Digital Commons Network^™

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft play a key role in urban air mobility (UAM), which aims to alleviate traffic congestion in urban areas. Despite their value, eVTOL aircraft suffer from battery energy consumption, which affects their range and endurance in real world flight tasks. Especially, the takeoff process has been identified for excessive power demands. Multidisciplinary analysis and optimization manage to discover optimal takeoff trajectories with minimum energy consumption while balancing multidisciplinary trade-offs, such as short distance takeoff and passengers' comfort. However, conventional parametrization methods (such as B-spline curves) leverage an empirically high-dimensional design space to include real …

A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents the ongoing progress of a vacuum facility upgrade at the Gas and Plasma Dynamics Laboratory (GPDL) at Missouri University of Science and Technology. A movable shroud has been fabricated and installed to enable the simulation of extreme cold conditions. The cooling rate of the shroud, a dummy test article, and a platform, using liquid nitrogen as the thermal fluid, is analyzed and reported under varying vacuum conditions for cryogenic runs. Preliminary testing revealed substantial thermal exchange between the shroud and the chamber walls, underscoring the necessity for implementing effective thermal isolation measures to mitigate heat transfer.

Arc-Jet And Free-Flight Evaluation Of Laminar And Turbulent Diffusion Models On Ablation, Kyle Worden, Andrew Heider, Serhat Hosder

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effect of diffusion models on carbon ablation with a parametric study on a slug-calorimeter geometry in arc-jet flow at two enthalpy conditions using two arc-jet flow modeling approaches, and at corresponding enthalpy-matched free-flight conditions using RANS CFD simulations. Additionally, a sphere-cone geometry is modeled at the arc-jet enthalpy matched free-flight conditions and at a high Reynolds number free-flight condition. The approximate-corrected form of Fick's law and the Stefan-Maxwell diffusion models are investigated for equilibrium and finite-rate carbon ablation in laminar and turbulent flows, which is simulated with the Menter-SST turbulence model. The turbulent cases include the …

Multifidelity Dust Erosion Analysis Of Mars Entry Vehicles, Adam Boland, Dominic Zanti, Serhat Hosder, Andrew Hinkle

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The objective of this paper is to present a multifidelity approach for estimating recession rate and kinetic energy impact rate on the surface of planetary entry vehicles operating in dusty atmospheric environments at hypersonic speeds. The multifidelity model used a co-Kriging approach that combined a low-fidelity correlation with a correction factor from high-fidelity CFD solutions. The developed multifidelity model enables efficient and accurate exploration of a design space to determine at what conditions encountering dust is most dangerous to TPS survivability. Two sample problems are used to demonstrate the effectiveness of the approach: the Mars 2020 lander and a HIAD-type …

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Design problems in aerospace engineering often require numerous evaluations of expensive to-evaluate high-fidelity models, resulting in prohibitive computational costs. One way to address the computational cost is through building surrogates, such as deep neural networks (DNNs). However, DNNs may only be an effective surrogate when sufficient evaluations of the high-fidelity model are required such that the up-front training cost is amortized, or in situations that require real-time responses (such as interactive visualizations). Typically, the data requirements for adequately accurate training of DNNs are often impractical for engineering applications. To alleviate this issue, the proposed work utilizes output dimensionality reduction along …

Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A Ti-Ni-based bi-metallic shape memory alloy was fabricated using directed energy deposition, and the tensile testing behavior at two sections after post-heat treatments were focused. The Ti-rich Ti-Ni-Cu ternary shape memory alloy was first fabricated on a TiNi shape memory alloy with near-equiatomic composition to achieve multi-functional shape memory behaviors using powder-based additive manufacturing. The bi-metallic part then underwent 400°C and 600°C heat treatment at the interfacial area, and the interfacial area was subject to tensile loading and unloading. The digital image correlation technique was applied to extract the tensile stress–strain behavior and map out the local strain evolution of …

Study On Field Emission Characteristics Of Carbon Nanotube Arrays Patterned Via Laser Welding Of Dissimilar Materials, Hung Yin Tsai, Yi Hung Chen, Kuan Ching Wang, Paul W. Leu, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper describes a new method of growing carbon nanotube (CNT) arrays using laser welding of a catalyst metal onto the surface of a quartz substrate, followed by CNT growth through the chemical vapor deposition (CVD) process. A major advantage of this method is its ability to pattern the catalyst before growing the CNTs, thus allowing for the formation of CNTs at specific locations. The laser pre-treatment method minimized structural damage to CNTs in comparison to the laser post-processing method, achieving a lower ID/IG value of 0.72 in Raman spectroscopy analysis. Using hexagonally patterned CNT arrays on quartz, we achieve …

Correction: Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems (American Institute Of Aeronautics And Astronautics Inc, Aiaa), Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Correction Notice • Page 8: "$\lambda_2$: It represents the cardinality-weighted" corrected to "$\lambda_2$: It represents the inverse of cardinality-weighted." Equation $\lambda_2=\sum_{i=1}^{10}(n_i\Xi_i)$ corrected to $\lambda_2=1/(\sum_{i=1}^{10}(n_i \Xi_i))$ • Page 11: Table 1 is updated with new orbital families and number of satellites & 1 & $L_2$ Halo south|$L_1$ Halo north|Butterfly south & 1|2|3\\ & 2 & $L_1$ Halo north|$L_2$ Halo south|Dragonfly south & 5|10|3\\ & 3 & Butterfly south|$L_2$ Halo south|$L_2$ Lyapunov & 3|10|4\\ & 4 & $L_1$ Halo south|$L_2$ Halo north|$L_1$ Halo north & 5|3|1\\ A|B|C & 5 & $L_2$ Halo south|$L_1$ Lyapunov|$L_2$ Halo north & 2|8|9\\ & 6 & $L_3$ …

Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems, Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The number of cislunar resident space objects is expected to proliferate rapidly because of strategic interests targeting long-term presence on the Moon and exploration of other planets (e.g., Artemis Accords) and liberalization of space through the entry of private space players (e.g., Intuitive Machines). It necessitates expanding current near-Earth space domain awareness (SDA) operation systems and knowledge to the relatively unexplored cislunar region. Besides the traditional complexities, xGEO orbits (orbits beyond the geosynchronous Earth orbit (GEO) region) face additional challenges because of highly non-linear and non-Keplerian dynamics, which results in inaccuracies in uncertainty propagation and state estimation. Further challenges include …

Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Industry 4.0 has created a growing need for effective human-robot collaboration (HRC). As robots and humans work more closely together, efficient communication becomes essential for coordinating their actions seamlessly. While speech may seem like the obvious choice for communication, noisy factory environments can render it impractical. Additionally, workers often have their hands occupied with assembly tasks, making hand-controlled interfaces less practical for controlling robots. To address these challenges, this paper presents a novel, hands-free method for robot control using electrooculography (EOG) signals–specifically, eye movements and blinks–with unmanned aerial vehicles (UAVs) used as the demonstration platform. We developed a real-time system …

High-Order Dynamic Mode Decomposition For Multidimensional Harmonic Retrieval, Yanming Zhang, Steven Gao, Lijun Jiang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Estimating channel parameters such as azimuth, elevation, Doppler shift, and delay is a key challenge in wireless communication, often formulated as a multidimensional harmonic retrieval (MHR) problem. To address this, we propose a high-order dynamic mode decomposition (HODMD) framework for robust frequency estimation from high-dimensional signals in noisy environments. The HODMD approach combines high-order singular value decomposition (HOSVD) to decompose tensor data into a core tensor and mode matrices, with dynamic mode decomposition (DMD) to extract frequencies from the imaginary parts of the DMD eigenvalues. Simulation examples validate the effectiveness of the proposed method, demonstrating its efficiency in solving MHR …

Characterizing Intralaminar Distal Crack And Delamination In Multidirectional Laminates Under Low Velocity Impact: Modeling Approach With Ultrasound Testing Validation, Niildiip Chandraa, Rachel Van Lear, Arief Yudhanto, Yuqing Zhao, David A. Jack, Douglas E. Smith

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multidirectional laminated composites are essential for load-bearing structures, especially under frequent impact loading. While existing modeling techniques simulate various impact damage modes, our understanding of the underlying mechanisms, specifically the initiation and progression of intralaminar distal cracks and interlaminar delamination, needs improvement. Validating these mechanisms is crucial for enhancing modeling accuracy and expediting the design process. In this work, we propose a three-dimensional finite element modeling (3D FEM) approach aimed at elucidating the impact damage mechanisms in multidirectional carbon fiber reinforced polymer (CFRP). Our model incorporates cohesive zone models (CZM) to simulate the behavior of intralaminar cracks at distal points …

Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortex beams with helical phase fronts have immense potential to enhance data capacity due to the unbounded values of orbital angular momentum. Chip-scale platforms for producing vortex beams are of paramount importance for a variety of applications. On the other hand, 2D materials with unique optical properties are essential for developing multifunctional ultrathin photonic devices. Here, anisotropic and temperature-tunable second-harmonic vortex beam generation is demonstrated with ultrathin ferroelectric niobium oxide dichloride (NbOCl₂) fork holograms. The polarization-resolved Raman measurements are performed on the NbOCl₂ crystal to understand the anisotropic behavior of the Raman modes. It is demonstrated …

Performance Evaluation And Multiphysics Process Modeling Of Carbon Fiber Reinforced Thermoset Composites Using Microwave And Autoclave, Nayan Pundhir, Patrick Schwartzkopf, K. Chandrashekhara, Logan Wilcox, Kristen M. Donnell, Jim Lua, Rui Li

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, IM7/Cycom 5320-1 unidirectional prepreg has been utilized to manufacture 16-layer laminated composites: a symmetric cross-ply ([0°/90°]4s) and a quasi-isotropic ([45°/90°/−45°/0°]2s) configuration. Microwave and autoclave curing processes have been employed to manufacture the laminated composites. The manufactured composite cure was assessed using differential scanning calorimetry (DSC). The quality and porosity of the microwave-cured parts were juxtaposed to those of autoclave-cured parts through optical microscopy and micro-computed tomography (micro-CT) scanning. Mechanical characterization of the microwave-cured panels was conducted using uniaxial tensile and flexural tests, with results juxtaposed to autoclave-cured samples. Experimental characterization revealed that the microwave-cured parts exhibited nearly …

Design And Testing Of An Intrusive Arm For Supersonic Flow Sampling, Caleb Roberts, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Intrusive probes are critical tools in supersonic wind tunnel testing, enabling direct measurement of flow properties such as pressure and heat flux. To support these measurements, a single-axis intrusive arm was designed and implemented in the Missouri S&T Supersonic Wind Tunnel. The system is designed to maintains precise probe positioning, while withstanding the aerodynamic loads, and preserving a dynamic seal between the test section and ambient environment. Its modular design accommodates a range of probe types for various research applications. This paper presents the design methodology, including structural, mechanical, and aerodynamic considerations, and details the integration process. System performance was …

Physics-Constrained Generative Artificial Intelligence For Rapid Takeoff Trajectory Design, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The urban air mobility (UAM) industry is rapidly growing to alleviate regional transportation congestion. Electric vertical takeoff and landing (eVTOL) aircraft plays a critical role in this growth due to their efficiency and reduced operating cost. However, excessive energy demands by the takeoff phase impact the practicality of the aircraft. Conventional multidisciplinary analysis and optimization (MDAO) identifies a minimum energy trajectory but can be computationally intensive due to iteratively evaluating high-fidelity simulation models. In addition, complex constraints in practical MDAO pose crucial challenges to the already demanding process. Surrogate models enable efficient design optimization, but complex constraints could prohibit surrogate-based …

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus³ Vahana …

Industry 5.0, Human–Machine Interface, And Smart Manufacturing In Additive Manufacturing—A Recent Trend, Atiqur Rahman, Md Hazrat Ali, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The emergence and importance of Industry 5.0 are transforming production by integrating smart technology with human creativity and intelligence, especially in advanced additive manufacturing. This critical review precisely analyzes the function of human–machine interfaces (HMIs) in enhancing additive processes, emphasizing their incorporation into smart manufacturing systems and hybrid manufacturing methods, including material extrusion (MEX), laser powder bed fusion (LPBF), and directed energy deposition (DED). It also evaluates artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, which enhance HMIs in process monitoring, operation, and system adaptability. This study aims to provide a critical analysis and future research direction on …

Optimizing Uav Swarm Deployment For Efficient Communication Signal Strength Alignment In Disaster Scenarios, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In disaster scenarios, establishing reliable communication infrastructure is critical, and unmanned aerial vehicle (UAV) swarms offer a promising solution as temporary base stations. This study models communication demand in disaster-affected areas by applying Gaussian kernels to building data, forming a spatial demand distribution. Signal strength is estimated using the normalized inverse Free Space Path Loss (FSPL) to account for realistic attenuation. To guide UAV placement, we extract high-demand regions from the demand distribution using a gradient-based thresholding method. Based on this information, we develop a greedy algorithm to iteratively position UAVs for optimal coverage in areas with the greatest communication …

Few-Shot Learning-Enhanced Tiered Path Planning For Mars Rover Navigation, Ziyi Wang, Di Yu, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Path planning for Mars rovers presents significant challenges due to the diverse terrain, ranging from easily navigable areas to hazardous zones. Traditional methods typically classify terrain simply as passable or impassable, failing to account for the nuances of more moderately challenging areas. In this paper, we introduce a tiered terrain-aware path planning strategy, employing few-shot learning to classify and segment Martian terrain into levels of difficulty. The few-shot learning model, trained on Earth, is sent to the rover, enabling real-time processing of images from satellites or helicopters. The flexibility of few-shot learning, which requires minimal data and training time, enables …

Machine Learning Approach For Defect Prediction In Metal 3d Printing For Aerospace Applications, Yerlik Gabdulla, Md Hazrat Ali, Frank Liou, Essam Shehab

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Additive manufacturing (AM) has revolutionized the aerospace industry by enabling the production of lightweight and high-strength components, such as aerospace engine components and structural elements. The ability to create complex geometries and reduce material waste is particularly beneficial for aerospace applications, where performance and weight reduction are paramount. However, ensuring the quality and reliability of these components remains a challenge, particularly in mass production, which is related to material quality, expensive processes, and longer computational times than conventional manufacturing methods. This paper proposes an approach utilizing a Decision Tree Classification Machine Learning Algorithm to predict the possibility of defect occurrence …

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Investigation Of Arm Stiffness Modulation During Overground Physical Human-Human Interaction, Henry Tien

Masters Theses

The vision of advancing robots capable of direct physical engagement with humans begins with an understanding of how humans interact with each other. Even rudimentary interactive tasks, such as shaking hands, provides tremendous challenges for modern robotics and current research into the biomechanics of such interactions is limited. Thus, further analysis of physical Human-Human Interaction (pHHI) will bolster efforts to enhance collaborative robot capabilities. To this end, a custom Force Perturbation Handle (FPH) was developed, including the requisite mechanical, electrical, and software systems, to investigate the unique role of arm stiffness modulation in haptic communication between humans. The novel device …

Extraction And Separation Of Metal Cations From Synthetic Acidic Solutions Using Emulsion Liquid Membrane, Nouhaila Filali

Masters Theses

The work is organized into two main papers supported by experimental and comparative studies using Emulsion Liquid Membrane (ELM) systems. The first paper explores the individual extraction of heavy metals (Cd, Cr, As, Ni) from synthetic phosphoric acid using Alamine 336 and D2EHPA as carriers. Alamine 336 achieved the highest extraction efficiency (>90%) and stability, offering a promising route to reduce toxic impurities in fertilizer-grade acid. The second paper examines the selective separation of Ni2+ and Co2+ from various acidic solutions using the ELM configuration. Systematic variation of carriers, stripping agent and feed acidity, clarified transport mechanisms and stability, …

Empirical Study Of Far-Field Radio Frequency Wireless Power Transfer Testbed For Underground Mines Based On 1.8 Ghz, Anabi Hilary Kelechi, Samuel Frimpong

Mining Engineering Faculty Research & Creative Works

A novel 1.8 GHz far-field wireless power transfer (WPT) testbed was designed to achieve long-distance energy harvesting in underground mine (UM). Prior experimental studies confirm that underground mines experience 50 dB radio frequency (RF) signal attenuation compared to a typical wireless environment. Due to this severe signal attenuation, the currently proposed radio frequency energy harvesting (RF-EH) testbed cannot be deployed in underground mines. In this study, we proposed, designed and performed an empirical study with a military-grade class A radio frequency wireless power transfer (RF-WPT) testbed. The various digital modulation schemes experimented with included: BPSK, DBPSK, QPSK, OQPSK, Pi4DQPSK, 8PSK, …

Exploring The Link Between Hy Wet Ball Mill Work Index And Grinding Energy Consumption, Chen Peng, Hou Ying, Lv Hongxu, Sobhy Ahmed

Mining Engineering Faculty Research & Creative Works

In evaluating ore grinding energy consumption using the Bond ball mill work index, discrepancies were identified. As a result, an investigation into the determination method of Hou Ying (HY) wet ball milling work index (WHY) for Gongchangling magnetite ore was conducted to determine the correlation between WHY and grinding energy consumption at varying particle sizes. The research results indicated that WHY had an error less than 3.33%, which is closely aligned with on-site grinding energy consumption. This surpassed the numerical error of 15.9% in the Bond ball grinding power index and demonstrated superior accuracy in representing ore grinding energy consumption, …

Enhancing Safety In U.S. Coal Mines Through A Rib Support Recommendation Tool, Alper Kirmaci, Dakshith Ruvin Wijesinghe, Dogukan Guner, Kutay E. Karadeniz, Cameron Mitchell, Taghi Sherizadeh

Mining Engineering Faculty Research & Creative Works

Despite ongoing efforts to enhance coal rib stability, the underground coal mining sector continues to face incidents of rib failure, leading to injuries and fatalities. The development and validation of effective rib support systems are crucial for mitigating these risks. Unfortunately, a standardized design methodology that accommodates the diverse geological conditions of U.S. coal mines is missing. Current practices are often based on trial-and-error or outdated methods, yielding unreliable outcomes. This research aims to fill this gap by creating a comprehensive methodology for designing rib support systems suitable for U.S. underground mines. It encompasses in situ pull-out tests of coal …

Application Of Gurney And Flight Of Fragment Calculations For Water Jet Velocities In Explosive Applications, Rachel L. Bauer, Tate B. Friedrich, Catherine E. Johnson

Mining Engineering Faculty Research & Creative Works

This study investigates the application of Gurney and flight of fragment equations, typically used to predict metal fragment velocities, in modeling the water jet behavior. Three shotgun cartridge sizes were used as the energy source: 2.59 g, 5.83 g, and 7.13 g. Two configurations were tested: standard (full-barrel water load) and "negative 8" (partial water load). High-speed footage captured water column velocities, and Gurney models, including infinitely tamped and open-faced configurations, combined with the flight of fragment model were used to assess prediction accuracy. Results showed charge strength significantly affects water column velocity, with higher strengths yielding greater stability and …