Industrial Hazards Research Articles

Assessment of the Ergonomic Exposures for Home Healthcare Workers in the United Kingdom

Home healthcare has been identified amongst the most hazardous industries in healthcare. Many of the tasks being conducted by home healthcare workers are associated with significant demands including physical demands such as mobility and repositioning activities as well as psychological demands which is attributed by dealing with a complex environment whilst administering medical and life saving care to patients, and social demands that encompasses dealing with dying and grieving patients. With the homes in United Kingdom having potentially unique exposures due to the healthcare system and design of the homes such as multi-floors, smaller condensed rooms, and limited ventilation, the purpose of this study was to investigate the exposures for home healthcare workers in the United Kingdom. Ergonomic hazards were observed through various tasks such as repositioning in bed (34.8%), transfer from bed to chair (30.4%), transfer from bed to chair (26.1%), and transfer from chair to chair (26.1%) and particularly for nursing aides. Lifting hoists were only used 13 times (19%) and predominantly by nursing aides (12 of 13, 92%). A slip sheet or slide board was used 7 times (10.1%), all being nursing aides using them.

Unifying the roll waves.

Free surface flows down a slope occur in various real-life scenarios, such as civil engineering, industry, and natural hazards. Unstable waves can develop at the free surface when inertia is sufficiently strong, indicated by the Reynolds number exceeding a critical value. Although this instability has been investigated for specific fluids with different rheologies, a common framework is still lacking to facilitate comparison among the various models. In this study, we investigate the linear stability of a generalized Newtonian fluid, where the viscosity [Formula: see text] remains unspecified. We meticulously construct new dimensionless quantities to minimize dependence on the rheology, and subsequently derive the Orr-Sommerfeld equation of stability for any generalized Newtonian fluid, which has never been done before. We conduct a long-wave expansion and generate a novel analytical expression for the wave celerity, along with the critical Reynolds number. The originality in this study is that the analytical expressions obtained are valid for any rheology, and are easy to compute from a rheological measurement or from a base flow profile measurement. These results are subsequently scrutinized using various shear-thinning, shear-thickening, and viscoplastic rheology models. They exhibit excellent agreement with experimental or numerical data as well as theoretical findings from existing literature. Furthermore, the novel analytical expressions enable a much more comprehensive investigation into the impact of rheology on stability. While our approach does not encompass singular or non-monotonous rheology, the analytical expressions derived from the long-wave expansion exhibit remarkable resilience and they continue to accurately predict both the wave speed and the instability threshold in such cases.

Experimental study on radiative heat flux from annular pool fires under the cross airflow

This paper investigates the radiative heat flux of annular pool fires under cross airflow (0–5 m/s), a configuration that has been underexplored in fire safety research despite its relevance in industrial fire hazards. Results show that radiative heat flux decreases with increasing distance from the fire source but increases with higher cross airflow speeds and larger annular pool diameters (Din/Dout). Existing models overestimate radiative heat flux in annular pool fires due to the underrepresented hollow flame region. A new modified triangular prism radiation model was developed based on the similarity criterion of annular pool fires. An extensive comparative analysis was further conducted, encompassing a wide array of experimental configurations documented in the literature, characterized by varying diameters spanning from 0.1 m to 0.7 m and cross wind velocity ranges extending from 0 m/s up to 5 m/s. The results of this comprehensive examination reveal a good agreement between the newly established model and the empirical data, thereby substantiating the model’s universal applicability and robust reliability. The new model will effectively assist industrial facilities in enhancing fire safety design, strengthening thermal hazard prevention and control, and ensuring a higher level of fire safety design.

Research on the evolution of state field and damage range of multiple source cloud explosions

Multi-source cloud detonations, as a form of industrial hazard, pose a significantly increased risk. To investigate the distribution of the state field and the extent of damage caused by multi-source cloud detonations, an experimental setup in an open space, along with numerical simulation, was employed to reconstruct the state field. The equivalent area method was utilized to analyze the distribution patterns of the overpressure field, impulse field, and the combined overpressure-impulse field associated with multi-source cloud detonations. The study demonstrates that the numerical simulation method developed aligns with experimental outcomes within a 10 % margin of error, thereby validating the accuracy of the simulation model. As the distance between the multiple explosive sources in a cloud detonation increases, the overpressure field, impulse field, and the combined overpressure-impulse field all exhibit a trend of initially increasing and then decreasing. Notably, the threshold ranges of 0.1 MPa, 0.05 MPa, and 0.03 MPa for multi-point cloud detonations each reach their maximum when the distribution distance of the explosive sources is twice the radius of the threshold range for a single explosive source. The overpressure-impulse criterion is found to be a more rational metric for characterizing the damage extent of multi-point cloud detonations. According to this criterion, the extent of level-five damage under various conditions is approximately located at a position 5.5 times the scale distance.

Assessing Crisis Management Tools for Sustainability of Industrial Safety

This study presents a comprehensive risk assessment of ammonia leaks, focusing on the quantitative modelling of hazardous area ranges, concentration dynamics, and thermal radiation effects under varying leakage scenarios using the ALOHA 5.4.7 software. The analysis involves two key scenarios: an ammonia gas leak and a pool fire, each modelled under distinct atmospheric conditions. For the gas leak scenario, ammonia concentrations were mapped across ERPG-defined hazard zones, ranging from low-level irritation zones (ERPG-1) to life-threatening exposure levels (ERPG-3), with maximum concentrations reaching 1500 ppm within a 110 m radius. The second scenario examined the impact of thermal radiation from a pool fire, identifying critical radiation zones where exposure to heat fluxes exceeding 10 kW.m−2 could cause fatal outcomes within 12 m. Despite ALOHA’s strengths in modelling acute exposure risks and providing valuable input for emergency response planning, the study identifies several limitations, particularly regarding the long-term environmental and health impacts of chemical releases and the effects of varying meteorological conditions. These findings suggest that integrating ALOHA with advanced real-time monitoring and AI-based prediction systems could significantly improve its capacity to manage dynamic, rapidly evolving industrial hazards.

Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention

Due to its inherent complexities in the process and the dynamic interactions with external environmental factors, the construction industry is widely considered one of the most hazardous industries worldwide. With advancements in artificial intelligence (AI), construction safety management practices have increasingly used knowledge-driven approaches. Such incorporation of knowledge-based methods has led to significant improvements in various elements of construction safety management systems, including hazard identification and risk assessment, selection of risk mitigation strategies, analysis of accident information, sharing of health and safety knowledge, access to regulations, and identification of applicable safety requirements. Against this background, this paper presents a systematic literature review to provide an overview of the current state of the art in the use of knowledge-driven approaches in construction safety management. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedure, this study reviews how the knowledge-driven approach is utilized in the construction safety management field to automate different activities that come under it. Journal papers published from 2000 were considered for this review, and the analysis focused on the contributions of research, the evolution of knowledge-driven approaches, sources of incorporated knowledge, methods of system development, yearly publications, and publication by journals. The results provide a comparison of related studies over two decades and offer insights into trends and gaps in this research field. Notably, the trend analysis shows a dramatic increase in the number, as well as the depth, of research efforts utilizing AI techniques for analyzing unstructured data, such as construction images and texts from construction documents, and drawing data-based decisions for accident prevention.

Aluminum dust concentration detection based on LSTM-Kalman filter

Industrial dust emissions present serious hazards, including respiratory issues and explosion risks. Traditional dust concentration detection methods are often compromised by environmental factors. This study introduces a novel FFT-KF-LSTM-NET model to predict high-concentration aluminum powder levels, utilizing 128 sets of electrostatic induction measurement data. By applying the Fast Fourier Transform (FFT) to eliminate low-frequency interference, integrating Long Short-Term Memory (LSTM) networks for advanced time series analysis, and using the Kalman Filter (KF) for rapid model convergence, this approach significantly enhances prediction accuracy. The model achieves an 82% improvement in Mean Squared Error (MSE), reducing it to 0.1336, outperforming traditional methods. Furthermore, by modeling the voltage signal generated by charged dust particles in the electrostatic induction sensor's sensing area and using the first derivative of the voltage signal as a learning feature, the model's prediction speed is increased from 1.5 s-2 s–0.5 s, with improved anti-interference capabilities. These advancements position the FFT-KF-LSTM-NET model as a crucial tool for real-time, reliable dust concentration detection in industrial environments.

The brick kiln child workers of Pakistan.

Pakistani law recognises that no young person under the age of 18 years can enter into a valid and binding contract. In hazardous industries, such as brick kilns, none of the children working in them have any formal contract, so limiting any rights they may have. Any contract that does exist is with the child's father and will be linked to everlasting debts and constitutes a form of bondage. This paper reviews the adverse medical effects on children of such employment.

Automated construction safety reporting system integrating deep learning-based real-time advanced detection and visual question answering

The construction sector is globally acknowledged as one of the most hazardous industries, owing to the vulnerability of its workers to accidents, injuries, and even loss of life. Effective precautionary measures are necessary and ensuring the use of personal protective equipment (PPE) by workers is crucial for protecting them from accidents. Existing deep learning-based PPE detection systems mainly use simple vision-based target detection methods for tasks such as the identification of helmets or vests, and they tend to be task-specific. However, the identification of specific PPE based on respective job types and maintaining detailed safety records, requires further innovative approaches. In this paper, we propose an innovative intelligent system that not only accurately recognizes specific PPE according to the needs of different work types but also automatically generates safety inspection reports and establishes complete safety records, thus providing critical data to support accident investigations. The proposed system integrates a target detection model, visual question answering model, and text-based analysis of the relevant regulations to realize real-time detection of PPE and automatic generation of safety inspection reports. The experimental results show that the proposed YOLOv8n-DCA network strikes a good balance between performance and computational cost—, with a mAP value of 86%. Compared to the original YOLOv8n network, the mAP value is improved by 5.1%, while the model parameters and size are significantly reduced. Further, the visual question answering model exhibited a precision is 95.9. Finally, the automatic generation of safety inspection reports was successfully realized, verifying the feasibility of the developed system. This innovative system promises a comprehensive and efficient PPE management solution for the construction industry to ensure worker safety and provide strong data support.

Application of STPA for Comprehensive Risk Analysis of Naphtha Explosion Hazards

Chemical accidents always result in significant losses due to the flammable, explosive, and toxic characteristics of hazardous chemicals. Analysis of process safety parameters is an effective way to prevent hazardous chemical accidents and reduce losses. System-theoretic process analysis (STPA) is a newer hazard analysis technique that is based on systems theory. It has been shown to be effective in identifying hazards in other industries, but its application in oil and gas plants is still rare and limited due to systems complexities and other challenges. This paper aims to apply the STPA method to a complex system “column C-63” at the Skikda RA1K refinery to prevent the explosion scenario of naphtha. The results show that STPA was able to identify the root causes of the explosion scenario, which is important for preventing chemical risks.

Predicting the risk of uterine fibroids in female copper smelter workers by cytogenetic abnormalities of buccal epithelium

Exposure to adverse occupational factors increases the risk of diseases of the reproductive system. Long-term studies have shown a high prevalence of uterine fibroids among all diseases of the reproductive system in women exposed to occupational hazards in industry. The occurrence of fibroids, having such complications as menorrhagia, pain in the pelvic area, and infertility, hampers performance and diminishes the quality of life. The risk of genetic mutations in cells playing a key role in the development of fibroids is raised by inhalation of industrial aerosols containing metals possessing mutagenic and carcinogenic potencies. Cytology of the buccal epithelium can be used as a method objectively indicating the genetic risk. The purpose of the study was to develop a predictive model for assessing the risk of uterine fibroids in female workers exposed to aerosols containing metal particles at a copper smelter using buccal cytograms. We examined 47 female workers of a copper smelter, of which 39 formed the main (exposed) group. Uterine fibroids were more frequent in the main group than in the controls (25.6 % versus 0.0 %, p ≤ 0.05). Genotoxic indicators, such as protrusions and micronuclei, and cytotoxicity indicators were also significantly increased in this group (nuclear vacuolization and cytoplasmic vacuolation were 1.6 times and karyolysis 1.8 times higher compared with the controls, p ≤ 0.05). We have developed two mathematical models for assessing the risk of uterine fibroids. Model 1 includes variables without restrictions of characteristics, i.e. micronuclei, perinuclear vacuoles, and cytoplasmic vacuolation (AUROC – 0.940), while Model 2 necessarily includes such genotoxic parameters as micronuclei and protrusions (AUROC – 0.883). The 4-member model (M1+M2), which includes both genotoxic (micronuclei and protrusions) and cytotoxic (binucleated cells and cytoplasmic vacuolation) indicators, has the highest significance (AUROC – 0.998). The results indicate involvement of both genetic and cytotoxic mechanisms in the development of uterine fibroids in female workers exposed to toxic industrial aerosols. The models including both two indicators of genotoxicity (micronuclei and protrusion) and one and/or two cytotoxicity indicators have the greatest predictive value.

Метод буккальных цитограмм для задач выделения групп риска развития миомы матки у работниц медеплавильного производства

Exposure to adverse occupational factors increases the risk of diseases of the reproductive system. Long-term studies have shown a high prevalence of uterine fibroids among all diseases of the reproductive system in women exposed to occupational hazards in industry. The occurrence of fibroids, having such complications as menorrhagia, pain in the pelvic area, and infertility, hampers performance and diminishes the quality of life. The risk of genetic mutations in cells playing a key role in the development of fibroids is raised by inhalation of industrial aerosols containing metals possessing mutagenic and carcinogenic potencies. Cytology of the buccal epithelium can be used as a method objectively indicating the genetic risk. The purpose of the study was to develop a predictive model for assessing the risk of uterine fibroids in female workers exposed to aerosols containing metal particles at a copper smelter using buccal cytograms. We examined 47 female workers of a copper smelter, of which 39 formed the main (exposed) group. Uterine fibroids were more frequent in the main group than in the controls (25.6 % versus 0.0 %, p ≤ 0.05). Genotoxic indicators, such as protrusions and micronuclei, and cytotoxicity indicators were also significantly increased in this group (nuclear vacuolization and cytoplasmic vacuolation were 1.6 times and karyolysis 1.8 times higher compared with the controls, p ≤ 0.05). We have developed two mathematical models for assessing the risk of uterine fibroids. Model 1 includes variables without restrictions of characteristics, i.e. micronuclei, perinuclear vacuoles, and cytoplasmic vacuolation (AUROC – 0.940), while Model 2 necessarily includes such genotoxic parameters as micronuclei and protrusions (AUROC – 0.883). The 4-member model (M1+M2), which includes both genotoxic (micronuclei and protrusions) and cytotoxic (binucleated cells and cytoplasmic vacuolation) indicators, has the highest significance (AUROC – 0.998). The results indicate involvement of both genetic and cytotoxic mechanisms in the development of uterine fibroids in female workers exposed to toxic industrial aerosols. The models including both two indicators of genotoxicity (micronuclei and protrusion) and one and/or two cytotoxicity indicators have the greatest predictive value.

Understanding Structural Changes in Recycled Aggregate Concrete under Thermal Stress

Objective: This study investigates the influence of high-temperature treatment on the deformation properties and structural deformation of recycled aggregate concrete (RAC) in response to potential fire hazards in the construction industry. Methods: Standard-cured 28-day RAC specimens were subjected to microwave heating at 300 °C and 600 °C, with subsequent uniaxial compression tests utilizing a WDW-2000 machine and a VIC 3D strain measurement system to analyze strain data through digital image correlation (DIC) technology. Results: After treatment at 300 °C, recycled aggregate concrete (RAC) demonstrated superior mechanical properties to fresh concrete aggregates. This enhancement may be attributed to the more robust siloxane bonds (Si-O-Si) in the recycled materials. Conversely, exposure to 600 °C intensified internal structural damage, notably lowering the material’s elastic modulus and peak stress. DIC analysis highlighted the correlation among temperature, volumetric strain, and crack development patterns, with more extensive cracking at 600 °C. Conclusions: Moderate-temperature treatment enhances RAC’s structure and deformation properties, while high-temperature treatment diminishes its performance. These findings provide valuable insights for assessing building safety post-fire and the application of RAC, emphasizing its suitability at moderate temperatures and risks at high temperatures.

Investigating the Causes of Work-Related Injuries and their Impact on the Employee Health and Safety in Organizations in GCC Region

Ensuring employee health and safety has been considered the top priority by OSHA. Although employee health and safety has an been considered paramount in ensuring effective company operations around the world yet limited efforts are being taken by the organizations to enhance employee health and safety. This research paper aims to explore the various industrial hazards and their impact on the employee health and safety in the GCC region. This research uses primary and secondary data, Qualitative and quantitative data analysis techniques to test the hypothesis. Descriptive statistics including relationship charts, frequency analysis, and ANOVA testing were included to reach the conclusion. The response was received 100 responses from different industries in GCC region to whom the survey was disseminated. The researcher has also used open publicly available data through the published information by the General Organization for Social Insurance (GOSI). The results conclude close inverse relationship between the dependent and independent variables where the (Independent variable) is Employee safety and health and the dependent variables are electric hazard, fire hazards, fall hazards, ergonomics hazards. The reduction in the hazards will lead to increase in the employee safety and health.

Experimental validation of the use of thermal stimuli for space charge measurements in dielectric liquids: Application to electrical double layers

Electric charges in liquids are at the basis of numerous applications and may drive industrial hazards. The Thermal Step Method is applied to liquid/solid interfaces to validate the use of thermal stimuli techniques for space charge measurements in dielectric liquids. Experimental results obtained for different electrical double layers are presented and discussed. They show that thermal convection has no significant contribution to the signal compared to the response of the charges from the solid/liquid interface. The measured signals are in accordance with the classical theory of thermal methods in solids and are consistent with the behavior expected from numerical simulations.

Occupational hazards in sawmill industry and its effect on sawmill output in Nigeria

Occupational hazards in sawmill industry and its effect on sawmill output in Nigeria

SRGAN-enhanced unsafe operation detection and classification of heavy construction machinery using cascade learning

In the inherently hazardous construction industry, where injuries are frequent, the unsafe operation of heavy construction machinery significantly contributes to the injury and accident rates. To reduce these risks, this study introduces a novel framework for detecting and classifying these unsafe operations for five types of construction machinery. Utilizing a cascade learning architecture, the approach employs a Super-Resolution Generative Adversarial Network (SRGAN), Real-Time Detection Transformers (RT-DETR), self-DIstillation with NO labels (DINOv2), and Dilated Neighborhood Attention Transformer (DiNAT) models. The study focuses on enhancing the detection and classification of unsafe operations in construction machinery through upscaling low-resolution surveillance footage and creating detailed high-resolution inputs for the RT-DETR model. This enhancement, by leveraging temporal information, significantly improves object detection and classification accuracy. The performance of the cascaded pipeline yielded an average detection and first-level classification precision of 96%, a second-level classification accuracy of 98.83%, and a third-level classification accuracy of 98.25%, among other metrics. The cascaded integration of these models presents a well-rounded solution for near-real-time surveillance in dynamic construction environments, advancing surveillance technologies and significantly contributing to safety management within the industry.

Occupational risk management in construction supply chain

The building is historically a driver of the economy, creating thousands of direct and indirect jobs, moving a huge chain of suppliers of raw materials, supplies and services, besides building a country’s infrastructure and the homes of millions of people. But working conditions in this sector that is so important to the country are not the best, exposing workers to risks of work accidents and occupational diseases. Therefore, this study sought to present the main occupational hazards in the construction industry, discussing alternatives for effective risk management by reducing the rates of accidents and illness among workers. In this research, case studies were done in small and medium-sized construction sector facing the residential construction market. It was also proposed solutions for the implementation of risk management and occupational health and safety for businesses to succeed and lower the rates of accidents at work, health and safety, and quality of work life in these companies.

Design and Implementation of Low-cost, Low-power Industrial Grade Tiny Sensor Nodes for Mesh Networking in Hazardous Industries

Design and Implementation of Low-cost, Low-power Industrial Grade Tiny Sensor Nodes for Mesh Networking in Hazardous Industries

Deciphering the antiochratoxigenic activity of plant extracts and Debaryomyces hansenii against Penicillium nordicum in a “chorizo”-based medium by proteomic analysis

Penicillium nordicum is the main ochratoxin A (OTA)-producing species on the surface of dry-fermented sausages, such as the “chorizo”. New antifungal strategies are being developed using biocontrol agents (BCAs), such as plant extracts and native microorganisms. This work aimed to evaluate the antiochratoxigenic capacity and the causative modes of action of BCAs (rosemary essential oil (REO), acorn shell extract and the yeast Debaryomyces hansenii (Dh)) in a “chorizo”-based medium (Ch-DS). BCAs were inoculated on Ch-DS together with P. nordicum and incubated at 12 °C for 15 days to collect mycelia for OTA analyses and comparative proteomics. Both REO and Dh alone decreased OTA accumulation up to 99% and affected the abundance of P. nordicum proteins linked to cell wall organisation, synthesis of OTA-related metabolites and ergosterol synthesis. It is worth highlighting the increased abundance of an amidase by REO, matching with the decrease in OTA. The use of REO and Dh as BCAs could be an effective strategy to reduce the OTA hazard in the meat industry. Based on their not fully coincident modes of action, their combined application could be of interest in “chorizo” to maximise their potential against ochratoxigenic strains.