SEARCH · Search NASA

Results for “Empirical characteristic function”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Hybrid interatomic potential for Sn

To design materials for extreme applications, it is important to understand and predict phase transitions and their influence on material properties under high pressures and temperatures. Atomistic modeling can be a useful tool to assess these behaviors. However, this can be difficult due to the lack of fidelity of the interatomic potentials in reproducing this high pressure and temperature extreme behavior. Here, in this work, a hybrid EAM-R—which is the combination of embedded atom method (EAM) and rapid artificial neural network potential—for Tin (Sn) is described which is capable of accurately modeling the complex sequence of phase transitions between different metallic polymorphs as a function of pressure. This hybrid approach ensures that a basic empirical potential like EAM is used as a lower energy bound. By using the final activation function, the neural network contribution to energy must be positive, assuring stability over the whole configuration space. This implementation has the capacity to reproduce density functional theory results at 6 orders of magnitude slower than a pair potential for molecular dynamics simulation, including elastic and plastic characteristics and relative energies of each phase. Using calculations of the Gibbs free energy, it is demonstrated that the potential precisely predicts the experimentally observed phase changes at temperatures and pressures across the whole phase diagram. At 10.2 GPa, the present potential predicts a first-order phase transition between body-centered tetragonal (BCT) β-Sn and another polymorph of BCT-Sn. This structure transforms into body-centered cubic near the experimentally reported value at 33 GPa. Thus, the Sn potential developed in this paper can be used to study complex deformation mechanisms under extreme conditions of high pressure and strain rates unlike existing potentials. Moreover, the framework developed in this paper can be extended for different material systems with complex phase diagrams.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Asymptotic form of the longitudinal correlation function for isotropic homogeneous turbulence

An asymptotic form is derived for the longitudinal correlation function for isotropic homogeneous turbulence in an incompressible fluid governed by the Navier-Stokes equation. The result is obtained from an analysis of the algebraic-differential structure of the two-point correlation tensor contained in the complex-valued Fourier transform of the probability measure over the turbulence ensemble, which reveals that the Hopf characteristic functional (the complex-valued Fourier transform of the probability measure) satisfies the Fourier interference inequality. Consequences of the expression obtained, in which the correlation function is a positive definite function of the inverse cube of the spatial coordinate as it approaches infinity, are shown to include the nonexistence of the Loitsianskii invariant, and the solution is shown to be consistent with empirical formulas.

Rosen, G.↗

NASA NTRS2011

Canopy Spectral Invariants: Application to Classification of Forest Types from Hyperspectral Data - Part 2

Many studies have been conducted to demonstrate the ability of hyperspectral data to discriminate plant dominant species. Most of them have employed the use of empirically based techniques, which are site specific, requires some initial training based on characteristics of known leaf and/or canopy spectra and therefore may not be extendable to operational use or adapted to changing or unknown land cover. In this paper we propose a physically based approach for separation of dominant forest type using hyperspectral data. The radiative transfer theory of canopy spectral invariants underlies the approach, which facilitates parameterization of the canopy reflectance in terms of the leaf spectral scattering and two spectrally invariant and structurally varying variables - recollision and directional escape probabilities. The methodology is based on the idea of retrieving spectrally invariant parameters from hyperspectral data first, and then relating their values to structural characteristics of three-dimensional canopy structure. Theoretical and empirical analyses of ground and airborne data acquired by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two sites in New England, USA, suggest that the canopy spectral invariants convey information about canopy structure at both the macro- and micro-scales. The total escape probability (one minus recollision probability) varies as a power function with the exponent related to the number of nested hierarchical levels present in the pixel. Its base is a geometrical mean of the local total escape probabilities and accounts for the cumulative effect of canopy structure over a wide range of scales. The ratio of the directional to the total escape probability becomes independent of the number of hierarchical levels and is a function of the canopy structure at the macro-scale such as tree spatial distribution, crown shape and size, within-crown foliage density and ground cover. These properties allow for the natural separation of dominant forest classes based on the location of points on the total escape probability vs the ratio log-log plane.

Schull, M. A.↗

NASA NTRS1975

Radar return from a continuous vegetation canopy

The radar backscatter coefficient, sigma deg, of alfalfa was investigated as a function of both radar parameters and the physical characteristics of the alfalfa canopy. Measurements were acquired with an 8-18 GHz FM-CW mobile radar over an angular range of 0 - 70 deg as measured from nadir. The experimental data indicates that the excursions of sigma deg at nadir cover a range of nearly 18 dB during one complete growing cycle. An empirical model for sigma deg was developed which accounts for its variability in terms of soil moisture, plant moisture and plant height.

Bush, T. F.↗

NASA NTRS1991

Macromolecular recognition: Structural aspects of the origin of the genetic system

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of evolution of life. Using computational and modeling techniques and guided by analogies from present day systems we, seek to understand the emergence of genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. In one possible scenario, the RNA enzymatic reaction plays a key role in the emergence of the self-replicating and offers a clue to the onset of enzymatic catalysis prior to the existence of the protein biosynthetic machinery. Our ultimate goal is to propose a simple RNA segment which contains the specificity and catalytic activity of the contemporary RNA enzyme and which could emerge in a primordial chemical environment. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation have been studied. Another important aspect of this reaction is the identity of the functional groups which are essential for the acid base catalysis. The structural characteristics of the target helices, particularly a possible role of G center dot T pair, is under examination by molecular dynamics (MD) simulation technique. Modeling of the ancestral aminoacyl-tRNA synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. Assuming that the catalytic function evolved before the elements of specific recognition of a particular amino acid, we are exploring the minimal structural requirements for the catalysis of tRNA aminoacylation. The molecular modeling system SYBYL was used for this study based on the high resolution crystallographic structures of the present day tyrosyl-adenylate:tyrRS and tRNA(Gln): ATP:glnRS complexes. The trinucleotide CCA of the 3'-end tRNA is placed into the active site pocket of tyrRS, based on the scheme of interaction between tRNA(Gln) and glnRS, and upon the stereochemistry of the tyrRS:tRNA:Tyr-AMP transition state. This provides a model of the non-specific recognition of a tRNA's 3'-end by an aRS, which might be similar to that of the ancestral aRS's. In the next step, modeling of the rest of the acceptor stem of tRNA (Tyr) with tyrRS is carried out.

Rein, Robert↗

NASA NTRS2001

Shock Formation of Slow Magnetosonic Waves in Coronal Plumes

We investigate the height of shock formation in coroner plumes for slow magnetosonic waves. The models take into account plume geometric spreading, heat conduction and radiative damping. The wave parameters as well as the spreading functions of the plumes and the base magnetic field strengths are given by empirical constraints mostly from Solar and Heliospheric Observatory/Ultraviolet Coronagraph Spectrometer (SOHO/UVCS). Our models show that shock formation occurs at low coronal heights, i.e., within 1.3 solar radius, depending on the model parameters. The shock formation is calculated using the well-established wave breaking condition given by the intersection of C+ characteristics in the space-time plane. Our models show that shock heating by slow magnetosonic waves is expected to be relevant at most heights in solar coronal plumes, although slow magnetosonic waves are most likely not a solely operating energy supply mechanism.

Cuntz, Manfred↗

DOE OSTI2023

A data-driven method for modelling dissipation rates in stratified turbulence

We present a deep probabilistic convolutional neural network (PCNN) model for predicting local values of small-scale mixing properties in stratified turbulent flows, namely the dissipation rates of turbulent kinetic energy and density variance, $\varepsilon$ and $\chi$ . Inputs to the PCNN are vertical columns of velocity and density gradients, motivated by data typically available from microstructure profilers in the ocean. The architecture is designed to enable the model to capture several characteristic features of stratified turbulence, in particular the dependence of small-scale isotropy on the buoyancy Reynolds number $Re_b:=\varepsilon /(\nu N^2)$ , where $\nu$ is the kinematic viscosity and $N$ is the background buoyancy frequency, the correlation between suitably locally averaged density gradients and turbulence intensity and the importance of capturing the tails of the probability distribution functions of values of dissipation. Empirically modified versions of commonly used isotropic models for $\varepsilon$ and $\chi$ that depend only on vertical derivatives of density and velocity are proposed based on the asymptotic regimes $Re_b\ll 1$ and $Re_b\gg 1$ , and serve as an instructive benchmark for comparison with the data-driven approach. When trained and tested on a simulation of stratified decaying turbulence which accesses a range of turbulent regimes (associated with differing values of $Re_b$ ), the PCNN outperforms assumptions of isotropy significantly as $Re_b$ decreases, and additionally demonstrates improvements over the fitted empirical models. A differential sensitivity analysis of the PCNN facilitates a comparison with the theoretical models and provides a physical interpretation of the features enabling it to make improved predictions.

42 ENGINEERING↗

NASA NTRS2017

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics↗

NASA NTRS1999

The Prospect for Remote Sensing of Cirrus Clouds with a Submillimeter-Wave Spectrometer

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

Evans, K. Franklin↗

DOE OSTI2018

Modeling the effects of molecular disorder on the properties of Frenkel excitons in organic molecular semiconductors

The Frenkel exciton model offers a convenient framework for simulating electronic excitations in organic conjugated systems that are too large to address with atomistic level electronic structure methods. Parameterization of this model is typically based on analytical expressions that incompletely describe the spatial and temporal correlations that are inherent to many condensed phase molecular systems. In this manuscript, we introduce a general procedure for including these correlations in the Frenkel exciton model, by mapping them directly from all-atom molecular configurations, for instance from classical molecular dynamics. Regardless of system morphology, this mapping automatically captures the spatial and temporal molecular correlations that are otherwise difficult or impossible to represent in terms of low-dimensional correlation functions. We apply this procedure to study the excited state properties of condensed phase materials made up of thiophene oligomers. We demonstrate that Frenkel model parameters can be mapped from a series of single molecule electronic structure calculations, and that for these materials efficient semi-empirical methods are sufficient to accurately reproduce experimental spectral measurements. By analyzing the statistics of model parameters derived from materials with different characteristic morphologies, we highlight failures in some assumptions that are commonly applied when generating model parameters. Finally, by simulating exciton dynamics on a mapped Frenekel exciton model, we demonstrate the ability to quantify the effect of material morphology on the dynamic properties of excitons.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1992

Performance characteristics of STIS detectors

We report quantum efficiency measurements of back-illuminated, ion-implanted, laser-annealed charge coupled devices (CCD's) in the wavelength range 13-10,000 A. The equivalent quantum efficiency (EQE = effective photons detected per incident photon) ranges from a minimum of 5 percent as 1216 A to a maximum of 87 percent at 135 A. Using a simple relationship for the charge collection efficiency of the CCD pixels as a function of depth, we present a semi-empirical model with few parameters which reproduces our measurements with a fair degree of accuracy. The advantage of this model is that is can be used to predict CCD QE performance for shallow backside implanted devices without detailed solution of a system of differential equations, as in conventional approaches, and yields a simple analytic form for the charge collection efficiency which is adequate for detector calibration purposes. Making detailed assumptions about the dopant profile, we also solve the carrier density and continuity equations in order to relate our semi-empirical model parameters to surface and bulk device properties. The latter procedure helps to better establish device processing parameters for a given level of CCD QE performance.

Stern, Robert A.↗

NASA NTRS1993

Energy transfer and constrained simulations in isotropic turbulence

The defining characteristic of turbulent flows is their ability to dissipate energy, even in the limit of zero viscosity. The Euler equations, if constrained in such a way that the velocity derivatives remain bounded, conserve energy. But when they arise as the limit of the Navier-Stokes (NS) equations, when the Reynolds number goes to infinity, there is persuasive empirical evidence that the gradients become singular as just the right function of Re for the dissipation to remain non-zero and to approach a well defined limit. It is generally believed that this limiting value of the dissipation is a property of the Euler equations themselves, independent of the particular dissipative mechanism involved, and that it can be normalized with the large scale properties of the turbulent flow (e.g. the kinetic energy per unit volume u'(exp 2)/2, and the integral scale L) without reference to the Reynolds number or to other dissipative quantities. This is usually taken to imply that the low wave number end of the energy spectrum, far from the dissipative range, is also independent of the particular mechanism chosen to dispose of the energy transfer. In the following sections, we present some numerical experiments on the effect of substituting different dissipation models into the truncated Euler equations. We will see that the effect is mainly felt in the 'near dissipation' range of the energy spectrum, but that this range can be quite wide in some cases, contaminating a substantial range of wave numbers. In the process, we will develop a 'practical' approximation to the subgrid energy transfer in isotropic turbulence, and we will gain insight into the structure of the nonlinear interactions among turbulent scales of comparable size, and into the nature of energy backscatter. Some considerations on future research directions are offered at the end.

Jimenez, Javier↗

NASA NTRS2000

Study of High Lift Configurations

This project focus on the implementation of the Warren-Hassan transition / turbulence model (Journal of Aircraft, Vol. 35, No. 5) into the NASA code CFL3D and its testing for multi-element airfoils in landing configuration at different angles of attack. The Warren-Hassan transition model solves an evolution equation for a kinetic energy characteristic of non-turbulent fluctuations. This is combined with an empirical estimate of the frequency of the most amplified first-mode disturbance to yield an expression for an eddy viscosity characteristic of non-turbulent fluctuations. This is combined with the k - zeta model for fully turbulent flow to yield a unified approach capable of predicting both transition onset and extent. Blending of the non-turbulent and turbulent components of the model is accomplished by an intermittency function based on the work of Dhawan and Narasimha (Journal of Fluid Mechanics, Vol. 3, No. 4).

Edward, Jack R.↗

DOE OSTI2019

Spectrum and structure of octet and decuplet baryons and their positive-parity excitations

A continuum approach to the three-valence-quark bound-state problem in quantum field theory, employing parametrizations of the necessary kernel elements, is used to compute the spectrum and Poincare-covariant wave functions for all flavor- SU (3) octet and decuplet baryons and their first positive-parity excitations. Such analyses predict the existence of nonpointlike, dynamical quark-quark (diquark) correlations within all baryons; and a uniformly sound description of the systems studied is obtained by retaining flavor-antitriplet-scalar and flavor-sextet-pseudovector diquarks. Thus constituted, the rest-frame wave function of every system studied is primarily S wave in character; and the fast positive-parity excitation of each octet or decuplet baryon exhibits the characteristics of a radial excitation. Importantly, every ground-state octet and decuplet baryon possesses a radial excitation. Hence, the analysis predicts the existence and masses of positive-parity excitations of the Ξ, Ξ*, and Ω baryons, states which have not yet been empirically identified. This body of analysis suggests that the expression of emergent mass generation is the same in all u , d , and s baryons and, notably, that dynamical quark-quark correlations play an essential role in the structure of each one. Furthermore, it also provides the basis for developing an array of predictions that can be tested in new generation experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1991

Software reliability through fault-avoidance and fault-tolerance

Twenty independently developed but functionally equivalent software versions were used to investigate and compare empirically some properties of N-version programming, Recovery Block, and Consensus Recovery Block, using the majority and consensus voting algorithms. This was also compared with another hybrid fault-tolerant scheme called Acceptance Voting, using dynamic versions of consensus and majority voting. Consensus voting provides adaptation of the voting strategy to varying component reliability, failure correlation, and output space characteristics. Since failure correlation among versions effectively reduces the cardinality of the space in which the voter make decisions, consensus voting is usually preferable to simple majority voting in any fault-tolerant system. When versions have considerably different reliabilities, the version with the best reliability will perform better than any of the fault-tolerant techniques.

Vouk, Mladen A.↗

NASA NTRS1965

Ground testing at MSFC

The large-scale field collection of acoustic data and their analysis are described in this review. The entire sound-field program has the purpose of solving complex problems of excessive noise propagation associated with the static test firing of large space-booster powerplants. The site of data collection has been Mississippi Test Facility (MTF), where far-field sound-propagation and correlated meteorological measurements were initiated in 1962. The statistical evaluation of sound-measurement data shows that the polar distribution of sound in the springtime (at MTF) is determined mainly by the temperature field of the atmosphere. Greater deformation of sound-intensity polar distribution occurs in the autumn as a result of the influence of the wind field. The data on sound attenuation as a function of distance from its source revealed attenuation in excess of the expected magnitude. The excess was mainly between 1 and 10 kilometers from the source, with maximum attenuation (17 to 18 decibels) near 6 kilometers. Excess sound attenuation was compared with calculated sound dispersion. For all sound frequencies in all seasons the deviation between reference and empirical attenuation values formed a bell-shaped distribution on a semilogarithmic plot. The physical causes for the sound- attenuation behavior are considered to be atmospheric diffraction and scattering effects. Statistical analysis of sod-intensity extremes indicated amplification of the sound signals by focusing which could be expected along selected azimuths. Empirical amplification values showed the maximum occurring in winter (50 decibels at 22 kilometers). For the analysis of correlation between empirical sound data and local atmospheric sound- propagation conditions, #e concept of analytical classification of sound-velocity profiles has been developed. Examination of over a quarter-million individual sound-velocity profiles indicates that 33 profile types for heights up to 3 kilometers constitute the empirical possibilities of sound-propagation conditions in southeastern United States. Since the focusing qualities of each sound- velocity profile can be determined as a class characteristic, the overall probabilities of focusing occurrence can he obtained. The severity of focusing, as based upon lateral spread of focusing areas, has been determined. The data for MTF indicate focusing is most severe in winter, with the direction toward east being most affected. Sound propagation is a fluctuating phenomenon because atmospheric conditions vary continuously. A measuring system for analyzing the nonstationary sound-propagation phenomena has been established. The analysis of the acoustic fluctuation data is sup- posed to provide "dynamic” perturbation functions of sound, which are to be superimposed on the related characteristic sound-velocity-profile type. The ultimate result of the program will be the establishment of reliable contingency tables showing the relationship between atmospheric parameters and far-field sound intensities. These data will be the basis for more accurate sound-propagation forecasting for static firing tests.

STATIC TESTING↗

DOE OSTI2015

A prototype, glassless densitometer traceable to primary optical standards for quantitative radiochromic film dosimetry

Purpose: To evaluate a prototype densitometer traceable to primary optical standards and compare its performance to an EPSON Expression{sup ®} 10000XL flatbed scanner (the Epson) for quantitative radiochromic film (RCF) dosimetry. Methods: A prototype traceable laser densitometry system (LDS) was developed to mitigate common film scanning artifacts, such as positional scan dependence and high noise in low-dose regions, by performing point-based measurements of RCF suspended in free-space using coherent light. The LDS and the Epson optical absorbance scales were calibrated up to 3 AU, using reference materials calibrated at a primary standards laboratory and a scanner calibration factor (SCF). Calibrated optical density (OD) was determined for 96 Gafchromic{sup ®} EBT3 film segments before and after irradiation to one of 16 dose levels between 0 and 10 Gy, exposed to {sup 60}Co in a polymethyl-methacrylate (PMMA) phantom. The sensitivity was determined at each dose level and at two rotationally orthogonal readout orientations to obtain the sensitometric response of each RCF dosimetry system. LDS rotational scanning dependence was measured at nine angles between 0°and 180°, due to the expected interference between coherent light and polarizing EBT3 material. The response curves were fit to the analytic functions predicted by two physical response models: the two-parameter single-hit model and the four-parameter percolation model. Results: The LDS and the Epson absorbance measurements were linear to primary optical standards to within 0.2% and 0.3% up to 2 and 1 AU, respectively. At higher densities, the LDS had an over-response (2.5% at 3 AU) and the Epson an under-response (3.1% and 9.8% at 2 and 3 AU, respectively). The LDS and the Epson SCF over the applicable range were 0.968% ± 0.2% and 1.561% ± 0.3%, respectively. The positional scan dependence was evaluated on each digitizer and shown to be mitigated on the LDS, as compared to the Epson. Maximum EBT3 rotational dependence was found to have a strong dependence on dose (0.1% and 34% at 30 mGy and 5 Gy, respectively). The preferred EBT3 polymerization axis angle was constant within experimental uncertainties. In its most sensitive orientation, the LDS-measured EBT3 sensitivity was 7.13 × 10{sup −4} ± 9.2 × 10{sup −6} AU/mGy, which represented a 4.5 fold increase over the Epson of 1.58 × 10{sup −4} ± 9.8 × 10{sup −6} AU/mGy. To first order approximations, EBT3 response was linear up to 500 mGy to within 0.80% and to within 7.5% for the most sensitive LDS and the Epson orientations, respectively. The corresponding single-hit and percolation model relative residual norms were 0.082 and 0.074 for LDS as compared to 0.29 and 0.18 for the Epson, which represented a significant increase in LDS-measured agreement with the simple physical model. Less sensitive LDS and the Epson orientations showed a marked decrease in the physical model agreement, which suggested that suboptimal readout device characteristics may be the origin of the complex sensitometric functional forms currently required for accurate RCF dosimetry. Conclusions: The prototype densitometer was shown to be superior to a conventional scanner for quantitative RCF dosimetry based on physical models of film response. The Epson was shown to be a reliable tool for routine RCF dosimetry in a clinical setting, yet calibration to primary optical standards did not mitigate the necessity for complex, empirical functional form fitting.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗