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DOE OSTI2020

New Designed Containers for Activated ILW from NPP Decommissioning - 20208

The paper focuses on packaging of dismantled and fragmented reactor components into containers and their transport to their storage and/or disposal facility within the immediate dismantling strategy applied on decommissioning of nuclear power plant (NPP) finally shutdown after standard operation. The main purpose of the paper is to present the process of design, manufacture, testing and use of new transport and storage containers for activated intermediate level waste (ILW) from V1 NPP decommissioning at Jaslovske Bohunice site. Legislation conditions, container selection process, requirements on their design and manufacture, scope of associated licensing documentation and technical procedures applied up to their use on site are described in detail. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Purification of U from U-10Mo scrap generated during the fabrication of high performance research reactor fuel

A low enriched U-Mo alloy fuel is under development to replace highly enriched U fuels currently used in United States high performance research reactors. The alloy casting and fuel fabrication processes will generate scrap streams containing low enriched U (LEU) which must be recovered. Solvent extraction processes were designed using the Argonne Model for Universal Solvent Extraction (AMUSE) to purify solutions containing 20 and 50 g/L U. The feed for the solvent extraction processes was prepared from solutions generated from the dissolution of U-10Mo-Zr foils and U-10Mo-Zr-Al mini-plates. The U purification processes were demonstrated using two, 16-stage banks of miniature mixer-settlers. The solvent extraction experiments demonstrated that all design objectives for the U purification processes could be met. The U recovery in the product stream for each flowsheet was ≥99.9%. The flowsheet demonstrations also showed that the purity of the U Product will meet the requirements of the ASTM International C1462-21 specification for LEU metal enriched to less than 20% 235 U. In conclusion, the AMUSE modeling for both flowsheet demonstrations was validated by comparing predicted and measured concentrations of U, Mo, and Zr in the exit streams and stage samples at steady-state conditions in the mixer-settlers.

modified PUREX process↗

DOE OSTI2022

Ion Exchange Processing of AP-105 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System (Rev.1)

The Tank Side Cesium Removal (TSCR) system, under development by Washington River Protection Solutions LLC (WRPS), will send initial low-activity Hanford waste tank supernate feeds to the Hanford Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) Facility. In addition to entrained solids removal from the supernate, the primary goal of TSCR is to remove cesium-137 ( 137 Cs) by ion exchange, allowing contact handling of the liquid effluent product at the WTP. Crystalline silicotitanate (CST) ion exchange media, manufactured by Honeywell UOP, LLC (product IONSIVTM R9140-B), was selected as the ion exchange media at TSCR. CST is a non-elutable inorganic material that has demonstrated robust chemical, physical, and radiation tolerance while maintaining functionality. However, exchange kinetics of Cs onto CST is slow, resulting in low utilization of the CST Cs load capacity before unacceptable Cs breakthrough. Two process flow designs have been tested, as follows. 1. Lead-lag column processing: The lead column was removed after the lag column effluent reached the waste acceptance criteria (WAC) limit, the lag column was moved into the lead position, and a new lag column was installed. This format used ~52% Cs load capacity on the lead column. 2. Lead-lag-polish column processing: The processing was stopped when the polish column effluent reached the WAC limit. This format resulted in 81% Cs load capacity on the lead column. Testing with diluted feed from Hanford tank AP-105 (AP-105DF) incorporated a nuanced change to the lead-lag-polish column system where the polish column was inserted when the lag column effluent reached WAC limit. A 10.9-L volume of AP-105DF (diluted to 5.6 M Na) was processed through the Direct Feed Test Platform system, established at Pacific Northwest National Laboratory to support small-scale waste qualification efforts. The columns consisted of 10-mL CST beds (CST Lot 2002009604, sieved to screen out >30-mesh particles) placed in 1.5-cm-inner-diameter columns. Feed was processed at 1.83 bed volumes (BV) per hour; the flowrate, in terms of contact time with the CST bed, matched the expected flowrate at TSCR. The <30-mesh CST sieve cut was expected to provide appropriate performance scaling to a full-height column. The installation of the polish column later in processing (after processing 523 BVs) did not appear to fundamentally change the utilization of the lead column for Cs exchange nor did it extend the total feed processing volume when compared to the previous test with AP-107 feed. Table ES.1 and Figure ES.1 summarize the measured AP-105DF Cs load performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Automated AI-driven Molecular Design for Therapeutic Discovery

In recent years, artificial intelligence and machine learning (AI/ML) approaches have revolutionized the process of designing new therapeutics, enabling scientists to rapidly respond to emerging threats from various pathogens. A prime example is the SARS-CoV-2 main protease, a key target for the development of antiviral inhibitors. In this study, we employed a novel, integrated approach that combines AI-driven iterative design of inhibitor candidates, screening based on physio-chemical properties and toxicity, physics-based computational modeling of protein-inhibitor interactions, and AI-assisted analysis of Native MS biophysical assay and characterization of designed candidates. Our deep learning 3D-scaffold model, which uses an input scaffold as a starting point, generated tens of thousands of compounds while preserving the key scaffold. To optimize these candidates, we calculated a comprehensive set of 136 descriptors, including both 2D and 3D molecular features, for compounds targeting the SARS-CoV-2 Main protease (Mpro) and a neurodegenerative disease-associated protein, cyclophilin (Cyp). The generated compounds were initially filtered based on their properties and then ranked according to their predicted binding affinity using our automated modeling and ML methods. Experimental validation of the Mpro candidates showing inhibitory activity demonstrates that our workflow can expedite the therapeutic discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Implementation of Surface Tension on a Reacting Flow Solver, PeleLM: Preprint

In liquid rocket engines, the fuel is supplied to the combustion chamber in the liquid state though injectors. Such fuel undergoes atomization, vaporization, and combustion processes. To design reliable and efficient injectors, it is required to understand the full processes. This research is part of an effort to develop a full atomization-vaporization-combustion solver from first principles. As an initial step to tackle the atomization process, a multiphase flow solver is under development. For the development, a library of the volume of fluid scheme for multiphase, IRL is coupled with a reacting Navier-Stokes equation solver, PeleLM. Furthermore, as the surface tension has considerable effects on spray breakup. surface tension is implemented in the momentum equation using the continuum surface force model and the improved height function technique.

height function↗

DOE OSTI2020

Process Development of a Direct Cast U-6Nb 250 mm Cylinder

Direct Casting is the process of casting a near-net shape part of U-6wt%Nb in a multi-zone VIM furnace for subsequent heat treatment and machining in to a final component. This interim report describes ongoing work to further develop a sound technical basis and best practices for mold design and process parameters for the Direct Casting of U-6Nb components with a cylindrical geometry. Specifically, process parameters and mold design are examined in detail for producing a hollow cylinder 250 mm diameter by 450 mm long which is 10 to 12 mm thick. The goal is to efficiently produce a sound casting with a minimum of microporosity and uniform niobium composition.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.

Romanov, Vyacheslav↗

DOE OSTI2023

Design of Multi-Stage Solvent Extraction Process for Separation of Rare Earth Elements

Flowsheet design and stage determination for the separation of rare earth elements (REEs) using solvent extraction (SX) is a challenging task because of the chemical similarity of the REEs. Low separation factors between the elements and complex equilibrium chemistry provide unique challenges to designing an efficient flowsheet for the separation of elements. The multi-stage nature of the SX process adds further complexity, making the assessment of products for a proposed design and stage combination difficult. Therefore, to develop a SX flowsheet, it is essential to quantify the performance for various design and separation conditions. This paper attempts to address the challenge by utilizing an equilibrium and process modeling approach. Results from a bench-scale study performed on a 10 g/L rare earth salt mixture were used in studying the extraction/stripping behavior and developing equilibrium models. DEHPA with TBP as a phase modifier was used as an extractant, while hydrochloric acid was utilized as a stripping agent. The results obtained were used in developing extraction/stripping models, which were integrated into a process framework of a SX train in a Matlab/Simulink environment. The models were programmed as a function block routine and used for developing a flowsheet, which was simulated for differing separation and design conditions. To identify optimum stage combinations, a particle swarm optimization (PSO) routine was developed and implemented for each SX train. Recovery and purity of elements of interest were used as objective function criteria. The stage combination leading to the minimization of the objective function was used to identify the optimum stage combination for a series of SX trains to attempt a balance of purity and recovery. The models and optimization method were implemented to separate a feed mixture containing REEs, which indicated that 99.52 and 85.41 percent purity is achievable for Yttrium and Lanthanum separation using 8-12-3 and 10-3-5 stage combination for loading, scrubbing, and striping. The model also indicated difficult separability between neodymium, praseodymium, and cerium.

Srivastava, Vaibhav (ORCID:0000000212645987)↗

DOE OSTI2025

Standardization of ancillary installation tooling for SRF cavities at Fermilab

For assemblies of cavities in cleanrooms, single-use tooling systems are made for the alignment and installation of ancillary components such as couplers and bellows. To minimize the number of tooling sets created, a design has been created to standardize alignment features to allow for assembly of different components with one set of tooling. A prototype set of tooling has been developed to with the required degrees of freedom for multiple assemblies while minimizing deformation during the assembly process. Prototype designs have been created for PIP-II SSR2 and 650 Cavities and for AUP Crab Cavities. Using 3D printing, this tooling can be quickly adjusted to allow for different ancillary components. The development process and status of the design will be discussed.

Narug, C. [Fermilab]↗

DOE OSTI2024

Standardization of Ancillary Installation Tooling for SRF Cavities at Fermilab

For assemblies of cavities in cleanrooms, single-use tooling systems are made for the alignment and installation of ancillary components such as couplers and bellows. To try and minimize the amount of tooling sets used, a design has been created to standardize alignment features to allow for assembly of different components with one set of tooling. A prototype set of tooling has been developed to with the required degrees of freedom for multiple assemblies while minimizing deformation during the assembly process. Prototype designs have been created for PIP-II SSR2 and 650 Cavities and for AUP Crab Cavities. Using 3D printing, this tooling can be quickly adjusted to allow for different ancillary components. The development process and status of the design will be discussed.

Narug, Colin↗

DOE OSTI2021

Optimal toolpath design of additive manufactured composite cylindrical structures

Structural design optimization for additive manufacturing is primarily focused on planar layer-by-layer processes and design of composite cylindrical structures does not often accommodate manufacturing constraints. In this study, we propose to optimize the toolpath trajectory of additively manufactured composite cylinders comprised of multiple thin cylindrical annuli. Additionally, our printing process is based on direct ink writing in which short carbon fibers in a thermoset resin are extruded through a moving nozzle to build up a structure. Since the fibers are primarily aligned in the flow direction of the extrudate, the printing trajectory influences the material properties of the composite structure. To accommodate this, we define the toolpaths as contours of parameterized level-set functions. This parameterization allows us to optimize the material properties and impose manufacturing constraints such as no-overlap, no-sag, minimum radius of curvature, and continuity of the toolpaths. Several examples illustrate the optimization procedure.

42 ENGINEERING↗

DOE OSTI2020

Morphological–Electrical Property Relation in Cu(In,Ga)(S,Se) 2 Solar Cells: Significance of Crystal Grain Growth and Band Grading by Potassium Treatment

Abstract Solution‐processed Cu(In,Ga)(S,Se) 2 (CIGS) has a great potential for the production of large‐area photovoltaic devices at low cost. However, CIGS solar cells processed from solution exhibit relatively lower performance compared to vacuum‐processed devices because of a lack of proper composition distribution, which is mainly instigated by the limited Se uptake during chalcogenization. In this work, a unique potassium treatment method is utilized to improve the selenium uptake judiciously, enhancing grain sizes and forming a wider bandgap minimum region. Careful engineering of the bandgap grading structure also results in an enlarged space charge region, which is favorable for electron–hole separation and efficient charge carrier collection. Besides, this device processing approach has led to a linearly increasing electron diffusion length and carrier lifetime with increasing the grain size of the CIGS film, which is a critical achievement for enhancing photocurrent yield. Overall, 15% of power conversion efficiency is achieved in solar cells processed from environmentally benign solutions. This approach offers critical insights for precise device design and processing rules for solution‐processed CIGS solar cells.

Kim, Joo‐Hyun↗

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 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↗