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At least 73 records · Page 4

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DOE OSTI2024

Quench process modeling & simulation in the heat-treatment of critical aerospace components

To manufacture light-weight, advanced metal alloy components for gas turbine engines, quench heat-treatment processes are typically used. By quenching the component from elevated tempera-tures, the alloy sometimes undergoes a solid-state phase transformation which produces special microstructures with the required, enhanced mechanical properties. However, the quenching can also lead to cracks forming in the component. Addressing the quench cracking problems adds a significant burden to the cost, schedule, and energy demand of manufacture. Currently, optimizing the quench process to mitigate or avoid the cracking is performed largely by trial-and-error, relying heavily on costly experimental (thermocouple) trials to understand the local thermal gradients which cause the cracks to form. In this first part (Phase 1) of the work, high-performance computing is employed to establish the ability of modern CFD (computational fluid dynamics) to alleviate or wholly replace the experimental quenching trials by virtual testing. A baseline CFD model is defined and its accuracy established to be comparable to (and which usually exceeds) the accuracy of existing HTC (heat-transfer correlation) based simulation methods of quenching. As a first-principles based approach, “calibration” of the Baseline CFD model is independent of the quench process itself, but instead relies on the accuracy of the underlying (modeled), generic two-phase fluid processes which cannot be currently resolved by CFD for large, industrial-scale cases. A novel, high-fidelity DNS capability has been developed and verified to examine and further improve upon the mean-field closure submodels on which the Baseline CFD approach is based.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

DOE OSTI2021

BETO 2021 Peer Review - Biochemical Process Modeling and Simulation (BPMS)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Quantum signal processing for simulating cold plasma waves

Numerical modeling of radio-frequency waves in plasma with sufficiently high spatial and temporal resolution remains challenging even with modern computers. However, such simulations can be sped up using quantum computers in the future. In this work, we propose how to do such modeling for cold plasma waves, in particular, for an X wave propagating in an inhomogeneous one-dimensional plasma. The wave system is represented in the form of a vector Schrödinger equation with a Hermitian Hamiltonian. Block encoding is used to represent the Hamiltonian through unitary operations that can be implemented on a quantum computer. To perform the modeling, we apply the so-called quantum signal processing algorithm and construct the corresponding circuit. Quantum simulations with this circuit are emulated on a classical computer, and the results show agreement with traditional classical calculations. We also discuss how our quantum circuit scales with the resolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Process Modeling of CO 2 Absorption with Monoethanolamine Aqueous Solutions Using Rotating Packed Beds

A first-principle process simulation model is presented for the chemical absorption of carbon dioxide (CO 2 ) with monoethanolamine (MEA) aqueous solutions using rotating packed beds (RPB). Built on a proven rate-based packed bed absorber model, the RPB model rigorously simulates the phase and chemical equilibria at the vapor-liquid interface, the heat and mass transfer across the gas and liquid films, the fast reactions between MEA and CO 2 in the liquid film, and the RPB hydraulics. Here, estimation of the mass transfer rate across the liquid film is central to accurate simulation of the CO 2 absorption process with MEA aqueous solutions. We show that the literature lab-scale RPB data for CO 2 removal efficiency can be satisfactorily correlated by introducing a correction factor for the effective packing surface area predicted by the Onda correlation. Given the validated RPB model, we further show that, among the gas-phase mass transfer coefficient, the liquid-phase mass transfer coefficient, and the reaction rate constant for the reaction between amine and CO 2 , the reaction rate constant is the controlling step with the highest potential to enhance the CO 2 absorption performance in RPB.

42 ENGINEERING↗

DOE OSTI2018

An Integrated Supercritical System for Efficient Produced Water Treatment and Power Generation

The main goal of this project was to evaluate the feasibility of an integrated supercritical (SC) water desalination and power generation system for treatment of produced waters from CO 2 sequestration, oil production, and coal-bed methane recovery. This system may offer a transformative approach to generating power from coal or natural gas (NG) and purifying saline water or produced water with high total dissolved solids (TDS) in a zero-liquid discharge plant. The closed-loop steam cycle of conventional power plants was replaced with an open-loop steam cycle that heated the pretreated produced water above the SC point of water (374 °C and 221 bar) to precipitate and separate the salts dissolved in the water. After separation of the precipitated salt, the SC steam required further treatment to reduce the salt content from ~100 mg/L (ppm) to <1 ppm to make it suitable for use in turbines for power generation. A SC membrane distillation unit was used to polish the SC steam, which could be sent through a series of turbines for power generation, and the steam exiting the low-pressure turbine could be condensed by cooling water to produce pure water. Project tasks included a process simulation and a techno-economic evaluation of the integrated system; design and assembly of SC salt precipitation and membrane distillation systems; development and characterization of advanced carbon membranes for SC membrane distillation; and pretreatment, desalination, and purification of different produced water samples with salt concentrations of 30,000–200,000 ppm to a high-purity (<1 ppm) level. Process simulations were performed for 550 MW SC coal-fired or NG baseline cases and various scenarios for the proposed integrated SC system using produced water as the water source and coal or NG as the fuel source. Simulation results indicated that the net plant efficiency loss of the proposed SC cogeneration process would be in the range of <1% to ~4%, in which NG and lower TDS produced water cases would have higher efficiencies. The proposed process for coal-fired cases could provide all water needs for the power generation process and generate additional pure water for beneficial use. A techno-economic analysis was performed to estimate the cost of produced water treatment (dollars /kgal of treated water) by conventional treatment processes compared with the proposed cogeneration process. The cost estimation for the proposed cogeneration system included the cost of pretreatment, the cost of power loss to integrate the water desalination process into the power generation system, and the cost of plant modification or retrofitting. The cost of produced water treatment was calculated by assuming three different scenarios in which converting a baseline power plant to the proposed cogeneration plant would increase the cost of the boiler and feed water system by 10%, 50%, and 100%. Results indicated that the cost of produced water treatment, even with a 100% cost increase, was in the range of $8.6–11.6 dollars per kgal, which is about half of the treatment cost by conventional methods. The cost of produced water treatment by the proposed cogeneration system could be further reduced or a considerable income could be generated if the values of saltwater and freshwater products are considered. Overall, the techno-economic analysis results indicated that the proposed integrated SC system could potentially treat produced water at a cost significantly lower than the cost of produced water treatment by conventional technologies. To evaluate the feasibility of the proposed treatment system at a laboratory scale, a SC salt precipitation and membrane distillation system was designed and fabricated to treat a simulated brine or pretreated produced water by precipitating salts and further polishing the SC steam containing ~100 ppm salts to a high-purity steam. Through baseline tests with NaCl solutions, with concentrations ranging from 30,000 to 200,000 ppm, it was demonstrated that concentrated feed solutions could be treated by precipitating salt at SC conditions to a TDS level of 130 ppm. Produced water samples were collected from a potential CO 2 sequestration site, a coal-bed methane site, and an oilfield in Illinois. Representative samples were characterized for various water quality parameters, including pH; turbidity; conductivity; and concentrations of selected anions, cations, alkalinity, dissolved organic carbon, total suspended solids, TDS, and total petroleum hydrocarbons. The produced water samples were first treated by conventional pretreatment methods to remove residual oil, dissolved organic matter, and scale-forming species. Pretreatment methods included coagulation, sedimentation, filtration, activated carbon adsorption, and ion-exchange adsorption. Pretreated produced waters were treated at SC conditions in which salts were precipitated. Analysis of treated samples revealed that the concentration of Na (the main cation) in produced waters was reduced dramatically from 14,000–47,400 ppm in the feed to 21–80 ppm in treated waters. Concentrations of other main cations (Ca, Mg, Sr, K) also decreased significantly from initial values of ~1,000–22,000 ppm to ~1 ppm or less. However, a significant increase in the concentrations of Fe, Ni, Cu, and Co was observed, mainly caused by leaching of these elements from the system (vessels, filters, tubing), which is manufactured from alloys containing Fe, Ni, Cu, and Co. To polish the SC steam containing a salt content of ~100 ppm to a high-purity level of <1 ppm, a SC membrane distillation treatment using carbon membranes was employed. Different types of self-standing or supported carbon membranes were developed from graphite, graphene, carbon nanotubes, carbon nanofibers, and pyrolytic carbon. Screening tests revealed that only a limited number of developed carbon membranes were suitable for the purification of steam at SC conditions. Membranes that were either fragile and lacked mechanical strength or had large pores and showed limited salt rejection (<20%) were found to be unsuitable for the purification of SC steam. Promising carbon membranes that were successfully tested for purifying SC steam included two graphite membranes (i.e., AF-5, a porous graphite material, and FGS, a flexible graphite sheet) and a carbon nanotube membrane grown on a Hastelloy substrate and then further modified using a proprietary method (i.e., membrane C). The AF-5 membrane exhibited a stable water flux of ~50 kg/m 2 ∙h and ~40% salt rejection. The FGS membrane had a high salt rejection of 95%–98% but a lower water flux of ~15 kg/m 2 ∙h. Membrane C showed an extremely high flux of 200-800 kg/m 2 ∙h, which is one order of magnitude higher than the water flux of conventional membranes. Membrane C also exhibited 87%–93% salt rejection. Overall, a two-stage or multistage polishing treatment by these membranes could lower the salt content of the SC steam from initial values of ~100–200 ppm to the steam quality of <1 ppm or to parts per billion levels required for the power cycle.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Screening and evaluation of biomass upgrading strategies for sustainable transportation fuel production with biomass-derived volatile fatty acids

Biomass conversion to fuels and chemicals is crucial to decarbonization, but choosing an advantageous upgrading pathway out of many options is challenging. Rigorously evaluating all candidate pathways (process simulation, product property testing) requires a prohibitive amount of research effort; even simple upgrading schemes have hundreds of possible permutations. We present a method enabling high-throughput screening by approximating upgrading unit operations and drop-in compatibility of products (e.g., fuel properties) and apply it to volatile fatty acid (VFA) conversion to liquid transportation fuels via a MATLAB script, VFA Upgrading to Liquid Transportation fUels Refinery Estimation (VULTURE). VULTURE selects upgrading configurations that maximize fuel blend bio-derived content. We validate VULTURE's approximations through surrogate fuel property testing and process simulation. Techno-economic and life cycle analyses suggest that VFA upgrading processes down-selected by VULTURE are profitable and have low carbon intensities, demonstrating the potential for the strategy to accelerate process development timelines at decreased costs.

09 BIOMASS FUELS↗

DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Fission In R-Process Elements

The goal of the FIRE topical collaboration in nuclear theory is to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This will be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration is composed of LLNL (lead) and LANL for fission work, BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r -process simulations. Under DOE/NNSA agreement, both universities receive funds from DOE Office of Science, while national laboratories receive funds directly from NA221.