Margie and Bill Klesse College of Engineering and Integrated Design
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Browsing Margie and Bill Klesse College of Engineering and Integrated Design by Department "Mechanical Engineering"
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Item A 3D Printed Linear Pneumatic Actuator for Position, Force and Impedance Control(2018-05-24) Krause, Jeremy; Bhounsule, PranavAlthough 3D printing has the potential to provide greater customization and to reduce the costs of creating actuators for industrial applications, the 3D printing of actuators is still a relatively new concept. We have developed a pneumatic actuator with 3D-printed parts and placed sensors for position and force control. So far, 3D printing has been used to create pneumatic actuators of the bellows type, thus having a limited travel distance, utilizing low pressures for actuation and being capable of only limited force production and response rates. In contrast, our actuator is linear with a large travel distance and operating at a relatively higher pressure, thus providing great forces and response rates, and this the main novelty of the work. We demonstrate solutions to key challenges that arise during the design and fabrication of 3D-printed linear actuators. These include: (1) the strategic use of metallic parts in high stress areas (i.e., the piston rod); (2) post-processing of the inner surface of the cylinder for smooth finish; (3) piston head design and seal placement for strong and leak-proof action; and (4) sensor choice and placement for position and force control. A permanent magnet placed in the piston head is detected using Hall effect sensors placed along the length of the cylinder to measure the position, and pressure sensors placed at the supply ports were used for force measurement. We demonstrate the actuator performing position, force and impedance control. Our work has the potential to open new avenues for creating less expensive, customizable and capable actuators for industrial and other applications.Item A GPU-Accelerated Particle Advection Methodology for 3D Lagrangian Coherent Structures in High-Speed Turbulent Boundary Layers(2023-06-19) Lagares, Christian; Araya, GuillermoIn this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian coherent structures (LCS) in large-scale direct numerical simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains, requiring efficient search algorithms in large, structured domains. While this article focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication.Item A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting(2016-01-19) Li, Zhaoxuan; Rahman, SM Mahbobur; Vega, Rolando; Dong, BingWe evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statistics such as mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), relative MBE (rMBE), mean percentage error (MPE) and relative RMSE (rRMSE). This work provides findings on how forecasts from individual inverters will improve the total solar power generation forecast of the PV system.Item A Miniature 3D Printed On-Off Linear Pneumatic Actuator and Its Demonstration into a Cartoon Character of a Hopping Lamp(2019-10-17) Nall, Christian L.; Bhounsule, Pranav A.Although 3D printing has been extensively used to create passive machines and mechanisms, 3D printing of actuators is a relatively new concept. 3D printing of actuators allows greater customization, accelerates the design and development, and consequently saves time and money. We present the design and fabrication of a 3D printed, miniature size, double-acting, On-Off type, linear pneumatic actuator. The actuator has an overall length of 8 cm, a bore size of 1.5 cm, and a stroke length of 2.0 cm. The overall weight is 12 gm and it generates a peak output power of 2 W when operating at an input air pressure of 40 psi (275.79 kPa). This paper demonstrates novel methods to solve the challenges that arise during fabrication that include: (1) chemical post-processing to achieve airtight sealing and a smooth surface finish, (2) strategic placement of a metallic part within 3D printed plastic for higher strength, (3) design of an airtight seal between the cylinder and piston head, (4) chemical bonding of printed parts using adhesive, and (5) use of a lubricant to reduce friction and improve force generation. The power-to-weight ratio of our actuator is comparable to that of high-end commercial actuators of similar size. The utility of the actuator is demonstrated in a series of jumping experiments with the actuator and by incorporating the actuator into a hopping robot inspired by Disney/Pixar Luxo lamp. We conclude that 3D printed pneumatic actuators combine the high power of pneumatics with the low weight of plastics, and structural strength through the selective placement of metal parts, thus offering a promising actuator for robotic applications.Item A Neural Network Powered Solution Approach for Computationally Expensive Mixed Integer Programs for Bio Jet-fuel Supply Chain Network Design(Association for Computing Machinery, 2023-05-09) Keith, Kolton; Castillo-Villar, Krystel K.; Alaeddini, AdelBio jet fuels derived from feedstock offer a sustainable alternative to meeting energy needs. Modeling supply chains that produce said fuels can lead to computationally prohibitive mixed integer linear programs (MILP) that consider optimal facility location and materials routing. The present work proposes an iterative machine learning-based hybrid solution procedure that transfers some of the responsibility of facility location to the learner. First, given a random selection of facility locations, a collection of model solutions is generated. Next, a neural network is fit to the collection of solutions, with facility locations being the input and total supply chain (SC) costs as the output. Then, the next set of locations is selected to optimize the predicted output of the neural network. Finally, the MILP optimization model is called to test the selected locations, and the results are fed back into the neural network and the process is repeated. Numerical experimentation demonstrates the proposed solution procedures yield near-optimal solutions with 0.10-0.18% increase in objective function value alongside a 40-65% reduction in computational time.Item A Novel Mechanically Overdamped Actuator with Adjustable Stiffness (MOD-AwAS) for Safe Interaction and Accurate Positioning(2017-06-28) Lee, Jae Hoon; Wahrmund, Christian; Jafari, AmirThis paper presents the design and development of a novel mechanically overdamped actuator with adjustable stiffness (MOD-AwAS). The novelty of MOD-AwAS compared to other variable stiffness actuators relates to its mechanical design, which prevents oscillations at the output link. Almost all variable stiffness actuators have an overshooting problem that require a sophisticated control algorithm to be able to perform accurate positioning. MOD-AwAS can regulate the stiffness from zero to its maximum (theoretically infinite) in less than 0.2 s by changing the position of the pivot point of its lever mechanisms. MOD-AwAS employs only one rotational spring with no pre-deflection, which gives it full accessibility to its energy storage capacity. Experimental results are presented to show the ability of MOD-AwAS to control its position accurately with a wide range of stiffness adjustment.Item A Principal Component Analysis in Switchgrass Chemical Composition(2016-11-04) Aboytes-Ojeda, Mario; Castillo-Villar, Krystel K.; Yu, Tun-hsiang E.; Boyer, Christopher N.; English, Burton C.; Larson, James A.; Kline, Lindsey M.; Labbé, NicoleIn recent years, bioenergy has become a promising renewable energy source that can potentially reduce the greenhouse emissions and generate economic growth in rural areas. Gaining understanding and controlling biomass chemical composition contributes to an efficient biofuel generation. This paper presents a principal component analysis (PCA) that shows the influence and relevance of selected controllable factors over the chemical composition of switchgrass and, therefore, in the generation of biofuels. The study introduces the following factors: (1) storage days; (2) particle size; (3) wrap type; and (4) weight of the bale. Results show that all the aforementioned factors have an influence in the chemical composition. The number of days that bales have been stored was the most significant factor regarding changes in chemical components due to its effect over principal components 1 and 2 (PC1 and PC2, approximately 80% of the total variance). The storage days are followed by the particle size, the weight of the bale and the type of wrap utilized to enclose the bale. An increment in the number of days (from 75–150 days to 225 days) in storage decreases the percentage of carbohydrates by −1.03% while content of ash increases by 6.56%.Item A Review of Methodological Approaches for the Design and Optimization of Wind Farms(2014-10-29) Herbert-Acero, José F.; Probst, Oliver; Réthoré, Pierre-Elouan; Larsen, Gunner Chr.; Castillo-Villar, Krystel K.This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research.Item An Innovative Polymeric Platform for Controlled and Localized Drug Delivery(2023-06-23) Elbjorn, Monica; Provencio, Jacob; Phillips, Paige; Sainz, Javier; Harrison, Noah; Di Rocco, David; Jaramillo, Ada; Jain, Priya; Lozano, Alejandro; Hood, R. LylePrecision medicine aims to optimize pharmacological treatments by considering patients' genetic, phenotypic, and environmental factors, enabling dosages personalized to the individual. To address challenges associated with oral and injectable administration approaches, implantable drug delivery systems have been developed. These systems overcome issues like patient adherence, bioavailability, and first-pass metabolism. Utilizing new combinations of biodegradable polymers, the proposed solution, a Polymeric Controlled Release System (PCRS), allows minimally invasive placement and controlled drug administration over several weeks. This study's objective was to show that the PCRS exhibits a linear biphasic controlled release profile, which would indicate potential as an effective treatment vehicle for cervical malignancies. An injection mold technique was developed for batch manufacturing of devices, and in vitro experiments demonstrated that the device's geometry and surface area could be varied to achieve various drug release profiles. This study's results motivate additional development of the PCRS to treat cervical cancer, as well as other malignancies, such as lung, testicular, and ovarian cancers.Item An Stochastic Cold Food Supply Chain (CFSC) Design(Association for Computing Machinery, 2023-05-09) Hernandez-Cuellar, David; Castillo-Villar, Krystel K.Produce supply chains are a critical part of the food industry, as they are responsible for ensuring that fruits and vegetables are delivered to customers on time, at the right cost, and with the desired quality. Over the past few decades, researchers have been proposing the usage of Hub-and-Spoke networks as a modeling method to optimize large-scale food supply chains. Traditional optimization of supply chains involves identifying and eliminating inefficiencies, reducing lead times, improving inventory management, enhancing supplier relationships, and leveraging technology to improve visibility and control over the entire process. However, the majority of previous models are deterministic and fail to consider the implicit variability of crop yields and the consequence of climate change on the agricultural supply. The increasing amount of CO2 in the atmosphere, along with the shifts in temperatures and weather patterns, may influence harvests. Consequently, forcing distributors and consumers to look up for different suppliers in other areas to compensate for the fluctuations in the supply of produce. In this research, a stochastic Hub-and-spoke network model and an optimization algorithm are proposed to reduce transportation costs by finding an optimal production, distribution, and transportation network while considering climate variability and its impact on crop yield. A case study for an stochastic Cold Food Supply Chain (CFSC) considering several scenarios with different weather conditions is created using climate models and real soil data for the state of California. Strawberry is studied in this work, given that California is one of the major strawberry-producing states in the U.S. The preliminary results of the analysis indicate that weather scenarios showing more precipitation are more likely to increase crop yield, while scenarios with less precipitation yield lower amounts of fresh fruit.Item Analysis and Development of a Small-Scale Supercritical Carbon Dioxide (sCO2) Brayton Cycle(2022-05-13) Patel, Raj C.; Bass, Diego C.; Dukuze, Ganza Prince; Andrade, Angelina; Combs, Christopher S.Carbon dioxide’s (CO2) ability to reach the supercritical phase (7.39 MPa and 304.15 K) with low thermal energy input is an advantageous feature in power generation design, allowing for the use of various heat sources in the cycle. A small-scale supercritical carbon dioxide (sCO2) power cycle operating on the principle of a closed-loop Brayton cycle is currently under construction at The University of Texas at San Antonio, to design and develop a small-scale indirect-fired sCO2 Brayton cycle, acquire validation data of the cycle's performance, and compare the cycle's performance to other cycles operating in similar conditions. The power cycle consists of four principal components: A reciprocating piston compressor, a heating source, a reciprocating piston expander to produce power, and a heat exchanger to dissipate excess heat. The work explained in the present manuscript describes the theory and analysis conducted to design the piston expander, heating source, and heat exchanger in the cycle. Theoretical calculations indicate that using sCO2 for the Brayton cycle generates 4.5 kW of power with the inlet pressure and temperature of 17.23 MPa and 358.15 K to the piston expander. Based on the fully isentropic conditions, the thermal efficiency of the system is estimated to be 12.75%.Item Animal Model Dependent Response to Pentagalloyl Glucose in Murine Abdominal Aortic Injury(2021-01-09) Anderson, Jennifer L.; Niedert, Elizabeth E.; Patnaik, Sourav S.; Tang, Renxiang; Holloway, Riley L.; Osteguin, Vangelina; Finol, Ender A.; Goergen, Craig J.Abdominal aortic aneurysms (AAAs) are a local dilation of the aorta and are associated with significant mortality due to rupture and treatment complications. There is a need for less invasive treatments to prevent aneurysm growth and rupture. In this study, we used two experimental murine models to evaluate the potential of pentagalloyl glucose (PGG), which is a polyphenolic tannin that binds to and crosslinks elastin and collagen, to preserve aortic compliance. Animals underwent surgical aortic injury and received 0.3% PGG or saline treatment on the adventitial surface of the infrarenal aorta. Seventeen mice underwent topical elastase injury, and 14 mice underwent topical calcium chloride injury. We collected high-frequency ultrasound images before surgery and at 3–4 timepoints after. There was no difference in the in vivo effective maximum diameter due to PGG treatment for either model. However, the CaCl2 model had significantly higher Green–Lagrange circumferential cyclic strain in PGG-treated animals (p < 0.05). While ex vivo pressure-inflation testing showed no difference between groups in either model, histology revealed reduced calcium deposits in the PGG treatment group with the CaCl2 model. These findings highlight the continued need for improved understanding of PGG's effects on the extracellular matrix and suggest that PGG may reduce arterial calcium accumulation.Item Arbitrary-Order Sensitivity Analysis of Eigenfrequency Problems with Hypercomplex Automatic Differentiation (HYPAD)(2023-06-14) Velasquez-Gonzalez, Juan C.; Navarro, Juan David; Aristizabal, Mauricio; Millwater, Harry R.; Montoya, Arturo; Restrepo, DavidThe calculation of accurate arbitrary-order sensitivities of eigenvalues and eigenvectors is crucial for structural analysis applications, including topology optimization, system identification, finite element model updating, damage detection, and fault diagnosis. Current approaches to obtaining sensitivities for eigenvalues and eigenvectors lack generality, are complicated to implement, prone to numerical errors, and are computationally expensive. In this work, a novel methodology is introduced that uses hypercomplex automatic differentiation (HYPAD) and semi-analytical expressions to obtain arbitrary-order sensitivities for eigenfrequency problems. The new methodology exhibits no sign of truncation nor subtractive cancellation errors regardless of the order of the sensitivity, it is general, and can obtain any high-order sensitivities with the simplicity of first-order computations. A numerical example is presented to verify the accuracy of the method, where the free vibration of a homogeneous cantilever beam is studied. For this problem, up to third-order sensitivities of the eigenvalues and eigenvectors with respect to the material and geometrical parameters were obtained, considering the cases of close and distinct eigenvalues. The results were verified using analytical equations, showing excellent agreement for the eigenvalues and the eigenvectors. The new method promises to facilitate the computation of sensitivities for eigenfrequency problems into routine practice and commercial software.Item Assessment and Modeling of Plasmonic Photothermal Therapy Delivered via a Fiberoptic Microneedle Device Ex Vivo(2021-12-10) Akhter, Forhad; Manrique-Bedoya, Santiago; Moreau, Chris; Smith, Andrea Lynn; Feng, Yusheng; Mayer, Kathryn M.; Hood, R. LylePlasmonic photothermal therapy (PPTT) has potential as a superior treatment method for pancreatic cancer, a disease with high mortality partially attributable to the currently non-selective treatment options. PPTT utilizes gold nanoparticles infused into a targeted tissue volume and exposed to a specific light wavelength to induce selective hyperthermia. The current study focuses on developing this approach within an ex vivo porcine pancreas model via an innovative fiberoptic microneedle device (FMD) for co-delivering light and gold nanoparticles. The effects of laser wavelengths (808 vs. 1064 nm), irradiances (20–50 mW·mm(−2)), and gold nanorod (GNR) concentrations (0.1–3 nM) on tissue temperature profiles were evaluated to assess and control hyperthermic generation. The GNRs had a peak absorbance at ~800 nm. Results showed that, at 808 nm, photon absorption and subsequent heat generation within tissue without GNRs was 65% less than 1064 nm. The combination of GNRs and 808 nm resulted in a 200% higher temperature rise than the 1064 nm under similar conditions. A computational model was developed to predict the temperature shift and was validated against experimental results with a deviation of <5%. These results show promise for both a predictive model and spatially selective, tunable treatment modality for pancreatic cancer.Item Biglycan and chondroitin sulfate play pivotal roles in bone toughness via retaining bound water in bone mineral matrix(Elsevier, 2020-09-28) Hua, Rui; Ni, Qingwen; Eliason, Travis D.; Han, Yan; Gu, Sumin; Nicolella, Daniel P.; Wang, Xiaodu; Jiang, Jean X.Recent in vitro evidence shows that glycosaminoglycans (GAGs) and proteoglycans (PGs) in bone matrix may functionally be involved in the tissue-level toughness of bone. In this study, we showed the effect of biglycan (Bgn), a small leucine-rich proteoglycan enriched in extracellular matrix of bone and the associated GAG subtype, chondroitin sulfate (CS), on the toughness of bone in vivo, using wild-type (WT) and Bgn deficient mice. The amount of total GAGs and CS in the mineralized compartment of Bgn KO mouse bone matrix decreased significantly, associated with the reduction of the toughness of bone, in comparison with those of WT mice. However, such differences between WT and Bgn KO mice diminished once the bound water was removed from bone matrix. In addition, CS was identified as the major subtype in bone matrix. We then supplemented CS to both WT and Bgn KO mice to test whether supplemental GAGs could improve the tissue-level toughness of bone. After intradermal administration of CS, the toughness of WT bone was greatly improved, with the GAGs and bound water amount in the bone matrix increased, while such improvement was not observed in Bgn KO mice or with supplementation of dermatan sulfate (DS). Moreover, CS supplemented WT mice exhibited higher bone mineral density and reduced osteoclastogenesis. Interestingly, Bgn KO bone did not show such differences irrespective of the intradermal administration of CS. In summary, the results of this study suggest that Bgn and CS in bone matrix play a pivotal role in imparting the toughness to bone most likely via retaining bound water in bone matrix. Moreover, supplementation of CS improves the toughness of bone in mouse models.Item Bioinspired design of hybrid composite materials(Taylor & Francis, 2018-11-24) Maghsoudi-Ganjeh, Mohammad; Lin, Liqiang; Wang, Xiaodu; Zeng, XiaoweiMimicking the natural design motifs of structural biological materials is a promising approach to achieve a unique combination of strength and toughness for engineering materials. In this study, we proposed a 2D computational model, which is a two-hierarchy hybrid composite inspired by the ultrastructural features of bone. The model is composed of alternating parallel array of two subunits (A & B) mimicking ‘mineralized collagen fibril’ and ‘extrafibrillar matrix’ of bone at ultrastructural level. The subunit-A is formed by short stiff platelets embedded within a soft matrix. The subunit-B consists of randomly distributed stiff grains bonded by a thin layer of tough adhesive phase. To assess the performance of the bioinspired design, a conventional unidirectional long-fiber composite made with the same amount of hard and soft phases was studied. The finite element simulation results indicated that the toughness, strength and elastic modulus of the bioinspired composite was 312%, 83%, and 55% of that of the conventional composite, respectively. The toughness improvement was attributed to the prevalent energy-dissipating damage of adhesive phase in subunit-B and crack-bridging by subunit-A, the two major toughening mechanisms in the model. This study exemplifies some insights into natural design of materials to gain better material performance.Item Biomechanical Restoration Potential of Pentagalloyl Glucose after Arterial Extracellular Matrix Degeneration(2019-07-03) Patnaik, Sourav S.; Piskin, Senol; Pillalamarri, Narasimha Rao; Romero, Gabriela; Escobar, G. Patricia; Sprague, Eugene; Finol, Ender A.The objective of this study was to quantify pentagalloyl glucose (PGG) mediated biomechanical restoration of degenerated extracellular matrix (ECM). Planar biaxial tensile testing was performed for native (N), enzyme-treated (collagenase and elastase) (E), and PGG (P) treated porcine abdominal aorta specimens (n = 6 per group). An Ogden material model was fitted to the stress–strain data and finite element computational analyses of simulated native aorta and aneurysmal abdominal aorta were performed. The maximum tensile stress of the N group was higher than that in both E and P groups for both circumferential (43.78 ± 14.18 kPa vs. 10.03 ± 2.68 kPa vs. 13.85 ± 3.02 kPa; p = 0.0226) and longitudinal directions (33.89 ± 8.98 kPa vs. 9.04 ± 2.68 kPa vs. 14.69 ± 5.88 kPa; p = 0.0441). Tensile moduli in the circumferential direction was found to be in descending order as N > P > E (195.6 ± 58.72 kPa > 81.8 ± 22.76 kPa > 46.51 ± 15.04 kPa; p = 0.0314), whereas no significant differences were found in the longitudinal direction (p = 0.1607). PGG binds to the hydrophobic core of arterial tissues and the crosslinking of ECM fibers is one of the possible explanations for the recovery of biomechanical properties observed in this study. PGG is a beneficial polyphenol that can be potentially translated to clinical practice for preventing rupture of the aneurysmal arterial wall.Item A block forward substitution method for solving the hypercomplex finite element system of equations(Elsevier, 2021-12-15) Aguirre-Mesa, Andres M.; Garcia, Manuel J.; Aristizabal, Mauricio; Wagner, David; Ramirez-Tamayo, Daniel; Montoya, Arturo; Millwater, HarryThe hypercomplex finite element method, ZFEM, allows the analyst to compute highly-accurate arbitrary-order shape, material property, and loading derivatives by augmenting the traditional finite element method with multiple imaginary degrees of freedom. In ZFEM, the real variables are converted to hypercomplex variables such as multicomplex, multidual, or quaternions. By uplifting the real variables to hypercomplex, derivatives are computed in an automated fashion using a standard finite element formulation. The use of multicomplex or multidual numbers provides higher-order derivatives. The drawback of ZFEM is that it increases the number of degrees of freedom of the real variable system by a factor 2^n, where n is the order of the required derivative. In consequence, ZFEM increases the memory consumption and the solution time of the system of equations compared to the real variable system. The block forward substitution method (BFS), proposed in this work, addresses the memory and runtime issues. This new method solves the original real-valued FEM system once. Then, the derivatives are computed using pseudo-loads with the original system of equations. In contrast with the conventional solution method of ZFEM, BFS computes the hypercomplex contributions to the stiffness matrix element-wise, and it never assembles nor solves the full hypercomplex system of equations. In effect, the BFS method generalizes the first-order semi-analytical complex variable method to any order derivative. The BFS method provides the capability to allow a combination of real-variable and hypercomplex-variable elements within the same model. The numerical results indicate that a first-order derivative can be obtained with 1% to 8% additional computational time of the real-variable analysis. This allows the computation of multiple first-order derivatives by post-processing of a single FEM analysis. Additionally, it was shown that fourth-order shape sensitivities can be computed in less than 5% additional runtime of the real-variable FEM analysis.Item Characterizing Conformational Change of a Thermoresponsive Polymeric Nanoparticle with Raman Spectroscopy(2023-06-19) Trabucco, Luis; Heath, Savannah; Shaw, Jonathan; McFadden, Sean; Wang, Xiaodu; Ye, Jing YongMolecular conformational changes in the collapsing and reswelling processes occurring during the phase transition at the lower critical solution temperature (LCST) of the polymer are not well understood. In this study, we characterized the conformational change of Poly(oligo(Ethylene Glycol) Methyl Ether Methacrylate)-144 (POEGMA-144) synthesized on silica nanoparticles using Raman spectroscopy and zeta potential measurements. Changes in distinct Raman peaks associated with the oligo(Ethylene Glycol) (OEG) side chains (1023, 1320, and 1499 cm−1) with respect to the methyl methacrylate (MMA) backbone (1608 cm−1) were observed and investigated under increasing and decreasing temperature profiles (34 ◦C to 50 ◦C) to evaluate the polymer collapse and reswelling around its LCST (42 ◦C). In contrast to the zeta potential measurements that monitor the change in surface charges as a whole during the phase transition, Raman spectroscopy provided more detailed information on vibrational modes of individual molecular moieties of the polymer in responding to the conformational change.Item CO2 Hydrogenation: Na Doping Promotes CO and Hydrocarbon Formation over Ru/m-ZrO2 at Elevated Pressures in Gas Phase Media(2023-03-24) Seuser, Grant; Staffel, Raechel; Hocaoglu, Yagmur; Upton, Gabriel F.; Garcia, Elijah S.; Cronauer, Donald C.; Kropf, A. Jeremy; Martinelli, Michela; Jacobs, GarySodium-promoted monoclinic zirconia supported ruthenium catalysts were tested for CO2 hydrogenation at 20 bar and a H2:CO2 ratio of 3:1. Although increasing sodium promotion, from 2.5% to 5% by weight, slightly decreased CO2 conversion (14% to 10%), it doubled the selectivity to both CO (~36% to ~71%) and chain growth products (~4% to ~8%) remarkably and reduced the methane selectivity by two-thirds (~60% to ~21%). For CO2 hydrogenation during in situ DRIFTS under atmospheric pressure, it was revealed that Na increases the catalyst basicity and suppresses the reactivity of Ru sites. Higher basicity facilitates CO2 adsorption, weakens the C–H bond of the formate intermediate promoting CO formation, and inhibits methanation occurring on ruthenium nanoparticle surfaces. The suppression of excessive hydrogenation increases the chain growth probability. Decelerated reduction during H2-TPR/TPR-MS and H2-TPR-EXAFS/XANES at the K-edge of ruthenium indicates that sodium is in contact with ruthenium. A comparison of the XANES spectra of unpromoted and Na-promoted catalysts after H2 reduction showed no evidence of a promoting effect involving electron charge transfer.