Engineering Commons^™

Active Control Of Equilibrium, Near-Equilibrium, And Far-From-Equilibrium Colloidal Systems, Mark N. Mcdonald, Qinyu Zhu, Walter F. Paxton, Cameron K. Peterson, Douglas R. Tree

Faculty Publications

The development of top-down active control over bottom-up colloidal assembly processes has the potential to produce materials, surfaces, and objects with applications in a wide range of fields spanning from computing to materials science to biomedical engineering. In this review, we summarize recent progress in the field using a taxonomy based on how active control is used to guide assembly. We find there are three distinct scenarios: (1) navigating kinetic pathways to reach a desirable equilibrium state, (2) the creation of a desirable metastable, kinetically trapped, or kinetically arrested state, and (3) the creation of a desirable far-from-equilibrium state through …

Bioaugmentation With Tetrasphaera To Improve Biological Phosphorus Removal From Anaerobic Digestate Of Swine Wastewater, Jiaxin Wang, Chiqian Zhang, Ping Li, Hui Xu, Weiqu Wang, Weizhao Yin, Jinhua Wu, Zhiqiang Hu

Faculty Publications

Tetrasphaera-enhanced biological phosphorus removal (T-EBPR) was developed by augmenting conventional EBPR (C-EBPR) with Tetrasphaera to improve phosphorus removal from anaerobic digestate of swine wastewater. At influent total phosphorus (TP) concentrations of 45 to 55 mg/L, T-EBPR achieved effluent TP concentration of 4.17 ± 1.02 mg/L, 54% lower than that in C-EBPR (8.98 ± 0.76 mg/L). The enhanced phosphorous removal was presumably due to the synergistic effect of Candidatus Accumulibacter and Tetrasphaera occupying different ecological niches. Bioaugmentation with Tetrasphaera promoted the polyphosphate accumulation metabolism depending more on the glycolysis pathway, as evidenced by an increase in intracellular storage compounds of glycogen …

Drone Detection Using Yolov5, Burchan Aydin, Subroto Singha

Faculty Publications

The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). …

Laser Powder Bed Fusion Of Molybdenum And Mo-0.1sic Studied By Positron Annihilation Lifetime Spectroscopy And Electron Backscatter Diffraction Method, Nathan E. Ellsworth, Joshua R. Machacek, Ryan A. Kemnitz, Cayla C. Eckley, Brianna M. Sexton, Joel S. Gearhart, Larry W. Burggraf

Faculty Publications

Positron annihilation lifetime spectroscopy (PALS) has been used for the first time to investigate the microstructure of additively manufactured molybdenum. Despite the wide applicability of positron annihilation spectroscopy techniques to the defect analysis of metals, they have only been used sparingly to monitor the microstructural evolution of additively manufactured metals. Molybdenum and molybdenum with a dilute addition (0.1 wt%) of nano-sized silicon carbide, prepared via laser powder bed fusion (LPBF) at four different scan speeds: 100, 200, 400, and 800 mm/s, were studied by PALS and compared with electron backscatter diffraction analysis. The aim of this study was to clarify …

Steering Particles Via Micro-Actuation Of Chemical Gradients Using Model Predictive Control, Mark N. Mcdonald, Cameron K. Peterson, Douglas R. Tree

Faculty Publications

Biological systems rely on chemical gradients to direct motion through both chemotaxis and signaling, but synthetic approaches for doing the same are still relatively naïve. Consequently, we present a novel method for using chemical gradients to manipulate the position and velocity of colloidal particles in a microfluidic device. Specifically, we show that a set of spatially localized chemical reactions that are sufficiently controllable can be used to steer colloidal particles via diffusiophoresis along an arbitrary trajectory. To accomplish this, we develop a control method for steering colloidal particles with chemical gradients using nonlinear model predictive control with a model based …

Ash Aerosol Particle Size Distribution, Composition, And Deposition Behavior While Co-Firing Coal And Steam-Exploded Biomass In A 1.5 Mwth Combustor, Rajarshi Roy, Brian Schooff, Xiaolong Li, Scott Montgomery, Jacob Tuttle, Jost O.L. Wendt, Kingsley Dickson, Brian Iverson, Andrew R. Fry

Faculty Publications

Five different blends of Utah bituminous coal and steam-exploded pine (100/0, 75/25, 50/50, 25/75, 0/100 by mass) were fired in a 1.5 MWth combustor. Primary objectives were to understand mineral matter behavior by analyzing aerosol size distribution, aerosol size-segregated composition, ash deposition mass, and ash composition. For particle size < 0.1 μm, pure coal had the lowest aerosol concentration and pure biomass showed the highest (higher nucleation of potassium salts), a trend which reversed for particles >0.1 μm. During pure biomass combustion, aerosol particles >15 μm contained higher mass fractions of potassium (+126%), calcium (+132%), and iron (+115%) and lower fractions of aluminum (−49%) and silicon (−29%) than pure coal. Ash deposition mass decreased with increasing biomass blends. …

Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton, Richard Dill, Michael R. Grimaila, Douglas Hodson

Faculty Publications

Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of …

Normalized Coordinate Equations And Energy Method For Predicting Natural Curved-Fold Configurations, Jacob Badger, Todd G. Nelson, Rober J. Lang, Denise M. Halverson, Larry L. Howell

Faculty Publications

Of the many valid configurations that a curved fold may assume, it is of particular interest to identify natural—or lowest energy—configurations that physical models will preferentially assume. We present normalized coordinate equations—equations that relate fold surface properties

to their edge of regression—to simplify curved-fold rela- tionships. An energy method based on these normalized

coordinate equations is developed to identify natural con- figurations of general curved folds. While it has been noted

that natural configurations have nearly planar creases for curved folds, we show that non-planar behavior near the crease ends substantially reduces the energy of a fold.

A Pseudo-Static Model For Dynamic Analysis On Frequency Domain Of Distributed Compliant Mechanisms, Mingxiang Ling, Larry L. Howell, June Cao, Zhou Jiang

Faculty Publications

This paper presents a pseudo-static modeling methodology for dynamic analysis of distributed compliant mechanisms to provide accurate and efficient solutions. First, a dynamic stiffness matrix of the flexible beam is deduced, which has the same definition and a similar form as the traditional static compliance/stiffness matrix but is frequency-dependent. Second, the pseudo-static modeling procedure for the dynamic analysis is implemented in a statics-similar way. Then, all the kinematic, static and dynamic performances of compliant mechanisms can be analyzed based on the pseudo- static model. The superiority of the proposed method is that when it is used for the dynamic modeling …

Origami-Based Design Of Conceal-And-Reveal Systems, Bryce P. Defigueiredo, Kyler A. Tolman, Spencer P. Magleby, Nathan A. Pehrson, Erica Crampton, Larry L. Howell

Faculty Publications

This work introduces a type of motion termed “conceal-and-reveal” which is characterized by a state that protects a payload, a state that exposes the payload, and coupled motions between these two states. As techniques for thick, rigid origami-based engineering designs are being developed, origami is becoming increasingly more

attractive as inspiration for complex systems. This paper proposes a process for designing origami-based conceal- and-reveal systems, which can be generalized to design similar thick, rigid origami-based systems. The process

is demonstrated through the development of three conceal-and-reveal systems that present a luxury product to the consumer. The three designs also confirm …

Kinematic/Static Model Of Complex Compliant Mechanisms With Serial-Parallel Substructures: A General Approach, Mingxiang Ling, Junyi Cao, Larry L. Howell

Faculty Publications

Kinematic and static analyses of compliant mechanisms are crucial at the early stage of design, and it can be difficult and laborsome for complex configurations with distributed compliance. In this paper, a general and concise kinematic/static modeling method of flexure-hinge-based compliant mechanisms with arbitrary serial-parallel substructures is presented to provide accurate and efficient solutions by combining the matrix displacement method with the transfer matrix method. The transition between the elemental stiffness matrix and the transfer matrix of the flexure hinge and the flexible beam is straightforward, enabling the condensation of a hybrid serial-parallel substructure into one equivalent element simple. Then, …

Origami-Inspired Sacrificial Joints For Folding Compliant Mechanisms, Todd G. Nelson, Alex Avila, Larry L. Howell, Just L. Herder, Davood Farhadi Machekposhtic

Faculty Publications

Folding is a manufacturing method which can create complex 3D geometries from flat materi- als and can be particularly useful in cost-sensitive or planar-limited fabrication applications.

This paper introduces compliant mechanisms that employ folding techniques from origami to evolve from a flat material to deployed state. We present origami-inspired sacrificial joints, joints which have mobility during assembly of the mechanism but are rigid in their final position, to create regions of high and low stiffness and the proper alignment of compliant flexures in folded mechanisms. To demonstrate the method we fold steel sheet to create some well-known and complex compliant …

Regional Stiffness Reduction Using Lamina Emergent Torsional Joints For Flexible Printed Circuit Board Design, Bryce P. Defigueiredo, Brian Dale Russell, Trent K. Zimmerman, Larry L. Howell

Faculty Publications

Flexible printed circuit boards (PCBs) make it possi- ble for engineers to design devices that use space efficiently

and can undergo changes in shape and configuration. How- ever, they also suffer from trade-offs due to non-ideal mate- rial properties. Here, a method is presented that allows en- gineers to introduce regions of flexibility in otherwise rigid

PCB substrates. This method employs geometric features to reduce local stiffness in the PCB, rather than reducing

the global stiffness by material selection. Analytical and fi- nite element models are presented to calculate the maximum

stresses caused by deflection. An example device is produced …

Magnetic Tilt Effect On Externally Driven Electromagnetic Ion Cyclotron (Emic) Waves, Eun-Hwa Kim, Jay R. Johnson

Faculty Publications

No abstract provided.

Performance Of Rubberized Concrete And The Effect Of Temperature And Stainless Steel Fibers, Ayman El-Zohairy, Matthew Sanchez, Bahram Abediniangerabi, Perry Moler

Faculty Publications

Rubberized concrete is widely used in construction by utilizing the advantages of partially replacing fine or coarse aggregate with rubber to enhance several properties of concrete and provide an environmentally friendly solution. This paper experimentally explores the influence of utilizing crumb rubber (CR) as an alternate coarse aggregate in concrete. Concrete specimens were prepared with different percentages of rubber (0%, 5%, 10%, 15%, and 20%). Additionally, other parameters, such as freezing–thawing cycles, temperature, and stainless steel fibers (SSFs), were investigated. The workability of fresh concrete and the compression properties of hardened concrete were examined. Reductions in the mechanical properties of …

Deep Transfer Learning For Approximate Model Predictive Control, Samuel Arce Munoz, Junho Park, Cristina M. Stewart, Adam M. Martin, John Hedengren

Faculty Publications

Transfer learning is a machine learning technique that takes a pre-trained model that has already been trained on a related task, and adapts it for use on a new, related task. This is particularly useful in the context of model predictive control (MPC), where deep transfer learning is used to improve the training of the MPC by leveraging the knowledge gained from related controllers. One way in which transfer learning is applied in the context of MPC is by using a pre-trained deep learning model of the MPC, and then fine-tuning the controller training for a new process automation task. …

Engineering At-Home Dilution And Filtration Methods To Enable Paper-Based Colorimetric Biosensing In Human Blood With Cell-Free Protein Synthesis, Tyler J. Free, Ryan W. Tucker, Katelyn M. Simonson, Sydney A. Smith, Caleb M. Lindgren, William G. Pitt, Bradley C. Bundy

Faculty Publications

Diagnostic blood tests can guide the administration of healthcare to save and improve lives. Most clinical biosensing blood tests require a trained technician and specialized equipment to process samples and interpret results, which greatly limits test accessibility. Colorimetric paper-based diagnostics have an equipment-free readout, but raw blood obscures a colorimetric response which has motivated diverse efforts to develop blood sample processing techniques. This work uses inexpensive readily-available materials to engineer user-friendly dilution and filtration methods for blood sample collection and processing to enable a proof-of-concept colorimetric biosensor that is responsive to glutamine in 50 µL blood drop samples in less …

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman

Faculty Publications

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and …

Dataset For Effects Of Single-Session Practice Structure On Motor Skill Acquisition And Alpha And Beta Eeg Oscillations, Audrey Porter, Ronald V. Croce, Wayne Smith

Faculty Publications

Although it is known that practicing a motor skill updates the associated internal model, it is still unclear as to how cortical oscillations linked with the motor skill change under differing practice schedules. The current study investigated α- and β-power changes associated with motor skill acquisition. Firstly, we investigated the behavioral effects of practice on motor learning and retention during repetitive (RP) and variable (VP) practice schedules on an anticipation timing task. Secondly, we investigated changes in cortical α (10-13 HZ) and β (15-30 Hz) event-related synchronization and dyssynchronization (ERS/ERD) under RP and VP during early (EP) and late …

Perspective On Predictive Modeling: Current Status, New High-Order Methodology And Outlook For Energy Systems, Dan Gabriel Cacuci

Faculty Publications

This work presents a perspective on deterministic predictive modeling methodologies, which aim at extracting best-estimate values for model responses and parameters along with reduced predicted uncertainties for these best-estimate values. The two oldest such methodologies are the data-adjustment method, which stems from the nuclear energy field, and the data-assimilation method, which is implemented in the geophysical sciences. Both of these methodologies attempt to minimize, in the least-square sense, a user-defined functional that represents the discrepancies between computed and measured model responses. These two methodologies were briefly reviewed and shown to be inconsistent even to first-order in the sensitivities of the …

Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning

Faculty Publications

Optimizing wind farm layouts is an important step in designing an efficient wind farm. Optimizing wind farm layouts is also a difficult task due to computation times increasing with the number of turbines present in the farm. The most computationally expensive part of gradient- based optimization is calculating the gradient. In order to reduce the expense of gradient calculation, we performed a study on the use of sparsity in wind farm layout optimization. This paper presents the findings of the sparsity study and provides a method to use sparsity in wind farm layout optimization. We tested this sparsity method by …

Aerostructural Predictions Combining Fenics And A Viscous Vortex Particle Method, Ryan Anderson, Andrew Ning, Ru Xiang, Sebastiaan P. C. Van Schie, Mark Sperry, Darshan Sarojini, David Kamensky, John T. Hwang

Faculty Publications

Electric Vertical Takeoff and Landing (eVTOL) aircraft experience complex, unsteady aerodynamic interactions between rotors, wings, and fuselage that can make design difficult. We introduce a new framework for predicting aerostructural interactions. Specifically, we demonstrate the coupling of a finite element solver with Reissner-Mindlin shell theory for computing deflections and a viscous vortex particle for capturing wakes. We perform convergence studies of the aerodynamics and the coupled aerostructural model. Finally, we share some preliminary results of the dynamic aeroelastic response of Uber’s eCRM-002 main wing, and share some qualitative observations.

A Coupled Source Panel, Actuator Line, And Viscous Vortex Particle Method In An O(N) Scheme, Ryan Anderson, Andrew Ning

Faculty Publications

Wake interactions play a significant role in aerodynamics. However, common modeling approaches are either expensive or lack fidelity, making them unreliable or difficult to use in the design process. The vortex particle method can capture the relevant physics effectively, but imposing boundary conditions with solid surfaces in a computationally efficient way is challenging. We explore two possible methods of imposing solid surface boundary conditions of vortex particle simulations. The first, a novel variation on a pure particle approach, is easy to implement but is moderately expensive, and suffers from some numerical instability. The second, source panels accelerated with a fast …

Isogeometric Boundary-Conforming Body-In-White Crash Model Construction, Analysis, And Comparison With Fem Model, Kendrick M. Shepherd

Faculty Publications

In this paper, we discuss model generation to rebuild the body-in-white of a 1996 Dodge Neon finite element model into a isogeometric conforming analysis-suitable crash model. We then perform the first known boundary-fit isogeometric body-in-white crash analysis of the vehicle and compare results achieved by traditional finite element methods. Results indicate the value and potential of high-order meshes in analysis.

Triangular Fin Array Passively Actuated By Bimetallic Coils For Cubesat Thermal Control, Josh Cannon, Rydge B. Mulford, Brian D. Iverson

Faculty Publications

CubeSat thermal control can be especially demanding due to volume and size constraints, high power dissipation per unit surface area, and highly variable internal and external heat loads. As such, CubeSat developers must rely on thermal control systems that meet the specific requirements of their mission and environmental conditions. Deployable radiators enable satellites to increase their radiative surface area and to reveal highly emissive surfaces during times when increased heat rejection is desired. In colder conditions, when decreased heat loss is preferable, the radiators can be stowed. Passive thermal control systems are unpowered and can increase system reliability by not …

Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

U.S. Department of Defense (DoD) personal property moves account for 15% of all domestic and international moves - accurate prediction of their cost could draw attention to outlier shipments and improve budget planning. In this work 136,140 shipments between 13 personal property shipment hubs from April 2022 through March 2023 with a total cost of $1.6B were analyzed. Shipment cost was predicted using recursive feature elimination on linear regression and XGBoost algorithms, as well as through neural network hyperparameter sweeps. Modeling was repeated after removing 28 features related to shipment hub location and branch of service to examine their influence …

Low-Fidelity Design Optimization And Parameter Sensitivity Analysis Of Tilt-Rotor Evtol Electric Propulsion Systems, Tyler Critchfield, Andrew Ning

Faculty Publications

Urban air mobility requires a multidisciplinary approach to tackle the important chal- lenges facing the design of these aircraft. This work uses low-to-mid fidelity tools to model rotor aerodynamics, blade structures, vehicle aerodynamics, and electric propulsion for a tilt-rotor electric vertical takeoff and landing (eVTOL) aircraft. We use gradient-based design optimization and extensive parameter sensitivity analysis to explore the design space and complex tradeoffs of tilt-rotor distributed electric propulsion systems.

Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch

Faculty Publications

Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.

Live-Sky Gnss Signal Processing Using A Dual-Polarized Antenna Array For Multipath Mitigation, Eric Hahn, Sanjeev Gunawardena, Chris Bartone

Faculty Publications

Excerpt: Multipath results from reflections of Global navigation satellite signals (GNSS) signals arriving at a receiver that are delayed with respect to the desired line-of-sight (LOS) signals. The delayed signals distort the received LOS signals, thereby causing pseudorange and carrier phase measurement errors. Traditional multipath mitigation techniques include antenna gain pattern shaping (primarily to reduce ground multipath) and correlator gating techniques (such as narrow correlator and double-delta correlator [1]).

To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis

Faculty Publications

China’s advancing space capabilities, particularly in the cislunar region, call for increased cislunar space domain awareness on the part of the United States. US military and civilian decisionmakers must take into account the full scope of China’s cislunar plans and capabilities as the military builds space strategies and future force designs. The United States must also increase near-term investments that support more robust cislunar space domain awareness.