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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Multi-Component, Multi-Point Interferometric Rayleigh/Mie Doppler Velocimeter

An interferometric Rayleigh scattering system was developed to enable the measurement of multiple, orthogonal velocity components at several points within very-high-speed or high-temperature flows. The velocity of a gaseous flow can be optically measured by sending laser light into the gas flow, and then measuring the scattered light signal that is returned from matter within the flow. Scattering can arise from either gas molecules within the flow itself, known as Rayleigh scattering, or from particles within the flow, known as Mie scattering. Measuring Mie scattering is the basis of all commercial laser Doppler and particle imaging velocimetry systems, but particle seeding is problematic when measuring high-speed and high-temperature flows. The velocimeter is designed to measure the Doppler shift from only Rayleigh scattering, and does not require, but can also measure, particles within the flow. The system combines a direct-view, large-optic interferometric setup that calculates the Doppler shift from fringe patterns collected with a digital camera, and a subsystem to capture and re-circulate scattered light to maximize signal density. By measuring two orthogonal components of the velocity at multiple positions in the flow volume, the accuracy and usefulness of the flow measurement increase significantly over single or nonorthogonal component approaches.

Danehy, Paul M.↗
DOE OSTI2020

Model Development for Multi-Component Fuel Vaporization and Flash Boiling

The objectives of this project are to improve the multi-component fuel droplet and film vaporization models used in internal combustion engine simulation, and to develop a comprehensive model to predict the characteristics of multi-component flash boiling spray. This work explores two approaches to fuel composition treatment for modeling multi-component fuel vaporization: one based on discretization and surrogates, and the other based on continuous thermodynamic distribution of fuel properties. The experimental data collected for model validation are done under three fuel form factors: droplet, spray, and thin film. The study on sprays also include experimentation under non-flash and flash boiling conditions, a phenomenon that enhances fuel vaporization. The main goals of this work are: Design and develop a multi-component fuel droplet and wall film vaporization model using both discrete and continuous thermodynamics methods. Design and develop an analytical model for multi-component flash boiling. Integrate the multi-component droplet and film model into multi-dimensional engine calculations to predict the fuel vaporization process under engine operation condition. Conduct multi-component droplet and fuel film vaporization experiments in a non-combusting chamber to verify the proposed vaporization models. Characterize flash boiling phenomena of multi-component fuel sprays by optical and laser diagnostic techniques. This report will detail the experimental setup and the numerical basis for developing a model to achieve the main goals listed above. Key features of observed multi-component fuel vaporization will be summarized at the end of each experimental sections, and corresponding model performance evaluation will be presented at the end of each model development section.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Multi-stage heat release of multi-component fuels: Insights and implications for advanced engine operation

Multi-stage heat release (MSHR) is a unique phenomenon typically seen in lean/diluted and low- to intermediate-temperature combustion. Despite its relevance to advanced engine operation, the MSHR of multi-component fuels has barely been quantified. This study aims to characterize the MSHR of multi-component fuels in a rapid compression machine (RCM) at conditions representative of advanced combustion engines. New experimental data are first reported in the RCM at an equivalence ratio of 0.4, pressure of 60 bar and temperatures from 702 to 795 K for a research grade, multi-component gasoline surrogate, termed PACE-20. Here, experiments confirm the existence of MSHR for PACE-20 at all temperatures, and reveal the strong inhibiting effect of temperature on MSHR, where increasing temperature inhibits MSHR by suppressing first stage heat release and promoting second and third stage heat release. A detailed chemical kinetic model is also adopted to model the experiments, with good agreement observed. The response of MSHR characteristics to changes in different engine operating parameters (i.e., temperature, pressure, equivalence ratio and CO 2 dilution level) and fuel compositions (i.e., mole fraction of n-pentane, n-heptane, isooctane, cyclopentane, 1-hexene, ethanol and aromatics in PACE-20) is further evaluated via statistical analysis coupling quasi-random sampling, extensive computer experiments and high-dimensional model representation. The change in MSHR is characterized through 8 quantities of interest (QOIs), i.e., duration and extent of each heat release stage, and their standard deviations. The analysis highlights the dependence of the QOIs on the individual parameters as well as their interplays, with temperature exhibiting the strongest impact among all parameters. Furthermore, it is demonstrated that if MSHR is to be facilitated and combustion phasing is to be extended to enable engine operation at higher compression ratios, it is recommended to operate the engine at low intake temperatures, boosted intake pressures and high CO 2 dilutions (i.e., high EGR levels) with gasoline fuels containing more n-pentane and less aromatics.

42 ENGINEERING↗
NASA NTRS1990

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Zhu, Dongming↗
NASA NTRS2003

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Zhu, Dongming↗
DOE OSTI2019

A New Efficient Quantitative Multi-component Phase Field: Lattice Boltzmann Model for Simulating Ti6Al4V Solidified Dendrite Under Forced Flow

Ti6Al4V is a widely used, multi-component alloy in additive manufacturing, during which the fluid flow in the molten pool significantly affects the solidified dendrites. To predict and further control the microstructure, modeling and simulating the microstructure evolution play a critical role. In this study, a newly developed, efficient, quantitative multi-component phase-field (PF) model is coupled with a lattice Boltzmann (LB) model to simulate Ti6Al4V solidified dendrite evolution under fluid flow. The accuracy and convergence behavior of the model is validated by the Gibbs–Thomson relation at the dendrite tip. Single and multiple two-dimensional (2D) equiaxed dendrite evolution cases under forced flow were simulated. Results show that the dendrite pattern is influenced remarkably by the fluid flow. Underlying mechanisms of the asymmetrical evolution are revealed by discussing the interaction among the flow, composition distribution and dendrite morphology, quantitatively. The dendrite kinetics are also derived, which ascertains the relationship between tip velocity and undercooling and inlet velocity and is the foundation for larger-scale simulation. We believe that the coupled quantitative multi-component PF–LB framework employed in this study helps in investigating the solidified dendrite morphology evolution in a deep and quantitate manner.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Determining Multi-Component Phase Diagrams with Desired Characteristics Using Active Learning

Herein, we demonstrate how to predict and experimentally validate phase diagrams for multi-component systems from a high-dimensional virtual space of all possible phase diagrams involving several elements based on small existing experimental data. The experimental data for bulk phases for known systems represents a sampling from this space, and screening the space allows multi-component phase diagrams with given design criteria to be built. This approach uses machine learning methods to predict phase diagrams and Bayesian experimental design to minimize experiments for refinement and validation, all within an active learning loop. The approach is proven by predicting and synthesizing the ferroelectric ceramic system (1-ω)(Ba 0.61 Ca 0.28 Sr 0.11 TiO 3 )-ω(BaTi 0.888 Zr 0.0616 Sn 0.0028 Hf 0.0476 O 3 ) with a relatively high transition temperature and triple point, as well as the NiTi-based pseudo-binary phase diagram (1-ω)(Ti 0.309 Ni 0.485 Hf 0.20 Zr 0.006 )-ω(Ti 0.309 Ni 0.485 Hf 0.07 Zr 0.068 Nb 0.068 ) designed for high transition temperature (ω ≤ 1). Each phase diagram is validated and optimized through only three new experiments. The complexity of these compounds is beyond the reach of today’s computational methods.

36 MATERIALS SCIENCE↗
NASA NTRS1980

An analysis method for multi-component airfoils in separated flow

The multi-component airfoil program (Langley-MCARF) for attached flow is modified to accept the free vortex sheet separation-flow model program (Analytical Methods, Inc.-CLMAX). The viscous effects are incorporated into the calculation by representing the boundary layer displacement thickness with an appropriate source distribution. The separation flow model incorporated into MCARF was applied to single component airfoils. Calculated pressure distributions for angles of attack up to the stall are in close agreement with experimental measurements. Even at higher angles of attack beyond the stall, correct trends of separation, decrease in lift coefficients, and increase in pitching moment coefficients are predicted.

Rao, B. M.↗
DOE OSTI2024

Spray process of multi-component gasoline surrogate fuel under ECN Spray G conditions

As modern gasoline direct injection (GDI) engines utilize sophisticated injection strategies, a detailed understanding of the air-fuel mixing process is crucial to further improvements in engine emission and fuel economy. In this study, a comprehensive evaluation of the spray process of single-component iso-octane (IC8) and multi-component gasoline surrogate E00 (36 % n-pentane, 46 % iso-octane, and 18 % n-undecane, by volume) fuels was conducted using an Engine Combustion Network (ECN) Spray G injector. High-speed extinction, schlieren, and microscopy imaging campaigns were carried out under engine-like ambient conditions in a spray vessel. Experimental results including liquid/vapor penetration, local liquid volume fraction, droplet size, and projected liquid film on the nozzle tip were compared under ECN G1 (573 K, 3.5 kg/m 3 ), G2 (333 K, 0.5 kg/m 3 ), and G3 (333 K, 1.01 kg/m 3 ) conditions. In addition to the experiments, preferential evaporation process of the E00 fuel was elucidated by Large–Eddy Simulations (LES). The three-dimensional liquid volume fraction measurement enabled by the computed tomographic reconstruction showed substantial plume collapse for E00 under the G2 and G3 conditions having wider plume growth and plume-to-plume interaction due to the fuel high vapor pressure. Here, the CFD simulation of E00 showed an inhomogeneity in the way fuel components vaporized, with more volatile components carried downstream in the spray after the end of injection. The high vapor pressure of E00 also results in ~4 μm smaller average droplet diameter than IC8, reflecting a higher rate of initial vaporization even though the final boiling point temperature is higher. Consistent with high vapor pressure, E00 had a wider plume cone angle and enhanced interaction with the wall to cover the entire surface of the nozzle tip in a film. However, the liquid fuel underwent faster evaporation, so the final projected tip wetting area was smaller than the IC8 under the flash-boiling condition.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Large-Scale, GPU-Enhanced DFTB Approaches for Probing Multi-Component Alloys

The major goals of the project are to develop and apply GPU-enhanced density functional theory tight binding (DFTB) calculations for efficient simulations of structural materials of alloy systems. The figure below depicts the GPU algorithmic developments on the left that will be carried out, and the solid-state structures on the right are representative of the complex alloys that can be computed with the GPU-enhanced DFTB approach. The methodology and tools developed in this project encompass accurate intermolecular potentials and GPU enhancements to the density functional tight binding (DFTB) approach for high-throughput ab initio molecular dynamics calculations of multi-component alloys at elevated temperatures. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of large, multi-component alloys at the predictive quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum nature of chemical systems; however, these methods cannot tackle the large sizes relevant to these multi-component systems. The DFTB-based ab initio molecular dynamics approach (coupled with our in-house GPU capabilities for enhanced speed) used in this project provides a viable approach for probing these large systems at a quantum level of detail that is significantly faster than current first-principle methods Collectively, the capabilities developed in this project directly respond to DOE HBCU-OMI, AOI 2-1 initiatives by (1) enabling accurate and efficient predictions and (2) bringing a fundamental understanding of structural interactions in these complex systems at elevated temperatures.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2006

Single-Pulse Multi-Point Multi-Component Interferometric Rayleigh Scattering Velocimeter

A simultaneous multi-point, multi-component velocimeter using interferometric detection of the Doppler shift of Rayleigh, Mie, and Rayleigh-Brillouin scattered light in supersonic flow is described. The system uses up to three sets of collection optics and one beam combiner for the reference laser light to form a single collimated beam. The planar Fabry-Perot interferometer used in the imaging mode for frequency detection preserves the spatial distribution of the signal reasonably well. Single-pulse multi-points measurements of up to two orthogonal and one non-orthogonal components of velocity in a Mach 2 free jet were performed to demonstrate the technique. The average velocity measurements show a close agreement with the CFD calculations using the VULCAN code.

Bivolaru, Daniel↗
NASA NTRS2003

Fast Rotating Scalar and Multi-component Bose Gases

We show that in the limit of large angular momentum, many equilibrium and dynamical phenomena of scalar and multi-component Bose gases can be accounted for by approximating the system to reside in an effective lowest Landau level. This method explains the origin of the mysterious stripe formation in fast rotating Bose gas recently observed at JILA, and accounts for all the dynamical details observed in this experiment. To further demonstrate the usefulness of this method, we present its predictions of the interference patterns of two vortex lattices, and rich vortex lattice structures in multi-component Bose gases.

Ho, TIn-Lun Jason↗
NASA NTRS2016

Photogrammetric Deflection Measurements for the Tiltrotor Test Rig (TTR) Multi-Component Rotor Balance Calibration

Calibrating the internal, multi-component balance mounted in the Tiltrotor Test Rig (TTR) required photogrammetric measurements to determine the location and orientation of forces applied to the balance. The TTR, with the balance and calibration hardware attached, was mounted in a custom calibration stand. Calibration loads were applied using eleven hydraulic actuators, operating in tension only, that were attached to the forward frame of the calibration stand and the TTR calibration hardware via linkages with in-line load cells. Before the linkages were installed, photogrammetry was used to determine the location of the linkage attachment points on the forward frame and on the TTR calibration hardware. Photogrammetric measurements were used to determine the displacement of the linkage attachment points on the TTR due to deflection of the hardware under applied loads. These measurements represent the first photogrammetric deflection measurements to be made to support 6-component rotor balance calibration. This paper describes the design of the TTR and the calibration hardware, and presents the development, set-up and use of the photogrammetry system, along with some selected measurement results.

Calibration↗
NASA NTRS2016

Photogrammetric Deflection Measurements for the Tiltrotor Test Rig (TTR) Multi-Component Rotor Balance Calibration

Calibrating the internal, multi-component balance mounted in the Tiltrotor Test Rig (TTR) required photogrammetric measurements to determine the location and orientation of forces applied to the balance. The TTR, with the balance and calibration hardware attached, was mounted in a custom calibration stand. Calibration loads were applied using eleven hydraulic actuators, operating in tension only, that were attached to the forward frame of the calibration stand and the TTR calibration hardware via linkages with in-line load cells. Before the linkages were installed, photogrammetry was used to determine the location of the linkage attachment points on the forward frame and on the TTR calibration hardware. Photogrammetric measurements were used to determine the displacement of the linkage attachment points on the TTR due to deflection of the hardware under applied loads. These measurements represent the first photogrammetric deflection measurements to be made to support 6-component rotor balance calibration. This paper describes the design of the TTR and the calibration hardware, and presents the development, set-up and use of the photogrammetry system, along with some selected measurement results.

Calibration↗
DOE OSTI2021

Machine learning elastic constants of multi-component alloys

The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. Here, a number of machine learning models, including linear regression, neural network and random forest based models, are trained and tested on a dataset of binary alloys generated using density functional theory (DFT) calculations and spanning over a large number of elemental species in the periodic table. Starting with a wide range of simple and easily accessible compositionally-averaged elemental features, a correlation-based feature selection strategy was used to systematically down-select a set of most relevant features towards the prediction of the elasticity tensor components. The true predictive performance and the associated uncertainties of the models were established by testing on unseen data and bootstrapping, respectively. A single and pair-wise feature partial dependence analysis was performed to visualize the average property trends in the multi-dimensional feature space in order to further understand the achieved predictive performance. The utility of the trained model is further demonstrated by obtaining sufficiently accurate yet highly efficient approximations for bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio for alloys beyond the binary space (i.e., two-component alloys) on which the model was originally trained. More importantly, we test and validate the predictive performance of the developed model directly against the experimentally measured elastic constants of technologically relevant multi-component alloys (such as, Ni- and Ti-based alloys). Finally, utility of such a data-enabled route is demonstrated by predicting the possible range of various elastic properties for vast composition space available within the five component Ni-Cr-Fe-Mo-W alloy system in a high-throughput manner.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Advanced Multi-Component Defect Cluster Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

The advantages of using ceramic thermal barrier coatings in gas turbine engine hot sections include increased fuel efficiency and improved engine reliability. However, current thermal barrier coatings will not have the low thermal conductivity and necessary sintering resistance under higher operating temperatures and thermal gradients required by future advanced ultra efficient and low emission aircraft engines. In this paper, a novel oxide defect cluster design approach is described for achieving low thermal conductivity and excellent thermal stability of the thermal barrier coating systems. This approach utilizes multi-component rare earth and other metal cluster oxide dopants that are incorporated in the zirconia-yttna based systems, thus significantly reducing coating thermal conductivity and sintering resistance by effectively promoting the formation of thermodynamically stable, essentially immobile defect clusters and/or nanoscale phases. The performance of selected plasma-sprayed cluster oxide thermal barrier coating systems has been evaluated. The advanced multi-component thermal barrier coating systems were found to have significantly lower initial and long-term thermal conductivities, and better high temperature stability. The effect of oxide cluster dopants on coating thermal conductivity, sintering resistance, oxide grain growth behavior and durability will be discussed.

Zhu, Dongming↗
NASA NTRS1990

Advanced Multi-Component Defect Cluster Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

The advantages of using ceramic thermal barrier coatings in gas turbine engine hot sections include increased fuel efficiency and improved engine reliability. However, current thermal barrier coatings will not have the low thermal conductivity and necessary sintering resistance under higher operating temperatures and thermal gradients required by future advanced ultra-efficient and low-emission aircraft engines. In this paper, a novel oxide defect cluster design approach is described for achieving low thermal conductivity and excellent thermal stability of the thermal barrier coating systems. This approach utilizes multi-component rare earth and other metal cluster oxide dopants that are incorporated in the zirconia-yttria based systems, thus significantly reducing coating thermal conductivity and sintering resistance by effectively promoting the formation of thermodynamically stable, essentially immobile defect clusters and/or nanoscale phases. The performance of selected plasma-sprayed cluster oxide thermal barrier coating systems has been evaluated. The advanced multi-component thermal barrier coating systems were found to have significantly lower initial and long-term thermal conductivities, and better high temperature stability. The effect of oxide cluster dopants on coating thermal conductivity, sintering resistance, oxide grain growth behavior and durability will be discussed.

Zhu, Dongming↗
DOE OSTI2025

Modeling of multi-component precipitation and crystallization for zero-liquid-discharge desalination

This study proposes novel ZLD treatment trains that integrate multi-component chemical precipitation and multi-effect evaporative crystallization for efficient brine management. The methodology emphasizes sustainability by integrating CO₂ for chemical precipitation and reducing environmental impact, exemplified with two case studies: produced water that includes industrial waste heat utilization by adopting the emerging vacuum air-gapped membrane distillation (VAGMD) technology, and brackish groundwater that is abundant in sulphate which undergoes treatment by low-salt-rejection reverse osmosis (LSRRO) with interstage chemical precipitation. Here, this study is the first of its kind to simultaneously account for reducing risk of mineral scaling and effective recovery of valuable solids when incorporating VAGMD and LSRRO in ZLD treatment trains. Using Reaktoro and WaterTAP, both Python-based, open-source platforms, we model the recovery of high-purity magnesium, calcium, and sodium salts while optimizing energy consumption and operational efficiency in proposed ZLD pathways for case studies of produced water and brackish desalination brine management. Validation with experimental and reference data confirms the reliability of the models used. In both case studies, the optimized ZLD process achieves recovery rates of 97%, 99%, and 90% for Mg, Ca, and Na, with purities exceeding 99%, and brine volume reduced to less than 4% of the initial feed flow.

3D CT scans↗