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DOE OSTI2018

Synthesis of Operable Process Intensification Systems—Steady-State Design with Safety and Operability Considerations

In this work, we present an integrated approach to synthesize process intensification systems with guaranteed flexibility and safety performances. The synthesis of intensified equipment/flowsheets is addressed through the Generalized Modular Representation Framework (GMF), which utilizes an aggregation of multifunctional mass/heat exchange modules to represent chemical processes. Thus, the optimal design options are investigated as mass- and heat-transfer opportunities using superstructure-based optimization techniques without a prepostulation of plausible configurations. To ensure that the designs can be operated under a specified range of uncertain parameters, a multiperiod GMF representation is developed based on the critical operating conditions identified by flexibility test. Risk assessment, accounting for equipment failure frequency and consequence severity, is incorporated as a constraint into this synthesis model to derive inherently safer designs. The resulting safely operable intensified systems, which are represented via phenomenological modules, are then identified as corresponding equipment-based flowsheets and validated with steady-state simulation. We demonstrate the proposed approach through a case study for the production of methyl tert-butyl ether. Here, the results indicate that safety and operability considerations can result in significant changes in the structural and operating parameters of the optimal intensified design configuration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Outreach to Industry on Safeguards by Design Concept for Small Modular Reactors

"Safeguards by Design" (SBD) is the process of incorporating safeguards features into the design of a nuclear facility during the design stage. The goal of SBD is to increase the safeguardability of a facility, which is a qualitative measure of the degree of ease with which a nuclear energy system can be effectively and efficiently placed under international safeguards. During the past decade, the National Nuclear Security Administration's (NNSA) Next Generation Safeguards Initiative funded the Pacific Northwest National Laboratory (PNNL), Brookhaven National Laboratory, and several consultants to develop the Facility Safeguardability Assessment (FSA) process. FSA is a screening process used by a facility designer to focus attention on the aspects of their facility or process design that would most benefit from application of SBD principles and practices. The process identifies the most relevant guidance within the SBD tools for enhancing the safeguardability of the design. During FY 2014, NNSA sponsored BNL and LANL to introduce the FSA to Westinghouse designers of their small modular nuclear power plant design. This report documents the interactions with Westinghouse Electric Company LLC ("Westinghouse") staff. The report describes the Westinghouse safeguards design concept with a view towards eventual application of the FSA to their design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

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 OSTI2018

Distributed Wind Competitiveness Improvement Project

The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. Manufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. This fact sheet describes the CIP and funding awarded as part of the project.ufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. This fact sheet describes the CIP and funding awarded as part of the project.

17 WIND ENERGY↗

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 OSTI2018

Design Load Analysis for Wave Energy Converters: Preprint

This study demonstrates a systematic methodology for establishing the design loads of a wave energy converter (WEC). The proposed design load methodology incorporates existing design guidelines, where they exist, and follows a typical design progression; namely, advancing from many, quick, order-of-magnitude accurate, conceptual stage design computations to a few, computationally intensive, high-fidelity, design validation simulations. The goal of the study is to streamline and document this process based on quantitative evaluations of the design loads' accuracy at each design step and consideration for the computational efficiency of the entire design process. For the WEC, loads, and site conditions considered, this study demonstrates an efficient and accurate methodology of evaluating the design loads.

16 TIDAL AND WAVE POWER↗

DOE OSTI2017

CO 2 capture from natural gas power plants using selective exhaust gas recycle membrane designs

This paper describes membrane processes to capture the CO 2 produced by combustion gas turbines in natural gas combined cycle power plants. Because combustion turbines typically use a large excess of air, the resulting turbine exhaust gas is relatively dilute (only 3–4% CO 2 ), making subsequent CO 2 capture difficult and costly. Previously, we’ve shown that a membrane process can be used to selectively recycle CO 2 to the combustion step, which significantly increases the CO 2 content in the exhaust gas. In this way, selective exhaust gas recycle (S-EGR) makes CO 2 capture energetically easier. Here, various membrane design concepts incorporating S-EGR are described and compared. Furthermore, a combination of S-EGR with non-selective exhaust gas recycle (EGR) is shown to offer advantages in reduced capital, while retaining most of the energy benefits of S-EGR alone. For all of the membrane designs analyzed, the energy and cost of capture vary with the capture rate. Generally, if flue gas compression is not used, the lowest capture cost ($\$$/tonne CO 2 ) for membranes occurs at partial capture rates of 60–70%. Of the process designs studied, the lowest cost of capture (~$44/t) is achieved by an integrated turbine/membrane design that would require changes to existing turbines.

03 NATURAL GAS↗

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 OSTI2017

ClusterCAD: a computational platform for type I modular polyketide synthase design

Here, we present ClusterCAD, a web-based toolkit designed to leverage the collinear structure and deterministic logic of type I modular polyketide synthases (PKSs) for synthetic biology applications. The unique organization of these megasynthases, combined with the diversity of their catalytic domain building blocks, has fueled an interest in harnessing the biosynthetic potential of PKSs for the microbial production of both novel natural product analogs and industrially relevant small molecules. However, a limited theoretical understanding of the determinants of PKS fold and function poses a substantial barrier to the design of active variants, and identifying strategies to reliably construct functional PKS chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify the process of designing experiments to test strategies for engineering PKS variants. ClusterCAD provides chemical structures with stereochemistry for the intermediates generated by each PKS module, as well as sequence- and structure-based search tools that allow users to identify modules based either on amino acid sequence or on the chemical structure of the cognate polyketide intermediate. ClusterCAD can be accessed at https://clustercad.jbei.org and at http://clustercad.igb.uci.edu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗