Source Of Hazard Research Articles

An optimization method of multiscale storage tank target detection introducing an attention mechanism

Under the combined action of the expansion of the chemical industry zone and urban boundaries, urban areas exposed to danger are also increasing. As containers for chemical storage, storage tanks are potential sources of hazards. Conducting target detection for hazard risk analysis is essential. YOLOv5, a single-stage algorithm with good performance, accurately identifies most storage tanks with clear contours and evident positions; however, the identification effect is not good for storage tanks with small targets or unclear boundaries. This study proposes an optimized model based on the YOLOv5 model. First, the Coordinate Attention (CA) mechanism is introduced to make the model focus on the effective information of the target. Second, to improve the detection effect of small targets, the model adds a small target detection head and performs multiscale target detection. Finally, the EIOU loss function is employed instead of the CIOU loss function in the original model to improve the algorithm’s accuracy and speed. Experimental results show that the optimized model significantly improves the detection effect on small targets compared with the original YOLOv5 model. The number of small targets detected by the optimized model is significantly increased compared with the original model, and the size of the smallest targets detected by the optimized model is reduced by about twice compared with the original model. The model’s accuracy, recall rate, and mean average precision (mAP@0.5) are improved, which can be better applied to the detection of storage tanks.

A Study on the Impact of IoT Technology on the Operation Management of the Wastewater Management Sector

The research aims to analyze the impact of the Internet of Things (IoT) technology on the operation of the wastewater management (WWM) sector. The study results show that IoT technology could enhance operational process innovation in WWM. It is mainly reflected in wastewater pipeline network management, water quality monitoring, risk monitoring, and equipment maintenance. Through field data collection, transmission, fault detection, and decision-making support, it replaces the conventional manual operation, simplifies the workflow, and improves efficiency. In addition, IoT technology not only improves operation quality, and dependability, and reduces costs, but also improves the environment and water hygiene from the social level. In terms of risk management, IoT technology improves the accuracy and timeliness in hazardous sources monitoring, handling, and potential hazards prediction, to improve the risk management capability. Finally, IoT technology can enhance “demand” management by WWM authorities and provide accurate decision support for base capacity setting, also can solve the constraints of WWM system capacity to improve supply capacity.

Study and calculation of the specific natural radioactivity of samples of Portland cement in Iraq using a high-purity germanium detector

In the current work, we used a high-purity germanium (HPGe) detector to assess particular activity concentrations in Seventeen cement samples from various origins. The results have shown that the specific activity, for 226Ra, ranged from 10.6±0.7Bq/kg) in Sample No. 11 to(59.1±2.4Bq/kg)in Sample No 12, for 228Ac ranged from (6.6±1Bq/kg) in Sample No.9 to(10.5±1Bq/kg) in Sample NO.7, for 40K was ranged from (81.4±7.6Bq/kg) in Sample NO.12 to (209.5±14.1Bq/kg) in Sample No.7. The research demonstrates that the cement samples are safe to use in the construction of homes and do not offer any substantial sources of radiation hazard.

Evaluating the effect of urban flooding on spatial accessibility to emergency shelters based on social sensing data

AbstractUrban flooding is a growing source of natural hazards, significantly threatening the safety of sustainable development in cities. The distribution of flood risks is heterogeneous, so it is crucial to allocate emergency resources reasonably. This article develops an analytical framework to evaluate the effect of urban flooding on emergency responses based on social sensing data. Initially, we designed a Weibo search pattern and used natural language processing technologies to get high‐risk flood points. Then, assuming that such high‐risk flood points can disrupt traffic, we assessed urban emergency shelter accessibility after flooding events. Finally, we carried out an evaluation of spatial fairness between population and emergency shelter accessibility through spatial correlation analysis. We analyzed the urban area of Nanjing as a case study, extracting 37 high‐risk flood points from the past 5 years. The results highlight that existing emergency shelters fall short in accommodating the needs of urban residents under disaster conditions. This disparity is notably amplified in high‐risk flood points. By measuring the impact of flooding quantitatively, we expect to promote a more comprehensive management on urban flood risks.

Reuse of Tunisian excavated material into composite soil for rainwater infiltration within urban green infrastructure

Excavated material or soil is one of the most abundant types of waste produced by civil works. The study draws a methodology for assessing through selected standard tests the environmental, geotechnical, and agronomical features of excavated material to highlight the most ecological way to reuse it. In view of making a constructed soil to be implemented within green infrastructure part of new urban landscape, imperative skills of soil or material are referred to as SWOFI: safety, workability, fertility, infiltrability, and guidelines are derived accordingly. As a practical case of the application of the methodology, a non-cohesive sedimentary parent rock with a sandy loam texture excavated at Bou Argoub in Tunisia has been characterised. This excavated material is a negligible source of pollution hazard by heavy metals. It classifies in a category very sensitive to compaction and strongly influenced by the clay content, so difficult to reuse in road applications. It is very poor in organic matter and too much alkaline, so grape marc waste is used to improve its fertility, thus making a composite soil that prefigures a constructed soil. This allows the valorisation of local agriculture waste throughout the designed strategy.Novelty resides in the selection of tests and the association of technics issued from usually separated disciplines and the integrated workflow of the soil at three stages of the value-chain: excavated-homogenised, amended, then repacked at a given bulk density as a composite soil. Immediate compactibility changes as a linear function of repacked bulk density BD; from the literature, this result is assumed true in the composite soil as well as the excavated material. Based on required intervals of permeability for the projected use in green infrastructure requiring rainwater infiltration, a decision-making table is applied with, as input, the most probable value of permeability determined from pedotransfer function as topsoil or as subsoil. Combining pollution hazard assessment, geotechnical improvement, agronomical amendment, an innovative approach leads to pedological and hydrological functionality for constructed soil, a nature-based solution.

Fuzzy Support Vector Machine Based Outlier Detection for Financial Credit Score Prediction System

Economic Credit Scoring (CS), which aids in calculating the credit worth of both individuals and companies, is regarded as one of the greatest study issues in the finance field. In the banking industry, data mining techniques are believed to be helpful since they help designers and developers create appropriate goods or services for customers with the fewest possible risks. Losses and loan cancellations, which are the major sources of hazards in the banking industry, are related to credit risks. A Support Vector Machine based architecture is presented in the current study for the financial credit score prediction system. However, the existing work tends to have increased computational overhead and that requires complete data for attaining required accurate rate. The system known as the Fuzzy Support Vector Machine based Outlier Detection System is introduced in the suggested research study to address this (FSVM-ODS). This study's first grouping of data items utilising a hybrid genetic algorithm with K-Means clustering algorithm is named (HKGA). The dataset must be gradually lowered in size, and calculation time must likewise be decreased. The Enhanced Z-score (EZS) outlier identification (OD) technique was employed in the second step to identify outliers in the dataset. Then, we use a customized beaver searching method to choose the database. For categorization of the datasets, a fuzzy support vector machine is utilised. The whole study project is carried out in the Matlab simulation environment, and it has been shown that the suggested technique achieves a higher outlier identification rate than the current methodology.

Assessment of natural radioactivity levels and potential radiological risks of commonly used building materials in Uttara Kannada District, Karnataka, India.

The main goal of this study is to evaluate the natural radioactivity and potential radiological risks of frequently used building materials in Uttara Kannada district. Using an High purity Germanium Detector (HPGe) detector-based gamma-ray spectrometer, the activity concentration of 226Ra, 232Th and 40K was determined. The activity concentration of 226Ra, 232Th and 40K in the construction materials vary from 13.78±0.90 to 151.9±1.85, 14.21±0.80 to 207.72±2.9 and 55.26±1.20 to 1298.24±25Bqkg-1 with an average value of 40.57±1.37,60.13±1.70 and 425.38±4.75Bqkg-1 having a geometric mean of 33.07, 46.49 and 290.20Bqkg-1, respectively. The mean annual effective dose equivalent was found to be 0.68mSv y-1 and is less than the International Commission on Radiological Protection proposed acceptable limit of 1mSv y-1. The estimated radiological hazard parameters show that these building materials are safe to use in the construction of homes and do not offer a substantial source of radiation hazard.

Analisis Pengendalian Risiko Keselamatan dan Kesehatan Kerja (K3) dengan Metode Failure Mode and Effect Analysis (FMEA) pada PT. ABC

PT. ABC is engaged in metal casting such as drinking water pipe connections and quality drainage components. Existing manufacturing processes involve direct interaction of workers with equipment in production situations that have sufficiently high safety risks. The research aims to identify the type or source of hazard, determine the value of high risk, and appropriate risk control measures. Using the Failure Mode and Effect Analysis (FMEA) method to identify failures from facilities, systems or equipment that have an impact on work accidents. The results of the study found 48 hazards with identifying the risk of work accidents with categories are very low (7), low (48), medium (17), high (10) and there is no risk of work accidents with very high categories. Work accidents that have a high risk in the metal casting process at PT. ABC is at the die-making, smelting and pouring, roughing, and finishing work stations. Potential risks to work safety include dust from mixing, being crushed by solid iron, exposed to sparks, exposed to molten liquids, electrocuted, and exposed to odors from paint. Risk control measures are proposed in the metal casting process at PT. ABC is carried out with engineering control and the use of PPE according to the source of danger.

Numerical parametric analysis of the decomposition and propagation of combustion products in a confined environment in the early stages of a fire

Numerical research findings are presented on the patterns of spread of thermal decomposition products of wood-based materials in confined spaces isolated from the external environment. Based on the experimental data, a physical problem statement was formulated and a mathematical model of heat and mass transfer was developed for rooms with the most typical sources of fire hazard. The experimental and numerical research findings were obtained for the conditions corresponding to compartments isolated from the external environment (e.g., rooms at dedicated facilities, like ships, small and medium-sized rooms) and to underventilated rooms. The performed experiments and calculations revealed satisfactory agreement in the findings and demonstrated the validity of the proposed model of heat and mass transfer. Wood was used as the main material in fires. A comparative analysis was also carried out for paper of different quality. The modeling was performed for the most frequent causes of fires: careless handling of fire, unsafe operation of heating equipment and electrical short circuits. The rates of growth of thermal decomposition product concentrations were determined for different distances from the material. The impact of a number of factors on the characteristics under study was determined. These are the fire and room sizes, fire cause, supply and exhaust ventilation. The data were extrapolated to the conditions corresponding to business, warehouse and residential premises.

Laboratory Risk Assessment Based on SHELL-HACCP-Cloud Model

With the increasing demand and expanding scale of laboratories in colleges and universities, laboratory accidents frequently occur, seriously impacting personal health, schools, society, and the environment. Scientific and effective risk assessment is crucial to prevent accidents. Therefore, in order to effectively reduce the risk of chemical laboratories and minimize the frequency of accidents. This study employs the combination of the SHELL model and HACCP system to analyze the potential sources of hazards in hazardous chemical laboratories and establish a risk assessment index system. Based on the Cloud model, a dynamic risk assessment model for the laboratory is established to quantitatively evaluate the risk level of the evaluation results. In order to ensure the rationality of the assessment results, the subjective and objective weights are combined by the principle of minimizing information entropy. Case analysis proves the scientific validity of the evaluation results of the model, which can assist laboratory managers in formulating emergency plans and risk management mechanisms to reduce or eliminate the occurrence of experimental accidents. This approach ensures the safe and sustainable development of schools and laboratories, which is conducive to the progress of researchers’ scientific research results.

Flammable gas leakage risk assessment for methanol to hydrogen refueling stations and liquid hydrogen refueling stations

Due to its excellent combustion properties and environmental performance, the development of hydrogen energy has become an international trend in recent years. However, hydrogen refueling stations, which are the infrastructure for hydrogen energy development, contain flammable gases such as hydrogen and methanol, which are highly susceptible to explosion and may threaten people's health and property safety. In this paper, a dynamic risk assessment method based on Dynamic Bayesian Network (DBN) is established for combustible gas leakage accidents in hydrogen refueling stations, and the methanol to hydrogen refueling stations and liquid hydrogen refueling stations are taken as research objects to quantitatively analyze their leakage risks and accident consequences. It is found that the leakage accident probability and consequences of methanol to hydrogen refueling stations show periodicity with a period of three months, while there is no periodicity for liquid hydrogen refueling stations. The probabilities of leakage accident and serious consequences in methanol to hydrogen refueling stations show a sudden increase within a cycle, on the other hand, those in liquid hydrogen refueling stations tend to increase linearly over three years with time. In addition, based on the diagnostic reasoning function of DBN, this paper identifies the two most critical hazard sources for flammable gas leakage accident in hydrogen refueling stations: human factors and corrosion factors, and provides guidance for relevant enterprises to reduce the risk.

An extended social force model on unidirectional flow considering psychological and behavioral impacts of hazard source

An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks. Hazard sources not only physically but psychologically affect the pedestrians, which may further alter their behavioral patterns. This effect is especially significant in narrow spaces, such as corridors and alleys. This study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation, and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard source. The integration include a virtual repulsion force from the hazard source and a decay on the social force term. The simulations reveal (i) that the hazard source creates virtual bottlenecks that suppress the flow, (ii) that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities, and (iii) that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios, possibly with lateral collisions passing the hazard source.

Analysis of OSH risk level in forest management activities using remote sensing approach in RPH Takokak, KPH Sukabumi, West Java Province

Indonesian forests are known to have high diversity and play an important role in human life, so they need to be managed sustainably. Sustainable forest management does not only pay attention to productivity aspects but also demands protection of Occupational Safety and Health (OSH). Remote sensing is used to provide information about hazard sources using geospatial data to analyze the level of risk of OSH interference in forest management activities at RPH Takokak, KPH Sukabumi. There are six hazard sources as parameters, namely slope, elevation, rainfall, type of soil, vegetation density, and accessibility, as well as the history of work accidents which are addressed to forest management stakeholders through the questionnaire method. From the five classification classes, it was found that the study location was dominated by class 3 classification or had a moderate level of risk of OSH interferences with an area of 1.661,02 ha or 77.36%, and an area of 0.49 ha or 0.02% included in risk class 4 or had a high level of risk of OSH interferences. The results and recommendations of this study are expected to provide information to Perum Perhutani in managing forest areas, especially risk management and can become a reference for further research.

Assessment of safety risk in airline operations based on constant-sum game

Safety is the key to airline operations. The premise for ensuring safety is valid classification and scientific assessment of hazardous sources. The airlines, however, are deficient in an overall mastery and effective analysis of the hazardous sources currently. Here, we propose a model for a safety risk assessment in airline operations based on constant-sum games, with a comprehensive analysis of hazardous sources identified by airlines. The subjective and objective weights of the hazardous source indicators are balanced depending on the optimal coefficients, which are determined by deriving the countermeasure model through the constant-sum game theory. The comparative analysis of safety risks and weaknesses in management for airlines or secondary departments is then conducted. Meanwhile, a long-term reward mechanism is introduced into the model to eliminate the negative effect of a sudden increase in safety risk indices caused by the newly added hazardous sources. This method provides airlines with an accurate assessment of the safety status and an estimation of safety development which trends to make targeted decisions and realize prevention beforehand.

Experimental research on the removal characteristics of simulated radioactive aerosols by a cloud-type radioactive aerosol elimination system

Abstract Radioactive aerosols in the confined workplace are a major source of internal exposure hazards for workers. Cloud-type radioactive aerosol elimination system (CRAES) have great potential for radioactive aerosol capture due to their high adsorption capacity, lack of cartridges and less secondary contamination. A CRAES was designed and constructed, and a FeOOH/rGO composite was directly prepared by a hydro-thermal method to characterise and analyse its morphology, chemical structure and removal efficiency for simulated radioactive aerosols. The results show that the FeOOH/rGO composite works in synergy with the CRAES to effectively improve the removal efficiency of simulated radioactive aerosols. A 30-minute simulated radioactive aerosol removal rate of 94.52% was achieved when using the experimentally optimized composite inhibitor amount of 2 mg/L FeOOH/rGO with 0.2 g/L PVA as a surfactant. Therefore, the CRAES coupled with the composite inhibitor FeOOH/rGO has broad application potential for the synergistic treatment of radioactive aerosols.

Regression-enhanced Entrotaxis as an autonomous search algorithm for seeking an unknown gas leakage source

Rapid localization of hazardous gas leak sources is a vital task regarding the security of human society. Over the past few decades, autonomous search using mobile sensing devices equipped with gas sensors has become a promising field. Cognitive search strategies, such as Infotaxis and Entrotaxis, have been successfully used to search an unknown source autonomously in turbulence. However, they are time-consuming and may not be efficient because all source parameters (locations and strength) are estimated via particle filtering, especially when the prior information of source strength is rarely known. To address this inefficiency, this paper proposes a hybrid autonomous source searching approach, named as regression-enhanced Entrotaxis, which incorporates the Entrotaxis algorithm with the regression methods. Only the position of leak source is inferred by particle filtering, while the strength is estimated by the least squares based on the historical measurements. Through this way, the searching space in particle filtering is converted from 3-dimensions (source position in x–y plane and source strength) to 2-dimensions (source position in x–y plane), speeding up the computation significantly. Then, the reward function according to maximum entropy sampling principles is utilized to guide the robot’s next move. The performance of the proposed method is compared to that of the Entrotaxis algorithm. The results of Monte Carlo simulations demonstrate that fewer particles will be used to reach a specific success rate, saving time in the search process. Besides, the proposed strategy relies on less prior information regarding source strength, which is more in line with the actual scenario. In addition, the proposed approach is adaptable to a broader search region.

Regulated synthesis of cobalt phosphide/biochar utilizing phytic acid: Biochar enhances anion co-catalysis of cobalt phosphides in persulfate activation

Effective activation of persulfate (PS) contributes to the efficient degradation of emerging organic pollutants in water matrices. Cobalt phosphides (CoxP) have been testified as promising catalysts in efficiently activating PS, but their applications in water purification are still restricted by hazardous and costly chemical phosphorus sources used in traditional syntheses. Here, the synthesis of CoxP on biochar is regulated by an eco-friendly biomass phytic acid (PA) through low-speed ball milling combined with catalytic pyrolysis. Under the condition of 1 mM PS, 0.2 g/L catalyst, and pH 7, SMX (10 mg/L) can be thoroughly removed within 120 min with a TOC removal efficiency of 52 %. When dealing with low concentrations of SMX (0.25–1 mg/L), the oxidation is completed within 60 min. The simulated complex aqueous matrices (sodium humate solution and surface water) only exert trivial inhibition of SMX removal. Moreover, the leached Co2+ ion concentration is lower than the discharge standard (0.39 mg/L within 180 min). The crucial reactive oxygen species are identified as SO4−•, •OH, 1O2, and O2−•. Density functional theory (DFT) calculations indicate that the most pivotal active site in CoP/biochar is the P ion, while in Co2P/biochar is the Co ion. Biochar may potentially influence the electronic structure, thereby altering the oxidation states of ions and significantly enhancing the synergistic catalytic effect of anions in both cobalt phosphides. The more pronounced anion co-catalysis endows CoP/biochar with a better catalytic capacity than Co2P/biochar.

Analisis Risiko K3 pada Bongkar Muat di Pelabuhan dengan Metode HAZOP (Hazard Analysis and Operability Study) (Studi Kasus : PT. XYZ)

Occupational Safety and Health (OHS) is one of the very important factors in the smooth production process so that the OHS program must be implemented in every company. One possible cause of accidents is still ignoring the requirements and regulations in OHS. Lack of awareness and concern for OHS, resulting in the risk of accidents occurring in the loading and unloading process such as blisters on the hands, slipping, and falling objects. In this case the Occupational Safety and Health (OHS) management is required to be implemented during the loading and unloading process because this is also part of the planning and control of the loading and unloading process. To analyze the hazards to OHS risk in this study, the HAZOP (Hazard Analysis and Operability Study) method aims to identify, provide assessments and overcome OHS risk factors. In the process of loading and unloading. Based on the assessment on the Risk Matrix, there are 3 (three) levels of risk levels that have the potential to cause work hazards. The level of risk consists of high risk, medium risk, low risk. From this research there are no sources of hazard that are of extreme value, 2 (two) hazard sources that have a "high risk" value are in "placing a crane, and loading and unloading, 4 (four) hazard sources that have a" moderate risk "value on "Preparing loading and unloading equipment, Installing slings and Hooks to crane cranes, Workers entering barges, and Directing transport trucks" and 1 (one) source of hazard which has a "low risk" value found in "Installing slings and hooks on hook cranes.

Brazilian wind energy generation potential using mixtures of Weibull distributions

As concerns about the greenhouse effect and the resulting increase in carbon dioxide levels in the atmosphere continue to mount, there is an increasing need to curtail the use of fossil fuels for energy generation, especially given the ever-growing energy demands of the population. In this work, we applied the Weibull–Weibull distribution mixture to adjust the wind speed series of all 575 weather stations at six different heights for the 12 months of the year in the period from 01-01-2000 to 03-31-2022 measured in the hourly interval. We present the main results for the month with the lowest and the month with the highest incidence of wind speed in Brazil for the height of 120 m, which are the months of May and September, respectively. In estimating the Weibull–Weibull parameters, the Expectation–Maximization algorithm was used. Using the results obtained at each meteorological station and the Inverse Distance Weighting method, we predicted wind energy generation at points without information about wind speed. We observed that the Weibull–Weibull distribution mixture proved excellent for estimating wind energy density distribution over large areas We were able to provide a suitable fit for the different regions of Brazil. The findings indicate that the model employed has the potential to serve as a strong contender for adoption in other nations, enabling the integration of alternative energy sources in a complementary fashion. This measure could prove instrumental in mitigating the use of environmentally hazardous energy sources.

Seismic Hazard Assessment and Source Zone Delineation in Northeast India: A Case Study of the Kopili Fault Region and Its Vicinity

Seismic Hazard Assessment and Source Zone Delineation in Northeast India: A Case Study of the Kopili Fault Region and Its Vicinity