Smoke detectors face the challenges of increasing accuracy, sensitivity, and high reliability in complex use environments to ensure the timeliness, accuracy, and reliability of very early fire ...detection. The improvement and innovation of the principle and algorithm for smoke particle concentration detection provide opportunities for improving the performance of the detector. This study represents a new refinement of the smoke concentration detection principle based on capacitive detection of cell structures, and detection signals are processed by a multiscale smoke particle concentration detection algorithm to calculate smoke concentration. Through experiments, it was found that the detector provides effective detection of smoke particle concentrations ranging from 0 to 10% obs/m; moreover, when the detection accuracy is greater than a certain number of parts per million (PPM), the sensitivity of the detector can reach the PPM level; furthermore, the detector can detect smoke particle concentrations higher than the PPM level accuracy even in an environment with a certain concentration of petroliferous and dust particles of different sizes.
Smoke detectors face the challenges of increasing accuracy, sensitivity, and high reliability in complex use environments to ensure the timeliness, accuracy, and reliability of very early fire ...detection. The improvement in and innovation of the principle and algorithm of smoke particle concentration detection provide an opportunity for the performance improvement in the detector. This study is a new refinement of the smoke concentration detection principle based on capacitive detection of cell structures, and detection signals are processed by a multiscale smoke particle concentration detection algorithm to calculate particle concentration. Through experiments, it is found that the detector provides effective detection of smoke particle concentrations ranging from 0 to 10% obs/m; moreover, the detector can detect smoke particles at parts per million (PPM) concentration levels (at 2 and 5 PPM), and the accuracy of the detector can reach at least the 0.5 PPM level. Furthermore, the detector can detect smoke particle concentrations at better than 1 PPM accuracy even in an environment with 6% obs/m oil gas particles, 7% obs/m large dust interference particles, or 8% obs/m small dust interference particles.
•The flow field profiles along the tunnel under ventilation conditions were measured.•The excess temperature profile of the tunnel has been studied.•A non-dimensional model for the ceiling ...temperature decay under stable smoke layer condition has been developed.•Higher smoke concentrations result in faster decay of the ceiling temperature.
The methanol-gasoline blends fire-induced smoke temperature profiles were measured in full scale tunnel fire experiments with different blends and different longitudinal ventilation conditions. The flow field profile, which was nonuniform in the full-scale tunnel, was characterized by the wind speeds of tunnel cross-sections. The experiments investigated the ceiling temperatures along the tunnel centerline, the smoke layer temperature profiles, the smoke transmissivities and other parameters. A model was developed for the ceiling temperature decay along the tunnel under stable fire-induced smoke layer conditions based on theoretical analysis and the curve fits of the ceiling temperature decay with distance from the fire source. Higher smoke transmissivity resulted in higher visibility and lower smoke concentration. The smoke concentration significantly influences the ceiling temperature decay with higher smoke concentration leading to faster decay of the ceiling temperature.
In some countries, test standards have been adopted which measure the effectiveness of smoke exhaust systems in clearing out heat and smoke produced separately. However, because these standards ...provide no quantitative provisions for dealing with the amount of visual smoke, there is an unclear correlation between the amount of smoke generated and the fire load. This paper applied the homogeneity concept of using a smoke collection box to examine the smoke generation rate of a smoke generator using CO2 as the driving gas. To avoid using the previous visual method of judging the rates, this research used measurement equipment to conduct a scientific analysis. Thus, the results were more objective. The equipment used included a Closed-Circuit Television (CCTV) Camera, a thermocouple, a traditional P-type smoke detector, a digital R-type smoke detector, and light attenuation measurement equipment. Under release pressures of 40, 60 and 80 psi, a 15% smoke density required smoke generation at 6.50, 8.42 and 10.46 m
3
/s, respectively. Achieving a homogeneous distribution of smoke within the space was accomplished. The data obtained in the test could be used not only to judge the efficiency of a smoke exhaust system but also provide adjustment information for a smoke exhaust system.
This study aims to evaluate the safety and efficacy of various levels of moxibustion smoke concentration (MSC), represented by particulate matter 10mm (PM
), on pain and motor dysfunction in patients ...with stage 1 post-stroke shoulder-hand syndrome (SHS).
In this multi-center, sham-controlled, single-blind, randomized controlled trial (RCT), a total of 140 eligible patients with stage 1 post-stroke SHS will be recruited from March 2022 to February 2023 and randomly allocated to five groups in a ratio of 1:1:1:1:1. Moxibustion, in addition to standard medical care, will be applied to subjects in all groups. No acupoints on the affected upper limb will be utilized. Moxibustion smoke therapy, with varying levels of MSC, will be applied to the five groups as follows: (A) sham control group, (B) zero MSC group, (C) low MSC group, (D) medium MSC group, and (E) high MSC group. Patients in each group will be treated for 20 minutes per session, with five sessions each week, over a course of six weeks, with a total follow-up interval of eight weeks. The primary outcome measure will be a visual analog scale (VAS) assessment of the intensity of regionalized pain in the affected upper limb. Secondary outcome measures will include scoring on the Fugl-Meyer Assessment of the Upper Extremity Scale (FMA-UE), the Modified Barthel Index (MBI) and the measurement of somatosensory evoked potential (SEP). All participants will be evaluated before treatment, during treatment (ie, at two weeks and four weeks), immediately after concluding treatment (ie, at six weeks) and at two weeks post-treatment (ie, at eight weeks). Intention-to-treat analysis will be applied.
ChiCTR2100043076.
In order to solve the complex production process, high technical content, bad working environment, frequent blowout accidents, and other problems. A method based on the concentration distribution ...characteristics of explosion flue gas emission in deepwater area is proposed. Based on the computational fluid dynamics theory, the basic governing equations of blowout and explosion of natural gas in deepwater are obtained. Based on the basic governing equations of deepwater natural gas blowout and explosion, the diffusion of natural gas in deepwater natural gas blowout and explosion is studied by using the K-turbulence model. The diffusion process of gas explosion in deepwater is obtained. Two Gaussian smoke model parameters, atmospheric diffusion parameter and average wind speed, were realized by combining the segmenting smoke flow with Gaussian smoke mass concentration distribution. The blowout and explosion process of natural gas in deepwater is simulated by MATLAB software, and the distribution characteristics of flue gas concentration are analyzed. The results showed that the smoke concentration and the change of smoke concentration were not affected by the change.
As some parts of the Building Standards Act have been specified in 2000, and more safety secured by the Method of Verification for Evacuation Safety, a wider range of architectural design has become ...possible. Safety is more confirmed by the Method of Verification for Evacuation Safety as it evaluates performance by calculating Evacuation time, unlike former regulations. Evacuation time is consisted of ‹Starting time of Evacuation›, the time taken from the start of fire until the start of evacuation, and ‹Behavior time of Evacuation›, the time taken from the start of evacuation until the people evacuating arrive at a safe area. It is confirmed by studies from the past that it is more important to study Starting time of Evacuation as it is more likely to take up most of Evacuation time, compared to Behavior time of Evacuation. Unfortunately, the calculation of Starting time of Evacuation shown in the Method of Verification for Evacuation Safety only considers the surface area of the room and does not consider human characteristics such as vision and smell. Therefore, the establishment of a calculating method that considers human characteristics is requested. In order to calculate Starting time of Evacuation, the time taken to sense emergency and its factor is important. A factor that lets people sense emergency can be witnessing a fire or smoke, hearing a crowd, or breathing in the smell of smoke. Studies focusing on visual factors shows that smoke originated from the fire stays around the lightings on the ceiling, and the visual detection of change in luminance due to increase in smoke density, leads to accident perception. Therefore Starting time of Evacuation based on accident perception can be assumed as the time taken to visually detect the change in luminance under ceiling lightings. To estimate Starting time of Evacuation , a calculation model that derives the change in luminance under ceiling lightings due to the relationship between different space elements (wall reflectance, illuminance, room dimension) and smoke density is needed. Additionally, smoke density changes from moment to moment therefore the model estimating smoke density is needed to be represented by time as its variable. That been said, by making clear how people react to luminance change, it is possible to construct a model that estimates Starting time of Evacuation with space elements as its variable. In this study, an experiment was executed by creating an equipment that measures luminance with space elements as its variables, in purpose of constructing a model to estimate the luminance of ceiling lightings from the relationship between space elements and smoke density. In addition, a combustion experiment assuming an initial fire in an actual size model was held, in purpose of constructing s model that estimates smoke density with time as its variable. In conclusion, the Luminance Estimation Model, and the Smoke Concentration Estimation Model were individually constructed, and its consistency were confirmed by comparing the estimate and actual measurements. Moreover, by combining the two models, a model that estimates the luminance of ceiling lighting by the relationship between time and actual space elements was constructed.
PDF
