Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Institutional trust - development of the construct and the scale

Organisatorisen luottamuksen tutkimuksessa luottamus nähdään yleensä henkilöiden välisenä ilmiönä kuten työntekijän luottamuksena työtovereihin, esimieheen tai lähimpään johtoon. Organisatorisessa luottamuksessa on kuitenkin myös ei-henkilöityvä ulottuvuus, ns. institutionaalinen luottamus. Tähän mennessä vain muutamat tutkijat ovat omissa tutkimuksissaan käyttäneet myös institutionaalista luottamusta osana organisatorista luottamusta. Tämän työn tavoitteena on kehittää institutionaalisen luottamuksen käsitettä sekä mittari sen havainnoimiseksi organisaatioympäristössä. Kehitysprosessi koostui kolmesta vaiheesta. Ensimmäisessä vaiheessa kehitettiin mittariin tulevia väittämiä sekä arvioitiin sisällön validiteetti. Toinen vaihe käsitti aineiston keruun, väittämien karsimisen sekä vaihtoehtoisten mallien vertailun. Kolmannessa vaiheessa arvioitiin rakennevaliditeetti sekä reliabiliteetti. Työn empiirinen osatoteutettiin internet-kyselynä aikuisopiskelijoiden keskuudessa. Aineiston analysoinnissa käytettiin pääkomponenttianalyysiä sekä konfirmatorista faktorianalyysiä. Institutionaalinen luottamus muodostuu kahdesta ulottuvuudesta: kyvykkyys ja oikeudenmukaisuus. Kyvykkyys muodostuu viidestä alakomponentista: operatiivisen toiminnan organisointi, organisaation pysyvyys, kyvykkyys liiketoiminnan ja ihmisten johtamisessa, teknologinen luotettavuus sekä kilpailukyky. Oikeudenmukaisuus puolestaan muodostuu HRM-käytännöistä, organisaatiossa vallitsevasta reilun pelin hengestä sekä kommunikaatiosta. Lopullinen mittari kyvykkyydelle käsittää 18 väittämää ja oikeudenmukaisuudelle 13 väittämää. Työssä kehitetty mittari mahdollistaa organisatorisen luottamuksen entistä paremman ja luotettavamman mittaamisen. Tutkijan tietämyksen mukaan tämä onensimmäinen kokonaisvaltainen mittari institutionaalisen luottamuksen mittaamiseksi.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Challenges in managing large-scale agile software development transformation

Adapting and scaling up agile concepts, which are characterized by iterative, self-directed, customer value focused methods, may not be a simple endeavor. This thesis concentrates on studying challenges in a large-scale agile software development transformation in order to enhance understanding and bring insight into the underlying factors for such emerging challenges. This topic is approached through understanding the concepts of agility and different methods compared to traditional plan-driven processes, complex adaptive theory and the impact of organizational culture on agile transformational efforts. The empirical part was conducted by a qualitative case study approach. The internationally operating software development case organization had a year of experience of an agile transformation effort during it had also undergone organizational realignment efforts. The primary data collection was conducted through semi-structured interviews supported by participatory observation. As a result the identified challenges were categorized under four broad themes: organizational, management, team dynamics and process related. The identified challenges indicate that agility is a multifaceted concept. Agile practices may bring visibility in issues of which many are embedded in the organizational culture or in the management style. Viewing software development as a complex adaptive system could facilitate understanding of the underpinning philosophy and eventually solving the issues: interactions are more important than processes and solving a complex problem, such a novel software development, requires constant feedback and adaptation to changing requirements. Furthermore, an agile implementation seems to be unique in nature, and agents engaged in the interaction are the pivotal part of the success of achieving agility. In case agility is not a strategic choice for whole organization, it seems additional issues may arise due to different ways of working in different parts of an organization. Lastly, detailed suggestions to mitigate the challenges of the case organization are provided.

Working fluid selection and design of small-scale waste heat recovery systems based on organic Rankine cycles

Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.

Assessment of techno-economic use cases for small-scale island grids

The main objective of the study was to define the methodology for assessing the limits for application island grids instead of interconnecting with existing grid infrastructure. The model for simulation of grid extension distance and levelised cost of electricity has been developed and validated by the case study in Finland. Thereafter, sensitivities of the application limits were examined with the respect to operational environment, load conditions, supply security and geographical location. Finally, recommendations for the small-scale rural electrification projects in the market economy environment have been proposed.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.