaptive selection strategy for regularization parameter and group size is discussed. Simulations and two real experimental cases verify that the proposed method can determine the early fault occurrence point and extract the fault features more accurately than other comparison methods.

Lateral Deflection Behavior of Perforated Steel Plates: Experimental and Numerical Approaches

This study aimed to investigate the behavioral characteristics of the lateral deflection of a simply supported perforated steel plate subjected to axial compression. Investigating the lateral deflection of the perforated plate is of great significance because the buckling limit of structural members can be predicted not only by strength but also by displacement (or deflection). For this purpose, we conducted buckling experiments by considering various variables of the perforated plate, such as opening size, thickness, and aspect ratio. In addition, a series of elastoplastic large deflection analyses were performed using the commercial finite element analysis program, and the calculated results were compared along with the experimental results. Finally, practical curves, which can predict lateral deflection with an increase in axial displacement, and the occurrence point of ultimate strength are reported in this study. The results showed that there was a distinct difference in the behavior of lateral deflection between perforated plates with different opening ratios. The local buckling occurred mainly around the opening and was more dominant with an increase in the opening ratio. In addition, the ultimate strength of the perforated plate was determined at the end of the local buckling phase.

Multi-parameter tunable terahertz absorber based on graphene and vanadium dioxide

This article is based on graphene and vanadium dioxide (VO2) to build a THz metamaterial absorber that can be exchanged in three modes: single-band, dual-band, and broadband. The change of the frequency band can be accomplished by changing the Fermi level of graphene and the state of VO2. When VO2 is in a metallike state, diverse single-band absorbers can be gotten, and after that, a dual-band absorber can be gotten by controlling the movement of VO2 from a metallike state to an insulation state. When VO2 is in a metallic state, the mutual coupling between graphene and VO2 expands the absorption bandwidth and realizes broadband absorption. Also, the broadband collector is not insensitive to the polarization point and occurrence point of TE polarization and TM polarization. Compared with the existing absorber, the absorber based on graphene and VO2 we outlined not only has a higher bandwidth but for most critically, can accomplish higher integration, compatibility, and a more adaptable adjustable range.

Bifurcation Characteristics of Airfoil-NESs coupled System

Aeroelastic instability has become a hot research topic. It has increasingly high-lighted its importance in the aircraft and fluid machinery industry and brings challenges to the safe flight of various aircraft and the safe operation of fluid machinery. Numerical simulations were performed to study the flow-induced oscillation of a two-dimensional airfoil with two non-linear energy sinks (NES). The main system has two degrees of freedom-pitch and heave. These two NESs are considered as subsystems, with the first NES at the leading edge and the second NES at the trailing edge. The bifurcation behaviour and the mechanism of the system leading to chaos of the coupled system under different parameters and initial conditions is studied by nonlinear analysis, and the relationship between large amplitude limit cycle oscillation and the chaotic occurrence point of the main system is revealed, this corresponding relationship has important theoretical significance for mastering and adjusting system parameters to make NES work within its ideal oscillation suppression parameters.

Study on the Optimal Number and Position of Drones in Fire Prevention in Victoria

During the 2019-2020 fire season, every state in Australia had devastating fires, with the worst impact on eastern Victoria. In order to help Victoria’s Country Fire Authority (CFA) to monitor and rescue the fire in time, we set up an optimized model of the number of drones combinations, which saves the national cost while monitoring the fire occurrence. We first carry on the K-means cluster analysis to the fire dense points according to the fire occurrence situation in Victoria, Australia, which obtains the possible fire area. Then, we calculate the emergency factor to judge the fire grade, according to the area fire occurrence frequency and the fire intensity. By using the improved ant colony algorithm, we find the shortest path through each fire occurrence point. Therefore, the multi-objective optimization model is established with the minimum total cost and the highest safety factor as the optimization target. And we make the signal propagation distance SSA drones, Radio Repeater drones and fireman under different terrain as the constraint conditions. Through the model, we calculate that the Victoria’s Country Fire Authority (CFA) needs 23 SSA drones and 20 Radio Repeater drones, as well as the location of the relays and the combination of DRONESs in different positions. The occurrence of fire is related to climate and season. Through the data of Victorian fire in the past 20 years, we use ARIMA time series to predict the severity and frequency of fire in different areas over the next decade. Then, we determine the annual monitoring range of each area to estimate the probability of fire. In the case of extreme fire events, we update the scale and frequency of volcanic occurrence, using the model of question one, find the optimal number of drones combinations, calculate the increase in equipment costs, and finally get the need to increase the equipment cost price of $500000(AUD). Considering the different terrain conditions in Victoria, we introduce the altitude correction coefficient to obtain the influence of altitude on radio signal propagation, combing the change of altitude. Then, the influence of terrain on the signal propagation of hovering radio-repeater drones is obtained, and the signal propagation distance under different terrain problem one is changed. The position of the optimized relay is obtained. Finally, we get the number of radio-repeater drones increases to 25. Finally, we examine the sensitivity and stability of the model and prove that our model is accurate and stable for the problems.

Lightning Performance of Unshielded 220kV Transmission Lines Equipped with Metal-oxide Arresters

Overhead ground wires have been proved to be effective to protect conductors from direct lightning strikes, but breakouts of ground wires have been frequently reported. In order to prevent ground wire breakout incidents to happen, unshielded 220kV lines equipped with metal oxide arresters (MOAs) whole line have been proposed in this paper. After cancelling ground wire, lightning strike risk of transmission lines becomes much higher. In order to improve the anti-lightning abilities of unshielded transmission lines, it is necessary to obtain the lightning energy absorption ability of these MOAs. In this paper, simulation model of MOA equipped unshielded 220kV transmission line was built, the influences of lightning parameters, striking occurrence point and grounding resistance of transmission tower on the absorbed energy of MOAs were calculated, and the suggested energy absorption ability of MOA was given, which can give references for the improvement of power supply reliability of transmission lines.

Susceptibility Analysis of the Mt. Umyeon Landslide Area Using a Physical Slope Model and Probabilistic Method

Every year, many countries carry out landslide susceptibility analyses to establish and manage countermeasures and reduce the damage caused by landslides. Because increases in the areas of landslides lead to new landslides, there is a growing need for landslide prediction to reduce such damage. Among the various methods for landslide susceptibility analysis, statistical methods require information about the landslide occurrence point. Meanwhile, analysis based on physical slope models can estimate stability by considering the slope characteristics, which can be applied based on information about the locations of landslides. Therefore, in this study, a probabilistic method based on a physical slope model was developed to analyze landslide susceptibility. To this end, an infinite slope model was used as the physical slope model, and Monte Carlo simulation was applied based on landslide inventory including landslide locations, elevation, slope gradient, specific catchment area (SCA), soil thickness, unit weight, cohesion, friction angle, hydraulic conductivity, and rainfall intensity; deterministic analysis was also performed for the comparison. The Mt. Umyeon area, a representative case for urban landslides in South Korea where large scale human damage occurred in 2011, was selected for a case study. The landslide prediction rate and receiver operating characteristic (ROC) curve were used to estimate the prediction accuracy so that we could compare our approach to the deterministic analysis. The landslide prediction rate of the deterministic analysis was 81.55%; in the case of the Monte Carlo simulation, when the failure probabilities were set to 1%, 5%, and 10%, the landslide prediction rates were 95.15%, 91.26%, and 90.29%, respectively, which were higher than the rate of the deterministic analysis. Finally, according to the area under the curve of the ROC curve, the prediction accuracy of the probabilistic model was 73.32%, likely due to the variability and uncertainty in the input variables.

Validating management strategies for invasive species from a spatial perspective: Common ragweed in the Republic of Korea

Owing to their potentially wide-ranging adverse effects, invasive species are a growing global problem. The common ragweed (Ambrosia artemisiifolia var. elatior (L.) Desc) is one of the most important invasive plants, necessitating management because of its tendency to “spread.” Various studies and management strategies are being conducted based on the concept of “density” because of the increasing importance of the spatial perspective in this application. Although eradicating from the outliers (low-density regions) has a high efficiency, there is a lack of validation methodology for deriving both spatial and statistical results. We formed a general validation methodology by assessing various removal scenarios based on two removal strategies, namely Outside-in and Inside-out. These approaches exhibited several removal rates, and take into account the spatial perspective by considering species density. The Outside-in strategy entails the removal of species, which commences from the low-density regions, whereas the Inside-out removal initiates from the high-density regions. To classify the spatial regions for priority removal using each strategy, we defined the density level and then processed the removal of the occurrence points for each strategy to derive generalized results. We used the species distribution model MaxEnt to determine the predicted distribution of the target species for each removal strategy applied; subsequently, the final randomly generalized occurrence point results were used as model input data. Assessment analyses were conducted based on the final probability distribution and appearance level for each scenario, which included a newly proposed index was termed the “removal effect index.” Results indicated that the efficacy of the Outside-in removal strategy exceeded that of the Inside-out strategy for all assessment analyses, with the removal effect index showing a difference of about 2–5 times between strategies in each removal rate. In addition, through numerical analysis of the changed area of each scenario, the Outside-in strategy showed a successful removal effect in the “removal management priority spatial range,” whereas the Inside-out strategy showed limitations. We confirmed the efficacy of the Outside-in strategy as an optimal removal approach that takes into account spatial information of the priority spatial range for eradication in terms of the removal effect.