A Review of the Fire and Explosion Hazards of Particulates

Lemkowitz, Saul; Pasman, Hans J.

doi:10.14356/kona.2014010

Cited by 17 publications

(6 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For aerosols and dust suspensions near concentration combustion limits value s X is more than 15 m and value s  is more than 2 min. Those results are in good agreement with experimental data and numerical researches for open spaces, wide channels and wide tubes with smooth walls [2,3], [4,5], [6,7], [8,9], [10]. These results are the basis for designing explosion-proof objects, as well as for making decisions that ensure explosion safety in the operational control mode.…”

Section: And Discussionsupporting

confidence: 84%

“…fuzzy logical variable F D , expressing maintenance of the absence for the combustion suppressing distance [3,4]; fuzzy logical variable F P , expressing exceeding of the initial pressure over the critical one [3,4,10].…”

Section: Fuzzy Logic For Decision Making In Control Systems For Poten...mentioning

confidence: 99%

“…First, it should be taken into account that the possibility of an explosion in the event of a fire may be great [1,4], [5] in spite of the relatively low probability of ignition. This is especially true for coal mines [6,7], [8] and for those enterprises, where explosive dust-air mixtures are formed during the technological process [4,9]. These cases need to be specifically diagnosed, because the damage and loss of life from explosions is much greater than from fires.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mathematical and information models of decision support systems for explosion protection

Volkov¹

2022

AAIT

View full text Add to dashboard Cite

This paper is dedicated to the issue of mathematical and information modeling of the combustion-to-explosion transition that makes it possible to create an adequate mathematical and information support for decision support systems (DSS) for automatedcontrol of explosive objects.A simple mathematical model for the transition of combustion to explosion is constructed. This model is based on solving mathematical problems of the hydrodynamic stability of flames and detonation waves. These problems are reduced to solving eigenvalue problems for linearized differential equations of gas dynamics. Mathematical model is universal enough. It provides opportunities for making simple analytical estimates for the explosive induction distance and the time of the shock wave formation. The possibilities of the transition of slow combustion to both a deflagration explosion and a detonation wave are considered. Theoretical estimates of the explosive induction distance and the time of the combustion-to-explosion transition are obtained. These estimates are expressed by algebraic a formula, the use of which save computer resources and does not require significant computer time. The application of fuzzy logic makes it possible to use the proposed mathematical model of the combustion-to-explosion transition for real potentially explosive objects in industry and transport.Mathematical models of potentially explosive objects are based on combination of the fuzzy logic and classical mathematical methods. These models give possibilities for creating corresponding information models. Thus mathematical and information support of DSS for automated control systems of explosive objects is developed. The main advantage of these DSS is that it makes it possible for decision makers to do without experts. In particular, developed mathematical and information models create the base forsoftware of DSS for explosion safety of grain elevators. Appropriate software is developed and some calculations are performed. These calculations are useful not only from the point of view of testing the proposed method of mathematical modeling of a grain elevator as a potentially explosive object or testing the software itself, but also from the point of view of the grain elevator designing.

show abstract

Section: And Discussionsupporting

confidence: 84%

Section: Fuzzy Logic For Decision Making In Control Systems For Poten...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical and information models of decision support systems for explosion protection

Volkov¹

2022

AAIT

View full text Add to dashboard Cite

show abstract

“…From the results, the particle size of 160 μm shows the highest value of P max for both before and after the drying process which is 1.97 bar and 2.09 bar. As discussed by Lemkowitz and Pasman [18], the behaviour of the dust explosion strongly depends on the particle size. When the particle size decreases, the minimum energy required igniting the dust cloud decreases and thus the P max will increase.…”

Section: Maximum Explosion Overpressure (P Max ) Of Tea Dustmentioning

confidence: 93%

Preliminary study on the tea dust explosion: the effect of tea dust size

et al. 2019

View full text Add to dashboard Cite

Food-based dust is considered as combustible dust as they composed of distinct particles, regardless of the size or chemical composition and when suspended in air or any other oxidizing medium over a range of concentrations will present a fire or deflagration hazard. The explosion effect from food-based dust can cause catastrophic consequences because the initial shock wave from the explosion lift up more dust and triggers a chain reaction through the plant. One of the parameters that can enhance the explosion is the particle size of the dust. In this study, the effect of four different particle sizes of tea dust on the dust explosion severity was tested in a confined 20 L explosion bomb. Tea dust tends to explode due to its molecular structure which contains a carbon-hydrogen bond that can release the significant amount of thermal energy. The experimental results showed that the values of Pmax and (dP/dt)max of tea dust were more severe for the particle size of 160 ?m for which are 1.97 bar and 4.97 bar/s before drying and 2.09 bar and 7.01 bar/s after drying process. The finer dust reacted more violently than coarser ones. As particle size decreases, the rate of explosion pressure change increases, as long as the size is capable of supporting combustion.

show abstract

“…It has a significant impact on energetic efficiency of grinding, resultant particle size distribution and particle shape [ 2 , 3 , 4 , 5 ]. Too dry powders pose the risk of explosion [ 6 , 7 , 8 ], whereas too wet–clog transport pipes and other installation elements [ 9 ]. In addition, usability of the grinding product (as a final product or as input for following technological processes) often depends on contained moisture, e.g., because of its effect on powder flowability [ 10 ], storage methods, and durability (shelf life) [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Measurement-Based Modelling of Material Moisture and Particle Classification for Control of Copper Ore Dry Grinding Process

Krauze

Buchczik

Budzan

2021

Sensors

View full text Add to dashboard Cite

Moisture of bulk material has a significant impact on energetic efficiency of dry grinding, resultant particle size distribution and particle shape, and conditions of powder transport. As a consequence, moisture needs to be measured or estimated (modelled) in many points. This research investigates mutual relations between material moisture and particle classification process in a grinding installation. The experimental setup involves an inertial-impingement classifier and cyclone being part of dry grinding circuit with electromagnetic mill and recycle of coarse particles. The tested granular material is copper ore of particle size 0–1.25 mm and relative moisture content 0.5–5%, fed to the installation at various rates. Higher moisture of input material is found to change the operation of the classifier. Computed correlation coefficients show increased content of fine particles in lower product of classification. Additionally, drying of lower and upper classification products with respect to moisture of input material is modelled. Straight line models with and without saturation are estimated with recursive least squares method accounting for measurement errors in both predictor and response variables. These simple models are intended for use in automatic control system of the grinding installation.

show abstract

A Review of the Fire and Explosion Hazards of Particulates

Cited by 17 publications

References 71 publications

Mathematical and information models of decision support systems for explosion protection

Mathematical and information models of decision support systems for explosion protection

Preliminary study on the tea dust explosion: the effect of tea dust size

Measurement-Based Modelling of Material Moisture and Particle Classification for Control of Copper Ore Dry Grinding Process

Contact Info

Product

Resources

About