Experimental thermal hydraulic studies on the enhancement of safety of LWRs

The safe use of nuclear power plants (NPPs) requires a deep understanding of the functioning of physical processes and systems involved. Studies on thermal hydraulics have been carried out in various separate effects and integral test facilities at Lappeenranta University of Technology (LUT) either to ensure the functioning of safety systems of light water reactors (LWR) or to produce validation data for the computer codes used in safety analyses of NPPs. Several examples of safety studies on thermal hydraulics of the nuclear power plants are discussed. Studies are related to the physical phenomena existing in different processes in NPPs, such as rewetting of the fuel rods, emergency core cooling (ECC), natural circulation, small break loss-of-coolant accidents (SBLOCA), non-condensable gas release and transport, and passive safety systems. Studies on both VVER and advanced light water reactor (ALWR) systems are included. The set of cases include separate effects tests for understanding and modeling a single physical phenomenon, separate effects tests to study the behavior of a NPP component or a single system, and integral tests to study the behavior of the whole system. In the studies following steps can be found, not necessarily in the same study. Experimental studies as such have provided solutions to existing design problems. Experimental data have been created to validate a single model in a computer code. Validated models are used in various transient analyses of scaled facilities or NPPs. Integral test data are used to validate the computer codes as whole, to see how the implemented models work together in a code. In the final stage test results from the facilities are transferred to the NPP scale using computer codes. Some of the experiments have confirmed the expected behavior of the system or procedure to be studied; in some experiments there have been certain unexpected phenomena that have caused changes to the original design to avoid the recognized problems. This is the main motivation for experimental studies on thermal hydraulics of the NPP safety systems. Naturally the behavior of the new system designs have to be checked with experiments, but also the existing designs, if they are applied in the conditions that differ from what they were originally designed for. New procedures for existing reactors and new safety related systems have been developed for new nuclear power plant concepts. New experiments have been continuously needed.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Experimental Studies on Non-Metallic Composite Bone Implants With a Special Reference to Staphylococcal Biofilm Infection

Non-metallic implants made of bioresorbable or biostable synthetic polymers are attractive options in many surgical procedures, ranging from bioresorbable suture anchors of arthroscopic surgery to reconstructive skull implants made of biostable fiber-reinforced composites. Among other benefits, non-metallic implants produce less interference in imaging. Bioresorbable polymer implants may be true multifunctional, serving as osteoconductive scaffolds and as matrices for simultaneous delivery of bone enhancement agents. As a major advantage for loading conditions, mechanical properties of biostable fiber-reinforced composites can be matched with those of the bone. Unsolved problems of these biomaterials are related to the risk of staphylococcal biofilm infections and to the low osteoconductivity of contemporary bioresorbable composite implants. This thesis was focused on the research and development of a multifunctional implant model with enhanced osteoconductivity and low susceptibility to infection. In addition, the experimental models for assessment, diagnostics and prophylaxis of biomaterial-related infections were established. The first experiment (Study I) established an in vitro method for simultaneous evaluation of calcium phosphate and biofilm formation on bisphenol-Aglycidyldimethacrylate and triethylenglycoldimethacrylate (BisGMA-TEGDMA) thermosets with different content of bioactive glass 45S5. The second experiment (Study II) showed no significant difference in osteointegration of nanostructured and microsized polylactide-co-glycolide/β-tricalcium phosphate (PLGA /β-TCP) composites in a minipig model. The third experiment (Study III) demonstrated that positron emission tomography (PET) imaging with the novel 68Ga labelled 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) CD33 related sialic-acid immunoglobulin like lectins (Siglec-9) tracer was able to detect inflammatory response to S. epidermidis and S. aureus peri-implant infections in an intraosseous polytetrafluoroethylene catheter model. In the fourth experiment (Study IV), BisGMATEGDMA thermosets coated with lactose-modified chitosan (Chitlac) and silver nanoparticles exhibited antibacterial activity against S. aureus and P. aeruginosa strains in an in vitro biofilm model and showed in vivo biocompatibility in a minipig model. In the last experiment (Study V), a selective androgen modulator (SARM) released from a poly(lactide)-co-ε-caprolactone (PLCL) polymer matrix failed to produce a dose-dependent enhancement of peri-implant osteogenesis in a bone marrow ablation model.