bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wavelet analysis to reveal fluctuations in near-surface temperature and wind speed during the FireFlux I experimental fire
Authors: Antolin William P. , Rochoux Mélanie C. , Moigne Patrick Le 
Published: November 2024

Abstract
Field-scale wildland fire experiments are needed to validate coupled atmosphere/fire models and to assess their ability to represent wildland fire dynamics, including surface fire spread and perturbed local meteorology in the immediate vicinity of the spreading fire. These experiments provide access to the in situ turbulence observations needed to understand the local turbulent structures, which are impacted by the strong heat fluxes released by the fire and by the presence of forest canopies. In this paper, we present a wavelet analysis approach to extract turbulence information, based on frequency localization, from observed time series of temperature and wind speed during the FireFlux I experimental fire. Wavelets are used to robustly decompose the time series of interest into mean and fluctuation components by separating scales in the frequency space, where it is possible to identify the scales that contribute most to the energy spectrum. Fluctuations in temperature and wind speed are then used as input to a quadrant analysis to characterize the possible interactions between variables as the fire front passes, and to identify the most dominant events such as sweeps, puffing and local cooling. Wavelets therefore have great potential for observation-model comparison, i.e. for assessing the ability of coupled atmosphere-fire models to represent realistic turbulence patterns associated with atmosphere-canopy-fire interactions.
Particle Size Prediction Method for Fire or Nuisance Event using a Simple Photoelectric Detector
Authors: Özyurt Osman 
Published: November 2024

Abstract
This study demonstrates that a simple smoke detector with minimal components can be used to estimate the particle size of fires or nuisance incidents. Machine learning (ML) models were created using scattered light data. Various test materials such as wood, cotton, polyurethane foam, cigarette, N-heptane, printed circuit board (PCB), paraffin, polyalpha olefin (PAO), di-ethyl hexyl-sebacate (DEHS), plaster powder, and cement dust were used in the experiments. The proposed prediction method was tested against completely unknown particles of cigarette, PAO, PCB, and plaster powder, which were not used in the training. The particle size prediction capability of forward, backward, and side scattering of light at 980 nm was investigated using ML models with time correlation function (TCF) data. The prediction errors of the best ML model for particle median sizes ranged from 0.4% to 35.1%. Traditional simple smoke detectors using the proposed methodologies can measure the median particle size and volume concentration, thereby effectively suppressing false alarms.
CO – hazardous gas indicates hidden smoldering fires
Authors: Wegner S , Ruhe H , Klein K , Braun F , Lange J , Kampmeier B , Wellisch A , Neske M 
Published: November 2024

Abstract
The growing importance of wood construction presents new challenges for fire departments and leads to new areas of responsibility and research. In particular, hidden smoldering fires can damage building structures and release toxic gases if not detected. This study investigates the detection of cavity fires in modern wood construction using carbon dioxide (CO) gas measurement technology. For this purpose, the propagation within the compartment and to adjacent compartments is investigated. The measurement is performed both through the plaster layers and with copper tubes, allowing measurements directly on the insulation material. For gas measurement in this paper, only fire service gas meters have been used.
A Study on Domestic Metal Waste Fire Extinguishing Experiment Against Metal Fires
Authors: Park TH , Kim TS , Yang JH , Kwon JS 
Published: November 2024

Abstract
There are no test standards in Korea for effective suppression of metal fires. In addition, metal dust generated during the aluminium recycling process is easily exposed to fire. Experiments were conducted with the expended vermiculite and wetting agent selected according to ISO 7165 standards and samples collected from factories. In addition, additional experiments were conducted according to KS F 2271 standards to find out the hazards of field workers.
Limits of assisted evacuation considering the safety of caregivers and impact of smoke control at small-scale older people’s welfare facilities
Authors: Minegishi Yoshikazu 
Published: November 2024

Abstract
This study investigated the limits of caregivers’ assistance during evacuations in small-scale older people welfare facilities, considering their safety and the impact of smoke control. Using virtual reality experiments, caregivers’ behavior during assistive evacuation was examined across different smoke-controlled scenarios. The participants, fire safety professionals, performed two evacuation procedures: “Attend,” by guiding residents outside, and “Refuge,” by having the residents stay inside. Results showed successful evacuation when smoke control measures were implemented, emphasizing their necessity for ensuring caregiver and resident safety during emergencies. Difficulties included loss of a sense of direction, smoke visibility, and challenges in assisting residents, highlighting the complexity of real-life scenarios. Effective smoke control measures are crucial for facilitating successful evacuations in small-scale older people welfare facilities.
Using CO and HCN as surrogates for multiple gases in fire toxicity calculations
Authors: Hostikka Simo , Linna Antti 
Published: November 2024

Abstract
Engineering analyses of fire toxicity are often limited to the production and transport of carbon monoxide and hydrogen cyanide, despite the broader range of gases in the Purser’s formulation for the fractional effective dose (FED). In this work, we show how these two gases can be used as surrogates for the other gases. We validate the method by measuring the yields of asphyxiant and irritant gases for five fuels, assigning them to a source of a small room fire and carrying out CFD predictions of FED using full and simplified schemes of gas species. Results indicate that replacing the full list of species with surrogates leads to less than 6 % relative error while simplifying the user input considerably and saving computational resources.
De-gendering firefighting: exploring risk perception and psychological resilience
Authors: Cuesta Arturo , Alvear Daniel , Balboa Adriana , Ortiz Gemma 
Published: November 2024

Abstract
This study explores psychological differences between male and female firefighters. A convenience sample of 202 firefighters (62 females) filled out an anonymous web-based survey designed to capture self-repots on risk propensity, risk tolerance, resilience and coping resilience. Overall small differences were found suggesting that the hypothetical gender discrepancies may be reduced in firefighting occupational contexts. Further research is needed to confirm this.
Determinants of Response to Fire Incidents in the Informal Settlements: A Case of Jhuggi Jhonpdi Clusters in Delhi, India
Authors: Karmakar Satorupa , Sharma Upasna , Lange David 
Published: November 2024

Abstract
Urban fires are exacerbated by global urbanisation trends, as characterised by dense and unplanned settlements in the global south. The contribution of flammable building materials, narrow lanes and an inability/unwillingness to adhere to the building regulations as the primary drivers behind elevating fire risk in informal settlements is well studied. Considering the impact of human behaviour during and after fire, this study draws insights from informal settlements in Delhi. The primary aim is to understand the manifold impacts of demographic, social, economic, infrastructural factors on response patterns to fire. Based on household surveys in 31 Jhuggi Jhonpdi clusters and resettlement colonies, we conducted multiple linear regression to understand the impact of predictors on response to fire. Our findings suggest that prior experience to fire has the strongest impact on household response to fire, followed by familiarity to place. The scope of the research lies in unfolding the nuanced dynamics of human actions during fire in the informal settlements, which otherwise, lie outside the purview of formal policy regulations.
Examining the Effects of Deep Learning Model Structure on Model Interpretability for Time-Series Classifications in Fire Research
Authors: Cheong Tam Wai , Fan Linhao , Tong Qi , Fang Hongqiang 
Published: November 2024

Abstract
This present work utilizes an interpretability model to understand and explain the decisions of deep learning models. The use of DeepLIFT is proposed and attributions of a study case are obtained. Benchmarking against two other interpretability models, namely Grad-CAM and dCAM, is conducted. Results show that DeepLIFT can provide precise attributions to the model inputs in both temporal and spatial directions. A parametric study is also carried out to understand the effects of deep learning model structure on the attributions obtained from the interpretability model. Ten different convolutional neural network model structures are considered. Three important observations are made: 1) changes in the model structure have minor effects on the attributions in the temporal direction, but 2) they have negligible effects on attributions in the spatial direction, and 3) convolutional layers need to be fixed to avoid attribution discrepancies. By understanding the model decision and the resulting effects of the model structure, it is hoped that this work can contribute to the development of trustworthy deep learning models for the fire research community.
Evaluating impacts of a LFP battery fire within a subsurface train compartment
Authors: Mamgain Alankrita , Restuccia Francesco 
Published: November 2024

Abstract
The application of lithium-ion batteries is becoming progressively prominent in everyday applications due to their high energy density, high output power and more favourable ageing characteristics in comparison to alternatives such as nickel metal hydride and lead acid batteries. However, when exposed to abuse conditions, lithium-ion batteries may undergo a thermal runaway reaction, resulting in high temperatures and release of flammable and toxic gases. This paper evaluates the temperature and smoke distribution to determine tenability period within a subsurface train compartment in the event of a lithium iron phosphate (LFP) battery fire. The results concluded that within 17 minutes of the failure of lithium iron phosphate batteries, the critical temperature of 60°C was exceeded in the entire carriage whilst the visibility threshold of 10m was exceeded in the carriage in under 86 seconds. Consequently, for an effective evacuation in this scenario, all passengers should be able to reach a place of relative safety before the critical limit for visibility is reached.
Predicting the total wall time of CFD simulations of single-compartment fires
Authors: Veit Martin , Lucherini Andrea , Maragkos Georgios , Merci Bart 
Published: November 2024

Abstract
The total wall time is often difficult to predict a priori in compartment fire simulations due to dynamic phenomena that can occur, e.g., flame extinction. The wall time is dependent on multiple physical factors in the simulation, along with simulation factors and the system used to compute the model. Specifically, the CFL number of a simulation is highly influential to the wall time, as this restricts the time step size. In this paper, the prediction of the total wall time for a single-compartment fire is investigated considering varying fire heat release rates and compartment ventilation factors. It is shown that an increasing heat release rate increases the total wall time due to higher velocities inside the compartment. Furthermore, when the compartment becomes under-ventilated, the wall time becomes more difficult to predict early on in the simulation, as steady state conditions are reached later, compared to well-ventilated cases. The time at which the wall time can be accurately predicted changed from a few physical seconds in the well-ventilated case, to up to 60 physical seconds for the under-ventilated case.
Application of machine learning techniques to predict fire development in an ISO 9705 room
Authors: Nasar Lareb , Dixon Harriet , Drosopoulos Georgios , Asimakopoulou Eleni 
Published: November 2024

Abstract
Machine learning, a subset of artificial intelligence, shows potential for enhancing computational fire modelling compared to traditional methods such as computational fluid dynamics. This study explored using artificial neural networks to predict heptane fire development within a compartment, varying heat release rates from 100 to 3000 kW and ventilation areas from 0.16 to 4.8 m2. Artificial neural networks (ANNs) were trained using computational data from an ISO 9705 room. Network optimisation involved adjusting training-to-validation ratios and fine-tuning hidden layer neuron counts. Results indicate optimised ANNs achieved less than 7% error for heat release rate predictions and 1.5% for ventilation size predictions, with a notable computational cost reduction exceeding 104-fold. These findings suggest a promising future for integrating machine learning into fire engineering, significantly reducing analysis time therefore fostering safety improvements and innovation in the field.
Exploration of Trends and Characteristics in Malaysian Building Fires and Wildfires (2000-2019)
Authors: Noumeur A , Tohir M Z M , Said M S M , Baharudin M R , Yusoff H M 
Published: November 2024

Abstract
Efforts to reduce fire casualties are crucial, and fire statistics are considered an important element that provides vital insights for assessing future risks. In line with Malaysia’s development, this study conducts a comprehensive analysis of the 9 fire indicators in Malaysia from 2000 to 2019 with the aim to explore fire incident patterns, including causes, fatalities, injuries, and associated losses. A notable escalation in fire breakouts and associated risks during this period were observed. Arson emerges as the leading cause of these incidents, closely followed by electricity and smoking-related fires. This analysis facilitates the deeper comprehension of fires trends in Malaysia and open the door for future comparison with other countries offering valuable insights for the fire department to forecast future fire scenarios.
High-Intensity Fast-Response Electric radiant Panel (HIFREP) for increased accuracy on thermal boundary conditions during fire testing
Authors: Put Florian , Jovanović Balša , Symoens Evelien , Lucherini Andrea , Merci Bart , Van Coile Ruben 
Published: November 2024

Abstract
Fire resistance tests rely on the use of standardized furnaces to apply specific thermal boundary conditions to assess the performance of construction materials and systems in fire conditions. However, these tests are very expensive and encounter challenges related to repeatability and uncertainties in establishing thermal boundary conditions. Moreover, their incapacitance to tailor experiments hinders advancements in understanding structural behaviour during fire exposure. In this work, a novel type of radiant panel, that operates on electricity, is introduced: the High-Intensity Fast-Response Electric radiant Panel (HIFREP). This innovation offers enhanced sustainability performance while ensuring more precise control over thermal boundary conditions. By eliminating the need for gas combustion, the panel can be used in a traditional structural testing lab to investigate non-combustible materials (e.g. concrete), without requiring extraction hoods and other provisions. The presented electric radiant panel system represents a significant step forward from fire resistance furnace testing.
Evaluation of GPU-based Conductive Heat Transfer Algorithms
Authors: Döhle Daniele , Börger Kristian , Arnold Lukas 
Published: November 2024

Abstract
The one-dimensional heat transfer algorithm of the Fire Dynamics Simulator (FDS) is currently implemented to run on a CPU (Central Processing Unit). This study explores the potential advantages of adapting the algorithm for Graphics Processing Units (GPUs), which could offer significant computational benefits.
The motivation behind this work stems from the intention to speed up numerical fire simulations. Up to now, simplifications with regard to grid resolution and level of detail have been made, compromising accuracy for quicker results. Simulations, especially for heat transfer in solid objects such as walls, require computationally intensive resources. By leveraging the GPUs’ superior parallel processing capabilities, it is possible to conduct faster and more accurate simulations, avoiding these compromises.
Both a CPU and a GPU algorithm for computing the 1D heat transfer are developed, and the computation time is compared against each other. Both implementations are validated against a simple FDS simulation with identical boundary conditions. The investigations show that the GPU algorithm is promising above a certain number of wall elements, depending on the employed hardware. The results show that this is generally the case from 2048 elements.
Universal nature of quantum supremacy
Authors: Kocharovsky Vitaly 
Published: November 2024

Abstract
We disclose the universal nature of computational #P-hardness and quantum supremacy of quantum many-body systems. We do so by means of the new powerful technique (the hafnian master theorem) that allows one to address the #P-hard problems systematically. We consider a generic example of many-body interacting systems – a trapped BEC-gas of interacting Bose atoms, apply the hafnian master theorem and refer to the Toda’s theorem on a #P-complete oracle.
Two-mode squeezing and entanglement in atomic boson sampling
Authors: Shannon William , Kocharovsky Vitaly 
Published: November 2024

Abstract
Recently, atomic boson sampling of excited atom occupations in an equilibrium interacting gas with a Bose-Einstein condensate (BEC) has been suggested as a process that could be #P-hard for classical computing. Here we consider this process within the simplest possible model of a BEC trap – the box with the periodic boundary conditions. Remarkably, this model remains pertained to #P-hardness and quantum supremacy. We evince two-mode squeezing and entanglement in the statistics of sampling from (i) a single eigen-squeeze mode or (ii) two counter-propagating waves. Although not complex enough on its own to show #P-hard behavior, such a sampling reveals the basic mechanism of the #P-hardness – an interplay between two intrinsic entities existing in the BEC gas, the eigen-energy quasiparticles and eigen-squeeze modes, that causes the interference and squeezing of the sampled excited atom states.
Linear and Angular Momentum of Classical Particles Interacting with a Laguerre-Gauss Laser Pulse
Authors: Toma Petru-Vlad , Băran Virgil , Micluta-Campeanu Sebastian , Boca Madalina 
Published: November 2024

Abstract
We investigate the evolution of an ensemble of classical charged particles interacting with a Laguerre-Gauss laser pulse. We integrate numerically the relativistic equations of motion for the particles which at the initial moment (before the arrival of the laser pulse) are at rest, distributed uniformly in a disk in the focal plane of the laser. We study the evolution in time of the linear and the angular momentum of the particles, and its dependence on the laser parameters (radial and azimuthal indices of the LG mode, waist, duration, and intensity) and also on the initial position of the particle in the focal plane. We show that in the low-intensity regime, the net transfer of linear momentum is parallel to the focal plane, while at large intensities the dominant component of the momentum is along the laser propagation direction. We also identify scaling laws obeyed by the net transfer of linear and angular momentum to the particles as a function of the field intensity. We present the relativistic ponderomotive force approximation model and study its validity for different parameters of the laser field. The scaling laws mentioned above are discussed also in the context of this approximation.
Ultrabroad Band Collinear Mid-Infrared Optical Parametric Amplifier Driven by a Millijoule Femtosecond Tm:YAP Regenerative Amplifier
Authors: Fuji T , Rezvani S A 
Published: November 2024

Abstract
We present a comprehensive study on the development and performance of an ultra-broadband mid-infrared (MIR) optical parametric amplifier (OPA) pumped by a home-built solid-state amplification system. The intricate design encompasses a thulium-doped fluoride (Tm:ZBLAN) fiber oscillator, a two-stage Tm:ZBLAN fiber preamplifier, and a regenerative amplifier featuring a thermoelectrically cooled thulium-doped yttrium aluminium perovskite crystal (Tm:YAP). The amplifier yields 265 fs 1 mJ pulses at 1940 nm. A portion of the pulse is directed into a polarization-maintaining ZBLAN fiber, generating a multi-octave MIR supercontinuum through self-phase modulation process. This supercontinuum is then collinearly combined with the regenerative amplifier’s output pulse and further amplified within a 1-mm thick gallium selenide crystal through an optical parametric process. The resulting spectra of the signal pulse and the idler pulse span from 2.5 to 4 µm and from 4 to 9 µm, respectively. The combined power of the signal and idler waves reaches 10 mW, with an overall efficiency of 4%. Remarkably, the transform-limited pulse durations for the signal and idler are 22 fs and 17 fs, respectively. This work underscores the successful realization of an advanced collinear MIR OPA system, offering unprecedented capabilities in terms of spectral coverage.
Correlation Effects in a Trapped Bose-Fermi Mixture: Exact Results
Authors: Alon O E , Cederbaum L S 
Published: November 2024

Abstract
Many-body properties of a fermionic impurity embedded in a Bose-Einstein condensate are analyzed analytically using a solvable model, the harmonic-interaction model for Bose-Fermi mixtures. The one-particle and two-particle densities, reduced density matrices, and correlation functions of the fermions and bosons, both in position and momentum spaces, are prescribed in closed form. The various coherence lengths are analyzed. We show that the first-order coherence lengths in position and momentum spaces are equal whereas the second-order quantities can differ substantially. Illustrative examples where the sole interaction is between the impurity and the condensate are presented. Implications are briefly discussed.
Modal dynamics of random Raman lasing in multimode graded-index fibers
Authors: Fan Chenchen , Yao Tianfu , Wu Jian , Xiao Hu , Xu Jiangming , Leng Jinyong , Zhou Pu , Kuznetsov Alexey G. , Wolf Alexey A. , Nemov Ilya N. , Babin Sergey A. 
Published: November 2024

Abstract
Random Raman lasing in multimode graded-index fibers is accompanied by sufficient improvement of the output beam quality in comparison with that for pump radiation resulting in brightness enhancement, however the threshold pump power is rather high. Here we study an opportunity to reduce Raman threshold and to obtain random Raman lasing in laser diode pumped multimode graded-index fiber with enhanced backscattering on artificial fs-inscribed random structures of Rayleigh type (random points) or an array of short fiber Bragg gratings randomly spaced in longitudinal and transverse directions. Another goal is to test scaling capabilities for output power of random Raman finer laser based on natural Rayleigh scattering with higher pump powers. In both experiments, 100-µm graded fibers with UV-laser inscribed FBG (R∼90%) are explored and some kinds of unstable behavior with specific modal dynamics is observed and analyzed.