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DOE OSTI2023

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Designing a Robust MEA-Based Post-Combustion Carbon Capture Process with Capture Rate Guarantees

This work presents an application of the nonlinear two-stage robust optimization solver PyROS to the model-based design and operation of a monoethanolamine scrubbing process for CO2 capture under epistemic uncertainty. Through this application, risk-averse process designs are successfully obtained for CO2 capture targets ranging from 90% to over 99%. In particular, the risk-averse solutions for CO2 capture targets of up to 98% are shown to be only marginally more expensive than their nominally optimal counterparts. Thus, the results demonstrate the utility of recently developed nonlinear robust optimization approaches for the solution of large-scale chemical process models under uncertainty.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management using Smart Meters

This paper describes a systematic process of designing resilient electric distribution systems and microgrids using smart meters for surgical load management (SLM) as part of Advanced Metering Infrastructure (AMI). The work focuses on selection approach, integration, and interoperability aspects for AMI in microgrids. SLM is proposed as a granular control methodology for serving selective critical loads across different distribution feeders in the system during extreme events. The surgical load shedding as well as load pick-up provides a robust approach for maximizing critical load served in a resource-constrained electric distribution system or a microgrid. We present the case of a 20 MW islanded microgrid in Cordova, AK, USA, which is the demonstration site for field validation of resilience enhancement technologies for the DOE-funded Grid Modernization project RADIANCE. Cordova microgrid is an islanded distribution grid that provides an environment to prove the approach, and the techniques may also be applicable to other regional distribution systems.

microgrids↗

DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Integrated Turbine Component Cooling Designs Facilitated by Additive Manufacturing and Optimization

This research program involved the development of improved gas turbine cooling by optimizing the combined internal and film cooling configurations used for turbine blades and vanes. Improved cooling of turbine airfoils allows the gas turbines to be operated at higher temperatures which improves efficiency for gas turbine-based power generation. This also facilitates operation with hydrogen-based fuels which inherently generate higher operating temperatures. Designs of the new cooling configurations were based on the added geometric flexibility that is available when using metal additive manufacturing techniques. When making these designs, adjustments were made to account for imperfections occurring in the metal additive manufacturing process. New designs for film cooling holes were developed using computational adjoint gradient optimization techniques which generated a unique film cooling hole with 70% greater film cooling effectiveness compared to conventional shaped film cooling holes. A major factor in improving the film cooling effectiveness were small external protrusions on either side of the new hole which generated vortices that pushed coolant towards the surface and increased the lateral spreading of the coolant. Our studies also included optimization of film cooling holes that can be built with conventional manufacturing techniques and optimizing the internal coolant channels that supply coolant to the film cooling holes. Various internal coolant channel shapes were investigated and designs that maximized the cooling of the airfoil while minimizing pressure losses in the channel flows were identified. Testing and verification of the performance of the final configurations was done with a transonic wind tunnel facility which allowed testing at engine realistic high velocities. Final testing of the combined internal and film cooling configurations was done by incorporating the configurations in Penn State’s National Experimental Turbine (NExT) vane. These tests confirmed the enhanced overall cooling effectiveness provided by the new cooling configuration designs.

03 NATURAL GAS↗

DOE OSTI2022

Radically Engineered Modular Air Separation System with Tailored Oxygen Sorbents

The commercial energy sector relies heavily on fossil fuel conversion, and in the process releases a significant amount of CO 2 . A promising technology to utilize fossil fuels with relatively affordable CO 2 capture is gasification. However, it requires a pure oxygen stream. The current state of the art method to produce oxygen is cryogenic air separation, which supercools air to a liquid, and then using distillation columns to separate the components. While this method has been thoroughly studied, it only has a 25% efficiency from a second law standpoint and therefore requires a significant amount of energy (and associated emissions) for oxygen production. This, then, lowers the incentive for carbon capture within a plant, so alternative methods need to be investigated. One potential method, chemical looping air separation (CLAS), is a promising method to replace state of the art oxygen generation technologies. CLAS utilizes a cyclic redox scheme with an oxygen sorbent to create pure oxygen streams. This approach typically utilizes a dual reactor scheme where the oxygen deficient sorbent enters the first reactor and is subjected to high oxygen partial pressures to re-oxidize the sorbent. Then the sorbent is sent to the reducing reactor, where it is subjected to low oxygen partial pressure (steam or vacuum) to releases oxygen. The overarching objective of this project was to discover the principles for rational design and optimization of oxygen sorbents and process design to ensure the process is a viable replacement for cryogenic air separation, especially in the context of modular gasification systems. This was done through development, characterization, testing, and analyses of (a) high temperature mixed composite oxides; (b) low temperature doped perovskite oxides (A1 x A2 1-x B1 y B2 1-y O 3 ); (c) scale up synthesis and testing of the optimized sorbent particles; (d) process design and analyses of the CLAS system in the context of modular gasification applications.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management Using Smart Meters: Preprint

microgrids↗

DOE OSTI2019

Designing Critical Experiments Using Gaussian Process Optimization

New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Implementation of Increased Salt and Decreased Sludge Volumes in the Defense Waste Processing Facility - 19597

The Savannah River Site (SRS) Liquid Waste System (LWS) safely stores and treats high-level radioactive waste. The LWS consists of 51 waste storage tanks (eight of which are operationally closed and filled with grout), waste evaporators, treatment facilities, and solidification facilities such as the Defense Waste Processing Facility (DWPF) and Saltstone Production Facility (SPF). The disposition of high-level waste (HLW) into a glass waste form poured into canisters at the DWPF began in 1996. DWPF processed a sludge only flowsheet until 2008 when the Actinide Removal Process (ARP) and Modular Caustic Side Solvent Extraction Unit (MCU) began treating the salt waste from the underground liquid storage tanks by striking with monosodium titanate (MST) to remove actinides, when necessary to meet downstream acceptance criteria, and removing the MST and entrained sludge solids (SS) by filtration before using an organic solvent to strip the cesium from the salt, creating two new concentrated HLW streams. This change caused the DWPF to begin processing under both a sludge-only and a coupled operations flowsheet where salt streams would only be added when available. This strategy allows for continuous glass canister production at DWPF. Recently, DWPF completed a 10-month melter replacement in December 2017 and the Concentrate, Storage, and Transfer Facility (CSTF) has completed repairs to the 3H Evaporator system. These facility outages have caused delays in preparing the next batch of sludge feed for DWPF. Concurrent with these facility outages, the Salt Waste Processing Facility (SWPF) has been undergoing system testing and commissioning, working toward startup. SWPF is designed to process salt waste in the same manner as ARP/MCU, but with much higher throughput volumes produced per unit time. In order to process the SWPF salt streams efficiently, DWPF will implement a coupled operation only flowsheet. Based on the facility outages mentioned above, efforts have been made to identify strategies to minimize sludge volumes and maximize salt volumes in the DWPF until the next sludge batch is ready for processing in DWPF. Savannah River Remediation (SRR) recently performed an evaluation that examines the effects of reducing the volume of sludge and maximizing the addition of the cesium-rich concentrated salt solution in each Sludge Receipt and Adjustment Tank (SRAT) batch in order to extend the existing sludge batch as long as possible until the next sludge batch is ready. These effects include a reduction of weight percent solids in the DWPF processing vessels, an increase in cycle time, a new canister heat generation value that remains within regulatory limits, and higher gamma source that remains within bulk facility gamma shielding. Balancing the above parameters resulted in a small reduction of sludge volume per SRAT batch under SWPF operation and maximizing the salt volumes for both ARP/MCU and SWPF operation. This slight reduction in sludge volume and increase in salt volumes allows SRR to mitigate some of the schedule impact incurred by the facility outages. This strategy was evaluated for both ARP/MCU and SWPF operation. This strategy has been successfully implemented under ARP/MCU operation using small step changes in the current process. This paper provides an overview of the evaluation performed for DWPF with ARP/MCU and DWPF with SWPF operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Electrochemical Reaction Engineering: A Lost (and Found) Art

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For non-electrochemical industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, electrolytic processes face a dearth of well documented reaction engineering principles and design practices. This tutorial-style poster presentation introduces electrochemistry students and industrial practitioners to the "lost art" of reaction engineering and its organic extensions to electrochemical devices. Electrochemical reactor fundamentals and illustrative design equations are presented alongside a proposed five-step generalizable methodology for electrochemical reactor scale-up. Overall, this contribution seeks to educate electrochemistry researchers on practical means of reducing laboratory technologies to commercial practice.

electrochemistry↗

DOE OSTI2024

Neural Networks for Prediction of Complex Chemistry in Water Treatment Process Optimization

Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.

Dudchenko, Alexander V↗

DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗

DOE OSTI2024

Reaction engineering: a lost (and found) art for a decarbonized future [Slides]

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For traditional industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, new-age process concepts proposing to use "exotic" reactors and/or sustainable inputs (e.g., renewable carbon resources, electrons, photons, plasma) face a dearth of well documented reaction engineering principles & design practices that eclipses their rapid adoption. This presentation features two vignettes of (the return of) reaction engineering in sustainable process science, first in the valorization of lignin from biomass, and second in understanding multimodal catalyst deactivation in industrial-scale reactors within the Catofin process for propane dehydrogenation. Overall, this seminar seeks to educate student researchers on practical means of advancing laboratory reactor technologies towards commercial practice.

09 BIOMASS FUELS↗

DOE OSTI2023

Modeling of Reactor Design and Optimization for Scale-Up of the Catalyxx Process for Ethanol Conversion to Higher Alcohol Biofuels

This report summarizes the results of a collaborative efforts between Oak Ridge National Laboratory (ORNL) and Catalyxx Inc. to investigate scale-up of Catalyxx’s Ethanol upgrading to higher alcohols process. The study was funded by the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) under CRADA (Cooperative Research and Development Agreement) No: NFE-20-08396. The project is part of the Direct Funding Opportunity (DFO) for Computational Science to Enable Bioenergy program which utilized computational toolsets developed by the Consortium for Computational Physics and Chemistry, a multi-laboratory consortium in BETO. The report here summarizes a packed-bed reactor modeling effort spanning the range from lab to industrial scale (from 4 gram to 5-ton catalyst beds), and examining reactor design, process optimization strategies, and suggested design and operating conditions for Catalyxx’s ethanol upgrading plants. The results in this report have been shared in monthly steering meetings and presentations are available in the shared data house owned by Catalyxx. The modeling effort helped to define optimum operation conditions for maximum alcohol selectivity and yield: i.e., temperature control scenarios ranging from adiabatic to isothermal, feed rate, pressure, and inlet H 2 /Ethanol ratio. The modeling results were verified at lab-(4 gram) and pre-pilot (4 kg) scales and has been used to evaluate a 5-ton packed-bed reactor and identify operating conditions to maximize the butanol yield. Special focus was given to understanding mass-transfer effects in the pre-pilot and pilot-scale reactors, over the domain of flow rate, pressure, feed composition, pellet size, shape, porosity, bed voidage, and reactor dimensions (i.e., length/diameter). Modeling was also used to evaluate innovative reactor design concepts such as water removal to improve alcohol selectivity and yield, and a reactor with an additional side inlet to facilitate quenching. These concepts were thoroughly explored, and potential benefits were disclosed. The results in this report are summarized and described qualitatively to protect the IP rights of Catalyxx. The details have been shared with the Catalyxx team in the regular steering meetings. At the end of the project, Catalyxx Inc. announced a successful demonstration of pilot scale operation in Seville, Spain.

02 PETROLEUM↗

DOE OSTI2019

Synthesis of operable process intensification systems: advances and challenges

Process intensification (PI) has been gaining increasing momentum in the chemical engineering research community and the chemical/energy industry. While many PI alternative technologies and their conventional counterparts exist, systematic approaches and tools to decide on the most promising intensified process solutions are currently rather lacking. Process Systems Engineering (PSE) can contribute uniquely to this challenge by leveraging process synthesis, design, analysis, and optimization tools. However, key open questions in this area still remain, including: (i) how to efficiently address the combinatorial design space and systematically deliver intensified designs, and (ii) how to ensure the operablility performances of the derived intensified structures at an early design stage. Here, this paper provides a brief review of recent progress towards the synthesis of operable process intensification systems, highlights major challenges, and discusses future research opportunities.

42 ENGINEERING↗

DOE OSTI2019

Abengoa/Acciona Power Plant Hydrogen Mitigation Project (Cooperative Research and Development Final Report, CRADA Number CRD-15-583)

Several Gigawatts (GW) of solar concentrating parabolic trough generating capacity have been installed in the U.S. and internationally in the past five years. Many of these power plants include thermal energy storage, which allows the plants to generate electricity during off-sun hours. The U.S. now has about 1 GW of solar-to-electric generating capacity using concentrating parabolic trough technology. Parabolic trough power plants have a long-standing performance issue relating to the build-up of trace quantities of hydrogen gas in the receiver tubes. Hydrogen is a byproduct of the very slow breakdown of the heat transfer fluid. Accumulation of hydrogen in the receivers causes a loss in the thermal efficiency of the receivers and an overall decrease in the power plant annual electricity output. Since a typical plant contains 50,000 receivers, addressing this issue by individual receiver is not practical. The National Renewable Energy Laboratory (NREL) conceived and developed a method to remove or purge hydrogen from the power plant receivers by removing hydrogen from a single location within the plant. Hydrogen gas is purged from the heat transfer fluid that resides in the power plant expansion tanks. Modeling shows that quantitative removal of hydrogen from the expansion tanks will reverse build-up of hydrogen in the receiver tubes and restore the power plant to its full performance and annual energy output. This method is documented in U.S. Patent 8,568,582, which issued in October 2013. Two companies, Abengoa Solar and Acciona Solar Power, Inc. contacted NREL to discuss solutions to the eventual build-up of hydrogen in their commercial parabolic trough power plants. NREL proposed to implement its method at Acciona's Nevada Solar One (NSO) parabolic trough power plant in Boulder City, Nevada. The first year will consist of laboratory testing at the NREL Energy Systems Integration Facility (ESIF) along with process specification, design, and costing. The second year will be the full-scale implementation of the hydrogen mitigation process at the NSO power plant in Nevada.

14 SOLAR ENERGY↗

DOE OSTI2024

SPC-71145 Rev 0 MARVEL Process Heat Extraction System Conceptual Design

The Microreactor Applications Research Validation and Evaluation (MARVEL) reactor will offer experimental capabilities that are not currently available at DOE’s national laboratories. The MARVEL reactor is a microreactor which uses eutectic sodium-potassium alloy (NaK) as a primary coolant. The primary coolant is circulated through four primary loops by natural convection of the coolant. In each loop is a closed well which will accommodate an intermediate heat exchanger (IHX) for extracting heat from the loop. These wells will be referred to in this specification as the “IHX wells”. It is intended for the IHX containment to also be filled with NaK. The MARVEL design team is currently looking for alternative means of extracting heat from these wells to be utilized in downstream applications. This Heat Utilization System (HUS) will enable MARVEL operations including the ability to test, demonstrate, and address issues related to installation, startup, and operations. In addition, it will allow down-stream utilization of process heat for various uses. Depending on the methodology used, the interface between the secondary coolant and the HUS is the Process Heat Extraction System (PHES) and is the subject of this specification.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗