Publications

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Ceramic fiber insulation materials, such as Fiberfrax and Min-K products, are used in a number of applications (e.g. aerospace, fire protection, and military) for their stability and performance in extreme conditions. However, the thermal properties of these materials have not been thoroughly characterized for many of the conditions that they will be exposed to, such as high temperatures and pressures. This complicates the design of systems using these insulations as the uncertainty in the thermal properties is high. In this study, the thermal conductivity of three ceramic fiber insulations, Fiberfrax T-30LR laminate, Fiberfrax 970-H paper, and Min-K TE1400 board, was measured as a function of atmospheric temperature and compression. Measurements were taken using the transient plane source technique. The results of this study are compared against three published data sets.

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Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

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A three year LDRD was undertaken to look at the feasibility of using magnetic sensing to determine flows within sealed vessels at high temperatures and pressures. Uniqueness proofs were developed for tracking of single magnetic particles with multiple sensors. Experiments were shown to be able to track up to 3 dipole particles undergoing rigid-body rotational motion. Temperature was wirelessly monitored using magnetic particles in static and predictable motions. Finally high-speed vibrational motion was tracked using magnetic particles. Ideas for future work include using small particles for measuring vorticity and better calibration methods for tracking multiple particles.

Kinetic models have been developed to understand the manufacturing of polymeric foams, which evolve from low viscosity Newtonian liquids, to bubbly liquids, finally producing solid foam. Closed-form kinetics are formulated and parameterized for PMDI-10, a fast curing polyurethane, including polymerization and foaming. PMDI-10 is chemically blown, where water and isocyanate react to form carbon dioxide. The isocyanate reacts with polyol in a competing reaction, producing polymer. Our approach is unique, although it builds on our previous work and the polymerization literature. This kinetic model follows a simplified mathematical formalism that decouples foaming and curing, including an evolving glass transition temperature to represent vitrification. This approach is based on IR, DSC, and volume evolution data, where we observed that the isocyanate is always in excess and does not affect the kinetics. The kinetics are suitable for implementation into a computational fluid dynamics framework, which will be explored in subsequent articles. © 2017 American Institute of Chemical Engineers AIChE J, 63: 2945–2957, 2017.

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We present selected results from a series of Open Stack thermal battery tests performed in FY14 and FY15 and discuss our findings. These tests were meant to provide validation data for the comprehensive thermal battery simulation tools currently under development in Sierra/Aria under known conditions compared with as-manufactured batteries. We are able to satisfy this original objective in the present study for some test conditions. Measurements from each test include: nominal stack pressure (axial stress) vs. time in the cold state and during battery ignition, battery voltage vs. time against a prescribed current draw with periodic pulses, and images transverse to the battery axis from which cell displacements are computed. Six battery configurations were evaluated: 3, 5, and 10 cell stacks sandwiched between 4 layers of the materials used for axial thermal insulation, either Fiberfrax Board or MinK. In addition to the results from 3, 5, and 10 cell stacks with either in-line Fiberfrax Board or MinK insulation, a series of cell-free “control” tests were performed that show the inherent settling and stress relaxation based on the interaction between the insulation and heat pellets alone.

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Remote temperature sensing is essential for applications in enclosed vessels, where feedthroughs or optical access points are not possible. A unique sensing method for measuring the temperature of multiple closely spaced points is proposed using permanent magnets and several three-axis magnetic field sensors. The magnetic field theory for multiple magnets is discussed and a solution technique is presented. Experimental calibration procedures, solution inversion considerations, and methods for optimizing the magnet orientations are described in order to obtain low-noise temperature estimates. The experimental setup and the properties of permanent magnets are shown. Finally, experiments were conducted to determine the temperature of nine magnets in different configurations over a temperature range of 5 °C to 60 °C and for a sensor-to-magnet distance of up to 35 mm. To show the possible applications of this sensing system for measuring temperatures through metal walls, additional experiments were conducted inside an opaque 304 stainless steel cylinder.

Physical property measurements including viscosity, density, thermal conductivity, and heat capacity of low-molecular weight polydimethylsiloxane (PDMS) fluids were measured over a wide temperature range (-50°C to 150°C when possible). Properties of blends of 1 cSt and 20 cSt PDMS fluids were also investigated. Uncertainties in the measurements are cited. These measurements will provide greater fidelity predictions of environmental sensing device behavior in hot and cold environments.

We present a new collection of data on the load-stress relaxation-unload behavior of MinK and FiberFrax Board (FF) insulation materials used as pellets in-line with thermal battery electrochemical stacks. Both materials were subjected to standard thermal preparations, and then tested at room temperature. Intermediate term stress relaxation tests are presented (order 104 minutes of relaxation) showing that FF relaxation is not significantly stress or deformation dependent, but MinK is moderately so. Moreover, stress-strain curves associated with specimen unloading, reloading, and unloading again are presented for both materials. FF and MinK are substantially different here. Acute material variability is observed though test conditions and material preparations are standardized. A modeling approach is presented to empirically estimate the amount of stress relaxation at room temperature, and from this state, represent the unloading stress-strain behavior of both materials. This effort provides a complete framework for representing (in an engineering sense) both materials in thermal battery performance simulations.

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Polyurethane is a complex multiphase material that evolves from a viscous liquid to a system of percolating bubbles, which are created via a CO2 generating reaction. The continuous phase polymerizes to a solid during the foaming process generating heat. Foams introduced into a mold increase their volume up to tenfold, and the dynamics of the expansion process may lead to voids and will produce gradients in density and degree of polymerization. These inhomogeneities can lead to structural stability issues upon aging. For instance, structural components in weapon systems have been shown to change shape as they age depending on their molding history, which can threaten critical tolerances. The purpose of this project is to develop a Cradle-to-Grave multiphysics model, which allows us to predict the material properties of foam from its birth through aging in the stockpile, where its dimensional stability is important.

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The transient transport of electrolytes in thermally-activated batteries is studied using electron probe micro-analysis (EPMA), demonstrating the robust capability of EPMA as a useful tool for studying and quantifying mass transport within porous materials, particularly in difficult environments where classical flow measurements are challenging. By tracking the mobility of bromine and potassium ions from the electrolyte stored within the separator into the lithium silicon anode and iron disulfide cathode, we are able to quantify the transport mechanisms and physical properties of the electrodes including permeability and tortuosity. Due to the micron to submicron scale porous structure of the initially dry anode, a fast capillary pressure driven flow is observed into the anode from which we are able to set a lower bound on the permeability of 10-1 mDarcy. The transport into the cathode is diffusion-limited because the cathode originally contained some electrolyte before activation. Using a transient one-dimensional diffusion model, we estimate the tortuosity of the cathode electrode to be 2.8 ± 0.8.

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We are developing computational models to elucidate the expansion and dynamic filling process of a polyurethane (PMDI) foam used to encapsulate electronic components or to produce lightweight structural parts. The polyurethane of interest is a chemically blown foam, where carbon dioxide is produced via the reaction of water, a blowing agent, and isocyanate. Here, we take a careful look at the evolution of the bubble sizes during blowing. This information will help the development of subgrid models to predict bubble formation, growth, coalescence and collapse, drainage, and, hence, eventually the development of engineering models to predict foam expansion into a mold. Close-up views of bubbles at a transparent wall of a narrow, temperature-controlled channel are recorded during the foaming reaction and analyzed with image processing. Because these bubbles are pressed against the wall, the bubble sizes in the last frames after the expansion has stopped are compared to scanning electron microscope (SEM) images of the interior of some of the cured samples to determine if the presence of the wall significantly changes the bubble sizes. In addition, diffusing wave spectroscopy (DWS) is used to determine the average bubble sizes across the width of a similar channel as the bubbles change with time. DWS also gives information about microstructural changes as bubbles rearrange upon bubble collapse or coalescence. In this paper we conclude qualitatively that the bubble size distribution is heavily dependent on the formulation of foam being tested, temperature, the height in the foam bar, the proximity to a wall, and the degree of over-packing.

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Temperature monitoring is essential in automation, mechatronics, robotics and other dynamic systems. Wireless methods which can sense multiple temperatures at the same time without the use of cables or slip-rings can enable many new applications. A novel method utilizing small permanent magnets is presented for wirelessly measuring the temperature of multiple points moving in repeatable motions. The technique utilizes linear least squares inversion to separate the magnetic field contributions of each magnet as it changes temperature. The experimental setup and calibration methods are discussed. Initial experiments show that temperatures from 5 to 50 °C can be accurately tracked for three neodymium iron boron magnets in a stationary configuration and while traversing in arbitrary, repeatable trajectories. This work presents a new sensing capability that can be extended to tracking multiple temperatures inside opaque vessels, on rotating bearings, within batteries, or at the tip of complex endeffectors.

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We are studying PMDI polyurethane with a fast catalyst, such that filling and polymerization occur simultaneously. The foam is over-packed to tw ice or more of its free rise density to reach the density of interest. Our approach is to co mbine model development closely with experiments to discover new physics, to parameterize models and to validate the models once they have been developed. The model must be able to repres ent the expansion, filling, curing, and final foam properties. PMDI is chemically blown foam, wh ere carbon dioxide is pr oduced via the reaction of water and isocyanate. The isocyanate also re acts with polyol in a competing reaction, which produces the polymer. A new kinetic model is developed and implemented, which follows a simplified mathematical formalism that decouple s these two reactions. The model predicts the polymerization reaction via condensation chemis try, where vitrification and glass transition temperature evolution must be included to correctly predict this quantity. The foam gas generation kinetics are determined by tracking the molar concentration of both water and carbon dioxide. Understanding the therma l history and loads on the foam due to exothermicity and oven heating is very important to the results, since the kinetics and ma terial properties are all very sensitive to temperature. The conservation eq uations, including the e quations of motion, an energy balance, and thr ee rate equations are solved via a stabilized finite element method. We assume generalized-Newtonian rheology that is dependent on the cure, gas fraction, and temperature. The conservation equations are comb ined with a level set method to determine the location of the free surface over time. Results from the model are compared to experimental flow visualization data and post-te st CT data for the density. Seve ral geometries are investigated including a mock encapsulation part, two configur ations of a mock stru ctural part, and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Thoughts on m odel improvements are also discussed.

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