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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CFD unified approach under Eulerian–Lagrangian framework for methanol and gasoline direct injection sprays in evaporative and flash boiling conditions

Innovative synthetic fuels for advanced propulsion systems, such as methanol and ammonia, and synthetic blended fuels (E00, E10, and E30), known for their high volatility, are often injected directly into combustion chambers. It follows that Eulerian–Lagrangian spray models need to accurately capture the spray collapse as a consequence of flash boiling onset and be capable of proficiently handling the preferential evaporation of multi-component fuels in evaporative scenarios. So, we performed the assessment of an Eulerian–Lagrangian CFD code for simulating methanol and E00 gasoline blend sprays in both early and late injection conditions involving flash boiling conditions and preferential evaporation. The adoption of an effervescent breakup model and of a non-equilibrium phase transition model for the discrete phase allows the adoption of a setup that is almost completely free from specific constant tuning, especially for what concerns the breakup model. We validated the simulations using experimental PLV maps of methanol and E00 sprays issued from the ECN Spray M injector. The results highlight a significantly different morphology of the methanol spray compared to the E00 one under late injection conditions. Under stratified combustion, low-volatile fuels are likely to be ignited first, and the flame propagates toward the high-volatile fuels. In conclusion, the spray collapse was also correctly reproduced, inducing the presence of a low-pressure zone and modifying the spray morphology.

E00↗
DOE OSTI2024

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

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

diffused-interface method↗
DOE OSTI2024

Dynamic modeling studies of basin-scale pressure interference and CO 2 plume evolution in multi-well geologic CO 2 storage

This research employs numerical modeling to analyze how CO 2 plumes and pressure fronts evolve when CO 2 is injected into a single storage formation from multiple projects located in proximity. Here, this analysis also evaluates the extent to which injection well spacing alleviates pressure buildup in the absence of active pressure management tactics. The simulation approach was based on a single, homogenous saline aquifer in which CO 2 injection occurs under a one-injector baseline case and several multi-well cases where well spacing varies. Analysis results show that the extent of pressure buildup is in the range of tens or a few hundreds of kilometers and contingent upon the defining pressure buildup demarcating the front edge. For the geological setting evaluated in this paper, our analysis suggests that without active basin pressure management strategies, commercial-scale projects would likely need to be sited far apart to avoid pressure interference from one another. Analysis results show the radius of CO 2 plume varies approximately from 2 to 3 km from injection wells (each injecting 1 Mt/year for 30 years) depending on cases and modeling parameters assumed. Given the pressure interference, this paper thus draws attention to the importance of greater coordination among storage operators and regulatory stakeholders. Because this analysis assumes a very specific geologic setting, this exploratory analysis bears further investigations across other geologic scenarios.

42 ENGINEERING↗
DOE OSTI2024

Numerical modeling of impurity powder injection in W7-X

In this work, we present numerical simulation results of powder injection in W7-X using the EMC3-EIRENE and DIS codes. First, we model powder injection experiments performed in W7-X with the Probe Mounted Powder Injector. The simulation results qualitatively agree with visible imaging measurements. Secondly, we perform predictive simulations to guide the installation of an Impurity Powder Dropper in W7-X, allowing to choose in between several available non-vertical ports to maximize the amount of powder penetrating into the plasma, as well as the verticality of the port, to minimize sticking of the powders in the in-vessel stainless steel guiding tube. Port AEM41 is selected as the best candidate for IPD installation. The robustness of the simulation results has been verified for different plasma densities, powder materials and sizes, powder friction coefficient and changes in the plasma flow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗
DOE OSTI2020

Liquid-phase turbulence measurements in air-water two-phase flows using particle image velocimetry

Liquid-phase turbulence plays a vital role in determining various gas-liquid two-phase flow parameters, such as void fraction distribution, bubble morphology, bubble-bubble interactions, and interfacial area concentration. In this study, a two-phase flow database including both the gas- and liquid-phases measurements was developed focusing on three bubbly flow conditions in an air-water two-phase flow loop with a vertical one-inch diameter circular pipe test section. A particle image velocimetry (PIV) system integrating an optical phase separation method, i.e., the planar laser-induced fluorescence (PLIF) technique using fluorescent particles and optical filtration, was applied to measure the liquid-phase turbulence information, including the time-averaged velocity, Reynolds stress, and turbulent kinetic energy for the liquid phase. The PIV measurements were taken at three ports along the test section at 14.5, 51.5, and 88.5 pipe inner diameters downstream of a bubble injector. In addition, a double-sensor conductivity probe was used to measure radial distributions of the local time-averaged void fraction and gas velocity. The measured liquid-phase turbulence was used to benchmark Sato's turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. Lastly, in the two bubbly flows tested that have low void fractions being less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction.

42 ENGINEERING↗
DOE OSTI2021

CFD investigation of low-attrition air-reactor designs for the NETL chemical-looping combustion reactor

The flow dynamics and attrition characteristics of three air reactor designs are investigated using an Eulerian-Eulerian kinetic theory model. The hydrodynamics of these reactor designs are analyzed to identify the flow regimes in which the particles evolve. The investigated designs which differ in the configuration of the secondary flow ports, exhibit bubbling and turbulent fluidization regimes within similar spatial regions. The most substantial differences in the hydrodynamics was in the turbulent fluidized regions near the secondary inlets. The mechanical stressing environments undergone by the particles were analyzed using the collision energy spectra, reconstructed using the local flow field properties (i.e. granular temperature and particle number density). The spectra show that the increase in the specific collision power is associated with the regions near the secondary injector ports, which are in a turbulent fluidization regime. A simple analysis relying upon a partitioning of the energy spectrum, showed that attrition rate may be reduced by about 34% over the original design.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

The role of cool-flame fluctuations in high-pressure spray flames, studied using high-speed optical diagnostics and Large-Eddy Simulations

Here this work investigates the low- and high-temperature ignition and combustion processes, applied to the Engine Combustion Network Spray A flame, combining advanced optical diagnostics and large-eddy simulations (LES). Simultaneous high-speed (50 kHz) formaldehyde (CH 2 0) planar laser-induced fluorescence (PLIF) and line-of-sight OH* chemiluminescence imaging were used to measure the low- and high-temperature flame, during ignition as well as during quasi-steady combustion. While tracking the cool flame at the laser sheet plane, the present experimental setup allows detection of distinct ignition spots and dynamic fluctuations of the lift-off length over time, which overcomes limitations for flame tracking when using schlieren imaging. After significant development to improve LES prediction of the low-and high-temperature flame position, both during the ignition processes and quasi-steady combustion, the simulations were analyzed to gain understanding of the mixture variance and how this variance affects formation/consumption of CH 2 0. Analysis of the high-temperature ignition period shows that a key improvement in the LES is the ability to predict heterogeneous ignition sites, not only in the head of the jet, but in shear layers at the jet edge close to the position where flame lift-off eventually stabilizes. The LES analysis also shows concentrated pockets of CH 2 0, in the center of jet and at 20 mm downstream of the injector (in regions where the equivalence ratio is greater than 6), that are of similar length scale and frequency as the experiment (approximately 5–6 kHz). The periodic oscillation of CH 2 0 match the frequency of pressure waves generated during auto-ignition and reflected within the constant-volume vessel throughout injection. The ability of LES to capture the periodic appearance and destruction of CH 2 0 is particularly important because these structures travel downstream and become rich premixed flames that affect soot production.

42 ENGINEERING↗
DOE OSTI2026

Flame stabilization in DME spray flames under engine-relevant conditions characterized by OH* chemiluminescence and formaldehyde laser-induced fluorescence

The transient and quasi-steady flame structures of Dimethyl Ether (DME) fuel sprays, produced by a single-hole injector (Spray D), were investigated using Planar Laser-Induced Fluorescence (PLIF) and chemiluminescence imaging in a constant-volume chamber under Engine Combustion Network (ECN) Spray A conditions (900 K ambient temperature, 60 bar ambient pressure, 1500 bar injection pressure, and 22.8 kg/m 3 ambient density). Low-temperature chemical reaction zones were visualized using formaldehyde (CH 2 O) PLIF with 355 nm excitation, while high-temperature flame regions were captured via chemiluminescence imaging of excited-state hydroxyl radicals (OH*). Both transient and quasi-steady flame structures clearly show the transition from CH 2 O to OH*, highlighting the progression from low- to high-temperature combustion, while the position of the flame is displaced for DME compared to reference hydrocarbon n-dodecane. Homogeneous reactor calculations with detailed chemistry and using adiabatic mixing for initial temperature show that CH 2 O peaks are significantly higher for DME at the same equivalence ratio, with a higher heat-release during the cool-flame regime with respect to the fuel heating value. Thus, the cool-flame dynamic as a precursor to high-temperature combustion and flame stabilization exhibit distinct behavior for DME relative to conventional hydrocarbons, and these phenomena are effectively resolved through the soot-free nature of DME and the high-speed, time-resolved diagnostics.

CH2O laser-induced fluorescence↗
DOE OSTI2021

Potential Link Between 2020 Mentone, West Texas M5 Earthquake and Nearby Wastewater Injection: Implications for Aquifer Mechanical Properties

Abstract The M5 Mentone earthquake that occurred on March 26, 2020, was the largest event recorded over the last 2 decades in West Texas within the Delaware Basin, a U.S. major petroleum‐producing area. Also, numerous hydrofracturing and wastewater disposal wells are spread across this region. Within a 30 km distance to mainshock, eight class‐II injection wells for industrial wastewater disposal target the deep porous Ellenburger aquifer at an average rate of 1.36 × 10 6 barrel (BBL) per month during 2012–2020. Poroelastic models of fluid diffusion show these nearby injectors collectively imparted up to 80.5 kPa of Coulomb stress at the mainshock location, capable of triggering this M5 event. Assuming the Mentone event occurs when pore‐pressure increase is maximum, the time delay between peak injection and the M5 occurrence corresponds with an optimal permeability of 6.76 × 10 ‐14 m 2 for the Ellenburger aquifer layer, in agreement with independent estimates.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Pore Pressure Diffusion and Onset of Induced Seismicity

The Raton Basin of Southern Colorado and Northern New Mexico experienced a significant increase in seismicity over the last several decades, including two M5+ earthquakes. The increase in seismicity started soon after an increase in wastewater disposal associated with coal-bed methane production. Twenty-nine wastewater injection wells have operated in the Basin, with several high-rate injectors located within a kilometer of the most seismically active regions. We developed a pore pressure model to investigate the relationship between pore pressure diffusion and onset of induced seismicity, with an emphasis on the Trinidad fault zones. Our model indicates that sufficient pore pressure increase had accumulated on the northern extent of the Trinidad fault zone to induce seismicity at the time of early-stage seismic activity. The hydrogeologic architecture of the Basin played a key role in controlling pore pressure perturbation. The basal sedimentary interval with moderately low diffusivity restricted vertical pore pressure diffusion, creating a substantial lag time between wells becoming active and the expression of perturbation in the fault zones. The spatiotemporal relationship between early-stage seismicity and wastewater injection in conjunction with modeled pore pressures suggests that the early-stage seismicity in the Raton Basin was likely triggered by pore pressure diffusion.

58 GEOSCIENCES↗
DOE OSTI2020

Small-wedge synchrotron and serial XFEL datasets for Cysteinyl leukotriene GPCRs

Structural studies of challenging targets such as G protein-coupled receptors (GPCRs) have accelerated during the last several years due to the development of new approaches, including small-wedge and serial crystallography. Here, we describe the deposition of seven datasets consisting of X-ray diffraction images acquired from lipidic cubic phase (LCP) grown microcrystals of two human GPCRs, Cysteinyl leukotriene receptors 1 and 2 (CysLT 1 R and CysLT 2 R), in complex with various antagonists. Five datasets were collected using small-wedge synchrotron crystallography (SWSX) at the European Synchrotron Radiation Facility with multiple crystals under cryo-conditions. Two datasets were collected using X-ray free electron laser (XFEL) serial femtosecond crystallography (SFX) at the Linac Coherent Light Source, with microcrystals delivered at room temperature into the beam within LCP matrix by a viscous media microextrusion injector. All seven datasets have been deposited in the open-access databases Zenodo and CXIDB. Here, we describe sample preparation and annotate crystallization conditions for each partial and full datasets. We also document full processing pipelines and provide wrapper scripts for SWSX and SFX data processing. A Correction to this paper has been published: https://doi.org/10.1038/s41597-020-00759-w

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Demonstration of an intense lithium beam for forward-directed pulsed neutron generation

Abstract As an alternative to research nuclear reactors, a compact accelerator-driven neutron generator that uses a lithium beam driver could be a promising candidate since it produces almost no undesired radiation. However, providing an intense lithium-ion beam has been difficult, and it has been thought that the practical application of such a device would be impossible. The most critical problem of insufficient ion fluxes has been solved by applying a direct plasma injection scheme. In this scheme, a pulsed high-density plasma from a metallic lithium foil generated by laser ablation is efficiently injected and accelerated by a radio-frequency quadrupole linear accelerator (RFQ linac). We have obtained a peak beam current of 35 mA accelerated to 1.43 MeV, which is two orders of magnitude higher than a conventional injector and accelerator system can deliver.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Leveraging prior mean models for faster Bayesian optimization of particle accelerators

Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. One of the major advantages of Bayesian algorithms is the ability to incorporate prior information about beam physics and historical behavior into the model used to make control decisions. In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. We show that in ideal cases, this technique substantially increases convergence speed to optimal solutions in high-dimensional tuning parameter spaces. Additionally, we demonstrate that even in non-ideal cases, where prior models of beam dynamics do not exactly match experimental conditions, the use of this technique can still enhance convergence speed. Finally, we demonstrate how these methods can be used to improve optimization in practical applications, such as transferring information gained from beam dynamics simulations to online control of the LCLS injector, and transferring knowledge gained from experimental measurements across different operating modes, such as accelerating different ion species at the ATLAS heavy ion accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Plug-and-play polymer microfluidic chips for hydrated, room temperature, fixed-target serial crystallography

The practice of serial X-ray crystallography (SX) depends on efficient, continuous delivery of hydrated protein crystals while minimizing background scattering. Of the two major types of sample delivery devices, fixed-target devices offer several advantages over widely adopted jet injectors, including: lower sample consumption, clog-free delivery, and the ability to control on-chip crystal density to improve hit rates. In this study we present our development of versatile, inexpensive, and robust polymer microfluidic chips for routine and reliable room temperature serial measurements at both synchrotrons and X-ray free electron lasers (XFELs). Our design includes highly X-ray-transparent enclosing thin film layers tuned to minimize scatter background, adaptable sample flow layers tuned to match crystal size, and a large sample area compatible with both raster scanning and rotation based serial data collection. The optically transparent chips can be used both for in situ protein crystallization (to eliminate crystal handling) or crystal slurry loading, with prepared samples stable for weeks in a humidified environment and for several hours in ambient conditions. Serial oscillation crystallography, using a multi-crystal rotational data collection approach, at a microfocus synchrotron beamline (SSRL, beamline 12-1) was used to benchmark the performance of the chips. Furthermore, high-resolution structures (1.3–2.7 Å) were collected from five different proteins – hen egg white lysozyme, thaumatin, bovine liver catalase, concanavalin-A (type VI), and SARS-CoV-2 nonstructural protein NSP5. Overall, our modular fabrication approach enables precise control over the cross-section of materials in the X-ray beam path and facilitates chip adaption to different sample and beamline requirements for user-friendly, straightforward diffraction measurements at room temperature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Upgrading the LANSCE accelerator with a SNS RF-driven H− ion source

The LANSCE accelerator is currently powered by a filament-driven, biased converter-type H− ion source that operates at 10%, the highest plasma duty factor for this type of source, using only ∼2.2 SCCM of H2. The ion source needs to be replaced every 4 weeks, which takes up to 4 days. The measured negative beam current of 12–16 mA falls below the desired 24 mA acceptance of the LANCSE accelerator. The SNS (Spallation Neutron Source) RF-driven, H− ion source injects ∼50 mA of H− beam into the SNS accelerator at 60 Hz with a 6% duty factor and an availability of >99.5% but requires ∼30 SCCM of H2. Up to 7 A h of H− have been produced during the 14-weeks-long source service cycles, which is unprecedented for small emittance, high-current, pulsed H− ion sources. The emittance of the SNS source is slightly smaller than the emittance of the LANSCE source. The SNS source also features unrivaled low Cs consumption and can be installed and started up in <12 h. LANSCE and SNS are working toward the use of SNS H− ion sources on the LANSCE accelerator because they could (a) fill the LANSCE accelerator to its capacity, (b) decrease the source replacement time by a factor of up to 7, and (c) increase source lifetime by a factor of about 4. This paper discusses some of the challenges that emerge when trying to match a different H− source into an existing injector with significantly different characteristics and operating regimes.

Stockli, Martin P.↗
DOE OSTI2020

Characterizing magnetized plasmas with dynamic mode decomposition

Accurate and efficient plasma models are essential to understand and control experimental devices. Existing magnetohydrodynamic or kinetic models are nonlinear and computationally intensive and can be difficult to interpret, while often only approximating the true dynamics. In this work, data-driven techniques recently developed in the field of fluid dynamics are leveraged to develop interpretable reduced-order models of plasmas that strike a balance between accuracy and efficiency. In particular, dynamic mode decomposition (DMD) is used to extract spatio-temporal magnetic coherent structures from the experimental and simulation datasets of the helicity injected torus with steady inductive (HIT-SI) experiment. Three-dimensional magnetic surface probes from the HIT-SI experiment are analyzed, along with companion simulations with synthetic internal magnetic probes. A number of leading variants of the DMD algorithm are compared, including the sparsity-promoting and optimized DMD. Optimized DMD results in the highest overall prediction accuracy, while sparsity-promoting DMD yields physically interpretable models that avoid overfitting. These DMD algorithms uncover several coherent magnetic modes that provide new physical insights into the inner plasma structure. These modes were subsequently used to discover a previously unobserved three-dimensional structure in the simulation, rotating at the second injector harmonic. Finally, using data from probes at experimentally accessible locations, DMD identifies a resistive kink mode, a ubiquitous instability seen in magnetized plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗