Search Results (264)

This paper presents a method for functionally extending an IoT indoor air quality monitoring network by adding a cloud-level fire detection logic component. The proposed method does not aim to replace traditional fire detection systems at this stage of research, but to propose a solution for the development of fire detection capabilities and to improve the support provided to firefighting teams by providing a geospatial representation of the building in which a fire occurs. The proposed solution is based on a series of laboratory tests that demonstrated that air quality sensors can successfully detect the effects caused by an ignition event of common materials and can differentiate fire events from other events that can generate false-positive alarms by classic detection systems. The research involved five laboratory combustion tests based on the measurement of temperature, humidity, PM2.5 particle concentration, volatile organic compound index, and nitrogen oxide index. Following the tests, a warning mechanism and geospatial representation were designed using a system with ten IoT sensors to monitor the indoor air quality in a building on our university’s campus. Full article

This study examines the effects of injection timing and cerium oxide (CeO₂) nanoparticle (NP) size on NOx emissions and brake thermal efficiency (BTE) in a compression ignition engine, contributing to Sustainable Development Goals 7 and 13. Experiments were conducted at four load conditions (25–100%) using NP sizes of 10 nm, 30 nm, and 80 nm. An artificial neural network integrated with multi-objective particle swarm optimization (ANN-PSO) was employed to identify optimal operating parameters. The optimized configurations improved BTE and reduced NOx emissions across all loads; for example, at 75% load, BTE increased from 30.38% (average) to 32.13% (optimum), while simultaneously reducing the NOx emissions from 1322 ppm (average) to 1272 ppm (optimum). Analysis of variance (ANOVA) confirmed load as the most significant factor (p < 0.001), followed by injection timing and NP size. The model predictions closely matched experimental results, validating the optimization approach. The optimization suggests an interpolated optimal NP size of approximately 45 nm, highlighting the potential for further exploration. This integrated experimental and computational approach offers a promising framework for improving combustion efficiency and reducing emissions, thereby advancing cleaner and more sustainable fuel technologies. Full article

Aluminum hydride (AlH₃) is a promising candidate for enhancing the combustion performance of liquid fuels due to its high energy density and exceptional hydrogen storage capacity. This study investigated the ignition and combustion characteristics of μ-AlH₃ particles in kerosene droplets using TG-DSC analysis, high-speed imaging, laser ignition, and combustion product characterization, with comparisons to micron- and nano-aluminum powders. Results showed that the exothermic combustion of hydrogen released from AlH₃ decomposition lowered the primary oxidation temperature of aluminum, leading to more intense combustion with smaller ejected particles. The particle size of kerosene droplets containing AlH₃ rapidly decreases due to the escape of hydrogen. The heat released by the combustion of hydrogen significantly accelerates the combustion of droplets, and the fastest combustion rate is observed at a concentration of 1% AlH₃. The combustion products of kerosene droplets containing AlH₃ are smaller than those of kerosene droplets containing aluminum, indicating that their combustion efficiency is higher. A combustion model for AlH₃-based kerosene droplets was developed, demonstrating less than 10% error in predicting ignition delay and burning rates. These findings provide valuable insights for the application of AlH₃ in liquid fuels. Full article

Three TOP TIER^TM gasoline deposit control additives (DCAs) of differing chemistries were tested for their impact on particulate matter emissions in terms of particulate mass (PM) and particle number (PN) at operating conditions representative of road load, cold start, and high load on a 2.0 L, 4-cylinder, gasoline direct injection (GDI) spark ignition (SI) engine. The PM-PN emissions were measured using an Exhaust Emissions Particle Sizer (EEPS). Deposit control additives or detergents are gasoline additives used to prevent and clean combustion chamber and injector deposits in gasoline spark ignition (SI) engines. All three gasoline additives were tested at each operating condition at three different treatment rates. In addition, one of the additives was tested with a fuel-based friction modifier (FM). The results showed that of the treatment rates tested, the lowest allowable concentration (LAC) for all additives requires the least time for the emissions to settle. However, the impact of the gasoline additives on PM-PN emissions is not linear and changes with additive concentration depending on the additive chemistry and operating conditions. The additive with the friction modifier resulted in an increase of over 19% particle number and over 30% particulate mass at the road load operating condition, while the increase at high load was over 27% for particle number and 11% for particle mass. Full article

This study develops, implements, and evaluates the Firebrand Spotting parameterization within the WRF-Fire coupled fire–atmosphere modeling system. Fire spotting is an important mechanism characterizing fire spread in wind-driven events. It can accelerate the rate of spread and enable the fire to spread over streams and barriers such as highways. Without the capability to simulate fire spotting, wind-driven fire simulations cannot accurately represent fire behavior. In the Firebrand Spotting parameterization, firebrands are generated with a set of fixed properties, from locations vertically aligned with the leading fire line. Firebrands are transported using a Lagrangian framework accounting for particle burnout (combustion) through an MPI-compatible implementation within WRF-Fire. Fire spots may occur when firebrands land on unburned grid points. The parameterization is verified through idealized simulations and its application is demonstrated for the 2021 Marshall Fire, Colorado. The simulations are assessed using the observed fire perimeter and time of arrival at multiple locations identified from social media footage and official documents. All simulations using a range of ignition thresholds outperform the control without spotting. Simulations accounting for fire spots show more accurate fire arrival times (i.e., reflecting a better fire rate of spread), despite producing a generally larger fire area. The Heidke Skill Score (Cohen’s Kappa) for the burn area ranges between 0.62 and 0.78 for simulations with fire spots compared to 0.47 for the control. These results show that the parameterization consistently improves the fire forecast verification metrics, while also underscoring future work priorities, including advancing the generation and ignition components. Full article

In this study, reaction mechanisms of polytetrafluoroethylene/Al materials under shock compression were investigated. The reaction-induced pressure perturbations in PTFE/Al materials were identified by comparing pressure profiles with those of inert PTFE/LiF counterparts. The pressure rebounded to a range of 10.2–16.9 GPa under an incident shock pressure range of 11.5–22.6 GPa. The pressure perturbation amplitude induced by reaction gradually attenuated with increasing propagation distance. The delay time between the observed pressure perturbations and the incident shock front arrival ranged from 0.84 to 1.71 μs and showed a decreasing trend with increasing incident shock pressure and decreasing aluminum particle size. The results suggest that the reaction ignition and energy release of PTFE/Al materials change from closely following the shock front to being delayed by hundreds of microseconds behind the shock front when shock compression intensity decreases from GPa to MPa levels. Full article

This study aimed to assess the physical, chemical, and combustion properties of pellets made from corncob and rice husk residues sourced in Sucre, Colombia, and to evaluate the performance of different blending ratios. Before pelletization, the residues were ground and processed using a small-scale flat die pellet mill equipped with a 6 mm die. Physical properties were evaluated according to ISO standards for particle density, bulk density, and impact resistance assessment. Proximate and ultimate analyses, as well as heating values, were determined and compared against the ISO 17225-6:2021 classification for herbaceous biomass. The 70:30 corncob-to-rice husk blend (CC70:RH30) showed good quality, with 7.23% ash, 9.18% moisture, and an LHV of 15.19 MJ/kg, meeting the criteria for Class B pellets. Combustion performance was assessed using a custom-designed macro-TGA, revealing that co-pelletized blends exhibited improved ignition temperatures and comprehensive combustion indices compared to the individual feedstocks. Additionally, calorific values were proportional to the blending ratios. In summary, controlling the blending ratio of corncob and rice husk residues during pellet production allows modulation of both the total ash content and the lower heating value of the resulting solid biofuels, making them more suitable for thermochemical conversion routes such as combustion and/or gasification. Full article

This study describes a quite special and interesting atmospheric event characterized by the simultaneous presence of fresh and aged smoke layers. These peculiar conditions occurred on 16 July 2024 at the CNR-IMAA atmospheric observatory (CIAO) in Potenza (Italy), and represent an ideal case for the evaluation of the impact of aging and transport mechanisms on both the optical and microphysical properties of biomass burning aerosol. The fresh smoke was originated by a local wildfire about 2 km from the measurement site and observed about one hour after its ignition. The other smoke layer was due to a wide wildfire occurring in Canada that, according to backward trajectory analysis, traveled for about 5–6 days before reaching the observatory. Synergetic use of lidar, ceilometer, radar, and microwave radiometer measurements revealed that particles from the local wildfire, located at about 3 km a.s.l., acted as condensation nuclei for cloud formation as a result of high humidity concentrations at this altitude range. Optical characterization of the fresh smoke layer based on Raman lidar measurements provided lidar ratio (LR) values of 46 ± 4 sr and 34 ± 3 sr, at 355 and 532 nm, respectively. The particle linear depolarization ratio (PLDR) at 532 nm was 0.067 ± 0.002, while backscatter-related Ångström exponent (AEβ) values were 1.21 ± 0.03, 1.23 ± 0.03, and 1.22 ± 0.04 in the spectral ranges of 355–532 nm, 355–1064 nm and 532–1064 nm, respectively. Microphysical inversion caused by these intensive optical parameters indicates a low contribution of black carbon (BC) and, despite their small size, particles remained outside the ultrafine range. Moreover, a combined use of CIAO remote sensing and in situ instrumentation shows that the particle properties are affected by humidity variations, thus suggesting a marked particle hygroscopic behavior. In contrast, the smoke plume from the Canadian wildfire traveled at altitudes between 6 and 8 km a.s.l., remaining unaffected by local humidity. Absorption in this case was higher, and, as observed in other aged wildfires, the LR at 532 nm was larger than that at 355 nm. Specifically, the LR at 355 nm was 55 ± 2 sr, while at 532 nm it was 82 ± 3 sr. The AEβ values were 1.77 ± 0.13 and 1.41 ± 0.07 at 355–532 nm and 532–1064 nm, respectively and the PLDR at 532 nm was 0.040 ± 0.003. Microphysical analysis suggests the presence of larger, yet much more absorbent particles. This analysis indicates that both optical and microphysical properties of smoke can vary significantly depending on its origin, persistence, and transport in the atmosphere. These factors that must be carefully incorporated into future climate models, especially considering the frequent occurrences of fire events worldwide. Full article

To improve the prediction accuracy of soot load in gasoline particulate filters (GPFs) and the control accuracy during GPF regeneration, this study developed a prediction model to predict the soot mass concentration at the GPF inlet of gasoline direct injection (GDI) engines using advanced machine learning methods. Three machine learning approaches, namely, support vector regression (SVR), deep neural network (DNN), and a Stacking integration model of SVR and DNN, were employed, respectively, to predict the soot mass concentration at the GPF inlet. The input data includes engine speed, torque, ignition timing, throttle valve opening angle, fuel injection pressure, and pulse width. Exhaust gas soot mass concentration at the three-way catalyst (TWC) outlet is obtained by an engine bench test. The results show that the correlation coefficients (R²) of SVR, DNN, and Stacking integration model of SVR and DNN are 0.937, 0.984, and 0.992, respectively, and the prediction ranges of soot mass concentration are 0–0.038 mg/s, 0–0.030 mg/s, and 0–0.07 mg/s, respectively. The distribution, median, and data density of prediction results obtained by the three machine learning approaches fit well with the test results. However, the prediction result of the SVR model is poor when the soot mass concentration exceeds 0.038 mg/s. The median of the prediction result obtained by the DNN model is closer to the test result, specifically for data points in the 25–75% range. However, there are a few negative prediction results in the test dataset due to overfitting. Integrating SVR and DNN models through stacked models extends the predictive range of a single SVR or DNN model while mitigating the overfitting of DNN models. The results of the study can serve as a reference for the development of accurate prediction algorithms to estimate soot loads in GPFs, which in turn can provide some basis for the control of the particulate mass and particle number (PN) emitted from GDI engines. Full article

Amorphous boron powder, as a high-energy fuel, is widely used in the energy sector. However, its ignition and combustion difficulties have long limited its performance in propellants, explosives, and pyrotechnics. In this study, Mg/Al-coated boron powder with enhanced combustion properties was synthesized using the electrical explosion method. To investigate the effect of Mg/Al coating on the ignition and combustion behavior of boron powder, four samples with different Mg/Al coating contents (4 wt.%, 6 wt.%, 8 wt.%, and 10 wt.%) were prepared. Compared with raw B95 boron powder, the coated powders showed a significant reduction in particle size (from 2.9 μm to 0.2–0.3 μm) and a marked increase in specific surface area (from 10.37 m²/g to over 20 m²/g). The Mg/Al coating formed a uniform layer on the boron surface, which reduced the ignition delay time from 143 ms to 40–50 ms and significantly improved the combustion rate, combustion pressure, and combustion calorific value. These results demonstrate that Mg/Al coating effectively promotes rapid ignition and sustained combustion of boron particles. Furthermore, with the increasing Mg/Al content, the ignition delay time decreased progressively, while the combustion rate, combustion pressure, and heat release increased accordingly, reaching optimal values at 8 wt.% Mg/Al. An analysis of the combustion residues revealed that both Mg and Al reacted with boron oxide to form new multicomponent compounds, which reduced the barrier effect of the oxide layer on oxygen diffusion into the boron core, thereby facilitating continuous combustion and high heat release. This work innovatively employs the electrical explosion method to prepare dual-metal-coated boron powders and, for the first time, reveals the synergistic promotion effect of Mg and Al coatings on the ignition and combustion performance of boron. The results provide both experimental data and theoretical support for the high-energy release and practical application of boron-based fuels. Full article

Compression–ignition engines emit particulate matter (PM) (soot), prompting the widespread use of diesel particulate filters (DPFs) in the automotive sector. An alternative method for PM reduction involves the use of ultrasonic waves to disperse and modify the structure of exhaust particles. This article presents experimental results of the effects of ultrasonic emitter parameters, including the number, arrangement, and power, along with the engine speed, on the exhaust smoke density. Tests were conducted on a laboratory prototype equipped with six ultrasonic emitters spaced 0.17 m apart. The exhaust source was a diesel engine from a construction excavator, based on the MTZ-80 tractor design, delivering 80 HP and a displacement of 4750 cm³. A regression model was developed to describe the relationship between the engine speed, emitter power and spacing, and smoke density. The optimal configuration was found to involve an emitter power of 319.35 W and a spacing of 1.361 m for a given engine speed. Under the most effective conditions—an engine speed of 1500 rpm, six active emitters, and a total power of 600 W—smoke emissions were reduced by 18%. These findings support the feasibility of using ultrasonic methods as complementary or alternative exhaust gas filtration techniques for non-road diesel engines. Full article

Melamine formaldehyde particle boards (MFPBs), commonly utilized as a wooden decorative material in traditional architecture, demonstrate considerable performance deterioration with extended age, with reductions in essential flame retardancy and structural integrity presenting substantial risks to fire safety in structures. This research examines the impact of thermo-oxidative aging on the flame retardancy of MFPBs. The morphological evolution, surface composition, and flame-retardant characteristics of aged MFPBs were examined via scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), limiting oxygen index (LOI), and cone calorimeter (CCT). The results indicate that thermo-oxidative aging (60 °C, 1440 h) markedly reduces the activation energy (E, by 17.05%), pre-exponential factor (A, by 68.52%), LOI value (by 4%, from 27.5 to 26.4), and time to ignition (TTI, by 17.1%, from 41 s to 34 s) while augmenting the peak mass loss rate (MHRR, by 4.7%) and peak heat release rate (pHRR, by 20.1%). Subsequent investigation indicates that aging impairs the char layer structure on MFPB surfaces, hastens the migration and degradation of melamine formaldehyde resin (MFR), and alters the dynamic equilibrium between “MFR surface enrichment” and “thermal decomposition”. The identified degradation thresholds and failure mechanisms provide essential parameters for developing aging-resistant fireproof composites, meeting the pressing demands of building safety requirements and sustainable material design. Full article

In gas transmission stations, flame arrestors are typically installed in pipelines and venting systems to prevent the flames resulting from accidental ignition or deflagration of combustible gases during transmission from propagating through the pipelines. During actual operation, the presence of solid particulates in the gas compromises the flame-arresting efficacy and increases the failure rate of current pipeline flame arrestors. This study employs an integrated approach combining theoretical analysis and numerical simulation to establish a numerical model for flame arrestors that accounts for solid particle deposition effects. The model reveals the distribution characteristics of velocity fields, pressure fields, gas phase volumetric concentration fields, and solid deposition rate fields within pipeline flame arrestors. It systematically investigates the influence mechanisms of porosity, flame arrestor core thickness, inlet flame velocity, arrestor length, particle size, particle concentration on pressure drop, flame arrestment velocity, and deposition rate. These findings provide theoretical support for optimizing flame arrestor structural design and reducing operational failure rates. Full article

This experimental study examines the particle-level combustion behavior of high-volatile bituminous coal and walnut shell particles in oxyfuel environments, with a particular focus on the gas-phase ignition characteristics and the structural development of volatile flames. Particles with similar size and shape distributions (a median diameter of about 126 µm and an aspect ratio of around 1.5) are combusted in hot flows generated using lean, flat flames, where the oxygen mole fraction is systematically varied in both CO₂/O₂ and N₂/O₂ atmospheres while maintaining comparable gas temperatures and particle heating rates. The investigation employs a high-speed multi-camera diagnostic system combining laser-induced fluorescence of OH, diffuse backlight-illumination, and Mie scattering to simultaneously measure the particle size, shape, and velocity; the ignition delay time; and the volatile flame dynamics during early-stage volatile combustion. Advanced detection algorithms enable the extraction of these multiple parameters from spatiotemporally synchronized measurements. The results reveal that the ignition delay time decreases with an increasing oxygen mole fraction up to 30 vol%, beyond which point further oxygen enrichment no longer accelerates the ignition, as the process becomes limited by the volatile release rate. In contrast, the reactivity of volatile flames shows continuous enhancement with an increasing oxygen mole fraction, indicating non-premixed flame behavior governed by the diffusion of oxygen toward the particles. The analysis of the flame stand-off distance demonstrates that volatile flames burn closer to the particles at higher oxygen mole fractions, consistent with the expected scaling of O₂ diffusion with its partial pressure. Notably, walnut shell and coal particles exhibit remarkably similar ignition delay times, volatile flame sizes, and OH-LIF intensities. The substitution of N₂ with CO₂ produces minimal differences, suggesting that for 126 µm particles under high-heating-rate conditions, the relatively small variations in the heat capacity and O₂ diffusivity between these diluents have negligible effects on the homogeneous combustion phenomena observed. Full article

Improving the energy release and safety of composite solid propellants is a key focus in energetic materials research. Graphene, with its excellent thermal conductivity and lubrication properties, is a promising additive. In this study, Al@AP core–shell particles doped with graphene were prepared via an in-situ deposition method. The structure, thermal decomposition, combustion, and safety performance of the graphene-doped Al@AP samples were investigated. Results showed that AP effectively coated aluminium to form a typical core-shell structure, with graphene uniformly loaded into the framework. Graphene contents of 1.0 and 4.0 wt.% reduced AP’s thermal decomposition temperature by 0.97 and 16.68 °C, respectively. Closed-bomb and laser ignition tests revealed that pressure rise rates and combustion intensity increased with graphene content up to 1.0 wt.% but declined beyond that. Peak pressure reached 114.65 kPa at 1.0 wt.% graphene, and the maximum pressure increase rate was 13.29 kPa ms⁻¹ at 2.0 wt.%. Additionally, graphene significantly improved safety by reducing sensitivity to impact and friction. The enhanced performance is attributed to graphene’s large surface area and excellent thermal and electrical conductivity that promote AP decomposition and combustion, combined with its lubricating effect that enhances safety, though excessive graphene may hinder these benefits. This study provides balanced design criteria for graphene-doped Al@AP as solid propellants. Full article