SEARCH · Engineering Papers

Results for “operational processes”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Additive friction stir deposition of SS316: Effect of process parameters on microstructure evolution

Solid state nature of additive friction stir deposition (AFSD) additive manufacturing process is very advantageous in terms of defect formation and microstructural refinement in the material. Current study presents the process optimization, microstructural evolution and kinetics of recrystallization for AFSD deposited low stacking fault energy material - SS316. As deposited microstructure shows equiaxed ultra fine grains with an average grain size of ~5.0 ± 0.5 μm. Shear deformation at high temperature during processing leads to the operation of restoration mechanisms. Observation of necklace type microstructure in the as deposited SS316 is attributed to discontinuous dynamic recrystallization during processing. Recrystallization kinetics of the AFSD SS316 is characterized using Johnson-Mehl-Avarami-Kolmogorov (JMAK) model. Deformation – thermal cycling during AFSD process resulted in inconsistent recrystallization kinetics. Variation in strain, strain rate and temperature during processing with processing parameters result in varying microstructure and tool wear. Further, high strength-ductility combination and sustained work hardening in as deposited SS316 appear to arise from transformation and twinning during deformation, leading to the formation of hierarchical twins and martensitic phase after deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Testing Rod Seal Leakage of a 700 HP Reciprocating Compressor

Methane emissions from reciprocating compressors in the U.S. natural gas industry account for over 72.4 Bcf per year according to a 2006 statement by the United States Environmental Protection Agency. Methane also has a global warming potential 50 times greater than carbon monoxide. Reciprocating compressors are the machinery type with the highest contribution to methane emissions at natural gas transmissions stations. The largest contributing factor comes from the sealing components in the packing components around the piston rod. SwRI, therefore, designed and setup a test loop to perform baseline packing leakage measurements on a four stage 700 HP JGT/4 compressor. The goal was to improve upon current packing leakage models and to compare new seals vs. used seals. The test loop design is described including the limits of operation. The Data Acquisition System (DAQ), including data measurements, is also fully described. The project shows the results of the commissioning process that verified the operation of all the components. Once the loop was commissioned, SwRI performed baseline packing leakage for multiple pressure ratios on each of the four stages of the compressor. The data was collected to develop an analytical model of the packing leakage. Finally, similar testing was performed after replacing the typical rod seal packing with used packing. The used packing leakage was compared to the baseline packing leakage.

03 NATURAL GAS↗

DOE OSTI2022

Gamma Driven Catalysis of Ammonia

Experiments were conducted to investigate a passive production mechanism for the world’s most energy intensive commodity, ammonia. A novel method, gamma catalyzed ammonia production at ambient conditions, was investigated. Ammonia is currently produced through the highly energy intensive Haber-Fritz process, which requires an operation pressure of 400 atmosphere and 600 degrees Celsius. Due to the high demand and need for ammonia, the Haber-Bosch process consumes 25% all energy produced globally. Reported herein was an attempt to produce ammonia at ambient temperature (20 C) and ambient pressure (1 atm), through a novel process developed at PNNL, gamma driven catalysis of ammonia. Although the measurements of the ammonia production suggest wild success, reports in the literature by Gao et.al. suggest an experimental positive bias in the results. To rule out the potential positive bias, multiple additional production campaigns would be needed to with an alternate analysis technique such as ion chromatography, as suggested by Gao et.al. Unfortunately, due to this late determination of potential positive bias, the results of this study remain inconclusive to the feasibility of gamma driven catalysis of ammonia and more work is needed to describe the chemical evolution with time. The results are a first step and demonstrate that gamma-catalyst mediated reactions are possible. This represents a key opportunity to explore the fundamental chemistry of high band gap catalysts that can change the paradigm of radiation, transforming it from a waste to a valuable energy source.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

A Tandem Electrolysis Process for Multi-Carbon Chemical Production from Carbon Dioxide (Final Technical Report)

a two-step CO 2 electroreduction process for selective production of acetate and ethylene was successfully developed at the kW-scale. The CO 2 and CO electrolyzers were first investigated individually on the Watt-scale to achieve high current densities and more durable operation by using a reinforced GDL. High CO 2 conversion was obtained in the first CO 2 electrolyzer to produce a CO-dominant gas stream with minimal CO 2 , and highly pure acetate stream was produced in the second CO electrolyzer by using NiFe anode, which promoted alcohol oxidation to carboxylates. The two-step process operated stably for 200 h with acetate and ethylene as the major C 2+ products. Degradation mechanism study revealed that the flooding and the salt formation in the GDL is likely the biggest contributor to the performance degradation for both CO 2 and CO electrolyzers. A 1,000 cm 2 CO electrolyzer stack was then designed, fabricated, and operated up to a total current of 300 A along with a 500 cm 2 CO 2 electrolyzer stack which was operated up to a total current of 100 A. The CO electrolyzer stack demonstrated good stability at 300 A for at least 125 h at a carbon selectivity >96%. The impact of CO 2 , O 2 , N 2 , SO x , and NO x gas impurities on the CO electrolyzer stack was studied and a relatively high resistance to these contaminants was demonstrated. Electroreduction of CO 2 into acetic acid was also demonstrated to be environmentally favorable when compared to the traditional production of acetic acid when powered by renewable electricity. Additionally, electricity cost was identified as the primary source of cost sensitivity indicating substantial economic improvements could be achieved by continuing to drive down the cost of renewable electricity. Overall, the presented approach demonstrates the feasibility of the two-step electrochemical CO 2 reduction process for the effective production of C 2+ products at the kW-scale which should inspire future scaling efforts accelerating commercialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗

DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

DOE OSTI2022

The Energy in Modular (EMOD) Buildings Method: A Guide to Energy-Efficient Design for Industrialized Construction of Modular Buildings

Industrialized construction has immense potential to address the growing need globally to build and upgrade the building stock to be affordable, energy-efficient, and resilient. It can also help achieve the United States' goal of a 50% reduction in U.S. greenhouse gas (GHG) emissions by 2030. Despite this potential, and the ever-increasing push for electrification and decarbonization of households in the United States, industrialized construction has not yet been leveraged specifically to help address these challenges and accelerate the pathway to meet these goals. The National Renewable Energy Laboratory (NREL) aims to claim this missed opportunity by focusing on delivering affordable, grid-efficient net-zero energy (NZE) modular buildings for underserved communities to ensure an equitable transition to the future of clean energy, accelerate decarbonization of the built environment, and support the development of a high-productivity construction and energy efficiency workforce. The Energy in Modular (EMOD) method is our approach to designing, producing, and delivering affordable, net-zero energy, low-carbon, and healthier buildings at scale. The following energy efficiency strategies are part of the scope of this guide: envelope thermal control, envelope infiltration control, mechanical, electrical, and plumbing systems, smart controls, and solar plus storage. We draw synergies between design for manufacturing and assembly, process optimization, retrofit technologies, and digitization. Our goal is to influence the improvement and production of buildings to increase performance, enhance energy efficiency, and reduce GHG emissions. This guide documents the research and development efforts initiated by a set of design objectives to "modularize" a set of energy efficiency and low-carbon strategies into a housing unit while preserving and enhancing energy efficiency benefits and decarbonization pathways. This guide is intended to serve as a framework for housing developers, housing agencies, architects, energy experts, and process engineers or factory operator personnel who are critical to today's modular builder teams. This guide focuses on specific energy efficiency strategies, decarbonization pathways, and associated processes as part of NREL's research efforts. Stakeholders may substitute other means, methods, and technologies for the ones evaluated in this study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

DOE OSTI2025

Roadmap for Assessing Fuel Reprocessing in Fluoride-Based Salts

This joint report assesses the pyroprocessing of used nuclear fuel from molten fluoride salts being conducted between Idaho National Laboratory and Argonne National Laboratory. The goal of this report is to identify the research and development gaps needed to reduce the technical risks of extending pyroprocessing technologies and unit operations to molten fluoride salts used in molten salt reactors (MSRs). Assessing and performing the tasks outlined in this report will help mitigate the technical risks and design appropriate flowsheets for reprocessing fuel and coolant salts. These suggested tasks will provide necessary data to implement the development of unit operations. Sections are highlighted to identify processes that need to be assessed and unit operations that may be used in fluoride-based chemistries. Research and development needs are listed and discussed including re-fluorination methods, electrowinning for separations, reference electrode development, materials compatibility, salt purification/re-fluorination, and waste disposition. This report will examine the technical challenges associated with pyroprocessing in molten fluoride-based salt and outline approaches to increase the technical readiness level of pyroprocessing in molten fluoride salts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Energy efficient membrane-based process for CO 2 capture

Processes and systems for the energy efficient capture of CO 2 from a flue gas stream such as produced or resulting from power plant operation, are provided. The processes and systems integrate the use of high CO 2 /N 2 selectivity membranes and high CO 2 flux membranes, to capture CO 2 . Useful membranes can desirably be graphene oxide-based membranes.

Li, Shiguang↗

DOE OSTI2026

Chemical-Free Lithium Separation from High-Salinity Brines Using Model-Informed and Machine Learning-Optimized Multi-Column Zwitterionic Chromatography

Direct Lithium Extraction (DLE) technologies often struggle to produce high-purity lithium salts from high-salinity brines, as current approaches require chemical-based elution, regeneration, and precipitation steps, resulting in significant environmental footprints. A novel salt fractionation approach using carboxybetaine resin, known as zwitterionic chromatography (ZIC), has demonstrated that lithium ions can be separated from divalent cations under high-salinity conditions using only water as eluent, with no regeneration required. To enable continuous and scalable deployment of this approach, we developed a chemical-free Multi-column Zwitterionic Chromatography (MZC) process and its theoretical and process models. To predict and optimize this nontraditional separation system, we introduced a novel anti-Langmuir isotherm, and the isotherm parameters were estimated through a machine learning-driven optimization based on artificial neural network ensembles with numerical feasibility assessment. Using machine learning-driven optimization, the MZC process achieved 98.0% lithium recovery, 99.5 % Li/(Li + Mg + Ca) purity, a 31.3% productivity increase, and a 33% reduction in water use compared to batch operation. The proposed MZC process enables lithium separation at $0.6-1.2 kg-1 Li, with costs dominated by resin manufacturing, while offering lower separation costs and carbon footprint compared with conventional carbonation. Overall, these findings position the MZC process as an effective polishing step within scalable and sustainable lithium production pipelines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗

DOE OSTI2021

Monitoring Radiochemical Processing Streams for the 238 Pu Supply Program with Process Pulse II

Oak Ridge National Laboratory (ORNL) is developing advanced spectroscopic and real-time monitoring capabilities to improve the timeliness of analytical measurements and process decisions for the 238Pu Supply Program. Reducing the time, resources, and costs associated with each production campaign is critical because overlapping campaigns will be required to meet the production goals of the National Aeronautics and Space Administration. Real-time, in situ analytical measurements in the heavily shielded hot cells at the Radiochemical Engineering Development Center (REDC) will allow for rapid process information feedback and operational benefits that help the 238Pu supply program scale-up production efforts. Noteworthy steps were taken during Campaign 5 to establish the ability to monitor processing streams in real time with spectrophotometry and a commercially available online monitoring software called The Unscrambler X Process Pulse II (PP) multivariate statistical process monitoring system by Camo Analytics (version 5.60). PP automates univariate-type calculations within the software itself and executes multivariate models built using The Unscrambler X (version 10.4 or newer). The Unscrambler is a commercially available data analysis software made by the same company. PP is composed of easy-to-use-tools for all personnel, including data scientists and technicians. The software can be used to plot analyte concentration profiles, spectral data, and other process variables in real time. All process data are represented in a single view with interactive charts useful for viewing how a process evolves over time.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2023

High Temperature Steam Electrolysis Process Model

The code models the operation of a high temperature steam electrolysis (HTSE) plant coupled with a nuclear power plant, and provides calculations of the process energy requirements; water feed stream flow rate requirements; process cooling requirements; process conditions such as temperature, pressure, and flow rate, throughout the process; product purity and flow rate, as well as data that can be used to determine the sizing, performance, and cost specifications of individual equipment components that comprise the system.

Wendt, DanielS (0000000344914296)↗

DOE OSTI2024

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Development of Methods for In-line Monitoring of Yield Stress During the Transfer of Radioactive Waste - 20435

Radioactive waste slurries at the Savannah River Site (SRS) and Hanford often behave as non-Newtonian fluids with a yield stress. The yield stress increases the size of equipment needed to transport or mix these slurries and can increase the risk of process upsets. This property is often measured by collection of samples and transportation to a laboratory, which can increase the risk of personnel exposure and even change the rheology. In addition, slurry rheology has been observed to change with time. Real-time in-line monitoring (RTIM) of rheological properties of slurries can have substantial benefits to critical processes which are currently in operation or will be part of future plans in Department of Energy (DOE) complex processes. The need for an appropriate RTIM technology that can potentially minimize or eliminate numerous sampling operations was recently identified. This research at Florida International University focuses on addressing the need for a reliable RTIM technology at US Department of Energy sites. The objective of this work is to investigate and develop appropriate and reliable technologies that can perform accurate and easy measurements of yield stress with minimal changes to the flow conditions at US Department of Energy sites. Use of ultrasound in longitudinal and shear modes was considered as a method for monitoring of yield stress variations with no disturbance to the flow. Measurement of shear wave velocity (in shear mode) and monitoring of sound velocity variations with start of flow from rest (longitudinal mode) are the underlying principles. Measurement of pressure loss and liquid rise (due to static differential pressure) during flow of slurries were two other methods that were considered and investigated. In addition, analysis of stability depth of a penetrometer in slurry medium (penetrometer method) revealed a potential suitability. This paper presents efforts associated with investigation of different methods mentioned earlier for kaolin-water mixtures at different concentrations. Theoretical analysis showed that all methods under investigation were capable of monitoring yield stress in a desirable range of 0 to 70 pascal. A bench scale test setup was constructed for investigation of pressure loss and liquid rise methods. Simulants at different concentrations were created for initial testing campaigns. For ultrasonic testing, effects of yield stress on sound propagation speed in longitudinal and shear modes were investigated for simulants placed inside PVC pipes. Parameters such as simulant concentration and pipe diameter were varied to find optimal values. It was found that spacing (or medium thickness) of 1/8 inch or less was necessary to observe echoes with sufficient strength. In addition, a significant effect of yield stress on sound propagation velocity was observed. For the liquid rise method, kaolin-water simulant at 1.17 specific gravity was pumped through a 1/4 inch pipe and liquid height was measured in a vertical riser branching off a three-way connection. Static gauge pressure was varied within [0.3 to 1.1] psi range by increase of pumping pressure and flow. Results showed consistent yield stress data within 10% deviation from values reported by a rheometer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗

DOE OSTI2023

Molecular Design of Functional Polymers for Silica Scale Inhibition

Silica polymerization, which involves the condensation reaction of silicic acid, is a fundamental process with wide-ranging implications in biological systems, material synthesis, and scale formation. The formation of a silica-based scale poses significant technological challenges to energy-efficient operations in various industrial processes, including heat exchangers and water treatment membranes. Despite the common strategy of applying functional polymers for inhibiting silica polymerization, the underlying mechanisms of inhibition remain elusive. In this study, we synthesized a series of nitrogen-containing polymers as silica inhibitors and elucidated the role of their molecular structures in stabilizing silicic acids. Polymers with both charged amine and uncharged amide groups in their backbones exhibit superior inhibition performance, retaining up to 430 ppm of reactive silica intact for 8 h under neutral pH conditions. In contrast, monomers of these amine/amide-containing polymers as well as polymers containing only amine or amide functionalities present insignificant inhibition. Molecular dynamics simulations reveal strong binding between the deprotonated silicic acid and a polymer when the amine groups in the polymer are protonated. Notably, an extended chain conformation of the polymer is crucial to prevent proximity between the interacting monomeric silica species, thereby facilitating effective silica inhibition. Furthermore, the hydrophobic nature of alkyl segments in polymer chains disrupts the hydration shell around the polymer, resulting in enhanced binding with ionized silicic acid precursors compared to monomers. Finally, our findings provide novel mechanistic insights into the stabilization of silicic acids with functional polymers, highlighting the molecular design principles of effective inhibitors for silica polymerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗