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At least 649 records · Page 36

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Machine Governor

This paper introduces the development of a high-fidelity gas turbine governor model using a programmable logic controller for power-hardware-in-the-loop (PHIL) validation. The governor model is integrated with the National Renewable Energy Laboratory's (NREL) PHIL test bed, featuring a 2-MVA synchronous machine and a 2.5-MW variable-speed drive, to emulate NG-driven HRSGs and CTs under various operational scenarios. The primary objective of this research is to study the grid-connected and islanding operations of conventional generation sources, with representative startup sequences including turbine purge, ignition, speed ramp-up, synchronization, and breaker closure. Preliminary results of the generator governor model on NREL PHIL platform, particularly using the 2.5-MW dynamometer system, offered significant insights into the modeling techniques, hardware integration, scaling, and real-world simulation dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Finite Element Modeling of the Phase Change in Thermally-Grown SiO 2 in SiC Systems for Gas Turbines

The operating lifetimes of SiC-based components in combustion environments are directly linked to the adhesion of the protective environmental barrier coating (EBC) layer. One of the major known failure modes for EBCs is the formation of a thick SiO 2 thermally grown oxide (TGO), which decreases coating adhesion and encourages eventual coating spallation. The effect of the TGO thickness under Yb 2 Si 2 O 7 EBCs on silicon carbide was investigated using finite element models (FEMs) with various interfacial architectures and SiO 2 TGO thicknesses. Further, the FEMs incorporated a user-defined material to simulate the volume contraction of the TGO during the silica phase transformation from β-cristobalite to α-cristobalite upon cooling from the stress-free state at 1350°C to room temperature. Systems with and without a silicon bond coating intermediary layer were assessed. It was shown that the TGO phase transformation stress (1.6–1.7 GPa) dominated the increase in stress in the TGO and EBC layers. Furthermore, it was found that stress increase in the TGO was independent of TGO thickness and interface geometry. These results indicate that stabilization of the TGO to mitigate the phase transformation could dramatically improve the performance of SiC-base components with EBCs.

36 MATERIALS SCIENCE↗

Acclimation of Phytoplankton Fe:C Ratios Dampens the Biogeochemical Response to Varying Atmospheric Deposition of Soluble Iron

Abstract Dissolved iron (dFe) plays an important role in regulating marine productivity. In high nutrient, low chlorophyll regions (>33% of the global ocean), iron is the primary growth limiting nutrient, and elsewhere iron can regulate nitrogen fixation by diazotrophs. The link between iron availability and carbon export is strongly dependent on the phytoplankton iron quotas or cellular Fe:C ratios. This ratio varies by more than an order of magnitude in the open ocean and is positively correlated with ambient dFe concentrations in field observations. Representing Fe:C ratios within models is necessary to investigate how ocean carbon cycling will interact with perturbations to iron cycling in a changing climate. The Community Earth System Model ocean component was modified to simulate dynamic, group‐specific, phytoplankton Fe:C that varies as a function of ambient iron concentration. The simulated Fe:C ratios improve the representation of the spatial trends in the observed Fe:C ratios. The acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition of soluble iron, compared to a fixed Fe:C ratio. However, varying atmospheric soluble iron supply has first order impacts on global carbon and nitrogen fluxes and on nutrient limitation spatial patterns. Our results suggest that pyrogenic Fe is a significant dFe source that rivals mineral dust inputs in some regions. Changes in dust flux and iron combustion sources (anthropogenic and wildfires) will modify atmospheric Fe inputs in the future. Accounting for dynamic phytoplankton iron quotas is critical for understanding ocean biogeochemistry and projecting its response to variations in atmospheric deposition.

Environmental Sciences & Ecology↗

Development of Hydrogen-Fueled, Highly Energy-Efficient, Electro-Hydraulic Excavator

Regulations for CO2 emissions reduction are driving increasing demand for “zero emissions” off-road vehicles (ORVs). Hydrogen internal combustion engines (H2 ICEs) are closer to commercial viability, and less expensive than fuel cells. The major challenge is the slow torque response of H2 ICEs, that makes it difficult to sustain the harsh torque requirements typical of ORVs. The goal of this paper is to overcome this challenge by proposing an electro-hydraulic hybrid technology with hybrid powertrain and multi-pressure rail technology as fluid power system for an excavator, to enable the use of the H2 ICE, while improving efficiency. The study is based on simulation in MATLAB/Simulink environment, using duty cycle data from a 24-ton excavator. Simulation results show that in respect to the diesel-powered baseline, the proposed electro-hydraulic hybrid allows the use of a H2 ICE, eliminates CO2 emissions and ensures a 52% fuel consumption reduction.

08 HYDROGEN↗

A scalable compressible volume of fluid solver using a stratified flow model

Here, in this paper, a Volume of Fluid method which uses a Stratified Flow model for flux calculation is proposed to solve a compressible multiphase flow in a way that has high parallel efficiency. The solver is part of an open-source computing tool to study fuel entrainment and combustion in the application of paraffin-based hybrid rocket motors. This paper focuses on the compressible Volume of Fluid solver for the liquid and gaseous phases in this environment. This solver uses perfect gas and stiffened gas models for equation of state, with the ability to easily add other models as desired. Additionally a comparison of a Riemann solver versus an AUSM+up scheme is conducted, showing improvement with the later in the solution of multiphase flows. This solver successfully reproduces shock tube cases with the expected accuracy, as well as simulating two-dimensional shear and gravity-driven flows. Results also show that the code is able to utilize a Stratified Flow model to evaluate shear flow without the need for interface reconstruction or gradient calculations. Finally, it is shown that the solver has near-ideal scaling under strong scaling tests as well as good performance in static scaling, giving improved performance over current options and implying future advancement of high-performance computing efficiency for multiphase flow solvers.

97 MATHEMATICS AND COMPUTING↗

Analysis of soot formation from aviation fuels in laminar counterflow flames

Combustion emissions from aviation contribute to the formation of condensation trail (contrail) that can lead to the formation of anthropogenic cirrus clouds. Ice particles that form contrails are observed to have a linear correlation with soot particle number density. Synthetic aviation fuels (SAFs) offer a promising route to mitigate the production of soot particles while also increasing energy security. Although studies have focused on combustion and spray behavior, the detailed investigation of soot formation processes for different jet fuels and their impact on models for computational fluid dynamics (CFD) applications is not well understood. Moreover, experimental measurements of soot for canonical flames using Synthetic aviation fuels (SAF) for model validation remain scarce. To address this, we use employed the Lawrence Livermore National Laboratory (LLNL) detailed soot model based on the discrete sectional method. Additionally, we develop two reduced chemical mechanisms for Jet-A and Alcohol-to-Jet (C1) that are suitable for turbulent flame simulations and couple them with the Hybrid Method of Moments (HMOM). The detailed and reduced model frameworks are validated against experimental measurements of soot volume fraction (ƒ ν ) from a counterflow burner experiment previously reported in the literature. Given the good agreement between modeling results and experimental measurements for the (1) spatial distribution of ƒ ν and (2) the non-linear variation of peak ƒ ν with strain rate, we further investigate the modeled sub-processes (nucleation, condensation, surface growth, and oxidation) using the LLNL model to analyze the assumptions in the reduced model framework. Furthermore, the results indicate a significant contribution from resonant radicals to the surface growth of soot particles, which are not accounted for in the current implementation of HMOM and could help reconcile soot predictions by the reduced model with observations.

Counterflow↗

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗

Roles of kaolinite-oil-gas molecular interactions in hydrogen storage within depleted reservoirs

Hydrogen is a clean alternative to fossil fuels, emitting only water vapor during combustion. In a future hydrogen economy, large-scale storage will be an important component of the supply chain. Due to its low volumetric density, conventional surface storage methods are inadequate. Underground hydrogen storage (UHS) offers a viable solution, enabling the storage of millions of cubic meters. Among potential geological sites, including salt caverns, aquifers, and depleted gas reservoirs, depleted oil reservoirs show promise. Studying hydrogen interactions with residual oil and reservoir minerals is vital for understanding the properties of hydrogen and the reservoir post-injection. In this work, we employed molecular dynamics simulations to gain molecular-level insights into these interactions. We investigated hydrogen dissolution in oil, adsorption at kaolinite/oil interfaces, the role of CO 2 as a cushion gas, and the influence of kaolinite’s hydrophobicity on H 2 behavior. The main findings include: (1) hydrogen dissolves more in oil than in water, (2) the introduction of CO 2 suppresses hydrogen dissolution in oil and reduces the interfacial tension (IFT) between oil and gas, (3) CO 2 decreases H 2 partitioning near kaolinite surfaces due to its strong affinity for the hydrophilic gibbsite surface of kaolinite, and (4) CO 2 is more effective than H 2 in reducing IFT between kaolinite and the oil–gas mixture. These findings emphasize the effectiveness of CO 2 as a cushion gas and the important role of clay hydrophobicity in UHS, providing insights that are challenging to obtain experimentally.

08 HYDROGEN↗

Differentiation of static and dynamic interfacial area in the structured packed column

Effective mass-transfer area plays a key role for post-combustion carbon capture. The static area, an inactive part relative to mass transfer, needs to be differentiated in the interfacial area. In the present study, CFD method is employed to investigate static and dynamic interfacial areas in Mellapak 500.Y structured packing. Here, a wide range of physical properties and loading conditions are included to understand their effects on both areas. The result shows that the relationship between interfacial area and interfacial velocity at the local scale can be described by gamma distribution with good accuracy. The influences of various physical properties derived from simulation are compared with existing experiment-based correlations for both static and interfacial areas. The result shows the dominant influence of viscosity on the static area, and the most importance of the influence of contact angle on the interfacial area. This study also highlights the importance of viscosity, which is usually ignored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gaseous jet through an outward opening injector: Details of mixing characteristic and turbulence scales

Direct injection (DI) strategy of natural gas (NG) into internal combustion engines (ICE) has led to higher thermal efficiency and lower exhaust emissions. In order to thoroughly understand the most relevant phenomena affecting the performances of such engines, computational fluid dynamics (CFD) plays a key role as an accurate description of the jet evolution and interaction within the combustion chamber is required to that aim. Accurate description of high-pressure gaseous jets is rather challenging at high Mach numbers, as the injected gas is strongly under-expanded once in the ambient, giving room to shocks due to compressibility effects. Also the interaction between shock waves and mixing layers needs to be carefully represented with a multi-dimensional model, calling for substantial computational resources requirements. In this paper a numerical investigation of the behavior of a gaseous jet (Argon) through an outward opening injector has been carried out. A Large Eddy Simulation (LES) approach has been used in order to track the structures derived by the interaction of the injected fuel with the surrounding ambient. Although already good results were obtained using a Reynolds Averaged Navier-Stokes (RANS) approach, the adoption of LES is required to characterize more accurately the jet properties in terms of vortex structures and mixing effectiveness. Finally, the effect of the Nozzle Pressure Ratio (NPR) on the jet evolution has been highlighted in the paper, showing how a higher NPR would give a faster injection process, compromising however the homogeneity of the mixture.

33 ADVANCED PROPULSION SYSTEMS↗

Reconciliation of asynchronous satellite-based $\mathrm{NO_2}$ and $\mathrm{XCO_2}$ enhancements with mesoscale modeling over two urban landscapes

Fossil fuel carbon dioxide (CO 2ff ), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x ) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff . Because of NO 2 ’s shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2 ) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i.e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and > 10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff . Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

54 ENVIRONMENTAL SCIENCES↗

Size Up or Size Down? National Analysis of Heat Pump Sizing and Impacts

Electrification of on-site fossil fuel combustion in buildings is recognized as a key component of achieving global greenhouse gas emissions targets. Air-source heat pumps are an efficient approach for space heating electrification. However, a major barrier to heat pump adoption is the high installation cost relative to furnaces and air conditioners. Because the installation cost of heat pumps - especially cold climate models - is dependent on their size, it is important to understand the distribution of heat pump sizes using different sizing methods and factors that impact heat pump sizing. In this study, we use sub-hourly physics simulations of 550,000 statistically representative dwelling units to analyze the distribution of heat pump size in the U.S. for three different efficiency levels of heat pumps, with and without building insulation and air sealing upgrades. We will present results from the national analysis of different factors affecting heat pump sizing along with the impact of sizing decisions on upgrade costs and operating costs.

electrification↗

Multi-modal effects on indirect noise induced by turbulent entropy fields

Planar entropy waves are commonly assumed for predicting indirect combustion noise. However, the non-planar and turbulent nature of flows found in most practical combustors challenges this assumption. In the present paper, we examine the indirect noise generated by non-planar and turbulent entropy fields through subsonic nozzles. Firstly, we introduce a new transfer function framework that accounts for the contribution of non-planar Fourier modes of the entropy field to the indirect noise spectra. When applied to a turbulent flow field, this method demonstrates a significant improvement in spectral predictions compared with a conventional approach that only considers the planar mode. Secondly, simulations show that non-planar Fourier modes become significant above a threshold frequency ƒ thresh , found in the mid- to high-frequency range. This contribution of non-planar modes is explained by two-dimensional shear effects that distort the entropy waves. A scaling relation that uses residence times along streamlines is developed for ƒ thresh , showing good agreement with simulation results. Finally, we show that the indirect noise from non-planar entropy modes found in aviation combustors can be significant at frequencies below 1 kHz, which might be relevant in situations of thermo-acoustic instabilities coupled to indirect noise.

42 ENGINEERING↗

Uncertainty in determining carbon dioxide removal potential of biochar

A quantitative and systematic assessment of uncertainty in life-cycle assessment is critical to informing sustainable development of carbon dioxide removal (CDR) technologies. Biochar is the most commonly sold form of CDR to date and it can be used in applications ranging from concrete to agricultural soil amendments. Previous analyses of biochar rely on modeled or estimated life-cycle data and suggest a cradle-to-gate range of 0.20–1.3 kg CO 2 net removal per kg of biomass feedstock, with the range reported driven by differences in energy consumption, pyrolysis temperature, and feedstock sourcing. Herein, we quantify the distribution of CDR possible for biochar production with a compositional life-cycle inventory model paired with scenario-aware Monte Carlo simulation in a 'best practice' (incorporating lower transportation distances, high pyrolysis temperatures, high energy efficiency, recapture of energy for drying and pyrolysis energy requirements, and co-generation of heat and electricity) and 'poor practice' (higher transportation distances, lower pyrolysis temperatures, low energy efficiency, natural gas for energy requirements, and no energy recovery) scenarios. In the best-practice scenario, cradle-to-gate CDR (which is representative of the upper limit of removal across the entire life cycle) is highly certain, with a median removal of 1.4 kg of CO 2 e/kg biomass and results in net removal across the entire distribution. In contrast, the poor-practice scenario results in median net emissions of 0.090 kg CO 2 e/kg biomass. Whether this scenario emits (66% likelihood) or removes (34% likelihood) carbon dioxide is highly uncertain. The emission intensity of energy inputs to the pyrolysis process and whether the bio-oil co-product is used as a chemical feedstock or combusted are critical factors impacting the net carbon dioxide emissions of biochar production, together responsible for 98% of the difference between the best- and poor-practice scenarios.

54 ENVIRONMENTAL SCIENCES↗

Skeletal Kinetics Reduction for Astrophysical Reaction Networks

A novel methodology is developed to extract accurate skeletal reaction models for nuclear combustion. Local sensitivities of isotope mass fractions with respect to reaction rates are modeled based on the forced optimally time-dependent (f-OTD) scheme. These sensitivities are then analyzed temporally to generate skeletal models. The methodology is demonstrated by conducting skeletal reduction of constant density and temperature burning of carbon and oxygen relevant to Type Ia supernovae (SNe Ia). The 495-isotopes Torch model is chosen as the detailed reaction network. A map of maximum production of 56 Ni in SNe Ia is produced for different temperatures, densities, and proton-to-neutron ratios. The f-OTD simulations and the sensitivity analyses are then performed with initial conditions from this map. A series of skeletal models are derived and their performances are assessed by comparison against currently existing skeletal models. Previous models have been constructed intuitively by assuming the dominance of α-chain reactions. The comparison of the newly generated skeletal models against previous models is based on the predicted energy release and 44 Ti and 56 Ni abundances by each model. The consequences of ye ≠ 0.5 in the initial composition are also explored where ye is the electron fraction. The simulated results show that 56 Ni production decreases by decreasing ye as expected, and that the 43 Sc is a key isotope in proton and neutron channels toward 56 Ni production. It is shown that an f-OTD skeletal model with 150 isotopes can accurately predict the 56Ni abundance in SNe Ia for ye ≲ 0.5 initial conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

Source-Resolved Inversion of Elemental Carbon Emissions in California Using Log-Space Bayesian Inference

Elemental carbon (EC), operationally quantified by thermal-optical analysis, is widely used as a proxy for black carbon (BC) relevant to short-term climate forcing and public health. Current EC emission inventories remain highly uncertain, with persistent discrepancies between bottom-up and top-down estimates. In this study, we develop a source-resolved, log-space Bayesian inversion framework applied to estimate California’s statewide EC emissions in 2019. By integrating surface EC measurements from the EPA’s Air Quality System network with high-resolution source contributions simulated by a chemical transport model, we identify a one-third underestimation in the existing statewide EC inventory, requiring an increase of the total from a prior of 8.58 [5.49–13.75] Gg year–1 to a posterior estimate of 12.78 [10.71–15.37] Gg year–1. This discrepancy is primarily driven by substantial underestimations in the power and industrial and off-road mobile sectors. Furthermore, population-weighted exposure analysis reveals a marked sectoral divergence between emission mass and health burden: off-road mobile sources dominate both emissions and exposure, accounting for 31% of statewide exposure, while residential wood combustion contributes 26% of total exposure despite comprising only 19% of total emissions, due to its source proximity to population. These findings underscore the need to update sector-specific EC speciation profiles and demonstrate that mitigation strategies targeting off-road mobile sources and residential wood combustion are critical for reducing EC-related health impacts in California.

Zhang, Jie↗

Unraveling the Physics Associated with the Production of Extremely Dense Plasma States of Microscale Nanosecond-pulsed Discharges

The research carried out on this grant aimed to study the properties of anomalously dense plasmas formed in so-called ”fast” discharges, such as high pressure narrow-gap nanosecond pulsed discharges and short pulse (nanosecond-scale) laser driven discharges. These fast discharges are receiving much attention as they now enable new applications in aerodynamics, combustion, biology, and medicine. The mechanisms that generate these high electron densities (ne > 10 19 cm −3 ) that encroach on warm dense matter regimes are not well understood. Such densities are orders of magnitude higher than those (≈ 10 15 cm −3 ) routinely seen in classical high-pressures (streamer) discharges. Furthermore, the dense plasmas are reported to be highly nonequilibrium, with T gas <<, T i << T e . These properties would place these discharges in a regime of near full ionization (Z ≥ 1) where there is inadequate electron screening and therefore strong ion coupling - physics that is not generally accounted for in simulations. In this project work, we seek to study these fast discharges, validate simulations with experiments at pressures as high as 10-50 bar, and augment plasma production to even higher levels of n e (> 10 20 cm −3 ) with second-stage picosecond laser heating. In parallel, we have studied the use of these fast discharges in reactive gases, unraveling mechanisms related to the fast discharge dissociation of CO 2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows

Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR codes. In this work a novel hybrid adaptive multiresolution (HAMR) approach to AMR-based calculations is introduced to address this issue. The multiresolution (MR) smoothness indicators are used to identify regions of smoothness on the mesh where the computational cost of individual physics solvers may be decreased by replacing direct calculations with interpolation. We suggest an approach to balance the errors due to the adaptive discretization and the interpolation of physics quantities such that the overall accuracy of the HAMR solution is consistent with that of the MR-driven AMR solution. The performance of the HAMR scheme is evaluated for a range of test problems, from pure hydrodynamics to turbulent combustion.

97 MATHEMATICS AND COMPUTING↗