A general rotating frame formulation of the Navier-Stokes equations has been added to the incompressible and arbitrary Mach number versions of UNCLE. While eliminating the need for moving grids, this formulation also reduces the error caused by linear approximations of rotational motion. The formulation is validated for single axis rotations by comparing the simulations of a marine propeller and an isolated helicopter rotor with experimental data. A simulation of the helicopter rotor in pitching motion is also performed. Results are compared between the non-inertial reference frame formulation and absolute frame solver for a prolate spheroid with all the components of angular velocity. The use of the non-inertial reference frame promises a faster and more accurate six-degree-ofreedom simulations.

High energy density experiments rely heavily on predictive physics simulations in the design process. Specifically in inertial confinement fusion (ICF), predictive physics simulations, such as in the radiation-hydrodynamics code xRAGE, are computationally expensive, limiting the design process and ability to find an optimal design. Machine learning provides a mechanism to leverage expensive simulation data and alleviate limitations on computational time and resources in the search for an optimal design. Machine learning efficiently identifies regions of design space with high predicted performance as well as regions with high uncertainty to focus simulations, which may lead to unexpected designs with great potential. This dissertation focuses on the application of Bayesian optimization to design optimization for ICF experiments conducted by the double shell campaign at Los Alamos National Lab (LANL). The double shell campaign is interested in implementing graded inner shell layers to their capsule geometry. Graded inner shell layers are expected to improve stability in the implosions with fewer sharp density jumps, but at the cost of lower yields, in comparison to the nominal bilayer inner shell targets. This work explores minimizing hydrodynamic instability and maximizing yield for the graded inner shell targets by building and coupling a multi-fidelity Bayesian optimization framework with multi-dimensional xRAGE simulations for an improved design process. / Doctor of Philosophy / Inertial confinement fusion (ICF) is an active field of research in which a fuel is compressed to extreme temperatures and densities to achieve thermonuclear ignition. Ignition is achieved when the fuel can continuously heat itself and sustain its reactions. These fusion reactions would produce large amounts of energy. Power plants using fusion could solve many of the world's energy concerns with far less pollution than current energy sources. Although ignition has not been achieved in the lab, ICF researchers are actively working towards this goal. At Los Alamos National Lab (LANL), ICF researchers are focused on studying ignition-relevant conditions for "double shell" targets through experiments at laser facilities, such at the National Ignition Facility (NIF). These experiments are extremely expensive to field, design, and analyze. To obtain the maximum information from each experiment, researchers rely on predictive physics simulations, which are computationally intensive, making it difficult to find optimal target designs. In this dissertation, better use of simulations is made by focusing on using machine learning along with simulation data to find optimal target designs. Machine learning allows for efficient use of limited computational time and resources on simulations, such that an optimal target design can be found in a reasonable amount of time before an ICF experiment. This dissertation specifically looks at using Bayesian optimization for design optimization of LANL's double shell capsules with graded material inner shells. Several Bayesian optimization frameworks are presented, along with a discussion of optimal designs and physics mechanisms that lead to high performing capsule designs. The work from this dissertation will create an improved design process for the LANL double shell (and other) campaigns, providing high fidelity optimization of ICF targets.

The aim of this master’s thesis was to describe the basic measurement methods for measurement of inertial sensor, their physical principles and errors. The next step was to select a specific parameter, then test it on a number of sensors and evaluate the results. Measurement of inertial sensors is very important for the parametrization of their errors and their subsequent mathematical model by which it is possible to minimize their impact on inertial navigation. The practical part is dedicated to the measurement of stability of the offset. Data acquisition card NI-USB 6215, which can supply two accelerometers at the same time using analog outputs, was used for data acquisition and power supply. It was tested on seven inertial sensor from four manufacturers. Two connection methods with NI-USB 6215, by whose it was determined which one is better to suppress the crosstalk between channels, were used for measurement. The NI PXI 4462 was used to verify that the NI-USB 6215 card is sufficient. The parameters for description of the changes in inertial sensors were established, transition between the initial and final value of the output measurement, variance of the values on which the sensor fixates after 72 iterations, and the fixation time of the sensor.

The aim of this master’s thesis is to describe the basic measurement methods of micro-electromechanical inertial sensor, their physical principles and errors. Measurement of inertial sensors is very important for the parameterization of their errors and their subsequent mathematical model by which it is possible to minimize the measurement error impact on inertial navigation. The practical part is dedicated to create automated measurement setup for measurement stability of the offset. Hardware and software from National Instruments is used in measurement chain. The work is next focused on measuring seven inertial sensors based on three different physical principles. In addition to creating measurement setup, we also defined three inertial sensor parameters, describing theoretical behavior of the sensor output.

Motion analysis deals with determining what and how activities are being performed by a subject, through the use of sensors. The process of answering the what question is commonly known as classification, and answering the how question is here referred to as characterization. Frequently, combinations of inertial sensor such as accelerometers and gyroscopes are used for motion analysis. These sensors are cheap, small, and can easily be incorporated into wearable systems. The overall goal of this thesis was to improve the processing of inertial sensor data for the characterization of movements. This thesis presents a framework for the development of motion analysis systems that targets movement characterization, and describes an implementation of the framework for gait analysis. One substantial aspect of the framework is symbolization, which transforms the sensor data into strings of symbols. Another aspect of the framework is the inclusion of human expert knowledge, which facilitates the connection between data and human concepts, and clarifies the analysis process to a human expert. The proposed implementation was compared to state of practice gait analysis systems, and evaluated in a clinical environment. Results showed that expert knowledge can be successfully used to parse symbolic data and identify the different phases of gait. In addition, the symbolic representation enabled the creation of new gait symmetry and gait normality indices. The proposed symmetry index was superior to many others in detecting movement asymmetry in early-to-mid-stage Parkinson's Disease patients. Furthermore, the normality index showed potential in the assessment of patient recovery after hip-replacement surgery. In conclusion, this implementation of the gait analysis system illustrated that the framework can be used as a road map for the development of movement analysis systems.

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 / In pursuit to understanding the flight behavior and characterizing the stability of a flarestabilized projectile, an experiment was conducted to assess the robustness of an inertial sensor suite the size of a dime (17.5mm) by integrating to a telemetry system for recording. The system had to survive launch acceleration exceeding 25,000G’s. This is the beginning of an effort to reduce the size of telemetry systems and diagnostic devices for use in medium caliber munitions and smaller. A description of the telemetry system and subsystem will be presented along with the results.

No description available.

The ability to walk and negotiate stairs is an important predictor of independent ambulation. The superposition of mobility impairments to the effects of natural aging in persons with stroke render the completion of many daily activities unsafe, thus limiting individuals’ independence within their communities. Currently however, no means exist for the monitoring of mobility levels during daily living in survivors after the completion of rehabilitation programs. The application of inertial sensors for stroke survivors could provide a basis for the study of gait outside of traditional laboratory settings. The main objective of this thesis was to evaluate the performance of inertial sensors in measuring gait of hemiparetic stroke survivors through the completion of three studies. The first study explored the use of inertial measurement units (IMUs) for the measurement of lower limb joint kinematics during stair ascent and descent in both stroke survivors and healthy older adults. Results suggested that IMUs were suitable for the measurement of lower limb range of motion in both healthy and post-stroke subjects during stair ambulation. The second study evaluated the measurement of step length and spatial symmetry during overground walking using IMUs. A systematic error resulting in the underestimation of step lengths calculated using IMUs compared with those measured using video analysis was found, however results suggested that IMUs were suitable for the assessment of spatial symmetry between affected and less-affected limbs in stroke survivors. The final study evaluated the automatic classification of gait activities using inertial sensor data. Findings revealed that the use of a classifier composed of frequency-features extracted from IMU accelerometer and gyroscope data from both the affected and less-affected limbs most accurately identified gait activities from post stroke gait data. This thesis provides a first attempt at applying IMUs to the study of gait post-stroke. Future work may extend the findings of these studies to provide a better understanding to rehabilitation professionals of the demands of everyday life for stroke survivors. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2013-08-29 12:42:05.505

I used a Mach-Zehnder atom interferometer to measure the static electric-dipole polarizabilities of K, Rb, and Cs atoms with 0.11\% uncertainty. Static polarizability measurements serve as benchmark tests for 𝑎𝑏 𝑖𝑛𝑖𝑡𝑖𝑜 atomic structure calculations. Calculating atomic properties such as polarizabilities, van der Waals coefficients, state lifetimes, or oscillator strengths involves accurately calculating the valence electrons' electric-dipole transition matrix elements. Additionally, testing Cs atomic structure calculations helps interpret the results of parity non-conservation experiments, which in turn places constraints on beyond-the-standard-model physics. I discuss improvements to our experiment that allowed us to measure static polarizabilities with 0.11% uncertainty, and we present our results in the context of recent 𝑎𝑏 𝑖𝑛𝑖𝑡𝑖𝑜 and semi-empirical static polarizabilities and recent, high-precision measurements of excited state lifetimes and van der Waals C₆ coefficients. I also used our interferometer to develop a new technique for inertial sensing. High precision, portable, atom-interferometer gyroscopes and accelerometers are desirable for self-contained inertial navigation and in the future may be used for tests of General Relativity and searches for gravitational waves using satellite-mounted inertial sensors. Satellite-mounted atom interferometers are challenging to build because of size, weight, power, and reliability constraints. Atom interferometers that use nanogratings to diffract atoms are attractive for satellite-mounted inertial sensing applications because nanogratings weigh approximately nothing and require no power. We developed a new 𝑖𝑛 𝑠𝑖𝑡𝑢 measurement technique using our nanograting atom interferometer, and we used it to measure inertial forces for the benefit of our static polarizability measurements. I also review how to calculate the sensitivity of a nanograting atom interferometer, and I employed these calculations in order to design a portable, nanograting atom interferometer inertial sensor.

Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Includes bibliographical references. / Sc.D.