The Jet Propulsion Laboratory has a keen interest in exploring icy moons in the solar system, particularly Jupiter's Europa. Successful exploration of the moon's surface includes planetary protection initiatives to prevent the introduction of viable organisms from Earth to Europa. To that end, the Europa lander requires a Terminal Sterilization Subsystem (TSS) to rid the lander of viable organisms that would potentially contaminate the moon's environment. Sandia National Laboratories has been developing a TSS architecture, relying heavily on computational models to support TSS development. Sandia's TSS design approach involves using energetic material to thermally sterilize lander components at the end of the mission. A hierarchical modeling approach was used for system development and analysis, where simplified systems were constructed to perform empirical tests for evaluating energetic material formulation development and assist in developing computational models with multiple tiers of physics fidelity. Computational models have been developed using multiple Sandia-native computational tools. Three experimental systems and corresponding computational models have been developed: Tube, Sub-Box Small, and Sub-Box Large systems. This paper presents an explanation of the application context of the TSS along with an overview description of a small portion of the TSS development from a modeling and simulation perspective, specifically highlighting verification, validation, and uncertainty quantification (VVUQ) aspects of the modeling and simulation work. Multiple VVUQ approaches were implemented during TSS development, including solution verification, calibration, uncertainty quantification, global sensitivity analysis, and validation. This paper is not intended to express the design results or parameter values used to model the TSS but to communicate the approaches used and how the results of the VVUQ efforts were used and interpreted to assist system development.
Thermally activated batteries undergo a series of coupled physical changes during activation that influence battery performance. These processes include energetic material burning, heat transfer, electrolyte phase change, capillary-driven two-phase porous flow, ion transport, electrochemical reactions, and electrical transport. Several of these processes are strongly coupled and have a significant effect on battery performance, but others have minimal impact or may be suitably represented by reduced-order models. Assessing the relative importance of these phenomena must be based on comparisons to a high-fidelity model including all known processes. In this work, we first present and demonstrate a high-fidelity, multi-physics model of electrochemical performance. This novel multi-physics model enables predictions of how competing physical processes affect battery performance and provides unique insights into the difficult-to-measure processes that happen during battery activation. We introduce four categories of model fidelity that include different physical simplifications, assumptions, and reduced-order models to decouple or remove costly elements of the simulation. Using this approach, we show an order-of-magnitude reduction in computational cost while preserving all design-relevant quantities of interest within 5 percent. The validity of this approach and these model reductions is demonstrated by comparison between results from the full fidelity model and the different reduced models.
This memo summarizes the aerodynamic drag scoping work done for Goodyear in early FY18. The work is to evaluate the feasibility of using Sierra/Low-Mach (Fuego) for drag predictions of rolling tires, particularly focused on the effects of tire features such as lettering, sidewall geometry, rim geometry, and interaction with the vehicle body. The work is broken into two parts. Part 1 consisted of investigation of a canonical validation problem (turbulent flow over a cylinder) using existing tools with different meshes and turbulence models. Part 2 involved calculating drag differences over plate geometries with simple features (ridges and grooves) defined by Goodyear of approximately the size of interest for a tire. The results of part 1 show the level of noise to be expected in a drag calculation and highlight the sensitivity of absolute predictions to model parameters such as mesh size and turbulence model. There is 20-30% noise in the experimental measurements on the canonical cylinder problem, and a similar level of variation between different meshes and turbulence models. Part 2 shows that there is a notable difference in the predicted drag on the sample plate geometries, however, the computational cost of extending the LES model to a full tire would be significant. This cost could be reduced by implementation of more sophisticated wall and turbulence models (e.g. detached eddy simulations - DES) and by focusing the mesh refinement on feature subsets with the goal of comparing configurations rather than absolute predictivity for the whole tire.
With growing use of carbon fiber-epoxy in transportation systems, it is important to understand fire reaction properties of the composite to ensure passenger safety. Recently, a micro-scale pyrolysis study and macro-scale fire tests were performed using carbon fiber-epoxy at Sandia National Laboratories. Current work focuses on numerical modeling of the material conversion, pyrolysis, and gas-phase combustion that replicate the experiments. Large-eddy simulations (LES) and eddy-dissipation concept (EDC) approach are incorporated in the gas phase along with multiple relevant reaction model methods in the solid phase. The numerical methods that use multi-step pyrolysis rate expressions are validated by thermogravimetric analysis (TGA) results. The pyrolyzed fuel components participate in gas-phase combustion using a turbulent combustion model. The multi-phase combustion capability was further assessed using two cases: a single particle reaction and a solid panel exposed to strong radiant heat. The panel fire test indicates that the model accurately reproduces panel temperature profile while a weaker oxidation is predicted.
Safety basis analysts throughout the U.S. Department of Energy (DOE) complex rely heavily on the information provided in the DOE Handbook, DOE - HDBK - 3010, Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities, to determine radionuclide source terms. In calculating source terms, analysts tend to use the DOE Handbook's bounding values on airborne release fractions (ARFs) and respirable fractions (RFs) for various categories of insults (representing potential accident release categories). This is typically due to both time constraints and the avoidance of regulatory critique. Unfortunately, these bounding ARFs/RFs represent extremely conservative values. Moreover, they were derived from very limited small-scale bench/laboratory experiments and/or from engineered judgment. Thus, the basis for the data may not be representative of the actual unique accident conditions and configurations being evaluated. The goal of this research is to develop a more accurate and defensible method to determine bounding values for the DOE Handbook using state-of-art multi-physics-based computer codes. This enables us to better understand the fundamental physics and phenomena associated with the types of accidents in the handbook. In this year, this research included improvements of the high-fidelity codes to model particle resuspension and multi-component evaporation for fire scenarios. We also began to model ceramic fragmentation experiments, and to reanalyze the liquid fire and powder release experiments that were done last year. The results show that the added physics better describes the fragmentation phenomena. Thus, this work provides a low-cost method to establish physics-justified safety bounds by taking into account specific geometries and conditions that may not have been previously measured and/or are too costly to perform.
This study presents a design analysis for the development of highly efficient heat exchangers within stationary metal hydride heat pumps. The design constraints and selected performance criteria are applied to three representative heat exchangers. The proposed thermal model can be applied to select the most efficient heat exchanger design and provides outcomes generally valid in a pre-design stage. Heat transfer effectiveness is the principal performance parameter guiding the selection analysis, the results of which appear to be mildly (up to 13%) affected by the specific Nusselt correlation used. The thermo-physical properties of the heat transfer medium and geometrical parameters are varied in the sensitivity analysis, suggesting that the length of independent tubes is the physical parameter that influences the performance of the heat exchangers the most. The practical operative regions for each heat exchanger are identified by finding the conditions over which the heat removal from the solid bed enables a complete and continuous hydriding reaction. The most efficient solution is a design example that achieves the target effectiveness of 95%.
In this work we have presented a particle resuspension model implemented in the SNL code SIERRA/Fuego, which can be used to model particle dispersal and resuspension from surfaces. The method demonstrated is applicable to a class of particles, but would require additional parametric fits or physics models for extension to other applications, such as wetted particles or walls. We have demonstrated the importance of turbulent variations in the wall shear stress when considering resuspension, and implemented both shear stress variation models and stochastic resuspension models (not shown in this work). These models can be used in simulations with of physically realistic scenarios to augment lab-scale DOE Handbook data for airborne release fractions and respirable fractions in order to provide confidences for safety analysts and facility designers to apply in their analyses at DOE sites. Future work on this topic will involve validation of the presented model against experimental data and extension of the empirical models to be applicable to different classes of particles and surfaces.