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- Genre: Academic theses
- Creators: Phelan, Patrick
Description
Additive manufacturing, also known as 3-dimensional (3-d) printing, is now a rapidly growing manufacturing technique. Innovative and complex designs in various aspects of engineering have called for more efficient manufacturing techniques and 3-d printing has been a perfect choice in that direction. This research investigates the use of additive manufacturing in fabricating polymer heat exchangers and estimate their effectiveness as a heat transfer device. Fused Deposition Modeling (FDM), Selective Laser Sintering (SLS) and Stereolithography (SLA) are the three 3-d printing techniques that are explored for their feasibility in manufacturing heat exchangers. The research also explores a triply periodic minimal structure–the gyroid, as a heat exchanger design. The performance of the gyroid heat exchanger was studied using experiments. The main parameters considered for the experiments were heat transfer rate, effectiveness and pressure drop. From the results obtained it can be inferred that using polymers in heat exchangers helps reducing corrosion and fouling problems, but it affects the effectiveness of the heat exchangers. For our design, the maximum effectiveness achieved was 0.1. The pressure drop for the heat exchanger was observed to decrease with an increase in flow rate and the maximum pressure drop measured was 0.88 psi for a flow rate of 5 LPM.
ContributorsDanayat, Swapneel Shailesh (Author) / Phelan, Patrick (Thesis advisor) / Kwon, Beomjin (Committee member) / Azeredo, Bruno (Committee member) / Arizona State University (Publisher)
Created2019
Description
This thesis presents efficient implementations of several linear algebra kernels, machine learning kernels and a neural network based recommender systems engine onto a massively parallel reconfigurable architecture, Transformer. The linear algebra kernels include Triangular Matrix Solver (TRSM), LU Decomposition (LUD), QR Decomposition (QRD), and Matrix Inversion. The machine learning kernels include an LSTM (Long Short Term Memory) cell, and a GRU (gated Recurrent Unit) cell used in recurrent neural networks. The neural network based recommender systems engine consists of multiple kernels including fully connected layers, embedding layer, 1-D batchnorm, Adam optimizer, etc.
Transformer is a massively parallel reconfigurable multicore architecture designed at the University of Michigan. The Transformer configuration considered here is 4 tiles and 16 General Processing Elements (GPEs) per tile. It supports a two level cache hierarchy where the L1 and L2 caches can operate in shared (S) or private (P) modes. The architecture was modeled using Gem5 and cycle accurate simulations were done to evaluate the performance in terms of execution times, giga-operations per second per Watt (GOPS/W), and giga-floating-point-operations per second per Watt (GFLOPS/W).
This thesis shows that for linear algebra kernels, each kernel achieves high performance for a certain cache mode and that this cache mode can change when the matrix size changes. For instance, for smaller matrix sizes, L1P, L2P cache mode is best for TRSM, while L1S, L2S is the best cache mode for LUD, and L1P, L2S is the best for QRD. For each kernel, the optimal cache mode changes when the matrix size is increased. For instance, for TRSM, the L1P, L2P cache mode is best for smaller matrix sizes ($N=64, 128, 256, 512$) and it changes to L1S, L2P for larger matrix sizes ($N=1024$). For machine learning kernels, L1P, L2P is the best cache mode for all network parameter sizes.
Gem5 simulations show that the peak performance for TRSM, LUD, QRD and Matrix Inverse in the 14nm node is 97.5, 59.4, 133.0 and 83.05 GFLOPS/W, respectively. For LSTM and GRU, the peak performance is 44.06 and 69.3 GFLOPS/W.
The neural network based recommender system was implemented in L1S, L2S cache mode. It includes a forward pass and a backward pass and is significantly more complex in terms of both computational complexity and data movement. The most computationally intensive block is the fully connected layer followed by Adam optimizer. The overall performance of the recommender systems engine is 54.55 GFLOPS/W and 169.12 GOPS/W.
Transformer is a massively parallel reconfigurable multicore architecture designed at the University of Michigan. The Transformer configuration considered here is 4 tiles and 16 General Processing Elements (GPEs) per tile. It supports a two level cache hierarchy where the L1 and L2 caches can operate in shared (S) or private (P) modes. The architecture was modeled using Gem5 and cycle accurate simulations were done to evaluate the performance in terms of execution times, giga-operations per second per Watt (GOPS/W), and giga-floating-point-operations per second per Watt (GFLOPS/W).
This thesis shows that for linear algebra kernels, each kernel achieves high performance for a certain cache mode and that this cache mode can change when the matrix size changes. For instance, for smaller matrix sizes, L1P, L2P cache mode is best for TRSM, while L1S, L2S is the best cache mode for LUD, and L1P, L2S is the best for QRD. For each kernel, the optimal cache mode changes when the matrix size is increased. For instance, for TRSM, the L1P, L2P cache mode is best for smaller matrix sizes ($N=64, 128, 256, 512$) and it changes to L1S, L2P for larger matrix sizes ($N=1024$). For machine learning kernels, L1P, L2P is the best cache mode for all network parameter sizes.
Gem5 simulations show that the peak performance for TRSM, LUD, QRD and Matrix Inverse in the 14nm node is 97.5, 59.4, 133.0 and 83.05 GFLOPS/W, respectively. For LSTM and GRU, the peak performance is 44.06 and 69.3 GFLOPS/W.
The neural network based recommender system was implemented in L1S, L2S cache mode. It includes a forward pass and a backward pass and is significantly more complex in terms of both computational complexity and data movement. The most computationally intensive block is the fully connected layer followed by Adam optimizer. The overall performance of the recommender systems engine is 54.55 GFLOPS/W and 169.12 GOPS/W.
ContributorsSoorishetty, Anuraag (Author) / Chakrabarti, Chaitali (Thesis advisor) / Kim, Hun Seok (Committee member) / LiKamWa, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
In nature, it is commonly observed that animals and birds perform movement-based thermoregulation activities to regulate their body temperatures. For example, flapping of elephant ears or plumage fluffing in birds. Taking inspiration from nature and to explore the possibilities of such heat transfer enhancements, augmentation of heat transfer rates induced by the vibration of solid and well as novel flexible pinned heatsinks were studied in this research project. Enhancement of natural convection has always been very important in improving the performance of the cooling mechanisms. In this research, flexible heatsinks were developed and they were characterized based on natural convection cooling with moderately vibrating conditions. The vibration of heated surfaces such as motor surfaces, condenser surfaces, robotic arms and exoskeletons led to the motivation of the development of heat sinks having flexible fins with an improved heat transfer capacity. The performance of an inflexible, solid copper pin fin heat sink was considered as the baseline, current industry standard for the thermal performance. It is expected to obtain maximum convective heat transfer at the resonance frequency of the flexible pin fins. Current experimental results with fixed input frequency and varying amplitudes indicate that the vibration provides a moderate improvement in convective heat transfer, however, the flexibility of fins had negligible effects.
ContributorsPrabhu, Saurabh (Author) / Rykaczewski, Konrad (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
It is well known that radiative heat transfer rate can exceed that between two blackbodies by several orders of magnitude due to the coupling of evanescent waves. One promising application of near-field thermal radiation is thermophotovoltaic (TPV) devices, which convert thermal energy to electricity. Recently, different types of metamaterials with excitations of surface plasmon polaritons (SPPs)/surface phonon polaritons (SPhPs), magnetic polaritons (MP), and hyperbolic modes (HM), have been studied to further improve near-field radiative heat flux and conversion efficiency. On the other hand, near-field experimental demonstration between planar surfaces has been limited due to the extreme challenge in the vacuum gap control as well as the parallelism.
The main objective of this work is to experimentally study the near-field radiative transfer and the excitation of resonance modes by designing nanostructured thin films separated by nanometer vacuum gaps. In particular, the near-field radiative heat transfer between two parallel plates of intrinsic silicon wafers coated with a thin film of aluminum nanostructure is investigated. In addition, theoretical studies about the effects of different physical mechanisms such as SPhP/SPP, MPs, and HM on near-field radiative transfer in various nanostructured metamaterials are conducted particularly for near-field TPV applications. Numerical simulations are performed by using multilayer transfer matrix method, rigorous coupled wave analysis, and finite difference time domain techniques incorporated with fluctuational electrodynamics. The understanding gained here will undoubtedly benefit the spectral control of near-field thermal radiation for energy-harvesting applications like thermophotovoltaic energy conversion and radiation-based thermal management.
The main objective of this work is to experimentally study the near-field radiative transfer and the excitation of resonance modes by designing nanostructured thin films separated by nanometer vacuum gaps. In particular, the near-field radiative heat transfer between two parallel plates of intrinsic silicon wafers coated with a thin film of aluminum nanostructure is investigated. In addition, theoretical studies about the effects of different physical mechanisms such as SPhP/SPP, MPs, and HM on near-field radiative transfer in various nanostructured metamaterials are conducted particularly for near-field TPV applications. Numerical simulations are performed by using multilayer transfer matrix method, rigorous coupled wave analysis, and finite difference time domain techniques incorporated with fluctuational electrodynamics. The understanding gained here will undoubtedly benefit the spectral control of near-field thermal radiation for energy-harvesting applications like thermophotovoltaic energy conversion and radiation-based thermal management.
ContributorsSabbaghi, Payam (Author) / Wang, Liping (Thesis advisor) / Phelan, Patrick (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Robert (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Phononic crystals are artificially engineered materials that can forbid phonon propagation in a specific frequency range that is referred to as a “phononic band gap.” Phononic crystals that have band gaps in the GHz to THz range can potentially enable sophisticated control over thermal transport with “phononic devices”. Calculations of the phononic band diagram are the standard method of determining if a given phononic crystal structure has a band gap. However, calculating the phononic band diagram is a computationally expensive and time-consuming process that can require sophisticated modeling and coding. In addition to this computational burden, the inverse process of designing a phononic crystal with a specific band gap center frequency and width is a challenging problem that requires extensive trial-and-error work.
In this dissertation, I first present colloidal nanocrystal superlattices as a new class of three-dimensional phononic crystals with periodicity in the sub-20 nm size regime using the plane wave expansion method. These calculations show that colloidal nanocrystal superlattices possess phononic band gaps with center frequencies in the 102 GHz range and widths in the 101 GHz range. Varying the colloidal nanocrystal size and composition provides additional opportunities to fine-tune the phononic band gap. This suggests that colloidal nanocrystal superlattices are a promising platform for the creation of high frequency phononic crystals.
For the next topic, I explore opportunities to use supervised machine learning for expedited discovery of phononic band gap presence, center frequency and width for over 14,000 two-dimensional phononic crystal structures. The best trained model predicts band gap formation, center frequencies and band gap widths, with 94% accuracy and coefficients of determination (R2) values of 0.66 and 0.83, respectively.
Lastly, I expand the above machine learning approach to use machine learning to design a phononic crystal for a given set of phononic band gap properties. The best model could predict elastic modulus of host and inclusion, density of host and inclusion, and diameter-to-lattice constant ratio for target center and width frequencies with coefficients of determinations of 0.94, 0.98, 0.94, 0.71, and 0.94 respectively. The high values coefficients of determination represents great opportunity for phononic crystal design.
In this dissertation, I first present colloidal nanocrystal superlattices as a new class of three-dimensional phononic crystals with periodicity in the sub-20 nm size regime using the plane wave expansion method. These calculations show that colloidal nanocrystal superlattices possess phononic band gaps with center frequencies in the 102 GHz range and widths in the 101 GHz range. Varying the colloidal nanocrystal size and composition provides additional opportunities to fine-tune the phononic band gap. This suggests that colloidal nanocrystal superlattices are a promising platform for the creation of high frequency phononic crystals.
For the next topic, I explore opportunities to use supervised machine learning for expedited discovery of phononic band gap presence, center frequency and width for over 14,000 two-dimensional phononic crystal structures. The best trained model predicts band gap formation, center frequencies and band gap widths, with 94% accuracy and coefficients of determination (R2) values of 0.66 and 0.83, respectively.
Lastly, I expand the above machine learning approach to use machine learning to design a phononic crystal for a given set of phononic band gap properties. The best model could predict elastic modulus of host and inclusion, density of host and inclusion, and diameter-to-lattice constant ratio for target center and width frequencies with coefficients of determinations of 0.94, 0.98, 0.94, 0.71, and 0.94 respectively. The high values coefficients of determination represents great opportunity for phononic crystal design.
ContributorsSadat, Seid Mohamadali (Author) / Wang, Robert Y (Thesis advisor) / Huang, Huei-Ping (Committee member) / Ankit, Kumar (Committee member) / Wang, Liping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2020
Description
The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed system was developed in order to fluidize nanoparticles. The system was tested and the parameters optimized using two commercially available TiO2 nanoparticles: P25 and P90. The fluidization quality was assessed by determining the non-dimensional bed height as well as the non-dimensional pressure drop. The non-dimensional bed height for the nanosized TiO2 in the MVA system optimized at about 5 and 7 for P25 and P90 TiO2, respectively, at a resonance frequency of 50 Hz. The non-dimensional pressure drop was also determined and showed that the MVA system exhibited a lower minimum fluidization velocity for both of the TiO2 types as compared to fluidization that employed only vibration assistance. Additional experiments were performed with the MVA to characterize the synergistic effects of vibrational intensity and gas velocity on the TiO2 P25 and P90 fluidized bed heights. Mathematical relationships were developed to correlate vibrational intensity, gas velocity, and fluidized bed height in the MVA. The non-dimensional bed height in the MVA system is comparable to previously published P25 TiO2 fluidization work that employed an alcohol in order to minimize the electrostatic attractions within the bed. However, the MVA system achieved similar results without the addition of a chemical, thereby expanding the potential chemical reaction engineering and environmental remediation opportunities for fluidized nanoparticle systems.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
ContributorsAn, Keju (Author) / Andino, Jean (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Adrian, Ronald (Committee member) / Emady, Heather (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019
Description
This work describes an approach for distance computation between agents in a
multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof-
Arrival (AoA) data and local trajectory data. Each agent in the swarm is able
to discretely determine distance and bearing to every other neighbor agent in the
swarm. From this information, I propose a lightweight method for sensor coverage
of an unknown area based on the work of Sameera Poduri. I also show that this
technique performs well with limited calibration distances.
multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof-
Arrival (AoA) data and local trajectory data. Each agent in the swarm is able
to discretely determine distance and bearing to every other neighbor agent in the
swarm. From this information, I propose a lightweight method for sensor coverage
of an unknown area based on the work of Sameera Poduri. I also show that this
technique performs well with limited calibration distances.
ContributorsMulford, Philip (Author) / Das, Jnaneshwar (Thesis advisor) / Takahashi, Timothy (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2020
Description
Deformable heat exchangers could provide a multitude of previously untapped advantages ranging from adaptable performance via macroscale, dynamic shape change (akin to dilation/constriction seen in blood vessels) to enhanced heat transfer at thermal interfaces through microscale, surface deformations. So far, making deformable, ‘soft heat exchangers’ (SHXs) has been limited by the low thermal conductivity of materials with suitable mechanical properties. The recent introduction of liquid-metal embedded elastomers by Bartlett et al1 has addressed this need. Specifically, by remaining soft and stretchable despite the addition of filler, these thermally conductive composites provide an ideal material for the new class of “soft thermal systems”, which is introduced in this work. Understanding such thermal systems will be a key element in enabling technology that require high levels of stretchability, such as thermoregulatory garments, soft electronics, wearable electronics, and high-powered robotics. Shape change inherent to SHX operation has the potential to violate many conventional assumptions used in HX design and thus requires the development of new theoretical approaches to predict performance. To create a basis for understanding these devices, this work highlights two sequential studies. First, the effects of transitioning to a surface deformable, SHX under steady state static conditions in the setting of a liquid cooling device for thermoregulation, electronics and robotics applications was explored. In this study, a thermomechanical model was built and validated to predict the thermal performance and a system wide analysis to optimize such devices was carried out. Second, from a more fundamental perspective, the effects of SHXs undergoing transient shape deformation during operation was explored. A phase shift phenomenon in cooling performance dependent on stretch rate, stretch extent and thermal diffusivity was discovered and explained. With the use of a time scale analysis, the extent of quasi-static assumption viability in modeling such systems was quantified and multiple shape modulation regime limits were defined. Finally, nuance considerations and future work of using liquid metal-silicone composites in SHXs were discussed.
ContributorsKotagama, Praveen (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Green, Matthew (Committee member) / Arizona State University (Publisher)
Created2020
Description
The relationship between settler-colonial governments and Indigenous nations has been a contentious one, filled with disingenuity and fueled by the abuse of power dynamics. Specifically, colonial governments have repeatedly used power in mapping, cultural Othering, resource control, and research methodologies to assimilate, acculturate, or otherwise dominate every aspect of Indigenous lives. A relatively recent pushback from Indigenous peoples led to the slow reclamation of sovereignty, including in the United States. Revamped federal Indian programs allegedly promote tribal self-determination, yet they paradoxically serve a vast quantity of cultures through singular blanket programs that are blind to the cultural component of Indigenous identity - the centerfold of colonial aggression for centuries. The U.S. Department of Housing and Urban Development’s Office of Public and Indian Housing is no exception, using a Western framework to provide generic services that neither serve cultural needs nor are tailored to the specific environment traditional homes were historically and epistemologically suited for. This research analyzes the successes of new programs as well as the failures of the federal government to conduct responsible research and promote the authentic self-determination of tribes in terms of housing and urban development. It also considers the successes and failures of tribes to effectively engage in program reformation negotiation, community planning, and accountability measures to ensure their communities are served with enough culturally-appropriate, sustainable housing without mistrusting their own housing entities. Solutions for revising this service gap are proposed, adhering to a framework that centers diverse cultural values, community input, and functional design to increase each tribe’s implementation of self-determination in HUD housing programs.
ContributorsDeVault, Kayla (Author) / Martinez, David (Thesis advisor) / Hale, Michelle (Thesis advisor) / Phelan, Patrick (Committee member) / Dalla Costa, Wanda (Committee member) / Arizona State University (Publisher)
Created2020
Description
Gas Dynamic Virtual Nozzles (GDVN) produce microscopic flow-focused liquid jets and are widely used for sample delivery in serial femtosecond crystallography (SFX) and time-resolved solution scattering. Recently, 2-photon polymerization (2PP) made it possible to produce 3D-printed GDVNs with submicron printing resolution. Comparing with hand- fabricated nozzles, reproducibility, and less developing effort, and similarity of the performance of different 3D printed nozzles are among the advantages of using 3D printing techniques to develop GDVN’s. Submicron printing resolution also makes it possible to easily improve GDVN performance by optimizing the design of nozzles. In this study, 3D printed nozzles were developed to achieve low liquid and gas flow rates and high liquid jet velocities. A double-pulsed nanosecond laser imaging system was used to perform Particle Tracking Velocimetry (PTV) in order to determine jet velocities and assess jet stability/reproducibility. The testing results of pure water jets focused with He sheath gas showed that some designs can easily achieve stable liquid jets with velocities of more than 80 m/s, with pure water flowing at 3 microliters/min, and helium sheath gas flowing at less than 5 mg/min respectively. A numerical simulation pipeline was also used to characterize the performance of different 3D printed GDVNs. The results highlight the potential of making reproducible GDVNs with minimum fabrication effort, that can meet the requirements of present and future SFX and time-resolved solution scattering research.
ContributorsNazari, Reza (Author) / Adrian, Ronald (Thesis advisor) / Kirian, Richard (Thesis advisor) / Herrmann, Marcus (Committee member) / Phelan, Patrick (Committee member) / Weierstall, Uwe (Committee member) / Arizona State University (Publisher)
Created2020