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Title:Modeliranje za hitro ocenjevanje posledic kemijskih nesreč
Authors:ID Trajkovska, Violeta (Author)
ID Novak Pintarič, Zorka (Mentor) More about this mentor... New window
ID Finšgar, Matjaž (Co-mentor)
Files:.pdf MAG_Trajkovska_Violeta_2016.pdf (1,97 MB)
MD5: 65507168533DFEA07C18B3ECA8BD90DB
 
Language:Slovenian
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FKKT - Faculty of Chemistry and Chemical Engineering
Abstract:Veliko nevarnih snovi se shranjuje, prečrpava in uporablja na številnih industrijskih lokacijah pri podobnih pogojih. Pri tem lahko pride do izpustov in nezgod, ki povzročijo veliko škodo in posledice za ljudi in okolje. Zato je potrebno učinkovito prepoznavanje možnih scenarijev izpustov in ocenjevanje njihovih posledic. V magistrski nalogi je prikazan razvoj empiričnih regresijskih modelov za hitro in približno ocenjevanje posledic nesreč z nevarnimi snovmi, ki povzročijo požar, eksplozije ali strupene koncentracije. Osredotočili smo se na kemikaliji, ki se uporabljata najpogosteje, to sta klor in utekočinjeni naftni plin. Med scenariji smo izbrali katastrofalni trenutni izpust celotne vsebine in iztekanje snovi iz rezervoarja skozi odprtino. Simulacije izpustov smo izvedli z računalniškim programom Phast in določili vplivna območja. Uporabili smo statistične metode, kot je eksperimentalni načrt, za določanje vplivnost vhodnih parametrov. Na osnovi dobljenih rezultatov statističnih testov smo prepoznali tiste vhodne podatke, ki pomembno vplivajo na vplivna območja in izločili preostale. Z uporabo večkratne linearne ali polinomske regresije smo izdelali matematične modele z najmanjšo napako za napoved velikosti vplivnih območij z uporabo pomembnih parametrov. Nazadnje smo preverili ustreznost modela iz prejšnjega koraka tako, da smo izvedli analizo variance, z uporabo F-testa pa smo ocenili, kolikšen delež variacije vplivnih območij lahko pojasnimo z razvitim modelom. Rezultati kažejo da je mogoče s statističnimi metodami določiti manjše število najpomembnejših vhodnih parametrov, ki opisujejo znatni delež variacije vplivnih območij, napovedanih z računalniškimi programi, hkrati pa je možno generirati nelinearne regresijske modele za hitro napovedovanje vplivnih območij ob določeni stopnji zaupanja.
Keywords:klor, utekočinjeni naftni plin, izpust, analiza variance, večkratna polinomska regresija, eksperimentalni načrt
Year of publishing:2016
Publisher:[V. Trajkovska]
Source:Maribor
PID:20.500.12556/DKUM-64626 New window
UDC:546.13:620.262(043.2)
COBISS.SI-ID:20372758 New window
NUK URN:URN:SI:UM:DK:AAP3CDKX
Publication date in DKUM:23.12.2016
Views:1319
Downloads:152
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FKKT
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Secondary language

Language:English
Title:Modeling for quick assessment of chemical accidents consequences
Abstract:Many hazardous substances are stored, pumped and used at several industrial sites under similar conditions. This can lead to emissions and accidents that cause a severe damage and the consequences for people and the environment. Therefore, it is necessary to effectively identify possible scenarios of emissions and assess their consequences. This master's thesis presents the development of the empirical regression models for quick and approximate assessment of the consequences of those accidents involving dangerous substances that result in fires, explosions or toxic concentrations. The focus was on two very common chemicals, namely, the chlorine and liquefield petroleum gas. Two scenarios were studied: a catastrophic instantaneous release of the entire content, and the leakage of the substance from the reservoir through the hole. Simulations of the releases were performed by a computer program Phast, which determined the impact areas. Statistical methods, such as experimental design,were used to determine the influence of the input parameters. Based on the results of the statistical tests, those input parameters were identified that showed significant influence on the impact areas while other parameters were skipped. Linear or polynomial regression methods were applied to generate mathematical models with the smallest error for the predicting the sizes of the impact regions by using the influential input parameters. Finally, the derived models were tested through the analysis of variance by using the F-test, in order to evaluate the appropriateness of the model and the proportions of the impact areas variations that can be explained by the developed model. The results showed that it would be possible to determine a smaller number of the most important input parameters that describe a significant part of variations of impact areas predicted by computer programs, and it would be also possible to derive non-linear regression models for quick prediction of the impact areas at a given confidence level
Keywords:chlorine, liquefied petroleum gas, release, analysis of variance, multiple polynomial regression, experimental design


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