Development of an HTR-10 model in the Serpent reactor physics code

The use of exact coordinates of pebbles and fuel particles of pebble bed reactor modelling becoming possible in Monte Carlo reactor physics calculations is an important development step. This allows exact modelling of pebble bed reactors with realistic pebble beds without the placing of pebbles in regular lattices. In this study the multiplication coefficient of the HTR-10 pebble bed reactor is calculated with the Serpent reactor physics code and, using this multiplication coefficient, the amount of pebbles required for the critical load of the reactor. The multiplication coefficient is calculated using pebble beds produced with the discrete element method and three different material libraries in order to compare the results. The received results are lower than those from measured at the experimental reactor and somewhat lower than those gained with other codes in earlier studies.

Leijukattilan savukaasujen loppulämpötilan hallinta

Nykyaikaista leijukattilaa voidaan ohjata ja säätää erilaisten säätöpiirien ja sekvenssien kautta erittäin tarkasti. Toiminnot on optimoitu parhaan hyötysuhteen saavuttamiseksi ja kunnossapitokustannusten minimoimiseksi. Tehokkaasta automaatiosta ja nykyaikaisista laitevalinnoista huolimatta leijukattiloissa on usein yksi osa-alue, jota ei pystytä hallitsemaan tehokkaasti. Useilla voimalaitoksilla savukaasu poistuu liian korkeassa lämpötilassa viimeiseltä lämpöpinnalta. Kun kattilahyötysuhdetta tarkastellaan epäsuoralla menetelmällä, savukaasuhäviö on merkittävin tekijä kaikista häviöstä. Tässä diplomityössä on etsitty mahdollisuuksia savukaasun loppulämpötilan hallintaan kattilan ajoarvojen muutoksella sekä lämpöpintoja muuttamalla. Tutkimus keskittyy Järvi-Suomen Voima Oy:n Ristiinan voimalaitokselle. Tutkimus on tehty yhteistyössä laitoksen omistajien Pohjolan Voima Oy:n, UPM-Kymmene Oyj:n sekä laitetoimittaja Valmet Oyj:n kanssa.

Energy aware software for many-core systems

Many-core systems provide a great potential in application performance with the massively parallel structure. Such systems are currently being integrated into most parts of daily life from high-end server farms to desktop systems, laptops and mobile devices. Yet, these systems are facing increasing challenges such as high temperature causing physical damage, high electrical bills both for servers and individual users, unpleasant noise levels due to active cooling and unrealistic battery drainage in mobile devices; factors caused directly by poor energy efficiency. Power management has traditionally been an area of research providing hardware solutions or runtime power management in the operating system in form of frequency governors. Energy awareness in application software is currently non-existent. This means that applications are not involved in the power management decisions, nor does any interface between the applications and the runtime system to provide such facilities exist. Power management in the operating system is therefore performed purely based on indirect implications of software execution, usually referred to as the workload. It often results in over-allocation of resources, hence power waste. This thesis discusses power management strategies in many-core systems in the form of increasing application software awareness of energy efficiency. The presented approach allows meta-data descriptions in the applications and is manifested in two design recommendations: 1) Energy-aware mapping 2) Energy-aware execution which allow the applications to directly influence the power management decisions. The recommendations eliminate over-allocation of resources and increase the energy efficiency of the computing system. Both recommendations are fully supported in a provided interface in combination with a novel power management runtime system called Bricktop. The work presented in this thesis allows both new- and legacy software to execute with the most energy efficient mapping on a many-core CPU and with the most energy efficient performance level. A set of case study examples demonstrate realworld energy savings in a wide range of applications without performance degradation.