Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “mixture experiment models”

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.

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

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational and Experimental Study for the Denitrification of Biomass-Derived Hydrothermal Liquefaction Oil

Hydrothermal liquefaction (HTL) is a promising method for processing wet biomass and waste feedstock to produce biofuels. During the HTL process, proteins and other biomolecules in certain feedstock get converted into nitrogenous compounds in produced biocrude, which represents a major challenge to further upgrading them into fuels. One promising approach is to separate nitrogenous compounds from the biocrude using polymeric resins. In this study, experiments were conducted to down-select sorbent and resin systems using a nitrogen-compound-containing surrogate biocrude. We model the binding interactions between an Amberlyst polymeric resin with various compounds present in the biocrude mixture such as nitrogenous compounds like pyrrole, pyridine, hexanamide, and representative co-existing compounds like phenol and dodecanoic acid. To ascertain the efficiency of various resins in the denitrogenation process, we have developed a quantitative structure–function model for the interacting components in the mixture. Our results suggest that the Amberlyst resin is a viable candidate for efficient removal of target nitrogen-containing compounds (such as pyridine) from the biocrude as a result of favorable interactions. The computational studies provide some insight into how and why the identified resin (Amberlyst) works in selective extraction of nitrogenous compound(s).

09 BIOMASS FUELS↗
NASA NTRS2003

Recent Advances In Science Support For Isolated Droplet Combustion Experiments

In a joint program involving Prof. F.A. Williams of the University of California, San Diego and Dr. V. Nayagam of the National Center for Microgravity Research, the combustion characteristics of isolated liquid fuel droplets of n-heptane, n-decane, methanol, methanol-water, ethanol and ethanol-water having initial diameters between about 1 mm and 6 mm continues to be investigated. The objectives of the work are to improve fundamental knowledge of droplet combustion dynamics for pure fuels and fuel-water mixtures through microgravity experiments and theoretical analyses. The Princeton contributions support the engineering design, data analysis, and data interpretation requirements for the study of initially single component, spherically symmetric, isolated droplet combustion studies through experiments and numerical modeling. UCSD contributions are described in a companion communication in this conference. The Princeton effort also addresses the analyses of Fiber Supported Droplet Combustion (FSDC) experiments conducted with the above fuels and collaborative work with others who are investigating droplet combustion in the presence of steady convection. A thorough interpretation of droplet burning behavior for n-heptane and n-decane over a relatively wide range of conditions also involves the influences of sooting on the combustion behavior, and this particular aspect on isolated burning of droplets is under consideration in a collaborative program underway with Drexel University. This collaboration is addressed in another communication at this conference. The one-dimensional, time-dependent, numerical modeling approach that we have continued to evolve for analyzing isolated, quiescent droplet combustion data has been further applied to investigate several facets of isolated droplet burning of simple alcohols, n-heptane, and n-decane. Some of the new results are described below.

Dryer, F. L.↗
NASA NTRS2007

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Principe, Jose C.↗
NASA NTRS2012

Air Density Measurements in a Mach 10 Wake Using Iodine Cordes Bands

An exploratory study designed to examine the viability of making air density measurements in a Mach 10 flow using laser-induced fluorescence of the iodine Cordes bands is presented. Experiments are performed in the NASA Langley Research Center 31 in. Mach 10 air wind tunnel in the hypersonic near wake of a multipurpose crew vehicle model. To introduce iodine into the wake, a 0.5% iodine/nitrogen mixture is seeded using a pressure tap at the rear of the model. Air density was measured at 56 points along a 7 mm line and three stagnation pressures of 6.21, 8.62, and 10.0 MPa (900, 1250, and 1450 psi). Average results over time and space show rho(sub wake)/rho(sub freestream) of 0.145 plus or minus 0.010, independent of freestream air density. Average off-body results over time and space agree to better than 7.5% with computed densities from onbody pressure measurements. Densities measured during a single 60 s run at 10.0 MPa are time-dependent and steadily decrease by 15%. This decrease is attributed to model forebody heating by the flow.

Balla, Robert J.↗
DOE OSTI2018

Multi-dimensional modeling of non-equilibrium plasma for automotive applications

While spark-ignition (SI) engine technology is aggressively moving towards challenging (dilute and boosted) combustion regimes, advanced ignition technologies generating non-equilibrium types of plasma are being considered by the automotive industry as a potential replacement for the conventional spark-plug technology. However, there are currently no models that can describe the low-temperature plasma (LTP) ignition process in computational fluid dynamics (CFD) codes that are typically used in the multi-dimensional engine modeling community. A key question for the engine modelers that are trying to describe the non-equilibrium ignition physics concerns the plasma characteristics. A key challenge is also represented by the plasma formation timescale (nanoseconds) that can hardly be resolved within a full engine cycle simulation. This paper reports on the multi-dimensional modeling of LTP generated by a nanopulsed high-voltage discharge in a pin-to-pin electrode configuration, and evaluates the effects of ambient pressure on the post-discharge results. It is shown that a nanopulsed delivery can result in a LTP or a mode transition to an arc-like event depending on the mixture properties in the gap between the two electrodes. It is further shown that numerical predictions of the LTP-to-arc transition point as a function of ambient pressure along with qualitative distributions of important radicals and temperature closely match recent experiments with identical geometry and discharge characteristics. As a result, the high-fidelity modeling effort described in this paper can be used as a key tool to deliver in-depth understanding of non-equilibrium plasmas for automotive applications and lead to the future implementation of dedicated models for ignition technologies that are based on non-equilibrium plasma physics.

Scarcelli, Riccardo↗
DOE OSTI2018

Explosion-induced ignition and combustion of acetylene clouds

We investigate the explosion-induced ignition and combustion of an acetylene cloud in a rectangular chamber (10 cm × 10 cm × 39 cm). In the experiments, a 0.2-g PETN charge was located at $x = 9.7\,\hbox {cm}$ and a soap bubble (d=5cm) filled with pure acetylene was located at $x = 27\,\hbox {cm}$ as measured relative to the end wall. Detonation of the charge created a blast wave that crushed the soap bubble—inducing mixing with the air. After 0.55 ms, the mixture ignited, forming at turbulent combustion cloud. The flow was modeled using the compressible Navier–Stokes equations assuming unity Lewis number. Arrhenius-based kinetics were used to model ignition. Adaptive mesh refinement was used to capture turbulent mixing on the grid (the MILES approach of J. Boris). Computed pressures were found to be in agreement with measured pressure histories. Finite-rate kinetics were required to capture the ignition processes over the duration of the experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Putting Priors in Mixture Density Mercer Kernels

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Srivastava, Ashok N.↗
DOE OSTI2013

Investigation of an ion-ion hybrid Alfven wave resonator

A theoretical and experimental investigation is made of a wave resonator based on the concept of wave reflection along the confinement magnetic field at a spatial location where the wave frequency matches the local value of the ion-ion hybrid frequency. Such a situation can be realized by shear Alfven waves in a magnetized plasma with two ion species because this mode has zero parallel group velocity and experiences a cut-off at the ion-ion hybrid frequency. Since the ion-ion hybrid frequency is proportional to the magnetic field, it is expected that a magnetic well configuration in a two-ion plasma can result in an Alfven wave resonator. Such a concept has been proposed in various space plasma studies and could have relevance to mirror and tokamak fusion devices. This study demonstrates such a resonator in a controlled laboratory experiment using a H{sup +}-He{sup +} mixture. The resonator response is investigated by launching monochromatic waves and impulses from a magnetic loop antenna. The observed frequency spectra are found to agree with predictions of a theoretical model of trapped eigenmodes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Measurements of Density and Sound Speed in Mixtures Relevant to Supercritical CO2 Cycles

Abstract The objective of this research is to validate properties of mixtures relevant to supercritical carbon dioxide (sCO2) power cycles. Direct-fired sCO2 cycles are a promising technology for the future power generation systems. The working fluid of sCO2 cycles will be near and above critical point of CO2. One of the challenges is that the simulation of mixtures should consider real gas behavior. Expected operating conditions of Allam cycles reach up to 300 bar and 1000 °C. Characterizing the mixtures at the extreme conditions is an important issue in current researches and industrial applications. Thermophysical properties of mixtures may be beyond the valid range of the widely used database such as NIST REFPROP. Experimental data of mixture properties in the literature are limited which is necessary to develop high-fidelity design tools for sCO2 power cycles. We measured the density and sound speed of several multi-component mixtures. A temperature-controlled high-pressure test cell was used for the density measurements. Sound speed was measured by resonant frequency detection using an external speaker and a piezoelectric pressure sensor. Mixtures studied in this work include carbon dioxide, methane, oxygen, and water vapor. Properties of pure CO2 were measured to show the validity of our technique. Compositions were selected to be close to frozen mixtures at the inlet, mid-progress, and exhaust conditions of a model sCO2 combustor in the previous numerical simulation work. Corresponding reaction progress variables (RPV) were RPV = 0, 0.5, and 1. Temperature and pressure conditions of experiments are 310–450 K and 0–150 bar. In our study, density and sound speed from the NIST REFPROP database agree with experimental measurements within the range of our measurement uncertainties.

Energy & Fuels↗
DOE OSTI2020

Influence of Equation-of-States on Supercritical CO2 Combustion Mixtures

Abstract Fossil fuel based direct-fired supercritical CO2 (sCO2) cycles are gaining the attention of industry, academia, and government due to their remarkable efficiency and carbon capture at high-source temperatures. Modeling plays an important role in the development of sCO2 combustors because experiments are very expensive at the designed operating conditions of these direct-fired cycles. Inaccurate density estimates are detrimental to the simulation output. Hence, this work focuses on comprehensive evaluation of the influence and applicability of various equation-of-states (EOS) which are being used in the supercritical combustion modeling literature. A state-of-the-art supercritical combustion modeling methodology is used to simulate counter-flow supercritical CO2 flames by using various equation-of-states. The results show that using the corresponding state principle to evaluate compressibility factor is not accurate. Also, van der Waal type EOSs predictions can be as accurate as complex Benedict–Webb–Rubin EOSs; hence van der Waal EOSs are more suitable to simulate sCO2 combustor simulations. Non-ideal effects are significant under the operating conditions considered in this work. The choice of EOS significantly influences the flame structure and heat release rate. Also, assuming the binary interaction parameter as zero is reasonable in sCO2 combustion simulations.

Energy & Fuels↗
DOE OSTI2015

The CPA Equation of State and an Activity Coefficient Model for Accurate Molar Enthalpy Calculations of Mixtures with Carbon Dioxide and Water/Brine

Thermodynamic property calculations of mixtures containing carbon dioxide (CO 2 ) and water, including brines, are essential in theoretical models of many natural and industrial processes. The properties of greatest practical interest are density, solubility, and enthalpy. Many models for density and solubility calculations have been presented in the literature, but there exists only one study, by Spycher and Pruess, that has compared theoretical molar enthalpy predictions with experimental data. In this report, we recommend two different models for enthalpy calculations: the CPA equation of state by Li and Firoozabadi, and the CO 2 activity coefficient model by Duan and Sun. We show that the CPA equation of state, which has been demonstrated to provide good agreement with density and solubility data, also accurately calculates molar enthalpies of pure CO 2 , pure water, and both CO 2 -rich and aqueous (H 2 O-rich) mixtures of the two species. It is applicable to a wider range of conditions than the Spycher and Pruess model. In aqueous sodium chloride (NaCl) mixtures, we show that Duan and Sun’s model yields accurate results for the partial molar enthalpy of CO 2 . It can be combined with another model for the brine enthalpy to calculate the molar enthalpy of H 2 O-CO 2 -NaCl mixtures. We conclude by explaining how the CPA equation of state may be modified to further improve agreement with experiments. This generalized CPA is the basis of our future work on this topic.

02 PETROLEUM↗
DOE OSTI2022

Polymers in Deep Eutectic Solvents

The project investigated the behavior of polymers in ionic liquids such as deep eutectic solvents using an array of techniques. These included the development of atomistic force fields, coarse graining these force fields to the united atom level, large scale molecular dynamics (MD) simulations using new thermostat algorithms, and machine learning (ML) methods for the phase behavior. The project demonstrated the feasibility and accuracy of first principles force fields for ionic liquids, deep-eutectic solvents, and urea-water mixtures. A novel hierarchical coarse graining method was then used to develop accurate and efficient united-atom models, using which microsecond simulations were performed for polymers in ionic liquids. These simulations were in quantitative agreement with experiment, thus resolving previous controversies. Methods were also developed to obtain the potential of mean force between complex ions in solution. Finally, supervised ML methods were developed for the phase behavior of polymers in ionic liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Capillary rise, wetting layers, and critical phenomena in confined geometry

Interferometric procedures have been used to measure the thickness of the wetting layers of liquid SF6 which intrude between SF6 vapor and the walls of an interferometer. Close to the critical temperature the measurements show that the layers become thicker as the height at which they are observed approaches the height of the bulk liquid-vapor meniscus. The functional form of the thickness increase agrees with the dependence expected from models in which the layers' thicknesses are governed by a competition between gravitational and van der Waals forces. The layers are a factor of three thicker than a simple estimate based on such models. No evidence is found of a transition from three-dimensional critical behavior towards two-dimensional critical behavior in the available temperature and size ranges. This contrasts with the interpretation of experiments in binary liquid mixtures carried out with comparable size and temperature resolution.

Moldover, M. R.↗
NASA NTRS1987

Enhancements to Program LAURA for computation of three-dimensional hypersonic flow

Changes to Program Laura (Langley Aerothermodynamic Upwind Relaxation Algorithm) are presented which enhance both stability and accuracy of the algorithm. A discussion of iteration/sweeping strategies and their relation to computer architectures is included to best exploit the capabilities of serial, vector, and parallel processor machines. Test cases for Mach 10 perfect gas flow and Mach 32 real gas flow in chemical nonequilibrium over a blunt, raked elliptic cone using the thin-layer Navier-Stokes equations are presented in order to demonstrate the current improved capabilities. Algorithm changes include the use of volume averaging, application of a symmetric total variation diminishing (TVD) scheme, and stronger interaction between the grid/shock alignment routine and the relaxation algorithm. Good comparisons with heat transfer and pitching moment data at three different angles of attack for the Mach 10 tests serve to further validate the present algorithm. Parameters are defined which control the coupling of the specie continuity equations with the solution of the mixture conservation equations. A discussion of the consequences involved in the choice of strong versus weak coupling is presented, and a sample nonequilibrium calculation on a fine grid over a full scale model of the Aeroassist Flight Experiment (AFE) demonstrates current capabilities.

Gnoffo, Peter A.↗
NASA NTRS1988

Studies of blackbody-pumped lasers

Laser action was achieved in a large-scale pulsed system and meaningful experiments were carried out in the axial flow facility to understand the physics of solar-pumped lasers. Studies of the variation of laser mixture composition were done for mixtures of CO2 and N2O additions. Theoretical analysis and modeling of the system were also performed based on a model including radiative pumping, diffusion and wall deactivation, and vibrational energy transfer between two optically active species. Qualitative agreement between predictions in the parameter variation and the experimental results were obtained with CO and N2O mixtures. Several experimental studies were performed to quantify the properties of carbon monoxide as absorber and storage of energy in the blackbody pumped system.

Christiansen, W. H.↗
NASA NTRS1997

SiC Recession Due to SiO2 Scale Volatility Under Combustor Conditions

One of today's most important and challenging technological problems is the development of advanced materials and processes required to design and build a fleet of supersonic High Speed Civil Transport (HSCT) airliners, a follow-up to the Concorde SST. The innovative combustor designs required for HSCT engines will need high-temperature materials with long-term environmental stability. Higher combustor liner temperatures than today's engines and the need for lightweight materials will require the use of advanced ceramic-matrix composites (CMC's) in hot-section components. The HSCT is just one example being used to demonstrate the need for such materials. This thesis evaluates silicon carbide (SiC) as a potential base material for HSCT and other similar applications. Key issues are the environmental durability for the materials of interest. One of the leading combustor design schemes leads to an environment which will contain both oxidizing and reducing gas mixtures. The concern is that these environments may affect the stability of the silica (SiO2) scale on which SiC depends for environmental protection. A unique High Pressure Burner Rig (HPBR) was developed to simulate the combustor conditions of future gas turbine engines, and a series of tests were conducted on commercially available SiC material. These tests are intended as a feasibility study for the use of these materials in applications such as the HSCT. Linear weight loss and surface recession of the SiC is observed as a result of SiO2 volatility for both fuel-lean and fuel-rich gas mixtures. These observations are compared and agree well with thermogravimetric analysis (TGA) experiments. A strong Arrhenius-type temperature dependence exists. In addition, the secondary dependencies of pressure and gas velocity are defined. As a result, a model is developed to enable extrapolation to points outside the experimental space of the burner rig, and in particular, to potential gas turbine engine conditions.

Robinson, Raymond Craig↗
DOE OSTI2015

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Characterizing the contribution of bioaerosols diversity from complex aerosol particle samples.

Current global change scenarios expect to significantly increase the contribution of pollen to the total organic aerosol budget. In addition, pollen can burst into smaller fragments that are highly efficient as cloud condensation nuclei. However, current climate models still do not incorporate the effects of these particles due to detection and quantification challenges in complex aerosol mixtures. Chemical biomarkers (i.e. fructose) have commonly been used to trace pollen but this approximation can generate false positive results given the large number of shared compounds between different bioaerosols. A previous pilot EMSL experiment performed on pure pollen samples suggested that using a set of metabolites as a fingerprint of bioaerosols could serve to substantially increase detection accuracy over single biomarker approaches. In this proposal we developed novel bioinformatic strategies to characterize and quantify complex pollen mixtures present in the atmosphere. For that, we used diverse machine learning algorithms to analyze metabolic fingerprints from complex mixtures of different pollen acquired with high-resolution mass spectrometry (Orbitrap Q-Exactive). Our preliminary results demonstrated the potential to accurately discern and identify at specific relative abundances different pollen species in complex mixtures. Our research will lead to a significant advancement in the atmospheric chemistry and provide much needed data to improve the accuracy of climate models.

54 ENVIRONMENTAL SCIENCES↗