It is of interest to investigate extended usability of Saab’s Deployable Aircraft Maintenance facility(DAM) with respect to Eurocode standards. One of the features of the deployable hangar is that it shouldcomply with the structural strength standards for permanent buildings which requires compliance withEurocodes.Eurocodes are European standards which deals with the development of building and structural design.Compliance with Eurocodes works as a proof of requirement for mechanical strength, stability andsafety of structures. The Eurocodes were created by the European Committee for Standardization withthe intent to simplify technical obstacles and enable trade within Europe and elsewhere.The thesis has resulted in the creation of a Finite Element Model (FE-Model) of the deployable hangar,for which different loading combinations have been applied. From the FE-results, trade-off curves havebeen generated that show the effect that the different loading conditions have on the differentcomponents of the hangar. This is done for the current configuration of the hangar and for differentproduct variants. The analysis includes the effects of increased load levels.From the trade-off curves it is possible to see to what extent the hangar can withstand increased load.This is being measured with a Eurocode ratio. It has been found that the Eurocode ratio is directlydependent on increase of loads i.e. increased loads give a linear increase in Eurocode ratio for most ofthe components studied. The product variants consists of different lengths of the hangar. From the studyit has been found that adding or removing sections does not have a substantial effect on the strength ofthe hangar and the Eurocode ratio mostly remains constant. In addition the most critical componentshave been found and design suggestions have been proposed to improve the strength of the hangarwithin compliance with Eurocodes.

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Data streams being transmitted over a network channel with capacity less than the data rate of the data streams is very common when using network channels such as dial-up, low bandwidth wireless links. Not only does this lower capacity creates delays but also causes sequential network problems such as packet losses, network congestion, errors in data packets giving rise to other problems and creating a cycle of problems hard to break out from. In this thesis, we present a new approach for shedding the less informative attribute data from a data stream with a fixed schema to maintain a data rate lesser than the network channels capacity. A scheme for shedding attributes, instead of tuples, becomes imperative in stream data where the data for one of the attributes remains relatively constant or changes less frequently compared to the data for the other attributes. In such a data stream management system, shedding a complete tuple would lead to shedding of some informative-attribute data along with the less informative-attribute data in the tuple, whereas shedding of the less informative-attribute data would cause only the less informative data to be dropped. In this thesis, we deal with two major problems in load shedding: the intra-stream load shedding and the inter-stream load shedding problems. The intra-stream load shedding problem deals with shedding of the less informative attributes when a single data stream with the data rate greater than the channel capacity has to be transmitted to the destination over the channel. The inter-stream load shedding problem refers to shedding of attributes among different streams when more than one stream has to be transferred to the destination over a channel with the channel capacity less than the combined data rate of all the streams to be transmitted. As a solution to the inter-stream or intra-stream load shedding problem, we apply our load shedding schema approach to determine a ranking amongst the attributes on a singe data stream or multiple data streams with the least informative attribute(s) being ranked the highest. The amount of data to be shed to maintain the data rate below the capacity is calculated dynamically, which means that the amount of data to be shed changes with any change in the channel capacity or any change in the data rate. Using these two pieces of information, a load shedding schema describing the attributes to be shed is generated. The load shedding schema is generated dynamically, which means that the load shedding schema is updated with any change in (i) the rankings of attributes that capture the rate of change on the values of each attribute, (ii) channel capacity, and (iii) data rate even after load shedding has been invoked. The load shedding schema is updated using our load shedding schema re-evaluation algorithm, which adapts to the data stream characteristics and follows the attribute data variation curve of the data stream. Since data dropped at the source may be of interest to the user at the destination, we also propose a recovery module which can be invoked to recover attribute data already shed. The recovery module maintains the minimal amount of information about data already shed for recovery purpose. Preliminary experimental results have shown that recovery accuracy ranges from 90% to 99%, which requires only 5% to 33% and 4.88% to 50% of the dropped data to be stored for weather reports and stock exchanges, respectively. Storing of recovery information imposes storage and processing burden on the source site, and our recovery method aims at satisfactory recovery accuracy while imposing minimal burden on the source site. Our load shedding approach, which achieves a high performance in reducing the data stream load, (i) handles wide range of data streams in different application domains (such as weather, stocks, and network performance, etc.), (ii) is dynamic in nature, which means that the load shedding scheme adjusts the amount of data to be shed and which attribute data to be shed according to the current load and network capacity, and (iii) provides a data recovery mechanism that is capable to recover any shedded attribute data with recovery accuracy up to 90% with very low burden on the source site and 99% with a higher burden on some stream data. To the best of our knowledge, the dynamic load shedding scheme we propose is the first one in the literature to shed attributes, instead of tuples, along with providing a recovery mechanism in a data stream management system. Our load shedding approach is unique since it is not a static load shedding schema, which is less appealing in an ever-changing (sensor) network environment, and is not based on queries, but works on the general characteristics of the data stream under consideration instead.

Friction stir spot welding (FSSW) is quickly becoming a method of interest for welding of high strength steel (HSS) and ultra high strength steel (UHSS). FSSW has been shown to produce high quality welds in these materials, without the drawbacks associated with fusion welding. Tool grade for polycrystalline cubic boron nitride (PCBN) tools has a significant impact on wear resistance, weld quality, and tool failure in FSSW of DP 980 steel sheet. More specifically, for a nominal composition of 90% CBN, the grain size has a significant impact on the wear resistance of the tool. A-type tools performed the best, of the three grades that were tested in this work, because the grain size of this grade was the finest, measuring from 3-6 microns. The effect of fine grain size was less adhesion of DP 980 on the tool surface over time, less abrasive wear, and better lap shear fracture loads of the welds that were produced, compared to the other grades. This is explained by less exposure of the binder phase to wear by both adhesion and abrasion during welding of DP 980. A-type tools were the most consistent in both the number of welds per tool, and the number of welds that reached acceptable lap shear fracture loads. B-type tools, with a bimodal grain size distribution (grain size of 4 – 40 microns) did a little bit better than C-type tools (grain size of 12-15 microns) in terms of wear, but neither of them were able to achieve consistent acceptable lap shear fracture load values after the first 200 welds. In fact only one out of five C-type tools was able to produce acceptable lap shear fracture loads after the first 100 welds.

Introduction: The global demand for renewable energy is expected to grow annually due to rising electricity consumption and economic and regulatory incentives. Efficient consumption and management of electricity consumption can support this trend (shifting from fossil resources to renewable resources) and benefit companies economically by reducing peak loads, reducing subscription costs, and protecting companies' power systems and networks. For effective and efficient electricity management that can help reduce peak electricity demand, resulting in lower demand charges and further reducing operational costs, it is necessary to understand the amount of electricity consumption and its influencing factors. Seasonal and daily variations and social behaviors influence changes in electricity consumption. Electric load variation management is essential for electricity consumers to control costs related to maximum load capacity and building electrical network equipment protection. This research presents an assessment method for describing daily electric load variations. It is applied to electricity consumption systems, but the technique is generic and can be applied to all activities where daily variations occur.Purpose: This thesis aims to show when and why peak load occurs in an office building and also to provide methods to improve the efficiency of electricity consumption during peak load.Method: This method implemented parameters like temperature, electricity consumption, and hours. It assessed a year's hourly electricity consumption in an office building to understand how load changes daily, weekly, and monthly. The case study was the AirSon office building. Data-driven from the efergy online portal was based on the hourly consumption every year.Results: The results show that the outdoor temperature, working hours, and consumption behavior can affect the overall electricity consumption and peak loads. Efficient building strategies are crucial for reducing peak loads by smartly controlling indoor temperature and managing electricity demand. The analysis offers insights into office building electricity consumption patterns and recommends strategies such as prioritizing car charging, optimizing the heat pump's operation of the HVAC system, improving the electricity management system, and using energy storage systems to reduce peak load.Discussion: The findings from this analysis carry implications for electricity consumption. It can provide some insights for reducing electricity consumption and enhancing efficiency in office buildings and similar facilities and also prioritization and rescheduling car chargers. In conclusion, it has interpreted and discussed the various electricity-saving strategies and their potential impact on electricity management.

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Denna studie undersökte hur smartklockors gränssnitt kan utformas för att upplevas användbara samt bidra till minimal kognitiv belastning under fysisk aktivitet. Smartklockors skärmar ställer andra krav på gränssnittet samt medför ett antal utmaningar för hur information kan presenteras på bästa sätt. Utöver detta brukar smartklockor användas i samband med fysisk aktivitet, som ställer höga krav på användarens uppmärksamhet. För att bibehålla hög kvalitet på träningen bör den kognitiva belastningen minska. För att undersöka detta har Cognitive Load Theory applicerats för att kunna optimera arbetsminnets kapacitet. Studien gjorde på personer i 20 års ålder. En kvalitativ datainsamling gjordes genom ett användartest och semistrukturerade intervjuer. Användartestet utfördes på en stationär cykel där deltagarna utförde ett antal uppgifter på en smartklocka. Efteråt skedde semistrukturerade intervjuer. Resultatet analyserades genom kategorisering och jämfördes med tidigare studier. Utifrån de mest förekommande resultaten skapades åtta designförslag. Resultaten visade att eliminering av viss information på gränssnitt kan minska den kognitiva belastningen samt höja användbarheten. Ett konsekvent gränssnitt skulle kunna minimera antal fel samt underlätta för användaren att korrigera fel. En tillämpning av de framtagna designförslagen kan eventuellt minimera den kognitiva belastningen vid interaktion med smartklockors gränssnitt vid fysisk aktivitet. Detta kan underlätta för användaren att fokusera på träningen samt uppleva klockan som mer användbar. / This study examined how an interface for smartwatches can be designed to be perceived as useful and reduce cognitive load during physical activity. Smartwatch screens have other demands on the interface and face several challenges regarding how information can be presented. In addition to this, smartwatches are often used in physical activity, which places high demands on user's attention. To maintain high-quality training, the cognitive load should be reduced. To investigate this, cognitive load theory has been applied to optimize the capacity of the working memory. The study looked at people in their 20s. Qualitative data collection was done through a user test and semi-structured interviews. The user test was done on a stationary bike, the participants performed several tasks on the smartwatch. The participants rode a stationary bicycle while performing tasks on a smartwatch, followed by semistructured interviews. The results were analyzed by thematization and compared with previous studies. Based on the most common results, eight design proposals were created. The results showed that by eliminating unnecessary information, the interface can reduce cognitive load and increase usability. A consistent interface could minimize the number of errors and make it easier for the user to correct errors. An application of the developed design proposals may minimize the external load when interacting with the smartwatch interface during physical activity. This can support users can focus on training and experience the watch as more useful.

The Hampton Roads Bridge-Tunnel is one of the oldest prestressed concrete structures in the United States. The 3.5 mile long twin structure includes the world's first underwater tunnel between two man-made islands. Throughout its 60 years in service, the harsh environment along the Virginia coast has taken its toll on the main load carrying girders. Concrete spalling has exposed prestressing strands within the girders allowing corrosion to spread. Some of the more damaged girders have prestressing strands that have completely severed due to the extensive corrosion. The deterioration has caused select girders to fail the necessary load ratings. The structure acts as an evacuation route for the coast and is a main link for the local Norfolk Naval Base and surrounding industry. Because of these constraints, load posting is not a viable option. Live load testing of five spans was performed to investigate the behavior of the damaged spans. Innovative techniques were used during the load test including a wireless system to measure strains. Two different deflection systems were implemented on the spans, which were located about one mile offshore. The deflection data was later compared head to head. From the load test results, live load distribution factors were developed for both damaged and undamaged girders. The data was also used by the local Department of Transportation to validate computer models in an effort to help pass the load rating. Overall, this research was at the forefront of the residual strength of prestressed concrete girders and the testing of in-service bridges. / Master of Science

The forecasting of Eskom transmission electrical network demands is a complex task. The lack of historical data on some of the network components complicates this task even further. In this dissertation a model is suggested which will address all the requirements of the transmission system expansion engineers in terms of future loads and market trends. Suggestions are made with respect to ways of overcoming the lack of historical data, especially on the point loads, which is a key factor in modelling the electrical networks. A brief overview of the transmission electrical network layout is included to provide a better understanding of what is required from such a forecast. Lastly, some theory on multiple regression, neural networks and qualitative forecasting techniques is included, which will be of value for further model developments. / Computing / M. Sc. (Operations Research)

The forecasting of Eskom transmission electrical network demands is a complex task. The lack of historical data on some of the network components complicates this task even further. In this dissertation a model is suggested which will address all the requirements of the transmission system expansion engineers in terms of future loads and market trends. Suggestions are made with respect to ways of overcoming the lack of historical data, especially on the point loads, which is a key factor in modelling the electrical networks. A brief overview of the transmission electrical network layout is included to provide a better understanding of what is required from such a forecast. Lastly, some theory on multiple regression, neural networks and qualitative forecasting techniques is included, which will be of value for further model developments. / Computing / M. Sc. (Operations Research)