Controlling thermal environments today is a complex subject and even more so when thetemperatures are cryogenic. The aim of this thesis is to investigate the crycooler GryoTelGT from Sunpower Inc under di erent conditions such as with or without insulation.The materials that will be used as insulation are Ni and Al foil. The insulation willbe assembled using di erent confgurations to test the eÿciency of these when used inconjunction with the cryocooler.Multiple formations of foil were assembled ranging between 5-10 layers, using lids madefrom Ni and Al foil as well as 3D-printed PLA plastic. Tests were conducted with thecryocooler operating at di erent power levels and through use of a thermal load.This thesis provides results from the tests made with di erent foil confgurations andvaried power levels on the thermal load and the CryoTel cryocooler. The thesis concludesthat Ni and Al foil has a minor but consistent e ect on the temperature of the cold tipin this setting and that the largest contributing factor was the power level of the CryoTelcooler during operation as well as the operating temperature of the CryoTel body.

No description available.

Indoor air quality is recognized as one of the most important environmental concerns, since people spend almost 90% of their lifetime indoors. Indoor sources of volatile organic compounds (VOCs) are a determinant of air quality in houses. Many materials used to construct and finish the interiors of new houses emit VOCs. These emissions are a probable cause of acute health effects and discomfort among occupants. Ventilation is another determinant of indoor air quality in houses, because it serves as the primary mechanism for removal of gaseous contaminants generated indoors. Thus, higher contaminant concentrations are expected at lower ventilation rates given constant emission rates. The trend in new construction is to make house envelopes tighter for higher energy efficiency. The use of Structural Insulated Panels (SIPs) in new construction and major renovation to create very tight building envelopes is one popular approach to realizing this goal. The basic SIPs configuration uses oriented strand board (OSB) and polystyrene foam (PSF) in a multi-layered sandwich-like structure. Specific benefits of SIPs include lower energy consumption, stronger more durable structures and better resource efficiency. These advantages make panelized systems very attractive from both environmental impact and energy use perspectives. However, there is a potential for houses constructed with SIPs to have degraded air quality relative to conventionally constructed houses that utilize fewer engineered wood products. OSB emits pentanal and hexanal, two odorous aldehydes. These contaminants originate in the wood drying process through the breakdown of wood tissue and are, thus, inherent to most engineered wood products. The PSF in SIPs is a major source of styrene. The large surface area of installed SIPs systems (typically the entire exterior shell), combined with the resulting decrease in ventilation rate due to very low infiltration, exacerbates the indoor air problem. Thus, the potential release of volatile contaminants must be taken into careful consideration when designing homes constructed with SIPs. The ability to predict and ultimately minimize the negative impact of panel systems on indoor concentrations of contaminants of concern would be extremely useful for advancing housing technologies. No prior investigations of VOC emissions from SIPs have been reported in the literature. Two main methods are used to characterize emissions from building materials: chamber studies and mathematical modeling. While chamber studies are costly and time-consuming, mathematical modeling is becoming an economical and effective alternative. Physically-based models are especially useful because they provide insight into the governing mechanisms and the factors that control the emissions process. Although emissions from building materials have traditionally been empirically characterized in chambers, we have recently validated a mechanistic model that predicts VOC emissions from vinyl flooring. The approach involved independently measuring C0 (the initial material-phase concentration), D (the material-phase diffusion coefficient), K (the material/air partition coefficient) and then predicting the emission rate a priori using a fundamental mass-transfer model We now wish to generalize this approach and use it to predict emissions from multi-layered SIPs. To begin with, we will apply a single-layer model to predict emissions from each of the two SIP components: OSB and PSF. Once this has been accomplished, it should be possible to develop a multi-layer model to predict emissions from the composite SIPs. Our first research objective was to characterize transport of volatile organic compounds (VOCs) in polystyrene foam (PSF), a diffusion-controlled building material. The sorption/desorption behavior of the polystyrene foam was investigated using a single-component system. A microbalance was used to measure the sorption/desorption kinetics and to obtain equilibrium relationships. Hexanal and styrene were selected as the target compounds. While styrene transport in PSF can be described by Fickian diffusion with a symmetrical and reversible sorption/desorption process, the hexanal transport process exhibited significant hysteresis, with desorption being much slower than sorption. To address this hysteresis, a porous media diffusion model that assumes local equilibrium governed by a non-linear Freundlich isotherm was developed. The model was found to conform closely to the experimental kinetic data for both sorption and desorption. By incorporating the Freundlich sorption mechanism into the traditional Fickian diffusion model, the hysteresis in the hexanal transport process in PSF was explained. Contaminant emissions from building materials may tail extensively and require longer times to desorb than absorb. This slow desorption or hysteresis problem has been an obstacle to understanding VOC emissions from building materials. The overall goal of our second research objective was to (i) develop a predictive nonlinear emission model by incorporating a local Freundlich sorption equilibrium to account for the slow desorption; (ii) validate the new nonlinear emission model using independent chamber data; and (iii) compare the new nonlinear emission model with a previously published linear emission model. Styrene in polystyrene foam (PSF) and hexanal in oriented strand board (OSB) were selected as the target compounds and materials, respectively. Sorption/desorption kinetic experimental data show that while styrene sorption/desorption in PSF is symmetrical, hexanal sorption/desorption in OSB is not symmetrical. For hexanal in OSB, slower desorption was observed. Model validation results show that while the simple linear emission model can predict styrene emissions from PSF, it underestimates hexanal emissions from OSB. With the new nonlinear emission model developed in this research, hexanal emission from OSB can be predicted. These results suggest that local sorption equilibrium needs to be considered when predicting the emission rate of polar compounds from building materials. The final objective was to develop a new multi-layer model for a layered SIP system. Composite layered building materials are widely used in indoor environments due to their environmental and energy advantages. However, the tight structure may result in degraded indoor air quality and the potential release of volatile organic compounds (VOCs) from these layered materials must be considered. A theoretical physically-based diffusion model for predicting VOCs emissions from such multi-layer materials is described in this research. It is assumed that the individual layers are flat homogeneous slabs, that internal mass transfer is governed by diffusion, and that the indoor air is well mixed. For each layer, the material-phase diffusion coefficient (D), the material-phase partition coefficient (K), and the initial material-phase concentration (C0) are the key model parameters. In this model, fugacity is used to numerically solve the model because this eliminates the discontinuities in concentration at the interface between layers. This overcomes an insurmountable obstacle associated with numerically simulating mass transfer in composite layers. The fugacity-based numerical model is checked by comparing predicted concentrations to those obtained with a previously published analytical model for double-layered materials. In addition, transport of hexanal and styrene within, and emissions of hexanal and styrene from, multi-layer Structural Insulated Panels (SIPs) are simulated to demonstrate the usefulness of the model. These preliminary results establish the viability of the fugacity approach. Finally, the multi-layer layer model is used to demonstrate the impact that barrier materials can have. Results show that contaminant gas phase concentration can be reduced greatly with a barrier layer on the surface. This deomonstrates the potential of thin barrier layers to minimize the environmental impact of panelized systems. Future work will focus on a more complete experimental validation of the multi-layer model. / Ph. D.

Electronic Health Record (EHR) is an umbrella term encompassing demographics and health information of a patient from many different sources in a digital format. Deep learning has been used on EHRs in many successful studies and there is great potential in future implementations. In this study, diagnosis classification of EHRs with Multi-layer Perceptron models are studied. Two MLPs with different architectures are constructed and run on both a modified version of the EHR dataset and the raw data. A Random Forest is used as baseline for comparison. The MLPs are not successful in beating the baseline, with the best-performing MLP having a classification accuracy of 48.1%, which is 13.7 percentage points lower than that of the baseline. The results indicate that when the dataset is small, this approach should not be chosen. However, the dataset is growing over time and thus there is potential for continued research in the future. / Elektronisk patientjournal (EHR) är ett paraplybegrepp som används för att beskriva en digital samling av demografisk och medicinsk data från olika källor för en patient. Det finns stor potential i användandet av djupinlärning på dessa journaler och många framgångsrika studier har redan gjorts på området. I denna studie undersöks diagnosklassificering av elektroniska patientjournaler med Multi-layer perceptronmodeller. Två MLP-modeller av olika arkitekturer presenteras. Dessa körs på både en anpassad version av EHR-datamängden och på den råa EHR-datan. En Random Forest-modell används som baslinje för jämförelse. MLP-modellerna lyckas inte överträffa baslinjen, då den bästa MLP-modellen ger en klassifikationsnoggrannhet på 48,1%, vilket är 13,7 procentenheter mindre än baslinjens. Resultaten visar att en liten datamängd indikerar att djupinlärning bör väljas bort för denna typ av problem. Datamängden växer dock över tid, vilket gör områdetattraktivt för framtida studier.

Multi-view video is capable of presenting a full and accurate depth perception of a scene. The concept of multi-view video is becoming more useful especially in 3D display systems by enhancing the viewing of high resolution stereoscopic images from arbitrary viewpoints without the use of any special glasses. Like monoscopic video, the multi-view video is faced with different challenges such as: reliable compression, storage and bandwidth due to the increased number of views as well as the high sensitivity to transmission errors. All these may lead to a detrimental effect on the reconstructed views. The work in this thesis investigates the problems and challenges of transmission losses in a multi-view video bitstream over error prone wireless networks. Based on the network simulation results, the proposed technique is capable of addressing the problem of transmission losses. In practical wireless networks, transmission errors are inevitable and pose a serious challenge to the coded video data. The aim of this research effort is to examine the effect of these errors in a multi-view video bitstream when transmitted over a lossy channel. Moreover, this research work aims to develop a novel scheme that can make the multi-view coded videos more robust to transmission errors by minimizing the error effects and improving the perceptual quality. Multi-layer data partitioning as an error resilient technique is developed in JMVC 8.5 reference software in order to make the multi-view video bitstream more robust during transmission. In addition to that, we propose a simple decoding scheme that can support the decoding of the multi-layer data partitioning bitstream over channels with high error rate. The proposed technique is benchmarked with the already existing H.264/AVC data partitioning technique. The work in this thesis also employs the use of group of pictures as a coding parameter to investigate and reduce the effects of transmission errors in multi-view video transmitted over a very high error rate channel. The experiments are carried out with different error loss rates in order to evaluate the performance of these techniques in terms of perceptual quality when transmitted over a simulated erroneous channel. Errors are introduced using the Sirannon network simulator. The error performance of each technique is evaluated and analysed both objectively and subjectively after reconstruction. The results of the research investigation and simulation are presented and analysed in chapter six of the thesis.

A structural health monitoring system is desired to monitor the integrity of cylindrical, multi-layer carbon over-wrapped pressure vessels intended to house hydrogen at high pressures. In order to develop the system based on ultrasonic guided wave technology, the interaction between ultrasonic guided waves and defect types of interest must be understood. Finite element models in two and three dimensions are developed to predict guided wave motion in the reservoirs. Key parameters are optimized including frequency range, excited modes, detected modes, and transducer dimensions. A novel baseline subtraction technique in the frequency wavenumber domain is presented to increase lower level detection limits. Some experiments are carried out to corroborate the findings in the finite element environment.

This paper reports the evaluation results of the mechanical structures of MEMS (micro electro mechanical systems) sensor implemented in the integrated MEMS inertial sensor for a wide sensing range from below 0.1 G to 20 G (1 G = 9.8 m/s^2). To investigate the mechanical tolerance, a maximum target acceleration of 20G was applied to the sub-1G sensor which had the heaviest proof mass of all that sensors had. The structure stability of Ti/Au multi-layered structures was also examined by using Ti/Au micro cantilevers. The results showed that the stoppers effectively functioned to prevent the proof mass and the springs from self-destruction, and that the stability of Ti/Au structures increased with an increase in width. Those results suggest that the proposed stopper and spring structures could be promising to realize MEMS sensors.

In this research, a novel machine learning method is designed and applied to Mine Countermeasure Missions. Similarly to some kernel methods, the proposed approach seeks to compute a linear model from another higher dimensional feature space. However, no kernel is used and the feature mapping is explicit. Computation can be done directly in the accessible feature space. In the proposed approach, the feature projection is implemented by constructing a large hidden layer, which differs from traditional belief that Multi-Layer Perceptron is usually funnel-shaped and the hidden layer is used as feature extractor. The proposed approach is a general method that can be applied to various problems. It is able to improve the performance of the neural network based methods and the learning speed of support vector machine. The classification speed of the proposed approach is also faster than that of kernel machines on the mine countermeasure mission task.

Kenneth John Nixon, Student no: 9307628H, PhD thesis, Electrical & Information Engineering, Faculty: Engineering & the Built Environment. 2006. / The work presented extends and contributes to research in earthing and lightning protection and focuses on the transient behaviour of a driven rod earth electrode. Although previous work in this area has produced practical guidelines and models that may be used for lightning protection system design and analysis purposes, there has not been an investigation into the commonly encountered scenario of multiple layers of di erent soil types, particularly where high current densities cause ionisation to occur in the surrounding soil. In the research presented, the behaviour of a practical driven rod earth electrode subjected to peak impulse currents of up to 30 KA is analysed. Measurements obtained using a large-scale experiment arrangement are compared against results obtained using a time-domain circuit model simulation. It is shown that a single apparent resistivity value calculated from the steady state resistance equation and the measured steady state resistance can be used as a simpli cation for modelling the lightning current transient behaviour of a driven rod earth electrode in multi-layer soil. This represents a unique and valuable contribution to engineers working in the eld of earthing and lightning protection.

The permanent magnet synchronous machines have been attracting more and more attention due to the advantages of high torque density, outstanding efficiency and maturing technologies. Under the urges of mandatory energy efficiency requirements, they are considered as the most potential candidates to replace the comparatively low-efficient induction machines which dominate the industrial market. However, most of the high performance permanent magnet machines are based on high cost rare-earth materials. Thus, there will be huge demands for low-cost high-performance permanent magnet machines. Ferrite magnet is inexpensive and abundant in supply, and is considered as the most promising alternative to achieve the goal of low cost and high performance. In consideration of the low magnetic energy, this thesis explored the recent developments and possible ideas of ferrite machines, and proposed a novel multi-layer spoke-type interior permanent magnet configuration combining the advantages of flux focusing technique and multi-layer structure. With comparable material cost to induction machines, the proposed ferrite magnet design could deliver 27% higher power with 2-4% higher efficiency with exactly the same frame size. Based on the data base of International Energy Agency (IEA), electricity consumed by electric machines reached 7.1PWh in 2006 [1]. Considering that induction machines take up 90% of the overall industrial installation, the potential energy savings is enormous. This thesis contributes in five key aspects towards the investigation and design of low-cost high-performance ferrite permanent magnet machines. Firstly, accurate analytical models for the multi-layer configurations were developed with the consideration of spatial harmonics, and provided effective yet simple way for preliminary design. Secondly, the influence of key design parameters on performance of the multi-layer ferrite machines were comprehensively investigated, and optimal design could be carried out based on the insightful knowledge revealed. Thirdly, systematic investigation of the demagnetization mechanism was carried out, focusing on the three key factors: armature MMF, intrinsic coercivity and working temperature. Anti-demagnetization designs were presented accordingly to reduce the risk of performance degradation and guarantee the safe operation under various loading conditions. Then, comparative study was carried out with a commercial induction machine for verification of the superior performance of the proposed ferrite machine. Without loss of generality, the two machines had identical stator cores, same rotor diameter and stacking length. Under the operating condition of same stator copper loss, the results confirmed the superior performance of the ferrite machine in terms of torque density, power factor and efficiency. Lastly, mechanical design was discussed to reduce the cost of mass production, and the experimental effort on the prototype machine validates the advantageous performance as well as the analytical and FEA predictions.