Engineering Commons^™

Small-Scale Testing Of Passive Fire Protection Systems For Structures On The Wildland-Urban Interface, Makenzie Wilson, Thomas H. Fletcher, Taylor J. Sorensen

Faculty Publications

The average intensity and frequency of wildland fires have been on the rise over the years due to climate change. This, in combination with recent expansion and growth of rural areas, has led to an increased risk of wildfire damage for structures in the Wildland-Urban Interface (WUI). This paper proposes a permanent passive fire protection system that is built into the structure. A flame-resistant material would be attached to the sheathing underneath the roofing and siding material. This system would allow the easily replaceable exterior components of the structure to burn while leaving the interior of the structure protected. Small-scale …

Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

High-frequency skywave propagation can be heavily impacted by D- and E-region dynamics requiring accurate global measurements to optimize performance. A standard measurement technique is to use ionosondes, but they are unable to measure below 1 MHz and are only available at a limited number of land-locked sites around the globe. In contrast, the Global Navigation Satellite System radio occultation (GNSS-RO) bottom-up method is a new approach specifically designed to generate electron density profiles in the D- and E- region ionosphere. It takes advantage of satellite constellations that currently provide over 20,000 daily measurements and global coverage. In this paper, GNSS-RO …

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—I: Underlying Motivation And Current Methods, Dan Gabriel Cacuci

Faculty Publications

The mathematical/computational model of a physical system comprises parameters and independent and dependent variables. Since the physical system is seldom known precisely and since the model’s parameters stem from experimental procedures that are also subject to uncertainties, the results predicted by a computational model are imperfect. Quantifying the reliability and accuracy of results produced by a model (called “model responses”) requires the availability of sensitivities (i.e., functional partial derivatives) of model responses with respect to model parameters. This work reviews the basic motivations for computing high-order sensitivities and illustrates their importance by means of an OECD/NEA reactor physics benchmark, which …

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—Ii: Introducing The Second-Order Adjoint Sensitivity Analysis Methodology For Computing Response Sensitivities To Functions/Features Of Parameters, Dan Gabriel Cacuci

Faculty Publications

This work introduces a new methodology, which generalizes the extant second-order adjoint sensitivity analysis methodology for computing sensitivities of model responses to primary model parameters. This new methodology enables the computation, with unparalleled efficiency, of second-order sensitivities of responses to functions of uncertain model parameters, including uncertain boundaries and internal interfaces, for linear and/or nonlinear models. Such functions of primary model parameters customarily describe characteristic “features” of the system under consideration, including correlations modeling material properties, flow regimes, etc. The number of such “feature” functions is considerably smaller than the total number of primary model parameters. By enabling the computations …

Bacterial Extraction And Concentration From Blood Through Filtration Processes, Ryan L. Wood, Rebecca Prymak, Evelyn Welling, Alayna Bedwell, Jordan T. Wood, Damian E. Teasley, Magdalena Crofts, Hope Callister Anderson, Clifton M. Anderson, W Cameron Beard, Jacob Stepan, Alexandra Carter, William G. Pitt

Faculty Publications

Blood stream infections (BSIs) are challenging to rapidly and precisely diagnose. Current clinical diagnostic methods for BSI identification require culturing the blood sample for many hours prior to identifying the bacteria and possible antibiotic resistance. Removing the culturing step from the bacterial identification process of a BSI provides a significant reduction in the processing time, but shifts the rate-limiting step from the growth time to the concentration procedure, since CFU levels in clinical blood samples can be as low as 10 CFU/mL in blood. This study developed a novel whole blood filtration method to concentrate bacteria from a BSI without …

Transferrin-Targeted Liposomes In Glioblastoma Therapy: A Review, Paul Kawak, Nour M Al Sawaftah, William G. Pitt, Ghaleb A. Husseini

Faculty Publications

Glioblastoma (GBM) is a highly aggressive brain tumor, and its treatment is further complicated by the high selectivity of the blood–brain barrier (BBB). The scientific community is urgently seeking innovative and effective therapeutic solutions. Liposomes are a promising new tool that has shown potential in addressing the limitations of chemotherapy, such as poor bioavailability and toxicity to healthy cells. However, passive targeting strategies based solely on the physicochemical properties of liposomes have proven ineffective due to a lack of tissue specificity. Accordingly, the upregulation of transferrin receptors (TfRs) in brain tissue has led to the development of TfR-targeted anticancer therapeutics. …

Recommended Separation Distances For 1.3 Ammunition And Explosives, Clint Guymon, Ming Liu, Josephine Covino

Faculty Publications

Separation Distances are used throughout the world to protect people and assets from the potential hazardous effects from propellants, explosives, and pyrotechnics. The current separation distances for Hazard Division (HD) 1.3 substances and articles used in the United States, in some cases, may not adequately protect against the effects from heat flux and debris when those substances and articles are ignited in a confined structure. Multiple tests in such a confined scenario with HD 1.3 substances have shown that the heat flux and debris hazards could result in injury at distances beyond the current specified explosives safety separation distance (ESSD). …

Simultaneous Multistep Transformer Architecture For Model Predictive Control, Junho Park, Mohammad Reza Babaei, Samuel Arce Munoz, Ashwin N. Venkat, John Hedengren

Faculty Publications

Transformer neural networks have revolutionized natural language processing by effectively addressing the vanishing gradient problem. This study focuses on applying Transformer models to time-series forecasting and customizing them for a simultaneous multistep-ahead prediction model in surrogate model predictive control (MPC). The proposed method showcases improved control performance and computational efficiency compared to LSTM-based MPC and one-step-ahead prediction models using both LSTM and Transformer networks. The study introduces three key contributions: (1) a new MPC system based on a Transformer time-series architecture, (2) a training method enabling multistep-ahead prediction for time-series machine learning models, and (3) validation of the enhanced time …

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4

Determination Of A Surrogate For Plutonium Electrorefining, Greg Chipman, Bryant Johnson, Suhee Choi, Chao Zhang, Michael Simpson, Devin Rappleye

Faculty Publications

Conducting research experiments on plutonium electrorefining is difficult due to the significant hazards and regulations associated with nuclear materials. Finding a surrogate for plutonium electrorefining studies would enable more fundamental research to be conducted. Potential surrogates were first identified by determining the physical properties required to conduct electrorefining at the same conditions commonly used in plutonium electrorefining, a molten metal and molten CaCl₂ at 1123 K. Ce-CeCl₃, In-InCl₃, and Pb-PbCl₂ were the only potential surrogates identified using these constraints. Sn-SnCl₂ was also tested at these same conditions. More potential surrogates were identified by …

Oxidation Of Hafnium Diboride—Silicon Carbide At 1500 °C In Air; Effect Of Compressive Stress, Anthony J. Degregoria, Marina B. Ruggles-Wrenn, Glen E. Pry

Faculty Publications

The long-term oxidation behavior of HfB₂ and of HfB₂-20 vol.% SiC was studied. Test samples of each material were oxidized at 1500 °C in air using a box furnace. The exposure times were 0, 0.5, 1, 2, 3, 6, 9, 12, 15, 30, 45 and 90 h. Weight gain, oxide scale composition and oxide scale thickness were characterized for both materials. Crystal structure of the surface scales was analyzed using x-ray diffraction. Oxide scales were further characterized via scanning electron microscopy with energy dispersive spectroscopy analysis. For HfB₂ the oxide scale consists predominantly of porous HfO …

Spectral Broadening Effects On Pulsed-Source Digital Holography, Steven A. Owens, Mark F. Spencer, Glen P. Perram

Faculty Publications

Using a pulsed configuration, a digital-holographic system is setup in the off-axis image plane recording geometry, and spectral broadening via pseudo-random bit sequence is used to degrade the temporal coherence of the master-oscillator laser. The associated effects on the signal-to-noise ratio are then measured in terms of the ambiguity and coherence efficiencies. It is found that the ambiguity efficiency, which is a function of signal-reference pulse overlap, is not affected by the effects of spectral broadening. The coherence efficiency, on the other hand, is affected. As a result, the coherence efficiency, which is a function of effective fringe visibility, is …

Structural Behavior Of Reactive Powder Concrete Under Harmonic Loading, Shatha D. Mohammed, Teghreed H. Ibrahim, Ban F. Salman, Abbas A. Allawi

Faculty Publications

Industrial buildings usually are designed to sustain several types of load systems, such as dead, live, and dynamic loads (especially the harmonic load produced by rotary motors). In general, these buildings require high-strength structural elements to carry the applied loads. Moreover, Reactive Powder Concrete (RPC) has been used for this purpose because of its excellent mechanical strength and endurance. Therefore, this study provides an experimental analysis of the structural behaviors of reinforced RPC beams under harmonic loads. The experimental program consisted of testing six simply supported RPC beams with lengths of 1500 mm, widths of 150 mm, and thicknesses of …

Liposomes For The Treatment Of Brain Cancer—A Review, Richu Raju, Waad H. Abuwatfa, William G. Pitt, Ghaleb A. Husseini

Faculty Publications

Due to their biocompatibility, non-toxicity, and surface-conjugation capabilities, liposomes are effective nanocarriers that can encapsulate chemotherapeutic drugs and facilitate targeted delivery across the blood–brain barrier (BBB). Additionally, strategies have been explored to synthesize liposomes that respond to internal and/or external stimuli to release their payload controllably. Although research into liposomes for brain cancer treatment is still in its infancy, these systems have great potential to fundamentally change the drug delivery landscape. This review paper attempts to consolidate relevant literature regarding the delivery to the brain using nanocarriers, particularly liposomes. The paper first briefly explains conventional treatment modalities for cancer, followed …

A Review On Membrane Fouling Prediction Using Artificial Neural Networks (Anns), Waad H. Abuwatfa, Nour Al Sawaftah, Naif Darwish, William G. Pitt, Ghaleb A. Husseini

Faculty Publications

Membrane fouling is a major hurdle to effective pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). Fouling refers to the accumulation of particles, organic and inorganic matter, and microbial cells on the membrane’s external and internal surface, which reduces the permeate flux and increases the needed transmembrane pressure. Various factors affect membrane fouling, including feed water quality, membrane characteristics, operating conditions, and cleaning protocols. Several models have been developed to predict membrane fouling in pressure-driven processes. These models can be divided into traditional empirical, mechanistic, and artificial intelligence (AI)-based models. Artificial neural networks …

A Hybrid Metaheuristic And Computer Vision Approach To Closed-Loop Calibration Of Fused Deposition Modeling 3d Printers, Graig S. Ganitano, Shay V. Wallace, Benji Maruyama, Gilbert L. Peterson

Faculty Publications

Fused deposition modeling (FDM) is one of the most popular additive manufacturing (AM) technologies for reasons including its low cost and versatility. However, like many AM technologies, the FDM process is sensitive to changes in the feedstock material. Utilizing a new feedstock requires a time-consuming trial-and-error process to identify optimal settings for a large number of process parameters. The experience required to efficiently calibrate a printer to a new feedstock acts as a barrier to entry. To enable greater accessibility to non-expert users, this paper presents the first system for autonomous calibration of low-cost FDM 3D printers that demonstrates optimizing …

Complex Systems Methods Characterizing Nonlinear Processes In The Near-Earth Electromagnetic Environment: Recent Advances And Open Challenges, Georgios Balasis, Michael A. Balikhin, Sandra C. Chapman, Giuseppe Consolini, Ioannis A. Daglis, Reik V. Donner, Jürgen Kurths, Milan Paluš, Jakob Runge, Bruce T. Tsurutani, Dimitris Vassiliadis, Simon Wing, Jesper W. Gjerloev, Jay Johnson, Massimo Materassi, Tommaso Alberti, Constantinos Papadimitriou, Pouya Manshour, Adamantia Zoe Boutsi, Mirko Stumpo

Faculty Publications

Learning from successful applications of methods originating in statistical mechanics, complex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between normal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly …

The Characteristics Of Successful Military It Projects: A Cross-Country Empirical Study, Helene Berg, Jonathan D. Ritschel

Faculty Publications

In the armed forces, successful digitalization is crucial to ensure effective operations. Much of the existing literature on project factors during the planning and execution phases of public IT projects do not focus specifically on military sector projects. Therefore, the paper aims to provide empirical insights into the characteristics of successful military IT projects. Data from such projects in NATO countries and agencies were collected through interviews and project documents. The findings relating to the main variable of interest, “delivery of client benefit,” supported previous findings on IT project performance. Medium-sized projects performed better than small and large projects, and …

Electrically-Evoked Referred Sensations Induce Embodiment Of Rubber Limb, Anthony Nguyen, Brooke Draggoo, Brooklyn Tobias, Payton Dubose, Katharine Polasek

Faculty Publications

Introduction: Electrical stimulation is increasingly relevant in a variety of medical treatments. In this study, the quality of referred sensations evoked using surface electrical stimulation was evaluated using the rubber hand and foot illusions.

Methods: The rubber hand and foot illusions were attempted under 4 conditions: (1) multi-location tapping; (2) one-location tapping; (3) electrical stimulation of sensation referred to the hand or foot; (4) asynchronous control. The strength of each illusion was quantified using a questionnaire and proprioceptive drift, where a stronger response suggested embodiment of the rubber limb.

Results: 45 able-bodied individuals and two individuals with amputations participated in …

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

Cost Estimation Trends For Major Defense Acquisition Programs, Sammantha Jones, Edward D. White, Jonathan D. Ritschel, Shawn M. Valentine

Faculty Publications

The authors use both descriptive and inferential techniques to investigate average and standard deviation trends in cost estimates for major defense acquisition programs (MDAPs) grouped into decades from the 1970s to 2010s. For total program-cost-growth factors (CGFs), the 2010s exhibited lower CGFs compared to the 1990s. For the program-acquisition-unit cost (PAUC) CGFs, the 2010s appear lower than the 1990s and borderline lower than the 1970s. A statistically significant decreasing trend in the standard deviations of total program CGFs throughout the decades was identified. This lowering variability trend also appeared for PAUC CGFs from the 1980s onward. This finding appears to …

Domain Restriction Zones: An Evolution Of The Military Exclusion Zone, Cole M. Mooty, Robert A. Bettinger, Mark G. Reith

Faculty Publications

Since the early part of the twenty-first century, US adversaries have expanded their military capabilities within and their access to new warfighting domains. When faced with the growth of adversaries’ asymmetric capabilities, the means, tactics, and strategies previously used by the US military lose their proportional effectiveness. To avoid such degradation of capability, the operational concept of the military exclusion zone (MEZ) should be revised to suit the modern battlespace while also addressing the shifts in national policy that encourage diplomacy over military force. The concept and development of domain restriction zones (DRZs) increase the relevancy of traditional MEZs in …

A Case For An Independent Cyber Force, Ian C. Heffron, Mark Reith, James W. Dean

Faculty Publications

Although cyberspace is considered the newest warfighting domain, military analysts and scholars have opined the United States remains woefully behind its peers in cyberspace and have called for the creation of a separate cyber service component. Yet a cohesive and robust discussion on this topic has yet to emerge. This article proposes a general framework that builds on the Joint doctrine, organization, training, materiel, leadership and education, personnel, facilities, and policy (DOTMLPF-P) analysis to address questions of sufficiency and necessity. Such analysis reveals DoD cyber operations do not maximize the United States’ ability to fight a cyber war, especially when …

Intrinsic Point Defects (Vacancies And Antisites) In Cdgep2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Peter G. Schunemann, Kevin T. Zawilski, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton

Faculty Publications

Cadmium germanium diphosphide (CdGeP₂) crystals, with versatile terahertz-generating properties, belong to the chalcopyrite family of nonlinear optical materials. Other widely investigated members of this family are ZnGeP₂ and CdSiP₂. The room-temperature absorption edge of CdGeP₂ is near 1.72 eV (720 nm). Cadmium vacancies, phosphorous vacancies, and germanium-on-cadmium antisites are present in as-grown CdGeP₂ crystals. These unintentional intrinsic point defects are best studied below room temperature with electron paramagnetic resonance (EPR) and optical absorption. Prior to exposure to light, the defects are in charge states that have no unpaired spins. Illuminating a CdGeP_{2 …}

Empowering Student Success: Unlocking The Potential Of Project-Based Steel Design Education, Aly Mousaad Aly

Faculty Publications

In the pursuit of student success, it is essential to acknowledge that a singular teaching style does not universally cater to all students. The educator's crucial role lies in creating an optimal learning environment that fosters students' endeavors to excel. This endeavor transcends mere classroom success or employment prospects, encompassing a broader impact on societal well-being. An experiential learning approach, where students actively engage in practical tasks, emerges as the most effective mode of instruction. Integrating project-based learning activities into the curriculum holds immense potential for enhancing student learning. Additionally, the utilization of analysis software tools like FTool and STAAD …

A Multi-Scale Method For Combined Design And Dispatch Optimization Of Nuclear Hybrid Energy Systems Including Storage, Daniel Hill, Dawson Mccrea, An Ho, Matthew Memmott, Kody Powell, John Hedengren

Faculty Publications

Reliable, carbon-free power generation is increasing in importance. Nuclear-renewable hybrid energy systems (NHES) are a potential solution for current generation challenges, but design and dispatch optimization for these systems remains challenging particularly when stochastic effects, long time horizons and nonlinear modeling are needed. This work presents a multi-scale method for combining the design and dispatch optimization problems for nonlinear NHES over long time horizons. Rather than treating the entire horizon as a single optimization problem, a large number of combined optimization problems are solved for shorter samples of the horizon resulting in distributions of optimal capacities for each of the …

Academic Success And Retention Pathway For Mechanical Engineering Major, Paul Akangah, Henry Ivuawuogu, Adeola Morawo, Andrea Nana Ofori-Boadu

Faculty Publications

Evaluating student success in higher education relies heavily on Grade Point Average (GPA), a measure determined by faculty through formative and summative assessments. Faculty determine these grades throughout the student's academic career. Society often equates higher grades with greater intelligence and engagement, assuming students work independently. Grades are also a means to measure or quantify learning and intellectual progress during students' academic careers. However, when students resort to unsanctioned online resources (UORs) using applications like Chegg, Course Hero, and Slader, the student may obtain good grades, but understanding and learning are grossly sacrificed. This study investigates the performance of 100 …

Optimal Estimation Inversion Of Ionospheric Electron Density From Gnss-Pod Limb Measurements: Part I-Algorithm And Morphology, Dong L. Wu, Nimalan Swarnalingam, Cornelius C. J. H. Salinas, Daniel J. Emmons, Tyler C. Summers, Robert Gardiner-Garden

Faculty Publications

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (Ne). In this study, we developed an optimal estimation (OE) method to retrieve Ne profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the Ne inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large Ne oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric Ne morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the Ne variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links.

Advancing Flame Retardant Prediction: A Self-Enforcing Machine Learning Approach For Small Datasets, Cheng Yan, Xiang Lin, Xiaming Feng, Hongyu Yang, Patrick Mensah, Guoqiang Li

Faculty Publications

Improving the fireproof performance of polymers is crucial for ensuring human safety and enabling future space colonization. However, the complexity of the mechanisms for flame retardant and the need for customized material design pose significant challenges. To address these issues, we propose a machine learning (ML) framework based on substructure fingerprinting and self-enforcing deep neural networks (SDNN) to predict the fireproof performance of flame-retardant epoxy resins. Our model is based on a comprehensive understanding of the physical mechanisms of materials and can predict fireproof performance and eliminate the needs for properties descriptors, making it more convenient than previous ML models. …

Intrinsically Stretchable Three Primary Light-Emitting Films Enabled By Elastomer Blend For Polymer Light-Emitting Diodes, Min Woo Jeong, Jin Hyun Ma, Jae Sung Shin, Jun Su Kim, Guorong Ma, Tae Uk Nam, Xiaodan Gu, Seong Jun Kang, Jin Young Oh

Faculty Publications

Intrinsically stretchable light-emitting materials are crucial for skin-like wearable displays; however, their color range has been limited to green-like yellow lights owing to the restricted stretchable light-emitting materials (super yellow series materials). To develop skin-like full-color displays, three intrinsically stretchable primary light-emitting materials [red, green, and blue (RGB)] are essential. In this study, we report three highly stretchable primary light-emitting films made from a polymer blend of conventional RGB light-emitting polymers and a nonpolar elastomer. The blend films consist of multidimensional nanodomains of light-emitting polymers that are interconnected in an elastomer matrix for efficient light-emitting under strain. The RGB blend …