Chemical Warehouse Research Articles

A Local Information Entropy-Based Point Cloud Simplification Algorithm for Hazardous Chemical Warehouses

A Local Information Entropy-Based Point Cloud Simplification Algorithm for Hazardous Chemical Warehouses

Complex network analysis for accident causes modelling to enhance process safety in chemical enterprises

AbstractHazardous chemicals often cause catastrophic accidents, and accidents often result from intricate interactions among various causes. Due to the varying risk factors in different areas of chemical enterprises, to achieve more precise prevention, a more detailed study of the accident risk factors in each area is necessary. Therefore, this study focuses on analyzing critical accident causes and their interrelationships in different functional areas of chemical enterprises to enhance process safety by using a complex network model. Based on 90 accident information, complex network models are constructed for hazardous chemical warehouse areas (HCWAs), tank farm areas (TFAs), and production areas (PAs). Subsequently, a topological analysis of the complex network models is conducted. Based on the PageRank algorithm, 13 critical nodes are identified for HCWAs, while 14 for TFAs and 13 for PAs. Node degree analysis with confidence quantifies mutual influences, forming critical accident causal links for each area. The research results offer decision support for precise accident risk control, aiding in reducing future accidents and improving process system safety in chemical enterprises.

Development of a Low-Cost Web-Based Information System for Managing a University Department Chemical Warehouse

Herein, we present the implementation of a low-cost web-based information system tailored to manage a university department chemical warehouse. The system provides a centralized platform for cataloging, tracking, and managing chemical inventory data, while also facilitating purchasing and various administrative tasks associated with laboratory operations. The system has been developed within the Campusnet platform and has the following functionalities: (i) an efficient way for cataloging the extensive array of products available in the warehouse; (ii) an intuitive web interface with a device-responsive layout to facilitate browsing and purchasing of products by students, researchers, and technical staff; (iii) an inventory transaction recording system to simplify the attribution of costs; (iv) a simple procedure to streamline the process of joint purchases; and (v) a low deployment cost and ease of maintenance. Key design considerations, including regulatory compliance and safety, are also presented.

A novel dynamic risk assessment method for hazardous chemical warehouses based on improved SVM and mathematical methodologies

Effective dynamic risk assessment is crucial for identifying process hazards and preventing accidents. The rapid development of modern technology urgently requires the development of new dynamic risk assessment methods to address current societal needs, especially in situations where a large amount of real-time data is available. Consequently, this manuscript presents an improved support vector machine model (SVM), integrated mathematical modeling, to facilitate dynamic risk assessment for hazardous chemical warehouses (HCWs). Firstly, an indicator framework and a quantitative risk factor table are crafted. Then a mathematical model using knowledge graph and DEMATEL-variable weight theory (VWT) is established, which combines accident information with VWT to optimize the weight calculation and provides reliable prior knowledge for the improved SVM model. Ultimately, the improved SVM model is crafted by the establishment of an improved hybrid kernel of polynomial and radial basis function kernel, fine-tuning its hyperparameters with particle swarm optimization, and utilizing sensitivity analysis to simplify the model. The model is formulated to accommodate the intricate non-linear relationships within indicators and dynamic risk, thereby establishing dynamic risk assessment rules. Through a case study, the improved SVM model demonstrates higher precision in dynamic risk prediction compared to original models. The results substantiate that the model can provide innovative insight and methodology for the precise evaluation of dynamic risk in HCWs.

Assessing the health risks of chemicals in a company supplying chemicals to drilling rigs in Southern Iran using COSHH, SHEM-SAM, and SQRA methods.

Chemical industries are among the process industries and cause many risks. The present research aimed to analyze the health risks of a chemical warehouse of drilling rigs chemical Supply Company based on COSHH (Control of Substances Hazardous to Health), CHEM-SAM (Chemical Risk Management Self-Assessment Model), and SQRA (Subjective Quantified Risk Assessment) methods in 2021. The information was collected based on document review, MSDS of chemicals, processes, employees, and chemical exposure. Flammability, toxicity, allergy-causing, corrosivity, reactivity, LD50, and permissible thresholds of chemicals were also collected. The present research results showed that out of 59 main chemicals in the operational processes of the chemical warehouse of drilling rigs, 14 chemicals are flammable, 22 cause allergy responses, and three can cause death if inhaled. According to the results of the CHEM-SAM method, the employees and people outside the organization are at medium and low chemical risk based on the current management of the chemical warehouse, respectively. The results of the COSHH health assessment showed that chemicals had low, medium, high, and very high risk in 31, 13, 12, and 3 cases, respectively. The high-risk cases consisted of Ammonium Nitrate، Caustic Soda, and Poly.Aluminum.Chloride. Health risk assessment was also performed using the SQRA method, and results showed that chemicals have a very low, low, medium, high, and very high risk in 27, 12, 8, 9, and 3 cases, respectively. The results showed that the adverse health effects of chemical exposure in the drilling industry are alarming. Employees of different sectors of oil and gas industries are exposed to chemicals.

Providing a model to evaluate the spread of fire in a chemical warehouse using numerical simulation and Bayesian network

Chemical warehouses are one of the important sources in process units. Locations are one of the issues that should be investigated in closed environments due to the many types of chemicals and storage conditions. In this study, fire dynamics simulation (FDS), was used to simulation of fire in the presence and non-presence of the ventilation system. Then the spread of fire in the warehouse was evaluated based on domino methods and finally the Bayesian network (BN) was used to update the rate of fire spread. The simulation results in this approach showed that the highest amount of heat flux related to iso-octane fire at L/D= 0.3 when the ventilation system is off and the doors are closed. The updated results of the fire spread modeling in BN showed that if a fire occurs in isooctane barrels, it has the highest rate of spread with a probability of 22% and the lowest rate of spread in Diglycolamine(DGA) barrels with a probability of 0.4%. From the results of this study, it is possible to understand the importance of arranging materials according to the principles of compatibility of chemical materials, and based on this, appropriate control measures can be provided.

Atmospheric negations: Weaponising breathing, attuning irreducible bodies.

This paper elaborates various ways in which atmospheric negations operate by weaponising bodily vulnerability to air. It shows, firstly, how bodies remain exposed to colonial proximities of respiratory, olfactory, and sonic violence with ways that are constituted through negating site- and body-spheres. It highlights these spheric materialities by discussing the use of tear gas and skunk water, bombing of chemical warehouses, and the sonic settler aggression in Palestine, further arguing that we need to pay more attention to the irreducibility of the body to such violent orchestrations of atmospheric. Here the irreducibility of the body and the incapacity of the spheric become key matters related to what is called, secondly, the reciprocal sphereological vulnerability between the corporeal and the spheric. By paying particular attention to difference between breathing and attunement, the paper shows how a negative limit condition resides at the heart of what constitutes sphere-dwelling. Here an ontological shift in thinking atmospheric is suggested, one that starts, not from current framings aligned around the notions of vitality, affirmation, and relationality, but from the weaponisation of the fundamental incapacity of the body to overcome its own vulnerability to the air it breathes.

Identification Methodology for Chemical Warehouses Dealing with Flammable Substances Capable of Causing Firewater Pollution

Major accidents involving flammable substances can lead to significant environmental damage. The operators of chemical warehouses—in order to prevent and mitigate harmful environmental impacts—based on fire prevention strategies should apply “firewater pollution prevention” (FPP) measures. The identification of affected warehouses already in operation is an important law enforcement task. Therefore, the authors—based on the assessment of firewater run-off scenarios—propose a simple and easy-to-use dangerous establishment identification procedure and methodology based on event tree analysis and indexing preliminary risk analysis approaches. Two independent expert groups validated—in the case of 10 facilities—the index components of the approach. The testing of the applicability of the approach took place in parallel with the analyses of the Hungarian operator’s practice. The research results—covering the inspection of 24 facilities—can assist the operators in the effective and unified implementation of FPP measures. In the case of 14 facilities, it was necessary to introduce FPP measures, which highlight the need to improve the law enforcement compliance of identified operators. The investigation results can also contribute to increases in the fire and environmental safety performance of chemical warehouses, which ensures a higher level of environmental protection and people’s health near chemical warehouses.

A Point Cloud Classification Method and Its Applications Based on Multi-Head Self-Attention

<p>In the monitoring the safety status of hazardous chemical warehouses by three-dimensional re-construction of deep camera point clouds, there are classification difficulties such as large space, sparse distribution of point clouds in cargo images, and similar distribution in low dimensions. Based on the above problem, a point cloud recognition method based on multi-head attention mechanism is proposed. The algorithm first normalizes the distribution of the point cloud data set through the affine transformation algorithm to solve the problem of sparse distribution. Then, the high-dimensional feature map is obtained by fusing the data down-sampling and curve feature aggregation algorithms to solve the problem of low-dimensional distribution approximation. The feature map is then encoded using a multi-head self-attention encoder to obtain features under different heads, which are then merged into a feature map. Finally, a multi-layer fully connected neural network is used as the decoder to decode the feature map into the final object classification. Comparative experiments were performed on the ModelNet40 dataset and the self-built dataset of warehouse goods, and the results showed that the accuracy of this paper was improved by 0.5% to 7.8% compared with that of other classification algorithms.</p> <p> </p>

Examination of the Fire Resistance of Construction Materials from Beams in Chemical Warehouses Dealing with Flammable Dangerous Substances

The recent expansion of logistics capacities entails the installation of chemical warehouses, which operations increase the occurrence of compartment fires involving flammable dangerous substances. The aim of this research was to compare and analyze the fire behavior of beams made of different structural materials but with the same load capacity. It is assumed that wooden beams, which are less commonly used in industrial facilities, may have a similar or even better load-bearing capacity in case of a fire than the generally used steel beams. The authors—based on the relevant EU standards—performed load capacity calculations of three beams prepared from different materials under the influence of fire and analyzed the changes in the material properties. Then, they examined the possibility of reinforcing the beams with carbon fiber lamellae and proposed additional fire protection requirements. The test results not only proved the different degrees of fire resistance of various building materials in the event of a fire and after their reinforcement but also suggested the application of special technical, prevention and response measures for the safe storage of dangerous substances. The study outputs enable warehouse designers, operators and safety experts to ensure a higher fire safety level for chemical warehouses.

An Intelligent Detection Approach for Smoking Behavior

Smoking in public places not only causes potential harm to the health of oneself and others, but also causes hidden dangers such as fires. Therefore, for health and safety considerations, a detection model is designed based on deep learning for places where smoking is prohibited, such as airports, gas stations, and chemical warehouses, that can quickly detect and warn smoking behavior. In the model, a convolutional neural network is used to process the input frames of the video stream which are captured by the camera. After image feature extraction, feature fusion, target classification and target positioning, the position of the cigarette butt is located, and smoking behavior is determined. Common target detection algorithms are not ideal for small target objects, and the detection speed needs to be improved. A series of designed convolutional neural network modules not only reduce the amount of model calculations, speed up the deduction, and meet real-time requirements, but also improve the detection accuracy of small target objects (cigarette butts).

Impact of Fireworks Industry Safety Measures and Prevention Management System on Human Error Mitigation Using a Machine Learning Approach.

In the fireworks industry (FI), many accidents and explosions frequently happen due to human error (HE). Human factors (HFs) always play a dynamic role in the incidence of accidents in workplace environments. Preventing HE is a main challenge for safety and precautions in the FI. Clarifying the relationship between HFs can help in identifying the correlation between unsafe behaviors and influential factors in hazardous chemical warehouse accidents. This paper aims to investigate the impact of HFs that contribute to HE, which has caused FI disasters, explosions, and incidents in the past. This paper investigates why and how HEs contribute to the most severe accidents that occur while storing and using hazardous chemicals. The impact of fireworks and match industry disasters has motivated the planning of mitigation in this proposal. This analysis used machine learning (ML) and recommends an expert system (ES). There were many significant correlations between individual behaviors and the chance of HE to occur. This paper proposes an ML-based prediction model for fireworks and match work industries in Sivakasi, Tamil Nadu. For this study analysis, the questionnaire responses are reviewed for accuracy and coded from 500 participants from the fireworks and match industries in Tamil Nadu who were chosen to fill out a questionnaire. The Chief Inspectorate of Factories in Chennai and the Training Centre for Industrial Safety and Health in Sivakasi, Tamil Nadu, India, significantly contributed to the collection of accident datasets for the FI in Tamil Nadu, India. The data are analyzed and presented in the following categories based on this study's objectives: the effect of physical, psychological, and organizational factors. The output implemented by comparing ML models, support vector machine (SVM), random forest (RF), and Naïve Bayes (NB) accuracy is 86.45%, 91.6%, and 92.1%, respectively. Extreme Gradient Boosting (XGBoost) has the optimal classification accuracy of 94.41% of ML models. This research aims to create a new ES to mitigate HE risks in the fireworks and match work industries. The proposed ES reduces HE risk and improves workplace safety in unsafe, uncertain workplaces. Proper safety management systems (SMS) can prevent deaths and injuries such as fires and explosions.

A new approach to chemicals warehouse risk analysis using computational fluid dynamics simulation and fuzzy Bayesian network

This study aims to assess the risk of chemicals warehouse using a Bayesian networks (BNs) and computational fluid dynamics (CFD). A methodology combining Bow-Tie (BT), fuzzy set theory (FST), and Bayesian network was employed, in which the BT was drawn for chemical spill scenarios. FST was utilized for the estimation of the basic events (BEs) occurrence probability, and the probability of interaction among a set of variables was obtained using BNs. Pool fire scenario radiation heat flux was evaluated using CFD code, fire dynamic simulator (FDS), and the solid flame model (SFM). Fail in forklift brake system (BE1), was the most significant cause for a chemical spill. Based on the CFD model, the heat flux is 31 kW/m2 at a distance of 3.5 m from the fire, decreasing to 6.5 m gradually. The maximum safety distance of 4 m is predicted by the CFD for heat flux that exceeds 12.5 kW/m2; however, SFM predicts approximately 4.5 m. According to the results, the amount of posterior risk is higher than the prior value. The framework presented in the chemicals warehouse for consequence analysis and dynamic risk assessment (DRA) of pool fire could be used for preventing the accidents and domino effects in the chemicals warehouse.

Chemical warehouse fire kills 38 in China

Some 38 people have died in a fire at a facility in Anyang city, Henan Province, China, according to Xinhua, China’s official state news agency. The fire occurred Nov. 21 at a site operated by Kaixinda Trading Company, a chemical wholesaler, media reports state. Chinese president Xi Jinping ordered all-out efforts to rescue and treat the injured, Xinhua reports. The incident is reminiscent of a 2015 warehouse fire in Tianjin, China , that killed 165 people.

Chemical warehouse fire kills 38 in China

Chemical warehouse fire kills 38 in China

Nondominated Sorting Differential Evolution Algorithm to Solve the Biobjective Multi-AGV Routing Problem in Hazardous Chemicals Warehouse

For the multiple automated guided vehicle (multi-AGV) routing problems in the warehousing link of logistics, where the optimization objective is to minimize both the number of AGVs used and the maximum pickup time simultaneously, a nondominant sorting differential evolution (NSDE) algorithm is proposed. In the encoding and decoding stages, the pickup point area is divided. AGVs are allocated to each region according to the proposed rule based on avoiding duplicate paths. Meanwhile, the pickup points within the region can be adjusted to optimize the pickup paths and improve the pickup efficiency. The fast nondominated sorting method and elitist selection strategy in the nondominated sorting genetic algorithm II (NSGA-II) are introduced into the differential evolution algorithm, which sorts all the regions to obtain the best Pareto solution set. Lastly, the domination of the proposed NSDE algorithm in Pareto frontier evaluation indicators is verified by some numerical experiments.

A hybrid model based on fuzzy VIKOR and the classical optimal search to detect illegal chemical warehouses

The use of chemical weapons has turned into an increasing risk for the world. In this study, a hybrid approach on the basis of fuzzy VIKOR and the optimal search model to cope with an important case study called the detection of illegal chemical warehouses is introduced. It is obvious that such illegal activities are accomplished under high secret considerations. Therefore, we have several types of ambiguity and uncertainty in this problem. First, fuzzy VIKOR is used to prioritize the suspicious warehouses based on time and cost of a search under fuzzy environment. Also the probability of existence of chemical agents in each warehouse and the probability of detection in case materials exist in warehouse, are estimated. Next, the output of VIKOR i.e., is assumed as an input of optimal search model and optimal strategy for searching is achieved by solving a stochastic dynamic programming. According to this hybrid approach, we start from the location that has the maximum value of Although we get benefits of fuzzy logic, VIKOR, and classical optimal search, the suggested method is easy to understand and straightforward to utilize in real-world problems. Also this model can enhance the robust nature of hybrid approach and reduces its sensitivity to the change of weights.

Modeling of Pool Fire Risk in a Chemical Warehouse

Background: Pool fire is a phenomenon caused by the leakage of flammable materials on the ground leading to serious hazards, irrespective of its consequences. The proximity and high volumes of chemicals in warehouses require that the characteristics of various materials in warehouses be taken into account for calculating the chain effects of the pool fire. Methods: One of the effective parameters in expanding the impact of pool fire chain is heat flux value. There are different models for calculating and predicting it. In this study, two approaches of computational fluid dynamic (CFD), fire-driven fluid flow, fire dynamics simulator (FDS), and solid flame model were used to predict heat flux values. Results: In both models, the calculated heat flux was used to evaluate the effects on humans (first-degree burns, second-degree burns, and deaths) and the materials. The CFD results were compared with the results of the solid flame model, which indicated that there was little error in the predicted heat flux values. Conclusion: The results of this study can be used to better understand the effects of pool fire on chemical warehouses, and provide appropriate control measures to prevent such accidents in warehouses.

Evaluation of ANSI Z535 Safety Sign Installation

A safety sign is a sign of equipment to provide protection for workers or visitors in the workplace. American National Standards Institute Z535 (ANSI Z535) is used as a basic guideline for installing safety signs in the workplace because it is more communicative by using global symbols to overcome language barriers. Occupational Safety Division of Manpower and Transmigration Departement, East Java Province (UPT Keselamatan Kerja Surabaya) is a workplace that has a risk of occupational accidents. The preliminary surveys in the area of the 3rd floor of the Division of Occupational Safety (UPT Keselamatan Kerja) Surabaya revealed that there were many sites with insufficient safety signboards. Many of the installed safety signs did not comply with ANZI Z535 standards. This study aimed to evaluate the installation of safety signs compared to the ANZI Z535 standard on the 3rd floor of UPT K2 Surabaya. This was an observational study examining the installation of safety signs. The data were obtained using the ANSI Z535 safety sign checklist. We found 2 out of 5 types of safety signs were in accordance with ANSI safety sign standards with a comparison percentage of more than 66%, such as the notice sign (67.85%) and safety condition sign (75%). Three other types of safety signs were in the unfavorable category with a percentage of less than 66%, such as danger sign (65.63%), warning sign (50%), and caution sign (46.88%). Some sites required additional safety signs, such as warning signs (at distillation site), caution signs (oven, stairs), notice signs (cylinder storage, elevator, chemical warehouse), and safety condition signs (stair, eyewash).

Design of Intelligent Early Warning Robot System for Warehouse Autonomous Patrol based on Scale Estimation Algorithm of Probability Theory

In view of the backward monitoring status in the traditional safety management of hazardous chemicals warehouse, a patrol robot for hazardous chemicals warehouse with autonomous patrol stereo detection, intelligent early warning and remote monitoring functions is designed, and the design process of related functions of autonomous patrol navigation subsystem, environmental detection subsystem and remote monitoring subsystem is discussed from two aspects of hardware and software. Because both the camera and the target may be in motion, it is necessary to consider the scale change of target influence caused by relative distance. In order to overcome the shortcoming of invariable scale in Mean Shift algorithm, this paper adopts a scale adaptive method to estimate the size of the target, adjusts the parameters of kernel function by using ellipse feature, and takes the parameters of the current frame as the initial data of the next frame, so as to achieve the effect of adaptively adjusting the target scale. The test results show that the system can effectively traverse the map of hazardous chemicals warehouse, accurately assess the leakage of hazardous chemicals and the environmental safety of warehouse, and give early warning. The remote monitoring platform greatly facilitates the remote management of the warehouse.