Srikanth Allu

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.

A parallel multi-domain solution methodology applied to nonlinear thermal transport problems in nuclear fuel pins

This paper describes an efficient and nonlinearly consistent parallel solution methodology for solving coupled nonlinear thermal transport problems that occur in nuclear reactor applications over hundreds of individual 3D physical subdomains. Efficiency is obtained by leveraging knowledge of the physical domains, the physics on individual domains, and the couplings between them for preconditioning within a Jacobian Free Newton Krylov method. Details of the computational infrastructure that enabled this work, namely the open source Advanced Multi-Physics (AMP) package developed by the authors is described. Details of verification and validation experiments, and parallel performance analysis in weak and strong scaling studies demonstrating the achieved efficiency of the algorithm are presented. Furthermore, numerical experiments demonstrate that the preconditioner developed is independent of the number of fuel subdomains in a fuel rod, which is particularly important when simulating different types of fuel rods. Finally, we demonstrate the power of the coupling methodology by considering problems with couplings between surface and volume physics and coupling of nonlinear thermal transport in fuel rods to an external radiation transport code.

Safer Batteries through Coupled Multiscale Modeling

Abstract Batteries are highly complex electrochemical systems, with performance and safety governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. We describe a new, open source computational environment for battery simulation known as VIBE - the Virtual Integrated Battery Environment. VIBE includes homogenized and pseudo-2D electrochemistry models such as those by Newman-Tiedemann-Gu (NTG) and Doyle-Fuller-Newman (DFN, a.k.a. DualFoil) as well as a new advanced capability known as AMPERES (Advanced MultiPhysics for Electrochemical and Renewable Energy Storage). AMPERES provides a 3D model for electrochemistry and full coupling with 3D electrical and thermal models on the same grid. VIBE/AMPERES has been used to create three-dimensional battery cell and 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 response under adverse conditions.

A Validation Study of Pin Heat Transfer for MOX Fuel Based on the IFA-597 Experiments

Abstract The Integrated Fuel Assessment IFA-432 experiments from the International Fuel Performance Experiments database were designed to study the effects of gap size, fuel density, and fuel densification on fuel centerline temperature in light water reactor fuel. An evaluation of nuclear fuel pin heat transfer in the FRAPCON-3.4 and Exnihilo codes for uranium dioxide (UO2) fuel systems was performed, with a focus on the densification stage (2.2 GWd/tonne UO2). In addition, sensitivity studies were performed to evaluate the effect of the radial power shape and approximations to the geometry to account for the thermocouple hole. The analysis demonstrated excellent agreement for rods 1, 2, 3, and 5 (varying gap thicknesses and density with traditional fuel), demonstrating the accuracy of the codes and their underlying material models for traditional fuel. For rod 6, which contained unstable fuel that densified an order of magnitude more than traditional, stable fuel, the magnitude of densification was overpredicted, and the temperatures were outside the experimental uncertainty. The radial power shape within the fuel was shown to have a significant impact on the predicted centerline temperatures, whereas the effect of modeling the fuel at the thermocouple location as either annular or solid was relatively negligible. This has provided an initial benchmarking of the pin heat transfer capability of Exnihilo for UO2 fuel with respect to a well-validated nuclear fuel performance code.

Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit

The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from many simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion battery (LIB) cell, by studying a coupled system involving the electrochemistry and ion transport at the lower length scales and thermal energy transport at the device scales. The DAKOTA-IPS system provides a flexible tool for use in optimization and parameter sweep studies involving loosely coupled simulations that is suitable for use in situations where changes to the constituent components in the coupled simulation are impractical due to intellectual property or code heritage issues.

CAEBAT OAS/VIBE Production Release v1.1

The objective of the project is to develop a mathematical and computational infrastructure, and modeling framework that will enable seamless multi-scale and multi-physics simulations of battery performance and safety. The modeling framework will transfer the information between models in a physically consistent and mathematically rigorous fashion for both spatial and temporal variations. The end result will be a verified, computationally scalable, portable, and flexible (extensible and easily-modified) framework that can integrate models from the other CAEBAT tasks and industrial partners. The framework will be used to validate models and modeling approaches against experiments and to support rapid prototyping of advanced battery concepts. Fig. 2 shows different parts of CAEBAT VIBE simulation environment that work together to provide user with flexibility in the problem setup, solution formulation and simulation launch. Each of the parts is discussed in subsequent sections with corresponding examples.

Fiscal Year 2011 Infrastructure Refactorizations in AMP

In Fiscal Year 2011 (FY11), the AMP (Advanced MultiPhysics) Nuclear Fuel Performance code [1] went through a thorough review and refactorization based on the lessons-learned from the previous year, in which the version 0.9 of the software was released as a prototype. This report describes the refactorization work that has occurred or is in progress during FY11.