Engineering topics

Mazzeo, Aaron D.

Publications and source records attributed to Mazzeo, Aaron D..

3 records

NASA NTRS2017

A Piezoelectric Passive Wireless Sensor for Monitoring Strain

Interest in passive wireless sensing has grown over the past few decades to meet demands in structural health monitoring.(Deivasigamani et al., 2013; Wilson and Juarez, 2014) This work describes a passive wireless sensor for monitoring strain, which does not have an embedded battery or chip. Without an embedded battery, the passive wireless sensor has the potential to maintain its functionality over long periods in remote/harsh environments. This work also focuses on monitoring small strain (less than 1000 micro-ɛ). The wireless sensing system includes a reader unit, a coil-like transponder, and a sensing unit. It operates in the Megahertz (MHz) frequency range, which allows for a few centimeters of separation between the reader and sensing unit during measurements. The sensing unit is a strain-sensitive piezoelectric resonator that maximizes the energy efficiency at the resonance frequency, so it converts nanoscale mechanical variations to detectable differences in electrical signal. In response to an external loading, the piezoelectric sensor breaks from its original electromechanical equilibrium, and the resonant frequency shifts as the system reaches a new balanced equilibrium. In this work, the fixture of the sensing unit is a small, sticker-like package that converts the surface strain of a test material to measurable shifts in resonant frequencies. Furthermore, electromechanical modeling provides a lumped-parameter model of the system to describe and predict the measured wireless signals of the sensor. Detailed characterization demonstrates how this wireless sensor has resolution comparable to that of conventional wired strain sensors for monitoring small strain.

Zou, Xiyue↗

NASA NTRS2017

Elastomeric Sensing of Pressure with Liquid Metal and Wireless Inductive Coupling

This project describes resistance-based soft sensors filled with liquid metal, which permit measurements of large strains (0 percent to 110 percent), associated with small forces of less than 30 Newtons. This work also demonstrates a methodology for wireless transfer of these strain measurements without connected electrodes. These sensors allow intermittent detection of pressure on soft membranes with low force. Adapting these sensors for passive wireless pressure sensing will eliminate the need for embedded batteries, and will allow the sensors to transmit pressure data through non-conductive materials including glass and acrylic. The absence of batteries allows us to embed these sensors into materials for long-term use because the sensors only use passive analog circuit elements. We found the oxidation of the liquid metal (eutectic gallium indium) plays a role in the repeatability of the soft sensors. We investigated how the oxidation layer affected the behavior of the sensor by encapsulating materials (silicone, fluorosilicone, and PVC) with varied permeabilities to oxygen. We measured the effects of mechanical loading on the oxidation layer and the effects of wireless inductive coupling on the oxidation layer. We concluded our research by investigating the effects of embedding self-resonant circuits into polydimethylsiloxane (PDMS). Efforts to design engineered systems with soft materials are a growing field with progress in soft robotics, epidermal electronics, and wearable electronics. In the field of soft robotics, PDMS-based grippers are capable of picking up delicate objects because their form-fitting properties allow them to conform to the shape of objects more easily than conventional robotic grippers. Epidermal devices also use PDMS as a substrate to hold electronic components such as radios, sensors, and power supply circuits. Additionally, PDMS-based soft sensors can monitor human motion with liquid metal embedded within micro-channels. Passive wireless sensors have applications in structural health monitoring and medical health monitoring. Doctors can take wireless blood pressure measurements inside arteries to monitor the progression of heart disease. Glaucoma patients can use this technology to monitor the pressure in their eyes to track the progression of the disease.

Dick, Jacob↗

NASA NTRS2017

Predictive Modeling of Fast-Curing Thermosets in Nozzle-Based Extrusion

This work presents an approach to modeling the dynamic spreading and curing behavior of thermosets in nozzle-based extrusions. Thermosets cover a wide range of materials, some of which permit low-temperature processing with subsequent high-temperature and high-strength working properties. Extruding thermosets may overcome the limited working temperatures and strengths of conventional thermoplastic materials used in additive manufacturing. This project aims to produce technology for the fabrication of thermoset-based structures leveraging advances made in nozzle-based extrusion, such as fused deposition modeling (FDM), material jetting, and direct writing. Understanding the synergistic interactions between spreading and fast curing of extruded thermosetting materials will provide essential insights for applications that require accurate dimensional controls, such as additive manufacturing [1], [2] and centrifugal coating/forming [3]. Two types of thermally curing thermosets -- one being a soft silicone (Ecoflex 0050) and the other being a toughened epoxy (G/Flex) -- served as the test materials in this work to obtain models for cure kinetics and viscosity. The developed models align with extensive measurements made with differential scanning calorimetry (DSC) and rheology. DSC monitors the change in the heat of reaction, which reflects the rate and degree of cure at different crosslinking stages. Rheology measures the change in complex viscosity, shear moduli, yield stress, and other properties dictated by chemical composition. By combining DSC and rheological measurements, it is possible to establish a set of models profiling the cure kinetics and chemorheology without prior knowledge of chemical composition, which is usually necessary for sophisticated mechanistic modeling. In this work, we conducted both isothermal and dynamic measurements with both DSC and rheology. With the developed models, numerical simulations yielded predictions of diameter and height of droplets, along with width and height of extruded lines cured at varied temperatures. Experimental results carried out on a goniometric platform and a nozzle-based 3D printer showed agreement with the numerical simulations. Finally, this presentation will show how the models are adaptable to the planning of tool paths and designs in additive manufacturing.

Xie, Jingjin↗