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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A kinetic modeling study on octane rating and fuel sensitivity under HCCI conditions

With the development of advanced compression ignition engines such as the homogeneous charge compression ignition (HCCI) and the reactivity controlled compression ignition (RCCI), the long existing research and motor octane rating for fuels, i.e., RON and MON, might be insufficient to describe the fuel reactivity and performance with these new combustion strategies due to their distinctive engine operation conditions. It is also noted that with the stringent regulation for CO2 emission, a detailed knowledge of fuel reactivity is urgently needed for the selection of novel alternative bio-fuels for transportation, and optimization of their engine performance in the future. It is therefore very important to understand the reactivity and sensitivity for general classes of fuels as a function of the operating conditions in these advanced combustion engines. In this modeling study, using validated kinetic mechanism for ignition, we have simulated the performance of different classes of fuels including hydrogen, alkanes (straight and branched), alcohols and potential bio-fuels under typical HCCI engine conditions using detailed chemical kinetics. The crank angle corresponding to 50% total heat release (CA50) is utilized as an indicator for the fuel reactivity. Iso-contours of CA50 are then plotted in the engine operating parameter coordinate, such as the intake temperature, and pressure. It is shown that CA50 value can vary significantly with different engine operating conditions, and that fuels with the same RON/MON even exhibit qualitatively different CA50 iso-contours in specific operating regimes, implying differences in the intrinsic reactivity of different classes of fuels, as well as the insufficiency of RON/MON as comprehensive metrics of fuel reactivity in advanced compression ignition (ACI) strategies. In addition, the operating regime with high and low sensitivity, as well as potential non-monotonic change in fuel reactivity, has been identified by the CA50 iso-contour map for all studied fuels.

Wu, Tong↗
DOE OSTI2019

Auto-ignitive deflagration speed of methane (CH 4 ) blended dimethyl-ether (DME)/air mixtures at stratified conditions

Front propagation speeds from fully resolved unsteady one dimensional simulations with dimethyl-ether (DME)/methane (CH 4 )/air mixtures under engine relevant conditions are presented using complex kinetics and transport. Different time-scales of monochromatic inhomogeneities in DME concentration with varying DME/CH 4 blending ratios are simulated to unravel the fundamental aspects of auto-ignition and flame propagation under the influence of reactivity stratification. To understand the influence of different stratification time-scales on the flame-ignition interaction, two sets of conditions are simulated such that low temperature chemistry is present in only one of them. For a given amplitude of stratification, it is found that the instantaneous propagation speed is significantly affected by the level of CH 4 concentration in the binary fuel blend. Specifically, for cases with low temperature chemistry, at relatively smaller time-scales, the overall fluctuation in the instantaneous propagation speed is found to subside as the level of CH 4 concentration in the mixture is increased. However, for both sets of conditions, at comparatively larger time-scales, a rapid change in the instantaneous propagation speed is observed with an increase in the level of CH 4 concentration in the mixture. The intrinsic effects of stratification time-scales on the low temperature chemistry and the high temperature chemistry are further examined to assess the flame-ignition interaction. A displacement speed analysis is also carried out to elucidate the underlying combustion modes that are responsible for such a variation in flame response.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Spectral Analysis of LDV Measurements inside of the TAMU Air-Cooled Reactor Cavity Cooling System - 18688

Spectral analysis was applied to the LDV measurements inside of the TAMU air-cooled RCCS facility at two different locations to both evaluate the feasibility of spectral methods for this experiment and gain a first insight into the flow behavior using a Fourier representation. Application of the wavelet transform showed that there are patterns in the flow signified by repeating frequencies and flow structures. Although the sampling rate of 7.92 Hz at the data point centered at the bottom center of riser 4 was lower than the higher frequency sampling rate of 57.92 Hz at the top data point of the upper plenum, the wavelet transforms of the higher frequency data point showed that the dominant frequencies were bounded within 4 Hz. Application of wavelet analysis is limited by the size of the interrogation window but may be modified according to the frequency range of interest by adjusting the size of the time width for the undilated Morlet mother wavelet. Spectral analysis can be applied to future experiments to understand uncharacterized flow behavior such as flow reversal inside of the upper plenum and for benchmarking future CFD simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Modeling primary atomization of liquid fuels using a multiphase DNS/LES Approach

We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were addressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to de- scribe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

02 PETROLEUM↗
DOE OSTI2021

Learning the solution operator of parametric partial differential equations with physics-informed DeepONets

Partial differential equations (PDEs) play a central role in the mathematical analysis and modeling of complex dynamic processes across all corners of science and engineering. Their solution often requires laborious analytical or computational tools, associated with a cost that is markedly amplified when different scenarios need to be investigated, for example, corresponding to different initial or boundary conditions, different inputs, etc. In this work, we introduce physics-informed DeepONets, a deep learning framework for learning the solution operator of arbitrary PDEs, even in the absence of any paired input-output training data. We illustrate the effectiveness of the proposed framework in rapidly predicting the solution of various types of parametric PDEs up to three orders of magnitude faster compared to conventional PDE solvers, setting a previously unexplored paradigm for modeling and simulation of nonlinear and nonequilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A complementarity-based vapor-liquid equilibrium formulation for equation-oriented simulation and optimization

Vapor-Liquid Equilibrium (VLE) is a cornerstone of computer aided process engineering (CAPE). Embedded within process system models, VLE calculations are inherently procedural with non-smooth behavior that frequently require discrete decisions. Traditionally, these features resist the incorporation of VLE within efficient, large-scale equation-oriented (EO) process simulation and optimization strategies. On the other hand, recent reformulation of VLE models through the incorporation of complementarity constraints has broadened its scope to deal seamlessly with phase transitions and even supercritical excursions in process simulation and optimization. In this study, we extend these VLE complementarity models to EO frameworks where procedural thermodynamic property libraries are still required. Here, we develop an efficient, non-intrusive, and intuitive “square-flash” equation system that has been implemented within the IDAES Integrated Platform (IDAES-IP). Further, the effectiveness of this modular approach is demonstrated on case studies for non-ideal flash calculations and distillation optimization with disappearing phases and supercritical transitions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Microstructure of vapor deposited coatings on curved substrates

Thermal barrier coating systems consisting of a metallic bond coat and ceramic over layer are widely used to extend the life of gas turbine engine components. They are applied using either high-vacuum physical vapor deposition techniques in which vapor atoms rarely experience scattering collisions during propagation to a substrate, or by gas jet assisted (low-vacuum) vapor deposition techniques that utilize scattering from streamlines to enable non-line-of-sight deposition. Both approaches require substrate motion to coat a substrate of complex shape. Here, direct simulation Monte Carlo and kinetic Monte Carlo simulation methods are combined to simulate the deposition of a nickel coating over the concave and convex surfaces of a model airfoil, and the simulation results are compared with those from experimental depositions. The simulation method successfully predicted variations in coating thickness, columnar growth angle, and porosity during both stationary and substrate rotated deposition. It was then used to investigate a wide range of vapor deposition conditions spanning high-vacuum physical vapor deposition to low-vacuum gas jet assisted vapor deposition. The average coating thickness was found to increase initially with gas pressure reaching a maximum at a chamber pressure of 8–10 Pa, but the best coating thickness uniformity was achieved under high vacuum deposition conditions. However, high vacuum conditions increased the variation in the coatings pore volume fraction over the surface of the airfoil. The simulation approach was combined with an optimization algorithm and used to investigate novel deposition concepts to tailor the local coating thickness.

42 ENGINEERING↗
DOE OSTI2014

Large-Scale Data Analytics and Its Relationship to Simulation

Large-Scale Data Analytics (LSDA) problems require finding meaningful patterns in data sets that are so large as to require leading-edge processing and storage capability. LSDA problems are increasingly important for government mission work, industrial application, and scientific discovery. Effective solution of some important LSDA problems requires a computational workload that is substantially different from that associated with traditional High Performance Computing (HPC) simulations intended to help understand physical phenomena or to conduct engineering. While traditional HPC application codes exploit structural regularity and data locality to improve performance, many analytics problems lead more naturally to very fine-grained communication between unpredictable sets of processors, resulting in less regular communication patterns that do not map efficiently on to typical HPC systems. In both simulation and analytics domains, however, data movement increasingly dominates the performance, energy usage, and price of computing systems. It is therefore plausible that we could find a more synergistic technology path forward. Even though future machines may continue to be configured differently for the two domains, a more common technological roadmap between them in the form of a degree of convergence in the underlying componentry and design principles to address these common technical challenges could have substantial technical and economic benefits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Modeling primary atomization of liquid fuels using a multiphase DNS/LES Approach

We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were ad- dressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to describe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

02 PETROLEUM↗
DOE OSTI2014

Development of a versatile hybrid testing system for seismic experimentation

The hybrid testing method for earthquake engineering was developed to evaluate the seismic performance of civil structural systems. During hybrid testing, part of the structure, called physical substructure, is physically tested using hydraulic loading equipment while the rest of the structure, named numerical substructure, is numerically simulated with a computer model. Thus, hybrid testing allows a complex physical substructure being tested experimentally, while the relatively simple part of the structure is numerically simulated to economically obtain the full structural response. Recently, a versatile hybrid testing system was built at Western Michigan University consisting of a shake table, an actuator/reaction system, and an advanced hybrid testing controller. Such a testing system is capable of conducting various seismic experiments such as displacement-based pseudodynamic substructure testing as well as force-based real time dynamic hybrid testing. Because of its versatility and easy operation at the benchmark scale, the developed testing system is particularly suitable for the development of advanced hybrid testing techniques and, earthquake engineering education/outreach activities. The development of the testing system is described in this article focusing on the hardware and software integrations. A three story shake table hybrid test is presented as an example to demonstrate the system’s capability and feasibility.

42 ENGINEERING↗
DOE OSTI2022

Dynamic force and stability prediction for milling using feed rate scheduling software and time-domain simulation

This paper describes: 1) the use of feed rate scheduling software to predict the radial depth of cut variation for three-axis milling toolpaths and; 2) the use of the radial depth profile in a time-domain simulation to predict dynamic cutting forces. The time-domain simulation, which also includes the tool tip frequency response functions and force model (which relates the cutting force components to the chip geometry) as inputs, enables dynamic force profiles to be predicted and parameter combinations that cause chatter to be identified. A ramp geometry is selected that provides constantly varying radial depth and force predictions are completed at multiple axial depths for comparison to measured forces. Both stable and unstable (chatter) milling conditions were observed with good agreement between time-domain simulation and measurement results. The value of combining the feed rate scheduling software and time-domain simulation is demonstrated.

42 ENGINEERING↗
DOE OSTI2016

Research reactor plate fuel multi-physics hotspot model for the HFIR

Ongoing development of a multi-physics hotspot model for nuclear research reactor plate fuel is presented with a focus on the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The background of plate fueled research reactors in general and the HFIR in particular are discussed along with the need to convert from high enriched uranium (HEU) to low enriched uranium (LEU) fuel, which drives the need to improve the analysis capability of fuel thermal-fluid performance. HFIR HEU fuel plate fabrication is described to explain the origin of fuel segregations and cladding non-bonds that currently contribute to the hotspot flux peaking factors. Previous efforts at modeling hotspots caused by these defects are reviewed and areas for improvement associated with high resolution multi-physics simulation are identified. Modes of heat transfer through non-bonds, including thermal contact conductance, are examined. Conjugate heat transfer over hotspots is also explored to high resolution up to and through the wall boundary. The challenges associated with multi-physics verification and validation (VV), particularly the requirements beyond VV 20, are presented. An approach to Validation within the limits of existing data for conduction heat transfer through the fuel plate, and convection into the cooling fluid is set forth. Preliminary simulations are presented assessing hot spot modeling approaches for contact conductance, and fluid turbulence modeling within COMSOL. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
DOE OSTI2020

Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling

The promise of data-driven predictive modeling is being increasingly realized in various science and engineering disciplines, where experts are used to the more conventional, simulation-driven modeling practices. However, trust remains a bottleneck for greater adoption of machine learning-based models for domain experts, who might not be necessarily trained in data science. In this paper, we focus on the building energy domain, where physics-based simulations are being complemented or replaced by machine learning-based methods for forecasting energy supply and demand at various spatio-temporal scales. We study the trust problem in close collaboration with energy scientists and engineers and describe how visual analytics can be leveraged for alleviating this trust bottleneck for stakeholders with varying degrees of expertise and analytics goals in this domain.

Kandakatla, Akshith R.↗
DOE OSTI2021

Manipulating Pore Topology and Functionality to Promote Fluorocarbon-Based Adsorption Cooling

With the worldwide demand for refrigeration and cooling expected to triple, it is increasingly important to search for alternative energy resources to drive the refrigeration cycles with reduced electricity consumption. Recently, adsorption cooling has gained increased attention since energy reallocation in such systems is based on gas adsorption/desorption, which can be driven by waste/natural heat sources. Eco-friendly sorption-based cooling relies on the cyclic transfer of refrigerant gas from a high to low energy state by the pseudo-compression effect resulting from adsorption and desorption. The driving force for energy transfer relies on heat rather than electricity. The performance of a sorption chiller is primarily influenced by this cyclic sorption behavior, which is characterized as the working capacity of the porous sorbent. Thus increases in this working capacity directly translate to a more compact and efficient cooling system. How-ever, a lack of highly effective sorbent/refrigerant pairs lowers cooling performance, and therefore has limited applicability. To this end, synthetic metal-organic frameworks (MOFs) and covalent organic polymers (COPs) possess higher porosity and greater tunability leading to more substantial potential benefits for adsorption, compared to traditional sorbent materials. Similarly, hydrofluorocarbon refrigerants have more favorable applicability given ease of operation above atmospheric pressures due to suitable saturated vapor pressures and boiling points. For these reasons, our work focuses on an ongoing strategy to promote sorption cooling via improvements in the sorbent/refrigerant pair. Specifically, we target the interaction of hydrofluorocarbon refrigerants with MOF/COP materials at a molecular level by interpreting the host-guest chemistry and the role of framework pore topology. These molecular level differences translate to cooling performance, which is described herein. These strategies include engineering framework porosity (i.e., pore size, pore volume) by using elongated organic linkers and stereochemistry control during synthesis; manipulating the sorb-ate/sorbent interaction by introducing functional moieties or unsaturated metal centers to enhance working capacities in narrow pressure ranges; varying pore topology/morphology to impact adsorption isotherm behavior; and leveraging defective sites within the frameworks to further enhance adsorption capability. Here this atomic level understanding of sorb-ate-sorbent interactions is conducted using various in situ experimental techniques such as synchrotron-based X-ray diffraction, X-ray absorption spectroscopy, in situ Fourier transform infrared spectroscopy, and direct sorption energies determinization with calorimetry. Moreover, the experimentally studied interactions and the corresponding adsorption mechanism are corroborated by computational studies using density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations. Using this approach, we envision the capability to engineer designed frameworks with precise molecular control to target refrigerant molecules and thereby enhance the performance of desired working pairs for sorption-based cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.

30 DIRECT ENERGY CONVERSION↗