Variations in vehicle noise, vibration and harshness (NVH) response from one vehicle to the next can have significant impact on an automotive company’s profile and profitability. The warranty claims due to excessive NVH response end up costing the manufacturers a large sum of money each year. In addition, the OEM will suffer a larger financial loss due to the poor perception of quality and customer dissatisfaction with their products due to the unacceptable NVH response. Therefore, measures must be taken to ensure less warranty claims and higher levels of customer satisfaction. This research focuses on aspects of design variations that are costly or difficult to be avoided in the design process such as variations with rubber parts and variations due to rotating components. Vibrations induced at the tire/wheel assembly due to variations in the radial and tangential forces and radial runout are responsible for the driverelt vibrations that can lead to a large number of warranty claims. The purpose of this research is to improve the process of determining and analyzing vibration sources in the tire/wheel assembly in order to benefit the automotive manufacturer during the development and manufacturing phases. This research identifies the relationship between non-uniformity forces of the tire/wheel assemblies and the driverelt vibrations during typical highway driving speeds. The contribution from each assembly location is analyzed and sensitivities are determined. A Monte Carlo process is used to predict numerous non-uniformity properties that are statistically representative of the assembly properties that can be expected at the manufacturing plant. The Monte Carlo produced non-uniformity properties are combined with the sensitivities to predict driverelt vibrations that can be expected from vehicles leaving the manufacturing plant. This process provides the tools to determine an acceptable level of non-uniformities based on targets for interior vibration levels or determine if the vehicle sensitivities to non-uniformities need to be improved.

Anwendung von maschinellen Lernverfahren (ML) in der Produktionstechnik, in Zeiten der Industrie 4.0, stark angestiegen. Insbesondere die Datenverfügbarkeit ist an dieser Stelle elementar und für die erfolgreiche Umsetzung einer ML-Applikation Voraussetzung. Falls für eine gegebene Problemstellung die Datenmenge oder -qualität nicht ausreichend ist, können Techniken, wie die Datenaugmentierung, der Einsatz von synthetischen Daten sowie das Transferlernen von ähnlichen Datensätzen Abhilfe schaffen. Innerhalb dieser Ausarbeitung wird das Konzept des Transferlernens im Bereich das Radial-Axial Ringwalzens (RAW) angewendet und am Beispiel der Zeitreihenprognose des Außendurchmessers über die Prozesszeit durchgeführt. Das Radial-Axial Ringwalzen ist ein warmumformendes Verfahren und dient der nahtlosen Ringherstellung.

Due to the increasing computing power and corresponding algorithms, the use of machine learning (ML) in production technology has risen sharply in the age of Industry 4.0. Data availability in particular is fundamental at this point and a prerequisite for the successful implementation of a ML application. If the quantity or quality of data is insufficient for a given problem, techniques such as data augmentation, the use of synthetic data and transfer learning of similar data sets can provide a remedy. In this paper, the concept of transfer learning is applied in the field of radial-axial ring rolling (rarr) and implemented using the example of time series prediction of the outer diameter over the process time. Radial-axial ring rolling is a hot forming process and is used for seamless ring production.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / The US ARMY, ARDEC; in cooperation with AMCOM AMRDEC, Missile Guidance and Engineering Directorates; the Office of Naval Research; Naval Surface Fire Support; and the Naval Surface Weapon Center, requires multiphase development of a common, low-cost, high G survivable, high accuracy, Micro Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) and Common, Deeply Integrated, Guidance and Navigation Unit (DI-GNU) for DoD gun launched guided munition and missile applications. The challenge for the Precision Munition Instrumentation Division (PMID) was to develop a Telemetry System to record the interior and exterior ballistics of a M831 TP-T projectile, which will be used as a carrier for soft recovery testing of IMUs and GNUs. This valuable data that would help The Government and contractors develop and validate multiple MEMS IMU design efforts, culminating with live fire verification performance test of pre-production in the Army’s 155-mm Soft Recovery Vehicle (SRVs) and missiles airframes.

Exoplanets are now known to be ubiquitous throughout the Galaxy. From the Kepler survey, we expect nearly every main-sequence star to form planetary systems during its formation phase. However, the detection limits of Kepler are confined to planets with short orbital periods, comparable to those in the inner solar system. Thanks to the long observational time baseline of the McDonald Observatory Radial Velocity (RV) Survey, we can identify gas giant planets in the outer regions of extrasolar planetary systems. The statistics of such planets are not well known, and are important for understanding the physics behind planet formation and migration. In this dissertation, I detail the discovery of five giant exoplanets on long-period orbits–so-called “Jupiter analogs.” For two systems of giant planets discovered through our survey, pairs of planets follow closely-packed orbits, creating the possibility for dynamical instability. I therefore examine the orbital resonances that allow these planets to avoid gravitational disruption. Because we see an abundance of small, potentially habitable exoplanets in the Kepler data set, current and upcoming exoplanet surveys concentrate on finding Earth-mass planets orbiting stars near enough to facilitate detailed follow-up observations. Particularly attractive targets are cool, low-mass “M dwarf” stars. Their low masses (and thus higher RV amplitudes from exoplanets) and close-in habitable zones allow for relatively quick detection of low-mass planets in the habitable zone. However, the RV signals of such planets will be obscured by stellar magnetic activity, which is poorly understood for M stars. In an effort to improve the planet detection capabilities of our M dwarf planet survey, I have conducted a detailed investigation of the magnetic behavior of our target stars. I show that, while stellar activity does not appear to systematically influence RV measurements above a precision level of ∼ 5 m/s, activity cycles can occasionally produce RV signals in excess of 10 m/s. Additionally, I show that long-term, solar-type stellar activity cycles are common amongst our M dwarf targets, although they are significantly less frequent than for FGK stars. In the case of GJ 328, I have discovered a magnetic activity cycle that appears in the RV data, causing the giant planet around the star to appear to be on a more circular orbit than indicated by the activity-corrected data. Such corrections are essential for the discovery of Earthlike exoplanets. / text

We study the motion of giant stars in the Solar neighbourhood and what they tell us about the dynamics of the Galaxy: we thus contribute to the huge project of understanding the structure and evolution of the Galaxy as a whole. We present a kinematic analysis of 5952 K and 739 M giant stars which includes for the first time radial velocity data from an important survey performed with the CORAVEL spectrovelocimeter at the Observatoire de Haute Provence. Parallaxes from the Hipparcos catalogue and proper motions from the Tycho-2 catalogue are also used. A maximum-likelihood method, based on a bayesian approach, is applied to the data, in order to make full use of all the available stars, and to derive the kinematic properties of the subgroups forming a rich small-scale structure in velocity space. Isochrones in the Hertzsprung-Russell diagram reveal a very wide range of ages for stars belonging to these subgroups, which are thus most probably related to the dynamical perturbation by transient spiral waves rather than to cluster remnants. A possible explanation for the presence of young group/clusters in the same area of velocity space is that they have been put there by the spiral wave associated with their formation, while the kinematics of the older stars of our sample has also been disturbed by the same wave. The emerging picture is thus one of "dynamical streams" pervading the Solar neighbourhood and travelling in the Galaxy with a similar spatial velocity. The term "dynamical stream" is more appropriate than the traditional term "supercluster" since it involves stars of different ages, not born at the same place nor at the same time. We then discuss, in the light of our results, the validity of older evaluations of the Solar motion in the Galaxy. We finally argue that dynamical modeling is essential for a better understanding of the physics hiding behind the observed kinematics. An accurate axisymmetric model of the Galaxy is a necessary starting point in order to understand the true effects of non-axisymmetric perturbations such as spiral waves. To establish such a model, we develop new galactic potentials that fit some fundamental parameters of the Milky Way. We also develop new component distribution functions that depend on three analytic integrals of the motion and that can represent realistic stellar disks.

We report on the scrambling performance and focal-ratio-degradation (FRD) of various octagonal and rectangular fibers considered for MAROON-X. Our measurements demonstrate the detrimental effect of thin claddings on the FRD of octagonal and rectangular fibers and that stress induced at the connectors can further increase the FRD. We find that fibers with a thick, round cladding show low FRD. We further demonstrate that the scrambling behavior of non-circular fibers is often complex and introduce a new metric to fully capture non-linear scrambling performance, leading to much lower scrambling gain values than are typically reported in the literature (<1000 compared to 10,000 or more). We find that scrambling gain measurements for small-core, non-circular fibers are often speckle dominated if the fiber is not agitated.

Opioid medications are medicine's best weapon against severe intractable pain, but prolonged use of these medications can be complicated by side effects like tolerance and mental clouding which, themselves, can be disabling. The present study examined the independent and combined effects of inflammatory pain and opioid medication on spatial memory for a well learned task in Sprague-Dawley rats. The Hargreaves method was used to verify the pain state of the animals after complete Freund's adjuvant injection and morphine treatment. Whereas pain had little effect on spatial memory, morphine had profound detrimental effects that persisted beyond the analgesic effectiveness of the drug. However, morphine-induced cognitive deficits were absent when morphine was provided to animals in chronic pain. Also, analgesic tolerance was significantly attenuated in these animals. Taken together, these results suggest that chronic pain activates a neural mechanism that antagonizes the unwanted effects of opioids.