The objective with this thesis is to build a Black-Box model of the tank pressurization system in JAS 39 Gripen. This model is intended to be used in an existing diagnosis system for the security control in the tank pressurization system. The tank pressurization system is a MIMO system. This makes the identification process more complicated when the best model is to be chosen. In this master's thesis the identification procedure for a MIMO system can be followed. Testing of the diagnosis system with the created Black-Box model shows that the model seems to be good enough. The diagnosis system takes the right decisions in the performed simulations. This shows that system identification might be a good alternative to physical modelling for a real-time model. The disadvantage with the Black-Box model is that it is less accurate in steady-state than the physical model used before is. The advantage is that it is faster than the physical model. The diagnosis system and the model developed in this thesis are not directly applicable on the real system today. The model has to be redesigned on the real system, this is also the case for the diagnosis system. The diagnosis system also has to be redesigned, so general flight cases, not only the security control can be supervised. However, experiences and choices like input and output signals, and choice of sample interval can be reused from this thesis when a new model might be developed.

<p>The objective with this thesis is to build a Black-Box model of the tank pressurization system in JAS 39 Gripen. This model is intended to be used in an existing diagnosis system for the security control in the tank pressurization system. The tank pressurization system is a MIMO system. This makes the identification process more complicated when the best model is to be chosen. In this master's thesis the identification procedure for a MIMO system can be followed. Testing of the diagnosis system with the created Black-Box model shows that the model seems to be good enough. The diagnosis system takes the right decisions in the performed simulations. This shows that system identification might be a good alternative to physical modelling for a real-time model. The disadvantage with the Black-Box model is that it is less accurate in steady-state than the physical model used before is. The advantage is that it is faster than the physical model. The diagnosis system and the model developed in this thesis are not directly applicable on the real system today. The model has to be redesigned on the real system, this is also the case for the diagnosis system. The diagnosis system also has to be redesigned, so general flight cases, not only the security control can be supervised. However, experiences and choices like input and output signals, and choice of sample interval can be reused from this thesis when a new model might be developed.</p>

A megacity is generally defined as a city that, together with its suburbs or recognised metropolitan area, has a total population of more than 10 million people. Air pollution in megacities is a major concern due to large increases of populations over the past decades. Increases of air pollution result from more anthropogenic emission sources in megacities, which include energy production, transportation, industrial activities and domestic fuel burning. In the developing parts of Africa, urbanisation is increasing rapidly, with growth rates of populations in cities of up to 5% per annum. The major driving forces for these population increases in African countries can be attributed to population growth, natural disasters and armed ethnic conflicts. In South Africa, 62% of the total population lived in cities in 2010. The rate of urbanisation growth is predicted to be 1.2% per annum. The largest urbanised city in South Africa is the Johannesburg-Pretoria conurbation (referred to as Jhb-Pta megacity) that has more than 10 million inhabitants. Johannesburg is considered to be the central hub of economic activities and -growth in South Africa. The larger conurbation includes all the suburbs of Johannesburg and Pretoria. In South Africa, household combustion and traffic emissions are major sources of pollutants in urbanised areas. The major pollutants emitted from these activities include nitrogen oxide (NO), nitrogen dioxide (NO 2 ), sulphur dioxide (SO2 ), carbon monoxide (CO), particular matter (PM) and various organic compounds. The Jhb-Pta megacity is also located relatively close to large industrialised regions in South Africa, i.e. the Mpumalanga Highveld and the Vaal Triangle. Very few air quality modelling studies have been conducted for the Jhb-Pta megacity. According to the knowledge of the author, no literature existed in peer-reviewed publications at the time of the study. An in-depth modelling study was therefore conducted to assess the current state of air quality within the Jhb-Pta megacity. The main objectives were to optimise an existing photochemical box model for the Jhb-Pta megacity and to utilise the model to investigate the photochemical processes in the Jhb-Pta megacity and surrounding areas. In this investigation, ground-based measurements of criteria atmospheric pollutant species representative of the Jhb- Pta megacity were obtained to utilise as input data in the model, as well as to compare to results determined with the model. From the ground-based measurements, the possible contribution of the Jhb-Pta megacity to the NO2 hotspot observed over the South African Highveld from satellite retrievals was also contextualised. Five ground-based monitoring sites were situated strategically within the boundaries of the Jhb- Pta megacity to measure the direct influences of urban air pollution, e.g. traffic emissions, biomass burning and residential pollution. One measurement site was situated outside the modelling domain in order to collect rural background data in close proximity to the Jhb-Pta megacity. All the air quality stations continuously measured the criteria pollutants NOx, SO2 and O3. In addition, benzene, toluene, ethylbenzene and xylene (BTEX) were measured at four sites. Passive sampling of NOx, SO2 , O3 and BTEX was also conducted in March and April 2010. Active data was obtained for March to May 2009, since no active measurements were available for the same year that passive sampling was performed due to logistical reasons. Meteorological parameters that included temperature, pressure and relative humidity were also measured at the monitoring stations Ground-based measurements provided a good indication of the state of the air quality in the Jhb-Pta megacity. The air quality levels of NO2 , SO2 , O3 and BTEX could be compared to other cities in the world. A distinct diurnal cycle was observed for NO2 at most of the stations. An early morning peak between 6:00 and 9:00 coincided with the time that commuters travel to work, whereas an evening peak between 18:00 and 21:00 could be attributed to traffic emissions and household combustion. Levels of O3, which is a secondary pollutant, peaked between 13:00 and 15:00. This diurnal pattern could be attributed to the photochemical formation of O3 from precursor species NO and VOCs. Toluene was predominantly higher than the other BTEX species. Benzene and xylene concentrations were in the same order, while the lowest levels were measured for ethyl benzene Ground-based measurements also indicated that the NO2 Highveld hotspot, which is well known in the international science community due to its prominence in satellite images, is accompanied by a second hotspot over the Jhb-Pta megacity. Peak NO2 pollution levels in the Jhb-Pta megacity exceeded the maximum daily Highveld values during the morning and evening rush hours. This result is significant for the more than 10 million people living in the Jhb-Pta megacity. Although satellite instruments have been extremely valuable in pointing out global hotspots, a limitation of satellite retrievals due to their specific overpass times has been presented. Chemical processes in the Jhb-Pta megacity were investigated by utilising an existing photochemical box model, i.e. MECCA-MCM. This model was further developed in this study and was termed the MECCA-MCM-UPWIND model. This model included horizontal and vertical mixing processes in the atmosphere. These processes were included to simulate the advection of upwind air masses into the modelling domain, as well as the entrainment from the troposphere resulting from the diurnal mixing layer (ML) height variation. Three processes, i.e. horizontal mixing, vertical mixing and ML height variation, were built into the MECCA-MCM- UPWIND model. The model was tested and evaluated to determine the efficiency of the model to represent atmospheric mixing processes. MECCA-MCM-UPWIND simulated horizontal mixing, vertical entrainment and ML height variations as expected. The input data for the model runs for the Jhb-Pta megacity modelling runs were either obtained from ground-based measurements or literature. Input data included meteorology, emission inventory, ML height and mixing ratios of the atmospheric chemical species. The chemical composition of the air mass entering the Jhb-Pta megacity was determined with MECCA-MCM- UPWIND. The concentrations and diurnal variability of criteria pollutant species were well predicted with the MECCA-MCM-UPWIND model. The day-time chemistry, especially, compared well, while slight under-predictions were observed for the night-time chemistry for most of the species. The differences observed between modelled and measured data could partially be ascribed to uncertainties associated with some of the input data obtained from literature used. The MECCA-MCM-UPWIND model was used to perform sensitivity studies on the influence of different parameters on O3 levels in the Jhb-Pta megacity. Possible scenarios to alter or mitigate pollution were also investigated. The results from the sensitivity analyses showed that O3 mixing ratios decreased within the Jhb-Pta megacity with increasing wind speeds. The contribution of local emissions to the change in the concentration of pollutants is reduced at higher wind speeds. It also indicated that the Mpumalanga Highveld can potentially be a source of NOx in the Jhb-Pta megacity that can lead to the titration of O3 . This also implies that if the air quality of the surrounding area improves, the concentration of the secondary pollutant O 3 will increase in the Jhb-Pta megacity due to the decrease in the titration of O3 . Sensitivity analyses also indicated that the Jhb-Pta megacity is a VOC-limited (or NOx-saturated) regime. Therefore, O3 reduction in the Jhb-Pta megacity will mostly be effective if VOC emissions are reduced. The same effect was observed in various cities world-wide where O3 increased when NOx emissions the Jhb-Pta megacity on the instantaneous production of O 3 was also investigated. A significant increase of approximately 23ppb O3 production was observed when changing from Euro-0 to Euro-3 vehicles with lower emissions of VOCs, NOx and CO. This compares with other modelled sensitivity studies of traffic emissions that also predict that future urban O 3 concentrations will increase in many cities by 2050 due to the reduction in the NOx titration of O3 despite the implementation of O3 control regulations / Thesis (PhD (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013

A megacity is generally defined as a city that, together with its suburbs or recognised metropolitan area, has a total population of more than 10 million people. Air pollution in megacities is a major concern due to large increases of populations over the past decades. Increases of air pollution result from more anthropogenic emission sources in megacities, which include energy production, transportation, industrial activities and domestic fuel burning. In the developing parts of Africa, urbanisation is increasing rapidly, with growth rates of populations in cities of up to 5% per annum. The major driving forces for these population increases in African countries can be attributed to population growth, natural disasters and armed ethnic conflicts. In South Africa, 62% of the total population lived in cities in 2010. The rate of urbanisation growth is predicted to be 1.2% per annum. The largest urbanised city in South Africa is the Johannesburg-Pretoria conurbation (referred to as Jhb-Pta megacity) that has more than 10 million inhabitants. Johannesburg is considered to be the central hub of economic activities and -growth in South Africa. The larger conurbation includes all the suburbs of Johannesburg and Pretoria. In South Africa, household combustion and traffic emissions are major sources of pollutants in urbanised areas. The major pollutants emitted from these activities include nitrogen oxide (NO), nitrogen dioxide (NO 2 ), sulphur dioxide (SO2 ), carbon monoxide (CO), particular matter (PM) and various organic compounds. The Jhb-Pta megacity is also located relatively close to large industrialised regions in South Africa, i.e. the Mpumalanga Highveld and the Vaal Triangle. Very few air quality modelling studies have been conducted for the Jhb-Pta megacity. According to the knowledge of the author, no literature existed in peer-reviewed publications at the time of the study. An in-depth modelling study was therefore conducted to assess the current state of air quality within the Jhb-Pta megacity. The main objectives were to optimise an existing photochemical box model for the Jhb-Pta megacity and to utilise the model to investigate the photochemical processes in the Jhb-Pta megacity and surrounding areas. In this investigation, ground-based measurements of criteria atmospheric pollutant species representative of the Jhb- Pta megacity were obtained to utilise as input data in the model, as well as to compare to results determined with the model. From the ground-based measurements, the possible contribution of the Jhb-Pta megacity to the NO2 hotspot observed over the South African Highveld from satellite retrievals was also contextualised. Five ground-based monitoring sites were situated strategically within the boundaries of the Jhb- Pta megacity to measure the direct influences of urban air pollution, e.g. traffic emissions, biomass burning and residential pollution. One measurement site was situated outside the modelling domain in order to collect rural background data in close proximity to the Jhb-Pta megacity. All the air quality stations continuously measured the criteria pollutants NOx, SO2 and O3. In addition, benzene, toluene, ethylbenzene and xylene (BTEX) were measured at four sites. Passive sampling of NOx, SO2 , O3 and BTEX was also conducted in March and April 2010. Active data was obtained for March to May 2009, since no active measurements were available for the same year that passive sampling was performed due to logistical reasons. Meteorological parameters that included temperature, pressure and relative humidity were also measured at the monitoring stations Ground-based measurements provided a good indication of the state of the air quality in the Jhb-Pta megacity. The air quality levels of NO2 , SO2 , O3 and BTEX could be compared to other cities in the world. A distinct diurnal cycle was observed for NO2 at most of the stations. An early morning peak between 6:00 and 9:00 coincided with the time that commuters travel to work, whereas an evening peak between 18:00 and 21:00 could be attributed to traffic emissions and household combustion. Levels of O3, which is a secondary pollutant, peaked between 13:00 and 15:00. This diurnal pattern could be attributed to the photochemical formation of O3 from precursor species NO and VOCs. Toluene was predominantly higher than the other BTEX species. Benzene and xylene concentrations were in the same order, while the lowest levels were measured for ethyl benzene Ground-based measurements also indicated that the NO2 Highveld hotspot, which is well known in the international science community due to its prominence in satellite images, is accompanied by a second hotspot over the Jhb-Pta megacity. Peak NO2 pollution levels in the Jhb-Pta megacity exceeded the maximum daily Highveld values during the morning and evening rush hours. This result is significant for the more than 10 million people living in the Jhb-Pta megacity. Although satellite instruments have been extremely valuable in pointing out global hotspots, a limitation of satellite retrievals due to their specific overpass times has been presented. Chemical processes in the Jhb-Pta megacity were investigated by utilising an existing photochemical box model, i.e. MECCA-MCM. This model was further developed in this study and was termed the MECCA-MCM-UPWIND model. This model included horizontal and vertical mixing processes in the atmosphere. These processes were included to simulate the advection of upwind air masses into the modelling domain, as well as the entrainment from the troposphere resulting from the diurnal mixing layer (ML) height variation. Three processes, i.e. horizontal mixing, vertical mixing and ML height variation, were built into the MECCA-MCM- UPWIND model. The model was tested and evaluated to determine the efficiency of the model to represent atmospheric mixing processes. MECCA-MCM-UPWIND simulated horizontal mixing, vertical entrainment and ML height variations as expected. The input data for the model runs for the Jhb-Pta megacity modelling runs were either obtained from ground-based measurements or literature. Input data included meteorology, emission inventory, ML height and mixing ratios of the atmospheric chemical species. The chemical composition of the air mass entering the Jhb-Pta megacity was determined with MECCA-MCM- UPWIND. The concentrations and diurnal variability of criteria pollutant species were well predicted with the MECCA-MCM-UPWIND model. The day-time chemistry, especially, compared well, while slight under-predictions were observed for the night-time chemistry for most of the species. The differences observed between modelled and measured data could partially be ascribed to uncertainties associated with some of the input data obtained from literature used. The MECCA-MCM-UPWIND model was used to perform sensitivity studies on the influence of different parameters on O3 levels in the Jhb-Pta megacity. Possible scenarios to alter or mitigate pollution were also investigated. The results from the sensitivity analyses showed that O3 mixing ratios decreased within the Jhb-Pta megacity with increasing wind speeds. The contribution of local emissions to the change in the concentration of pollutants is reduced at higher wind speeds. It also indicated that the Mpumalanga Highveld can potentially be a source of NOx in the Jhb-Pta megacity that can lead to the titration of O3 . This also implies that if the air quality of the surrounding area improves, the concentration of the secondary pollutant O 3 will increase in the Jhb-Pta megacity due to the decrease in the titration of O3 . Sensitivity analyses also indicated that the Jhb-Pta megacity is a VOC-limited (or NOx-saturated) regime. Therefore, O3 reduction in the Jhb-Pta megacity will mostly be effective if VOC emissions are reduced. The same effect was observed in various cities world-wide where O3 increased when NOx emissions the Jhb-Pta megacity on the instantaneous production of O 3 was also investigated. A significant increase of approximately 23ppb O3 production was observed when changing from Euro-0 to Euro-3 vehicles with lower emissions of VOCs, NOx and CO. This compares with other modelled sensitivity studies of traffic emissions that also predict that future urban O 3 concentrations will increase in many cities by 2050 due to the reduction in the NOx titration of O3 despite the implementation of O3 control regulations / Thesis (PhD (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013

Over the past three decades, interest in the topic of Business Incubation and more specifically University Business Incubation, has increased, due to its potential to encourage entrepreneurial activities, which initiate innovation and economic development. The literature on entrepreneurship devotes significant attention to BI as a tool for supporting entrepreneurs in overcoming difficulties associated with starting a business. Meanwhile, the fact that incubators themselves are vulnerable to different challenges needs to be sufficiently highlighted in the research currently in publication. By adopting an incubator’s perspective on developing entrepreneurs and, therefore, its dynamics that form new ventures, this qualitative study has focused on difficulties adjacent to the administration of the incubator. By building on the Black Box model of incubation, the Triad model, as well as Institutionalized entrepreneurship, the researchers have contributed to the phenomena of UBIs, and the many challenges they encounter when incubating business tenants. The thesis has successfully confirmed the inherent value of ensuring the financial viability of publicly financed incubators while shedding light on the challenges involved in achieving self-sufficiency. This examination has delved into the acquisition of government funds by incubators and explored the opportunities and constraints accompanying such support. Building on existing literature, which identifies sustainability and growth as key indicators, this study has provided empirical evidence and analysis that underscores the detrimental impact on the incubator's core mission when these criteria are not maintained.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24040号 / 情博第796号 / 新制||情||135(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 加納 学, 教授 大塚 敏之, 教授 下平 英寿 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

Buildings are currently controlled in a sub optimal way, using a WC controller that is dependent only on the external temperature. A rich amount of real-time data from installed sensors is available within the buildings and the network and can be used to counteract this. To better control the indoor temperature and the heat supply this degree-project develops a model and optimizer for control of the indoor temperature, where industry standard data streams are used as inputs. The model and optimizer can be implemented in a MPC which takes the future external temperature into consideration and enhances the ability to control the heat supply. There are two main reasons why enhanced control is interesting to look at, the economic aspects and the comfort of the occupancies. This degree project is focused on developing a general building model for the purpose of utilizing the building as an energy storage for peak-shaving.  The finalized model is a dynamic grey-box model developed using data from a multifamily building, Building A, located in Västerås Sweden. The training period is set to 408 hours, and the prediction horizon is set to 48 hours as a result of the verification. To demonstrate the utilization possibilities of using the building as a heat storage, an optimizer is constructed to evaluate a peak shaving control strategy. The control objective (Qsupply) is controlled by manipulating the indoor temperature (Tin) within a set interval. By setting a fixed interval for the indoor temperature within the comfort interval, the comfort is still maintained. For the peak shaving different flexibilities within the indoor temperature have been examined with a range from 22 +/- 0.25 degrees Celcius to 22 +/- 2.00 degrees Celcius.  The model is verified in 4 steps: prediction ability on the historic data, parametric verification on the time constant, simulation of heat supply separately from the historic data and model generality by implementing the model on a second multifamily building, Building B. The model has a RRMSE of 8% for Building A and 9% for Building B which is considered excellent.  Due to the lack of access to the real building, the developed model is not validated. Based on peak shaving and energy consumption, the preferred solution is 22+/- 1.25 degrees Celcius. But based on surveys about occupancies attitude toward flexibility in the indoor temperature and economical aspects, an indoor temperature of 22 +/- 0.50 degrees Celcius is considered the best choice with the maximum peak in the heat supplied decreased by 35% and the energy consumption is decreased by 10% compared to the historical case. We suggest allowing the customers to choose their preferred flexibility to ensure comfort.

The complexity that digital transformation brings to the business environment requires new knowledge and expertise in different domains. To avoid the extensive costs of acquiring and managing this knowledge internally, organizations frequently collaborate with external consultancies. In this exploratory case study, we investigate what role the consultancy agencies take within client organizations' transformation journey and how this role is affected by the dynamic nature of digital transformation. The study reveals that the notion of digital transformation in the business environment is fuzzy and challenging not only to the client organization but to the consultancy agency itself which leads to the necessity to narrow down the notion of digital transformation and form a new role.

Transients encountered by transformers in power stations during normal operation can have complex oscillatory overvoltages containing a large spectrum of frequency components. These transients can coincide with the natural frequencies of the transformers windings, leading to voltages that can be greater or more severe than the current factory proof tests. This may lead to insulation breakdown and catastrophic failures. Existing lumped parameter RLCG transformer models have been proven to be less accurate for very fast transient overvoltages (VFTO) with frequencies over 1 MHz. A white box model for transient analysis of transformer windings has been developed using Multiconductor Transmission Line (MTL) Theory. This model enables the simulation of natural frequencies of the transformer windings up to frequencies of several MHz, and can be used to compute voltages between turns by representing each turn as a separate transmission line. Both continuous and interleaved disk windings have been modelled and a comparison and validation of the results is presented. / May 2017

If sufficiently persistent, semi-volatile organic contaminants (SVOCs) can travel long distances through the atmosphere from their points of release and become concentrated in cold, remote regions. As air is sampled for SVOCs to establish both their presence and the success of emission reduction efforts, it becomes helpful to determine sampling site proximity to sources and the origin of the sampled air masses. Comparing three increasingly sophisticated methods for quantifying source proximity of sampling locations, it was judged necessary to account for the actual history of the sampled air through construction of an airshed, especially if wind is highly directional and population distribution is very non-uniform. The airshed concept was improved upon by introducing a ‘geodesic’ grid of equally spaced cells, rather than a simple latitude/longitude grid, to avoid distortion near Earth’s poles and to allow for the comparison of airshed shapes. Assuming that a perfectly round airshed reveals no information about sources allows the significance of each cell of an airshed to be judged based on its departure from roundness. Combining air-mass histories with a 2 year-long series of SVOC air concentrations at Little Fox Lake in Canada’s Yukon Territory did not identify distinct source regions for most analytes, although γ-hexachlorocyclohexane appears to originate broadly in north-eastern Russia and/or Alaska. Based on this remoteness from sources, the site is judged to be well suited to monitor changes in the hemispheric background concentrations of SVOCs. A model-based exploration revealed wet-gaseous deposition as the dominant process responsible for cold-trapping SVOCs in mountain soils. Such cold trapping is particularly effective if precipitation rate increases with altitude and if temperature differences along the mountain are large. Considerable sensitivity of the modeled extent of cold-trapping to parameters as diverse as scale, mean temperature, atmospheric particle concentration and time relative to emission maxima is consistent with the wide variety of observed enrichment behaviour. Concentration gradients of polycyclic aromatic hydrocarbons and polychlorinated biphenyls in air and soil measured on four Western Canadian mountains with variable distance from sources revealed source proximity as the main driver of concentrations at both the whole-mountain scale and along individual mountain transects.