La détection des très faibles valeurs de champ magnétique est un enjeu important pour l’émergence à plus grande échelle de techniques pour le domaine du médical telles que la magnéto cardiographie, ou la magnétoencéphalographie. Les solutions existantes industrialisées reposent sur l’utilisation de jonctions tunnels supraconductrices qui permettent de fabriques des SQUIDS (Superconducting Quantum Intereference Device) qui sont les briques de base des magnétomètres avec des sensibilités de l’ordre de la dizaine de femtotesla. Cependant cette approche impose de travailler à des températures très basses qui ne sont accessibles qu’avec de l’hélium liquide. Un approche récente, développée par le Spec-CEA permet de travailler à l’azote liquide (77K) ce qui lève un certain nombre de contraintes. Le dispositif est un capteur mixte composé d’une boucle supraconductrice de grande taille qui contient une constriction de taille micrométrique sur laquelle est rapportée une magnétorésistance tunnel qui sert de sonde locale du champ magnétique. L’objectif du travail dans ce travail de thèse est de poursuivre le développement de ce type de capteur en utilisant visant des structures tout oxyde. En effet l’intégration complète de ce type de capteur permettrait de gagner encore en termes de performances et d’atteindre une résolution de l’ordre du femtotesla. Pour ce faire le travail vise à intégrer une jonction tunnel tout oxyde directement par épitaxie sur la constriction. La jonction tunnel sera réalisée à partie d’oxydes magnétiques tels que les composés LaSrMnO3 ou SrRuO3 qui sont deux matériaux ferromagnétiques à la température de l’azote liquide. / Sensing of extremely weak magnetic signals, such as produced by electrical activity of the human heart and brain, still remains a challenge. A very promising alternative to established field-sensing techniques is a novel, spin electronic based, ultrasensitive device called an all-oxide mixed sensor. It is formed by a superconducting loop, acting as a flux-to-field transformer and field amplifier, combined with a magnetic tunnel junction sensing the field.Our research activities have the goal to improve the performance of the mixed sensor, focusing on its core component – the magnetic tunnel junction (MTJ). The capability of an MTJ is predominantly determined by the quality of the tunnel barrier and by the stability of magnetization states. In this context, oxide materials, known for their remarkable physical properties, have already shown their advantages. Thus, studies on La0.7Sr0.3MnO3/SrTi0.8Nb0.2O3 functional oxide interfaces, exploration of SrRuO3/ La0.7Sr0.3MnO3 exchange bias system, and the final integration of these two components into a magnetic tunnel junction form the main part of our work.In the presented thesis, oxide thin films and heterostructures used for studies were grown by pulsed laser deposition (PLD). We fabricated electronic devices for investigations using clean room microfabrication techniques , e.g. optical lithography, chemically assisted ion beam etching (CAIBE) and sputtering. Temperature dependent magnetic and (magneto-) transport measurements were performed.Metal-semiconductor interfaces formed by the half-metallic ferromagnet La0.7Sr0.3MnO3 (LSMO) and heavily doped semiconductor SrTi0.8Nb0.2O3 (Nb:STO) were studied. Antiferromagnetic coupling at the interface of the LaSrMnO3 and itinerant ferromagnet SrRuO3 was explored. Magnetic tunnel junctions with Schottky barrier were investigated (MTJs with Nb:STO and LSMRO).

High tunnels have been used successfully in many areas of the world to extend the growing season for numerous crops. However, very little research has been conducted to evaluate the season extension benefits offered by high tunnels to small fruit crops in high elevation growing areas such as the Intermountain West region of the United States. The use of high tunnels was investigated in North Logan, Utah (41.766 N latitude, 1405 m elevation, 119 freeze free days) to extend the growing season for both strawberries and raspberries. June-bearing `Chandler' strawberries in a fall-planted annual hill system were evaluated for early season production. High tunnels advanced spring strawberry production by approximately 3 weeks compared to field-grown plants. High tunnels were used for earlier planting and growth in a spring-planted day-neutral strawberry system. Day-neutral cultivars (`Albion', `Seascape', `Evie 2', and `Tribute') produced strawberries throughout the summer and into the fall with significantly higher yields from the high tunnel treatments than the field-grown plants. High tunnels also extended late-season strawberry production until mid-December. The floricane-fruiting red raspberry `Tulameen' was evaluated for early season production, and primocane-fruiting `Caroline' was evaluated for late season extension. High tunnels were unable to provide sufficient winter protection for the cold-tender `Tulameen' at this location. Results from late season extension indicated that high tunnels could extend late season raspberry production by as much as three weeks. However, peak yields for `Caroline' were before the first fall frost, and a later fruiting cultivar would be more suitable. In addition to research results, this thesis contains chapters on practical management considerations for commercial producers, and enterprise budgets to assist in evaluating the economic costs and returns of high tunnel strawberry and raspberry production.

High tunnels have been used for many years worldwide. However, there has been limited research about use of high tunnel technology in the southeastern United States and its popularity has recently increased in Mississippi. A planting date study of 'Roma'' tomato, 'Legend' tomato, 'Ichiban' eggplant, 'Sweet Banana' pepper, ‘Benary’s Giant’ zinnia and ‘Potomac Red’ snapdragon was conducted in spring 2010 in three high tunnels in Starkville, Mississippi. Results showed for most cultivars (tomatoes, eggplant and pepper) a 12 Mar. 2010 planting date did not differ in marketable yield from planting on 2 Apr. 2010. In 2011, a fertilizer study on Encore lettuce mix and Ovation green mix was conducted both in high tunnel and in the field. Results indicated there was no effect of vermicompost tea or fertilizer treatments on yields of salad mixes.

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Mississippi State University has a subsonic closed return wind tunnel facility with an open test section configuration. This research analyzes the test section flow quality using a numerical approach and explain how the diffuser's collector suppresses unsteadiness. Previous experiment assessed the flow quality at the wind tunnel without the collector, and velocity was measured using a pitot-static probe and hot wire. The results show a numerical comparison between the two configurations, with and without the collector, understand the effect of the diffuser 's collector on steadiness and uniformity. This paper will describe the wind tunnel facility and give further details about the measurements tools and the set up, and then introduce the numerical method used and analyze the cases of study and their results.

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Wind tunnel experiments often employ a wide variety and large number of sensor systems. Anomalous measurements occurring without the knowledge of the researcher can be devastating to the success of costly experiments; therefore, anomaly detection is of great interest to the wind tunnel community. Currently, anomaly detection in wind tunnel data is a manual procedure. A researcher will analyze the quality of measurements, such as monitoring for pressure measurements outside of an expected range or additional variability in a time averaged quantity. More commonly, the raw data must be fully processed to obtain near-final results during the experiment for an effective review. Rapid anomaly detection methods are desired to ensure the quality of a measurement and reduce the load on the researcher. While there are many effective methodologies for anomaly detection used throughout the wider engineering research community, they have not been demonstrated in wind tunnel experiments. Wind tunnel experimentation is unique in the sense that many repeat measurements are not typical. Typically, this will only occur if an anomaly has been identified. Since most anomaly detection methodologies rely on well-resolved knowledge of a measurement to uncover the expected uncertainties, they can be difficult to apply in the wind tunnel setting. First, the analysis will focus on pressure measurements around an airfoil and its wake. Principal component analysis (PCA) will be used to build a measurement expectation by linear estimation. A covariance matrix will be constructed from experimental data to be used in the PCA-scheme. This covariance matrix represents both the strong deterministic relations dependent on experimental configuration as well as random uncertainty. Through principles of ideal flow, a method to normalize geometrical changes to improve measurement expectations will be demonstrated. Measurements from a microphone array, another common system employed in aeroacoustic wind tunnels, will be analyzed similarly through evaluation of the cross-spectral matrix of microphone data, with minimal repeat measurements. A spectral projection method will be proposed that identifies unexpected acoustic source distributions. Analysis of good and anomalous measurements show this methodology is effective. Finally, machine learning technique will be investigated for an experimental situation where repeat measurements of a known event are readily available. A convolutional neural network for feature detection will be shown in the context of audio detection. This dissertation presents techniques for anomaly detection in sensor systems commonly used in wind tunnel experiments. The presented work suggests that these anomaly identification techniques can be easily introduced into aeroacoustic experiment methodology, minimizing tunnel down time, and reducing cost. / Doctor of Philosophy / Efficient detection of anomalies in wind tunnel experiments would reduce the cost of experiments and increase their effectiveness. Currently, manual inspection is used to detect anomalies in wind tunnel measurements. A researcher may analyze measurements during experiment, for instance, monitoring for pressure measurements outside of an expected range or additional variability in a time averaged quantity. More commonly, the raw data must be fully processed to obtain near-final results to determine quality. In this dissertation, many methods, which can assist the wind tunnel researcher in reviewing measurements, are developed and tested. First, a method to simultaneously monitor pressure measurements and wind tunnel environment measurements is developed with a popular linear algebra technique called Principal Component Analysis (PCA). The novelty in using PCA is that measurements in wind tunnels are often not repeated. Instead, the proposed method uses a large number of independent measurements acquired in various conditions and fundamental aspects of fluid mechanics to train the detection algorithm. Another wind tunnel system which is considered is a microphone array. A microphone array is a collection of microphones arranged in known locations. Current methods to assess the quality of the output data from this system require extended computation and review time during an experiment. A method parallel to PCA is used to rapidly determine if an anomaly is present in the measurement. This method does not require the extra computation necessary to see what the microphone array has observed and simplifies the quantities assessed for anomalies. While this is not a replacement for complete computation of the results associated with microphone array measurements, this can take most of the effort out of the experiment time and relegate detailed review to a time after the experiment is complete. Finally, an application of machine learning is discussed with an alternate application outside of the wind tunnel. This work explores the usefulness of a convolutional neural network (CNN) for cough detection. This can be similarly applied to detect anomalies in audio data if searching for specific anomalies with known characteristics. CNNs, in general, require much effort to train and operate effectively but are not dependent on the application or data type. These methods could be applied to a wind tunnel experiment. Overall, the work in this dissertation shows many techniques which can be implemented into current wind tunnel operations to improve the efficiency and effectiveness of the data review process.

Superconductor-Insulator-Superconductor (SIS) tunnel junction mixers are now commonly used in astronomical receivers at (sub)millimeter wavelengths because of their superb sensitivity, high dynamic range and stability of operation. Niobium SIS mixers operating at frequencies well below the super- conducting gap (∼680 GHz) have already achieved quantum limited sensitivity. Therefore to further enhance the receiver sensitivity, increasing the Intermediate Frequency (IF) bandwidth of SIS mixers has became crucial. This thesis focuses on the theoretical modeling, design and experimental verifi- cation of Nb SIS mixers operating around 230 GHz with a wide IF bandwidth of 1–15 GHz. These mixers were designed for a single baseline heterodyne interferometer (GUBBINS), which is being built to observe the Sunyaev-Zel’dovich effect in the Cosmic Microwave Background. The combination of wide IF bandwidth SIS mixers and complex analogue correlators will allow GUBBINS to feature high surface brightness sensitivity, that helps to distinguish the weak SZ effect from the background noise. The SIS mixer detector system was assembled inside the GUBBINS cryostat together with the IF electronics and RF/LO optical systems. Low noise temperatures of around 71 K were then measured in the GUBBINS system. The Nb SIS mixer we have developed uses a unilateral finline and fully integrated planar circuits deposited on a silicon substrate, to couple the electromagnetic radiation from the waveguide into the SIS junction. The finline mixer allows a broad-band RF coupling, an easy integration of the on-chip planar circuits and an easy-to-fabricate mixer block. To achieve a wide IF bandwidth, the output impedance of the SIS mixer was well matched to the input impedance of the amplifier by a multi-stage microstrip circuit. Additionally, the planar circuit of the SIS mixer was also designed to have a small lumped inductance and capacitance. The SIS mixer chip was extensively simulated by rigorous electromagnetic software (HFSS) and the S-parameter was exported to a quantum mixing package SuperMix to produce a full-wave model of the mixer. Experimental testing yielded a best noise temperature of 50 K with an average noise temperature of 75 K over an RF bandwidth of 160 GHz– 260 GHz. We have performed thorough experimental and computational investigation of the IF system in particular the constraints on the bandwidth caused by the lumped element capacitance of the mixer chip and the matching of the output impedance of the mixer to the IF amplifier. Our conclusion is that a bandwidth of 1–15 GHz could be achieved using our mixer design, subject to the performance of the amplifier. Finally, a variable temperature load system was successfully developed and tested inside the cryostat, to avoid the losses from the room-temperature optics. We have showed that the noise temperature of the SIS detector could be reduced by as much as 15 K by testing the mixer using a variable temperature load inside the cryostat.

The work presented in thesis is part of the DANIELA project which aims to replace the current air data system on civil aircrafts with a flush mounted Air Data System (ADS) built around a 3 axis Doppler LIDAR function as the primary data channel. This thesis is focused on the comparison of different window materials and their optical clarity by means of theoretical and experimental analysis. Four different window materials including BK7, Sapphire, Germanium and ZnS are placed in a wind tunnel. The samples are each exposed to flows of air and water for specific periods of time during which temperature, pressure and air speed are recorded. Subsequently, each sample is carefully observed under the microscope. This is followed by the measurement of the amount of back scatter via detecting the change in the voltage once it is placed in the optical station. The optical tests reveal the amount of dust adhered to the samples which results in increased voltage. Review of these samples under the microscope matches the results obtained from the optical test. The two sets of data obtained from the two tests determined that some samples collected more dust in comparison to others. It was established that under identical test conditions i.e. flow, temperature and moisture, BK7 and Sapphire collect considerably less dust compared to ZnS. Moreover it was impossible to test Germanium sample optically, under a microscope as it is a dark opaque glass.