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DOE OSTI2025

Explosive Soot Challenge (Final Report)

This project assembled a broad ensemble of modeling and experimentation tools to study the morphological and optical properties of detonation soots in explosive fireballs. A gram-scale hemispherical high explosive was studied in a low-pressure controlled environment using in-situ experimentation with diffusely illuminated visible absorption spectroscopy, particle sizing through light scattering techniques, and post-test collections with subsequent morphological analysis. Hydrocode modeling was performed to replicate the detonation flow observations, and subsequent aerosol kinetics models provided particle size distributions and extinction coefficients from the hydrocode results. Experimentally observed soot morphologies agreed with expectation from the literature - a bimodal distribution was found, brought upon by the particles growing to a size where their inertia and fluid wakes are non-negligible. The aerosol kinetics model did not replicate the observed bimodal size distribution for lack of a coagulation kernel to represent the behavior. To recover particulate optical properties, a spectrally resolved absorption spectroscopy method termed Spectral diffuse back-illuminated extinction imaging (SBI-EI) was developed and implemented on two explosive types. Inverting the absorption spectra using a Kramers-Kronig consistent method yielded the complex index of refraction for the soots produced by the explosives. This method resulted in an unrealistic index of refraction for one of the two explosives, and this is suspected to be due to the model neglecting scattering brought upon by the large particle sizes observed. In addition to the core work, three additional studies were performed in parallel. These investigated the impact of scattering on diffuse absorption spectroscopy, studied how soots oxidate and sublimate in a well-controlled shock tube, and laid the theoretical groundwork for a new collision kernel to replicate the bimodal size distribution from the observations. Summaries of these efforts are included at the end of this report.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2015

Next-Generation Ion Thruster Design Tool

Computational tools that accurately predict the performance of electric propulsion devices are highly desirable and beneficial to NASA and the broader electric propulsion community. The current state of the art in electric propulsion modeling relies heavily on empirical data and numerous computational "knobs." In Phase I of this project, Tech-X Corporation developed the most detailed ion engine discharge chamber model that currently exists. This kinetic model simulates all particles in the discharge chamber along with a physically correct simulation of the electric fields. In addition, kinetic erosion models are included for modeling the ion-impingement effects on thruster component erosion. In Phase II, Tech-X developed a user-friendly computer program for NASA and other governmental and industry customers. Tech-X has implemented a number of advanced numerical routines to bring the computational time down to a commercially acceptable level. NASA now has a highly sophisticated, user-friendly ion engine discharge chamber modeling tool.

Stolz, Peter↗

DOE OSTI2026

Data for Selective Oxidation of 3-Hydroxypropionic Acid to Malonic Acid over Pd/C: Mechanistic and Kinetic Study

Malonic acid (MA) is a high-value dicarboxylic acid with strong industrial demand, yet its current production heavily relies on petrochemical feedstocks. Here, we report the first systematic study for the sustainable production of MA via oxidation of 3-hydroxypropionic acid (3-HP) with a Pd/Carbon catalyst. The effects of oxidant type (O2 and H2O2), pH, and temperature on the reaction chemistry were comprehensively evaluated. Guided by experimental observation and DFT-calculated thermochemical energetics, reaction networks for 3-HP oxidation with both oxidants are proposed and validated through kinetic modeling. MA was identified as the primary oxidation product, while further oxidation yields acetic acid and oxalic acid. The kinetic model validated the network, displaying excellent agreement (R2 > 0.95). Kinetic observations also enabled a direct comparison between O2 and H2O2 and revealed their distinct behaviors. The model was further developed into a temperature-time map, providing insight into conditions that maximize MA production. Malonic acid selectivity of 56.9 % and yield of 50.5 % were achieved at 3 bar oxygen, equimolar NaOH:3-HP ratio, and 50 °C.

Bioproducts↗

DOE OSTI2021

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Uncertainty Quantification and Error Propagation in the Enthalpy and Entropy of Surface Reactions Arising from a Single DFT Functional

Accounting for parametric uncertainty in models is essential for quantifying the models’ predictive ability. Recently, approaches have been introduced to estimate parametric uncertainty in kinetic models while accounting for correlations among energy parameters. However, correlations have been estimated indirectly and correlations in entropies have not been accounted for. For surface-catalyzed microkinetic models of >C2 (more than two carbon-containing) molecules, which consist of thousands of reaction steps and intermediate surface species, first-principles density functional theory (DFT) is costly, and thus, estimation of thermochemistry and reaction barriers requires surrogate methods of DFT, such as group additivity and Brønsted–Evans–Polanyi relationships, respectively. For such parametrization, model uncertainty is unclear. This work develops a framework to overcome these gaps using group additivity and a single DFT functional. We estimate correlations in parameters of kinetic models and quantify uncertainty for thermochemistry, reaction barriers, reaction paths, and ultimately reaction rates, accounting also for the contribution of entropic uncertainty. Furthermore, the approach is illustrated on propane combustion and ethane oxidative dehydrogenation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1997

Heterogeneous Combustion of Porous Graphite Particles in Microgravity

Recent theoretical investigations on graphite particle combustion have employed several levels of heterogeneous reaction models, ranging from global to elementary models, to describe the oxidation of carbon to gaseous products. Unlike the counterpart homogeneous reaction models, these heterogeneous reaction models are not well developed because of the difficulties associated with decoupling the physical characteristics of the solid (e.g. surface area taking part in combustion) from the chemical kinetic data. This is certainly true for porous graphite particle combustion, where heterogeneous and homogeneous reactions occur within the pores and play an important role in the overall oxidation process. As a result, there are considerable uncertainties of physical phenomena predicted using different heterogeneous kinetic models available in the literature. A good example, discussed later in this paper, is the predicted critical particle size below which the mass burning rate becomes exponentially small. The main goal of this study is to understand the basic mechanism controlling such rapid changes in burning rates, by developing a model where physical contributions are decoupled from chemical rate constants in a consistent manner. Another important goal of the proposed study is to develop a truly intrinsic, detailed heterogeneous reaction model for porous graphite combustion at high-temperatures, and to derive a systematically reduced heterogeneous reaction model in terms of the elementary reaction rate constants of the detailed model. The validation of chemical kinetic models describing the heterogeneous and homogeneous combustion in and around a spherically symmetric porous graphite particle can be considerably simplified by experimental measurements obtained under microgravity conditions. A vital component of this study is to conduct such supporting experiments on particle burning rate and surface temperature using NASA microgravity facilities, in close coordination with the theoretical effort. The basic understanding obtained and models developed as part of this project will be useful for optimal design of coal combustion devices. These models can also be extended to investigate the role of heterogeneous chemistry on pollutant formation pathways in combustion devices. The theoretical approach developed here, with pore diffusion effects decoupled from the chemical effects, can also be extended to understand the heterogeneous combustion of other porous fuels, for example, combustion of magnesium in a CO2 environment for propulsion in the Martian atmosphere.

Chelliah, Harsha K.↗

DOE OSTI2021

Compositional patterning in irradiated alloys: Effective potentials and effective interfacial energy

Compositional patterning (CP) in binary alloys during energetic particle irradiation is studied using a kinetic model that considers two competing kinetic processes, a thermally activated one promoting macroscopic phase separation (MPS) of the concentration field c(r,t) and a forced one resulting in finite-range random atomic mixing. The forced mixing is modeled by a Gaussian relocation distribution with a characteristic distance R. A series of approximate kinetic models are introduced by expanding the mixing function into a series of n terms, thus replacing the non-local evaluations of the concentration field c(r'-r,t) by local derivatives of c(r,t). This approach makes it possible to obtain exact effective potentials and build steady-state diagrams for each order-n model. Phase field (PF) simulations using these order-n models reveal that near the onset of patterning, phase evolution is accurately described using an order-3 model, which changes smoothly from an extended Cahn-Hilliard free energy in the MPS regime to a one-mode Swift-Hohenberg functional in the CP regime. Deeper into the patterning regime, higher-order models are required to achieve convergence, yielding square-like concentration profiles characteristic of a strong segregation regime. These higher-order effective free energies are analogous to multimodal Swift-Hohenberg functionals. Here, a new definition for the effective interfacial energy is proposed in the CP regime, since the interfacial area is no longer an excess quantity in that regime, precluding the use of the standard thermodynamic definition of interfacial energy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation

Estimating the thermochemical properties of systems is important in many fields such as material science and catalysis. The Python multiscale thermochemistry toolbox (pMuTT) is a Python software library developed to streamline the conversion of ab-initio data to thermochemical properties using statistical mechanics, to perform thermodynamic analysis, and to create input files for kinetic modeling software. Its open-source implementation in Python leverages existing scientific codes, encourages users to write scripts for their needs, and allows the code to be expanded easily. The core classes developed include a statistical mechanical model in which energy modes can be included or excluded to suit the application, empirical models for rapid thermodynamic property estimation, and a reaction model to calculate kinetic parameters or changes in thermodynamic properties. In addition, pMuTT supports other features, such as Brønsted–Evans–Polanyi (BEP) relationships, coverage effects, and ab-initio phase diagrams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Vertical effective stress and temperature as controls of quartz cementation in sandstones: Evidence from North Sea Fulmar and Gulf of Mexico Wilcox sandstones

Here we present quantitative petrographic data, high spatial resolution oxygen isotope analyses of quartz cement, basin modelling and a kinetic model for quartz precipitation for two Paleocene-Eocene Wilcox Group sandstones from Texas and two Jurassic Fulmar Formation sandstones from the Central North Sea. At each location, one sandstone has been buried to ca. 145 °C and one to ca. 185 °C. A key difference between the Wilcox and Fulmar burial histories is that the Wilcox sandstones are currently at higher vertical effective stresses and, from basin modelling studies, have been subjected to generally higher vertical effective stresses through their burial history. The amounts of quartz cement in the Wilcox sandstones are between 12 and 18%, and between 2 and 6% in the Fulmar sandstones. High-spatial-resolution oxygen isotope data obtained from the quartz cements suggest temperature ranges for quartz precipitation from 60 to 80 °C to values approaching maximum burial temperature. Factors such as grain coatings or the timing of petroleum emplacement cannot explain the differences in the amounts of quartz cement. Petrographic data show that most of the silica for quartz cement can be derived from intergranular pressure dissolution. Although the sample set is small, we interpret the results to suggest that the differences in quartz cementation in Fulmar and Wilcox sandstones can be explained better by differences in their vertical effective stress history than their temperature history; in this case, the supply of silica rather than the precipitation of quartz becomes an important control on the rate and extent of cementation.

58 GEOSCIENCES↗

DOE OSTI2020

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called “lag time”). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5–10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1986

Direct solar-pumped iodine laser amplifier

In order to evaluate the feasibility of the solar pumped dye laser, the parametric study of a dye laser amplifier pumped by a solar simulator and flashlamp was carried out, and the amplifier gains were measured at various pump beam irradiances on the dye cell. Rhodamine 6G was considered as a candidate for the solar pumped laser because of its good utilization of the solar spectrum and high quantum efficiency. The measurement shows that a solar concentration of 20,000 is required to reach the threshold of the dye. The work to construct a kinetic model algorithm which predicts the output parameter of laser was progressed. The kinetic model was improved such that there is good agreement between the theoretical model and experimental data for the systems defined previously as flashlamp pumped laser oscillator, and the long path length solar pumped laser.

Han, Kwang S.↗

NASA NTRS2015

CFD Analysis of Emissions for a Candidate N+3 Combustor

An effort was undertaken to analyze the performance of a model Lean-Direct Injection (LDI) combustor designed to meet emissions and performance goals for NASA's N+3 program. Computational predictions of Emissions Index (EINOx) and combustor exit temperature were obtained for operation at typical power conditions expected of a small-core, high pressure-ratio (greater than 50), high T3 inlet temperature (greater than 950K) N+3 combustor. Reacting-flow computations were performed with the National Combustion Code (NCC) for a model N+3 LDI combustor, which consisted of a nine-element LDI flame-tube derived from a previous generation (N+2) thirteen-element LDI design. A consistent approach to mesh-optimization, spray-modeling and kinetics-modeling was used, in order to leverage the lessons learned from previous N+2 flame-tube analysis with the NCC. The NCC predictions for the current, non-optimized N+3 combustor operating indicated a 74% increase in NOx emissions as compared to that of the emissions-optimized, parent N+2 LDI combustor.

combustion chambers↗

NASA NTRS2019

CFD Evaluation of Lean-Direct Injection Combustors for Commercial Supersonics Technology

An overview is given of an effort that focused on using CFD analysis to complement design and configuration definition of Lean-Direct Injection (LDI) combustion concepts for NASA's Commercial Supersonic Transport (CST) program. The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for second and third generation LDI configurations at CST cruise conditions. All computations were performed with a consistent approach of mesh-generation, spray modeling, ignition and kinetics modeling. Emissions (EINOx) characteristics were predicted for CST cruise conditions, and compared with emissions data from experimental measurements to evaluate the fidelity of the CFD modeling approach to predict emissions changes in response to changes in supersonic cycle conditions.

nitrogen oxides injectors↗

NASA NTRS2019

Pilot Injector Redesign to Reduce N+3 Cycle Emissions for a Gas-Turbine Combustor

An overview is given of an effort for the use of CFD analysis to complement design and configuration definition of third generation Lean-Direct Injection combustion concepts (LDI-3) for NASA’s N+3 program. The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for a three-cup, nineteen-element flame tube array with redesigned pilot injectors to improve spray and emissions characteristics when compared to a previous LDI-3 design. All computations were performed with a consistent approach to mesh-generation, spray modeling, ignition and kinetics modeling for a ‘medium-power’ cycle condition. Computational predictions of the aerodynamics of a new pre-filming pilot injector were used to arrive at an optimized aerothermal design that meets effective area and fuel-air mixing criteria. The newly designed pilot injectors were shown to provide considerable improvements in aerodynamic stability, flame-tube pattern factor and NOx emissions, when compared to the original design.

nitrogen oxides injectors↗

NASA NTRS2019

Pilot Injector Redesign to Reduce N+3 Cycle Emissions for a Gas-Turbine Combustor

An overview is given of an effort for the use of CFD analysis to complement design and configuration definition of third generation Lean-Direct Injection combustion concepts (LDI-3) for NASA's N plus 3 program. The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for a three-cup, nineteen-element flametube array with redesigned pilot injectors to improve spray and emissions characteristics when compared to a previous LDI-3 design. All computations were performed with a consistent approach to mesh-generation, spray modeling, ignition and kinetics modeling for a "medium-power" cycle condition. Computational predictions of the aerodynamics of a new pre-filming pilot injector were used to arrive at an optimized aerothermal design that meets effective area and fuel-air mixing criteria. The newly designed pilot injectors were shown to provide considerable improvements in aerodynamic stability, flame-tube pattern factor and NOx emissions, when compared to the original design.

Nitrogen Oxides↗

NASA NTRS2019

CFD Evaluation Of Lean-Direct Injection Combustors for Commercial Supersonics Technology

Ajmani, Kumud↗

DOE OSTI2021

Autoignition study of iso -cetane/tetralin blends at low temperature

iso-Cetane and tetralin are the two fuel components commonly considered in literature diesel surrogates, and are hydrocarbon classes representative of iso-alkanes and naphthoaromatics, respectively. Since both surrogate components are involved in the key reactions controlling the autoignition reactivity of diesel surrogates, autoignition studies of iso-cetane, tetralin, and their blending behavior at low temperatures can be helpful in developing/refining chemical kinetic models of diesel surrogates, in order to better predict diesel ignition response under low temperature combustion conditions. In this investigation, autoignition experiments of iso-cetane, tetralin, and their binary mixtures at varying blending ratios have been conducted in a rapid compression machine (RCM) in the temperature/pressure range of 630–930 K and 10–20 bar. For the neat fuel components, the newly-acquired RCM data have been compared with the literature experimental results at some overlapping conditions. In addition, a chemical kinetic model describing the oxidation of iso-cetane and tetralin compiled/updated from the diesel surrogate model developed by Lawrence Livermore National Laboratory is used to simulate the experimental datasets. It is shown that this model exhibits good agreement with the experimental results of tetralin and also predicts the total ignition delay times of iso-cetane at lower temperatures reasonably well. However, the current model fails to fully capture the increase of total ignition delay time with increasing amount of tetralin in the binary blends observed in the present RCM experiments. Therefore, chemical kinetic analyses of the current model are conducted to help identify possible reasons leading to the discrepancies between simulations and experiments. Furthermore, the chemical kinetic interactions between iso-cetane and tetralin are explored by including additional cross-reactions among iso-cetane, tetralin, and their fuel fragments in the current model to assess their effects on model predictions. As a result, based on the chemical kinetic analysis results, future direction for model refinements is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗