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Missouri University of Science and Technology

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Articles 1 - 30 of 2216

Full-Text Articles in Mechanical Engineering

Optimizing Ball‐Milled Composites For Fast Energy Release Under Shock Compression, Siva Valluri, Edward Dreizin, Dana Dlott Aug 2026

Optimizing Ball‐Milled Composites For Fast Energy Release Under Shock Compression, Siva Valluri, Edward Dreizin, Dana Dlott

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Microparticle additives containing both Al fuel and oxidizer, fabricated by arrested reactive milling (ARM), could potentially increase the power of energetic materials such as HMX because they contain premixed fuel and oxidizer. Optimizing shock reactivity requires exploring a vast parametric space encompassing composition, milling parameters that govern microstructural features such as intraparticle voids and fuel-oxidizer mixing, and the resulting inhomogeneous shock reactivity of individual particles. To present our approach, we used a model composition 8Al⋅3CuO, previously optimized for combustion. We milled powders and prescreened different prepared batches using differential scanning calorimetry (DSC) to rule out batches with significant pre-reaction. Then …

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Percolation-Induced Thermo-Rheological Transitions In Biobased Graphene Nanoplatelet Nanofluids, Abiodun A. Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo Aug 2026

Percolation-Induced Thermo-Rheological Transitions In Biobased Graphene Nanoplatelet Nanofluids, Abiodun A. Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Biobased lubricants with thermally responsive rheology are increasingly needed for high-efficiency mechanical systems. Graphene nanoplatelet (GnP) nanofluids in vegetable oils are promising candidates, yet their percolation-driven thermo-rheological transitions remain insufficiently understood. In particular, the coupled concentration–temperature landscape controlling network-mediated flow transitions has not previously been established. Here, surfactant-free GnP nanofluids were prepared in high-oleic soybean oil (HOSO) at concentrations of 0.025–2.15% v/v (ϕ), and their rheological response was mapped between 25°C and 80 °C under steady-shear and oscillatory conditions. Below the percolation threshold (ɸ ≤ 0.1% v/v), the nanofluids exhibit near-Newtonian behavior, moderate reversible viscosity enhancement, and classical Arrhenius-type temperature …

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Magnetic Field-Induced Transformation In Polycrystalline Ni2mnal Heusler Type Magnetic Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely, Laura N. Bartlett Jul 2026

Magnetic Field-Induced Transformation In Polycrystalline Ni2mnal Heusler Type Magnetic Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely, Laura N. Bartlett

Materials Science and Engineering Faculty Research & Creative Works

The martensitic and magnetic transformations, as well as the mechanical properties, of Ni₂MnAl alloys in as-cast (AC) and heat-treated (HT) conditions were investigated. Magnetic-field-induced strain was evaluated via magnetostriction, with reversible strains of 0.14% and 0.2% achieved in the martensitic phase at 2 K for the AC and HT alloys, respectively. Transformation temperatures and Curie temperatures were determined under constant applied magnetic field, revealing that γ-phase inclusions in the AC microstructure suppress antiferromagnetic domain response, yielding a lower magnetization (∼8.4 emu g⁻¹) compared to the HT alloy (∼13.4 emu g⁻¹). Both alloys exhibited hysteretic behavior in the martensitic state and …

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Tracking Continuous Non-Differentiable Trajectories In Euler–Lagrange Systems With Continuous Dynamics, Nilay Kant Jun 2026

Tracking Continuous Non-Differentiable Trajectories In Euler–Lagrange Systems With Continuous Dynamics, Nilay Kant

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Tracking controllers for Euler–Lagrange systems are designed under the assumption that reference trajectories are continuous, and at least twice differentiable with respect to time. However, this assumption precludes several use cases, such as when a robot end-effector must track a path with corners at constant speed. This paper introduces the control design for tracking continuous but non-differentiable trajectories in fully actuated Euler–Lagrange systems that have continuous-time dynamics. The proposed controller combines a continuous feedback law with impulsive inputs, that are intermittently applied at the instants of non-differentiability. A Lyapunov stability analysis establishes global exponential convergence of the tracking error to …

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A Carbon Fiber-Based Self-Sensing Approach For Monitoring Damage Evolution In Coal Pillars, Shan Ning, Weibing Zhu, Jie Gao, Wei Qin, Guang Xu, Jingmin Xu Jun 2026

A Carbon Fiber-Based Self-Sensing Approach For Monitoring Damage Evolution In Coal Pillars, Shan Ning, Weibing Zhu, Jie Gao, Wei Qin, Guang Xu, Jingmin Xu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Under long-term high stress and dynamic disturbances, damage accumulation within underground coal masses can induce sudden instability, posing a considerable threat to coal mine safety. Real-time acquisition of coal damage information is essential for disaster prevention and control. This study proposes a coal damage and fracturing monitoring approach based on a carbon fiber composite mortar (CFCM) coating. By applying the CFCM coating to coal specimen surfaces and monitoring resistance changes, the dynamic evolution of damage can be tracked. The study combines experimental mechanical loading, continuous electrical resistance monitoring and acoustic emission recording with detailed numerical modelling to comprehensively evaluate sensing …

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Evaluation Of The Effect Of Vibration On Signal Reflection In Coaxial Cable Connectors For Vibration Sensing In Aircraft Structures And Systems, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Daniel S. Stutts, Jie Huang Jun 2026

Evaluation Of The Effect Of Vibration On Signal Reflection In Coaxial Cable Connectors For Vibration Sensing In Aircraft Structures And Systems, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Daniel S. Stutts, Jie Huang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effects of vibration on signal reflection (S11) in aerospace data transmission line (ADTL) and commercial data transmission line (DTL) connectors for their alternative use as vibration sensors. The impact of vibration on the S11 signal was investigated on five ADTL and four DTL connectors at six vibration frequencies (20 Hz, 40 Hz, 80 Hz, 160 Hz, 320 Hz, and 640 Hz) and four vibration accelerations (0.5G, 1 G, 2 G, and 4G). The experiment was conducted using a split-plot design with a cable type assigned as the main-plot factor, with vibration frequency and acceleration as subplot …

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Liquid-Phase Chemical Melting Deposition For Anchored Nanoparticle–Nanofiber Architectures, Hiep Pham, Kiernan O'Boyle, Gracie Boyer, Jonghyun Park May 2026

Liquid-Phase Chemical Melting Deposition For Anchored Nanoparticle–Nanofiber Architectures, Hiep Pham, Kiernan O'Boyle, Gracie Boyer, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We report chemical melting deposition (CMD), a manufacturing strategy designed to overcome the low mass loading and weak interfacial bonding inherent to vapor-based synthesis. Unlike conventional vapor routes, CMD leverages a transient liquid-phase transfer (TLPT) mechanism driven by the differential thermal degradation of carrier fibers to transfer and anchor nanoparticles directly onto target fibers. This process thermodynamically drives the wetting and interfacial fusion of nanoparticles, establishing a liquid-phase contact pathway that enables markedly higher active material loading. To validate the structural resilience of this fused architecture against extreme volumetric stress, we utilized lead oxide (PbO) as a model system, which …

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Effect Of Environmental Conditions On Fracture Of Composite Materials And Thin Films, Victor Birman May 2026

Effect Of Environmental Conditions On Fracture Of Composite Materials And Thin Films, Victor Birman

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Environmental conditions, i.e., temperature and moisture, affect mechanical properties of materials, including composites. In this paper, we concentrate on one of the aspects of the effect of environment on fracture in a composite lamina. The paper demonstrates an analytical approach to account for the effect of the changes in environment on the strain energy release rate of composite materials and thin films. These analytically determined strain energy release rates should be compared to fracture toughness to predict the susceptibility of the material to fracture. Numerical examples are presented for several polymeric and metal matrix composites using available experimental data for …

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Validity Of The Schrage Equation In Prediction Of Evaporation Rate Of Liquid N-Dodecane In High-Pressure Nitrogen Gas: A Molecular Dynamics Study, Wazih Tausif, Jordan Hartfield, Md Amin Haque, Zhi Liang May 2026

Validity Of The Schrage Equation In Prediction Of Evaporation Rate Of Liquid N-Dodecane In High-Pressure Nitrogen Gas: A Molecular Dynamics Study, Wazih Tausif, Jordan Hartfield, Md Amin Haque, Zhi Liang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Evaporation of liquid fuel in a high-pressure air is a process that critically influences fuel–air mixing in advanced propulsion systems. In this work, we use molecular dynamics (MD) simulations to study the validity and accuracy of the Schrage equation in quantifying the evaporation and condensation rates of n-dodecane (a diesel surrogate) in air (approximated as N2 gas) with gas pressure varying from 0 atm to above the critical pressure of n-dodecane. The MD simulation results show that the evaporation coefficient (αe) is higher than the condensation coefficient (αc) at the evaporating n-dodecane surface and is lower than αc at the …

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A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou May 2026

A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Featured Application: The proposed federated learning framework can be applied in distributed smart manufacturing environments where multiple factories or production facilities collaboratively develop predictive maintenance models without sharing sensitive operational data. This approach is particularly useful for industrial networks involving geographically distributed plants, contract manufacturing partners, and multi-site production systems where data sovereignty and avoidance of raw data sharing are critical. Predictive maintenance enables early detection of machine failures and reduces unexpected production downtime. However, conventional approaches typically rely on centralized data collection and model training which introduce challenges related to data sovereignty, communication overhead and data ownership. To address …

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Machine Vision For In Situ Measurement And Control Of Wire Stickout In Lwded Process, Braden Mclain, Remy Mathenia, Todd Sparks, Frank Liou May 2026

Machine Vision For In Situ Measurement And Control Of Wire Stickout In Lwded Process, Braden Mclain, Remy Mathenia, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents a machine-vision–based measurement and control framework for laser wire directed energy deposition (LWDED) processes. A visible-light camera system is used to capture meltpool images, from which a novel vision algorithm extracts the wire–meltpool interface location. By utilizing a camera that is rigidly mounted to the deposition head, the vision algorithm provides a relative measurement of the distance between the nozzle tip and the workpiece, also referred to as wire stickout. A proportional-derivative (PD) control strategy is implemented using the measured stickout as feedback to adjust deposition feedrate. Results show that the control system successfully compensates for improper …

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Using Machine-Learning-Based Process Map To Guide Evaluation Of Inconel 625 Mechanical Properties In Laser Foil Printing, Yu Hsiang Wang, Sung Heng Wu, Hung Chu Chiang, Pen Ning Yu, Chia Hung Hung, Ming C. Leu May 2026

Using Machine-Learning-Based Process Map To Guide Evaluation Of Inconel 625 Mechanical Properties In Laser Foil Printing, Yu Hsiang Wang, Sung Heng Wu, Hung Chu Chiang, Pen Ning Yu, Chia Hung Hung, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Inconel 625 is widely studied in powder-based additive manufacturing, but its processing characteristics and mechanical performance in foil-feedstock laser foil printing (LFP) remain largely unexplored. In this study, a gradient boosting regression (GBR)-based process map was developed for LFP of Inconel 625 using 32 single-track experiments. The GBR model achieved R2 values of 0.859 and 0.793 and mean absolute errors of 22.25 μm and 19.83 μm for melt-pool depth and width, respectively, outperforming second- and third-order polynomial regressions in capturing nonlinear melt-pool responses and distinguishing lack-of-fusion, conduction, and keyhole regimes. Three conduction-mode conditions with target depth-to-foil thickness ratios (D/T) …

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Quantitative Phase-Field Modeling Of Nonequilibrium Microstructural Evolution In Rapid Solidification For Additive Manufacturing, Leiji Li, Fei Xiao, Ying Zhou, Xiaorong Cai, Chongfeng Zhang, Jinzhong Gao, Xiaopeng Shen, Tianchi Zhu, Sihan Wang, Yijia Gu, Xuejun Jin Apr 2026

Quantitative Phase-Field Modeling Of Nonequilibrium Microstructural Evolution In Rapid Solidification For Additive Manufacturing, Leiji Li, Fei Xiao, Ying Zhou, Xiaorong Cai, Chongfeng Zhang, Jinzhong Gao, Xiaopeng Shen, Tianchi Zhu, Sihan Wang, Yijia Gu, Xuejun Jin

Materials Science and Engineering Faculty Research & Creative Works

Fusion-based metal additive manufacturing (AM) relies on layer-by-layer deposition and rapid solidification, where the material transitions swiftly from liquid to solid. A key phenomenon during this process is solute trapping, a nonequilibrium effect governed by a velocity-dependent partition coefficient, which critically influences microstructure kinetics, morphology, and phase formation. In this study, we employ a recently proposed quantitative phase field (PF) model to systematically explore solute trapping, solute drag, and their impacts on pattern formation during rapid solidification at AM-relevant velocities, in both one and two dimensions. Our simulations reveal a growth mode transition from planar to cellular to dendritic, and …

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Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin Apr 2026

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

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Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh Apr 2026

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

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Ballistic Trajectories From Triangular Libration Points To Moon, Collin Gentry Apr 2026

Ballistic Trajectories From Triangular Libration Points To Moon, Collin Gentry

Miners Solving for Tomorrow Research Conference

As stable points in the Earth-Moon system, the triangular libration points, L4 and L5, have many advantageous properties for space exploration. Ballistic trajectories at varying delta-Vs and impulse angles are computed and propagated from the libration points, and trajectories that arrive at the lunar surface are investigated. Preliminary conclusions are drawn about the accessibility of the lunar surface from the triangular libration points, and the implications for mission design are discussed. These trajectories present an alternative means of accessing the Moon, expanding the viability of the triangular points for missions and offering additional options for the use of cisular space.

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Additive Manufacturing Of Ti-Ni Based Ternary Shape Memory Alloys, Yitao Chen, Frank Liou Apr 2026

Additive Manufacturing Of Ti-Ni Based Ternary Shape Memory Alloys, Yitao Chen, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Metal 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 …

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Understanding Human Arm Stiffness Modulation In Overground Phri: The Roles Of Kinematics, Perturbation, And Trunk Sway, Mohsen Mohammadi Beirami, Sambad Regmi, Devin Michael Burns, Yun Seong Song Mar 2026

Understanding Human Arm Stiffness Modulation In Overground Phri: The Roles Of Kinematics, Perturbation, And Trunk Sway, Mohsen Mohammadi Beirami, Sambad Regmi, Devin Michael Burns, Yun Seong Song

Psychological Science Faculty Research & Creative Works

This study examines human arm kinematics during overground physical human-robot interaction (pHRI). Previous work showed humans adjust arm stiffness with changing trajectory uncertainty, but the roles of arm kinematics and muscle activation remained unclear. Building on a preliminary study, we analyzed arm movements with more participants (10 individuals) to achieve more reliable findings and examined two potential influences that arose in the preliminary study: the robot's perturbation effect (a brief hand push) and left-to-right trunk sway. Using a linear mixed-effects model, we evaluated the effects of participant, block, and trajectory condition on arm angles. Results showed minimal kinematic contribution to …

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Generative Artificial Intelligence In Aircraft Design Optimization, Xiaosong Du Feb 2026

Generative Artificial Intelligence In Aircraft Design Optimization, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Aircraft design optimization is essential for improving aircraft performance (such as reduced fuel consumption and lowered noise), which leads to more efficient, sustainable, and affordable aircraft. Conventional aircraft design adopts physics-based simulation models, but iteratively evaluating simulation models is computationally intensive, or even practically impossible. Meanwhile, artificial intelligence (AI) emerges as a revolutionary game changer in the modern engineering industry, including aircraft design optimization. Generative AI (genAI), one of the groundbreaking AI methods, has been advancing aircraft design optimization from various aspects, including intelligent parameterization, predictive modeling, training facilitation, and constraints handling. However, there is a lack of a review …

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Hybrid Sensing For Near-Earth Space Domain Awareness: Leveraging Space-Based Assets For Augmenting Optical Ground Observations, Smriti Nandan Paul, Hang Woon Lee Feb 2026

Hybrid Sensing For Near-Earth Space Domain Awareness: Leveraging Space-Based Assets For Augmenting Optical Ground Observations, Smriti Nandan Paul, Hang Woon Lee

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Because of recent advancements in space technologies, easier and more economical access to space, and an increase in commercial interests, the near-Earth space environment has witnessed an exploding number of objects being put into orbit. In particular, the low Earth orbit (LEO) region is at an increased risk of orbital collisions from large satellite constellation projects. Thus, monitoring LEO objects for space domain awareness and space traffic management has become increasingly imperative. In this paper, we use the concept of limited-CDF (cumulative distribution function) surface and mutual information for designing sensor tasking algorithms focusing on regular observation of known catalog …

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An Improved United-Atom Potential For Molecular Dynamics Simulation Of Saturated Properties Of N-Alkanes, Wazih Tausif, Jordan Hartfield, Alex George, Zhi Liang Jan 2026

An Improved United-Atom Potential For Molecular Dynamics Simulation Of Saturated Properties Of N-Alkanes, Wazih Tausif, Jordan Hartfield, Alex George, Zhi Liang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multiple united-atom (UA) potential models have been developed in the literature to reproduce experimental saturated properties of n-alkanes using Monte Carlo simulations. When these UA potentials are employed in molecular dynamics (MD) simulations, MD simulations often give relatively poor predictions of saturated properties of n-alkanes, particularly the saturated vapor densities, due to the challenges in accurate calculation of long-range intermolecular forces beyond the cutoff distance in an inhomogeneous system. In this work, a new set of UA Lennard-Jones (LJ) interaction parameters for n-alkanes is proposed to reproduce the saturated properties, including saturated liquid and vapor densities (ρf and ρ …

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Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara Jan 2026

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara

Engineering Management and Systems Engineering Faculty Research & Creative Works

Producing high-quality fiber-reinforced composites requires precise temperature control during autoclave curing, as even small variations can lead to defects that compromise strength and reliability. At the same time, manufacturers aim to reduce energy use and shorten curing cycles without sacrificing material performance. To address these challenges, this study develops a data-driven Long Short-Term Memory (LSTM) neural network model capable of forecasting temperature evolution inside the autoclave throughout the curing cycle. The model is trained on time-series temperature data collected from multiple sensing locations, enabling it to learn the spatial and temporal trends that govern heat flow during curing. Data augmentation …

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The Effects Of Mold Flux Contamination On Oxide Scale Formation And Hydro-Descaling Efficiency During Steel Processing, Tochukwu Princewill Ojiako, Richard Osei, Mario Buchely, Haiming Wen, Simon Lekakh, Ronald O'Malley Jan 2026

The Effects Of Mold Flux Contamination On Oxide Scale Formation And Hydro-Descaling Efficiency During Steel Processing, Tochukwu Princewill Ojiako, Richard Osei, Mario Buchely, Haiming Wen, Simon Lekakh, Ronald O'Malley

Materials Science and Engineering Faculty Research & Creative Works

Oxide scale formation during thin-slab continuous casting has a complex structure, which is influenced by mold flux contamination, that modifies interfacial reactions during solidification, subsequent reheating, and descaling. While individual aspects of the oxidation behavior of carbon steel have been previously examined, the synergetic effects of mold flux contamination during continuous casting and subsequent reheating on scale modification and the efficiency of hydraulic descaling remain inadequately studied. This study quantitatively examines the effect of flux composition on oxide scale evolution, adhesion, and hydraulic removal in low-carbon steel under simulated industrial conditions. Slab samples with as-cast, cleaned, and flux-coated surfaces were …

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Simulated Lunar Gravity Testing Of A Magnetic And Electrostatic System For Beneficiating Lunar Regolith, Blake A. Coffman, Gabriel Porter, Lindsay Manteufel, Mitchell Cottrell, Jeffrey D. Smith, David J. Bayless, William Shonberg, Frank D. Han, Fateme Rezaei, Kirby Runyon Jan 2026

Simulated Lunar Gravity Testing Of A Magnetic And Electrostatic System For Beneficiating Lunar Regolith, Blake A. Coffman, Gabriel Porter, Lindsay Manteufel, Mitchell Cottrell, Jeffrey D. Smith, David J. Bayless, William Shonberg, Frank D. Han, Fateme Rezaei, Kirby Runyon

Materials Science and Engineering Faculty Research & Creative Works

We present the design and testing of a lunar regolith beneficiation device that utilizes magnetic and electrostatic separation methods to concentrate desired minerals by removing unwanted material, such as the mineral anorthite, from bulk lunar regolith. The beneficiated materials would have value for downstream in-situ resource utilization (ISRU) processes such as metal extraction, oxygen extraction, and metal oxide additive manufacturing processes. The apparatus uses a dual-strength magnet system with N52 and N42 neodymium magnets to separate particles by magnetic susceptibility. The electrostatic separation system, which acts like a sieve, sorts the regolith simulant by particle size using a single-phase 50% …

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Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely Jan 2026

Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely

Materials Science and Engineering Faculty Research & Creative Works

All-d-metal Heusler alloys are emerging functional materials in which magnetic ordering, lattice distortion, and mechanical behavior are strongly coupled through d–d electronic interactions. This study systematically investigates the structural, thermal, magnetic, and mechanical properties of Mn₂FeCu synthesized within a Heusler-type compositional framework. SEM/EDS revealed a dual-phase FCC-based microstructure consisting of Mn–Fe–rich and Mn–Cu–rich domains, while XRD confirmed FCC symmetry with compositional partitioning rather than full L2₁ ordering. Differential scanning calorimetry identified partial melting of the Cu-rich phase near ~ 900 °C. Dilatometry showed a thermoelastic FCC → FCT transformation at ~ 770–780 °C with a recoverable strain of ~ 0.067%. …

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Overcoming Resolution Vs. Throughput Trade-Offs In Ceramic Material Extrusion Additive Manufacturing Via Viscoelastic Filament Stretching, Abid H. Rafi, David W. Lipke, Jeremy L. Watts, Gregory E. Hilmas, Ming C. Leu Jan 2026

Overcoming Resolution Vs. Throughput Trade-Offs In Ceramic Material Extrusion Additive Manufacturing Via Viscoelastic Filament Stretching, Abid H. Rafi, David W. Lipke, Jeremy L. Watts, Gregory E. Hilmas, Ming C. Leu

Materials Science and Engineering Faculty Research & Creative Works

Fabricating large, monolithic ceramic parts using material-extrusion additive manufacturing remains challenging due to difficulty maintaining uniform moisture content during printing, which can lead to drying-induced defects such as warping and cracking, especially as part size and print time increase. Fabricated parts have trade-offs among print resolution, high throughput, and structural fidelity. Our study has shown that increasing the ratio of nozzle traverse speed vs. material extrusion speed increases filament stretching in viscoelastic ceramic paste, helping to overcome the trade-offs between resolution and throughput. Using aqueous ZrB2–SiC (70/30 vol.%) as a representative ultra-high temperature ceramic paste, rheological characterisation revealed viscoelastic yield-stress …

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Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park Jan 2026

Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Translating the ultrahigh intrinsic conductivity of conjugated polymers into bulk 3D architectures remains a formidable challenge due to the fundamental dichotomy between rheological printability and electronic purity. Existing strategies necessitate a compromise: solution-processing requires insulating binders that degrade charge transport, while binder-free vapor-phase polymerization (VPP) is kinetically confined to surface-limited thin films by diffusion constraints. Here, we introduce atomized oxidative polymerization (AOP), a manufacturing paradigm that overcomes these kinetic barriers via active, layer-by-layer monomer atomization. This approach ensures stoichiometric reaction conditions throughout the printed volume, driving a structural transition toward highly conductive quinoid-dominant chains with enhanced π-π stacking. The resulting …

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Physics-Constrained Generative Adversarial Networks For Dimensionality Reduction In Optimization, Samuel Sisk, Xiaosong Du Jan 2026

Physics-Constrained Generative Adversarial Networks For Dimensionality Reduction In Optimization, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft make a unique form of urban air mobility due to their low noise, zero emission, and precision control. To maximize efficiency, high-fidelity simulation-based multidisciplinary design optimization discovers the optimal balance among subsystems within an eVTOL. However, conventional multidisciplinary design optimization is computationally intensive due to excessive high-fidelity model evaluations. Moreover, complex nonlinear constraints deteriorate optimization efficiency and convergence. While surrogate models enable efficient design optimization, surrogate modeling suffers in large-scale applications and surrogate-based optimization still has to deal with nonlinear constraints. To address these challenges, the authors' previous work proposed physics-constrained generative adversarial …

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Tomo-Piv Study Of Baseline Flow Structures Behind A Strut Injector, Josiah Mcdermott, Connor Bell, Davide Viganò Jan 2026

Tomo-Piv Study Of Baseline Flow Structures Behind A Strut Injector, Josiah Mcdermott, Connor Bell, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Stabilizing combustion in scramjet engines is a formidable challenge due to the small-time scales afforded for air-fuel mixing. Numerous studies in this area have demonstrated the potential of strut-style platforms for fuel injection and mixing enhancement, which remains an active area of research. In the Aerodynamics Research Laboratory at Missouri S&T, a strut-style injector system has recently been installed. In this study, we characterize the baseline flow structures behind this platform absent fuel injection. The wake generated by a strut itself has an appreciable impact on the resulting air-fuel mixing, which motivates its characterization. In future studies, this characterization will …

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Optimal Takeoff Trajectory Prediction Of Electric Drones Based On A Fully Automated Optimal Experimental Design Method, Jiachen Wang, Dheeraj Paramkusham, Xiaosong Du Jan 2026

Optimal Takeoff Trajectory Prediction Of Electric Drones Based On A Fully Automated Optimal Experimental Design Method, Jiachen Wang, Dheeraj Paramkusham, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft is attracting great interest as a viable solution to promote urban aerial mobility with promising flexibility as well as emission reductions. However, the low specific energy of the current battery is still a strong constraint on the range and endurance of eVTOL flights, especially considering the significant power demands during the takeoff process. Engineering design optimization permits promising solutions for the minimum takeoff energy consumption but can be computationally intensive due to iteratively evaluating simulation models. Surrogate-based design optimization is efficient but still relies on optimization iterations which prohibit real-time decision-making. To fill …

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