Replacing Copper with New Carbon Nanomaterials in Electrical Machine Windings

Electrical machines have significant improvement potential. Nevertheless, the field is characterized by incremental innovations. Admittedly, steady improvement has been achieved, but no breakthrough development. Radical development in the field would require the introduction of new elements, such that may change the whole electrical machine industry system. Recent technological advancements in nanomaterials have opened up new horizons for the macroscopic application of carbon nanotube (CNT) fibres. With values of 100 MS/m measured on individual CNTs, CNT fibre materials hold promise for conductivities far beyond those of metals. Highly conductive, lightweight and strong CNT yarn is finally within reach; it could replace copper as a potentially better winding material. Although not yet providing low resistivity, the newest CNT yarn offers attractive perspectives for accelerated efficiency improvement of electrical machines. In this article, the potential for using new CNT materials to replace copper in machine windings is introduced. It does so, firstly, by describing the environment for a change that could revolutionize the industry and, secondly, by presenting the breakthrough results of a prototype construction. In the test motor, which is to our knowledge the first in its kind, the presently most electrically conductive carbon nanotube yarn replaces usual copper in the windings.

Design and Drive-Cycle Based Analysis of Direct-Driven Permanent Magnet Synchronous Machine for a Small Urban Use Electric Vehicle

A direct-driven permanent magnet synchronous machine for a small urban use electric vehicle is presented. The measured performance of the machine at the test bench as well as the performance over the modified New European Drive Cycle will be given. The effect of optimal current components, maximizing the efficiency and taking into account the iron loss, is compared with the simple id=0 – control. The machine currents and losses during the drive cycle are calculated and compared with each other.

Forest inventory information needs in Northwest Russia

This thesis applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The thesis recommends strategic options for LiDAR technology’s value enhancement in Russian forestry.

Quality assurance of refuse derived fuel with machine vision

This thesis studies the use of machine vision in RDF quality assurance and manufacturing. Currently machine vision is used in recycling and material detection and some commer- cial products are available in the market. In this thesis an on-line machine vision system is proposed for characterizing particle size. The proposed machine vision system is based on the mapping between image segmenta- tion and the ground truth of the particle size. The results shows that the implementation of such machine vision system is feasible.

Forest inventory information needs in Northwest Russia

This research report applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The report recommends strategic options for LiDAR technology’s value enhancement in Russian forestry. This work has been conducted as a part of the project ‘Finnish-Russian Forest Academy 2 - Exploiting and Piloting’, which has been supported financially by the South-East Finland- Russia ENPI CBC 2007-2014 Programme.

Feasibility of industrial implementation of laser cutting into paper making machine

Laser cutting implementation possibilities into paper making machine was studied as the main objective of the work. Laser cutting technology application was considered as a replacement tool for conventional cutting methods used in paper making machines for longitudinal cutting such as edge trimming at different paper making process and tambour roll slitting. Laser cutting of paper was tested in 70’s for the first time. Since then, laser cutting and processing has been applied for paper materials with different level of success in industry. Laser cutting can be employed for longitudinal cutting of paper web in machine direction. The most common conventional cutting methods include water jet cutting and rotating slitting blades applied in paper making machines. Cutting with CO2 laser fulfils basic requirements for cutting quality, applicability to material and cutting speeds in all locations where longitudinal cutting is needed. Literature review provided description of advantages, disadvantages and challenges of laser technology when it was applied for cutting of paper material with particular attention to cutting of moving paper web. Based on studied laser cutting capabilities and problem definition of conventional cutting technologies, preliminary selection of the most promising application area was carried out. Laser cutting (trimming) of paper web edges in wet end was estimated to be the most promising area where it can be implemented. This assumption was made on the basis of rate of web breaks occurrence. It was found that up to 64 % of total number of web breaks occurred in wet end, particularly in location of so called open draws where paper web was transferred unsupported by wire or felt. Distribution of web breaks in machine cross direction revealed that defects of paper web edge was the main reason of tearing initiation and consequent web break. The assumption was made that laser cutting was capable of improvement of laser cut edge tensile strength due to high cutting quality and sealing effect of the edge after laser cutting. Studies of laser ablation of cellulose supported this claim. Linear energy needed for cutting was calculated with regard to paper web properties in intended laser cutting location. Calculated linear cutting energy was verified with series of laser cutting. Practically obtained laser energy needed for cutting deviated from calculated values. This could be explained by difference in heat transfer via radiation in laser cutting and different absorption characteristics of dry and moist paper material. Laser cut samples (both dry and moist (dry matter content about 25-40%)) were tested for strength properties. It was shown that tensile strength and strain break of laser cut samples are similar to corresponding values of non-laser cut samples. Chosen method, however, did not address tensile strength of laser cut edge in particular. Thus, the assumption of improving strength properties with laser cutting was not fully proved. Laser cutting effect on possible pollution of mill broke (recycling of trimmed edge) was carried out. Laser cut samples (both dry and moist) were tested on the content of dirt particles. The tests revealed that accumulation of dust particles on the surface of moist samples can take place. This has to be taken into account to prevent contamination of pulp suspension when trim waste is recycled. Material loss due to evaporation during laser cutting and amount of solid residues after cutting were evaluated. Edge trimming with laser would result in 0.25 kg/h of solid residues and 2.5 kg/h of lost material due to evaporation. Schemes of laser cutting implementation and needed laser equipment were discussed. Generally, laser cutting system would require two laser sources (one laser source for each cutting zone), set of beam transfer and focusing optics and cutting heads. In order to increase reliability of system, it was suggested that each laser source would have double capacity. That would allow to perform cutting employing one laser source working at full capacity for both cutting zones. Laser technology is in required level at the moment and do not require additional development. Moreover, capacity of speed increase is high due to availability high power laser sources what can support the tendency of speed increase of paper making machines. Laser cutting system would require special roll to maintain cutting. The scheme of such roll was proposed as well as roll integration into paper making machine. Laser cutting can be done in location of central roll in press section, before so-called open draw where many web breaks occur, where it has potential to improve runability of a paper making machine. Economic performance of laser cutting was done as comparison of laser cutting system and water jet cutting working in the same conditions. It was revealed that laser cutting would still be about two times more expensive compared to water jet cutting. This is mainly due to high investment cost of laser equipment and poor energy efficiency of CO2 lasers. Another factor is that laser cutting causes material loss due to evaporation whereas water jet cutting almost does not cause material loss. Despite difficulties of laser cutting implementation in paper making machine, its implementation can be beneficial. The crucial role in that is possibility to improve cut edge strength properties and consequently reduce number of web breaks. Capacity of laser cutting to maintain cutting speeds which exceed current speeds of paper making machines what is another argument to consider laser cutting technology in design of new high speed paper making machines.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.

Suitability of LiDAR technology for forest inventory in Russia

LiDAR is an advanced remote sensing technology with many applications, including forest inventory. The most common type is ALS (airborne laser scanning). The method is successfully utilized in many developed markets, where it is replacing traditional forest inventory methods. However, it is innovative for Russian market, where traditional field inventory dominates. ArboLiDAR is a forest inventory solution that engages LiDAR, color infrared imagery, GPS ground control plots and field sample plots, developed by Arbonaut Ltd. This study is an industrial market research for LiDAR technology in Russia focused on customer needs. Russian forestry market is very attractive, because of large growing stock volumes. It underwent drastic changes in 2006, but it is still in transitional stage. There are several types of forest inventory, both with public and private funding. Private forestry enterprises basically need forest inventory in two cases – while making coupe demarcation before timber harvesting and as a part of forest management planning, that is supposed to be done every ten years on the whole leased territory. The study covered 14 companies in total that include private forestry companies with timber harvesting activities, private forest inventory providers, state subordinate companies and forestry software developer. The research strategy is multiple case studies with semi-structured interviews as the main data collection technique. The study focuses on North-West Russia, as it is the most developed Russian region in forestry. The research applies the Voice of the Customer (VOC) concept to elicit customer needs of Russian forestry actors and discovers how these needs are met. It studies forest inventory methods currently applied in Russia and proposes the model of method comparison, based on Multi-criteria decision making (MCDM) approach, mainly on Analytical Hierarchy Process (AHP). Required product attributes are classified in accordance with Kano model. The answer about suitability of LiDAR technology is ambiguous, since many details should be taken into account.

Study of the physical and physicochemical characteristics of fruits of the licuri palm (Syagrus coronata (Mart.) Becc.) found in the Atlantic Forest of Minas Gerais, Brazil

AbstractThe Atlantic Forest has species of native fruits, consumed fresh and processed, which have an important contribution to food sovereignty of families that consume it. This study examined the physical and physicochemical characteristics, proximate composition, concentration of carotenoids, vitamin C, vitamin E and minerals in the pulp and kernels of fruits of licuri (Syagrus coronata (Mart.) Becc.). Titratable acidity was analyzed by volumetric neutralization, soluble solids by refractometry, proteins by the micro-Kjeldahl method, lipids by gravimetry using soxhlet, dietary fiber by non-enzymatic gravimetry, carotenoids and vitamin C by HPLC-DAD, vitamin E by HPLC-fluorescence, and minerals by ICP-AES. Pulp were a source of Zn (0.95 mg 100–1), a good source of fiber (6.15 g 100–1), excellent source of provitamin A (758.75 RAE 100–1), Cu (0.69 mg 100–1), Fe (3.81 mg 100–1), Mn (3.40 mg 100–1) and Mo (0.06 mg 100–1). The kernel were a source of Fe (3.36 mg 100–1) and excellent source of Mn (6.14 mg 100–1), Cu (0.97 mg 100–1) and Mo (0.07 mg 100–1). The nutritional value and wide availability of licuri fruit make it an important resource for reducing food insecurity and improving nutrition of the rural population and other individuals who have access to it.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Trophic cascades in boreal landscapes: top predator protection on tree seedlings and forest grouse

Changes in the abundance of top predators have brought about notable, cascading effects in ecosystems around the world. In this thesis, I examined several potential trophic cascades in boreal ecosystems, and their separate interspecific interactions. The main aim of the thesis was to investigate whether predators in the boreal forests have direct or indirect cascading effects on the lower trophic levels. First, I compared the browsing effects of different mammalian herbivores by excluding varying combinations of voles, hares and cervids from accessing the seedlings of silver birch (Betula pendula), Scots pine (Pinus sylvestris) and Norway spruce (Picea abies). Additionally, I studied the effect of simulated predation risk on vole browsing by using auditory cues of owls. Moving upwards on the trophic levels, I examined the intraguild interactions between the golden eagle (Aquila chrysaetos), and its mesopredator prey, the red fox (Vulpes vulpes) and the pine marten (Martes martes). To look at an entire potential trophic cascade, I further studied the combined impacts of eagles and mesopredators on the black grouse (Tetrao tetrix) and the hazel grouse (Tetrastes bonasia), predicting that the shared forest grouse prey would benefit from eagle presence. From the tree species studied, birch appears to be the most palatable one for the mammalian herbivores. I observed growth reductions in the presences of cervids and low survival associated with hares and voles, which suggests that they all weaken regeneration in birch stands. Furthermore, the simulated owl predation risk appeared to reduce vole browsing on birches in late summer, although the preferred grass forage is then old and less palatable. Browsing by voles and hares had a negative effect on the condition and survival of Scots pine, but in contrast, the impact of mammalian herbivores on spruce was found to be small, at least when more preferred food is available. I observed that the presence of golden eagles had a negative effect on the abundance of adult black grouse but a positive, protective effect on the proportion of juveniles in both black grouse and hazel grouse. Yet, this positive effect was not dependent on the abundance foxes or martens, nor did eagles seem to effectively decrease the abundance of these mesopredators. Conversely, the protection effect on grouse could arise from fear effects and also be mediated by other mesopredators. The results of this thesis provide important new information about trophic interactions in the boreal food webs. They highlight how different groups of mammalian herbivores vary in their effects on the growth and condition of different tree seedlings. Lowered cervid abundances could improve birch regeneration, which indirectly supports the idea that the key predators of cervids could cause cascading effects also in Fennoscandian forests. Owls seem to reduce vole browsing through an intimidation effect, which is a novel result of the cascading effects of owl vocalisation and could even have applications for protecting birch seedlings. In the third cascade examined in this thesis, I found the golden eagle to have a protective effect on the reproducing forest grouse, but it remains unclear through which smaller predators this effect is mediated. Overall, the results of this thesis further support the idea that there are cascading effects in the forests of Northern Europe, and that they are triggered by both direct and non‐lethal effects of predation.