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Nonlinear damping as the fourth dimension in optical fiber anemometry
No full textIn this study, nonlinear damping is introduced as the fourth dimension in the operation of a fiber tip optomechanical anemometer. The flow sensing element, featuring a 3D rotor measuring 110 µm in diameter and fabricated through a two-photon nanomachining process, is monolithically integrated onto the cleaved face of the optical fiber, which serves as an integrated waveguide. As the rotor encounters airflow, it spins, and mirrors on its blades reflect light across the fiber core at each pass. This setup permits precise measurement of gaseous fluid flow with minimal sensor footprint at the point of detection and accommodates a variety of optical sources and measurement apparatuses without the need for specific wavelength or broad-spectrum capabilities. To stabilize the rotation of the rotor and facilitate consistent frequency-domain analysis, a polydimethylsiloxane hydrocarbon stabilizing agent is infused into the gap between the rotor and stator of the sensing element via dual-function microfluidic channels. This enhancement allows for the measurement of gaseous nitrogen flow rates from 10 to 20 liters per minute (LPM), with a consistent periodic response. Comprehensive characterizations of the fiber tip anemometer are presented with and without the stabilizing medium, demonstrating its crucial role in regulating the dynamics between the rotor and the stator
The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity
Get PDFPrecise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification
Reliability analysis of deep space satellites launched 1991–2020: Bulk population and deployable satellite performance analysis
No full textFlight data for deep space satellites launched and operated between 1991 and 2020 is analyzed to generate various reliability metrics. Satellite reliability is first estimated by the Kaplan-Meier estimator, then parameterized through the Weibull distribution. This general process is applied to a general satellite data set that included all deep space satellites launched between 1991 and 2020, as well as two data subsets. One subset focuses on deployable satellites, while the other introduces a methodology of normalizing satellite lifetimes by satellite design life. Results from the general data set prove deep space satellites suffer from infant mortality while the results from the deployable data subset show deployable deep space satellites are only reliable over short periods of time. Results from the design life normalized data set give promising results, with satellites having a relatively high chance of reaching their design life. Available information regarding specific modes of failure is also leveraged to generate a percent contribution to overall satellite failure for eight distinct failure modes. Satellite failure due to crashing, in-space propulsion failure, and telemetry system failure are proven to drive both early in life failure and later in life failure, making them the main causes of decreased reliability
A techno-economic analysis of communication in low-voltage islanded microgrids
No full textExcerpt of abstract: Low-voltage islanded microgrids are an attractive solution for remote electrification due to their flexible and autonomous nature
Self-Referencing MEMS Resonator with Dual Mechanical Modes for Temperature-Independent Environmental Sensing
No full textMicroelectromechanical systems (MEMS) resonators are ideal for low-power, compact, and cost-effective sensing due to their small size and low power consumption. In this study, dual-mode Aluminum Nitride (AlN) transduced MEMS resonators were designed and characterized over a broad temperature range from -200°C to +200 °C. A systematic study was conducted to evaluate the influence of a silicon oxide (SiO2) thin film on the MEMS resonators\u27 quality factors (Q-factors) and temperature coefficient of frequency (TCF). The two adjacent mechanical modes consistently shifted together across the entire temperature range, enabling temperature-independent self-referencing for enhanced environmental sensing. The addition of the oxide film increased the quality factor of the resonators by more than 500%, significantly improving their sensitivity to various environmental phenomena. Abstract © IEEE
The BORIS experience: evaluating omnichannel returns and repurchase intention
Get PDFResearchers have examined the influence of the factors on reducing return rates in retailing over the years. However, the returns experience is often an overlooked way to drive customer engagement and repeat sales in the now ubiquitous omnichannel setting. The focus on returns prevention in existing research overshadows management’s need to understand better the comprehensive mechanics linking the customer in-store return experience with their repurchase actions. Recognizing the need to bridge different stages of the returns management process, this research aims to explore the facilitators and barriers of in-store return activities
Improvements to the Stacked Beacon TARDIS Analysis
No full textImprovements to the Turbulence and Aerosol Research Dynamic Interrogation System (TARDIS) analysis are presented. This includes accounting for square sub-apertures and advanced noise reduction. Low signal-to-noise ratio (SNR) still presents challenges for accurate turbulence profiling
Interference of photons and polarization-based quantum state tomography through emulated atmospheric turbulence
No full textReconstruction of Generic Light Pulses Stored via EIT using the Coherent Atomic Transfer Function
No full textWe use the Fourier-based coherent atomic transfer (CAT) function for EIT storage in a Λ atomic system to reconstruct an arbitrary pulse shape given the retrieved output using numerical deconvolution algorithms
Sun–Venus CR3BP, part 2: resonance investigation and planar periodic orbit family generation
No full textVenus, Earth’s closest neighbor in the Solar System, shares similar characteristics such as size, density, and location within the Sun’s hospitable zone. As a result, it has been proposed as an ideal destination for a range of missions, including Venus and Mercury planetary science, heliophysics observation, space weather monitoring, and Earth planetary defense. The current study examines exterior and interior resonance of discovered periodic orbits, as well as the creation families of Sun–Venus planar periodic orbits in the Sun–Venus system. The circular restricted three-body problem (CR3BP) is used to generate these orbit families via the method of pseudo-arclength continuation. This study identifies 16 exterior and 22 interior resonant periodic orbits from an initial collection of near-Venus and touring periodic orbits generated via a described grid search method. Next, the study produces a selection of 20 families of Sun–Venus periodic orbits with favorable stability properties that will serve to reduce orbit maintenance and station-keeping costs in terms of propellant expenditure, a primary constraint on spacecraft operational lifetime. This study aims to advance multi-body trajectory research and fill a catalog and wider literature hole by providing a preliminary investigation of Sun–Venus CR3BP periodic orbit resonance and orbit families