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Finney, Charles

Publications and source records attributed to Finney, Charles.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Validation Framework for Post-Combustion Carbon Capture CFD Simulations

First-principles based computational fluid dynamics (CFD) simulations are proposed as a fundamental tool for investigating solvent-based CO2 absorption in packed columns, due to the ability to accurately represent the underlying non-linear multiscale dynamics. In this work, we employ such models to investigate hydrodynamics of columns with structured by assessing the key hydrodynamic metrics, such as pressure drop and liquid holdup. Our models are validated with experimental data from a specifically designed column for this line of work. The test cases of gas and liquid flowrates and operating conditions were selected through a comprehensive sequential design of experiments approach offered by the CCSI2 toolset.

Panagakos, Grigorios↗
DOE OSTI2023

Measurement of needle and armature dynamics in a gasoline direct injector by high-speed neutron imaging

In modern spark ignition engines, precise delivery of fuel with gasoline direct injection has become increasingly important in the effort to meet ever stricter efficiency and emissions regulations. Use of multiple small close-coupled injections has become more common in attempt to precisely control fuel distribution in the cylinder, but these strategies are hindered by nonlinear injection effects due to operation in the ballistic region of the solenoid-operated valve and due to armature bounce at the end of injection. Understanding the internal dynamics of the injector is crucial to minimizing and controlling non-linearity and shot-to-shot variation, but the experimental techniques available to date are capable only of tracking the position of either the top of the needle (via laser sensors or by monitoring current and voltage in the solenoid coil) or the bottom of the needle (via transparent nozzles or high-speed x-ray imaging). Furthermore, a complete picture of the axial and radial motion of valve needle has until now remained elusive. In this work, we present high-speed ensemble neutron transmission imaging of an entire 8-hole gasoline direct injector operating at 200 bar, allowing for both visualization and quantification of the actuation dynamics including lift and wobble of the valve ball, oscillation and bending of the valve needle, lift, rocking, and bounce of the armature, compression of the springs, and radial swelling of the solenoid during energization. Because neutrons offer high penetration through the metal injector while also being sensitive to the 1 H nuclei in fuel molecules, it is also possible to simultaneously see the fluid dynamics of the injection process, including filling of the sac volume, emanation of the spray through the nozzle holes and into the downstream gas, and the formation and evolution of fuel films on the tip of the injector and the walls of the spray container.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Computational Requirements in Clean Energy and Manufacturing: Summary report of the virtual workshop held on June 28-29, 2021

On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Impact of Materials Properties on Higher-Temperature Engine Operation

Here, we examine the effects on materials temperatures and engine efficiency via simulations of engines operating at temperatures which exceed the thermal limits of today’s materials. Potential focus areas include high-speed, high-load operation (in the fuel-enrichment zone) as well as conditions of selective cooling at lower speeds and loads. We focus on a light-duty DISI and a heavy-duty CI engine using GT-Power. Temperature distributions within the head, block, piston, and valves were obtained from 3D FEA simulations coupled with 1D GT-Power representations of the engine’s gas flow and combustion regions. We use experimentally measured thermal properties of current commercial alloys for specific engine components, as well as candidate developmental alloys with improved temperature tolerance, to gauge the effects of materials properties on engine performance, particularly focusing on operating areas where materials which can withstand higher temperatures can enable intensified combustion conditions and increased specific output. The outcome of this work is guidance on materials selection targets and benefits as OEMs meet engine-performance needs in the coming decades, to include Class 8 line-haul freight vehicles with reduced emissions, as well as design of future near net zero-carbon light-duty range extenders for more rapid electrification of medium- and heavy-duty vehicles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Advanced Intra-Cycle Detection of Pre-Ignition Events through Phase-Space Transforms of Cylinder Pressure Data

The widespread adoption of boosted, downsized SI engines has brought pre-ignition phenomena into greater focus, as the knock events resulting from pre-ignitions can cause significant hardware damage. Much attention has been given to understanding the causes of pre-ignition and identify lubricant or fuel properties and engine design and calibration considerations that impact its frequency. This helps to shift the pre-ignition limit to higher specific loads and allow further downsizing but does not fundamentally eliminate the problem. Real-time detection and mitigation of pre-ignition would thus be desirable to allow safe engine operation in pre-ignition-prone conditions. This study focuses on advancing the time of detection of pre-ignition in an engine cycle where it occurs. Furthermore, phase space transforms through time-delay embedding of cylinder pressure and principal component analysis were applied to same-cycle detection of pre-ignition and shown to enable detection on the order of a crank degree earlier than deviation in cylinder pressure can be identified through direct statistical observation of the pressure data. Additionally, it appears that the deviation of the trajectory in phase space may offer the opportunity to extend this method to further extend the detection window and allow more time for mitigation actions to occur.

42 ENGINEERING↗
DOE OSTI2020

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗
DOE OSTI2019

Reduced-order model to estimate safe flammable refrigerant charge limits for a one-room air conditioner

The Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) industry is currently transitioning away from high global warming potential (GWP) hydrofluorocarbon (HFC) refrigerants. However, many lower-GWP alternatives are flammable. Current safety codes restrict use of all flammable refrigerants; revision of the codes is needed to facilitate wider use of flammable alternatives. Hence, information is needed to enable reliable estimates of safe charge limits for flammable refrigerant options for different HVAC&R applications. A reduced-order model (ROM) was developed and validated to help estimate safe charge limits based on computational fluid dynamics (CFD) simulations of refrigerant releases in a single room for a range of parameters. Validation of the ROM vs. the CFD results showed good general agreement for mean refrigerant concentration. The normalized mean bias error (NMBE) was 0.67% with a maximum error of 15%.

Edwards, Dean↗
DOE OSTI2019

Identifying sources of thermoacoustic vibrations (rumble) in industrial furnaces and boilers

Industrial gas-fired boilers, furnaces and heaters occasionally suffer low-frequency vibrations generated by dynamic feedback between the burner (or burners) and acoustic modes in adjacent cavities in the main combustion chamber or ductwork. Feedback occurs when pressure pulses associated with acoustic resonances propagate to the burner so that they are in phase with combustion rate fluctuations. When the combustion and acoustic fluctuations become sufficiently phase-synchronized, normal sources of dissipation are insufficient to damp the combined pressure waves, and they can become sufficiently amplified to reduce thermal efficiency, increase emissions, and even cause structural damage. In the literature, such oscillations are referred to as thermoacoustic oscillations or ‘rumble’, and their basic physics have been the subject of numerous investigations for well over a century. Although it occurs relatively infrequently, rumble poses a significant challenge because it is difficult to predict, diagnose, and resolve. The underlying relationships involved are sufficiently complex that it is possible for two apparently identical boilers or furnaces to exhibit completely different rumble tendencies. In this study, we review common sources of rumble and how nonlinear signal analyses, such as bivariate mutual information and transfer entropy, can be used to locate both its sources and impact in boilers, furnaces and heaters.

Flynn, T. J.↗
DOE OSTI2018

Benefits of Higher-Temperature Operation in Boosted SI Engines Enabled by Advanced Materials

To meet the demand for greater fuel efficiency in passenger vehicles, various strategies are employed to increase the power density of light-duty SI engines, with attendant thermal or system efficiency increases. One approach is to incorporate higher-performance alloys for critical engine components. These alloys can have advantageous thermal or mechanical properties at higher temperatures, allowing for components constructed from these materials to meet more severe pressure and temperature demands, while maintaining durability. Advanced alloys could reduce the need for charge enrichment to protect certain gas-path components at high speed and load conditions, permit more selective cooling to reduce heat-transfer losses, and allow engine downsizing, while maintaining performance, by achieving higher cylinder temperatures and pressures. As a first step in investigating downsizing strategies made possible through high-performance alloys, a GT-Power model of a 4-cylinder 1.6L turbocharged direct-injection SI engine was developed. The model was tuned and validated against experimental dynamometer data collected from a corresponding engine. The model was then used to investigate various operating strategies for increasing power density. Results from these investigations will provide valuable insight into how new materials might be utilized to meet the needs of future light-duty engines and will serve as the basis for a more comprehensive investigation using more-detailed thermo-mechanical modeling.

Mills, Zachary↗
DOE OSTI2018

Development of predictive capability of cycle-to-cycle variation in dual-fuel engines using supercomputing-based computational fluid dynamics

Cycle-to-cycle variation (CCV) in internal combustion engines is expected due to variabilities in operating conditions such as in-cylinder fuel stratification, mixing behavior, manifold air pressure, injection timing etc. Generally, engine experimental studies provide averaged quantities such as cylinder pressure, emissions, indicated mean effective pressure (IMEP) from multiple cycles and their CCV of IMEP, and CCV of cylinder pressure from consecutive cycles for a given test condition. Capturing 3D spatial distributions of relevant measures such as fuel-air mixing, temperature, turbulence levels and emissions from such experiments is challenging. Computational Fluid Dynamics (CFD) is an alternative to experiments, that can be used effectively to understand the spatial and temporal distributions of parameters of interest.Quantitative understanding of CCV in dual-fuel (DF) engines will accelerate the development and deployment of engines that provide fuel flexibility, economic advantage and emission compliance. Earlier work [1] performed to develop an understanding of the physics of CCV in large-bore, medium-speed, dual-fuel engines was partially successful. That effort entailed a sparse design of experiment (DOE) of full-cylinder geometry, closed-cycle, dual-fuel CFD simulations in which variabilities within some of the identified global parameters were exercised. The Coefficient of Variation (COV) of cylinder pressure was promising compared with experimental COV. This reinforced the understanding of which global parameters are significant contributors to CCV in DF combustion.The authors have used several high-performance supercomputing facilities in the process of developing predicting capability of CCV in large-bore engines, while operating in dual-fuel, diesel and natural gas (NG), combustion mode [1, 2]. In the current study CCV influencing parameters in a diesel-natural gas dual-fuel engine was studied using a 4th order DOE consisting of 137 concurrent cases. These full-geometry, closed-cycle, CFD simulations were run on the Mira supercomputing facility at the Argonne National Laboratory (ANL). This paper describes key learnings of that study along with a validation of the DOE. Further, the CCV prediction methodology, which is applicable to simulation-based design and testing, is described.

Gubba, Sreenivasa Rao↗
DOE OSTI2018

Neutron Imaging of Advanced Transportation Technologies

Unlike X-rays, neutrons are very sensitive to light elements such as hydrogen (H) atoms and can penetrate through thick layers of metals (Figure 1a). These two properties suggest neutrons are well suited to probe engine parts such as diesel particulate filters, exhaust gas recirculation coolers, fuel injectors, oil in engines, oil residues in filters, batteries, advanced materials, etc. Neutron imaging is based on the interactions of a sample with a neutron beam. The interactions are dependent on sample thickness/density and elemental make-up and result in absorption and scattering of neutrons within the sample. A two-dimensional position-sensitive detector placed behind the sample can measure the transmitted neutron flux (Figure 1b). When combined with a high-precision (~1/100 of a degree) rotational stage, it is possible to perform computed tomography (CT) scans and thus generate 3-dimensional images of working fluids inside real devices. Samples can be analyzed at one position or a complete reconstruction can provide a cross-section of the entire sample at a resolution of the detector; the detector resolution is currently at ~50–80 microns (at the detector).

47 OTHER INSTRUMENTATION↗