Matching Items (597)
Description
Total situational awareness is imperative for a healthy and safe grid. As more distributive energy resources (DERs) are connected to grid, the grid becomes more decentralized, meaning generation can be more widespread than relying solely on large plants burning fossil fuels or using water to spin generators far away from loads. Photovoltaic inverters are one such DER. They convert direct current (dc) which is produced by solar panels into alternating current (ac) to transmit on the grid. However, their advent introduces a variety of issues that must be tackled as utility companies and homeowners begin implementing more in everyday use. Voltage regulation can be difficult during times of high solar generation. In addition, if faults occur, they must be detected and cleared as soon as possible. Inverters are becoming smarter and their features can help solve some of these issues. Edge data (i.e. from inverters) must swiftly and securely reach a centralized controller for system operators to effectively take care of the grid. This is done with Supervisory Control and Data Acquisition (SCADA) protocols as well as internet connectivity through MQTT. In addition, operators must be able to send commands to individual generators to control power generation during peaks and dips to ensure grid stability. Thus, a secure two-way communications system is critical to achieving issues related to introducing greener energy sources. Once information from the edge-side inverter reaches the cloud, machine learning algorithms can use them to infer potential faults and locate them.
This report will dive into the details of why green DERs are being added to the grid, various SCADA protocols, the OSI model for internet connectivity, and present the lab work prepared, including modeling a real feeder in real time for communication testing and OpenDSS for fault studies. Two gateway devices are developed and implementation is extensively detailed. With voltage data from the inverters in the cloud, a number of machine learning algorithms are built and tested for high impedance fault detection on the feeder model. A summary of scientific contributions to the community is also given, including publications and presentations.
ContributorsMoldovan, Dan (Author) / Ayyanar, Raja (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Ranjram, Mike (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2024
Description
As the world shifts toward renewable energy, green hydrogen (H2) has emerged as a promising
solution for reducing emissions in sectors that are difficult to electrify. Thermochemical H2
production offers an alternative to electrolytic H2 production by using high-temperature redox
cycles. This individual research project focuses on the improvement of the fabrication methods
and eventual fabrication of a Labyrinth Reactor (LR) for thermochemically producing H2. The LR
is a compact system that uses a metal oxide, e.g. cerium oxide, to produce H2 through a two-step
metal oxide redox cycle. This cycle involves first reducing a metal oxide at high temperatures to
release oxygen. In the second step, the reduced metal oxide reacts with steam at a lower
temperature to be reoxidized, producing H2. Unlike many reactors that conduct this cycle in one
reaction zone, the LR physically separates this cycle into the reduction, heat recovery, and water
splitting zones. These zones are contained within an insulating firebrick cavity, where the metal
oxide weaves through a narrow path to each zone. This novel configuration fits a typically long
path into a small reactor volume. This allows for a compact design with a cyclical path, which
improves thermal efficiency and maximizes power density for a cost-effective H2 yield.
The reactor utilizes a firebrick insulating cavity with a path separating the three distinct zones.
This firebrick cavity required fabrication as it comprised of multiple layers of firebrick, each with
a distinct geometry, and additional firebrick components placed within the layers. The layers and
components were fabricated using a computer numerical control (CNC) milling machine. The
method for fabrication involved multiple steps; cutting the firebricks down to the desired size,
polishing the sides to be level, establishing the zero in the software used to control the CNC
machine, using various grinding bits to carve out the necessary path of each firebrick layer, and
assembling the layers to ensure they fit together securely. Throughout the fabrication process,
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several challenges were encountered, including uneven polishing, coordinate loss during CNC
operations, and deviations during grinding. These issues were addressed by optimizing spindle
speeds, shortening G-code runs, and reducing human error where possible. Additionally, CNC
processes were refined to improve accuracy.
The LR was developed from insights gained from teams around the world working on
thermochemical reactor systems. In particular, the LR design stems from the work done by
Sandia National Laboratories on the CR5 and Cascading Pressure Reactor. The first iteration,
version 1, of the LR was built and tested in ASU LightWorks® Laboratory. The testing resulted in
significant fractures within the firebrick layers and components. This led to the second iteration,
version 2, which involved a redesign of the firebrick layers to prevent these structural damages.
The focus of this research involves the fabrication process of version 2 of the LR. The fabricationprocess was improved through technique refinements, and design elements that made fabrication difficult were identified for future redesign. Ultimately, due to the complexity of
certain firebrick components, version 2 of the LR was not completed. Given the lengthy process,
it was decided that shifting focus to designing and fabricating a new LR iteration would be more
valuable. The constructed layers of version 2 were used for various testing. The lessons learned
through the fabrication process influenced the design of the third iteration of the LR, version 3.
Also, this project serves as a guide for best practices for future fabrication efforts.
Version 3 is far simpler in terms of layer geometry to expedite the fabrication process. Also,
the new iteration is larger, has more reactive material, and has the goal of producing 1g/hour of
H2. Version 3 is currently being fabricated by the ASU LightWorks® Laboratory and will then go on to be tested. Overall, this work contributes to LightWorks® Laboratory’s aim for the advancement of a thermochemical reactor for scalable green H2 production.
ContributorsHanabergh, Elena (Author) / Ermanoski, Ivan (Thesis director) / Miller, James (Committee member) / Ali, Natalia (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Sustainability (Contributor)
Created2025-05
Description
This research heavily involves improving the fabrication process of liquid metal soft strain (LMSS) sensors, which improves the robustness and sensitivity of the sensors. Traditional LMSS sensors can experience channel collapse as microchannels deform and lose conductivity under higher elongation when created manually without the use of advanced equipment. To address this issue, pressurizing the liquid metal (LM) was initially proposed as a solution after liquid metal sensors fabricated manually were characterized. After iterating the fabrication method with the use of a spin coater and a resin printer, the most recent sensors that were created during this project were able to not only withstand strains up to 800% but also increase the minimum aspect ratio of channel dimensions. The final sensor designs were fabricated using Ecoflex 00-10 silicone filled with Eutectic Gallium-Indium (EGaIn). This specific type of liquid metal was chosen because of its low toxicity, high conductivity, and liquid state at room temperature. The smallest microchannel dimensions at which the sensors were fabricated at were (WxH) 0.4 mm x 0.2 mm, 0.3 mm x 0.15 mm, and 0.2 mm x 0.1 mm channels. Small aspect ratios were considered to maximize sensitivity and improve resolution. The robustness of the sensor was achievable through different fabricating methods, the main differences being manual vs spin coating techniques. This was confirmed through tensile testing, where the sensors demonstrated improved reliability and consistent conductivity at higher strains compared to the sensors that were created without the spin coater. Shrinking the dimensions and the channel size not only provide a more sensitive sensor that is useful for measurement, but it can also open opportunities in human assisting technology where enhanced LMSS sensors have potential applications in biomechanical monitoring, such as human joint angle measurement and wearable motion tracking.
ContributorsFurukawa, Cindy (Author) / Sun, Jiefeng (Thesis director) / Lee, Hyunglae (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2025-05
Description
The presence of inclusions embedded within a polymer matrix significantly influences the macro- and nano-scale properties of the matrix. Characterizing the mechanical properties of such inclusion-embedded matrices is crucial for their diverse applications. Atomic force microscopy (AFM) has the unique ability to nondestructively characterize local modulus and height contours of nanocomposite surfaces. While previous studies have established a strong correlation between nanoparticle dispersion and the mechanical properties of nanocomposites, the combined influence of structural effects and material properties convolutes precise characterization. This study aims to deconvolute the effects of the nanoparticle’s embedment depth and damaged polymer on force-displacement curves using finite element analysis (FEA) to simulate the probe-matrix interactions in AFM. Validation of the FEA models was conducted using the Derjaguin-Muller-Toporov (DMT) and Hertzian contact mechanics models. Indentations were modeled for polymer matrices with inclusions embedded at varying depths and damaged polymer to analyze linear and nonlinear material, geometric, and contact mechanics effects. Nonlinear material behavior was characterized using a bilinear elastoplastic stress-strain curve and yield strength derived from Hertzian contact theory and Tresca’s yield criterion. Results revealed that inclusion depth and damaged polymer have distinct and measurable impacts on force-displacement curves retrace slopes, offering insights to identifiable patterns in mechanical behavior.
ContributorsChurch, Jett (Author) / Wilbur, Joshua (Thesis director) / Yekani Fard, Masoud (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2025-05
Description
This study presents a novel approach to 4D printing by employing surface tension-assisted additive manufacturing to fabricate multi-material structures with tunable surface roughness in response to humidity. Poly(ethylene glycol) diacrylate (PEGDA) was selected as the material due to its hygro-responsive and photocurable properties. The photocurable resin was prepared by varying concentrations of PEGDA, deionized (DI) water, and photoinitiator (PI). The optimized curing and drying times on swelling behavior were studied. The optimal material—mixture of 30 wt% DI water and 0.1 wt% PI—demonstrated the highest swelling ratio while maintaining structural integrity. Vat photopolymerization (VPP) printing method was used to create mesh designs and surface tension-assisted manufacturing was utilized to suspend films of hygro-responsive material. Retentiveness testing showed that circular holes with smaller diameters retained the most material due to uniform tension distribution. The structures exhibited increased surface roughness upon swelling which confirmed the feasibility of the manufacturing methodology. This research suggests the potential for adaptive applications such as responsive grippers or movements with different patterned surface roughness. Future work will focus on improving mechanical properties such as adhesion between different materials and structural brittleness and optimizing fabrication processes through the usage of hydrophobic coatings.
ContributorsYoo, Minju (Author) / Li, Cindy (Thesis director) / Tang, Tengteng (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / The Design School (Contributor)
Created2025-05
Description
Hats are commonly worn by people in extreme heat conditions, in a variety of colors and styles. In hot environments with high amounts of incident radiation, people often experience significant thermal discomfort, and conventional wisdom leads many of those people to wear hats to alleviate some of their discomfort. Despite this common practice, the effectiveness of different styles and colors of hats relative to each other has not been thoroughly researched. Hats can have varied impacts on the factors which impact thermal discomfort, including incident radiation, convective heat loss, and evaporative heat loss from sweat. The difference between styles and colors of hats can cause them to have different interactions with these methods of heat transfer, which lead to variance in the total impact on thermal discomfort. This research was conducted in order to create an experimentally justified recommendation for hat selection to limit thermal discomfort in hot and sunny areas.
ContributorsLyons, Caitlyn (Author) / Rykaczewski, Konrad (Thesis director) / Joshi, Ankit (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2025-05
Description
Conventional four-point-probe (4PP) stations achieve high-accuracy sheet-resistance measurements but often lack the ability to perform mapping across an area of a sample. Commercial tools also feature a large (80-100 mil) probe spacing, which limits the spatial resolution of the sheet-resistance measurement.We retrofitted an R-θ-Z wafer stage with a 3-D-printed probe head and spring-loaded, 410 µm-diameter gold pins, controlled through a new Python automation stack, to build a wafer-mapper. While the gold probe pins work well on metal films, sheet-resistance measurements on silicon samples require the probe tips to mechanically pierce the native SiO₂ that spontaneously grows on silicon wafers. For device-grade specimens this mechanical scratching is undesirable,because it could lead to the introduction of mechanical defects. Initial experiments were conducted that applied high-voltage (≤ 105V), low-current (≤ 1 mA) pulses to break down the oxide electrically. However, tip deformation increased the effective contact area, raising the breakdown voltage beyond practical limits and preventing reliable contact formation, causing large variations in the mapping data. We therefore explored a contact-less eddy-current approach using a single-loop RF coil. The RF excitation signal was swept from 100 kHz to 6 GHz while its complex reflection coefficient ( S₁₁ ) was captured. The resulting resonance-splitting or “fan-out” of S₁₁ spectra correlates monotonically with the sheet resistivity of test wafers (1-140 Ω □⁻¹). LTSpice models of the coil-wafer system reproduced the measured trends, lending confidence that calibrated peak-tracking can yield quantitative resistivity maps. This work demonstrates the feasibility of a hybrid probe station that performs non-contact characterization of bulk silicon samples. In future iterations this characterization technique can also be applied to thin-film measurements. Key design lessons and an outline for refining the probe head and extraction algorithms are presented.
ContributorsStringer, Evan (Author, Co-author) / Goryll, Michael (Thesis director) / Celano, Umberto (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2025-05