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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Suppression of Alfven Modes on the National Spherical Torus Experiment Upgrade with Outboard Beam Injection [Suppression of Alfven Modes on the NSTX-U with Outboard Beam Injection]

In this paper we present data from experiments on the National Spherical Torus Experiment Upgrade, where it is shown for the first time that small amounts of high pitch-angle beam ions can strongly suppress the counterpropagating global Alfven eigenmodes (GAE). GAE have been implicated in the redistribution of fast ions and modification of the electron power balance in previous experiments on NSTX. The ability to predict the stability of Alfven modes, and developing methods to control them, is important for fusion reactors like the International Tokamak Experimental Reactor, which are heated by a large population of nonthermal, super-Alfvenic ions consisting of fusion generated alpha's and beam ions injected for current profile control. We present a qualitative interpretation of these observations using an analytic model of the Doppler-shifted ion-cyclotron resonance drive responsible for GAE instability which has an important dependence on k(perpendicular to rho L). A quantitative analysis of this data with the HYM stability code predicts both the frequencies and instability of the GAE prior to, and suppression of the GAE after the injection of high pitch-angle beam ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Identification of Intraday False Data Injection Attack on DER Dispatch Signals

The urgent need for the decarbonization of power grids has accelerated the integration of renewable energy. Concurrently, increasing distributed energy resources (DER) and advanced metering infrastructure (AMI) have transformed the power grids into a more sophisticated cyber-physical system with numerous communication devices. While these transitions provide economic and environmental value, they also impose increased risk of cyber attacks and operation al challenges. This paper investigates the vulnerabilit y of the power grids with high renewable penetration against an intraday false data injection (FDI) attack on DER dispatch signals and proposes a kernel support vector regression (SVR) based detection model as a countermeasure. The intraday FDI attack scenario and the detection model are demonstrated in a numerical experiment using the HCE 187-bus test system.

Kim, Jip↗
DOE OSTI2021

Performance of direct injected propane and gasoline in a high stroke-to-bore ratio SI engine: Pathways to diesel efficiency parity with ultra low soot

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible combustion in a single-cylinder spark ignition (SI) research engine. A unique high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio ( r c ) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. Engine experiments were conducted with both 91 RON E10 gasoline and liquified petroleum gas (LPG) (i.e. autogas) and were compared to legacy gasoline data on the production engine. Geometric compression ratio ( r c ) of 13.3:1 was used for both fuels with additional experiments at 16.8:1 for LPG only. Measurements of exhaust soot particle size and number concentrations were made with both fuels. Significant reduction in soot particles across the whole particle size range were achieved with LPG due to the elimination of in-cylinder liquid films. The effects of EGR, late intake valve closing (IVC) and fuel characteristics were investigated through their effects on efficiency, combustion stability and soot production. Results of 47% gross thermal efficiency, and 45% net thermal efficiency at stoichiometric engine operation, at up to 17 bar IMEP and 2000 r/min with 16.8:1 r c were achieved with LPG. Estimated brake efficiency values were compared to a contemporary medium duty diesel engine illustrating the benefits of the chosen path for achieving diesel efficiency parity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Intermediate Scale Laboratory Testing to Understand Mechanisms of Capillary and Dissolution Trapping during Injection and Post-Injection of CO 2 in Heterogeneous Geological Formations

Carbon Capture and Storage (CCS) represents a technology aimed to reduce atmospheric loading of CO 2 from power plants and heavy industries by injecting it into deep geological formations, such as saline aquifers. A number of trapping mechanisms contribute to effective and secure storage of the injected CO 2 in supercritical fluid phase (scCO 2 ) in the formation over the long term. The primary trapping mechanisms are structural, residual, dissolution and mineralization. Knowledge gaps exist on how the heterogeneity of the formation manifested at all scales from the pore to the site scales affects trapping and parameterization of contributing mechanisms in models. An experimental and modeling study was conducted to fill these knowledge gaps. Experimental investigation of fundamental processes and mechanisms in field settings is not possible as it is not feasible to fully characterize the geologic heterogeneity at all relevant scales and gathering data on migration, trapping and dissolution of scCO 2 . Laboratory experiments using scCO 2 under ambient conditions are also not feasible as it is technically challenging and cost prohibitive to develop large, two- or three-dimensional test systems with controlled high pressures to keep the scCO 2 as a liquid. Hence, an innovative approach that used surrogate fluids in place of scCO 2 and formation brine in multi-scale, synthetic aquifers test systems ranging in scales from centimeter to meter scale developed used. New modeling algorithms were developed to capture the processes controlled by the formation heterogeneity, and they were tested using the data from the laboratory test systems. The results and findings are expected to contribute toward better conceptual models, future improvements to DOE numerical codes, more accurate assessment of storage capacities, and optimized placement strategies. This report presents the experimental and modeling methods and research results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Protection Against Graph-Based False Data Injection Attacks on Power Systems

Graph signal processing (GSP) has emerged as a powerful tool for practical network applications, including power system monitoring. By representing power system voltages as smooth graph signals, recent research has focused on developing GSP-based methods for state estimation, attack detection, and topology identification. Included, efficient methods have been developed for detecting false data injection (FDI) attacks, which until now were perceived as non-smooth with respect to the graph Laplacian matrix. Consequently, these methods may not be effective against smooth FDI attacks. In this paper, we propose a graph FDI (GFDI) attack that minimizes the Laplacian-based graph total variation (TV) under practical constraints. In addition, we develop a low-complexity algorithm that solves the non-convex GDFI attack optimization problem using ell_1-norm relaxation, the projected gradient descent (PGD) algorithm, and the alternating direction method of multipliers (ADMM). We then propose a protection scheme that identifies the minimal set of measurements necessary to constrain the GFDI output to high graph TV, thereby enabling its detection by existing GSP-based detectors. Our numerical simulations on the IEEE-57 bus test case reveal the potential threat posed by well-designed GSP-based FDI attacks. Moreover, we demonstrate that integrating the proposed protection design with GSP-based detection can lead to significant hardware cost savings compared to previous designs of protection methods against FDI attacks.

Morgenstern, Gal↗
DOE OSTI2016

Influence of asymmetric injection of laser radiation into capillary waveguides on wake acceleration of electrons possessing various injection energies

Laser wakefield acceleration of electron bunches possessing various initial injection energies in capillary waveguides is studied in the conditions of an asymmetric input of laser radiation into a waveguide (the propagation direction of laser radiation deviates from the capillary axis or the laser spot is not symmetric). The factors determining the critical angle of the laser radiation input into the capillary, within which the wake acceleration of electrons is close to optimal, have been found. It is shown that in acceleration stages where electron energies are high, the requirements to angular concentricity of the capillary axis and laser radiation focusing are substantially weaker due to the relativistic 'weighting' of the electron mass. (extreme laser radiation: physics and fundamental applications)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗
DOE OSTI2023

Resolving Electron Injection from Singlet Fission-Borne Triplets into Mesoporous Transparent Conducting Oxides

Photoinduced electron transfer from a molecular chromophore into mesoporous metal oxide substrates occurs efficiently from both singlet and triplet excited states for traditional metal-to-ligand charge transfer (MLCT) dyes. All organic molecules that undergo singlet fission (SF), the process of generating two triplet excitons with photoexcitation of one singlet exciton, offers a promising method of generating two charges per one absorbed photon. However, the singlet-triplet energy balance required to drive SF often places the driving force for triplet electron injection into metal oxides too low. As such, the dynamics of singlet vs. triplet electron transfer for SF in dye-sensitized solar cell configurations has not been elucidated. Here, we use applied bias transient absorption spectroscopy to modulate the driving force for triplet electron transfer from an anthradithiophene-based SF chromophore (ADT-COOH) adsorbed to mesoporous indium tin oxide (nanoITO).

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗
DOE OSTI2020

Ducted Fuel Injection vs. Free-Spray Injection: A Study of Mixing and Entrainment Effects Using Numerical Modeling

Diesel engines are an important technology for transportation of both people and goods. However, historically they have suffered a significant downside of high soot and nitrogen oxides (NO x ) emissions. Recently, ducted fuel injection (DFI) has been demonstrated to attenuate soot formation in compression-ignition engines and combustion vessels by 50% to 100%. This allows for diesel engines to be run at low-NO x emissions that would have otherwise produced significantly more soot due to the soot/NO x tradeoff. Currently the root causes of this soot attenuation are not well understood. To be able to better optimize DFI for use across a variety of engines and conditions, it is important to understand clearly how it works. This study expands on the current understanding of DFI by using numerical modeling under nonreacting conditions to provide insights about the roles of entrainment and mixing that would have been much more challenging to obtain experimentally. We report this study found that DFI enhances charge gas entrainment upstream of the duct and blocks entrainment inside of the duct. Mixing is enhanced by the duct, which results in lower peak equivalence ratios at the exit of the duct.

42 ENGINEERING↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗