Over the past decade, extensive research has been conducted on the strengthening of reinforced concrete (RC) structures using externally bonded fibre reinforced polymer (FRP). More recently, near-surface mounted (NSM) FRP reinforcement has attracted an increasing amount of research as well as practical applications. In the NSM method, grooves are first cut into the concrete cover of an RC element and the FRP reinforcement is bonded inside the groove with an appropriate filler (typically epoxy paste or cement grout). The FRP reinforcement is either prestressed or non-prestressed depending on the required level of strengthening. In all cases, the bond between an NSM bar and the substrate material plays a key role in ensuring the effectiveness of NSM strengthening. The present work investigated experimentally the bond behaviour of non-prestressed and prestressed beams reinforced with near surface mounted carbon fibre reinforced polymer (CFRP) bars under monotonic and fatigue loading. Forty concrete beams were cast and tested in seven groups. The test variables considered in this study were: presence of internal steel reinforcement or not, the type of CFRP rod (spirally wound or sand coated) and the prestressing force (non-prestressed or prestressed). Twenty eight beams were strengthened with non-prestressed CFRP rods; fifteen beams without internal steel reinforcement and thirteen beams with internal steel. Ten beams with internal steel were strengthened with prestressed CFRP rods. The beams were tested in four point bending. In each group, one beam was loaded monotonically. The remaining beams were loaded under different fatigue load levels. The minimum load was kept constant for all beams at 10% of their monotonic capacity and the peak load was varied from one beam to another (denoted as a percentage of the peak load level). Twenty eight beams were strengthened with non-prestressed CFRP rods. Bond failures for the beams with and without internal steel, strengthened with CFRP rods and tested under monotonic or fatigue loads was by debonding between the CFRP rod and the epoxy that started at the loading point and as the load was increased or cycled, the debonding spread towards the support until failure occurred. A comparison of the fatigue life curves for the beams with and without steel, strengthened with CFRP rods revealed that the sand coated rod had better bond characteristics than the spirally wound rod (at the same load range the beam strengthened with sand coated rod had a longer life than the beam strengthened with spirally wound rod). Beams with internal steel, strengthened with CFRP rods and tested under fatigue loading failed in bond at high load levels (short fatigue lives) and by rupture of the steel rebar at low load levels (long fatigue lives). Ten beams with internal steel were strengthened with prestressed CFRP rods. The CFRP rods were prestressed to a force of 62 kN which corresponds to 45% and 40% of the monotonic capacity of the spirally wounded and sand coated rods, respectively. Almost all the beams with internal steel that were strengthened with prestressed CFRP rods failed by slipping between the CFRP rod and the epoxy that started at the support and propagated inwards towards the loading point. The exception to this was the beam strengthened with prestressed sand coated rod and tested under monotonic loading that failed by debonding between the CFRP rod and the epoxy that started at the loading point and propagated towards the support. Comparing the load range (kN) versus life curve for the beams with steel, strengthened with prestressed spirally wound and sand coated rods that failed in bond, shows that the beam strengthened with sand coated rod has longer fatigue lives than beam strengthened with spirally wound rod. A model was used to describe the progress of the debonding crack until excessive slipping occurred. The model predicted the number of cycles until excessive slipping between the CFRP rod and the epoxy occurred and the forces in the CFRP rod at all locations in the shear span at the onset of failure with reasonable accuracy.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Abdel-Khalik, Said; Committee Member: Ammar, Mostafa H.; Committee Member: Ghiaasiaan, S. Mostafa; Committee Member: Hertel, Nolan E.; Committee Member: Liu, Yingjie.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisor: Oguzhan Bayrak. Vita. Includes bibliographical references.

Made available in DSpace on 2014-10-09T12:36:09Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:59:22Z (GMT). No. of bitstreams: 1 03640.pdf: 2315648 bytes, checksum: 3e352de4928e7b2ab584e9544c03cb24 (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP

Made available in DSpace on 2014-10-09T12:32:22Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:10:26Z (GMT). No. of bitstreams: 1 12903.pdf: 6975224 bytes, checksum: a1cdb876db960cf944dfe544cb40e00b (MD5) / Dissertacao (Mestrado) / IPEN/D / Universidade Estadual de Campinas - UNICAMP/SP

Made available in DSpace on 2014-10-09T12:36:09Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:59:22Z (GMT). No. of bitstreams: 1 03640.pdf: 2315648 bytes, checksum: 3e352de4928e7b2ab584e9544c03cb24 (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP

Made available in DSpace on 2014-10-09T12:32:22Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:10:26Z (GMT). No. of bitstreams: 1 12903.pdf: 6975224 bytes, checksum: a1cdb876db960cf944dfe544cb40e00b (MD5) / Dissertacao (Mestrado) / IPEN/D / Universidade Estadual de Campinas - UNICAMP/SP

The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. This is traditionally executed using fuel performance codes such as the Transuranus and FRAPCON. These codes offer intricate and accurate models of the underlying physical processes that govern fuel rod performance, encompassing aspects like linear heat generation rates, neutron flux and their irradiation effects, fuel rod expansion and contraction, clad corrosion, and fission gas release. However, fuel performance codes cannot be easily parallelized using modern hardware accelerators, such as graphic processing units, due to their iterative nature that follows from the complexity of coupling multiphysics-based models. Thus, they can only simulate one fuel rod at a time per CPU. The challenge comes when trying to simulate all the 10,000 to 100,000 fuel rods in a typical pressurized water reactor, which is a relatively slow process as compared to parallelized computation for all time steps using a GPU. To improve the speed aspect of the fuel performance modeling, a data-driven surrogate model based on neural networks is developed. The main advantage of a neural network over fuel performance codes is its ability to perform parallelized computations using one or more GPUs. The preexisting architectures that were explored include Temporal Convolutional Network, Fourier Neural Operator, and a Transformer. Additionally, a novel architecture is proposed, the Temporal Frequency Network. This is a heterogeneous ensemble method that is based on the Temporal Convolutional Network and the Fourier Neural Operator. The newly proposed architecture archives the lowest validation error among the preexisting architectures with a minor increase in the computations as compared to the ensemble components. The Temporal Frequency Network is then applied to take time-dependent inputs in the form of linear heat generation rate and use it as the only information to predict various time-dependent variables of the fuel rods. The predicted variables include fuel center-line temperature, central void pressure, oxidation thickness, fuel gap width, hydrogen absorption, integral fission gas release, and integral fractional gas release. When deploying the neural network in practice, the user cannot in general trust that the model will generalize from its training, especially in fuel performance modeling where accurate predictions are important to demonstrate safe operation. To ensure that the predictions of the model are reliable, a separate neural network called decoder is trained to qualitatively quantify the error of the previous model that made the predictions, called encoder. This is done by training the decoder to reconstruct the original input to the encoder by providing it with the output, e.g., the inverse task. It is then possible to compare the original input with the reconstructed input, thus, an error can be computed that can be used to qualitatively determine the quality of the predictions.  With the Temporal Frequency Network, the average validation error was roughly 1% error. This makes it a strong candidate surrogate model for fuel performance modeling. In addition, with the encoder-decoder setup, this work provides a robust framework for error estimation that can be performed on new, potentially out-of-distribution inputs without the need for a fuel performance code. This setup is therefore suitable for applications where a low false negative rate is desired. / Huvudkomponenten i ett kärnkraftverk är reaktorn och bränslestavarna som förser den med kärnbränsle. Effektiv och säker energiextraktion är därför starkt beroende av reaktorns utformning och bränslestavarnas skick. För att förutse högkvalitativ drift och potentiella risker i förväg måste man utföra simuleringar på bränslestavarna. Detta utförs traditionellt med bränslestavskoder som Transuranus och FRAPCON. Denna uppgift utförs traditionellt med bränsleprestandakoder som Transuranus och FRAPCON. Dessa koder tillhandahåller detaljerade och exakta modeller som modellerar bränslestavens fysikaliska beteende. Modelleringen i denna arbete omfattar aspekter som linjär längdvärmebelastning, snabbneutronflöde och deras bestrålnings effekter, expansion samt kontraktion av bränslestaven, kapslingskorrosion och utsläpp av fissionsgas. Emellertid kan dessa bränslestavskoder inte enkelt parallelliseras med moderna hårdvaruacceleratorer som grafikprocessorer på grund av deras iterativa karaktär som följer från komplexitiviteten med att modellera multiskaliga system med kopplade interaktioner mellan variablerna. Koderna kan således endast simulera ett bränslestav åt gången per CPU. Utmaningen uppstår när man försöker simulera alla 10,000 till 100,000 bränslestavar i en typisk tryckvattenreaktor, vilket är en relativt tidskrävande process i jämnförelse till paralelliserad beräkning för alla tidssteg genom att använda en GPU. För att reducera tiden för bränslestavsmodelleringen utvecklades en datadriven surrogatmodell som är baserad på neurala nätverk. Den viktigaste fördelen som ett neural nätverk har över en bränslestavskod är dess förmåga att utföra paralleliserade beräkningar genom att använda en eller flera GPU:er. De befintliga arkitekturerna som utforskades inkluderar Temporala faltningsnätverk, Fourier neurala operatorn och en Transformer. Dessutom föreslås en ny arkitektur, Temorala frekvensnätverk. Arkitekturen är en heterogen ensemblemetod som bygger på Temporala faltningsnätverk och Fourier neurala operator. Den nyligen föreslagna arkitekturen uppnår det lägsta valideringsfelet bland de föreslagna arkitekturerna med en mindre ökning av antal beräkningar i jämnförelse med dess individa ensemblekomponenter. Temporala frekvensnätverket användes sedan för att ta tidsberoende indata i form av linjära längdvärmebelastning och använda den som den enda informationen för att förutsäga olika tidsberoende variabler hos bränslestavarna. De förutsagda variablerna inkluderar bränslets temperatur, trycket hos den fria volymen, oxidationstjocklek, bränslegapsbredd, väteabsorption hos kapslingen, ackumulerad generad fissiongas och totalt relativt fissiongasutsläpp. När man implementerar det neurala nätverket i praktiken kan användaren i allmänhet inte lita på att modellen kommer att generalisera från sin träning, särskilt i bränslestavsmodellering där förutsägelser med hög noggrannhet är viktiga för att demonstrera säker drift. För att säkerställa att förutsägelserna är tillförlitliga tränas ett separat neuralt nätverk för att vara en avkodare vars uppgift är att kvantifiera kvaliteten på förutsägelser som görs av den tidigare modellen, kodaren. Detta uppnås genom att träna avkodaren på att lära sig funktionen som avbildar utdatan till indatan. På så vis kan den ursprungliga indatan jämnföras med den rekonstruerade indatan, och ett fel kan beräknas för att kvalitativt avgöra kvaliten hos prediktionerna av kodaren. Med Temporala frekvensnätverket hölls det genomsnittliga valideringsfelet vid cirka 1%, vilket gör det till en stark kandidat för bränslestavsmodellering. Dessutom, med uppställningen för kodare-avkodare, erbjuder detta arbete en robust utgångspunkt för felförutsägelse som kan utföras på nya indata som potentiellt är urvald bortom fördelningen för träningsdatan utan att behöva använda en bränslestavskod. Denna uppställning är därför lämplig för tillämpningar där låg andel falska negativa fall är önskvärd.

<p> An exact analysis for the state of strain in a three dimensional rod continuum is presented. The exact geometrical description of the rod involves the evaluation of a power series expansion of the radius vector. It is shown however, that by a suitable choice of coordinates in the reference configuration and an interpretation of the deformation gradient as a material transformation, the strain tensor may be evaluated to the degree of accuracy inherent in using the full power series expansion of the radius vector without necessitating the explicit evaluation of the power series. Some concepts from the theory of multipolar media are used in order to make this three dimensional analysis compatible with the exact analysis of one dimensional rods.</p> / Thesis / Master of Engineering (MEngr)

Scope and Contents: The first chapter of this thesis consists of a general introduction and a brief description of previous work done in this same laboratory. Also included is a preliminary description of the present experiment. This is followed, in Chapter 2, by a detailed description of the experimental apparatus. The third and last chapter contains a description of the procedure used in obtaining results, as well as the results themselves. Measurements were made of the diffraction patterns of a plastic prism, and five rods in a total of nine different cases. In all cases, the intensity measurements were made along the axis of propagation of the incident beam behind the diffracting object. A polarization normal to the axis of the rods was used. Theoretical calculations were made in three cases, and compared with the experimental results. / Thesis / Master of Science (MS)