Hammashihnajohdeakseleiden liikkeiden synkronointi

Nykyisessä valmistusteollisuudessa erilaisten robottien ja automatisoitujen tuotantovaiheiden rooli on erittäin merkittävä. Tarkasti suunnitellut liikkeet ja toimintavaiheet voidaan nykyisillä järjestelmillä ajoittaa tarkasti toisiinsa nähden, jolloin erilaisten virhetilanteidenkin sattuessa järjestelmä pystyy toimimaan tilanteen edellyttämällä tavalla. Automatisoinnin etuna on myös tuotannon muokkaaminen erilaisten tuotteiden valmistamiseen pienillä muutoksilla, jolloin tuotantokustannukset pysyvät matalina myös pienten valmistuserien tapauksissa. Usean akselin laitteissa eli niin sanotuissa moniakselikäytöissä laitteen toimintatarkkuus riippuu jokaisen liikeakselin tarkkuudesta. Liikkeenohjauksessa on perinteisesti ollut käytössä myötäkytketty paikkakaskadi, jonka virityksessä otetaan huomioon akselilla olevat erilaiset dynaamiset tilat ja käytettävät referenssit. Monissa nykyisissä hajautetuissa järjestelmissä eli moniakselikäytöissä, joissa jokaiselle akselille on oma ohjauslaite, ei yksittäisen akselin paikkavirhettä huomioida muiden akseleiden ohjauksessa. Työssä tutkitaan erilaisia moniakselijärjestelmien ohjausmenetelmiä ja myötäkytketyn paikkakaskadin toimintaa moniakselikäytössä pyritään parantamaan tuomalla paikkasäätimen rinnalle toinen säädin, jonka tulona on akseleiden välinen paikkaero.

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.

An EDTA-β-cyclodextrin adsorbent for the adsorption of rare earth elements and its application in preconcentration of ultratrace rare earth elements from seawater

The objectives of this work were synthesizing an EDTA-β-CD adsorbent and investigating its adsorption potential and applications in preconcentration of REEs from aqueous phase. The adsorption capacity of EDTA-β-CD was investigated. The adsorption studies were performed by batch techniques both in one- and multi-component systems. The effects of pH, contact time and initial concentration were evaluated. The analytical detection methods and characterization methods were presented. EDTA-β-CD adsorbent was synthesized successfully with high EDTA coverage. The maximum REEs uptake was 0.310 mmol g-1 for La(III), 0.337 mmol g-1 for Ce(III) and 0.353 mmol g-1 for Eu(III), respectively. The kinetics of REEs onto EDTA-β-CD fitted well to pseudo-second-order model and the adsorption rate was affected by intra-particle diffusion. The experimental data of one component studies fitted to Langmuir isotherm model indicating the homogeneous surface of the adsorbent. The extended Sips model was applicable for the isotherm studies in three-component system. The electrostatic interaction, chelation and complexation were all involved in the adsorption mechanism. The preconcentration of RE ions and regeneration of EDTA-β-CD were successful. Overall, EDTA-β-CD is an effective adsorbent in adsorption and preconcentration of REEs.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.