doktorska disertacija
Urška Dolinar (Avtor), Tomaž Hozjan (Mentor), Goran Turk (Član komisije za zagovor), Miha Boltežar (Član komisije za zagovor), Jurij Karlovšek (Član komisije za zagovor), Gregor Trtnik (Komentor)

Povzetek

V doktorski disertaciji nas je zanimala ocena nosilnosti armiranobetonskih (AB) okvirnih konstrukcij po požaru, kar smo izvedli v dveh delih. V prvem delu smo predstavili različne neporušne in porušne metode preizkušanja betona, ki so uporabljene v eksperimentalnem delu. V okviru eksperimentalnega dela je bilo izdelanih pet različnih betonskih mešanic z apnenčevim agregatom, ki se med seboj razlikujejo v vodo-cementnem razmerju, vrsti cementa ter količini vode in dodatkov. Betonski preizkušanci so bili po končani negi in sušenju na zraku v električni peči izpostavljeni temperaturam 200 °C, 400 °C, 600 °C oziroma 800 °C in nato ohlajeni na sobno temperaturo. Sledilo je eksperimentalno preizkušanje, pri čemer so bile uporabljene neporušne in porušne metode. Referenčne vrednosti eksperimentalnih meritev so bile določene na skupini preizkušancev, ki niso bili predhodno segrevani. Rezultati neporušnih preizkusov zajemajo določitev hitrosti preleta vzdolžnih ultrazvočnih valov, površinske trdnosti betona, dinamičnega modula elastičnosti in strižnega modula betona, medtem ko porušni preizkusi zajemajo določitev tlačne in upogibne natezne trdnosti ter modula elastičnosti betona. Nato je bilo s statističnimi metodami ugotovljeno, da temperatura statistično značilno vpliva na omenjene eksperimentalne rezultate, s čimer zaznamo spremembe med posameznimi predhodno segretimi preizkušanci. Sledila je ocena mehanskih lastnosti betona po izpostavljenosti povišanim temperaturam, imenovanih tudi preostale mehanske lastnosti, z regresijskima modeloma z eksplicitnimi zvezami in umetnimi nevronskimi mrežami. Pri tem smo ugotovili, da preostalo upogibno natezno trdnost in modul elastičnosti betona zelo natančno lahko ocenimo na podlagi regresijskih modelov z eksplicitnimi zvezami, medtem ko je za natančnejšo oceno preostale tlačne trdnosti potrebna uporaba umetnih nevronskih mrež. V drugem delu je na kratko predstavljen numerični model za določitev požarne odpornosti linijskih AB konstrukcij po požaru Nfira, ki deluje v programskem okolju Matlab. Novost numeričnega modela so eksperimentalno določeni materialni parametri konstitucijske zveze betona z apnenčevim agregatom po izpostavljenosti povišanim temperaturam. Sledila je izdelava parametričnih študij, pri čemer je bil raziskan vpliv različnih razvojev temperature po požarnem prostoru kot tudi vpliv sestave betonske mešanice na odziv linijskih AB konstrukcij po požaru.

Ključne besede

Grajeno okolje;gradbeništvo;disertacije;povišane temperature;eksperimentalne raziskave;neporušne metode;umetne nevronske mreže;požarna analiza;konstitucijske zveze betona;mehanska analiza linijskih AB elementov;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.08 - Doktorska disertacija
Organizacija: UL FGG - Fakulteta za gradbeništvo in geodezijo
Založnik: [U. Blumauer]
UDK: 624.012.35:624.94:614.84(043)
COBISS: 43010819 Povezava se bo odprla v novem oknu
Št. ogledov: 593
Št. prenosov: 167
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: Estimation of load bearing capacity of reinforced concrete frames after fire
Sekundarni povzetek: In our dissertation we dealt with the estimation of the load bearing capacity of reinforced concrete (RC) frame structures after fire, which we carried out in two parts. In the first part we presented various non-destructive and destructive methods for concrete testing used in the experimental part. Within the experimental investigation we prepared five different concrete mixtures with limestone aggregate, which differ in water to cement ratio, type of cement and the amount of water and additives. After the curing and air drying procedure the concrete samples were exposed to high temperatures 200 %C, 400 %C, 600 %C or 800 %C in an electric furnace and then cooled to the room temperature. This was followed by experimental investigation using non-destructive and destructive test methods. The reference values of the experimental measurements were determined on a non-preheated group of test specimens. The results of the non-destructive tests include the determination of the ultrasound (US) pulse velocity, the surface strength, the dynamic modulus of elasticity and the shear modulus of concrete, while destructive tests include the determination of the compressive and flexural strengths and the modulus of elasticity of concrete. Using statistical methods it was then determined that temperature has a statistically significant influence on the above mentioned experimental results, meaning that changes between individual preheated specimens can be detected. This was followed by an estimation of the mechanical properties of concrete after exposure to high temperatures, also named residual mechanical properties, using regression models with explicit relationships and artificial neural networks. We found that the residual flexural strength and modulus of elasticity of concrete can be estimated very accurately based on regression models with explicit relationships, whereas a more accurate estimation of residual compressive strength requires the use of artificial neural networks. In the second part a numerical model for the determination of the fire resistance of planar RC structures after a fire, named Nfira, is briefly presented. The novelty of the numerical model are the experimentally determined material parameters of the constitutive law of limestone concrete after exposure to high temperatures. This was followed by the parametric studies in which the influence of different fire scenarios and concrete mixture on the behavior of planar RC structures after fire were investigated.In our dissertation we dealt with the estimation of the load bearing capacity of reinforced concrete (RC) frame structures after fire, which we carried out in two parts. In the first part we presented various non-destructive and destructive methods for concrete testing used in the experimental part. Within the experimental investigation we prepared five different concrete mixtures with limestone aggregate, which differ in water to cement ratio, type of cement and the amount of water and additives. After the curing and air drying procedure the concrete samples were exposed to high temperatures 200 %C, 400 %C, 600 %C or 800 %C in an electric furnace and then cooled to the room temperature. This was followed by experimental investigation using non-destructive and destructive test methods. The reference values of the experimental measurements were determined on a non-preheated group of test specimens. The results of the non-destructive tests include the determination of the ultrasound (US) pulse velocity, the surface strength, the dynamic modulus of elasticity and the shear modulus of concrete, while destructive tests include the determination of the compressive and flexural strengths and the modulus of elasticity of concrete. Using statistical methods it was then determined that temperature has a statistically significant influence on the above mentioned experimental results, meaning that changes between individual preheated specimens can be detected. This was followed by an estimation of the mechanical properties of concrete after exposure to high temperatures, also named residual mechanical properties, using regression models with explicit relationships and artificial neural networks. We found that the residual flexural strength and modulus of elasticity of concrete can be estimated very accurately based on regression models with explicit relationships, whereas a more accurate estimation of residual compressive strength requires the use of artificial neural networks. In the second part a numerical model for the determination of the fire resistance of planar RC structures after a fire, named Nfira, is briefly presented. The novelty of the numerical model are the experimentally determined material parameters of the constitutive law of limestone concrete after exposure to high temperatures. This was followed by the parametric studies in which the influence of different fire scenarios and concrete mixture on the behavior of planar RC structures after fire were investigated.
Sekundarne ključne besede: Built Environment;civil engineering;doctoral thesis;high temperatures;experimental research;non-destructive techniques;artificial neural networks;fire analysis;constitutive law of concrete;mechanical analysis of RC elements;
Vrsta dela (COBISS): Doktorsko delo/naloga
Komentar na gradivo: Univ. v Ljubljani, Fak. za gradbeništvo in geodezijo
Strani: XXII, 133 str.
ID: 12375805