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At least 1,459 records · Page 81

Machine Learning Guided Synthesis of Flash Graphene

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low-value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves an r 2 score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction-limited to diffusion-limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta-learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. Furthermore, these results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.

01 COAL, LIGNITE, AND PEAT↗

Stochastic inverse problem in the radiation of noise

The reported investigation is concerned with a stochastic inverse radiation problem in a uniform medium. The problem is illustrated with the aid of a simple model consisting of an array of point sources. The entropy functional is chosen to be the structural functional in determining the source distribution. A general theory for the stochastic inverse problem is introduced. It is shown that the general procedure yields the methods of the Lagrangian multiplier, when the structural and residual functionals are specialized. Tihonov's regularization and a method related to generalized or pseudoinverses are also obtained. Examples considered for purposes of illustration are related to a continuous source with the least noise intensity, a continuous source with a potential, and an axisymmetric line source.

Chow, P. L.↗

Fuel injector: Air swirl characterization aerothermal modeling, phase 2, volume 1

A well integrated experimental/analytical investigation was conducted to provide benchmark quality relevant to a prefilming type airblast fuel nozzle and its interaction with the combustor dome air swirler. The experimental investigation included a systematic study of both single-phase flows that involved single and twin co-axial jets with and without swirl. A two-component Phase Doppler Particle Analyzer (PDPA) was used to document the interaction of single and co-axial air jets with glass beads that simulate nonevaporating spray and simultaneously avoid the complexities associated with fuel atomization processes and attendant issues about the specification of relevant boundary conditions. The interaction of jets with methanol spray produced by practical airblast nozzle was also documented in the spatial domain of practical interest. Model assessment activities included the use of three turbulence models (k-epsilon, algebraic second moment (ASM), and differential second moment (DSM)) for the carrier phase, deterministic or stochastic Lagrangian treatment of the dispersed phase, and advanced numerical schemes. Although qualitatively good comparison with data was obtained for most of the cases investigated, the model deficiencies in regard to modeled dissipation rate transport equation, single length scale, pressure-strain correlation, and other critical closure issues need to be resolved before one can achieve the degree of accuracy required to analytically design combustion systems.

Nikjooy, M.↗

Fuel Injector: Air swirl characterization aerothermal modeling, phase 2, volume 2

A well integrated experimental/analytical investigation was conducted to provide benchmark quality data relevant to prefilming type airblast fuel nozzle and its interaction with combustor dome air swirler. The experimental investigation included a systematic study of both single-phase flows that involved single and twin co-axial jets with and without swirl. A two-component Phase Doppler Particle Analyzer (PDPA) equipment was used to document the interaction of single and co-axial air jets with glass beads that simulate nonevaporating spray and simultaneously avoid the complexities associated with fuel atomization processes and attendant issues about the specification of relevant boundary conditions. The interaction of jets with methanol spray produced by practical airblast nozzle was also documented in the spatial domain of practical interest. Model assessment activities included the use of three turbulence models (k-epsilon, algebraic second moment (ASM) and differential second moment (DSM)) for the carrier phase, deterministic or stochastic Lagrangian treatment of the dispersed phase, and advanced numerical schemes. Although qualitatively good comparison with data was obtained for most of the cases investigated, the model deficiencies in regard to modeled dissipation rate transport equation, single length scale, pressure-strain correlation, and other critical closure issues need to be resolved before one can achieve the degree of accuracy required to analytically design combustion systems.

Nikjooy, M.↗

Co-Location of Cellulosic Bioethanol and Alcohol-to-Jet (ATJ) Production Facilities for Targeted Scale-Up of Sustainable Aviation Fuel (SAF) Production

Achieving aerospace industry net-zero emissions by 2050 requires rapid scaling of sustainable aviation fuel (SAF) production. Leveraging existing infrastructure, proven technologies like Alcohol-to-Jet (ATJ), and low carbon intensity (CI) feedstocks (e.g., switchgrass and miscanthus) can support this transition and help achieve near-term emissions reduction targets. This study evaluates the implications of lignocellulosic ethanol biorefinery siting and integration with petroleum refineries to produce SAF across 1000 sites randomly sampled from areas suitable for perennial grasses in the U.S. rainfed region. To better understand the logistics of material transport and handoffs, we integrated models of biomass harvest, transport, ethanol, and ATJ production in a stochastic framework based on Monte Carlo simulations to characterize SAF minimum selling price (MSP) and carbon intensity (CI), considering site-specific parameters (e.g., feedstock production, transportation, taxes, incentives). The results indicate trade-offs between MSP and CI across locations, with median MSP ranging from 7.9 to 12.8 USD·gal −1 and CI from −9.7 to 39.4 gCO 2 e·MJ −1 . Despite high estimated decarbonization costs (580 USD·tonCO 2 e −1 ), our results indicate that site-specific deployment of ATJ with low-CI feedstocks can improve sustainability outcomes. The framework provides a systematic approach to assess cost and sustainability trade-offs across locations, considering the end-to-end supply chain and supporting an informed investment in SAF production.

09 BIOMASS FUELS↗

Coupling Warm Rain With an Eddy Diffusivity/Mass Flux Parameterization: 2. Sensitivities and Comparison to Observations

Abstract This is the second part of the description and validation of the coupling of a warm‐rain microphysics scheme to a stochastic multi‐plume eddy‐diffusivity/mass‐flux parameterization. Part 1 provides the model description and initial validation of the parameterization in a single column model (SCM) against large eddy simulations. This manuscript provides additional comparisons against satellite observations of 500 unique simulation cases, an analysis of model parameter‐based sensitivities in those 500 cases, and an evaluation of the idealized LES case study paradigm for parameterization development. The SCM is forced by a weather reanalysis in the subtropical northeast Pacific region characterized by the stratocumulus‐to‐cumulus cloud transition. 18 scalar outputs are examined to identify the sensitivities to 22 of the model's parameters. The model is highly sensitive to parameters that determine the behavior of convective plumes, which collectively lead to the most sensitivity in 13 of the 18 outputs. Only a few parameters contribute sensitivities that are not highly correlated with those of other parameters. While forcing the model with two canonical field campaign cases results in similar picture of which parameters lead to high sensitivity in model outputs, the sensitivity magnitudes can be overestimated compared to when the model is forced by weather reanalyzes.

54 ENVIRONMENTAL SCIENCES↗

Position-dependent Voronoi probability distribution functions for matter and halos

Here, we measure the Voronoi density probability distribution function (PDF) for both dark matter and halos in N-body simulations. For the dark matter, Voronoi densities represent the matter density field smoothed on a uniform mass scale, which approximates the Lagrangian density field. For halos, the Voronoi densities contain information about the local environment of each halo. We measure the halo virial masses, the total amount of dark matter within each halo Voronoi cell, and the halo Voronoi cell volumes, and we show how halo abundances depend on these three quantities. We then study the position-dependent Voronoi density PDF, measured within finite subregions of the Universe, using separate universe simulations. We demonstrate that the spatial variation of the position-dependent PDF is due to large-scale density fluctuations, indicating that the position-dependent PDF is a biased tracer of large-scale structure. We measure this bias for the dark matter, and interpret it as the bias of regions of the Lagrangian density field that are selected based on density. For the halos, this bias can be interpreted as a form of assembly bias. We present the mapping from late-time to early-time Voronoi density for each simulation dark matter particle, which is highly stochastic. We compare the median of this stochastic map with spherical collapse calculations and discuss challenges involved in modeling the evolution of the density field on these scales.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Single-pass Cr:ZnSe amplifier for broadband infrared undulator radiation

An amplifier based on a highly-doped chromium zinc-selenide (Cr:ZnSe) crystal is proposed to increase the pulse energy emitted by an electron bunch after it passes through an undulator magnet. The primary motivation is a possible use of the amplified undulator radiation emitted by a beam circulating in a particle accelerator storage ring to increase the particle beam’s phase-space density—a technique dubbed optical stochastic cooling (OSC). This paper uses a simple four energy level model to estimate the single-pass gain of Cr:ZnSe and presents numerical calculations combined with wave-optics simulations of undulator radiation to estimate the expected properties of the amplified undulator wave-packet.

43 PARTICLE ACCELERATORS↗

State equations for an n-body spacecraft

Considerable attention, in the open literature, is being focused on the problem of developing a suitable set of deterministic dynamical equations for a complex spacecraft. The present paper addresses the problem of determining a set of state equations for an n-body spacecraft. The approach used in obtaining the state equations involves the application and interpretation of advanced dynamical principles. This set of state equations can be effectively used in the development of a stochastic controller for the spacecraft (in this latter development, the deterministic model developed in the present paper will be appropriately corrupted by plant noise). The major effort in the paper revolves around the determination of the plant matrices and the specification of the state vector and the control vector.

Larson, V.↗

Navigation capability for an ion drive rendezvous with Halley's Comet

Navigation accuracies are presented for a 1985 rendezvous with Halley's Comet using an ion propulsion system. Individual error sources are examined to determine their relative contributions to final delivery errors. The sensitivity of delivery accuracy to stochastic thrust variations is demonstrated by considering a baseline thrust error model and a more benign alternative model. Also studied are the effects of increased comet ephemeris uncertainties and of operational time delays between the orbit determination process and the guidance implementation.

Thornton, C. L.↗

A high speed implementation of the random decrement algorithm

The algorithm is useful for measuring net system damping levels in stochastic processes and for the development of equivalent linearized system response models. The algorithm works by summing together all subrecords which occur after predefined threshold level is crossed. The random decrement signature is normally developed by scanning stored data and adding subrecords together. The high speed implementation of the random decrement algorithm exploits the digital character of sampled data and uses fixed record lengths of 2(n) samples to greatly speed up the process. The contributions to the random decrement signature of each data point was calculated only once and in the same sequence as the data were taken. A hardware implementation of the algorithm using random logic is diagrammed and the process is shown to be limited only by the record size and the threshold crossing frequency of the sampled data. With a hardware cycle time of 200 ns and 1024 point signature, a threshold crossing frequency of 5000 Hertz can be processed and a stably averaged signature presented in real time.

Kiraly, L. J.↗

Expected cycle life versus depth of discharge relationships of well behaved single cells and cell strings

The factors that might influence the cycle life vs. depth of discharge relationship are examined. This is done first at the single cell level using a progressively more complex cell life model. This is then extended to multicell battery strings where the stochastic aspects associated with groupings of cells are introduced. These relationships are important when considering the weight, cost, and life of battery packs. The results of this theoretical study are compared with a recent review of actual cell cycling data. The factors examined are the rate of capacity loss, the amount of excess capacity built into the cells, and the penalty in capacity loss resulting from the use of deep depths of discharge. This study suggests that the relationship between cycle life and depth of discharge is not one that can be varied of significantly improved by cell research. The relationship appears to be determined by certain more or less fixed cell parameters. Among multicell strings, the standard deviation, as expected, plays an important role in determining overall battery life.

Thaller, L. H.↗

A high-speed implementation of the random decrement algorithm

The algorithm is useful for measuring net system damping levels in stochastic processes and for the development of equivalent linearized system response models. The algorithm works by summing together all subrecords which occur after predefined threshold level is crossed. The random decrement signature is normally developed by scanning stored data and adding subrecords together. The high speed implementation of the random decrement algorithm exploits the digital character of sampled data and uses fixed record lengths of 2(n) samples to greatly speed up the process. The contributions to the random decrement signature of each data point was calculated only once and in the same sequence as the data were taken. A hardware implementation of the algorithm using random logic is diagrammed and the process is shown to be limited only by the record size and the threshold crossing frequency of the sampled data. With a hardware cycle time of 200 ns and 1024 point signature, a threshold crossing frequency of 5000 Hertz can be processed and a stably averaged signature presented in real time.

Kiraly, L. J.↗

Probability of Failure and Risk Assessment of Propulsion Structural Components

Due to increasing need to account for the uncertainties in material properties, loading conditions, or geometries, a methodology was developed to determine structural reliability and the assess the risk associated with it. The methodology consists of a probabilistic structural analysis by a probabilistic finite element computer code Nonlinear Evaluation of Stochastic Structures Under Stress (NESSUS) and a generic probabilistic material properties model. The methodology is versatile and is equally applicable to high and cryogenic temperature structures. Results obtained demonstrate that the whole issue of structural reliability and risk can be formally evaluated using the methodology developed which is inclusive of uncertainties in material properties, structural parameters and loading conditions. The methodology is described in some detail with illustrative examples.

Shiao, Michael C.↗

Probability of failure and risk assessment of propulsion structural components

Because of the increasing need to account for the uncertainties in material properties, loading conditions, geometry, etc., a methodology was developed to determine structural reliability and to assess the associated risk. The methodology consists of a probabilistic structural analysis by a probabilistic finite element computer code, numerical evaluation of stochastic structures under stress (NESSUS), and a generic probabilistic material property model. The methodology is versatile and is equally applicable to structures operating at high and cryogenic temperature environments. Results obtained demonstrate that the issues of structural reliability and risk can be formally evaluated by using the methodology developed which is inclusive of the uncertainties in material properties, structural parameters, and loading conditions. The methodology is described in some detail with illustrative examples.

Shiao, Michael C.↗

Integrated Demand Management Techport Closeout

Over the period 2016 to 2020, Integrated Demand Management (IDM) concept, procedures, and tools have been developed - first for clear-weather and a single airport constraint and then expanded to handle a multi-constraint problem during convective weather at Newark (EWR), LaGuardia (LGA) and Philadelphia (PHL) airports. The concept was evaluated in a series of human-in-the-loop simulations to confirm concept benefits in terms of better schedule predictability, reduction of delays, and increased throughput, especially during convective weather. In addition, other conditions with mixed participation of multi-trajectories from the airlines were evaluated that showed significant benefits to the individual airlines as well as the overall traffic flow. The IDM concept was initiated in the SMART-NAS project, was completed under the ATM-X project, and was developed collaboratively with the FAA and airline partners. Over the course of IDM development, NASA researchers produced 19 conference papers and publications. Outside supporting organizations, funded by IDM, produced 20 additional conference papers and publications, in which they advanced fundamental research on topics such as better stochastic traffic demand prediction, and application of machine learning techniques for modeling traffic management initiatives. Final concept procedures and tool specifications have been transferred to the FAA Air Traffic Organization Operational Concepts, Validation, and Requirements group.

William N Chan↗

Computational Study of Oxidative Etch Pitting in FiberForm and the Effect on Its Material Properties

Erosion of carbon due to oxidation does not occur uniformly but through the formation of localized etch pits because of active surface sites. These active sites are formed due to the presence of atomic defects on the carbon surface, and have much higher reactivity compared to average non-defective sites. Thus, these active sites are first to react during ablation, resulting in their removal. This causes all the neighboring atoms to be defective and increase their reactivity, thus leading to the localized carbon removal around these “active” sites. In this manner, these highly reactive defective sites serve as nucleation sites for the formation and growth of etch pits with potentially detrimental effects on the structural integrity. In order to understand the influence of these etch pits on the material properties of carbon fiber microstructures, we have developed a new capability within direct simulation Monte Carlo (DSMC) to capture the etch pit formation process. This capability is developed within the DSMC code SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and can model the material removal in presence of active sites leading to the formation of etch pits. The focus of the current work will be to study the effect of etch pits on the material properties of FiberForm, a commonly used base material within many thermal protection system materials (TPS). The microstructure of virgin FiberForm obtained directly from X-ray microtomography experiments is used within SPARTA to obtain the ablated geometries with etch pits. These pitted microstructures are then imported within the Porous Microstructure Analysis (PuMA) software and various material properties such as elasticity, thermal conductivity, and permeability are computed. The variation of these properties as a result of the complex evolution of the surface topology due to etch pit formation is studied and analyzed. Furthermore, the effect of pitting is compared to the case of shrinking fibers, which has been the standard for modelling ablation of carbon structures; and significant differences are observed. Thus, such a physically realistic modeling of material removal through the formation of etch pits will be helpful in predicting the degradation of carbon-based TPS more accurately during oxidation; as well as other mechanisms such as spallation, which involves the removal of chunks of material into the flow due to etch pit growth. This will ultimately improve our understanding of the failure modes in these materials due to ablation.

Carbon Ablators↗

Computational Study of Oxidative Etch Pitting in FiberForm and the Effect on Its Material Properties

Erosion of carbon due to oxidation does not occur uniformly but through the formation of localized etch pits because of active surface sites. These active sites are formed due to the presence of atomic defects on the carbon surface, and have much higher reactivity compared to average non-defective sites. Thus, these active sites are first to react during ablation, resulting in their removal. This causes all the neighboring atoms to be defective and increase their reactivity, thus leading to the localized carbon removal around these “active” sites. In this manner, these highly reactive defective sites serve as nucleation sites for the formation and growth of etch pits with potentially detrimental effects on the structural integrity. In order to understand the influence of these etch pits on the material properties of carbon fiber microstructures, we have developed a new capability within direct simulation Monte Carlo (DSMC) to capture the etch pit formation process. This capability is developed within the DSMC code SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and can model the material removal in presence of active sites leading to the formation of etch pits. The focus of the current work will be to study the effect of etch pits on the material properties of FiberForm, a commonly used base material within many thermal protection system materials (TPS). The microstructure of virgin FiberForm obtained directly from X-ray microtomography experiments is used within SPARTA to obtain the ablated geometries with etch pits. These pitted microstructures are then imported within the Porous Microstructure Analysis (PuMA) software and various material properties such as elasticity, thermal conductivity, and permeability are computed. The variation of these properties as a result of the complex evolution of the surface topology due to etch pit formation is studied and analyzed. Furthermore, the effect of pitting is compared to the case of shrinking fibers, which has been the standard for modelling ablation of carbon structures; and significant differences are observed. Thus, such a physically realistic modeling of material removal through the formation of etch pits will be helpful in predicting the degradation of carbon-based TPS more accurately during oxidation; as well as other mechanisms such as spallation, which involves the removal of chunks of material into the flow due to etch pit growth. This will ultimately improve our understanding of the failure modes in these materials due to ablation.

Carbon Ablators↗