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This study presents a novel approach to emergency vehicle classification that leverages a comprehensive set of informative audio features to distinguish between ambulance sirens, fire truck sirens, and traffic noise. A unique contribution lies in combining time domain features, including root mean square (RMS) and zero-crossing rate, to capture the temporal characteristics, like signal energy changes, with frequency domain features derived from short-time Fourier transform (STFT). These include spectral centroid, spectral bandwidth, and spectral roll-off, providing insights into the sound's frequency content for differentiating siren patterns from traffic noise. Additionally, Mel-frequency cepstral coefficients (MFCCs) are incorporated to capture the human-like auditory perception of the spectral information. This combination captures both temporal and spectral characteristics of the audio signals, enhancing the model's ability to discriminate between emergency vehicles and traffic noise compared to using features from a single domain. A significant contribution of this study is the integration of data augmentation techniques that replicate real-world conditions, including the Doppler effect and noise environment considerations. This study further investigates the effectiveness of different machine learning algorithms applied to the extracted features, performing a comparative analysis to determine the most effective classifier for this task. This analysis reveals that the support vector machine (SVM) achieves the highest accuracy of 99.5%, followed by random forest (RF) and k-nearest neighbors (KNNs) at 98.5%, while AdaBoost lags at 96.0% and long short-term memory (LSTM) has an accuracy of 93%. We also demonstrate the effectiveness of a stacked ensemble classifier, and utilizing these base learners achieves an accuracy of 99.5%. Furthermore, this study conducted leave-one-out cross-validation (LOOCV) to validate the results, with SVM and RF achieving accuracies of 98.5%, followed by KNN and AdaBoost, which are 97.0% and 90.5%. These findings indicate the superior performance of advanced ML techniques in emergency vehicle classification. [ABSTRACT FROM AUTHOR]

An integrated quantitative risk analysis methodology based on the BT (bow-tie) and FBN (fuzzy Bayesian network) is developed in the present study to evaluate the risk evolution from causes to consequences of engine room fires on ships. Given limited historical statistics on engine room fire accidents, a probabilistic estimation model based on fuzzy sets is employed to determine prior probabilities of BN nodes. A case study of the engine room fire is carried out to demonstrate the soundness and applicability of the proposed methodology. Moreover, scenario analysis is implemented to assess how safety barriers can mitigate escalation of consequences triggered by engine room fires, while sensitivity analysis ranks critical hazards and quantifies correlations between different consequences and risk events within engine room fires. The results indicate that mechanical faults, improper bunker operation, improper maintenance, circuit overload or short circuit and insulation aging or damage are the main direct risk events triggering engine room fires on ships. The effectiveness of safety barrier (fire extinguishing devices) can play a decisive role in preventing further escalation of controlled fire incidents. [ABSTRACT FROM AUTHOR]

This article studies the influence of structural parameters of the optimization model for the gas–liquid mixing device of a fire truck (compressed air foam lift fire truck, model JP21/G2, made in China) on the liquid phase volume fraction, static pressure, velocity streamline, and the influence of smaller flow rates on the mixing effect. By using the computational fluid dynamics (CFD) software FLUENT 2021 R2, numerical simulations were conducted on the fluid domain model of the gas–liquid mixing device of the JP21/G2 fire truck. The changes in the mixing effect time dimension, liquid phase volume fraction, static pressure, and velocity streamline inside the gas–liquid mixing device were obtained. The optimal mixer structure combination in practical applications was inferred through orthogonal experiments, and the influence of flow rate on the optimal pipe diameter and shortest mixing distance was obtained through variable flow rate simulation experiments. The numerical simulation results show that the presence of bent pipes in the JP21/G2 real vehicle model hinders the gas–liquid mixing process. A straight pipe section of at least 8 m was added after the bent pipe to ensure the mixing effect. The optimal parameter combination for orthogonal experiments had an accurate value of 50°-50°-220 mm. Under the same pipe diameter, using a larger flow rate can achieve better mixing effects. [ABSTRACT FROM AUTHOR]

In order to realize the online diagnosis and prediction of gasoline engine fire faults, this paper proposes an improved misfire fault detection algorithm model based on YOLOv8 for sound signals of gasoline engines. The improvement involves substituting a C2f module in the YOLOv8 backbone network by a BiFormer attention module and another C2f module substituted by a CBAM module that combines channel and spatial attention mechanisms which enhance the neural network's capacity to extract the complex features. The normal and misfire sound signals of a gasoline engine are processed by wavelet transformation and converted to time–frequency images for the training, verification, and testing of convolutional neural network. The experimental results show that the precision of the improved YOLOv8 algorithm model is 99.71% for gasoline engine fire fault tests, which is 2 percentage points higher than for the YOLOv8 network model. The diagnosis time of each sound is less than 100 ms, making it suitable for developing IoT devices for gasoline engine misfire fault diagnosis and driverless vehicles. [ABSTRACT FROM AUTHOR]

Geo-mat system is considered as an alternative to a flexible or rigid pavement that can be used for fire lanes, parking areas, or roadway shoulders for cars, pickup trucks, utility/delivery trucks, and fire trucks. Also, it can be used to reduce the thickness of the base course in unpaved roads. In this investigation, six cyclic loading tests were conducted to assess the efficacy of the geo-mat system on weak to intermediate subgrade layers, characterized by California Bearing Ratios (CBR) of 2%, 3%, and 4%. Control sections, consisting of a 300-mm thick base course over subgrade layers with CBR values of 2% or 4%, were compared against the test sections comprising a geo-mat system placed atop aggregates of varied thickness (150 or 50 mm) on a geotextile layer over the same subgrade layers. Each test section underwent cyclic loading, progressively increasing from 17.8 to 71.2 kN using a 300-mm diameter steel plate. The results demonstrate that the geo-mat system, particularly when placed over a 150 mm-thick aggregate base, exhibited comparable or superior performance to the control sections with a 300 mm thickness, especially under substantial cyclic loading. This was evidenced by the reduced permanent deformations beneath the loading plate and a wider load distribution. The increase of the subgrade CBR value reduced the permanent deformation significantly. When the intermediate subgrade with a 4% CBR was used, the geo-mat system played a more important role than the aggregate base and the base thickness had a minor effect on the performance. [ABSTRACT FROM AUTHOR]

Emergency response vehicles (ERVs) need to move fast, which can lead to potential accidents. A system is proposed to utilize connected vehicle technology for facilitating the movement of multiple ERVs in a two-way roadway. A biobjective model was developed to minimize the ERVs' travel/response times while maximizing safety. The proposed system can help non-ERVs stop in assigned locations and wait for the ERVs to pass. According to mission priority, different types of ERVs (ambulance, fire truck, and police car) can use a travel lane from the opposite direction (contraflow) to move faster. A hybrid nondominated sorting genetic algorithm II-particle swarm optimization (NSGAII-PSO) approach was used to solve the model faster than CPLEX. To evaluate the system's performance, different experiments, including various road types, numbers and types of ERVs, direction priorities, and congestion levels, have been conducted. Results demonstrate that the proposed system can improve the travel time of ERVs that have the priority to use the contraflow lane in cases where the other side of the roadway is less congested and has a shoulder (when opposing ERVs use a two-way roadway simultaneously). The proposed system can eliminate weaving and passing among non-ERVs in all cases compared to two current strategies (going to the right edge and vacating the ERV lane without receiving instructions). [ABSTRACT FROM AUTHOR]

This study investigates the kickback force (FK) experienced by firefighters during fire suppression using hoses of varying diameters and different nozzle sizes. Rigorous ground tests were conducted, where a fire engine was employed to propel water through a 200 ft hose line, simulating real-life firefighting scenarios while using the hip grip and clamp techniques for hose advancement. Two distinct hose sizes, 13/4 and 21/2 in., were employed with solid stream nozzles of varying diameters, facilitating the examination of kickback forces at different attacking angles. The findings substantiate that the FK exhibits variability in response to changes in the attacking angle when utilizing the clamp technique, which encompasses angles of 45°, 30°, and 15°. The 45° angle exhibits the lowest force, while the 30° angle manifests the highest force, demonstrating a notable discrepancy of up to 25% compared to the 45° scenario. The FK observed at the 15° angle for the clamp technique closely approximates the corresponding values derived from the hip grip hose advancement method. The results also underscore the necessity of regarding the NFPA nozzle reaction force as an integral component of the all-encompassing FK experienced by firefighters during hose line operations. The NFPA nozzle reaction force resulted significantly below the actual FK observed in all tested experiments, displaying the most substantial difference of 50% in the case of the 30° angle utilizing the clamp technique. [ABSTRACT FROM AUTHOR]

To ensure the safe protection of marine engine systems, it is necessary to explore the hot surface ignition (HSI) characteristics of marine diesel in ship environments. However, an accurate model describing these complex characteristics is still not available. In this work, a new experimental method is proposed in order to enhance prediction performance by integrating testing data of the characteristics of HSI of marine diesel. The sensitivity of HSI is determined by various factors such as surface parameters, flow state, and the ship's environment. According to variations in the HSI status of marine diesel in an engine room, the HSI probability is distributed in three phases. It is essential to determine whether the presence of marine diesel or surrounding items can intensify the risk of an initial fire beginning in the engine room. A vapor plume model was developed to describe the relationship between HSI height and initial specific buoyancy flux in vertical space. Further, field distribution revealed significant variation in the increase in temperature between 200 and 300 mm of vertical height, indicating a region of initial HSI. In addition, increasing surface temperature did not result in a significant change in ignition delay time. After reaching a temperature of 773 K, the ignition delay time remained around 0.48 s, regardless of how much the hot surface temperature increased. This study reveals the HSI evolution of marine diesel in a ship engine room and develops data-based predictive models for evaluating the safety of HSI parameters during initial accident assessments. The results show that the goodness of fit of the predictive models reached above 0.964. On the basis of the predicted results, the HSI characteristics of marine diesel in engine rooms could be gleaned by actively determining the parameters of risk. [ABSTRACT FROM AUTHOR]

How to prioritise multiple objectives is a common dilemma of daily life. A simple and effective decision rule is to focus resources when the tasks are difficult, and divide when tasks are easy. Nonetheless, in experimental paradigms of this dilemma, participants make highly variable and suboptimal strategic decisions when asked to allocate resources to two competing goals that vary in difficulty. We developed a new version in which participants had to choose where to park a fire truck between houses of varying distances apart. Unlike in the previous versions of the dilemma, participants approached the optimal strategy in this task. Three key differences between the fire truck version and previous versions of the task were investigated: (1) Framing (whether the objectives are familiar or abstract), by comparing a group who placed cartoon trucks between houses to a group performing the same task with abstract shapes; (2) Agency (how much of the task is under the participants' direct control), by comparing groups who controlled the movement of the truck to those who did not; (3) Uncertainty, by adding variability to the driving speed of the truck to make success or failure on a given trial more difficult to predict. Framing and agency did not influence strategic decisions. When adding variability to outcomes, however, decisions shifted away from optimal. The results suggest choices become more variable when the outcome is less certain, consistent with exploration of response alternatives triggered by an inability to predict success. [ABSTRACT FROM AUTHOR]

Climate change has led to an increase in the frequency and intensity of natural disasters, necessitating the development of efficient crisis management strategies for population sheltering. However, existing research on this topic primarily focuses on the use of public resources such as ambulances and fire trucks, which may sometimes be insufficient due to high demand and impacted locations, worsening the shortage of resources. This research introduces an ontology-based crisis simulation system for population sheltering management that focuses on the integration and distribution of citizen–volunteer drivers/vehicles into the evacuation process. Recognizing the limitations of public resources in current crisis management models, our approach incorporates citizen resources to enhance overall evacuation capacity. We develop an ontology to standardize crisis management knowledge, frame vehicle distribution as a recommendation problem, and design a simulation module incorporating a constraint-based recommender system. The proposed scenario illustrates how the simulation system can recommend citizen resources during crisis situations by considering the constraints to be satisfied. With our system, we aim at helping stakeholders to be prepared for various disaster scenarios: optimizing resource allocation and reducing time to make decisions by decision-makers. [ABSTRACT FROM AUTHOR]

Fuel leakage in the ship engine room tends to form the dynamically evolving spill fires instead of pool fires, which are full of danger and have been scarcely concerned. In this work, one-dimensional spill fire experiments with different fuel leakage rates and substrate slopes are tentatively conducted in a well-confined model-scale ship engine room to reveal their fire dynamics characteristics. It is found that the development of spill fires in the ship engine room is quite different from that in open space, and it, to a great extent, depends on the specific leakage rate and substrate slope. Typically, the spill fire in the ship engine room can be divided into five stages: continuous spreading, steady burning, burning shrinkage, quasi-steady burning, and decay stages, while the steady or quasi-steady stage does not always appear for all cases. In the quasi-steady burning stage, the thickness of the critical oil film is between 0.97 and 1.55 mm, smaller than that in the open space. The special fire phenomena are mainly attributed to the confined boundary condition, where the competing mechanisms of fuel control and ventilation control effects will collectively influence the development of the spill fire in the ship engine room. Characteristic parameters of spill fires in ship engine room, including flame spread rate, burning area, burning rate, and flame height, are also quantitatively analyzed. [ABSTRACT FROM AUTHOR]

Fire accidents often pose severe threats to the safety of steel bridges. This paper presents the numerical study of the Runyang Suspension Bridge (RSB) fire accident with an emphasis on its in-fire thermal effect on the hangers. This fire accident was caused by the collision of two heavy-goods vehicles (HGVs) on March 4, 2017, and lasted for 1.5 h. Based on the simulated temperature, the structural safety of four burned hangers during and after the fire accident was evaluated and compared. In general, the simulation results are consistent with the actual situation, and the evidence for the replacement of the hangers is sufficient. The influence of wind parameters and cooling actions on the hanger safety is also discussed. It is found that the wind parameters affect the directions and tilts of the flame, so that the highest temperature and the corresponding height are influenced accordingly. Also, the efficiency of the water-cooling method is influenced by the intervention time of fire engines. If water spraying is conducted within 30 min from fire initiation, the safety of the hangers during and after the fire could be improved, as compared with air cooling. [ABSTRACT FROM AUTHOR]

We describe the physics of the "Windkessel effect" and its role in smoothing the output of water produced by piston-driven pumps found in early fire engines and modern residential well houses. We also construct a simple, analytical model of its operation and apply this model to the Windkessel in Richard Newsham's 1725 fire engine. We find that Newsham's Windkessel reduces the variations in the pump output stream from a high of 80% to a low of 16%. [ABSTRACT FROM AUTHOR]

The phenomena of droplet impact on the heated liquid surface are difficult to unify due to complexity of the interaction, but this process has significance for the study such as direct fuel injection in internal-combustion engines or pool fire suppression. A series of experiments on a water droplet impacting on the heated glycerol surface are carried under various surface temperatures (111.4°C ≤ Tgly ≤ 270.6°C) and impact Weber number (50.5 ≤ We ≤ 297.9). Four regimes, including penetration, crater–jet, vapor explosion and crater–jet–vapor explosion, are discussed in detail. With increase in the Tgly and We, the phenomena transform easier from penetration to crater–jet. The jet formation is affected by the interaction of vapor explosion (Tgly ≥ 222.3°C) and this process is mainly caused by two factors: the vapor explosion appears at the liquid-liquid interface and the vapor explosion time is equal to 4.8–15.8 ms. Increase in Tgly and We prolongs the crater evolution process and leads to growth of the maximum dimensionless crater depth (hmax). The contribution index shows that hmax is significantly increased by the vapor explosion and continued to increase for the higher We. Furthermore, the secondary breakup of droplets is observed at Tgly ≥ 222.3°C and this phenomenon mainly includes the processes of puffing, sputtering, vaporization and deformation. [ABSTRACT FROM AUTHOR]

This study investigates collaborative route mapping for a collection of connected automated vehicles (CAVs) traversing multi-lane pathways, with a particular emphasis on intersections without traffic signals. A distinctive feature of our research is the prioritization of emergency vehicles, such as ambulances and fire engines, according to their velocity demands. Additionally, a comprehensive analysis of the ethical ramifications of implementing such a prioritised system is engaged, while it is notable that in most of the existing studies, the ethical evaluation of intelligent transportation modalities is neglected. From a technical aspect, trajectories for CAVs in current models tend to be either inflexible or congruent with the collective formation of the fleet. Concurrently, the pre-set velocities for CAVs frequently demonstrate a lack of adaptability, which impedes cohesive operation. Moreover, there exists a pronounced deficiency in catering to the prioritization needs of emergency vehicles within these models. The current research endeavours to address these shortcomings by formulating the intersection management as an optimal control problem (OCP). This formulation enables CAVs to modulate their velocities in response to practical objectives, sidestepping fixed lane regulations at junctions. The control framework also encompasses autonomous vehicles of diverse sizes and velocities. An Adaptive Stepwise Optimization (ASO) methodology is proposed to augment the efficacy of the OCP resolution. [ABSTRACT FROM AUTHOR]

This paper discloses an early performed study on the fire-resistance design framework for cable-stayed bridges, including (1) the identification of potential fire scenarios and the calculation of fire return periods, (2) computational fluid dynamics simulation of the fire environment and analytical models of flame dimensions, (3) coupling thermomechanical finite element simulation to capture the bridge response, and (4) the determination of fire prevention and protection measures. The framework was then utilized on a two-level steel cable-stayed bridge. The return periods of vehicle fires on the upper, lower, and two-level decks were 1.13, 1.88, and 0.71 years, respectively. Numerical results showed that the bridge could resist car, bus, and truck fires but not tanker fires. Regulative fire prevention measures were undertaken to suppress the fire risk on the bridge, and drainages were designed to exclude the accumulation of fuel leaks. Although the work was finished in 2007, the proposed framework can still be a prototype for designing cable-stayed bridges against fires nowadays. From the current view, the framework can be improved by incorporating traffic data to calculate the fire return periods, using more precise fire models developed for bridges, and quantifying the cost-benefit of employing fire prevention and protection measures. [ABSTRACT FROM AUTHOR]

This article is a conversation between Loren J. Naidoo and Dr. Marcus Dickson about the use of artificial intelligence (AI) in the context of I-O psychology instruction. They discuss faculty fears about AI, particularly regarding cheating and the inability to assess students' understanding of the work. They also explore the challenges of detecting AI misuse and plagiarism, as well as the potential impact of AI on assessment validity. The conversation highlights the need for clear expectations and norms regarding the use of AI in the classroom and the importance of adapting teaching methods to the changing technological landscape. [Extracted from the article]