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DOE OSTI2022

Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys

We report Bayesian Optimization (BO) has emerged as a powerful framework to efficiently explore and exploit materials design spaces. To date, most BO approaches to materials design have focused on the materials discovery problem as if it were a single expensive-to-query ‘black box’ in which the target is to optimize a single objective (i.e., material property or performance metric). Also, such approaches tend to be constraint agnostic. Here, we present a novel multi-information BO framework capable of actively learning materials design as a multiple objectives and constraints problem. We demonstrate this framework by optimally exploring a Refractory Multi-Principal-Element Alloy (MPEA) space, here specifically, the system Mo-Nb-Ti-V-W. The MPEAs are explored to optimize two density-functional theory (DFT) derived ductility indicators (Pugh’s Ratio and Cauchy pressure) while learning design constraints relevant to the manufacturing of high-temperature gas-turbine components. Alloys in the BO Pareto-front are analyzed using DFT to gain an insight into fundamental atomic and electronic underpinning for their superior performance, as evaluated within this framework.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Phase-field modeling of thermally-grown oxide and damage evolution in environmental barrier coatings

Silicon carbide-based ceramic matrix composites protected by environmental barrier coatings (EBCs) present a promising materials solution for next-generation gas turbines. Developing more robust and efficient EBCs is therefore of significant technological importance. During the service in high-temperature oxidative environments, there is a thermally grown oxide (TGO) layer, spontaneously formed in the EBC system. TGO is recognized as a critical factor for the degradation and failure of EBCs, yet the detailed mechanisms of TGO growth and its effect on EBC failure remain unclear. In this study we develop a comprehensive chemo-mechano-phase-field model to simulate growth of the TGO in EBCs, factoring in creep and deformation, and especially the cracking behaviors. The volume expansion due to TGO growth and the resulting large inelastic deformation are addressed by using our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm, in combination with an adapted Hu-Chen spectral solver for elasticity. Simulations of TGO growth are performed considering different growth modes of TGOs determined mainly by the ratio of oxidant permeability in the topcoat to that in the TGO itself. Large-scale three-dimensional (3D) simulations are performed to model the formation of interconnecting vertical/channel cracks (often called ‘mud cracks’). The simulated crack morphology are in excellent agreement with the experimental observations from the literature. The simulations also provide insights into the cracking of EBCs and its dependence on the structure and constituent properties of the coating system. Furthermore, these results demonstrate the developed damage model can be a useful tool for design of more durable EBCs.

Cracking↗

DOE OSTI2023

System efficiency and power assessment of the all-aqueous copper thermally regenerative ammonia battery

Thermally regenerative ammonia batteries (TRABs) use low-temperature (T < 100 °C) heat to provide stationary energy and power with higher power densities and efficiency relative to other waste heat devices. TRABs are an active area of research in waste heat devices, but currently there is little consensus on what aspect of the system is limiting TRAB performance and what maximum efficiencies are possible. Experiments and numerical models were used here to examine the sensitivity of the battery and distillation column in a TRAB system to key operating variables, thereby establishing practical limits and identifying focus areas for improving performance. Battery power was eight times more sensitive to ohmic losses than kinetic and mass transfer losses, regardless of the operating temperature, and the peak power density was simulated to be 18.8 mW cm –2 at 75 °C. Theoretical energy efficiency limits were defined for a series of ammonia concentrations and operating pressures, ranging from 5 – 12%, which is 2–3 times higher than previous experimental estimations. Atmospheric pressure column operation used a larger amount of waste heat compared to sub-atmospheric pressure. It is estimated that the volume of the battery would take up 9.2m 3 for every 1% of the power output of a natural gas turbine, but with realistic improvements to cell conductivity, the size would reduce to 2.5 m 3 . Finally, the results presented in this work will help streamline future development by focusing on minimizing ohmic losses and provide specific data for full system evaluation of future TRABs.

25 ENERGY STORAGE↗

DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗

DOE OSTI2021

Direct Numerical Simulation of hydrogen combustion at auto-ignitive conditions: Ignition, stability and turbulent reaction-front velocity

Direct Numerical Simulations (DNS) are performed to investigate the process of spontaneous ignition of hydrogen flames at laminar, turbulent, adiabatic and non-adiabatic conditions. Mixtures of hydrogen and vitiated air at temperatures representing gas-turbine reheat combustion are considered. Adiabatic spontaneous ignition processes are investigated first, providing a quantitative characterization of stable and unstable flames. Results indicate that, in hydrogen reheat combustion, compressibility effects play a key role in flame stability and that unstable ignition and combustion are consistently encountered for reactant temperatures close to the mixture’s characteristic crossover temperature. Furthermore, it is also found that the characterization of the adiabatic processes is also valid in the presence of non-adiabaticity due to wall heat-loss. Finally, a quantitative characterization of the instantaneous fuel consumption rate within the reaction front is obtained and of its ability, at auto-ignitive conditions, to advance against the approaching turbulent flow of the reactants, for a range of different turbulence intensities, temperatures and pressure levels.

42 ENGINEERING↗

DOE OSTI2025

Plasma assisted NH 3 /H 2 /air ignition in nanosecond discharges with non-equilibrium energy transfer

Ammonia (NH 3 ), with its high energy density and easiness to store and transport as a hydrogen carrier, has become a promising alternative green fuel. However, its adoption in power generation is hindered by challenges such as low burning velocity, slow low-temperature oxidation, high NO x emissions, and ignition difficulty. Here, this work computationally investigates the effects of non-equilibrium energy transfer by nanosecond discharges on NH 3 ignition and flame propagation in an NH 3 /H 2 /air flow at 700 K and 1 atm. The simulation results demonstrate that NH 3 /air mixtures require a large ignition energy due to their large critical ignition radius. It is shown that adding 30 % hydrogen significantly reduces the critical ignition radius and minimum ignition energy. Two-dimensional modeling further shows a non-monotonic dependence of ignition kernel volume on the applied voltage and reduced electric field. The optimum ignition enhancement occurs at 200 Td where the generation of electronically excited species and radicals including N 2 (B), O( 1 D) and OH becomes most efficient. Higher voltages divert electron energy toward ionization, which makes it less effective for NH 3 ignition. The study also identifies an optimal electrode gap size for a given pulse energy. Smaller gap sizes increase deposited energy density, raising temperature and radical concentrations. However, excessive reduction of the gap distance reduces flame propagation speed due to the flame stretch effect in rich mixtures with the effective Lewis number greater than unity. A nonlinear relationship between pulse repetition frequency and ignition kernel volume is observed in a nanosecond pulsed high frequency discharge (NPHFD). An optimal frequency range of 200 kHz to 2 MHz is found when two pulses are used. In addition, an optimal number of pulses exists for each pulse repetition frequency, with higher frequencies requiring more pulses to maximize the overlap region. These findings provide critical insights on developing controlled plasma discharge techniques for efficient NH 3 ignition in reactive flows within internal combustion engines and gas turbines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Low-cost thermal/environmental barrier coatings: A first-principles study

Development of low-cost advanced thermal/environmental barrier coating (T/EBC) materials with acceptable thermal and mechanical properties is essential for safeguarding ceramic composites substrate against thermal and chemical degradation, thereby enhancing the efficiency of components in the high-temperature section of gas turbine engines. To this end, here we employed density functional theory-based approaches to predict the thermodynamic, mechanical, and thermal properties of rare earth disilicates based on abundant rare earth elements, namely La 2 Si 2 O 7 and Ce 2 Si 2 O 7 , as potential alternatives to the current-state-of-the-art ytterbium disilicate EBCs that uses expensive and scarce element Yb. The present study predicts that G-phase Ce 2 Si 2 O 7 has an ultralow thermal conductivity (0.26 W/m/K at 1500 K) and the apparent bulk coefficient of thermal expansion (ABCTE) (≈6.9x10 -6 K -1 ) slightly higher than SiC, demonstrating great potential as low-cost high-performance T/EBC. However, La 2 Si 2 O 7 and Ce 2 Si 2 O 7 undergo an A- to G-phase polymorphic transition at around 1470 K, resulting in significant changes to crystal structure and lattice parameters, and accordingly CTE and lattice thermal conductivity.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Sequence2Self: Self-supervised image sequence denoising of pixel-level spray breakup morphology

Optical imaging of fast and transient phenomena such as the turbulent breakup of liquid sprays exhibit low signal-to-noise ratios due to the limited illumination intensity relative to the short exposure time. Image denoising is required to facilitate physical studies over these data but is challenging due to the absence of clean ground-truths and the stringency of the denoising task (e.g., strong and complex noise, limited resolution, preserving physical fidelity), preventing supervised and existing un-/self-supervised deep learning methods. To this end, Sequence2Self (Seq2S) is proposed, an extension of Self2Self (S2S) to image sequences that leverages both the signal’s spatial and temporal correlation. Seq2S is demonstrated on time-resolved x-ray phase contrast imaging of liquid jet fuel sprays in a gas turbine combustor, which possesses all of challenges detailed above. Experiments are conducted across four fuels with different breakup morphology using various state-of-the-art methods. Overall, many of the methods failed and Seq2S was most successful: (1) Accurate spray structures were reconstructed with consistent evolution across frames void of artifacts. (2) The performance was robust, invariant to the hyperparameter choice. (3) Computational time is short and can be made eligible for real-time denoising. In particular, the images denoised by Seq2S showed spray droplet diameter distributions with near-zero Kullback–Leibler divergence (0.01 ± 0.01) to a cleaner reference, whereas the second best method yielded 0.06 ± 0.03. In conclusion, this suggests that Seq2S can be reliably used prior to subsequent quantitative spray analyses as it retains (if not, improves) the statistical physical properties of the data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

On the importance of species immiscibility in mixing-layer dynamics at supercritical pressures

The mixing dynamics of injected propellants is a key factor in determining the ignition performance and combustion-instability response of rocket engines, internal combustion engines, and gas turbines. A key source of uncertainty in the prediction of phase-exchange dynamics is the immiscibility of the injected propellants at supercritical pressure conditions, which induces liquid/vapor phase separation and surface-tension dynamics. While experimental observations indicate the presence of liquid/vapor interfacial structures, this interfacial dynamics is typically neglected in numerical analyses. To address this issue, the objective of the present study is to systematically evaluate the importance of species immiscibility on the phase-exchange dynamics of cryogenic LOX/GH2 mixing layers at typical rocket engine injection conditions. This is accomplished by comparing simulations of (i) a recently developed interface-capturing Regularized-Interface Method (RIM) formulation, and (ii) the commonly employed Diffuse-Interface Method (DIM) formulation. Analysis shows that the interfacial dynamics significantly impact the atomization and mixing of the propellants in the near-injector region, which is not captured by the DIM formulation. The findings of this study extend to other immiscible injection systems, such as LOX/kerosene and hydrocarbon-fuel/air, thereby highlighting the importance of resolving species immiscibility in simulating high-pressure combustion engines.

diffused-interface method↗

DOE OSTI2022

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Dry air cyclic oxidation of mixed Y/Yb disilicate environmental barrier coatings and bare silica formers

Here mixed Y and Yb disilicate coatings (Y/Yb)DS have been proposed as dual function thermal and environmental barrier coatings (EBCs) for protecting SiC-based ceramic matrix composites in gas-turbine environments. As an initial step, the 1350 °C dry air cyclic oxidation of atmospheric plasma sprayed (Y 1.2 /Yb 0.8 )DS and ytterbium disilicate/ytterbium monosilicate (YbDS/YbMS) EBCs deposited onto Si bond coatings was compared. As a baseline for evaluating EBC oxidant permeability, the dry air cyclic oxidation scale growth rates for bare silica formers (SiC, Si) were also measured and were consistently higher than rates previously measured after isothermal oxidation. Regarding Si bond coat oxidation rates underlying (Y/Yb)DS and YbDS/YbMS EBCs, the thinner silica scale formed under the thinner and denser (Y/Yb)DS coatings suggested a lower oxidant permeability than YbDS/YbMS. After 500 1-h cycles, the (Y/Yb)DS coating was comprised of only the β-polymorph disilicate and minor amounts of the X-2 phase monosilicate phase. Negligible differences in oxidation kinetics for (Y/Yb)DS coatings over the 90 – 240 µm thickness range were observed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Modeling deformation and failure in AlSi-polyester abradable sealcoating material using microstructure-based finite element simulation

A plasma-sprayed aluminum-silicon (AlSi)/polyester coating is applied in modern gas turbine engines as an abradable sealcoating to maintain tight clearances between the rotating blades and the static casing. While running the engine, the rotating blades “rub” with the abradable coating, which results in extreme strain rate (up to 10 6 ) dynamics and a high-temperature environment. Due to the difficulty of collecting direct measurements, predictive computational models are important for analyzing the deformation and failure of the abradable material, to help meet the design target of avoiding damage to the blade tip and maintaining high fuel efficiency. In this research, a microstructure-based finite element (FE) computational model was developed to capture the complex mechanical behavior of the AlSi/polyester microstructure. The model is based on a virtual representative-volume-element (RVE) of a metal-polymer microstructure, reconstructed from x-ray computed tomography. It models the plastic deformation of, and damage to, each AlSi and polyester constituents, as well as the failure at their interface. The model was calibrated and validated with uniaxial tension and compression experiments, conducted at two temperatures (298 K and 533 K) at an applied strain rate of 10 3 - 10 4 s -1 . The material exhibited strongly asymmetric tension-compression behavior and a sensitivity to temperature, which was well captured by the model. The model was further applied to investigate changes in mechanical behavior due to variations in constituents’ volume fractions, which provides guidance to the microstructural design of AlSi/polyester abradable materials. The model is expected to facilitate the development of improved abradable materials by bypassing the conventional trial-and-error approach and extensive testing requirements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Design of an alumina forming coating for Nb-base refractory alloys

Refractory multi-principal element alloys (RMPEAs) promise to significantly enhance gas turbine engine efficiency, but their poor oxidation performance inhibits their implementation. Alumina-forming bond coat alloys can provide oxidation protection, but discovering suitable chemistries remains a challenge. We employed a design methodology that screens for alumina-formation capability using Al activity and phase constitution predictions from CalPhaD (Thermo-Calc). Alloy down-selection from approximately 7,800 alloys in the Nb-Si-Ti-Al-Hf system was conducted via analysis of calculated thermodynamic properties with number-density topology style maps. This approach is validated by creating and testing the composition Nb 12 Si 23 Ti 24 Al 36 Hf 5 , which forms protective alumina scales up to 1400 °C and resists pesting at 800 °C. Further, the alloy has an average coefficient of thermal expansion of ~10.1 ppm/K, making it well matched to Nb-based refractory alloys. The methodology will be useful for the design of coatings for RMPEAs, enabling their implementation and significant efficiency benefits sooner.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Transcritical diffuse-interface hydrodynamics of propellants in high-pressure combustors of chemical propulsion systems

Rocket engines and high-power new generations of gas-turbine jet engines and diesel engines oftentimes involve the injection of one or more reactants at subcritical temperatures into combustor environments at high pressures, and more particularly at pressures higher than those corresponding to the critical points of the individual components of the mixture, which typically range from 13 to 50 bars for most propellants. This class of trajectories in the thermodynamic space has been traditionally referred to as transcritical. However, the fundamental understanding of fuel atomization, vaporization, mixing, and combustion processes at such high pressures remains elusive. In particular, whereas fuel sprays are relatively well characterized at normal pressures, analyses of dispersion of fuel in high-pressure combustors are hindered by the limited experimental diagnostics and theoretical formulations available. The description of the thermodynamics of hydrocarbon-fueled mixtures employed in chemical propulsion systems is complex and involves mixing-induced phenomena, including an elevation of the critical point whereby the coexistence region of the mixture extends up to pressures much larger than the critical pressures of the individual components. As a result, interfaces subject to surface-tension forces may persist in multicomponent systems despite the high pressures, and may give rise to unexpected spray-like atomization dynamics that are otherwise absent in monocomponent systems above their critical point. In this article, the current understanding of this phenomenon is reviewed within the context of propulsion systems fueled by heavy hydrocarbons. Emphasis is made on analytical descriptions at mesoscopic scales of interest for computational fluid dynamics. In particular, a set of modifications of the constitutive laws in the Navier–Stokes equations for multicomponent flows, supplemented with a high-pressure equation of state and appropriate redefinitions of the thermodynamic potentials, are introduced in this work based on an extended version of the diffuse-interface theory of van der Waals. The resulting formulation involves revisited forms of the stress tensor and transport fluxes of heat and species, and enables a description of the mesoscopic volumetric effects induced by transcritical interfaces consistently with the thermodynamic phase diagram of the mixture at high pressures. Additionally, applications of the theory are illustrated in canonical problems, including dodecane/nitrogen transcritical interfaces in non-isothermal systems. The results indicate that a transcritical interface is formed between the propellant streams that persists downstream of the injection orifice over distances of the same order as the characteristic thermal-entrance length of the fuel stream. The transcritical interface vanishes at an edge that gives rise to a fully supercritical mixing layer.

02 PETROLEUM↗

DOE OSTI2022

Experimental and modeling study of water time histories during H 2 S-N 2 O combustion in a shock tube

Here, with the interest in directly burning sour gas in gas turbines, and the fact that even small amounts of H 2 S or its combustion products can alter combustion characteristics, many research studies have been performed to better understand the combustion chemistry of H 2 S. In the present study, the water formation was followed by laser absorption with N 2 O as an oxidant, instead of O 2 . Nitrous Oxide being essentially consumed via N 2 O (+M) ⇌ N 2 + O (+M), the water formation via the H 2 S + O route can then be probed to further validate the models. Three H 2 S/N 2 O mixtures diluted in 98% Ar were studied to cover the following range of equivalence ratios: 0.5, 1.0, and 2.0, over a wide range of temperatures (1580–1940 K) around atmospheric pressure. A chemical kinetic model was then developed first by validating the base N 2 O kinetics mechanism, then by investigating the experimental results presented herein. The N 2 O kinetics mechanism was updated with recent work on the low- and high-pressure limits for N 2 O decomposition (N 2 O (+M) ⇌ N 2 + O (+M)) as well as a review of rate coefficients for N 2 O + H ⇌ N 2 + OH from the literature. Good agreement is shown for H 2 /N 2 O mixtures. Updates were then made to the H 2 S kinetics mechanism, specifically, an update from the literature on SO 2 + H (+M) ⇌ SO + OH (+M) and an adjustment to SO + SH ⇌ S 2 + OH. Additionally, reactions between SH and N 2 O were determined using W1BD data and transition state theory which required the addition of an NNS sub-mechanism. With these updates, the mechanism provides good agreement with the H 2 S/N 2 O experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Understanding the role of flow dynamics in thermoacoustic combustion instability

Thermoacoustic combustion instability is one of the most challenging operational issues in several high-performance, low-emissions combustion technologies, including gas turbines, aircraft engines, rockets, and industrial boilers. Driven by the coupling between combustor acoustics and flame heat release rate fluctuations, thermoacoustic combustion instability can lead to reduced operability, increased emissions, and, in the most extreme cases, catastrophic failure of combustor components. The feedback loop between acoustics and combustion is often facilitated by fluid mechanic oscillations, referred to as “velocity coupling,” whereby acoustic oscillations drive flow fluctuations, which in turn create fluctuations in the flame. The character of these fluid mechanic oscillations is highly dependent on the structure of the flow field and the receptivity of the flow to external excitation. Combustor flow fields use features like fluid recirculation and shear to enhance flame holding and reduce emissions, but these are also the same features that can make the flow receptive to acoustic excitation or even drive self-excited oscillations. Here, in this paper, we discuss the basics of thermoacoustic instability with a focus on the role of hydrodynamic oscillations in typical combustor flows. To facilitate this discussion, we explore the hydrodynamic instability characteristics of several key combustor unit flows (wakes, swirling jets, etc.) and show how the hydrodynamic stability of a flow is an important consideration in determining a combustor’s propensity for thermoacoustic oscillations. Several examples of coupling between hydrodynamics and thermoacoustics are discussed to illustrate this important link. The paper concludes by discussing the potential for designing flow fields that are thermoacoustic instability resistant, either through a reduction in the receptivity of the flow or through nonlinear coupling mechanisms by which self-excited flow instabilities can suppress velocity-coupled combustion oscillations.

42 ENGINEERING↗

DOE OSTI2025

Melting temperature, emissivity, and thermal conductivity of rare-earth silicates for thermal and environmental barrier coatings

In recent years, rare-earth silicates have become the industry standard for coating state-of-the-art SiC ceramic matrix composite (CMC) gas turbine engine components, due to their low volatility, high melting point, and thermal shock resistance. Current research is focused on designing rare-earth silicate based thermal-environmental barrier coatings (T/EBCs) with improved resistance to CMAS (CaO-MgO-Al 2 O 3 -SiO 2 ), steam, and crack formation, while maintaining high temperature performance and stability. Here, in this work we compare the high temperature performance of a variety of single and multi-component rare-earth mono- and disilicates (MS, DS) and rare earth apatites by measuring their melting points and spectrally averaged visible emissivities using laser heating and radiation pyrometry. We also report room temperature thermal conductivity measured by time-domain thermoreflectance (TDTR).

Environmental barrier coatings↗

DOE OSTI2023

Phase diagram to demarcate supercritical, transcritical, and continuous phase regimes for binary fluid equilibrium mixing relevant to combustion applications

Here, a robust methodology to develop phase diagrams of binary fluid mixtures at fixed thermo dynamic conditions (pressure, temperature, and mole fraction) as well as of two initially separated fluids undergoing mixing near critical conditions are presented for fluids and con ditions relevant to rockets, gas turbines, and diesel engine applications. Phase equilibria of mixtures is first examined to provide insight into the continuous-phase mixing behavior (including but not limited to supercritical behavior), and to develop a broadly applicable phase-diagram for binary fluid mixtures at fixed conditions. Next, adiabatic mixing theory and reduced Helmholtz equations of state are used to predict the thermodynamic conditions required to attain continuous-phase binary fluid mixing near critical conditions. Then, a 3D surface diagram (P,T fuel ,T amb ) separating single and two-phase regions is constructed by varying the ambient pressure and the initial temperatures of the two fluids. Polynomial fits of the 3D surfaces for 10 different binary mixtures are tabulated for nitrogen-alkane and methane-oxygen blends relevant to air-breathing and propellant based engines, respectively.

42 ENGINEERING↗