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The occurrence of fire leads to unparalleled loss of resources as well as human life and hence, fire detection systems must be trustworthy and less erroneous. Real-time assessment of fire conditions through predictive learning models could lead to easier decision-making and timely rescue operations. Reported works are often restricted to the use of singular rule-based algorithms which can hardly offer a comprehensive solution by adapting to changing dynamics of fire conditions due to their static features, mostly leading to inaccurate classification. In this research, an efficient fire prediction framework has been proposed by efficiently combining the outputs of recurrent neural networks which bear the advantages of short-term predictions with long short-term memory that takes care of long-term predictions. Weights to combine multi-objective optimization functions to minimize mean absolute error and root mean square error have been designed using non-dominated sorting genetic algorithm II (NSGA-II) which offers a lower time complexity. The benchmark dataset from the NIST website has been chosen for analysis and performance validation of the proposed classifier on experimental data pertaining to different fire scenarios. A Pareto optimal front has been obtained from the proposed algorithm which represents the optimum solutions. The performance of the proposed model has been exhaustively evaluated through different factors such as accuracy, RMSE, MAE, F-Measure, binary classification rate, negative predictive value, recall and precision which justifies its contribution. The proposed model reduced RMSE by 14.95–19.88% compared to baseline machine learning models along with an enhanced accuracy of 95.05% and reduced false positive rate which is better compared to reported works along with improvement in F-Measure. Results show that the proposed NSGA-II-based RNN LSTM model accurately predicts the occurrence of fire events with reduced false alarms while maintaining a low computational overhead. [ABSTRACT FROM AUTHOR]

One of the most important purposes of installing fire alarm systems is to provide an alarm signal in the protected building in the event of a fire. Fire alarms are most often provided by networked audible warning devices. The signal must be easily and quickly detectable and identifiable so that the occupants inside can start to escape after the alarm has been sounded. This is apparently a simple expectation, but if you look at the efficiency of fire alarms as a whole, and the effects that determine whether an evacuation will occur in response to an alarm during an actual fire, the question is not so simple anymore. In this article, we will examine the circumstances that may affect the alarm signal. Among these aspects, we will focus on the soundproofing properties of building structures, including interior doors, and their effect on sound propagation. By carrying out on-site measurements, we verify the design principles used in engineering practice, looking for the factors that may influence efficiency of the fire alarms in today’s construction environment. We hypothesise that the increase in sound insulation of certain building materials and structures has an increasingly negative effect on the audibility of fire alarm signals.

[Display omitted] • FC@NF and T@CF were prepared by LBL self-assembly and soaking methods, respectively. • Fire-retardant performance and mechanism of FC@NF were investigated. • FCF-TENG was fabricated for self-powered sensing in fire scenarios. The fabrics commonly used in architectural decorative materials pose significant fire hazards due to their flammability and rapid fire spread. Moreover, the traditional fire-alarm systems may fail to function properly in complex fire environments owing to power supply disruptions. In this study, we developed a low-cost and eco-friendly flame-retardant conductive fabric-based triboelectric nanogenerator (FCF-TENG) by integrating flame-retardant conductive nylon fabric and polytetrafluoroethylene soaked cotton fabric. This nanogenerator exhibits excellent flame-retardant properties and remarkable energy-harvesting capabilities. The nylon fabric, treated with layer-by-layer self-assembly method, possesses outstanding self-extinguishing capability and melt-dripping resistance. Additionally, the electrical performance of FCF-TENG significantly improves, with a 10-fold boost in conductivity, and the open-circuit voltage increases by 84% to 92 V. Besides, by incorporating the rectifier circuit, the FCF-TENG is capable of completely charging a 1 μF capacitor within 30 s. Furthermore, the FCF-TENG was successfully applied as a self-powered sensor in the fire-alarm system and served as a safety exit indicator for evacuees and fire rescue. This work presents an effective and innovative application of multifunctional smart textiles for energy harvesting and self-powered sensing. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Wildland Fire Science is the property of Journal of Wildland Fire Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fire is one of the most common disasters for human beings. It is also one of the disasters that cameras can easily catch. In order to detect a series of building fires efficiently, a fire image detection algorithm based on YOLOv4 is proposed in this paper. This algorithm can realize the real-time fire warning by identifying all images in the video. The comparison of different evaluation results found that the YOLOv4 fire image detection algorithm using both optimization algorithms achieved higher AP and recall rates. [ABSTRACT FROM AUTHOR]

Hazards like fires occur regularly and can cost people's lives. Optimal auditory alarm signals enable laypeople to recognise dangers and to protect themselves. Existing fire alarm sound research focuses on alarm sounds and voice alerts presented singularly. We explored a combination of both and aimed to identify alarm signals that work optimally in everyday life. Thus, we conducted two online experiments: In Study 1 (N = 379), we tested eight alarm sounds regarding their typicality, their familiarity, their arousal, their valence, and their dominance. Siren-like alarm sounds were the most effective. In Study 2 (N = 206), we combined the four most effective alarm sounds with a voice alert. The voice alert reinforced ambiguity reduction, action motivation, and action intention. Hence, we suggest using alarm sounds with siren-like patterns. They should be combined with a voice alert to foster a quick and specific (target task-oriented) reaction. Practitioner summary: Warning laypeople is of great importance in time-critical hazards. In two remote testing studies (NTotal = 585), auditory alarm sounds with siren-like patterns resulted in the most distinct and emotional perception. Combining the alarm sound with a voice alert adds meaning to the alarm and fosters action intention. Abbreviations: DIN: Deutsches Institut für Normung [German Institute for Standardization]; ISO: International Organization for Standardization; Mixed MANOVA: mixed measures multivariate analysis of variance; rmMANOVA: repeated measures multivariate analysis of variance. [ABSTRACT FROM AUTHOR]

This article aims to review the literature on the effect of the suitability level of fire alarm installations, fire detectors, and portable fire extinguishers on fire protection systems in buildings. Previous research is needed to support or oppose the new hypothesis. From the research conducted, it was found that the suitability level of fire protection equipment installation is very important to increase the effectiveness of the fire protection system. Appropriate fire alarms and fire detectors, as well as suitable portable fire extinguishers, are required to detect fires as quickly as possible and provide a rapid and appropriate response to address the fire. In addition, proper maintenance of fire protection equipment is also required to ensure optimal system performance. The results of this article show that: 1) The suitability level of the fire alarm installation affects the fire protection system; 2) The suitability level of the fire detector installation affects the fire protection system; and 3) The suitability level of portable fire extinguisher installation affects the fire protection system. Increasing the suitability of the installation of fire protection equipment in buildings, can increase the effectiveness of the fire protection system and minimize the risk of fire. [ABSTRACT FROM AUTHOR]

Hydrogel circuit materials have a wide range of applications, especially in the field of flexible electronics. However, developing smart hydrogel circuit materials with remarkable properties remains a difficult problem. Based on the flexible design of circuit structure and direct inkjet 3D printing technology, we designed a printable conductive sodium alginate/graphene/carbon nanotube (SGC) ink and achieved three-dimensional graphene-based flexible circuits with high resolution and multifunction. Compared with previous work, the addition of GO, SWCNT and Ca2+ make SGC have excellent conductivity and flame retardancy. The conductivity of SGC reaches 24.11S/m, which is 3 times higher than SA hydrogel. And the LOI is above 99.7%, which is far higher than most conductive polymer. We have conducted preliminary explorations and provided theoretical basis for the 3D printing of multifunctional SGC hydrogels with complex structures, which are expected to be applied in the field of flexible circuits, fire protection and artificial electronic skin.

Fire alarms play a significantrole in situational awareness and decision‐making pertaining to evacuation for fire evacuation safety in office buildings that include small rooms, where many occupants cannot directly see fire or smoke. We conducted experiments using a mobile VR head‐mounted display to examine how individuals perceive the sound of fire alarms in rooms of different sizes. Comparing the cases of hearing the alarm sound in the large room and the small room, approximately 70% of the test participants answered that they wanted to check the situation more when they were in the small room because they could not understand the surrounding situation. Regardless of the room size, when test participants hear the early warning voice, approximately 40% of them would check the neighborhood and evacuate, and when they hear the evacuation directive voice alarm, more than 90% will take the same action. We also discussed the awareness process of occupants considering this result and the configuration of a smoke detection system in Japan. Approximately half of the people in the large room take checking actions; however, the remaining people do not take specific confirmation actions for about 1–3 min and do not check for fires or evacuate. [ABSTRACT FROM AUTHOR]

Polyurethane sponge is frequently selected as a substrate material for constructing flexible compressible sensors due to its excellent resilience and compressibility. However, being highly hydrophilic and flammable, it not only narrows the range of use of the sensor but also poses a great potential threat to human safety. In this paper, a conductive flexible piezoresistive sensor (CHAP-PU) with superhydrophobicity and high flame retardancy was prepared by a simple dip-coating method using A-CNTs/HGM/ADP coatings deposited on the surface of a sponge skeleton and modified with polydimethylsiloxane. With great sensitivity and durability (>3000 cycles) as well as fast response/recovery time (152 ms/178 ms), the sensor is capable of monitoring human movement as a wearable device. The modified material surface has a hydrophobicity angle of 153°, which provides significant self-cleaning and weather resistance. Furthermore, the CHAP-PU sensor is able to respond stably to underwater movements. Importantly, when the sponge was directly exposed to an open flame, no flame spreading or dripping of molten material was detected, indicating excellent flame retardancy. Meanwhile, CHAP-PU was also equipped as a smart fire alarm system, and the results showed that an alarm signal was triggered within 2 s under flame erosion. Therefore, the flame-retardant superhydrophobic CHAP-PU sponge-based sensor shows great potential for human motion detection and fire alarm applications.

Abstract Fire alarms play a significantrole in situational awareness and decision‐making pertaining to evacuation for fire evacuation safety in office buildings that include small rooms, where many occupants cannot directly see fire or smoke. We conducted experiments using a mobile VR head‐mounted display to examine how individuals perceive the sound of fire alarms in rooms of different sizes. Comparing the cases of hearing the alarm sound in the large room and the small room, approximately 70% of the test participants answered that they wanted to check the situation more when they were in the small room because they could not understand the surrounding situation. Regardless of the room size, when test participants hear the early warning voice, approximately 40% of them would check the neighborhood and evacuate, and when they hear the evacuation directive voice alarm, more than 90% will take the same action. We also discussed the awareness process of occupants considering this result and the configuration of a smoke detection system in Japan. Approximately half of the people in the large room take checking actions; however, the remaining people do not take specific confirmation actions for about 1–3 min and do not check for fires or evacuate.

Accurate fire warning is very important for people's life and property safety. The most commonly used fire alarm is based on the detection of a single factor of gases, smoke particles, or temperature, which easily causes false alarm due to complex environmental conditions. A facile multi‐factor route for fabricating an accurate analog fire alarm using a Pb5S2I6 nanowire mesh based on its photoelectric and gas‐sensing dual function is presented. The Pb5S2I6 nanowire mesh presents excellent photoelectric detection capabilities and is sensitive to ppm‐level NO2 at room temperature. Under the "two‐step verification" circuit of light and gas factors, the bimodal simulation fire alarm based on this Pb5S2I6 nanowire mesh can resist the interference of complex environmental factors and effectively reduce the false alarm rate. [ABSTRACT FROM AUTHOR]

Factors and precautions against fire in blowing-carding unit process were summarized. According to production experience, precautions against fire were analyzed from the aspects of blowing-carding unit equipment, operation and dust removal equipment. It is considered that the main causes of fire are metal lighting in the picking cotton equipment, friction fire caused by cotton waste on the fan impeller and cotton waste inlaid on the machine wall, carding machine card clothing fire, configuration and improper use of card clothing. In practice, it is necessary to strictly regulate operator, arranger and maintenance worker, correct use of carding machine card clothing configuration and fire alarm, so as to prevent fire hazard and ensure the safety of production. [ABSTRACT FROM AUTHOR]

Traditional fire alarms emit a high-frequency sound to alert the occupants of an imminent threat, which may be less appropriate for people who are deaf or hard of hearing. To address this issue, the scientific literature concerning alternative alarm technologies has been reviewed to evaluate their effectiveness in awakening people who are deaf or hard of hearing. The results show that low-frequency alarms, bed shakers and/or pillow shakers seem to be the most reliable existing technologies for this group of people. The main codes and standards relevant to these technologies have also been screened. This highlighted that a new standard for alarm technologies incorporating tactile signals might be needed. In addition, this paper presents the responses of 36 people who were deaf or hard of hearing participating to a survey in which their experiences and preferences in relation to fire alarm technologies were investigated. While some technologies have been identified in the literature as potentially effective, the survey responses indicate that people who are deaf or hard of hearing do not necessarily use them. [ABSTRACT FROM AUTHOR]

This paper presents a wireless kitchen fire prevention system that can detect and notify the fire risk caused by gas stoves. The proposed system consists of two modules. The sensor module detects the concentration of carbon dioxide (CO 2 ) near the gas stove and transmits the monitoring results wirelessly. The alarm module, which is placed in other places, receives the data and reminds the user of the stove status. The sensor module uses a cost-efficient electrochemical CO 2 sensor and embeds an in situ algorithm that determines the status of the gas stove based on the measured CO 2 concentration. For the wireless communication between the modules, on-off keying (OOK) is employed, thereby achieving a longer battery lifetime of the alarm module, low cost, and simple implementation. To increase the lifetime further, a wake-up function based on passive infrared (PIR) sensing is employed in the alarm module. Our system can successfully detect the on state of the stove within 40 s and the off state within 200 s. Thanks to the low-power implementation, in situ algorithm, and wake-up function, the alarm module's expected battery lifetime is extended to about two months. [ABSTRACT FROM AUTHOR]

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The issues of elaboration of requirements for data transfer protocol in fire notification transmission systems are considered. The elaboration of requirements is related to the necessity of informational compatibility between fire notification transmission systems of various manufacturers and automated workstation of fire-and-rescue unit dispatcher. The basic structure of information data of the transfer protocol is proposed. The general and minimum required structure of information attributes of the database of objects of protection is determined. This database is installed at the automated workstation of the of fire-and-rescue unit dispatcher.

Kitchen fire has been becoming the majority risk to the ancient buildings, as the insufficient firefighting device, the excessive fuel, and the lower fire resistance structure. In this paper, a numerical simulation research was carried to access the effective of water spray in the kitchen fire of ancient buildings. The heat release rate (HRR), smoke temperature and spread process has been obtained, the efficiency of general water spray and kitchen special water spray has been compared, the necessary of the fire alarm device and the water spray have also discussed. The result indicated that the HRR peak is controlled by the water spray and fire detector devices, the activity time of water spray is the majority factor. The flame temperature is approximate to 400 °C without the firefighting device. Though the fire scenario protected by kitchen water spray and fire detector, the flame temperature is 67 °C and the HRR peak is 2.52 kW, which fire has been controlled in 32.7s. The result indicated that it is necessary for the ancient building's kitchen to fix the firefighting devices, and the numerical simulation is useful for the design and selection of firefighting device.

Although lignin-based carbon nanofibers (CNFs) have been successfully applied in the environmental, energy, and aerospace fields, obtaining fibers with excellent electrochemical performance is an urgent problem to be solved. In this work, lignin-based precursor fibers with nanofiber structures are prepared as the basal layer for the layer-by-layer (LbL) assembly of the electroactive substance polyethylenimine (PEI) and graphene oxide (GO) to obtain structured lignin-based CNFs with excellent electrochemical properties. The uniformly distributed multilayered nano-architecture and interconnected network structure provide a high specific surface area and effective contact area, thus promoting ion diffusion and transport and improving the electrical interaction and chemical reactions of the lignin-based CNFs. The specific capacitances and energy densities reach 339.3 F/g and 30.16 Wh/kg, respectively. Furthermore, the lignin-based CNFs exhibit an excellent durability and quick response to temperature (the current changes rapidly in 2 s of temperature rise). This work puts forward a simple and efficient strategy to fabricate nanocomposite fibers with orderly and controllable structures by LbL assembly using lignin-based raw materials. These nanocomposite fibers exhibit great potential for application in supercapacitor, fire alarm, and environment-friendly energy products. [ABSTRACT FROM AUTHOR]

The purpose of this study is to illustrate the special cases of a fire in a hospital especially in a perinatal intensive department, that may be encountered by the firefighters. Due to these special circumstances, the evacuation time of the facility can be significantly increased. There are unusual evacuation and rescue methods, which require special devices and more intense human resources. The evacuation requirement of a hospital is more than a usual evacuation plan, the goal is to maintain the health care services during and after the evacuation, so it is necessary to apply the Evacuation Plan of the Hospital Disaster Plan during a fire evacuation. This requires much more accurate and complex training from both the firefighters and the medical staff. Also, its effectiveness depends to a large extent on the architectural and fire protection design of the building, its modernity, the available medical and rescue equipment and the number of medical staff. The study examines the approximation and joint applicability of the plans above, based on the experience of a hospital evacuation exercise. [ABSTRACT FROM AUTHOR]

The airplane cargo fire is a severity disaster for the airplane in flight. The fire alarm system in cargo compartment plays an important part of the flight safety, which is a useful method to reduce the severity fight fire. However, the inflight altitude of airplane has been leading a low air pressure condition in the cargo, which should be affect the smoke spread and fire alarm process in the air cargo. In this paper, the smoke spread and fire alarm process has been investigated via numerical simulation. The various air pressure, fire source with different heat release rate and soot yield rate have been also discussed. During the simulation process, we can obtain the smoke spread, temperature distribution, and obscuration rate under the designed fire conditions. The fire alarms system response time of point-type smoke detector and line-type smoke detector (LSD) system have discussed under different fire scenarios and mounted location. The results indicate that the lower air pressure would accelerate the smoke speed velocity and bring the fire alarm time forward. The anti-interference property of LSD should be enhanced as the low air pressure influence and severe environment in the aircraft cargo. The results should offer the technical and scientific support for the cargo fire alarm system.

Design and development of fire-resistant composite materials with improved flame retardancy are critically needed for firefighters in fire protection fields. Herein, a novel fire-resistant composite hydrogel (FRCH) was fabricated based on calcium alginate (CA), poly (vinyl alcohol) (PVA) and expandable graphite (EG). The obtained FRCH material displayed prominent flame retardancy due to a large amount of heat was removed as contained water evaporation. Meanwhile, the EG in hydrogel occurred expansion to prevent heat transfer when exposed to fire. Results indicated that peak heat release rate and total release rate of FRCH decreased from 264.9 to 67.2 W/g and 15.4 to 12.1 KJ/g, respectively. The thermal kinetic behavior of FRCH was investigated by using Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) models. TPP test further confirmed that introduction of EG in hydrogel prolonged the second-degree skin burn time for 2.73 s compared to without EG component. Besides, benefiting from the expansion behavior of EG when being burned, EG formed a conductive pathway and resulting in LED light up. This work provided an effective way to prepare flame retardant composite material with an early fire warning detection function, which may meet the requirements in firefighting fields. [ABSTRACT FROM AUTHOR]

Wood, renowned for its sustainability, specific strength, and thermal insulation, stands as a highly sought-after sustainable structural material. However, the inherent flammability, decay susceptibility, and inadequate mechanical strength hinder its practical applications in high-rise buildings. Here, we report a groundbreaking solution to fabricate multi-functional fire-retardant wood (M-FRW) through a coupled delignification/impregnation procedure followed by densification treatment. The GO/BA created a hybridized network on the M-FRW surface, while BA molecules penetrated the wood cell. As-created M-FRW exhibits a superior flame retardancy due to the physical barrier and catalytic charring effect of GO/BA, as reflected by an ultrahigh limiting oxygen index value of >75 % and an 85 % reduction in the peak of heat release rate compared to natural wood. Furthermore, the GO/BA layer of M-FRW has a sensitive fire alarm response and ultralong alarm time (∼11280 s). More impressively, M-FRW exhibits an exceptional ability to inhibit decay fungi, mold fungi, and common bacteria due to the superimposed anti-microbial effect of GO and BA. Additionally, M-FRW shows desirable mechanical and thermal insulation properties. This work provides a facile strategy to fabricate a multi-functional advanced wood nanocomposite, making them hold great potential for various engineering applications, such as intelligent buildings. A highly fire-retardant, fire-warning, anti-microbial, and mechanically robust wood nanocomposite based on graphene oxide and boric acid has been developed using a graded-penetration impregnation strategy. The as-prepared multifunctional wood nanocomposite holds great promise for many engineering applications in buildings. [Display omitted] • A M-FRW was prepared by combining delignification, impregnation and densification. • PHRR and PSPR of M-FRW reduced by 85 and 78 % compared to natural wood, respectively. • M-FRW exhibits sensitive fire alarm response and ultralong alarm time (∼11280 s). • M-FRW shows excellent resistance to decay fungi and common bacteria. • The tensile strength of M-FRW is 3.1 times higher than natural wood. [ABSTRACT FROM AUTHOR]

• We assessed several algorithms to predict evacuation decision making. • Data used derived from web-based fire alarm experiments (n = 1.807) • We found that logistic regression is comparable to machine learning models. In this study we assessed logistic regression and machine learning models to explore their performance in predicting evacuation decisions and to provide readers with insights into the accuracy of these methods. We tested seven machine learning algorithms, including classification and regression tree, Naïve Bayes, K-nearest neighbours, support vector machine, random forest, extreme gradient boosting, and artificial neural network. We used data collected from 1,807 participants through web-based experiments to train and calibrate these models. The performance of each model was evaluated by area under the curve, accuracy, recall, specificity, precision, and F1-score. The results indicate that logistic regression had the highest area under the curve value (0.831), whereas extreme gradient boosting outperformed other machine learning models in terms of accuracy (0.780), specificity (0.810) and precision (0.820). K-nearest neighbours model had the greater recall (0.859) and artificial neural network the highest F1-score (0.785). The models identified that being with a close person was the most influential factor in the response to a fire alarm. [ABSTRACT FROM AUTHOR]

Due to the energy‐saving demands in chemical industries and building fields, thermal isolation materials (TIMs) are widely used. The general exploitation of combustible TIMs calls for timely fire alerts as well as flame‐retardant modifications. This work provides a novel paradigm to address the issues simultaneously by preparing a multifunctional aerogel via a facile and environmentally friendly freeze‐drying method. With the doping of ammonium polyphosphate and graphene oxide (GO), cellulose nanofiber‐based aerogel exhibits excellent thermal‐isolating as well as flame‐retardant properties. The composite aerogel displays flameless pyrolysis as well as increased residue char. A fire‐warning detector is designed to reliably monitor the early fire. Based on the flame‐induced electrical resistance transformation characteristic of GO, it endows the composite aerogel with an ultra‐fast fire‐response time of ~2.6 s and a durable alarm signal. The flame‐retardant and fire‐alarm mechanisms are concluded. Overall, these results suggest that this composite aerogel has an enticing prospect in chemical industries and high‐rise buildings, which may lay the foundation for designing multifunctional TIMs. The modified aerogel broadens its application territory by intrinsic fire‐alarm characteristics, which covers the deficiency of delaying reaction as well as restricted application scenarios in traditional fire detectors. [ABSTRACT FROM AUTHOR]

Detecting smoke from visual sensors is crucial for fire warnings. However, visually detecting smoke is still challenging because the chrominance, shape, transparency, texture, motion, and so on, of smoke vary over a wide range. A deep neural network (DNN) could detect smoke with higher accuracy, but the models are too large to run on limited resource platforms. To make the models smaller and improve the accuracy, three novel strategies are proposed in this paper: 1) feed the networks with blocks rather than the original image; 2) feed the network with condensed data rather than videos to extract dynamic characteristics; and 3) the framework has two stages, the first stage focuses on every block to find thin smoke, and the second stage focuses on the ascending and expanding motions in videos. It is not an end-to-end network, and every subnetwork works on a small matrix, even the one at the second stage, which operates on the whole image. Therefore, the network based on these strategies, the slight smoke perceptual network (SSPN), is small enough to be integrated on a raspberry pi. The experiments demonstrate that SSPN outperforms existing traditional methods and the methods based on DNN and achieves the highest accuracy and the highest sensitivity.

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • The expandable graphite-based cement composite (GCC) was fabricated. • The GCC exhibits with accurate and sensitive temperature sensing performance. • The GCC exhibits excellent mechanical and sensing stability when exposed to flame. • The GCC can be easily integrated into a building and transmit a fire alert. Fire alarms in buildings are essential for safety. However, due to the poor conductivity of cement, it remains a challenge to detect fire without the assistance of other monitoring equipment. In this study, a fire alarm cement composite containing expandable graphite, carbon fiber, and ordinary Portland cement that can achieve ultrasensitive temperature monitoring and indoor climate control in a building is developed. Homogeneously distributed expandable graphite in this smart cement rapidly expands under high temperatures, forming new electrically conductive pathways. This results in excellent temperature sensing performance, with a temperature coefficient of resistance of − 0.467 %/°C in the range of 220 °C–400 °C. The smart cement can be easily integrated into a building to transmit a fire alert to a computer, mobile phone, or visual alarm device in a timely manner. Furthermore, this smart cement exhibits higher flexural strength in harsh environments compared to ordinary cement. This smart cement exhibits potential to considerably broaden cement applications and be highly desirable for next-generation smart building materials. [ABSTRACT FROM AUTHOR]

[Display omitted] • Trifluoromethyl radicals are proposed as flame retardant radicals. • The flame-retardant mechanism of trifluoromethyl radicals is proposed. • Data support is provided for the applications of DGEBAF in fireproofing, electronic packaging, and other fields. • A novel approach is proposed for the analysis of fire safety. In order to obtain epoxy resins with flame retardant, dielectric properties, and easier industrialization, thus meeting the future development requirements in the field of electronic encapsulation, a trifluoromethylated epoxy resin (DGEBAF) was synthesized by using a two-step method, and the cured epoxy resin (DGEBAF/DDM) was prepared with DDM as the curing agent. Detailed studies of DGEBAF/DDM including curing kinetics, mechanical properties, and dielectric properties, etc. were conducted by using DGEBA/DDM (with dimethyl structure in DGEBA) and DGEBF/DDM (with dihydrogen structure in DGEBF) as the comparative samples. The results indicate that DGEBAF/DDM has higher storage modulus and strength, better dielectric properties, and hydrophobicity, and lowest thermal expansion coefficient, due to the existence of trifluoromethyl. Importantly, deeply study about the flame retardancy and its mechanism of DGEBAF/DDM was processed, which was of great significance for its application in the field of electronic packaging. Its vertical combustion level reaches UL-94 V-0. The limiting oxygen index of DGEBAF/DDM is 34.5 %, which is improved by 35.8 % and 30.2 % compared to DGEBA/DDM and DGEBF/DDM, respectively. The thermal decomposition mechanism of DGEBAF was explored by Py-GC/Mass, XPS, and FTIR analysis. It can be inferred that trifluoromethylated epoxy resin releases •CF 3 at high temperatures and effectively enhances the flame retardant of the epoxy resin through radical trapping. The smoke toxicity of DGEBAF/DDM combustion was detected in real time by conical thermal method combined with gas infrared analysis. In addition, we have found that DGEBAF/DDM decomposes at first but produces most residual carbon among the three epoxy resins. Based on the characteristics, an intelligent fire alarm system was designed. [ABSTRACT FROM AUTHOR]

Fire alarm causes and control measures in carding machine carding area were discussed. Combined with typical practical examples, fire alarm causes in carding area of high-yield carding machine were analyzed, mainly due to factors such as closer carding distance, tighter tooth distribution of card clothing, unreasonable correction gauge, worse sharpness of card clothing and excessive load on card clothing. It is considered that measures such as reasonable card clothing configuration and optimization of machine process are taken, problems can be effectively solved and safe production of carding machine can be ensured. [ABSTRACT FROM AUTHOR]

Since 2010 there have been at least 25 reported events that necessitated the evacuation of at least one full terminal of an airport. To facilitate the evacuation of the large number of passengers required, it is critical that airports install a properly designed emergency communications system (ECS). This paper discusses the key factors driving the design and operation of alarm systems in airport passenger terminal buildings. The technical requirements for passenger notification per the applicable codes and standards are discussed as well as the proper strategy for messaging and facilitating passenger evacuation. The paper discusses the various options for audible notification (including siren type alarms, pre-recorded announcements and live announcements) and visible notification (including strobes, exit signage and dynamic signage) and the impact of airport staff actions on facilitating evacuation. The paper concludes that a properly designed ECS incorporating verbal directive messaging may be most effective, with consideration being given to whether to augment this with enhanced visible notification. Perhaps equally important is developing standard operating procedures for assigning non-rescue-oriented airport staff with the responsibility to pay attention to and act upon ECS notification to provide direction to passengers and aid in facilitating evacuation. [ABSTRACT FROM AUTHOR]