Sreekanth Pannala

The metallurgy and processing science of metal additive manufacturing

Additive manufacturing (AM), widely known as 3D printing, is a method of manufacturing that forms parts from powder, wire or sheets in a process that proceeds layer by layer. Many techniques (using many different names) have been developed to accomplish this via melting or solid-state joining. In this review, these techniques for producing metal parts are explored, with a focus on the science of metal AM: processing defects, heat transfer, solidification, solid-state precipitation, mechanical properties and post-processing metallurgy. The various metal AM techniques are compared, with analysis of the strengths and limitations of each. Only a few alloys have been developed for commercial production, but recent efforts are presented as a path for the ongoing development of new materials for AM processes.

Computational gas-solids flows and reacting systems : theory, methods and practice

Computational Gas-Solids Flows and Reacting Systems: Theory, Methods and Practice addresses the need for a comprehensive book on computational gas-solids flow to aid researchers, graduate students, and practicing engineers in this rapidly expanding area. This unique book provides a full exploration of the theory, numerical methods, and practices associated with this emerging area, including hydrodynamic equations, quadrature-based moment methods, and direct numerical simulation.

Modeling the coupling of reaction kinetics and hydrodynamics in a collapsing cavity

We introduce a model of cavitation based on the multiphase Lattice Boltzmann method (LBM) that allows for coupling between the hydrodynamics of a collapsing cavity and supported solute chemical species. We demonstrate that this model can also be coupled to deterministic or stochastic chemical reactions. In a two-species model of chemical reactions (with a major and a minor species), the major difference observed between the deterministic and stochastic reactions takes the form of random fluctuations in concentration of the minor species. We demonstrate that advection associated with the hydrodynamics of a collapsing cavity leads to highly inhomogeneous concentration of solutes. In turn these inhomogeneities in concentration may lead to significant increase in concentration-dependent reaction rates and can result in a local enhancement in the production of minor species.

Time-parallel multiscale/multiphysics framework

We introduce the time-parallel compound wavelet matrix method (tpCWM) for modeling the temporal evolution of multiscale and multiphysics systems. The method couples time parallel (TP) and CWM methods operating at different spatial and temporal scales. We demonstrate the efficiency of our approach on two examples: a chemical reaction kinetic system and a non-linear predator-prey system. Our results indicate that the tpCWM technique is capable of accelerating time-to-solution by 2-3-orders of magnitude and is amenable to efficient parallel implementation.

Real-time optical diagnostics of graphene growth induced by pulsed chemical vapor deposition

The kinetics and mechanisms of graphene growth on Ni films at 720-880 °C have been measured using fast pulses of acetylene and real-time optical diagnostics. In situ UV-Raman spectroscopy was used to unambiguously detect isothermal graphene growth at high temperatures, measure the growth kinetics with ∼1 s temporal resolution, and estimate the fractional precipitation upon cooldown. Optical reflectivity and videography provided much faster temporal resolution. Both the growth kinetics and the fractional isothermal precipitation were found to be governed by the C2H2 partial pressure in the CVD pulse for a given film thickness and temperature, with up to ∼94% of graphene growth occurring isothermally within 1 second at 800 °C at high partial pressures. At lower partial pressures, isothermal graphene growth is shown to continue 10 seconds after the gas pulse. These flux-dependent growth kinetics are described in the context of a dissolution/precipitation model, where carbon rapidly dissolves into the Ni film and later precipitates driven by gradients in the chemical potential. The combination of pulsed-CVD and real-time optical diagnostics opens new opportunities to understand and control the fast, sub-second growth of graphene on various substrates at high temperatures.

Multiscale modeling and characterization for performance and safety of lithium-ion batteries

Lithium-ion batteries are highly complex electrochemical systems whose performance and safety are governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. Gaining an understanding of the role of these processes as well as development of predictive capabilities for design of better performing batteries requires synergy between theory, modeling, and simulation, and fundamental experimental work to support the models. This paper presents the overview of the work performed by the authors aligned with both experimental and computational efforts. In this paper, we describe a new, open source computational environment for battery simulations with an initial focus on lithium-ion systems but designed to support a variety of model types and formulations. This system has been used to create a three-dimensional cell and battery pack models that explicitly simulate all the battery components (current collectors, electrodes, and separator). The models are used to predict battery performance under normal operations and to study thermal and mechanical safety aspects under adverse conditions. This paper also provides an overview of the experimental techniques to obtain crucial validation data to benchmark the simulations at various scales for performance as well as abuse. We detail some initial validation using characterization experiments such as infrared and neutron imaging and micro-Raman mapping. In addition, we identify opportunities for future integration of theory, modeling, and experiments.

Advanced coal gasifier designs using large-scale simulations

Porting of the legacy code MFIX to a high performance computer (HPC) and the use of high resolution simulations for the design of a coal gasifier are described here. MFIX is based on a continuum multiphase flow model that considers gas and solids to form interpenetrating continua. Low resolution simulations of a commercial scale gasifier with a validated MFIX model revealed interesting physical phenomena with implications on the gasifier design, which prompted the study reported here. To be predictive, the simulations need to model the spatiotemporal variations in gas and solids volume fractions, velocities, temperatures with any associated phase change and chemical reactions. These processes occur at various time- and length-scales requiring very high spatial resolution and large number of iterations with small time-steps. We were able to perform perhaps the largest known simulations of gas-solids reacting flows, providing detailed information about the gas-solids flow structure and the pressure, temperature and species distribution in the gasifier. One key finding is the new features of the coal jet trajectory revealed with the high spatial resolution, which provides information on the accuracy of the lower resolution simulations. Methodologies for effectively combining high and low resolution simulations for design studies must be developed. From a computational science perspective, we found that global communication has to be reduced to achieve scalability to 1000s of cores, hybrid parallelization is required to effectively utilize the multicore chips, and the wait time in the batch queue significantly increases the actual time-to-solution. From our experience, development is required in the following areas: efficient solvers for heterogeneous, massively parallel systems; data analysis tools to extract information from large data sets; and programming environments for easily porting legacy codes to HPC.

Hybrid (OpenMP and MPI) parallelization of MFIX: a multiphase CFD code for modeling fluidized beds

We describe the effort and experience in generating a hybrid parallel version of MFIX (Multiphase Flow with Interphase eXchanges), a code for modeling reactive multiphase flow in fluidized beds. The code uses portable OpenMP and MPI in a unified source code. The resulting parallel code has been ported to Beowulf Linux clusters, SGI shared memory multiprocessors, Compaq SC clusters, and an IBM SP. We present hybrid parallel performance results specifically on the 32-way node of IBM SP. This experience is relevant, as most modern high-performance computing (HPC) systems are clusters of SMP nodes.

Open-source software in computational research: a case study

A case study of open-source (OS) development of the computational research software MFIX, used for multiphase computational fluid dynamics simulations, is presented here. The verification and validation steps required for constructing modern computational software and the advantages of OS development in those steps are discussed. The infrastructure used for enabling the OS development of MFIX is described. The impact of OS development on computational research and education in gas-solids flow, as well as the dissemination of information to other areas such as geophysical and volcanology research, is demonstrated. This study shows that the advantages of OS development were realized in the case of MFIX: verification by many users, which enhances software quality; the use of software as a means for accumulating and exchanging information; the facilitation of peer review of the results of computational research.

Spatiotemporal Compound Wavelet Matrix Framework for Multiscale/Multiphysics Reactor Simulation: Case Study of a Heterogeneous Reaction/Diffusion System

We present a mathematical method for efficiently compounding information from different models of species diffusion from a chemically reactive boundary. The proposed method is intended to serve as a key component of a multiscale/multiphysics framework for heterogeneous chemically reacting processes. An essential feature of the method is the merging of wavelet representations of the different models and their corresponding time and length scales. Up-and-down-scaling of the information between the scales is accomplished by application of a compounding wavelet operator, which is assembled by establishing limited overlap in scales between the models. We show that the computational efficiency gain and potential error associated with the method depend on the extent of scale overlap and wavelet filtering used. We demonstrate the method for an example problem involving a two-dimensional chemically reactive boundary and first order reactions involving two species.