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DOE OSTI2025

Detailed Design and Cost Estimation of a 300 MWe Oxy-Fuel sCO2 Turbine

The detailed design of a 300 MWe, utility scale oxy-fuel turbine has been completed for purposed operation in the sCO2 direct fired Allam-Fetvedt cycle, targeting near-zero emissions and a 50% LHV system efficiency. The turbine and its supporting plant aim to offer a lower levelized cost of energy than a natural gas combined cycle plant employing carbon capture. The oxy-fuel turbine conditions include an inlet temperature of 1150°C and inlet pressure of 305 bar, representing temperatures near that of a gas turbine simultaneously with pressures near an ultra-supercritical steam turbine. The combustor housing and turbine designs were completed according to the ASME BPVC; the turbine case specifically incorporates a multi-body design with inner high-pressure barrel case and low-pressure (30 bar) horizontally split outer case of low-chromium steel material. Lateral rotordynamic evaluation demonstrated acceptable vibration response for a range of imbalance conditions per API standards. The cooling flow required in the six-stage turbine flowpath for 30,000 hr. blade and stator lifetime is predicted through thermal and structural modeling of the first stage. The provided cost estimate of the turbine is formed through a combination of scaled up-costs from procured 10 MWe scale sCO2 turbomachinery hardware, and vendor provided budgetary quotes of larger components including the turbine case requiring casting, welding, and final machining processes. The performance and cost estimation of the oxy-fuel turbine predicted for the completed detailed design provides important information towards future development needs for market penetration of utility scale direct fired sCO2 power cycles.

Marshall, Michael [Southwest Research Institute, S↗

NASA NTRS2011

Limits to Mercury's Magnesium Exosphere from MESSENGER Second Flyby Observations

The discovery measurements of Mercury's exospheric magnesium, obtained by the MErcury Surface. Space ENvironment, GEochemistry. and Ranging (MESSENGER) probe during its second Mercury flyby, are modeled to constrain the source and loss processes for this neutral species. Fits to a Chamberlain exosphere reveal that at least two source temperatures are required to reconcile the distribution of magnesium measured far from and near the planet: a hot ejection process at the equivalent temperature of several tens of thousands of degrees K, and a competing, cooler source at temperatures as low as 400 K. For the energetic component, our models indicate that the column abundance that can be attributed to sputtering under constant southward interplanetary magnetic field (IMF) conditions is at least a factor of five less than the rate dictated by the measurements, Although highly uncertain, this result suggests that another energetic process, such as the rapid dissociation of exospheric MgO, may be the main source of the distant neutral component. If meteoroid and micrometeoroid impacts eject mainly molecules, the total amount of magnesium at altitudes exceeding approximately 100 km is found to be consistent with predictions by impact vaporization models for molecule lifetimes of no more than two minutes. Though a sharp increase in emission observed near the dawn terminator region can be reproduced if a single meteoroid enhanced the impact vapor at equatorial dawn, it is much more likely that observations in this region, which probe heights increasingly near the surface, indicate a reservoir of volatile Mg being acted upon by lower-energy source processes.

Sarantos, Menelaos↗

NASA NTRS2017

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

Computational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.

Monte Carlo Modeling↗

NASA NTRS2017

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

Atomic Oxygen↗

DOE OSTI2023

$\Sigma (1385)^{\pm }$ resonance production in Pb–Pb collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV

Hadronic resonances are used to probe the hadron gas produced in the late stage of heavy-ion collisions since they decay on the same timescale, of the order of 1–10 fm/c, as the decoupling time of the system. In the hadron gas, (pseudo)elastic scatterings among the products of resonances that decayed before the kinetic freeze-out and regeneration processes counteract each other, the net effect depending on the resonance lifetime, the duration of the hadronic phase, and the hadronic cross sections at play. In this context, the Σ(1385) ± particle is of particular interest as models predict that regeneration dominates over rescattering despite its relatively short lifetime of about 5.5 fm/c. The first measurement of the Σ(1385) ± resonance production at midrapidity in Pb–Pb collisions at $\sqrt{s_{NN}}$=5.02 TeV with the ALICE detector is presented in this Letter. The resonances are reconstructed via their hadronic decay channel, Λπ, as a function of the transverse momentum (p T ) and the collision centrality. The results are discussed in comparison with the measured yield of pions and with expectations from the statistical hadronization model as well as commonly employed event generators, including PYTHIA8/Angantyr and EPOS3 coupled to the UrQMD hadronic cascade afterburner. None of the models can describe the data. For Σ(1385) ± , a similar behaviour as K*(892) 0 is observed in data unlike the predictions of EPOS3 with afterburner.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1978

Asteroid collisions, craters, regoliths, and lifetimes

Laboratory experiments and computer modeling are used to predict the development of regoliths on all asteroids more than a few tens of kilometers in diameter, allowing for a wide range in the intrinsic strength of asteroidal surface materials. The high frequency of interasteroid collisions requires nearly all asteroids to be fragments of precursors.

Chapman, C. R.↗

NASA NTRS1992

Development of a simplified gravitational model for lifetime studies of lunar satellite orbits

Future lunar missions will involve long stay times in orbit about the moon. The moon's nonspherical gravitational field is the primary perturbation on a low altitude parking orbit. The objective of this study is to determine the orbital lifetime of a nearly circular low altitude parking orbit. In the present analysis, a simplified gravitational model of the moon is introduced which will enable mission designers to easily predict long term changes in lunar parking orbits at the preliminary design level. The development of a simplified gravitational model with sufficient accuracy is necessary to investigate orbital lifetimes for the large number of orbital parameters possible. Utilization of a simplified model will significantly reduce the required computational time needed to perform this analysis. By investigating the effects of the lunar gravity model on the various parking orbits, the parameters which are important in determining lifetime predictions are identified.

Meyer, Kurt W.↗

DOE OSTI2025

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

NASA NTRS1979

Spiral clouds on Mars - A new atmospheric phenomenon

Viking Orbiter images obtained during the 1978 northern summer on Mars show unusual spiral cloud patterns at high northern latitudes. Well-developed spirals occurred only during early summer at a time when the sublimation of the annual CO2 frost cap in the north had ceased. The systems ranged in size from 200 to 500 km and all spirals were wound in a counter-clockwise sense. An explanation is proposed, based on the radiatively driven instability described by Gierasch, Ingersoll, and Williams. The model predicts disturbances with the correct scale and lifetime. However, the successful development of the spirals depends on the existence of weak mean winds, suggesting that these instabilities can only develop at special null points in the general circulation. It is argued that such special circumstances are most likely to occur during early northern summer and are less likely to obtain at a comparable season in the Southern Hemisphere.

Gierasch, P.↗

NASA NTRS1996

Statistical Technique for Intermediate and Long-Range Estimation of 13-Month Smoothed Solar Flux and Geomagnetic Index

This report documents the Marshall Space Flight Center (MSFC) 13-month smoothed solar flux (F(sub 10.7)) and geomagnetic index (A(sub p)) intermediate (months) and long-range (years) statistical estimation technique, referred to as the MSFC Lagrangian Linear Regression Technique (MLLRT). Estimates of future solar activity are needed as updated input to upper atmosphere density models used for satellite and spacecraft orbital lifetime predictions. An assessment of the MLLRT computer program's products is provided for 5-year periods from the date estimates were made. This was accomplished for a number of past solar cycles.

Niehuss, K. O.↗

DOE OSTI2021

Modeling the Fundamental Radiation Chemistry of the Organic Diluent, and the Effect of Metal Ion Complexation on the Radiochemical Behavior of Active Compounds

All used nuclear fuel (UNF) reprocessing technologies must operate efficiently in the presence of an intense, multi-component (predominantly alpha, beta, and gamma) radiation field. Consequently, radiation-induced degradation of reprocessing systems is of concern, as it negatively impacts process performance over time due to the destruction of both active compounds (ligands, phase modifiers, holdback agents, etc.) and the formation of degradation products. Reprocessing solvent system radiolysis has been linked to changes in separation efficiency and physical properties of solvent mixtures, solvent-recycle longevity, crud formation, and other unexpected outcomes that impact the efficient recovery of valuable materials (e.g., the actinides) and the volume of hazardous radioactive waste for final disposal, i.e., in a geological repository. Consequently, a fundamental understanding of radiolytic processes and their effects on reprocessing solvent system performance is critical for: (i) the cost-effective development and innovation of separation technologies; (ii) the design and implementation of predictive radiation chemical models for process monitoring and lifetimes; and (iii) potentially the ability to exploit radiolytic phenomenon to our benefit, e.g., strategic radiolysis of active molecules to liberate specific degradation products that aid subsequent process stages. Despite extensive investigation into the radiolytic behavior of active solvent system compounds, little attention has been given to understanding (i) the radiation chemical behavior and modification of the organic diluent and (ii) the effect of metal ion complexation on the radiochemical behavior of active compounds.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

NASA NTRS2006

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Ovenvrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter error are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

stress ratios↗

DOE OSTI2021

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗

NASA NTRS1985

Preliminary study: Moisture-polymer interaction. Stuby objectives

The problems associated with mathematically modeling water-module interaction phenomena, including sorption and desorption, diffusion, and permeation are discussed. With reliable analytical models, an extensive materials data base, and solar radiation surface meteorological observations (SOLMET) weather data, predicting module lifetimes in realistic environments can become a practical reality. The status of the present techniques of simulating the various transport mechanisms was reported. The Dent model (a modified Brunauer-Emmet-Teller) approach represented polyvinyl butyral (PVB) sorption data. A 100-layer material model and Fick's diffusion model gave diffusivity values exhibiting adequate agreement with those measured for PVB. Diffusivity of PVB is concentration dependent, decreasing as the water content in PVB increases. The temperature dependence of diffusion in PVB is well modeled by the Arrhenius rate equation. Equilibrium conductivity and leakage current data are well represented by Hearle's model for bulk ionic conductivity. A nodal network analysis using the Systems Improved Numerical Differencing Analyzer (SINDA) Thermal Analyzer gave reasonable correlation with measurable data. It is concluded that realistic lifetime predictions seem to be feasible.

Wen, L. C.↗

DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

NASA NTRS2002

Great (Flame) Balls of Fire! Structure of Flame Balls at Low Lewis-number-2 (SOFBALL-2)

Everyone knows that an automobile engine wastes fuel and energy when it runs with a fuel-rich mixture. 'Lean' burning, mixing in more air and less fuel, is better for the environment. But lean mixtures also lead to engine misfiring and rough operation. No one knows the ultimate limits for lean operation, for 'weak' combustion that is friendly to the environment while still moving us around. This is where the accidental verification of a decades-old prediction may have strong implications for designing and running low-emissions engines in the 21st century. In 1944, Soviet physicist Yakov Zeldovich predicted that stationary, spherical flames are possible under limited conditions in lean fuel-air mixtures. Dr. Paul Ronney of the University of Southern California accidentally discovered such 'flame balls' in experiments with lean hydrogen-air mixtures in 1984 during drop-tower experiments that provided just 2.2 seconds of near weightlessness. Experiments aboard NASA's low-g aircraft confirmed the results, but a thorough investigation was hampered by the aircraft's bumpy ride. And stable flame balls can only exist in microgravity. The potential for investigating combustion at the limits of flammability, and the implications for spacecraft fire safety, led to the Structure of Flame Balls at Low Lewis-number (SOFBALL) experiment flown twice aboard the Space Shuttle on the Microgravity Sciences Laboratory-1 (MSL-1) in 1997. Success there led to the planned reflight on STS-107. Flame balls are the weakest fires yet produced in space or on Earth. Typically each flame ball produced only 1 watt of thermal power. By comparison, a birthday candle produces 50 watts. The Lewis-number measures the rate of diffusion of fuel into the flame ball relative to the rate of diffusion of heat away from the flame ball. Lewis-number mixtures conduct heat poorly. Hydrogen and methane are the only fuels that provide low enough Lewis-numbers to produce stable flame balls, and even then only for very weak, barely flammable mixtures. Nevertheless, under these conditions flame balls give scientists the opportunity to test models in one of the simplest combustion experiments possible. SOFBALL-2 science objectives include: Improving our understanding of the flame ball phenomenon; Determining the conditions under which flame balls exist; Testing predictions of flame ball lifetimes; Acquiring more precise data for critical model comparison.

Ronney, Paul↗

NASA NTRS2001

An Overview of Modeling Middle Atmospheric Odd Nitrogen

Odd nitrogen (N, NO, NO2, NO3, N2O5, HNO3, HO2NO2, ClONO2, and BrONO2) constituents are important components in the control of middle atmospheric ozone. Several processes lead to the production of odd nitrogen (NO(sub y)) in the middle atmosphere (stratosphere and mesosphere) including the oxidation of nitrous oxide (N2O), lightning, downflux from the thermosphere, and energetic charged particles (e.g., galactic cosmic rays, solar proton events, and energetic electron precipitation). The dominant production mechanism of NO(sub y) in the stratosphere is N2O oxidation, although other processes contribute. Mesospheric NO(sub y) is influenced by N2O oxidation, downflux from the thermosphere, and energetic charged particles. NO(sub y) is destroyed in the middle atmosphere primarily via two processes: 1) dissociation of NO to form N and O followed by N + NO yielding N2 + O to reform even nitrogen; and 2) transport to the troposphere where HNO3 can be rapidly scavenged in water droplets and rained out of the atmosphere. There are fairly significant differences among global models that predict NO(sub y). NO(sub y) has a fairly long lifetime in the stratosphere (months to years), thus disparate transport in the models probably contributes to many of these differences. Satellite and aircraft measurement provide modeling tests of the various components of NO(sub y). Although some recent reaction rate measurements have led to improvements in model/measurement agreement, significant differences do remain. This presentation will provide an overview of several proposed sources and sinks of NO(sub y) and their regions of importance. Multi-dimensional modeling results for NO(sub y) and its components with comparisons to observations will also be presented.

Jackman, Charles H.↗