Improve Safety Level Research Articles

Improving safety in complex systems: A review of integration of functional resonance analysis method with semi‐quantitative and quantitative approaches

AbstractFunctional resonance analysis method (FRAM) is extensively employed in analyzing and managing performance variabilities. Additionally, semi‐quantitative and quantitative methods have been increasingly integrated with the FRAM to analyze complex socio‐technical systems to improve safety levels. This review article presents a comprehensive and updated survey of current literature focused on semi‐quantitative and quantitative methods employed for quantifying performance variabilities and exploring aggregation/propagation rules. A total of 1659 studies published between 2012 and March 2024 from various scientific databases were systematically examined using preferred reporting items for systematic review and meta‐analysis, identifying 29 studies that met inclusion criteria. The identified studies were categorized into four groups based on the quantitative methods employed: Monte Carlo simulation, fuzzy logic, cognitive reliability and error analysis method, and miscellaneous approaches. While different methodologies had unique strengths, they commonly relied on expert judgment for data collection, whether for defining probability distributions in Monte Carlo simulations, membership functions, and fuzzy rule bases in fuzzy inference systems, or selecting common performance conditions, determining their interrelationships, and assigning scores. Addressing bias from expert judgment in assessing performance variabilities can be achieved by using suitable experts' opinions integration techniques, and leading safety indicators in the analysis.

Dynamic safety management model for rail traffic control

In rail transport, increasing emphasis has been placed in recent years on improving safety levels. Therefore, more requirements and legal documents require risk analyses to be carried out at various stages of investment implementation. One of the leading legal documents that introduce the obligation to monitor risk is Directive (EU) 2016/798 of the European Parliament and of the Council of 11 May 2016 on railway safety and Commission Implementing Regulation (EU) No 402/2013 of 30 April 2013 on the common safety method for risk evaluation and assessment and re-pealing Regulation (EC) No 352/2009. Additionally, for traffic control systems, the requirements of CENELEC standards are mandatory. These documents present the subject of safety level and show its relation with the safety targets defined in the railway system, including the different ways of measuring them. Methods are also available to analyse the safety level of railway system components in detail, both at the level of individual components, subsystems, and the whole national railway system. However, after conducting an in-depth analysis of the literature, the authors of the article indicate that these methods are not consistent with each other. There is no method defined to present the direct relation of the safety level of the components of the system on the achievement of safety targets for the national railway system. The research and analysis aimed to define an approach, a method that would meet all legal requirements but at the same time would allow to clearly and reliably determine the safety level of the railway system. To define a unified approach, the authors of the article propose to develop a model of a dynamic object - a railway system safety model, which has also been verified on accurate safety data in rail transport in recent years. This model organises the process of safety management on railways and allows to determine values influencing the achievement of safety targets on an assumed level.

Benefit of wind networking for aircraft arrival scheduling in terminal manoeuvring area

The effectiveness of air traffic management depends on the amount of obtained information and the accuracy of prediction, leading to a reduction in uncertainty disturbances, and an improvement in the robustness of decision-making results. Among all controlled areas, the Terminal Manoeuvring Area (TMA) is a complex and sophisticated airspace surrounding a coordinated airport in which there exists a high density of traffic, especially with arrivals converging from different directions. With the purpose of improving safety levels and operational efficiency, this paper addresses the aircraft arrival scheduling problem at the microscopic level, integrating the meteorological uncertainty based on wind networking into the optimization model. Wind uncertainty affects the flight speed, which in turn leads to uncertainty in the flight arrival time at one waypoint. Conflict detection and resolution are performed at waypoints and links in a predefined network, based on the predicted time information from the designated route. In order to optimize the time and speed for each aircraft entering TMA, this paper proposes a mathematical model that seeks to minimize the number of potential conflicts, flight delays and the number of flights deviating from the original plan under two assumptions. The first one considers regular weather forecasts for predicting the future positions of aircraft for conflict detection. The second one investigates the potential benefit for aircraft to share their local wind measure thanks to the ADSB-IN and ADSB-OUT channels. A resolution approach is proposed combining a simulated annealing algorithm and a simulation framework. Using data from a case study with 437 flights overflying the Paris Charles de Gaulle (CDG) airport TMA, we demonstrate the validity of the proposed scheduling strategy. A performance analysis is then conducted between standard forecast and wind networking.

A new approach of integrating industry prior knowledge for HAZOP interaction

Accidents often occur in the petrochemical industry, which have a negative impact on society and the environment. Learning Process Safety Knowledge (PSK) from accident cases is essential to prevent accidents and improve safety level. Hazard and Operability Analysis (HAZOP) is a popular hazard risk analysis method. Its report contains large-scale PSK, which can provide safety analysis and decision support for the industry. Subject to the characteristics of PSK, existing researches mine them in the form of sequence labeling. However, there are two intractable problems that cause the PSK mined by the model to be inaccurate. (1) PSK in HAZOP is domain specific, which is rare or even absent in general-domain texts. (2) The entity boundaries are ambiguous. Most domain-specific entities for HAZOP lack boundary characters. Inaccurate security knowledge is not acceptable from the perspective of process safety engineering. To solve the problems, we present a PSK mining architecture with External Lexicon Prior knowledge called EDPMA, EDPMA is prior knowledge-based multi-task HAZOP knowledge mining model. Specifically, EDPMA consists of prior knowledge constructor and sequence labeling model. The prior knowledge constructor expresses prior knowledge in the form of word embedding by three steps. For the sequence annotation model, we improve its embedding and decoding layers. The former incorporated the word vectors generated by the prior knowledge constructor, and the latter added the task of entity boundary prediction. We conduct multiple evaluation experiments on HAZOP datasets. The experimental results show that the accuracy, recall and F1-score of the EDPMA model are 92.92%, 91.85% and 92.38% respectively, which is better than the existing research. Our study represents a meaningful attempt to introduce prior knowledge in HAZOP knowledge mining and makes an important contribution to intelligence the field of process safety.

Acute Development Trends of Investment-Construction Sphere

The development of various industries during crisis presupposes certain deviations from forecasts made before such situations and it should be taken into account in development strategies of industries. Identifying development trends in the investment-construction sphere during crisis can help correct strategic management of the industry, which forms an acute scientific and practical task. The goal of the research is to identify trends in development of investment and construction sphere to estimate optimum nature of its strategic management. The authors used systematization, classification and statistic analysis as methods of the research. They underline the fact that lately project bank financing has been developing vigorously, which improved safety level of holders’ investment and raised the demand on new homes market. According to the authors the Strategy of innovative development of construction industry in the Russian Federation up to 2030 makes up a fundamental document formulating the vector of its development for decades ahead. The authors came to the conclusion that today investment-construction sphere of the Russian Federation is fast developing industry and it has already restored the growth in indicators after the crisis caused by the corona virus pandemic. The outcome of the research is identified trends in the development of the investment-construction sphere in Russia during crisis and after it.

Traffic Safety Improvement via Optimizing Light Environment in Highway Tunnels

Driving in tunnel areas depends more heavily on light conditions than that on open roadways. Traditional lighting systems in highway tunnels adjust lighting parameters only caring about outside light luminance, and focus is usually on energy conservation; however, little concern is about drivers’ actual physical and psychological needs. How to leverage the enormous research progress of traffic safety, light environment, human factors engineering, and modern lighting sources to create an ideal tunnel light environment that aids with ensuring driving safety and lower interference effects caused by the change of light environment will greatly improve safety level and reduce adverse influence on drivers’ visual health in a tunnel area. An intelligent lighting control system designed with multiple influence factors are systematically considered. Based on sensor data from outside natural light conditions, target lighting parameters are determined per each lighting zone requires; then, lighting commands will be transferred and parsed by adaptive lighting controllers and modules, eventually LED lighting properties are altered step by step. This system helps a lot with optimizing tunnel lighting quality and improving drivers’ visual performance; as a result, it contributes to lower the fluctuation of drivers’ workload and get a smooth traffic flow, and ultimately this technically ensures physical and mental health of drivers in a tunnel area.

Risk analysis of construction accidents with a weighted network model considering accident level

AbstractConstruction is considered to be one of the most dangerous industries due to its wide variety of accidents and high risk. Although people have been using various means to improve safety levels, the frequent occurrence of accidents still plagues the development of this industry. Accurately grasping the characteristics and analyzing the complex relationships between the risks of different accident types are the keys to a comprehensive understanding and promotion of construction safety. Simultaneously, we need to note that the level and frequency of accidents affects the risk characteristics, but previous studies have not paid sufficient attention to these features. Using complex network theory, based on the risk factors and risk triggering relationship extracted from construction accidents and considering the accident level and the frequency of occurrences as their weights, several weighted risk networks are generated according to different accident types. Then, several network analysis metrics are introduced to reveal the characteristics of the risk network and identify the key risk factors. The analytical framework helps to pose targeted suggestions to reduce the occurrence of frequent major accidents.

The Effects of Multi-Sociodemographic Characteristics of Construction Sites Personnel on Perceptions of Safety Climate-Influencing Factors: The Construction Industry in Saudi Arabia

The construction industry in Saudi Arabia relies prominently on migrant workers of multi-sociodemographic characteristics with different perceptions of a safety climate. The exploration of the perceptions regarding the safety climate among various groups of migrant workers may help identify effective means of improving safety levels at construction sites in Saudi Arabia. This study aimed to examine the effects of multi-sociodemographic characteristics of construction site personnel on their perceptions of the factors that influence the safety climate at construction sites in Saudi Arabia. Data were collected from 401 construction site workers, employed at ongoing construction project sites in Saudi Arabia, using a designed questionnaire. A generalized, linear model approach was applied, using the single ordinal logistic regression method, to analyze the collected data. The results revealed the significant sets of sociodemographic characteristics and their associated subgroups that had significant effects on the perception of importance assigned to each safety climate-influencing factor. These findings provide a better understanding of the views of construction site personnel on the safety climate and can assist construction industry decision-makers, safety policy designers, government agencies, and stakeholders when designing better-targeted enhancement plans and strategies to improve the safety climate of construction sites, based on the sociodemographic makeup of the personnel at each construction site.

Separation safety analysis using CFD simulation and remeshing

The work is aimed to simulate the separation process of a GBU-31 bomb and empty 370 gal fuel tank from an aircraft, using the 6 – Degree Of Freedom (6-DOF) procedure and Computational Fluid Dynamics (CFD) code for body movement. The procedure has an ability to simulate the sequential release from the joints, which is necessary for the lightweight tank separation, in order to avoid a collision with an aircraft. A set of unsteady CFD simulations were calculated. Both the in-house designed 6-DOF procedure and the CFD simulation settings were validated using the wind tunnel experiment data and a Covert criterion for safety separation. Similar approach could be used to analyze the separation of other kinds of external stores and during design the deployment of anti radar chaff, flares or ejection seats. This kind of research is extremely important in the way to improve safety level of flight operations and avoid hazardous situations in the air. This work presents original results obtained by the authors.

Development of crash modification factors for intersections in Toowoomba city

ABSTRACT This research outlines the analytical approaches that may be employed to recommend multiple treatments for application to improve safety level at hazardous intersections in regional areas. Data from 106 intersections in the regional city of Toowoomba, Queensland, Australia were used in modelling and subsequent analysis. Specifically, crash prediction models were developed to estimate crash modification factors that could be used to propose remedial measures. A total of sixteen geometric and operational conditions were used as explanatory variables including the number of legs at an intersection, the availability of entering and exiting via through lanes, the presence of left-turning lanes, right-turning lanes, slip lanes, median islands, traffic control, and speed limits on the feed roads. The Empirical Bayes approach was employed to identify five hazardous intersections in Toowoomba for further investigation. The four most suitable techniques for estimating combined crash modification factors were reviewed and then used to propose effective road safety measures for the five selected hazardous intersections. Finally, this research suggests four future areas worthy of further investigation. Highlights Estimated the number of road crashes at intersections using crash prediction models. Applied the Empirical Bayes method to identify the most hazardous intersections. Combined crash modifications factors were calculated using various techniques. Identified the effective countermeasures to reduce the road crashes at hazardous intersections.

Evolution of the importance of neutron-induced reactions along the cycle of an LFR

The Lead-cooled Fast Reactor is one of the three technologies selected by the Sustainable Nuclear Energy Technology Platform that can meet future European energy needs. Several LFR concepts are now in design phase, such as MYRRHA and ALFRED, and accurate nuclear data are required for the neutronic and safety assessment of the fast reactor designs. In this work, an assessment of the evolution of the importance of neutron-induced reactions along the cycle of a reference LFR design (i.e., ALFRED) with the state-of-the-art JEFF-3.3 nuclear data library is performed. Sensitivity analyses have been carried out with MCNP6 code in order to identify the most relevant isotopes and reactions from the neutronic point of view at BoL, BoC and EoC. Furthermore, an uncertainty quantification has been performed with the SUMMON system to study the evolution of uncertainties in the keff along the reactor cycle. The results from this work provide an exhaustive picture on the influence of nuclear data on core criticality performance, identifying key quantities and nuclear data needs relevant to achieve an improved safety level for LFR.

The Renovation of the Teatro Nuovo in Spoleto: Analysis of the Acoustic Quality of an Italian Opera House

After a complete renovation work and a structural and functional improvement, the Teatro Nuovo has been returned to the city of Spoleto (Italy) and its audience as a renewed venue for the renowned global “Two Worlds Festival.” The restoration works of the theatre started in 2003 to improve safety levels and the operational functionality of the machines on the stage, including acoustic performances, to meet the current needs of the show. The local authorities (Umbria Region) committed the University of Bologna for collaborating with the Teatro Nuovo, in order to analyse and improve its acoustic quality. Two acoustic measurement campaigns, respectively before and after restoration of the theatre, were carried out in order to monitor the Concert Hall’s acoustic performance, verifying the preservation of its original acoustic features. In order to control both monoaural and spatial sound distribution, the ESS pre-equalized signal, emitted by means of an omnidirectional loudspeaker, was recorded using a dummy head and a Soundfield probe. The results of the measurements of every campaign are presented and evaluated in this paper. As shown, the acoustic performances of the theatre are globally improved and contribute to excellent perception of the acoustic environment.

Study of the influence of employee safety voice on workplace safety level of small- and medium-sized enterprises

PurposeTo improve unsafe workplace of Chinese SMEs, this paper aims to use the multi-agent simulation experiment to reveal the relationship between employees’ safety voice and safety level of enterprises.Design/methodology/approachThrough simulation of employees’ safety voice activities, enterprises’ production activities, enterprises’ safety activities, an experiment platform is built. The experiment introduces external variable of labor resource and sets four experimental situations considering whether labor resource is sufficient and whether employees’ value is significant.FindingsThe result shows that not all the employees’ safety voice can change small- and medium-sized enterprises’ safety level. When there is sufficient labor supply, employee safety voice cannot improve the safety level of enterprises; when there is short of labor and employee safety voice is strong, safety level can be effectively improved. When employees have the strikingly different value variance, safety voice of common employees cannot improve safety level of enterprises, but employee safety voice with high value can improve safety level.Originality/valueThis fully provides that under the circumstances of disappearing demographic dividend in China, improving employees’ safety awareness and reasonably using their safety voice can boost SMEs to enhance safety level.

The impact of individual and environmental interventions on income inequalities in sports participation: explorations with an agent-based model

BackgroundIncome inequalities in sports participation are shaped by a system in which individuals and the environment interact. We developed an agent-based model (ABM) that could represent this system and used it to provide a proof-of-concept of its potential to explore the impact of individual and environmental interventions on reducing inequalities in sports participation.MethodsOur ABM simulates sports participation of individuals in the Dutch city of Eindhoven. In the model, sports participation is determined by an individual’s tendency to start sports (at a fitness center, sports club or self-organized), which is influenced by attributes of individuals (i.e. age, sex, income), sports facilities (i.e. price, accessibility) and the social environment (i.e. social cohesion, social influence). Sports facilities can adapt to changes in the demand by closures or startups, which in turn influence the tendency of individuals to participate in sport. We explored the impact of five interventions scenarios.ResultsExplorative results show that providing health education, increasing the availability of sports facilities, lowering prices of facilities and improving safety levels can increase sports participation and modestly reduce absolute income inequalities in sports participation. The largest gain can be attained through health education, if the effect and reach is sufficiently large. Environmental interventions alone have a modest impact. Marked effects are only achieved after five to 10 years.ConclusionsABMs have much potential to test the population-level effects of various interventions in the context of a system. Our study highlights the challenges of ABM development and reveals gaps in empirical data. With further refinements, our model could aid in understanding and finding optimal pathways to reduce income inequalities in sports participation.

Ni@Li2O co-axial nanowire based reticular anode: Tuning electric field distribution for homogeneous lithium deposition

The employment of three-dimensional (3D) conductive scaffolds can improve safety level of metallic anodes at high rates, since they can lower down the average current density per electrode area, and thus suppress/delay the formation of metal dendrites. However, metal dendrites would still preferentially grow in the anode areas which are near to cathode, due to the more concentrated electric field strength. Here, we demonstrate that in-situ forming Li2O nano-layer on the surface of 3D Ni nanowire scaffold can not only facilitate Li+ transportation, but also render more homogenous electric field strength distribution throughout the entire anode. We observed a very low voltage hysteresis (~55 mV during 200 cycles) with enhanced cycling stability of more than 150 cycles at 3 mA cm−2. When coupling with LiFePO4 cathode, the as-assembled full cell can stably run for over 300 cycles with minimal capacity degradation and an average Columbic efficiency of 99.9% at 1 C, showing significant improvement of battery cycling stability. This work may represent a key step towards scalable production of highly safe metal anodes using electric field theory.

Evaluating the influence of road lighting on traffic safety at accesses using an artificial neural network

Objectives: This article focuses on the effect of road lighting on road safety at accesses to quantitatively analyze the relationship between road lighting and road safety.Methods: An artificial neural network (ANN) was applied in this study. This method is one of the most popular machine learning methods and does not require any predefined assumptions. This method was applied using field data collected from 10 road segments in Nanjing, Jiangsu Province, China.Results: The results show that the impact of road lighting on road safety at accesses is significant. In addition, road lighting has a greater influence when vehicle speeds are higher or the number of lanes is greater. A threshold illuminance was also found, and the results show that the safety level at accesses will become stable when reaching this value.Conclusions: Improved illuminance can decrease the speed variation among vehicles and improve safety levels. In addition, high-grade roads need better illuminance at accesses. A threshold value can also be obtained based on related variables and used to develop scientific guidelines for traffic management organizations.

Wavelet-Based Multiresolution Bispectral Analysis for Detection and Classification of Helicopter Drive-Shaft Problems

Condition monitoring and fault diagnostics in rotorcraft have significant effect on improving safety level and reducing operational and maintenance costs. In this paper, a new method is proposed for fault detection and diagnoses of AH-64D (Apache helicopter) tail rotor drive-shaft problems. The proposed method depends on decomposing signal into different frequency ranges using mother wavelet. The most informative part of the vibration signal is then determined by calculating Shannon entropy of each part. Bispectrum is calculated for this part to investigate quadratic nonlinearities in this segment. Then, search algorithm is used to extract minimum number of indicative features from the bispectrum, which are then fed to classification algorithms. In order to quantitatively evaluate the proposed method, six classification algorithms are compared against each other such as fine K-nearest neighbor (KNN), cubic KNN, quadratic discriminant analysis, linear support vector machine (SVM), Gaussian SVM, and neural network. Comparison criteria include accuracy, precision, sensitivity, F score, true alarm, recall, and error classification accuracy (ECA). The proposed method is verified using real-world vibration data collected from a dedicated AH-64D helicopter tail rotor drive train (TRDT) research test bed. The proposed algorithm proves its ability in finding minimum number of indicative features and classifying the shaft faults with superior performance.

Inherently safer design of a reactor network system: A case study

The strategies of Inherently Safer Design (ISD) provide a conceptual approach in order to design equipment and processes with substantially improved safety level. However, this may lead to a less economically attractive design. This study aimed to obtain optimal decision parameters of a reactor network system to produce allyl chloride. The objective functions were the risk level, including the severity and the frequency of the accidents, which were associated with the hazards in the network and the economic profit of the process. Based on this optimization approach, an array of optimal solutions (called Pareto front) was obtained as a trade-off between the objectives under investigation. A final design point was ultimately selected using Shannon's entropy and Bellman-Zadeh's techniques of decision making in a fuzzy environment. Results showed that the optimum reactor network leads to a highly complex system and more process control difficulties. This result was inconsistent with the simplification strategy of Inherently Safer design. In order to deal with this problem, a sensitivity analysis was performed that yielded a decision guide to decide about the desirable level of the risk as well as the optimum design.

Research on Storage Management of Hazardous Chemicals based on Internet of Things

The storage of hazardous chemicals is an important link in the supply chain. Improper storage of hazardous chemicals can cause great security risks. The occurrence of hazardous chemicals accident not only causes economic losses, but also destroys environment. Much of this is due to the lack of effective means of storing hazardous chemicals. With the continuous development of modern science and technology, many new technologies have been used, such as RFID technology in the Internet of Things. However, many enterprises are still in the traditional stage in the storage of hazardous chemicals. If RFID technology is combined with the storage of hazardous chemicals, it is an effective way to improve management efficiency, reduce operation cost and enhance safety level. In this paper, we use RFID technology to establish the storage management system and traceability system of hazardous chemicals based on Internet of Things. Through the establishment of these two systems, it can effectively save costs, reduce security risks, improve safety levels and increase consumer confidence.

Millimeter-Wave V2V Communications: Distributed Association and Beam Alignment

Recently millimeter-wave bands have been postulated as a means to accommodate the foreseen extreme bandwidth demands in vehicular communications, which result from the dissemination of sensory data to nearby vehicles for enhanced environmental awareness and improved safety level. However, the literature is particularly scarce in regards to principled resource allocation schemes that deal with the challenging radio conditions posed by the high mobility of vehicular scenarios. In this work we propose a novel framework that blends together Matching Theory and Swarm Intelligence to dynamically and efficiently pair vehicles and optimize both transmission and reception beamwidths. This is done by jointly considering Channel State Information (CSI) and Queue State Information (QSI) when establishing vehicle-to-vehicle (V2V) links. To validate the proposed framework, simulation results are presented and discussed where the throughput performance as well as the latency/reliability trade-offs of the proposed approach are assessed and compared to several baseline approaches recently proposed in the literature. The results obtained in our study show performance gains in terms of reliability and delay up to 25% for ultra-dense vehicular scenarios and on average 50% more paired vehicles that some of the baselines. These results shed light on the operational limits and practical feasibility of mmWave bands, as a viable radio access solution for future high-rate V2V communications.