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NASA NTRS1990

Status of the Delco Systems Operations forward looking windshear detection program

Delco Systems Operations, a division of General Motors Hughes Electronics Corporation, is developing a Forward Looking Windshear Detection System based on the integration of infrared remote sensing and accelerometer reactive sensing technologies. The infrared sensor is a multi-spectral, scanning radiometer operating in the 8 to 14 micron region. A 2 x 5 detector array with parallel-serial scanning produces 60 degrees horizontal and 10 degrees vertical-fields of view. Using multiple wavelength signals, azimuth temperature gradients are analyzed for characteristic signatures of thermally induced windshear phenomena. Elevation temperature gradients are processed through an atmosphere model to continuously compute a stability index for arming microburst detection criteria. The atmosphere model and proprietary computer processing algorithms combine to generate coarse estimates of disturbance ranges based on multiple wavelength radiance data with different extinction coefficients. Computer outputs of atmospheric stability, disturbance intensity, and azimuth and range information provide a situation display capability. A ground operated, experimental radiometer has been developed and is being used to verify the detection and discrimination concepts at an atmospheric and simulated rain test facility in Milwaukee. A prototype airborne radiometer is being developed for flight test evaluation during the summer of 1989.

Gallagher, Brian J.↗

DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗

NASA NTRS1995

The effects of ion implantation on the tribology of perfluoropolyether-lubricated 440C stainless steel couples

The lubricating lifetime of thin films of a perfluoropolyether (PFPE) based on hexafluoropropene oxide in the presence of ion implanted 440C stainless steel is presented. Stainless steel discs, either unimplanted or implanted with N2, C, Ti, Ti + N2, or Ti + C had a thin film of PFPE (60-400 A) applied to them reproducibly (+/- 20 percent) and uniformly (+/- 15 percent) using a device developed for this study. The lifetimes of these films were quantified by measuring the number of sliding-wear cycles required to induce an increase in the friction coefficient from an initial value characteristic of the lubricated wear couple to a final, or failure value, characteristic of an unlubricated, unimplanted couple. The tests were performed in a dry nitrogen atmosphere (less than 1 percent RH) at room temperature using a 3 N normal load with a relative sliding speed of 0.05 m/s. The lubricated lifetime of the 440C couple was increased by an order of magnitude by implanting the disc with Ti. Ranked from most to least effective, the implanted species were: Ti; Ti+C; unimplanted; N2; C approximately equals Ti+N2. The mechanism postulated to explain these results involves the formation of a passivating or reactive layer which inhibits or facilitates the production of active sites. The corresponding surface microstructures induced by ion implantation, obtained using x-ray diffraction and conversion electron Mossbauer spectroscopy, ranked from most to least effective in enhancing lubricant lifetime were: amorphous Fe-Cr-Ti; amorphous Fe-Cr-Ti-C + TiC; unimplanted; epsilon-(Fe,Cr)(sub x)N, x = 2 or 3; amorphous Fe-Cr-C approximately equals amorphous Fe-Cr-Ti-N.

Shogrin, Bradley↗

NASA NTRS2004

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

A brief review of the evolutionary progress in computational aerothermodynamics is presented. The current status of computational aerothermodynamics is then discussed, with emphasis on its capabilities and limitations for contributions to the design process of hypersonic vehicles. Some topics to be highlighted include: (1) aerodynamic coefficient predictions with emphasis on high temperature gas effects; (2) surface heating and temperature predictions for thermal protection system (TPS) design in a high temperature, thermochemical nonequilibrium environment; (3) methods for extracting and extending computational fluid dynamic (CFD) solutions for efficient utilization by all members of a multidisciplinary design team; (4) physical models; (5) validation process and error estimation; and (6) gridding and solution generation strategies. Recent experiences in the design of X-33 will be featured. Computational aerothermodynamic contributions to Mars Pathfinder, METEOR, and Stardust (Comet Sample return) will also provide context for this discussion. Some of the barriers that currently limit computational aerothermodynamics to a predominantly reactive mode in the design process will also be discussed, with the goal of providing focus for future research.

Olynick, David R.↗

NASA NTRS1997

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

Gnoffo, Peter A.↗

NASA NTRS2005

Computational Aerothermodynamic Design Issues for Hypersonic Vehicles

A brief review of the evolutionary progress in computational aerothermodynamics is presented. The current status of computational aerothermodynamics is then discussed, with emphasis on its capabilities and limitations for contributions to the design process of hypersonic vehicles. Some topics to be highlighted include: (1) aerodynamic coefficient predictions with emphasis on high temperature gas effects; (2) surface heating and temperature predictions for thermal protection system (TPS) design in a high temperature, thermochemical nonequilibrium environment; (3) methods for extracting and extending computational fluid dynamic (CFD) solutions for efficient utilization by all members of a multidisciplinary design team; (4) physical models; (5) validation process and error estimation; and (6) gridding and solution generation strategies. Recent experiences in the design of X-33 will be featured. Computational aerothermodynamic contributions to Mars Path finder, METEOR, and Stardust (Comet Sample return) will also provide context for this discussion. Some of the barriers that currently limit computational aerothermodynamics to a predominantly reactive mode in the design process will also be discussed, with the goal of providing focus for future research.

Gnoffo, Peter A.↗

DOE OSTI2021

Dramatic Conformer-Dependent Reactivity of the Acetaldehyde Oxide Criegee Intermediate with Dimethylamine Via a 1,2-Insertion Mechanism

The reactivity of carbonyl oxides has previously been shown to exhibit strong conformer and substituent dependencies. Through a combination of synchrotron multiplexed photoionization mass spectrometry experiments (298 K, 4 Torr) and high-level theory (CCSD(T)-F12/cc-pVTZ-F12//B2PLYP-D3/cc-pVTZ with an added CCSDT(Q) correction), we explore the conformer dependence of the reaction of acetaldehyde oxide (CH 3 CHOO) with dimethyl amine (DMA). The experimental data supports the theoretically predicted 1,2-insertion mechanism and the formation of an amine-functionalized hydroperoxide reaction product. Tunable-VUV photoionization probing of anti- or anti- + syn-CH 3 CHOO reveals a strong conformer dependence of the title reaction. Here, the rate coefficient of DMA with anti-CH 3 CHOO is predicted to exceed that for the reaction with syn-CH 3 CHOO by a factor of ~34,000, which is attributed to submerged barrier (syn) vs. barrierless (anti) mechanisms for energetically downhill reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRSDate not supplied

Predicting Lightning Initiation using Deep Learning

Lightning occurrence presents safety challenges to people and property. The main challenge with lightning safety is that the majority of guidance is reactive. In other words, lightning has to have already occurred nearby before a person will respond and take shelter. Further, most injuries or fatalities occur as the storm approaches, or as it's moving away, when rainfall may not be present at the time of the flash. Thus, this project develops a physically-based deep learning model to produce lightning probabilities out to 15 minutes. The deep learning model combines a Convolutional Neural Network (CNN) with a Long Short-Term Memory (LSTM) network to capture both the spatial and temporal evolution of storms to predict the probability that lightning initiation will occur in the next 15 minutes. The model combines radar reflectivity, correlation coefficient and differential reflectivity to inferred storm hydrometer type and precipitation phase, which aids in the identification of electrification processes. The model is trained with data from the Geostationary Lightning Mapper (GLM), which is a near infrared sensor onboard the GOES-R series of satellites that measures optical brightness from lightning. This presentation will provide an overview of the project.

Andrew T White↗

DOE OSTI2026

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗

DOE OSTI2023

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Assessing Seismic Risk for CO2 Geologic Storage: Comparative Analysis of the Delaware Basin and Basin and Range Province Projects

ABSTRACT: Effective management of induced seismicity is critical for safe and sustainable CO2 storage. This study evaluates fault slippage risks in the Delaware Basin (Texas) and Basin and Range Province (Utah), integrating geological, operational, and geomechanical parameters to assess fault stability and seismic hazard mitigation. In the Delaware Basin, two sites were analyzed under an injection rate of 20,000 bbl/day over 25 years. One site showed low fault slip risk, while the other exhibited higher reactivation potential due to proximity to critically stressed faults. Sensitivity analysis revealed that increased pore pressure significantly heightened slip potential, highlighting the necessity of precise pressure control and real-time monitoring. In the Basin and Range Province, fault stability was evaluated at Neck of the Desert, Escalante Desert, Parowan, and Beaver sites under injection rates of 8,750 bbl/day per site over 30 years. Minimal fault slip risk was observed at Neck of the Desert and Escalante Desert sites, whereas Parowan and Beaver sites exhibited elevated slip potential due to semi-critically stressed faults sensitive to modest pore pressure increases. The findings demonstrate that fault slippage analysis, combined with sensitivity analysis of pore pressure and friction coefficients, is essential for understanding seismic risks. Continuous monitoring, adaptive injection management, and rigorous geomechanical analysis are key strategies for minimizing induced seismicity in CO2 sequestration projects.

58 GEOSCIENCES↗

DOE OSTI2021

The chemical and physical origin of incineration ash reactivity in cementitious systems

Incorporating industrial byproducts and waste in concrete is the key to reducing landfill usage as well as lowering the environmental footprint of cement industry. An emerging industrial byproduct which can partly replace cement is the Municipal Solid Waste Incinerator Ash (MSWI ash: residue that is left after incineration of municipal solid waste in a Waste-to-Energy facility). These ashes are predominantly calcium-rich; however, they also contain additional elements whose speciation is not known. These elements can significantly alter the hydration characteristics of a cementitious system. Here, our results suggest these ashes can accelerate as well as retard cement hydration. Specifically, Pb, Br, S, Ca, and Cl appear to accelerate cement hydration, whereas Cu, Fe, Al, Ti, Si, K, Zn, and Sr appear to retard cement hydration. Changes in hydration characteristics can have a strong bearing on the physical characteristics of cementitious systems incorporating incineration ashes. Thus, to selectively screen ashes that synergistically enhance the physical characteristics, we introduce a novel “Incineration Ash Coefficient (IAC),” which shows a strong correlation with the compressive strength (R 2 =0.79) of cement-ash binary mixtures.

42 ENGINEERING↗

NASA NTRS1982

RF sputtered silicon and hafnium nitrides: Properties and adhesion to 440C stainless steel

Silicon nitride and hafnium nitride coatings were deposited by reactive RF sputtering on oxidized and unoxidized 440C stainless steel substrates. Sputtering was done in mixtures of argon and nitrogen gases from pressed powder silicon nitride and from hafnium metal targets. Depositions were at two background pressures, 8 and 20 mtorr, and at two different fractions (f) of nitrogen in argon, 0.25 and 0.60, for hafnium nitride and at f = 0.25 for silicon nitride. The coatings and the interface between the coating and substrates were investigated by X-ray diffractometry, scanning electron microscopy, energy dispersive X-ray analysis and Auger electron spectroscopy. A Knoop microhardness of 1650 + or - 100 kg/sq mm was measured for hafnium nitride and 3900 + or - 500 kg/sq mm for silicon nitride. The friction coefficients between a 440C rider and the coatings were measured under lubricated conditions. Scratch test results demonstrate that the adhesion of hafnium nitride to both oxidized and unoxidized 440C is superior to that of silicon nitride. Oxidized 440C is found to have increased adhesion, to both nitrides, over that of unoxidized 440C.

Grill, A.↗

NASA NTRS1983

RF-sputtered silicon and hafnium nitrides - Properties and adhesion to 440C stainless steel

Silicon nitride and hafnium nitride coatings were deposited by reactive RF sputtering on oxidized and unoxidized 440C stainless steel substrates. Sputtering was done in mixtures of argon and nitrogen gases from pressed powder silicon nitride and from hafnium metal targets. Depositions were at two background pressures, 8 and 20 mtorr, and at two different fractions (f) of nitrogen in argon, 0.25 and 0.60, for hafnium nitride and at f = 0.25 for silicon nitride. The coatings and the interface between the coating and substrates were investigated by X-ray diffractometry, scanning electron microscopy, energy dispersive X-ray analysis and Auger electron spectroscopy. A Knoop microhardness of 1650 + or 100 kg/sq mm was measured for hafnium nitride and 3900 + or 500 kg/sq mm for silicon nitride. The friction coefficients between a 440C rider and the coatings were measured under lubricated conditions. Scratch test results demonstrate that the adhesion of hafnium nitride to both oxidized and unoxidized 440C is superior to that of silicon nitride. Oxidized 440C is found to have increased adhesion, to both nitrides, over that of unoxidized 440C.

Grill, A.↗

DOE OSTI2024

Full‐dimensional coupled‐channel statistical approach to atom‐triatom systems and applications to H/D + O 3 reaction

Abstract The statistical quantum model (SQM), which assumes that the reactivity is controlled by entrance/exit channel quantum capture probabilities, is well suited for chemical reactions with a long‐lived intermediate complex. In this work, a time‐independent coupled‐channel implementation of the SQM approach is developed for atom‐triatom systems in full dimensionality. As SQM treats the capture dynamics quantum mechanically, it is capable of handling quantum effects such as tunneling. A detailed study of the H/D + O 3 capture dynamics was performed by applying the newly developed SQM method on an accurate global potential energy surface. Agreement with previous ring polymer molecular dynamics (RPMD) results on the same potential energy surface is excellent except for very low temperatures. The SQM results are also in reasonably good agreement with available experimental rate coefficients. The strong H/D kinetic isotope effect underscores the dominant role of quantum tunneling under an entrance channel barrier at low temperatures.

Yang, Dongzheng↗

NASA NTRS2009

Nanocomposite Strain Gauges Having Small TCRs

Ceramic strain gauges in which the strain-sensitive electrically conductive strips made from nanocomposites of noble metal and indium tin oxide (ITO) are being developed for use in gas turbine engines and other power-generation systems in which gas temperatures can exceed 1,500 F (about 816 C). In general, strain gauges exhibit spurious thermally induced components of response denoted apparent strain. When temperature varies, a strain-gauge material that has a nonzero temperature coefficient of resistance (TCR) exhibits an undesired change in electrical resistance that can be mistaken for the change in resistance caused by a change in strain. It would be desirable to formulate straingauge materials having TCRs as small as possible so as to minimize apparent strain. Most metals exhibit positive TCRs, while most semiconductors, including ITO, exhibit negative TCRs. The present development is based on the idea of using the negative TCR of ITO to counter the positive TCRs of noble metals and of obtaining the benefit of the ability of both ITO and noble metals to endure high temperatures. The noble metal used in this development thus far has been platinum. Combinatorial libraries of many ceramic strain gauges containing nanocomposites of various proportions of ITO and platinum were fabricated by reactive co-sputtering from ITO and platinum targets onto alumina- and zirconia-based substrates mounted at various positions between the targets.

Gregory, Otto↗

DOE OSTI2025

Preferential adsorption of noble gases in zeolitic tuff with variable saturation: A modeling study of counter-intuitive diffusive-adsorptive behavior

Noble gas transport through geologic media has important applications in the prediction and characterization of measured gas signatures related to underground nuclear explosions (UNEs). Retarding processes such as adsorption can cause significant species fractionation of radionuclide gases, which has implications for measured and predicted signatures used to distinguish radioxenon originating from civilian nuclear facilities or from UNEs. Accounting for the effects of variable water saturation in geologic media on tracer transport is one of the most challenging aspects of modeling gas transport because there is no unifying relationship for the associated tortuosity changes between different rock types, and reactive transport processes such as adsorption that are affected by the presence of water likewise behave differently between gas species. In this study, we perform numerical diffusive-adsorptive transport simulations to estimate gas transport parameters associated with bench-scale laboratory diffusion cell experiments measuring breakthrough in zeolitic and non-zeolitic rocks for a gaseous mixture of xenon, krypton, and SF 6 at varying degrees of water saturation (S w ). Counter-intuitive transport behavior was observed in the zeolitic rock experiments whereby breakthrough concentrations were significantly higher when the core was partially saturated (S w = 17 %) than under dry (S w = 0 %) conditions. Breakthrough of xenon was especially retarded in the dry core – likely due to comparatively high affinity of xenon for zeolitic adsorption sites – and estimated effective diffusion coefficients for all gases were approximately an order of magnitude lower than what is predicted by porosity-tortuosity models. We propose the counter-intuitive behavior observed is because water infiltration of zeolite nanopores reduces both the adsorptive capacity of the rock and the tortuosity of connected flow paths. We developed a two-site competitive kinetic Langmuir adsorption reaction for the porous media transport simulator in order to constrain transport parameters within zeolitic tuff, where differential adsorption to zeolite and non-zeolite pores was observed. We determined that liquid saturation-dependent diffusive-adsorptive transport is affected by subtle and at times competing processes that are specific to different gases, which have a significant overall influence on effective transport parameters.

58 GEOSCIENCES↗

DOE OSTI2021

Modeling the Size Distribution and Chemical Composition of Secondary Organic Aerosols during the Reactive Uptake of Isoprene-Derived Epoxydiols under Low-Humidity Condition

Reactive uptake of isoprene epoxydiols (IEPOX), which are isoprene oxidation products, onto acidic sulfate aerosols is recognized to be an important mechanism for the formation of isoprene-derived secondary organic aerosol (SOA). While a mechanistic understanding of IEPOX-SOA formation exists, several processes affecting their formation remain uncertain. Evaluating mechanistic IEPOX-SOA models with controlled laboratory experiments under longer atmospherically relevant timescales is critical. Here, we implement our latest understanding of IEPOX-SOA formation within a box model to simulate the measured reactive uptake of IEPOX on polydisperse ammonium bisulfate seed aerosols within an environmental Teflon chamber. The model is evaluated with single-particle measurements of size distribution, volume, density, and composition of aerosols due to IEPOX-SOA formation at timescales of hours. Additionally, we find that the model can simulate the growth of particles due to IEPOX multiphase chemistry, as reflected in increases of the mean particle size and volume concentrations, and a shift of number size distribution to larger sizes. The model also predicts the observed evolution of particle number mean diameter and total volume concentrations at the end of the experiment. We show that in addition to self-limiting effects of IEPOX-SOA coatings, accounting for the molar balance between inorganic and organic sulfate and mass accommodation coefficient of IEPOX are important parameters governing modeling of IEPOX-SOA formation. Thus, models which do not account for the molar sulfate balance and/or diffusion limitations within IEPOX-SOA coatings are likely to predict too high IEPOX-SOA formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗