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At least 325 records · Page 18

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DOE OSTI2020

TAILORED BIOBLENDSTOCKS WITH LOW ENVIRONMENTAL IMPACT TO OPTIMIZE MCCI ENGINES

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗

DOE OSTI2020

Tailored Bioblendstocks with Low Environmental Impact to Optimize MCCI Engines

09 BIOMASS FUELS↗

DOE OSTI2023

Phase transition in bilayer MoS 2 under tensile loading: a molecular dynamics study

Abstract Molybdenum disulfide (MoS 2 ), especially single-layer MoS 2 , has been experimentally and computationally discovered to exist in several different polymorphs exhibiting various electronic and mechanical properties. The morphology of MoS 2 can be tuned through strain engineering. Molecular dynamics simulations are conducted to systematically study the phase transition of single-layer MoS 2 and bilayer MoS 2 under the uniaxial tensile condition at room temperature. The roles of edge and S-line vacancy are investigated. Phase transitions are always triggered near the edge and vacancy sites. The initiation of the metastable T″ phase can release the tensile stress in the lattice, followed by I4/mmm phase initiation, regardless of the edge conditions. The growth of the I4/mmm phase can cause the local buckling of the MoS 2 plane. With a tilted S-line vacancy, I4/mmm phase is first initiated to reduce the local shear stress accumulated near the vacancy line. Overall, the phase transition mechanism of single layer and bilayer MoS 2 under the uniaxial tensile loading is provided, which guides the future strain engineering of MoS 2 in nanoelectronics applications.

Materials Science↗

DOE OSTI2025

CFD modeling of non-catalytic, partial-oxidation engine reformer for flare mitigation

Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.

Computational Fluid Dynamics↗

DOE OSTI2020

A phenomenological rate of injection model for predicting fuel injection with application to mixture formation in light-duty diesel engines

Fuel injection rate laws are one of the most important pieces of information needed when modeling engine combustion with computational fluid dynamics. In this study, a simple phenomenological model of a common-rail injector was developed and calibrated for the Bosch CRI2.2 platform. The model requires three tunable parameter fits, making it relatively easy to calibrate and suitable for injector modeling when high-fidelity information about the internal injector’s geometry and electrical circuit details are not available. Each injection pulse is modeled as a sequence of up to four stages: an injection needle mechanical opening transient, a full-lift viscous flow inertial transient, a Bernoulli steady-state stage, and a needle descent transient. Parameters for each stage are obtained as polynomial fits from measured injection rate properties. The model enforces total injected mass, and the intermediate stages are only introduced if the injection pulse duration is long enough. Experimental rates of injection from two separate campaigns on the same injector were used to calibrate the model. The model was first validated against measured injection rate laws featuring pilot injections, short partially premixed combustion pulses, and conventional diesel combustion injection strategies. Then, it was employed as an input to engine computational fluid dynamics simulations, which were run to simulate experiments of mixture formation in an optically accessible light-duty diesel engine. It was found that, though simple, this model is capable of predicting both pilot and main injection pulse mass flow rates well: the simulations yielded accurate predictions of in-cylinder equivalence ratio distributions from injection strategies for both partially premixed combustion and pilot injections. Also, once calibrated, the model produced appropriate results for a wide range of injected mass and rail pressure values. Finally, it was observed that usage of such a relatively simple model can be a good choice when high-fidelity injection rate input and highly detailed information of the injector’s geometry and operation are not available, particularly as noticeable discrepancies can be present also among different experimental campaigns on similar hardware.

42 ENGINEERING↗

DOE OSTI2020

SENSITIVITY ANALYSIS OF FUEL PHYSICAL PROPERTY EFFECTS ON SPARK IGNITION ENGINE PERFORMANCE

Alternative fuels are of interest to automakers and regulators due to their potential to reduce net greenhouse gas emissions from transportation sources. Alternative fuels also have fuel properties which may enable advanced combustion modes with higher engine thermal efficiencies. There has been previous work to identify the relationship between various fuel properties and engine performance, but most of this work has been experiments or simulations where the change in properties was obtained through changing the fuel composition, making isolating the effects of individual fuel properties difficult. In this study, numerical simulations have been used to investigate the effects of individual fuel physical properties such as viscosity or heat of vaporization (HoV) on engine performance. Simulations have been performed of two different engine platforms, the first an optical, single-cylinder research engine and the second a multi-cylinder production engine. Both engines are direct-injection spark-ignition engines with pent-roof heads and are designed for automotive applications. Each engine was run at a different operating condition, one stable and one knock-limited. Different base fuels provided a variety of simulated conditions. Up to six different fuel properties were varied as part of Global Sensitivity Analyses performed for each of the engines with multiple performance targets including thermal efficiency, combustion efficiency and combustion phasing. Results show trends that are largely consistent with previous experimental findings using multiple fuels. The engine thermal efficiency was primarily sensitive to the fuel's HoV, with other fuel physical properties having smaller effects. For optical engine results, the magnitude of the effect was greater in this study than expected based on previous experimental results were many fuel physical and chemical properties were varied simultaneously. However, for the multi-cylinder production engine, the relationship between thermal efficiency and HoV was slightly smaller.

engine simulation↗

DOE OSTI2025

Breaking the passivation barrier via d-p orbital optimization for stable hydrogen production and sulfion upgrading

The development of energy-efficient hydrogen production technologies represents a critical pathway toward achieving global carbon neutrality objectives. This work provides fundamental insights into overcoming catalyst passivation challenges in sulfide oxidation reaction (SOR)-coupled hydrogen evolution reaction (HER) systems through precise orbital hybridization engineering. Our theoretical simulations reveal that sulfur-passivated ruthenium surfaces can effectively modulate d-p orbital hybridization, significantly reduce d-electron activity while stabilizing long-chain S 8 species and decreasing intermediate adsorption energies. Furthermore, metal carbides/ruthenium heterostructure (MC/Ru, M = V, Mo, W) was designed to achieve simultaneous optimization of both HER (∆G H* = −0.11 eV) and SOR (∆G RDS = 1.51 eV) via work-function-mediated interfacial electron transfer, which effectively tailors surface electronic states. Guided by theoretical predictions, we successfully synthesized a series of metal carbides/ruthenium/nitrogen-doped carbon catalysts based on a solid-phase reaction and designated as MC/Ru@NC (M = V, Mo, W). The optimized VC/Ru@NC catalyst exhibits exceptional performance in a membrane-free two-electrode system, achieving an ultralow cell voltage of 0.76 V at 200 mA cm −2 with outstanding stability over 1600 h, while maintaining 97.5 % Faradaic efficiency for hydrogen production and 73.8 % sulfur recovery efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Numerical study of a micro flow reactor at engine pressures: Flames with repetitive extinction and ignition and simulations with a reduced chemical model

Combustion in a narrow channel with an imposed temperature gradient is studied numerically at elevated pressure with engine-relevant fuels. Here, the focus is placed on unsteady flames with repetitive extinction and ignition (FREI) to determine the potential of this regime for fuel testing and calibration of reduced chemical mechanisms. First, it is shown that the FREI regime does occur at elevated pressures for sufficiently small tube diameters. The sensitivity of the extinction and ignition temperatures to low-temperature chemistry is found to be significantly enhanced at 25 bar compared to atmospheric conditions. The ignition and extinction temperatures differ by up to 100 K between PRF mixtures with varying octane numbers. Ternary mixtures of iso-octane/n-heptane/toluene and iso-octane/n-heptane/ethanol at similar research and motor octane numbers are also studied. Second, the potential of using data from the micro flow reactor to infer reaction rates is assessed. A reduced chemical mechanism combining a small fuel-dependent submechanism with a detailed fuel-independent submechanism for the core species chemistry is used for that purpose. Only the most sensitive fuel-dependent reactions are inferred. the calibrated reduced model is compared to a detailed model and good agreement in ignition delay times and laminar flame speeds is observed. Finally, this illustrates the potential of a micro flow reactor with a controlled temperature profile to test fuels and infer kinetic data.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Parametric amplification of spin-motion coupling in three-dimensional trapped-ion crystals

Three-dimensional (3D) crystals offer a route to scaling up trapped-ion systems for quantum sensing and quantum simulation applications; however, engineering coherent spin-motion couplings and effective spin-spin interactions in large crystals poses technical challenges associated with decoherence and prolonged timescales to generate appreciable entanglement. Here, we explore the possibility of speeding up these interactions in 3D crystals via parametric amplification. For this purpose, we derive a general Hamiltonian for the parametric amplification of spin-motion coupling that is broadly applicable to normal modes with motion transverse to or along the spatial extent of the crystal. Unlike in lower-dimensional crystals, we find that the ability to faithfully (uniformly) amplify the spin-spin interactions in 3D crystals depends on the physical implementation of the spin-motion coupling. We consider the light-shift gate, and the so-called phase-insensitive and phase-sensitive Mølmer-Sørensen (MS) gates, and we find that only the phase-sensitive MS gate can be faithfully amplified in general 3D crystals. We discuss a situation where nonuniform amplification can be advantageous. We also reconsider the effect of counter-rotating terms on parametric amplification and find that they are not as detrimental as previous studies suggest.

Optical parametric oscillators & amplifiers↗

DOE OSTI2024

Machine Learning Aided Modeling of Granular Materials: A Review

Artificial intelligence (AI) has become a buzzy word since Google’s AlphaGo beat a world champion in 2017. In the past five years, machine learning as a subset of the broader category of AI has obtained considerable attention in the research community of granular materials. This work offers a detailed review of the recent advances in machine learning-aided studies of granular materials from the particle-particle interaction at the grain level to the macroscopic simulations of granular flow. This work will start with the application of machine learning in the microscopic particle-particle interaction and associated contact models. Then, different neural networks for learning the constitutive behaviour of granular materials will be reviewed and compared. Finally, the macroscopic simulations of practical engineering or boundary value problems based on the combination of neural networks and numerical methods are discussed. We hope readers will have a clear idea of the development of machine learning-aided modelling of granular materials via this comprehensive review work.

42 ENGINEERING↗

DOE OSTI2022

Combined Experimental and Modeling Study of Microwave-Assisted Methane Dehydroaromatization Process

ACS Fall Meeting 2022, Chicago, IL, August 21-25, 2022

Bai, Xinwei↗

DOE OSTI2021

Parametric Studies of Heat Pump Water Heater Using Low GWP Refrigerants

A storage heat pump water heater (HPWH) comprises a vapor compression system and a hot water tank. It can lead to more than 70% energy saving, compared with electric resistance heating. HPWH usually uses a wrapped-tank coil as the water heater. The wrapped coil has a strong interaction with the water tank and impose a new challenge for the engineering design and simulation study. Based on the US DOE/ORNL Heat Pump Design Model (HPDM), i.e., a public-domain, component-based thermal system modelling platform, a segment-to-segment wrapped-tank coil model coupled with a one-dimensional stratified water tank model were developed, which facilitates modeling and design HPWHs having various configurations and components. Additionally, the hardware-based design model was used to evaluate refrigerants having lower global warming potentials to replace R-134a, including R-1234yf, R-1234ze, R-290, R-513A and R-450A, when effects of compressor size, refrigerant charge on 24-hour uniform energy factor (UEF) and first-hour rating (FHR) were investigated.In the drop-in replacements, R-1234ze achieved the best UEF, and R-290 resulted in the lowest UEF. When downsizing the compressor to maximize the UEFs, the UEFs of R-134a, R-290, R1234yf, R-450A and R-513A ascended to the range of 4.4 to 4.53, with R-513A having the highest UEF. The R-1234ze ended up having the lowest UEF of 4.27. Refrigerants having larger volumetric vaporization heat led to higher FHRs if using the fixed-size compressor, that R-290 resulted in the highest FHR.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

CALPHAD-based ICME design of single-step aging to enhance mechanical strength of WAAM Haynes 282

To match the strength of wire-arc additive manufactured Haynes 282 to its wrought counterpart via a single-step aging heat treatment, the CALPHAD (Calculation of Phase Diagrams) method is integrated with physics-based process-structure-property models and experimental validation. The integrated computational materials engineering (ICME) framework simulates the effects of aging on γ′ and M 23 C 6 precipitation and the resulting yield strength. To improve simulation reliability, the interfacial energies between γ/γ′ and γ/M 23 C 6 carbides were estimated by comparison with precipitation kinetic modeling and measured precipitate sizes. γ′ and M23C6 were found to precipitate simultaneously between 640 and 860 °C, producing microstructures similar to those produced by two-step aging. The optimal γ′ size for peak yield stress was calculated to be 20–23 nm. WAAM Haynes 282 aged at 780 °C for 50 h exceeded the mechanical performance of its wrought counterpart subjected to two-step aging, though desired properties can also be achieved at 800 °C for 16 h or less. The error in yield strength is less than 20 MPa, demonstrating good agreement between the modeling framework and experiments. Creep studies showed that WAAM Haynes 282 exceeded the calculated rupture time, reaching 481 h. This proposed methodology can accelerate the design of aging heat treatments for any γ′-strengthened nickel-base alloy, minimizing the resources required for trial-and-error experiments.

CALPHAD↗

DOE OSTI2021

Feasibility of full-core pin resolved CFD simulations of small modular reactor with momentum sources

Complex flow structure interactions and heat transfer processes take place in nuclear reactor cores. Given the extreme pressure/temperature and radioactive conditions inside the core, numerical simulations offer an attractive and sometimes more feasible approach to study the related flow and heat transfer phenomena in addition to the experiments. Under the Exascale Computing Project, the full-core simulation of a small modular reactor (SMR) has been pursued coupling Computational Fluid Dynamics (CFD) and neutronics. A key aspect of the modeling of SMR fuel assemblies is the presence of spacer grids and the mixing promoted by mixing vanes or the equivalent. A reduced order methodology is adopted based on momentum sources to mimic the mixing of the vanes. The momentum sources have been carefully calibrated with detailed Large Eddy Simulations (LES) of spacer grids performed with Nek5000. Modeling the spacer grid and mixing vanes (SGMV) effect without body-fitted computational grid avoids the excessive costs in resolving the local geometric details, and thus supports the simulation to be scaled up to the full core. Besides the progress on momentum source modeling, this paper also features the first full-core pin resolved CFD simulation ever performed to the authors' knowledge. This represents a significant advancement in capability for the CFD of nuclear reactors, which will hopefully serve as an inspiration for further integrating high-fidelity numerical simulations in actual engineering designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Transport Properties of Nanoporous, Chemically Forced Biological Lattices

Permselective nanochannels are ubiquitous in biological systems, controlling ion transport and maintaining a potential difference across a cell surface. Surface layers (S-layers) are proteinaceous, generally charged lattices punctuated with nanoscale pores that form the outermost cell envelope component of virtually all archaea and many bacteria. Ammonia oxidizing archaea (AOA) obtain their energy exclusively from oxidizing ammonia directly below the S-layer lattice, but how the charged surfaces and nanochannels affect availability of NH4+ at the reaction site is unknown. In this report, we examine the electrochemical properties of negatively charged S-layers for asymmetrically forced ion transport governed by Michaelis–Menten kinetics at ultralow concentrations. Our 3-dimensional electrodiffusion reaction simulations revealed that a negatively charged S-layer can invert the potential across the nanochannel to favor chemically forced NH 4 + transport, analogous to polarity switching in nanofluidic field-effect transistors. Polarity switching was not observed when only the interior of the nanochannels was charged. We found that S-layer charge, nanochannel geometry, and enzymatic turnover rate are finely tuned to elevate NH 4 + concentration at the active site, potentially enabling AOA to occupy nutrient-poor ecological niches. Strikingly, and in contrast to voltage-biased systems, magnitudes of the co- and counterion currents in the charged nanochannels were nearly equal and amplified disproportionally to the NH 4 + current. These simulations imply that engineered arrays of crystalline proteinaceous membranes could find unique applications in industrial energy conversion or separation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Artificial Intelligence-Aided Wind Plant Optimization for Nationwide Evaluation of Land Use and Economic Benefits of Wake Steering

If clean energy pathways are to harness massive increases in wind power, innovations with broad geographic viability will be needed to support buildout in diverse locations. However, geodiversity in impact potential is seldom captured in technology assessment. Here we propose a scalable approach to plant-level optimization using artificial intelligence to evaluate land sparing and economic benefits of wake steering at more than 6,800 plausible onshore wind locations in the USA. This emerging controls strategy optimizes plant energy production by directing turbine wakes. On the basis of estimates from our artificial intelligence model trained on engineering wind flow simulations, co-optimizing plant layouts with wake steering can reduce land requirements by an average of 18% per plant (site-specific benefits range from 2% to 34%), subject to errors and uncertainties in the flow model, wind resource estimates, buildout scenario and geographic factors. According to model estimates, wake steering is predicted to increase power production during high-value (relatively low wind) periods, boosting the annual revenue of individual plants by up to US$3.7 million (equivalent to US$13,000 MW-1 yr-1) but producing negligible gains in some settings. Consideration of wake steering’s geographic potential reveals divergent nationwide prospects for improved economics and siting flexibility.

deployment↗

DOE OSTI2020

Studying impacts of communication system performance on dynamic stability of networked microgrid

The development of smart grid technologies has resulted in increased interdependence between power and communication systems. Many of the operations in the existing power system rely on a stable and secured communication system. For electrically weak systems and time‐critical applications, this reliance can be even greater, where a small degradation in communication performance can degrade system stability. However, despite inter‐dependencies between power and communication systems, only a few studies have investigated the impacts of communication system performance on power system dynamics. This study investigates the dependencies of power system dynamics operations on a communication system performance. First, a detailed, dynamic networked microgrid model is developed in the GridLAB‐D simulation environment, along with a representative multi‐traffic, multi‐channel, multi‐protocol communication system model, developed in the network simulator (ns‐3). Second, a hierarchical engine for large‐scale infrastructure co‐simulation framework is developed to co‐simulate microgrid dynamics, its communication system, and a microgrid control system. The impact of communication system delays on the dynamic stability of networked microgrids is evaluated for the loss of generation using three use‐cases. While the example use‐cases examine microgrid applications and the impact to resiliency, the framework can be applied to all levels of power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗