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George W. Woodruff School of Mechanical Engineering

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https://hdl.handle.net/1853/70728

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College of Engineering

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Advanced Mechanical Bipedal Experimental Robotics Lab

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Computational Reactor and Medical Physics Laboratory

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Cryo Lab

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Environmentally Conscious Design and Manufacturing

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Fusion Research Center

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Publication Search Results

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Categorization of additive manufacturing techniques for nuclear nonproliferation threat analysis

(Georgia Institute of Technology, 2023-12-08) Cannon, Natalie L.

Additive manufacturing, or AM, is a rapidly developing technology that simplifies and automates the production of intricate objects. Recently, AM methods have been imple- mented in the domains of nuclear weapons and nuclear enrichment technologies. However, there are presently limited international or domestic regulations for AM’s involvement in the nuclear sector, leading to unregulated proliferation pathways. Existing export regu- lations are broad in scope and do not account for the particular nuances of different AM techniques. It is crucial to scrutinize and assess the nuclear applications of AM methods to establish effective regulations and limitations for monitoring proliferation routes. This project involves identifying and assessing 31 of the most commonly employed AM meth- ods based on their potential impact on the nuclear fuel cycle. Using this identification and classification system, export controls can be directed at nuclear proliferation threats posed by AM, without disrupting the entire industry and fuel cycle. Additionally, this compre- hensive approach to regulating and monitoring proliferation channels would expose gaps in export regulations.
Calibration and Deployment of an Inertial Acoustic Vector Sensor for Autonomous Underwater Vehicles

(Georgia Institute of Technology, 2023-12-08) Lawrence, Andrew James

For underwater acoustic directionality experiments below 1 kHz, it can be challenging to deploy a sufficiently sized array of hydrophones. The required mounting system could be too large to deploy feasibly in many situations. An inertial vector sensor can act as a solution to this problem. A Wilcoxon VS-301 is an inertial vector sensor, and it contains a pressure sensor and a 3-axis accelerometer that measures the particle acceleration of the water near the sensor, which is a directional quantity. This allows for a much smaller mounting system, but it has its own limitations. The vector sensor is sensitive to vibrations from movement and needs extensive calibration to ensure accuracy, as the directionality measurements from the vector sensor are calculated by comparing the amplitude measured on multiple accelerometers. A mounting system with minimal material in the near field was chosen for its ability to minimize acoustic interference, and it was thoroughly tested to ensure it was insulated from non-acoustic vibrations. Two calibration methods were investigated to characterize the VS-301’s sensitivities: an acoustic shaker and a standing wave tube device. Both were investigated due to the difference in medium, as one experiment is conducted in air while the other is conducted in water. With the final mounting system design and confidence in the sensor’s calibration, directionality measurements were taken in a large water tank to ensure that an acoustic source could be located accurately within 5 degrees within a frequency band of 350-1300 Hz.
An investigation of programmable spatiotemporal defect and exceptional points in piezoelectric metamaterials

(Georgia Institute of Technology, 2023-12-05) Lima Thomes, Renan

From Newton's conceptualization of air as an arrangement of lumped spring-masses in the 17th century to the present day, the evolution of elastic wave manipulation has spanned centuries. In parallel, recently, the realm of piezoelectric shunt damping has evolved to synthetic impedance circuits, which enables digital programmability. Inspired by these developments, this thesis offers an experimental framework for the realization of two wave phenomena in elastic media: space-time wave localization and exceptional points (EPs). First, the concept of space-time wave localization using programmable defects is experimentally demonstrated. The dynamic properties of the local resonators of an electromechanical metamaterial, comprising piezoelectric elements connected to synthetic impedance circuits, are digitally controlled to modulate a trivial point defect in space and time. The experimental results show that the vibration energy is gradually transferred and localized over subsequent unit cells according to the defect position. In another topic, this thesis introduces an experimentally validated framework for creating tunable exceptional points in electromechanical waveguides. EPs are non-Hermitian singularities typically found in parity-time (PT) symmetric systems with balanced gain and loss. Here, piezoelectric transducers are shunted through synthetic impedance circuits that emulate resistors (responsible for the gain and loss) and inductors (responsible for the tunability), and whose properties can be programmed via software. While the inherent structural damping of the waveguide has the effect of breaking PT symmetry, we show that EPs can still be created by using non-trivial gain and loss combinations. Ultimately, the results in this thesis pave the way for the practical realization of space-time wave localization and EPs in elastic media, opening avenues for their application in novel wave devices.
Through-metal ultrasonic transmission focusing on thermal effects and couplant material selection

(Georgia Institute of Technology, 2023-12-05) Zhou, Allen Guang

Sealed metallic enclosures, such as nuclear waste containers, often contain sensors and other electrical components which require through-barrier charging and communication. However, practical design limits interfacing through metal barriers to feed-through wires, which are undesirable due to an imperfect seal on the enclosure, and electromagnetic waves cannot be used since the systems act as a Faraday cage. Ultrasonic power transfer is thus an important alternative for powering and communicating with such systems. A typical ultrasonic power transmission (UPT) system consists of two piezoelectric transducers bonded on either side of a metallic barrier, where the transducers transmit and receive elastic waves and convert the mechanical energy into electrical energy. Such single-barrier systems have been widely studied, though the effects of self-generated heat have not been studied in detail; various sources of loss (including dielectric and mechanical losses) exist within piezoelectric transducers, which lead to self-generated heat that may affect the efficiency of the UPT system. The heat generation and effects of temperature on UPT efficiency are studied using both numerical and experimental methods. While UPT systems with piezoelectric transducers directly (and permanently) bonded to either side of a metallic barrier typically present the best performance, it is important to also consider applications which require multiple sealed metallic enclosures that are coupled in a detachable way for power and data transmission between enclosures. Due to the non-bonded nature of these multi-stage systems, a couplant (gasket) material is key for ensuring good transmission. A range of couplant materials are tested for optimizing power transmission efficiency in first a semi-detachable UPT stage, and in a completely detachable “wand” UPT stage, where attachment methods are also examined to find the most efficient and practical design for both power and data transmission.
A Simulation Study of Electric Vehicle Traffic Patterns in Germany using Route Planning and Queuing Theory

(Georgia Institute of Technology, 2023-12-05) Sharma, Deeksha

As the effects of climate change become increasingly severe, car manufacturers are facing more pressure from the public to offer alternatives to gasoline-powered cars such as Battery Electrical Vehicles (BEVs). As the number of BEVs grows, so do the need for more charge stations to fuel these vehicles. Using documented traffic patterns from electrical vehicles, this thesis aims to simulate BEV drivers’ behavior within Germany and reduce the queues of these drivers by using optimal route planning in conjunction with a large-scale agent-based transport simulation framework, while also implementing queuing theory. In these simulations, route planning algorithm provides each of the drivers their ideal route and charging plan to maximize battery range and improved comfort. On the other hand, queuing theory helps elevate the realism of the simulations by modeling human behavior. By using these methods, real traffic data of German BEV drivers can be modeled within a Multi Agent Transport Simulation tool and then analyzed. The results show that with the increase of BEV population, the demand of certain charge stations grows uncontrollably, leading to bottlenecks in certain areas of Germany. However, using queuing theory to simulate drivers' queuing behavior can reduce average wait times. Moreover, this thesis also simulates futuristic scenarios, where the charging infrastructure is improved. These result in further shortened queue times. More realistic simulations of BEVs are needed to not only predict how these vehicles interact with one another but also to accurately plan for the demand of charge stations. To conclude, the thesis reveals that the traffic patterns of simulated BEV drivers lead to long queue times at certain charge stations when traveling on real traffic routes scenarios, but can be reduce with the implementation of a better charging infrastructure.
Cyber-resilience of machine learning-based digital twins for reactor autonomous control systems

(Georgia Institute of Technology, 2023-11-03) Yockey, Patience Christina

The prevalence of Machine Learning (ML) technology in industrial control systems (ICS) and operational technology (OT) environments is on the rise. Autonomous control systems (ACS) based on ML digital twins (DTs) are being proposed as a new way to control nuclear power plant (NPP) subsystems using data-driven analytics and stochastic modeling. However, the implementation of ACS in advanced reactor controls must be assessed for its resilience against adversarial action, given the increasing incidence of cyber-attacks against critical infrastructure and OT environments. This thesis delves into the implementation techniques and cyber-resilience of ML-based ACS designs for advanced reactors. Its recommendations provide security and safeguards for physical and digital systems to protect against cyber-attacks on ML algorithms. Two implementations of ACS were considered: one as a virtual testbed using the International Atomic Energy Agency (IAEA) Asherah pressurized water reactor (PWR) nuclear power plant simulator, and one as a cyber-physical testbed using the Western Services Corporation (WSC) Generic Pressurized Water Reactor (GPWR) and real-time programmable logic controller (PLC) data. The purpose was to determine the impact of cyber-attacks on ACS in both a medium and high-fidelity environment. Cyber-attacks targeting ACS’ ML models’ training data, real-time data, and architecture were conducted to encapsulate potential targets against ML DTs and determine the impact and associated cyber risk of using ML-based DTs in control environments.
A Transfer Function-Equivalent-Diffusion-based Approach for Monoenergetic Flux Prediction

(Georgia Institute of Technology, 2023-10-31) Painter, Bailey Christopher

Coupled Monte Carlo (MC) and thermal hydraulic (TH) analysis is valuable as a design or reference tool but can be slow especially when implemented in a Picard iteration. Previous work has developed a novel prediction block to achieve convergence with fewer MC simulations. The prediction works in two stages: (1) a surrogate-like model predicts macroscopic cross sections on-the-fly and (2) a first order perturbation (FOP) solver predicts the flux response to the updated cross sections. The main challenge with the prediction block is that the FOP model requires a fission matrix. This fission matrix is impractical to generate for most problems, particularly fine-mesh problems. This work investigates replacing the FOP solution with a monoenergetic diffusion solution. For a simple 1D boiling water reactor (BWR) pincell, the proposed prediction block produces a monoenergetic flux that is within good agreement of the MC flux. A realistic 3D pressurized water reactor (PWR) core is then introduced to demonstrate that 3D, coarse mesh problems require the application of equivalence parameters such as assembly discontinuity factors (ADFs) and superhomogenization (SPH) factors to produce accurate 1-group nodal diffusion solutions. This work investigates the implementation of the well-established Jacobian-free Newton Krylov (JFNK) method to produce these equivalence parameters in a time-efficient manner. In this case, only tens of one-group nodal diffusion solutions are required to produce converged equivalence parameters. The results obtained in this work show that the converged equivalence parameters are very successful in reproducing the heterogenous solution (up to 2.5% error for SPH and 0.3% error for ADFs), without needing to modify the nodal diffusion solution. In addition, the results show that ADFs yield the best agreement and are also stable (i.e., not varying) when thermal hydraulic fields are perturbed. These results suggest that the proposed prediction block methodology is rigorous.
Development of Additively Manufactured Molybdenum and Improvement via Lanthanum Oxide Addition

(Georgia Institute of Technology, 2023-08-30) Hutchinson, Andrew

Additive manufacturing (AM) technologies have provided an avenue for processing traditionally difficult to manufacture metals. Manufacturability of one such material, molybdenum, has remained on the forefront of challenges hindering its widespread application. In fact, the current manufacturing methods employed by Framatome to create sintering boats for fissionable fuel out of a molybdenum-lanthanum oxide alloy often result in residual stress buildup, defects, and subsequent part failure. Thus, the use of AM methods could provide a promising path to remediate the expensive operations and tooling needed to manufacture molybdenum parts. To date, work done on the additive manufacturing of molybdenum has focused on small scale parts with processes such as powder bed fusion. Novel investigation of both pure molybdenum and molybdenum alloyed with nanoparticle lanthanum oxide manufactured by a directed energy deposition – laser beam – powder blown (DED-LB-PB) AM process is presented in this work. Importantly, the discovery of process parameter sets corresponding to high densities of molybdenum is accomplished via response surface methodology experimental design. Maximum densities achieved are 96.99% and 99.87% in the pure molybdenum and alloyed molybdenum systems, respectively, thus demonstrating the capability of the DEDLB-PB method for manufacturing commercial parts with future work. Furthermore, microstructural characterization of the AM specimens produced has demonstrated the effectiveness of the nanoparticle lanthanum oxide addition to reduce grain size, reducing millimeter-tall grains to hundreds of microns. Accordingly, grain boundary cracking is reduced significantly, allowing for the creation of larger mechanical samples. The compression testing of these alloyed samples yielded an average strength of 217 MPa, further indicating the possibility of commercial part manufacturability. Chemical analysis data alluded to the loss of lanthana during the DED-LB-PB process. Dimensional stability and accuracy of parts made with the AM method showed relationships to varied parameters of laser power, scan speed, and mass flow, as well as to the addition of lanthana.
Automated Analysis of Differential Scanning Calorimetry Data for Shape Memory Alloys Using the Hough Transform

(Georgia Institute of Technology, 2023-08-30) Kennedy, Dylan T.

Modern materials research has been revolutionized by machine learning (ML) which uses large amounts of data to predict the properties of new materials. The analysis of this data represents a significant bottleneck in the development of ML models. This is especially true for shape memory alloys (SMAs), where phase transformations need to be characterized in addition to standard thermo-mechanical properties. Automating the data extraction process of database building can serve as a solution to this issue, allowing faster model deployment. Additionally, rapidly analyzing experimental data can allow databases to be established from larger and more densely populated search spaces, as these experiments can be easily performed if the desired data does not exist in literature. This work aims to develop a tool that will autonomously extract desired properties of SMAs from raw data collected from a differential scanning calorimetry (DSC) experiments for use in ML models
Modeling of Fluoride Molten Salt Reactor Depletion in SCALE

(Georgia Institute of Technology, 2023-08-28) Bayne, Christopher

Molten Salt Reactors (MSRs) are Gen IV nuclear reactor designs that use fissile material dissolved in high-temperature molten salt. MSRs feature safety and economic benefits through their low operating pressure, combined fuel and coolant into one component, and high thermal efficiency. Due to the historically limited demand for modeling MSRs, there has been no established tool explicitly designed for such a task. The SCALE reactor modeling software suite, developed and maintained by Oak Ridge National Laboratory (ORNL), is selected as a tool to examine MSR modeling capabilities. SCALE has been widely used, verified, and benchmarked for modeling of light water reactors (LWRs) and it would prove beneficial to demonstrate and evaluate its use for MSRs. This thesis focuses on graphite-moderated, FLiBe-fueled MSRs. It aims to determine the impacts and trade-offs for a given SCALE MSR depletion model between the user-defined simulation parameters, accuracy of the depletion simulation results and the computational resources. Accuracy of the depletion simulations was determined through comparison of criticality estimates (keff) and isotopic compositions of key nuclides across the lifetime of the reactor simulation. The simulation parameters considered include: depletion sub-interval schemes (coarse vs fine depletion step schemes); trace-element tracking (addnux parameters 2 through 4), self-shielding methods (CENTRM vs BONAMI); cross-section libraries (ENDF/B-VII.1 252-multigroup vs continuous-energy); and specific power (10 MW/MTIHM vs 20 MW/MTIHM). All analyses were conducted up to burnups of 62 GWd/MTIHM. Additionally, the parallel performance on two supercomputing clusters (Idaho National Laboratory’s Sawtooth cluster and Georgia Institute of Technology’s PACE-Firebird cluster) was analyzed. Major findings include: • From coarser to finer depletion schemes. Maximum actinide percent differences experienced little effect (~ 0.32%), but percent difference of nuclides of significant radioactivity experienced significantly higher (~5.10%). Computational runtime was affected linearly with each additional depletion step introduced into the scheme. keff was statistically unaffected (<10 pcm difference). • From BONAMI to CENTRM self-shielding, runtime experienced relatively small change (6.81% increase), ~226 ppm average difference in keff, and ~2.51% maximum difference of actinides and nuclides of significant radioactivity. • From addnux=2 to addnux=4 nuclide tracking, runtime experienced only a 6.33% increase for MG. keff was significantly affected (167 pcm difference, growing to ~500 pcm at EOL). For CE addnux variation, the criticality and isotopic concentration differences were near indistinguishable from that of MG, but the computational runtime experienced a ~4.7x increase from addnux=2 to addnux=4. The difference between addnux=2 and addnux=3 was significantly smaller than that of addnux=3 to addnux=4, suggesting that addnux=4 contains nuclides with significantly more effect on reactivity for fluoride-fueled, graphite-moderated MSRs (potentially H-3 and He-3 stemming from larger Li-7 concentrations). • From MG to CE runtime experienced significant increase (~10x longer). Actinide maximum difference was ~7%, while the nuclides of significant radioactivity exhibited ~4% maximum difference. • Depletion at 20MW/MTIHM over 10 MW/MTIHM yielded differences that were expected due to the inherent changes in the reactor core physics, thus suggesting that analyses presented in this thesis can be scaled to other fluoride-fueled, graphite-moderated MSRs of different specific powers