Accident Situations Research Articles

A feasibility study of Augmented Reality Intervention for Safety Education for farm parents and children.

Agriculture is one of the most dangerous U.S. occupations with high rates of injuries and fatalities, and especially more dangerous for children, having more young worker deaths than any other industry. Thus, safety education is essential in promoting safe and healthy working habits in agriculture. Augmented reality (AR) technology has great potential to enhance the effectiveness of safety education due to its high levels of system-user interactivity and media enjoyment. This study aims to: (1) develop Augmented Reality Intervention for Safety Education (ARISE), an AR 3D simulator that presents farm accident situations with immersive media technology, (2) examine the feasibility of ARISE, and (3) evaluate the potential of ARISE as an effective agricultural safety education program for farm parents and children. To test the feasibility of ARISE, we conducted semi-structured in-depth interviews with ten parent-child dyads at an extension office located in Maryland. Participants were farmers who owned and operated a family farm(s) with their child or children ages 5-13. The interviews included asking participants questions about their perceptions of farm risks, sources of risk education, and protection methods. In the next step, participants used ARISE with researcher guidance. After using the application, participants were asked questions about their experience using ARISE and suggestions for improvement. The interviews were then transcribed and analyzed following the conventional content analysis method. Three main themes emerged-demand (e.g., perceived risk and need for education; lack of farm safety education from school), acceptability (e.g., attitude toward AR technology; perceived realism; perceived ease of use; perceived usefulness), and implementation. These findings help us understand how an immersive experience can play an impactful role in enhancing agricultural safety. The feasibility of ARISE sheds light on the potential of AR technology for an innovative safety education program.

ЭКСПЕРИМЕНТАЛЬНЫЕ И ТЕОРЕТИЧЕСККИЕ ИССЛЕДОВАНИЯ ЖЕЛЕЗОБЕТОННЫХ ПЛОСКИХ ПЕРЕКРЫТИЙ ПРИ УДАЛЕНИИ ЦЕНТРАЛЬНОЙ ОПОРЫ

The paper experimentally and theoretically considers the issues of assessing the robustness of reinforced concrete structural systems with flat slabs in an accidental design situation. The methodolody of experimental studies for two scale models of a flat slab fragment in the case of removal of the central support under static (sample FS-1) and dynamic (sample FS-2) loading are presented. Based on the data obtained, the analysis of the main mechanisms of resistance of flat slabs to progressive collapse was carried out. The article presents a theoretical approach to a direct quantitative assessment of robustness, which is based on the provisions of the energy balance of a damaged structural system in an accidental design situation. The proposed solutions make it possible to determine the non-linear quasi-static "load-displacement" reaction and the ultimate dynamic resistance for reinforced concrete structural systems with flat slabs in the case of removal of the vertical key element.

Design of intakes and outfalls to avoid risks during operation

The authors, engineers of the Consulting Company Increa, have significant and valuable experience in the design of marine installations (intake and outfall pipelines and intake structures) for desalination plants (Pita, 2014 and Pita, 2019). Increa’s engineers have been designing marine pipelines and structures for multiple plants throughout the world and in various different operating environments. This paper describes some of the problems that can be experienced during the operation of desalination plants and the way these can be prevented during the design stage. Proper design of marine installations should consider the most probable situations that can occur. In addition to normal operation, designers should consider accidental situations and the risks associated with these should also be evaluated and mitigated.

Practical application of pedagogical diagnostics to assess cadets' knowledge of lifeboat and raft equipment

An essential component of the professional training of maritime cadets is their readiness to act skilfully in any accident or emergency situation. When a ship is destroyed, it is the responsibility of every crew member to know how to use the salvage equipment available on board and how to use it promptly and effectively. The subject of the study is the professional training of maritime cadets. The authors of the article substantiate and disclose the main points of the methodology for assessing the knowledge of lifeboat and raft equipment of maritime cadets. The methodology aims to serve in the convention training process as well as in the final certification of cadets in the Initial Security Training discipline. The article contains the results of the experimental work: testing cadets on the test-questionnaire of the considered method, their analysis and interpretation, as well as the mathematical processing of the results, proving the reliability and validity of this method. The authors agree that the use of the developed methodology in the practice of convention training in all maritime educational organisations would be appropriate and effective.

Obstacle detection on rail-tracks: Study on situations for requirement specification

With the advance in technologies that enable assisted and driverless operations, developing detection systems that can detect any obstacle within a train's clearance gauge is critical. As a first step, it is vital to understand the hazardous track situations resulting in railway accidents. Currently, to the best of our knowledge, no public railway databases that document accident situations focus on obstacles on or near the tracks. In this study, we collect railway accident reports from different sources and establish a database2 of collisions and near-misses, including descriptions of the obstacle involved. Furthermore, our analysis provides a comprehensive list of obstacle classes and critical scenarios to consider during the development and testing of obstacle detection frameworks for a railway system.

Analytical Study of an IOT-based Accident Detection and Information Management System

Accidents wreak havoc on victims, costing them valuable time and money. After thorough investigation, it has been shown that the majority of accidents result in fatalities as a result of poor communication with the relevant medical authorities and the ensuing dearth of prompt medical attention. Several sensor nodes are combined in a single system to forecast likely accident combinations. Lab view-based simulation was used to handlepossible conditions for an accident to happen. With the IoT Interface, theproposed design would enable a novel model in the vehicular communication system to recognize various accident situations and provide associated information to the needy. The proposed model would handle all potential combinations and comparative analyses from low to high end cars, as well as provide a strategy framework for future IoT enabled v2v communication networks.

Experimental and theoretical study of the reinforced concrete flat slabs with the central support loss

The paper experimentally and theoretically considers the issues of assessing the robustness and resistance to progressive collapse of a flat slab with a sudden removal of the central support.
 The results of testing two scale models of a fragment of a flat ceiling in the case of removal of the central support under static (specimen FS-1) and dynamic (specimen FS-2) loading are presented and analyzed.
 A theoretical approach to the quantitative assessment of robustness was tested, which is based on the provisions of the energy balance of a damaged structural system in an accidental design situation.

Innovative Accident Tolerant Fuel Materials May Help Extending the Life of Light Water Reactors: A Perspective

One of the main sources of clean electricity in the civilian power grid comes from light water reactors (LWRs). Some of these LWRs are being decommissioned prematurely because they may not be economically sustainable. It is proposed that the use of accident-tolerant fuel concepts may enable for LWR plant operation extension by making them safer and more economically competitive to operate. For example, the use of iron-chromium-aluminum (FeCrAl) alloys for the cladding of the fuel would not only reduce the risk of catastrophic reaction between the cladding and its environment in the case of a loss of coolant accident situation but also, for example, allow for higher fuel burnup during normal plant operation.

The influence on microorganisms of heavy metals from refiner’s spent desulphurisation catalysts

ABSTRACT Refinery wastes generated in conventional crude oil refining processes, or in accidental situations, are complex substrates for treatment and disposal. Petroleum desulphurisation catalysts can also be hazardous refinery waste. They contain various metals, such as cobalt, molybdenum, nickel and tungsten. In this paper, three petroleum refiner’s spent desulphurisation catalysts were investigated. These catalysts were not suitable for recycling and, therefore, were classified as hazardous waste. They were chemically characterised, including phase composition and their effect on a consortium of microorganisms used in the process of bioremediation. Catalysts contained up to 2.26 g kg−1 of total petroleum hydrocarbons, up to 56.7 g kg−1 of iron, 18.6 g kg−1 of molybdenum, and less than 0.1 mg kg−1 each of cobalt and nickel. These obtained results show that bioremediation of such waste is possible.

Unmanned stationary online monitoring system based on buoy for marine gamma radioactivity

Research on unmanned online monitoring equipment for marine radioactivity surrounding nuclear power plants is of great significance. In this work, a small radioactivity monitoring system based on buoy was designed and manufactured for the emergency situation of nuclear accidents. The core of the radioactivity monitoring system is the underwater gamma spectrometer. The spectrometer can respond to gamma rays from 60 keV to 3 MeV, and can identify the nuclides whose characteristic rays belong to this energy range. The detection efficiency curve was calculated through Monte Carlo simulation and verified in a standard liquid source. A data acquisition processor was also designed to coordinate the detectors in the system and wirelessly transmit online monitoring data. Three experiments were carried out in the seawater around the Tianwan Nuclear Power Plant in Lianyungang, China using this online marine radioactivity monitoring system based on buoys. The stability and radioactivity monitoring capabilities of the system have been verified.

Vehicle Escape Mechanism

Abstract: The Idea is to make an Automated Vehicle Escape Mechanism or a Vehicle Escape device which would help the Passengers of the Car to get out in case of Certain Accidental Situations such as Drowning of Car and Car flipped Upside Down. Mechanism or a device used for breaking of window. Due to which person or people can be able to get out of car through window or windshield. In the case of drowning of car, window or glass which is not under water can be detected and breaks for getting out of car at the right time. The device is automatic as well as manual switch. Different types of sensors are involved for different situation scenarios.

Predicting Accident Vulnerable Situation and Extracting Scenarios of Automated Vehicleusing Vision Transformer Method Based on Vision Data

Predicting Accident Vulnerable Situation and Extracting Scenarios of Automated Vehicleusing Vision Transformer Method Based on Vision Data

Risk communication in the recovery phase after a nuclear accident: the contribution of the “co-expertise process”

Risk communication in post-nuclear accident situations faces many challenges related to the limited knowledge of experts about the actual situation in the affected communities, as well as of the affected people about radiological risk combined with their distrust of authorities and experts. In such an anxiety-provoking context, the co-expertise approach recommended by the ICRP combining technical expertise, citizen participation and two-way communication has shown that it was an effective approach for restoring trust between the experts and the people concerned and developing, among the latter, a practical radiological protection culture. In essence, technical-oriented risk communication is not sufficient alone. A dialogue with affected people is necessary in combination with measurements of radiation associated with their daily life in order to gain their participation in the co-expertise process and to progressively restore confidence in them and trust in authorities and experts. The article highlights the salient features of the co-expertise process in relation to risk communication.

Detection of accident situation by machine learning methods using traffic announcements: the case of metropol Istanbul

Information about the reality of the traffic accident, the clearness of the roads and the status of the accident can be obtained from the traffic accident announcements. By using the words in the radio or telephone announcements, you can be informed about the status of the accident. Inferences can be made with machine learning methods using a large number of data. In this study, the accident situation was classified using three different machine learning methods using radio and telephone announcements in Istanbul in Turkey. The dataset contains 156.856 announcement data. Classifications were performed using Artificial Neural Network (ANN), k-Nearest Neighbor (kNN) and Decision Tree (DT) machine learning methods. Classification success was 92.1% in the classification made with the ANN model, 91% in the classification made with the kNN model, and 89.8% in the classification made with the DT model. Classification performances of the models were also analyzed with precision, recall, F-1 Score and specificity metrics. In addition, the estimation abilities of the models with ROC curves and AUC values were analyzed. In addition, the training and testing times of the models were also analyzed. It will be possible to use the suggested models to automatically detect the accident situation from the announcements. In this way, it is thought that the most accurate direction can be made by obtaining information about crew orientation, traffic jams and the size of the accident.

청년 사회활동에서 배움의 의미 탐색을 위한 질적 사례연구

Objectives This study was conducted for the purpose of in-depth exploration of the meaning of learning derived from the process of youth forming groups voluntarily and experiencing social activities based on the three-dimensional model of experiential learning. Methods This study was conducted as a qualitative case study method. First, through the literature review, the researchers' initial problem consciousness, the main point and problem of research were drawn. Second, in order to collect qualitative data, in-depth interviews were conducted after selecting 6 research participants through intentional sampling among young people who had been social active for more than 5 years. The average active years of the study participants was 6 years and 8 months, and their average age was 26 years. Third, qualitative data analysis was conducted through constant comparison method, and in the categorized process, the words and phrase used by study participants were utilized. Finally, to get the validity and reliability of the research results, triangulation, researchers’ check and peer-review were performed. Results First, the content dimension consisted of six categories related to knowledge, understanding, and function, and derived the meaning of learning that youth found opportunities to understand themselves in accidental situations by participating in social activities. Second, the incentive dimension consisted of six categories of motivation, will, and emotion, and it was derived as a meaning of learning that youth actively explored new methods to maintain balance between their minds and bodies. Third, the social dimension consisted of five categories related to behavior, dialogue, and cooperation, and was derived as a meaning of learning that an individual's worldview was expanded through interactions between various resources related to youth. Conclusions The suggestion for the above research results was that first, it should be viewed as a research object and learner that could characterize youth in various ways. Second, learner participation should be discussed from a broad perspective that encompasses how to help learners utilize knowledge in connection with outside of the educational system. Third, educational institutions should seek an open learning ecosystem that considers not only the area of education and learning, but also the daily life of individuals. Fourth, educational support should be provided considering that the current youth requires an experience suitable for themselves.

Rolling Bearing Fault Detection System and Experiment Based on Deep Learning.

The current situation of frequent small-scale accidents shows that the existing methods have not completely solved the problem of bearing failures, and new research methods need to be used to complete the study of bearing failures. To prevent the failure of rolling bearings and meet the need for timely detection of faults, this research is based on deep learning. Using the combination of deep transfer learning and metric learning methods, the identification and analysis of bearing multi-state vibration signals under different working conditions are carried out. The combination of SSAE-based similarity measurement criteria and deep transfer learning can reduce the differences between different domains. It is difficult to distinguish the data samples at the boundary and diagnose the problems that the physical meaning is difficult to understand. Through the bearing fault diagnosis analysis, the validity of the deep learning diagnosis model proposed in this paper is verified. The results show that the detection accuracy of the rolling bearing fault detection method based on LCM-SSAE is 0.6 percentage points higher than that of the rolling bearing fault detection method based on SSAE, which proves that the method is suitable for the fault detection of rolling bearing, and it also shows the effectiveness and robustness of the fault detection system of rolling bearing.

Safety Production Supervision of Industrial Enterprises Based on Deep Learning and Artificial Intelligence

Since the beginning of the 21st century, with the continuous growth and improvement of the comprehensive strength of our national economy and the continuous improvement of our modern industrial machinery and equipment, the level of safety technology, production level, and quality management level see continuous steady improvement, resulting in the rapid economic growth of chemical industries in China in recent years. In recent years, chemicals have been widely used and demand is increasing. However, the physical properties of some chemical substances are very unstable and vary according to process conditions, making it difficult to control. At the same time, safety issues have become a major “red warning” for industrial enterprises. Various safety incidents have attracted social attention, and the chemical industry has also learned from them, sounding the safety alarm for itself and reviewing its own shortcomings, and taking improvement measures. Therefore, it is obviously necessary to always emphasize the concept of “safety first, prevention first, and comprehensive management” to prevent enterprise safety accidents. It is necessary to regularly investigate and analyze the situation of safety accidents to summarize and continuously improve. This is the most important thing for enterprises to prevent the continuous occurrence of safety accidents in a good and effective way. Regularly analyzing, summarizing, and improving safety issues are the best way to prevent accidents. Deep learning mainly relies on letting computers or other electronic devices perform iterative learning on a large number of data samples according to the rules defined by the program. The computer after learning will have the analysis ability similar to humans, but its analysis ability is limited to the range of the sample data to be learned. Artificial intelligence technology realizes an operation system that simulates human thinking through the definition of algorithms and programs. The use of deep learning and artificial intelligence in industrial enterprise safety production supervision can realize enterprise safety production supervision, early warning, and intelligent operation. Without the security of the production chain, a business cannot develop. Based on the basic theory of safety supervision and early warning in the field of enterprise safety production and related knowledge of artificial intelligence, this paper studies the work safety in the supervision and early warning mechanism abides by the selection principle of the management system, safety production indicators and indicator system, and conducts work based on the production work data of industrial plants. Reasonable safety supervision and early warning mechanism provide technical assistance for effectively controlling safety accidents in production and management measures to improve enterprise safety.

Analysis of steel frame under selected accidental situation

Analysis of steel frame under selected accidental situation

Research on the Risk Current Situation and Countermeasures of Sudden Environmental Accidents in Anshun City

Research on the Risk Current Situation and Countermeasures of Sudden Environmental Accidents in Anshun City

Luminescence studies in touch screen protective glass of mobile phones for its possible application as retrospective dosimeter

Thermoluminescence (TL) properties of display glass from three mobile phone brands were investigated for its application as a dosimeter in accident situation. The glow curves show TL peak between 520 and 550 K and have broad emission spectrum from 300 to 650 nm with a maximum at about 460 nm and a minor shoulder at about 590 nm. Thermal quenching studies of all three display glasses show that there is no thermal quenching. Fading studies show that the decay of the signal is purely thermal in nature and the rate of fading is different from that reported in the literature. A suitable protocol in order to minimise the effect of fading and the inherent background signal was used for dose recovery. Dose recovery tests carried out show that the glass can be used from a few mGy up to the studied dose of 5 Gy.