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Combined thermographic phosphor and digital image correlation (TP + DIC) for simultaneous temperature and strain measurements

Strain

Jones, Elizabeth M.; Jones, Amanda; Winters, Caroline W.

Thermographic phosphors (TP) are combined with stereo digital image correlation (DIC) in a novel diagnostic, TP + DIC, to measure full-field surface strains and temperatures simultaneously. The TP + DIC method is presented, including corrections for nonlinear CMOS camera detectors and generation of pixel-wise calibration curves to relate the known temperature to the ratio of pixel intensities between two distinct wavelength bands. Additionally, DIC is employed not only for strain measurements but also for accurate image registration between the two cameras for the two-colour ratio method approach of phosphoric thermography. TP + DIC is applied to characterize the thermo-mechanical response of 304L stainless steel dog bones during tensile testing at different strain rates. The dog bones are patterned for DIC with Mg3F2GeO4:Mn (MFG) via aerosol deposition through a shadow mask. Temperatures up to 425°K (150°C) and strains up to 1.0 mm/mm are measured in the localized necking region, with conservative noise levels of 10°K and 0.01 mm/mm or less. Finally, TP + DIC is compared to the more established method of combining infrared (IR) thermography with DIC (IR + DIC), with results agreeing favourably. Three topics of continued research are identified, including cracking of the aerosol-deposited phosphor DIC features, incomplete illumination for pixels on the border of the phosphor features, and phosphor emission evolution as a function of applied substrate strain. This work demonstrates the combination of phosphor thermography and DIC and lays the foundation for further development of TP + DIC for testing in combined thermo-mechancial environments.

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V31 Test Report

Stofleth, Jerome H.; Crocker, Robert W.; Tribble, Megan K.

The V31 containment vessel was procured by the US Army Recovered Chemical Material Directorate (RCMD) as a third - generation EDS containment vessel. It is the fifth EDS vessel to be fabricated under Code Case 2564 of the 2019 ASME Boiler and Pressure Vessel Code, which provides rules for the design of impulsively loaded vessels. The explosive rating for the vessel, based on the code case, is twenty-four (24) pounds TNT - equivalent for up to 1092 detonations. This report documents the results of explosive tests that were performed on the vessel at Sandia National Laboratories in Albuquerque, New Mexico to qualify the vessel for field operations use. There were three design basis configurations for qualification testing. Qualification test (1) consisted of a simulated M55 rocket motor and warhead assembly of 24lbs of Composition C-4 (30 lb TNT equivalent). This test was considered the maximum load case, based on modeling and simulation methods performed by Sandia prior to the vessel design phase. Qualification test (2) consisted of a regular, right circular cylinder, unitary charge, located central to the vessel interior of 19.2 lb of Composition C-4 (24 lb TNT equivalent). Qualification test (3) consisted of a 12-pack of regular, right circular cylinders of 2 lb each, distributed evenly inside the vessel (totaling 19.2 lb of C-4, or 24 lb TNT equivalent). All vessel acceptance criteria were met.

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Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Advances in Water Resources

Park, Heeho D.; Paul, Matthew J.; Valocchi, Albert J.; Hammond, Glenn E.

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. We use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton's method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. We show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Furthermore, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

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Schmid factor crack propagation and tracking crystallographic texture markers of microstructural condition in direct energy deposition additive manufacturing of Ti-6Al-4V

Additive Manufacturing

Saville, Alec I.; Benzing, Jake T.; Vogel, Sven C.; Buckner, Jessica L.; Donohoue, Collin; Kustas, Andrew K.; Creuziger, Adam; Clarke, Kester D.; Clarke, Amy J.

Metallic additive manufacturing (AM) provides a customizable and tailorable manufacturing process for new engineering designs and technologies. The greatest challenge currently facing metallic AM is maintaining control of microstructural evolution during solidification and any solid state phase transformations during the build process. Ti-6Al-4V has been extensively surveyed in this regard, with the potential solid state and solidification microstructures explored at length. This work evaluates the applicability of previously determined crystallographic markers of microstructural condition observed in electron beam melting powder bed fusion (PBF-EB) builds of Ti-6Al-4V in a directed energy deposition (DED) build process. The aim of this effort is to elucidate whether or not these specific crystallographic textures are useful tools for indicating microstructural conditions in AM variants beyond PBF-EB. Parent β-Ti grain size was determined to be directly related to α-Ti textures in the DED build process, and the solid state microstructural condition could be inferred from the intensity of specific α-Ti orientations. Qualitative trends on the as-solidified β-Ti grain size were also determined to be related to the presence of a fiber texture, and proposed as a marker for as-solidified grain size in any cubic metal melted by AM. Analysis of the DED Ti-6Al-4V build also demonstrated a near complete fracture of the build volume, suspected to originate from accumulated thermal stresses in the solid state. Crack propagation was found to only appreciably occur in regions of slow cooling with large α+β colonies. Schmid factors for the basal and prismatic α-Ti systems explained the observed crack pathway, including slower bifurcation in colonies with lower Schmid factors of both slip systems. Colony morphologies and localized equiaxed β-Ti solidification were also found to originate from build pauses during production and uneven heating of the build edges during deposition. Tailoring of DED Ti-6Al-4V microstructures with the insight gained here is proposed, along with cautionary insight on preventing unplanned build pauses to maintain an informed and controlled thermal environment for microstructural control.

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Grey Zone Test Range Social Model

Doyle, Casey L.; Gunda, Thushara G.; Bernard, Michael L.

The Grey Zone Test Range (GZTR) social model operates as a piece of the overall GZTR modeling effort. It works in conjunction with supply models for resources, an electric grid model for power availability, and a traffic model for road congestion, as well as a general controller framework that allows external system effects. The social model functions as an aggregate model where the entire population of the city is divided into groups based on the Transportation Analysis Zones (TAZs), a common geospatial boundary present in all GZTR models. These groups will act as a singular community; each time step the state of the system around them will be assessed and then community will come up with a general plan of action that they will attempt to follow for the day. Additionally, they will track values for their general emotional state and memory about negative impacts in the near past.

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Perspectives on the integration between first-principles and data-driven modeling

Computers and Chemical Engineering

Bradley, William; Kim, Jinhyeun; Kilwein, Zachary A.; Blakely, Logan; Eydenberg, Michael S.; Jalvin, Jordan; Laird, Carl; Boukouvala, Fani

Efficiently embedding and/or integrating mechanistic information with data-driven models is essential if it is desired to simultaneously take advantage of both engineering principles and data-science. The opportunity for hybridization occurs in many scenarios, such as the development of a faster model of an accurate high-fidelity computer model; the correction of a mechanistic model that does not fully-capture the physical phenomena of the system; or the integration of a data-driven component approximating an unknown correlation within a mechanistic model. At the same time, different techniques have been proposed and applied in different literatures to achieve this hybridization, such as hybrid modeling, physics-informed Machine Learning (ML) and model calibration. In this paper we review the methods, challenges, applications and algorithms of these three research areas and discuss them in the context of the different hybridization scenarios. Moreover, we provide a comprehensive comparison of the hybridization techniques with respect to their differences and similarities, as well as advantages and limitations and future perspectives. Finally, we apply and illustrate hybrid modeling, physics-informed ML and model calibration via a chemical reactor case study.

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A Liquid Stratification Model to Predict Failure in Thermally Damaged EBW Detonators

Propellants, Explosives, Pyrotechnics

Hobbs, Michael L.; Coronel, Stephanie C.

In previous work, commercially available downward facing exploding bridgewire detonators (EBWs) were exposed to elevated temperatures. These detonators were then initiated using a firing set which discharged a high amplitude short duration electrical pulse into a thin gold bridgewire. Responses of the detonators were measured using photonic doppler velocimetry (PDV) and high-speed photography. A time delay of 2 μs between EBW initiation and first movement of an output flyer separated operable detonators from inoperable detonators or duds. In the current work, we propose a simple method to determine detonator operability from the calculated state of the detonator at the time the firing set is initiated. The failure criterion is based on the gap distance between the exploding bridgewire (EBW) and the adjacent initiating explosive within the detonator which is low-density pentaerythritol tetranitrate (PETN) that melts between 413–415 K (140–142 °C). The gap forms as PETN melts and flows to the bottom of the input pellet. Melting of PETN is modeled thermodynamically as an energy sink using a normal distribution spread over a temperature range between the onset temperature of 413 K and the ending temperature of 415 K. The extent of the melt is determined from the average temperature of the PETN. The PETN liquid is assumed to occupy the interstitial gas volume in the lower part of the input pellet. The vacated volume from the relocated liquid forms the gap between the EBW and the PETN. The remaining sandwiched layer consists of solid PETN particles and gas filling interstitial volume. We predict that a threshold gap between 17–27 μm separates properly functioning detonators from duds.

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Results 3301–3400 of 96,771
Results 3301–3400 of 96,771