Adam J. Wachtor

Simulations of Richtmyer–Meshkov instabilities in planar shock-tube experiments

In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper—flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer–Meshkov instabilities in planar sho...

Implicit large-eddy simulation of passive scalar mixing in statistically stationary isotropic turbulence

Turbulent mixing of a passive scalar by forced isotropic turbulence with a prescribed mean scalar gradient is studied in the context of implicit large-eddy simulation. The simulation strategy uses a multi-dimensional compressible flux-corrected transport algorithm, with low wavenumber momentum forcing imposed separately for the solenoidal and dilatational velocity components. Effects of grid resolution on the flow and scalar mixing are investigated at turbulent Mach numbers 0.13 and 0.27. Turbulence metrics are used to show that an implicit large-eddy simulation can accurately capture the mixing transition and asymptotic self-similar behaviors predicted by previous theoretical, laboratory, and direct numerical simulation studies, including asymptotically constant scalar variance and increasing velocity-to-scalar Taylor micro-scales ratio as function of effective Reynolds number determined by grid resolution. The results demonstrate the feasibility of predictive under-resolved simulations of high Reynolds ...

Embedding Sensors in FDM Plastic Parts During Additive Manufacturing

In additive manufacturing, there is a necessity to qualify both the geometrical and material characteristics of the fabricated part, because both are being created simultaneously as the part is built up layer by layer. Increased availability of open source fused deposition modeling machines has expanded the parameter space for which the user has control during the build process. This work quantifies the effects of operator choices, such as print speed, printer head and build plate temperatures, layering thickness, or building in a thermally controlled or fully open environment, on the quality and reproducibility of the build. Modal analyses were performed on completed builds using an electrodynamic shaker and integrated circuit piezoelectric accelerometers embedded in the parts during the build process. Experimental measurements of the fused deposition modeled parts were benchmarked against eigenvalue analysis results for an idealized part with homogenous material properties to gauge the suitability of such analysis to fused deposition modeling additive manufacturing. Follow on work will use this embedded technique for state-of-health monitoring in deployed systems and real-time diagnostics and control of the build process.

On coarse-grained simulations of turbulent material mixing

Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.

Dispersal and fallout simulations for urban consequences management

Hazardous chemical, biological, or radioactive releases from leaks, spills, fires, or blasts, may occur (intentionally or accidentally) in urban environments during warfare or as part of terrorist attacks on military bases or other facilities. The associated contaminant dispersion is complex and semi-chaotic. Urban predictive simulation capabilities can have direct impact in many threat-reduction areas of interest, including, urban sensor placement and threat analysis, contaminant transport (CT) effects on surrounding civilian population (dosages, evacuation, shelter-in-place), education and training of rescue teams and services. Detailed simulations for the various processes involved are in principle possible, but generally not fast. Predicting urban airflow accompanied by CT presents extremely challenging requirements (Britter and Hanna, 2003; Patnaik et al., 2007; Grinstein et al., 2009).

Three dimensional simulations of Richtmyer-Meshkov instabilities in shock-tube experiments

In the large eddy simulation (LES) approach large-scale energy-containing structures are resolved, smaller (presumably) more isotropic structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive simulations of turbulent velocity fields are possible based on subgrid scale modeling implicitly provided by a class of high-resolution finite-volume algorithms. This strategy is called implicit LES. The extension of the approach to the substantially more difficult problem of material mixing IS addressed, and progress in representative shock-driven turbulent mixing studies is reported.

A Framework for Additive Manufacturing Process Monitoring & Control

Fused deposition modelling, like other additive manufacturing methods, has largely remained an open loop process in the absence of rigorous process monitoring and diagnostic functionality. By creating a framework that integrates quantitative diagnostic tools whose measurements are coordinated with the printing process and the system which commands the printer hardware, this paper demonstrates the feasibility of closing the loop in additive manufacturing systems. Specifically, this paper introduces the use of ultrasonic excitation as a means of detecting filament bonding failures introduced by manipulating the print bed temperature during the fused deposition modelling build process. Furthermore, this work demonstrates the capability of correcting these filament bonding failures using a correction mechanism introduced through tunable control of another process parameter of the printer. By demonstrating the detection and correction of filament bonding failures in situ, this work has demonstrated the progress toward fully closed loop control for fused deposition modeling processes.

In-Process Ultrasonic Inspection of Additive Manufactured Parts

This project introduces an in-situ application of ultrasonic inspection techniques to fused deposition modeling (FDM) in order to detect defects as they are produced in a 3D printed plastic part. The growth of additive manufacturing into performance critical applications has revealed the need for precise quantitative evaluation of printed parts. Ultrasonic testing has been extensively demonstrated as a means of detecting small geometric defects in materials, but has not previously been applied in-process to thermoplastic FDM. This experiment used four piezoelectric transducers bonded to the build plate of an FDM machine printing Acrylonitrile Butadiene Styrene (ABS) to ultrasonically inspect parts periodically during the printing process. Every 30 s, the partially formed model is interrogated with an ultrasonic chirp signal and the response recorded. The normalized frequency response is then compared to an experimentally determined ideal response in order to detect faults in the most recently deposited layers. This analysis is based on the hypothesis that the frequency response of the part will be substantially altered if unexpected (defective) geometries are present. Due to the complexity added by low-density internal structures, this work investigates only parts with a solid fill and simple external geometries. However, with sufficient signal processing capabilities, it is feasible to extend this technique to more complicated part shapes and low-density fill patterns, as might be expected in a manufacturing setting.

Buoyancy driven mixing of miscible fluids by volumetric energy deposition of microwaves.

Abstract An experiment that seeks to investigate buoyancy driven mixing of miscible fluids by microwave volumetric energy deposition is presented. The experiment involves the use of a light, non-polar fluid that initially rests on top of a heavier fluid which is more polar. Microwaves preferentially heat the polar fluid, and its density decreases due to thermal expansion. As the microwave heating continues, the density of the lower fluid eventually becomes less than that of the upper, and buoyancy driven Rayleigh-Taylor mixing ensues. The choice of fluids is crucial to the success of the experiment, and a description is given of numerous fluid combinations considered and characterized. After careful consideration, the miscible pair of toluene / tetrahydrofuran (THF) was determined as having the best potential for successful volumetric energy deposition buoyancy driven mixing. Various single fluid calibration experiments were performed to facilitate the development of a heating theory. Thereafter, results from two-fluid mixing experiments are presented that demonstrate the capability of this novel Rayleigh-Taylor driven experiment. Particular interest is paid to the onset of buoyancy driven mixing and unusual aspects of the experiment in the context of typical Rayleigh-Taylor driven mixing.

Remote Damage Detection of Rotating Machinery

Condition-based monitoring (CBM) is a method of damage detection that actively monitors continuously operating machines to identify the earliest signs of deteriorating performance. There are many accepted methods of CBM, however this paper focuses on remote sensing of the vibration signatures of rotating machinery, e.g. an AC motor. Traditionally, vibration-based CBM requires accelerometers to be mounted directly on the machinery of interest; however, certain operating conditions may prevent such direct accelerometer access. This research aims to understand how to improve upon existing CBM methods by developing a transfer function which accounts for the propagation environment between the machinery of interest and an accelerometer placed some distance away, and then use this transfer function to perform damage detection. By taking baseline measurements at the start of the life on an AC motor as well as a spatially separated location, a transfer function between the two measurements can be developed in a similar fashion to a frequency response function. Using the developed transfer function and spectral analysis, remote measurements can then be used to reconstruct the vibration signatures at the motor. Furthermore, it will be shown that using this transfer function improves performance of a damage detector using a matched filter. These methods were tested using a motor mounted to a plate that is mounted on a wooden table as well as with a characterization motor loosely mounted on compliant padding. Also discussed are the damage detection results, as evidenced by the improvement in the receiver operating characteristic (ROC) curves of four damage modes, showing that capturing the propagation environment through the transfer function improves remote damage detection performance.