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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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262 records · Page 15

EXTINCTION DROPLET SIZING MEASUREMENTS IN DIESEL RELEVANT SPRAYS

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination (DBI) imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path-integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced. This thesis aims to extend the initial development of the SAMR technique by presenting in detail: the experimental methodologies used in the SAMR technique, including the development of an ideal DBI setup for this technique; the data processing methodologies developed by the author; two-dimensional Sauter Mean Diameter measurements within diesel sprays for various experimental conditions; a summary of the various sources of measurement uncertainty; an assessment for how the sources of uncertainty affect the quantified SMD; and paths to improve the technique moving forward. The SMD results show that for low ambient density conditions droplets decrease in size as radial and axial position increases. For high ambient density conditions, however, the droplets show a stable size near the spray centerline and steadily increase in size as distance from the centerline increases. Additionally, this work provides 2-D droplet sizing maps which are particularly useful for model validation.

33 ADVANCED PROPULSION SYSTEMS↗

EXTINCTION DROPLET SIZING MEASUREMENTS IN DIESEL RELEVANT SPRAYS

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination (DBI) imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path-integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced. This thesis aims to extend the initial developmen of SAMR technique by presenting in detail: the experimental methodologies used in the SAMR technique, including the development of an ideal DBI setup for this technique; the data processing methodologies developed by the author; two-dimensional Sauter Mean Diameter measurements within diesel sprays for various experimental conditions; a summary of the various sources of measurement uncertainty; an assessment for how the sources of uncertainty affect the quantified SMD; and paths to improve the technique moving forward. The SMD results show that for low ambient density conditions droplets decrease in size as radial and axial position increases. For high ambient density conditions, however, the droplets show a stable size near the spray centerline and steadily increase in size as distance from the centerline increases. Additionally, this work provides 2-D droplet sizing maps which are particularly useful for model validation.

33 ADVANCED PROPULSION SYSTEMS↗

Measurement of Sauter Mean Diameter (SMD) in Diesel Sprays Using a Scattering-Absorption Measurement Ratio (SAMR) Technique

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial and temporal resolution of the corresponding droplet field. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced and demonstrated in diesel sprays using the Engine Combustion Network Spray D injector, however a more detailed treatment of measurement uncertainties has been needed. In the current work, we present a summary of the various sources of measurement uncertainty in the SAMR diagnostic, like those due to the experimental setup, data processing methods, and theoretical assumptions, and assess how these sources of uncertainty affect the quantified SMD. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. Careful evaluation and quantification of measurement uncertainties is important to support accurate model validation and to ensure the development of more predictive spray models.

33 ADVANCED PROPULSION SYSTEMS↗

Implementing a Stochastic Soot Model in a 3D Domain

In this document a highly detailed stochastic soot model limited to 0D simulations is coupled to 3D domains through the use of a Lagrangian parcel-Eulerian fluid method. Although both the stochastic soot model used and the Lagrangian parcel-Eulerian fluid method have long histories of development, their use, as described in this document, is novel and useful. Previous works significant to the model's development include documents from both the stochastic and simpler soot model genre and the fuel, aerosol, and other particle tracking and Lagrangian parcel-Eulerian fluid genres. Developing the theory behind the model is crucial to its implementation because of the unconventional Lagrangian parcel-Eulerian fluid representation. In fact, the Lagrangian parcel-Eulerian fluid coupling is only a means of simplifying the much more difficult theoretical model. Despite the accompanying assumptions, the complete model is validated from the bottom up and then again in a holistic fashion with promising results. Then the model is used in multiple case studies, showcasing capabilities not had by other models. The optical properties of soot generated in a Spray A simulation are calculated to find measured results are likely overpredicting the mass of soot along the central axis via KL extinction measurements. A thermophoresis submodel that calculates force based on the soot particles' shape is installed to find it has a high influence on the path of the heaviest soot particles. Investigations into the HACA mechanism for soot growth and the effect of syngas on soot in 3D domains are performed with much more detail than has been available before.

Strickland, Tyler↗

Prediction of Performance of a Pilot Scale Dual Fluidized Bed System for Chemical Looping with Oxygen Uncoupling

Chemical looping with oxygen uncoupling (CLOU) is a variant of chemical looping combustion that involves spontaneous release of gaseous oxygen in the fuel reactor, which enables efficient combustion of solid fuel char. The University of Utah has constructed a pilot-scale dual fluidized bed chemical looping process development unit (PDU) with a nominal thermal input of 200 kW. The CLOU oxygen carrier uses copper as the active metal, cycling between cupric (CuO) and cuprous (Cu2O) oxides. As an aid for design, troubleshooting and evaluation of the pilot system, a CFD model has been developed using CPFD Software’s Barracuda VR software. The 3D model includes both reactors, as well as loop seals and cyclone separators. Mechanisms describing CLOU reaction kinetics for cuprous oxide oxidation in the air reactor and cupric oxide reduction in the fuel reactor were adapted from previously done experimental work. Coal char kinetics were based on the carbon-hydrogen-nitrogen-oxygen-sulfur, CHNOS, method. Submodels for devolatilization, gasification, and homogenous gas-phase reactions used preexisting relationships in the literature. Results predict temperature profiles, concentration profiles, product gas composition, and CO¬2 capture efficiency. This paper presents results of a parametric study in which key operational variables were adjusted to determine the influence on simulated performance of the PDU. The adjusted variables include fuel feed rate, fuel particle size, total oxygen carrier inventory, oxygen carrier copper oxide loading, and oxygen carrier particle physical properties.

Reinking, Zachary↗

Experiment and simulation of high-speed gas jet penetration into a semicircular fluidized bed

This work marks the third in a series of experiments that were in a semi-circular, gas-fluidized bed with side jets. In this work, the particles are (nominally) 1 mm ceramic beads. The bed is operated just at and slightly above and below the minimum fluidization velocity and additional fluidization is provided by two high-speed gas located on the sides of the bed near the flat, front face of the unit. Two primary measurements are taken: high-speed video recording of the front of the bed and bed pressure drop from a tap in the back of the bed. Particle Image Velocimetry (PIV) is used to determine particle motion, characterized as a mean Froude number, from the high-speed video. A CFD-DEM model of the bed is presented using the recently released MFIX-Exa code. Four model subvariants are considered using two methods of representing the jets and two drag models, both of which are calibrated to exactly match the experimentally measured minimum fluidization velocity. Although it is more difficult to determine the jet penetration depths in a straightforward manner as in the previous works using Froude number contours, the CFD-DEM results compare quite well to the PIV measurements, particularly for submodel flow Syam. Unfortunately, the good agreement of the solids-phase is overshadowed by significant disagreement in the gas-phase data. Specifically, the predicted time averaged standard deviation of the pressure drop is found to be over an order of magnitude larger than measured. Due to the low value of the measurements, just 1% of the mean bed pressure drop, it seems possible that the data is in error. On the other hand, the model may not be accurately capturing pressure attenuation through an under-fluidized region in the back of the bed. Without the possibility additional experiments to test the validity of the data, this work is simply being reported “as is” without being able to indicate which, either the simulation or the experiment, is more correct.<br>

Fullmer, William D.↗

Modeling and Uncertainty Quantification of CESAR1 Solvent System for Post-Combustion Capture

This presentation is focused on the development of the CESAR1 solvent system model by the CCSI2 team and validation with pilot plant data from Technology Centre Mongstad. It also serves as an update of previous work by incorporating a new thermodynamic model of the system developed by collaborators from Heriot-Watt University through the SCOPE program. Finally, it includes some discussions on future directions of the project including collaboration with SCOPE to add the capability of amine emissions prediction along with some parametric uncertainty quantification work on the submodels.

Morgan, Joshua↗

A Decision-Based Iterative Modeling Framework for Probabilistic Performance Assessments - 18441

Radiological probabilistic performance assessments (PPAs) employ highly complex computer models to simulate the release of radionuclides from wastes in an engineered disposal facility, migration of these radionuclides over time, and resulting radiological dose to potentially exposed individuals. An iterative approach to PPA modeling is described to help define the appropriate complexity of the computer model. An initial model is developed that addresses all relevant processes and media, but that employs preliminary statistical parameter distributions to minimize the initial effort expended. Where appropriate, transport and exposure submodels with simplifying assumptions are also used in the initial model. Different assumptions and boundaries may be explored with the initial model to assess their importance in constraining model results. Exploration of the results of the initial model are used to determine the benefits of model refinements, and to guide such refinements to focus on specific areas of the model that most influence the model outputs of interest. This approach promotes efficiency and model parsimony, but does not compromise defensibility when performed in a transparent manner. Key model boundaries for a PPA include the time frame of the modeling (temporal boundaries), where future human receptors may be located (spatial boundaries), and what types of land uses and activities may exist in the future (exposure scenarios). Simplified transport and exposure models can be useful in helping decision makers and stakeholders establish such boundaries by analyzing the consequences of selecting different bounds and understanding which assumptions and boundaries have the greatest influence on the magnitude and distribution of model results. Pathway analysis and parameter sensitivity analysis performed on PPA model results are key components of the iterative modeling approach. The objective of pathway analysis is to identify the critical radionuclides and pathways contributing to radiation dose during the modeling performance period. An environmental 'pathway' is described by the connections from a waste package or cell in the disposal facility to a future human exposure event. These connections are commonly visualized using graphical means. A simple example of a potentially complete pathway for radon-222 is: radium-containing waste → radon emanation → upwards diffusion in cap material → diffusion/advection into a future building → inhalation exposure to a building occupant Parameter sensitivity analysis is conducted on the results of a PPA to identify those specific model input parameters whose distribution of values contributes the most to the distribution of target model output, such as annual radiation dose. Pathway and sensitivity analyses on initial modeling results provide information for guiding subsequent model development, and possibly interim decisions, by informing questions tied to the modeling objectives and performance criteria. For example, questions related to radiological doses from existing disposals may include: 1. Is radiation dose from radiological exposures either obviously negligible or obviously unacceptable based on initial modeling results? 2. If dose is not obviously negligible or unacceptable relative to applicable performance criteria, what model refinements would reduce uncertainty in the results to better inform decisions? (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

JetGP: A derivative enhanced Gaussian process library

Derivative enhanced Gaussian Processes (DEGPs) can significantly improve surrogate model accuracy over standard Gaussian Process (GP) formulations by incorporating derivative information. However, standard implementations scale poorly with dimension, limiting their use in high dimensional engineering problems. JetGP is a Python framework that unifies existing derivative enhanced GP methodologies into a single library and extends them to support arbitrary order derivative information. The library implements four complementary formulations: standard derivative enhanced Gaussian Processes (DEGP), directional DEGP (DDEGP), generalized directional DEGP (GDDEGP), and weighted DEGP (WDEGP). By unifying these approaches in a consistent interface with robust numerical implementations, JetGP enables practitioners to balance predictive accuracy and computational efficiency for high dimensional optimization, uncertainty quantification, and sensitivity analysis in engineering design.

Derivative enhanced Gaussian process↗

Augmenting the Structural Dynamics Workflow to Reduce Development Times [Slides]

The structural dynamics workflow at LANL stands to be improved by implementing methods and techniques related to reduced-order finite-element modeling (FEM), pretest predictions, and FEM-test correlation and updating. The benefits of these industry-standard practices are demonstrated in this work. Software used for this project included Ansys 2023 R2 (Mechanical and Spaceclaim), Creo Parametric 8.0, MathCAD Prime 8.0, Matlab R2023b.

42 ENGINEERING↗