Missouri University of Science and Technology
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Modeling and Characterizing the Electron Backscatter in a Cylindrical Anode-Based Distributed X-ray Source
No full textUpcoming advancements in computed tomography architectures warrants the investigation of new X-ray source designs and the impacts that electron backscatter can have on these designs. One such design being investigated is a distributed, cylindrical anode-based X-ray source. For such a distributed X-ray source, we developed a modeling pipeline for simulating electron optics and transport to characterize the quality of the primary X-ray beam and the electron backscatter behavior. We report our results on the energy distributions of the bremsstrahlung spectra; electron backscatter ratio; and spatial, temporal, and energy distributions of backscattered electrons that return to the anode
A Combined Tomographic Particle Image Velocimetry and Numerical Simulation Approach for Supersonic Wind Tunnel Calibration
No full textSupersonic wind tunnels remain essential tools for high-speed aerodynamics research, yet the characterization of their free-stream conditions remains technically challenging and lacks standardized criteria for defining good flow quality. While traditional calibration methods rely on intrusive probes, recent advances in optical diagnostics offer new opportunities for non-intrusive characterization. In this work, we demonstrate a novel use of Tomographic Particle Image Velocimetry (Tomo-PIV), combined with numerical simulations, as a methodology for supersonic wind tunnel calibration. The approach is applied to the recently upgraded Missouri S&T Supersonic Wind Tunnel, where Tomo-PIV measurements reveal uniform flow with low angularity and low turbulent noise under three operating conditions. Results are corroborated by pitot probe data and CFD analysis, with agreement within 2 % across methods. These findings establish Tomo-PIV as a viable and generalizable diagnostic for the calibration of supersonic wind tunnels
RESCUE: Routing under Evolving Stochastic Congestion and Uncertain Spread in Wildfire Emergencies
No full textWildfires cause unpredictable spread and panic-driven congestion, posing severe challenges to evacuation planning. We present RESCUE (Routing under Evolving Stochastic Congestion and Uncertain Spread in Wildfire Emergencies), a dynamic, risk-aware framework that models the road network as a time-varying weighted graph. RESCUE operates in two stages: (i) a preprocessing phase integrating fire forecasts, traffic density, and distance to assign edge weights, and (ii) a real-time routing phase that adaptively updates paths using a multi-granular strategy distinguishing macro-level disruptions (e.g., rapid spread) from micro-level changes (e.g., local congestion). Two stochastic edge-cost functions are introduced: the Edge-Fire Risk Function (EFRF), estimating road inaccessibility from the fire\u27s rate-of-spread, and a Beta cumulative distribution modeling evacuee speed under stress, combined with the Bureau of Public Roads (BPR) model for delay estimation. Formulated as a multi-objective shortest-path problem, on real-world networks, RESCUE reduces travel distance, fire risk, and congestion delay by, and over A∗-based routing. Compared to D∗, it achieves, and reductions in these metrics
Digital Twin Freshness Maximization in Edge Computing
No full textMobile Edge Computing (MEC) shifts powerful computing resource provisioning from remote powerful data centers to the edge of core networks. Meanwhile, Digital Twin (DT) has surfaced as a promising technology to provide comprehensive and dynamic descriptions of physical objects in cyberspace with bidirectional and real-time interactions. Moreover, Internet of Things (IoT) devices have contributed abundant, heterogeneous and continuous data from interconnected devices to the explosion of DTs. With technologies evolution, there is an increasing necessity to address the freshness of both DT states and DT data, through timely synchronizations between DTs and their objects in a highly dynamic IoT environment. In this paper, we develop innovative methodologies to improve the DT freshness while minimizing the cost of various resources consumed on the DT freshness improvement. Specifically, we first formulate two novel optimization problems of DT freshness: (i) The static DT freshness optimization problem, where all DT synchronization tasks are given in advance; and (ii) the dynamic DT freshness optimization problem without any knowledge of future DT synchronization tasks over a given finite time. We then devise an approximation algorithm with a provable approximation ratio for the static DT freshness optimization problem. Also, we develop an online algorithm with a provable competitive ratio for the dynamic DT freshness optimization problem. Finally, we evaluate the performance of the proposed algorithms through simulations. Simulation results show that the proposed algorithms outperform their comparison baselines by no less than 13.2%
Ultrasonic Extraction-Based Analysis of Persistent Organic Pollutants in Blubber from False Killer Whales
No full textIn view of the toxic effects of persistent organic pollutants (POPs), fast and effective assessment of their concentrations in marine mammals is important for understanding individual and population-level health impacts. This study developed an ultrasonic-based method that is less time-consuming, uses minimal solvent, and thus is more sustainable than the gold standard Soxhlet method for accurate analysis of organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and benzene hexachlorides (BHC) in false killer whale blubber. This method was developed by comparing concentrations of POPs obtained using the traditional Soxhlet and novel ultrasonic extraction methods using blubber from false killer whales (n = 4) that were stranded in the Hawaiian Islands. The average total POPs extracted from the four killer whales and adjusted for lipid weight (lw) were 11,379.57 ± 3,303.03 ng/g lw for Soxhlet extraction and 14,310.39 ± 4,469.00 ng/g lw for the ultrasonic method, indicating a greater extraction efficiency of the ultrasonic method. The results further revealed that false killer whale FKW2013018 (∑OCs 15,447.38 ± 812.17 ng/g lw and ∑PCBs 5,205.32 ± 253.46 ng/g lw) and false killer whale FKW2016016 (∑OCs 18,164.90 ± 1,433.15 ng/g lw and ∑PCBs 4,913.32 ± 447.29 ng/g lw) accumulated organochlorines and PCBs at very high and potentially toxic levels. The low ratio of 4,4′-DDT/4,4′-DDE (0.026 ± 0.004) using both extraction methods indicated that the stranded false killer whales experienced long-term exposure to 4,4′-DDT, leading to bioaccumulation of the stable 4,4′-DDE metabolite. The levels of OCs, PCBs, and BHCs in this study were below toxic threshold levels. However, in view of the susceptibility of cetaceans with reduced lipid content to the toxic effects of POPs, cetaceans with low lipid content (as a result of starvation, fasting, or extended migration events) may be at higher risk of the negative health impacts of organic pollutants
Additive Manufacturing of Ti-Ni based Ternary Shape Memory Alloys
No full textMetal additive manufacturing has become a powerful tool to develop customized metal alloys and to discover more advanced properties for novel extended applications. Ti-Ni based shape memory alloy is a group of intriguing smart functional materials, and adding a small amount of a third element can promote and induce more attractive functions. Due to the difficulty in traditional processing and the unique feature of material flexibility of in-situ alloying in additive manufacturing processes, not only Ti-Ni binary shape memory alloys but also Ti-Ni-X ternary shape memory alloys can be developed, manufactured, and investigated in-depth by additive manufacturing. This paper provides a brief review of the development of Ti-Ni based ternary shape memory alloys using metal additive manufacturing. The research status regarding a variety of Ti-Ni-X ternary alloys was summarized based on the classification of the two most widely used metal additive manufacturing processes: directed energy deposition and powder bed fusion. The main manufacturing issues were discussed and suggested, and the recommended research directions were made for future development
Long Range Battery-free Wireless Power Transfer Testbed for Underground Mines IoT and LPWAN Devices
No full textUnderground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, considerably reducing the adverse effects of the high signal attenuation power loss of about 50 dB. With the aid of a commercially available off-the-shelf (COTS) TPS61030 boost converter, a 2.5 V/25F supercapacitor was boosted to provide the energy needed to the Heltec ESP32 system-on-chip (SoC) microcontroller unit (MCU). The Heltec ESP32 integrates various components, including a dual-core CPU, LoRa, Wi-Fi, and Bluetooth radio connectivity modules. Thus, realizing far-field, IoT, and LPWAN battery-free technology in underground mines environment. This novel research exploited the concept of utilizing supercapacitors for the storage of harvested energy. To the best of our knowledge, this is the first long-range far-field WPT testbed specifically designed for underground mines facilities at 880 MHz band. In this study, we also investigated the impact of using various modulation schemes. The schemes evaluated were of amplitude modulation (AM), frequency modulation (FM), and pulse width modulation (PWM). Empirical results indicate that the most suitable scheme for RF-WPT in the underground mine is FM. In addition, we performed extensive analysis to understand the energy and current consumption profiles of the Heltec ESP32 LoRa, WiFi, and BLE transceiver using Power Profiler Kit II under different configurations and scenarios. The experimental results indicate that the WiFi connectivity is not energy efficient compared to the BLE transceiver
A Comprehensive Dataset for Underground Miner Detection in Diverse Scenario
No full textUnderground mining operations face significant safety challenges that make emergency response capabilities crucial. While robots have shown promise in assisting with search and rescue operations, their effectiveness depends on reliable miner detection capabilities. Deep learning algorithms offer potential solutions for automated miner detection, but require comprehensive training datasets, which are currently lacking for underground mining environments. This paper presents a novel thermal imaging dataset specifically designed to enable the development and validation of miner detection systems for potential emergency applications. We systematically captured thermal imagery of various mining activities and scenarios to create a robust foundation for detection algorithms. To establish baseline performance metrics, we evaluated several state-of-the-art object detection algorithms including YOLOv8, YOLOv10, YOLO11, and RT-DETR on our dataset. While not exhaustive of all possible emergency situations, this dataset serves as a crucial first step toward developing reliable thermal-based miner detection systems that could eventually be deployed in real emergency scenarios. This work demonstrates the feasibility of using thermal imaging for miner detection and establishes a foundation for future research in this critical safety application
High-resolution, Fast-response Optical Fiber Temperature Sensor with a Large Measurement Range based on Fiber-tip Alumina Fabry-Pérot Interferometer
No full textWe present an alumina-tip optical fiber Fabry-Pérot interferometric temperature sensor exhibiting high-temperature performance, rapid response, and high resolution. Fabricated by fusion splicing an alumina microdisk directly to a single-mode fiber, the sensor achieves robust, stable operation without complex fabrication processes or adhesives. Experimental evaluation confirms a measurement range extending to 1000°C, with sensitivity of 28.66 pm/°C, a resolution of 0.042°C, and a rapid response time of approximately 13 ms. Compared to state-of-the-art optical fiber FPI sensors, our alumina-tip sensor offers superior overall performance, effectively addressing critical demands for high-resolution, fast-response temperature measurement in extreme environments including aerospace, structural monitoring, metallurgy, and emerging flash-based thermal processing technologies
Evaluation of Two-group IATE Coupling with PBE for Beyond Bubbly Flows in a Large Diameter Pipe
No full textThis study evaluates the two-group interfacial area transport equation (2G IATE) coupled with the S-Gamma (Sγ) population balance equation (PBE) model for beyond bubbly flow regimes in a vertical large-diameter pipe. The 2G IATE framework incorporates intergroup mass transfer mechanisms and is implemented within the Sγ model, which assumes a log-normal bubble size distribution. The numerical approach is validated against experimental data from Schlegel et al. (2012), with a focus on the void fraction and interfacial area concentration (IAC) distributions. The results show that 2G IATE improves the predictions of the void fraction and IAC, although its accuracy varies with flow conditions. Dominant transport mechanisms, such as bubble interaction (IM), IAC from mass transfer between group-1 and group-2 bubbles (MT), and volume expansion (VE), are analyzed, revealing that the IM is the primary contributor to IAC variations, whereas MT effects become more significant at higher gas velocities. These findings contribute to the advancement of multiphase flow modeling, with potential applications in nuclear reactor safety, chemical processing, and CFD-based two-phase flow simulations