Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “process analysis”

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.

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

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Processing behavior evolution of recycled polypropylene: An integrated experimental and Computer-Aided engineering simulation study

Polypropylene (PP) comprises 21% of global plastics production and 18% of plastics waste, yet less than 1% of solid-waste PP is recycled in the United States (U.S.), representing significant environmental and economic challenges. Mechanical recycling, the most prevalent recycling method, subject's materials to thermomechanical stresses, which typically degrade polymer properties, affecting the quality of polymer products. This study replicates the impact of mechanical recycling through multiple extrusion cycles to examine the effects on PP's processing behavior. Dynamic scanning calorimetry (DSC) measurements showed stable melting behavior across all processing conditions, while crystallization analysis exhibited consistent shifts in kinetic parameters. Rheological characterization demonstrated progressive viscosity reductions through successive cycles, particularly pronounced at elevated reprocessing temperatures. Here, the integration of this experimental data into injection molding simulations showed that recycled PP maintains viable processing characteristics. Our findings establish quantitative correlations between processing history and material behavior, enabling optimization of processing parameters directly rather than relying on trial-and-error approaches. While these results reflect idealized recycling conditions with minimal contamination, they provide a framework for understanding fundamental property evolution during mechanical recycling.

42 ENGINEERING↗
DOE OSTI2021

A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

14 SOLAR ENERGY↗
DOE OSTI2026

Sustainable Ethylene via Chemical Looping – Oxidative Dehydrogenation

This Phase I final report evaluates chemical looping–oxidative dehydrogenation as a lower-energy and cost-competitive alternative to conventional ethane steam cracking for ethylene production. The project combined catalyst development and experimental testing with process modeling, techno-economic analysis, and life-cycle assessment. Results indicate that the proposed process could improve olefin production, reduce energy use, and lower production costs, particularly when integrated with carbon capture and renewable electricity. The report also identifies remaining technical, environmental, and safety considerations and presents a technology maturation plan focused on longer-term catalyst evaluation and advancement toward pilot-scale demonstration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Toward the Advanced Manufacturing of Land-Based Wind Turbine Blades: Preprint

The National Renewable Energy Laboratory (NREL) and General Electric (GE) are partners within the Additive and Modular Enabled Rotor Blades and Integrated Composites Assembly (AMERICA) project. AMERICA aims to develop advanced manufacturing solutions to reduce labor and cycle time while increasing recyclability of wind turbine blades. The project is funded by the Advanced Manufacturing Office (AMO) of the U.S. Department of Energy (DOE). This paper describes the techno-economic analysis of the novel manufacturing process applied to the tip of the blade of a representative land-based wind turbine. A comparison to a standard manufacturing process is established, highlighting challenges and opportunities. Several uncertainties affect the analysis, but with the current set of assumptions, the tip adopting advanced manufacturing is predicted to lower labor by 21%, cycle time by 39%, and total blade tip costs by 15% while simultaneously increasing production quality and adopting recyclable thermoplastic resin.

3D printing↗
DOE OSTI2024

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparing energy and water use of aqueous and gas-based metalworking fluids

Gas-based metalworking fluids (MWFs) have been proposed as alternative coolants and lubricants in machining operations to mitigate concerns surrounding water use and pollution, industrial hygiene, occupational health, and performance limitations associated with water-based (aqueous) MWFs that are ubiquitously used in the metals manufacturing industry. This study compares the primary energy and water use associated with the consumptive use, delivery, and disposal of aqueous MWFs with three gas-based MWFs in the literature-minimum quantity lubricant-in-compressed air (MQL), liquid/gaseous N-2, and liquid/supercritical CO2. The comparison accounts for reported differences in machining performance in peer-reviewed experimental studies across several machining processes and materials. The analysis shows that despite the reported improvement in tool life with N-2 and CO2-based MWFs, the electricity- and water-intensive separation and purification processes for N-2 and CO2 lead to their higher primary energy and water use per volume of material machined relative to water-based MWFs. Although MQL is found to have lower primary energy use, significant consumptive water use associated with the vegetable oil commonly used with this MWF leads to higher overall water use than aqueous MWF, which is operated in a recirculative system. Gas-based MWFs thus shift the water use upstream of the manufacturing plant. Primary energy and water use of gas-based MWFs could be reduced by focusing on achieving higher material removal rates and throughput compared to aqueous MWF instead of solely targeting improvements in tool life. Additionally, the consumptive use of CO2 and N-2 MWFs could be minimized by optimizing their flow rates and delivery to precisely meet the cooling and lubrication needs of specific machining processes instead of flooding the tool and workpiece with these gases. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

cutting fluids↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2022

HERO WEC V1.0 - Electrical PTO Deployment Data and Analysis

This submission includes the processed and raw field electrical data from NREL's August 2022 HERO WEC (hydraulic and electric reverse osmosis wave energy converter) deployment at Jennette's Pier for the electrical PTO (power take-off).

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Gas-mapping 3D imager measurement techniques and method of data processing

Measurement approaches and data analysis methods are disclosed for combining 3D topographic data with spatially-registered gas concentration data to increase the efficiency of gas monitoring and leak detection tasks. Here, the metric for efficiency is defined as reducing the measurement time required to achieve the detection, or non-detection, of a gas leak with a desired confidence level. Methods are presented for localizing and quantifying detected gas leaks. Particular attention is paid to the combination of 3D spatial data with path-integrated gas concentration measurements acquired using remote gas sensing technologies, as this data can be used to determine the path-averaged gas concentration between the sensor and points in the measurement scene. Path-averaged gas concentration data is useful for finding and quantifying localized regions of elevated (or anomalous) gas concentration making it ideal for a variety of applications including: oil and gas pipeline monitoring, facility leak and emissions monitoring, and environmental monitoring.

Thorpe, Michael↗
DOE OSTI2022

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors, this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. Here, the results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tetrafluoroboric Acid Digestion for Accurate Determination of Rare Earth Elements in Coal and Fly Ash by ICP-MS Analysis

Coal and coal-related fly ash often contain rare earth elements (REEs) that have the potential to be utilized as valuable mineral resources. Accurately determining the REE content in coal and fly ash is crucial for resource evaluation. The conventional approach involves using hydrofluoric acid (HF) to dissolve silicates and release REEs, which, however, prolongs the digestion process due to the additional step of complexing fluoride ions (F−) with boric acid (H3BO3). Determining the correct amount of H3BO3 for neutralization can be challenging, and in some instances, the binding of fluoride ions with certain lanthanides (Lns) hampers the accurate determination of all 14 naturally occurring rare earth elements in a single digestion batch by inductively coupled plasma mass spectrometry (ICP-MS). In this study, we present an alternative method that achieves the accurate determination of all 14 naturally occurring REEs using tetrafluoroboric acid (HBF4) followed by ICP-MS analysis. This approach eliminates the need for an F− complexing step. We tested this method on certified REE reference materials, including NIST 1632e (coal) and NIST 1633c (fly ash), as well as the REE geological reference material USGS AGV-1 (andesite). Our results demonstrated excellent recovery rates (relative standard deviation, RSD < ±10%), with a correlation coefficient (r2) exceeding 0.99. Using this method, we investigated the concentrations of all 14 REEs in coal and fly ash samples collected from various locations in the southwestern USA. This improved digestion technique streamlines the analysis process and enhances the accuracy of REE determination, facilitating a more comprehensive evaluation of REE-rich coal and fly ash deposits for resource exploration.

58 GEOSCIENCES↗
DOE OSTI2023

Magnesium production by molten salt electrolysis with liquid tin cathode and multiple effect distillation

Low-cost clean primary production of magnesium metal is important for its use in many applications, from light-weight structural components to energy technologies. This work describes new experiments and cost and emissions analysis for a magnesium metal production process. The process combines molten salt electrolysis of MgO using MgF₂-CaF₂ electrolyte and a reactive liquid tin cathode, with gravity-driven multiple effect thermal system (G-METS) distillation to separate out the magnesium product, and re-use of the tin. Electrolysis experiments with carbon anodes showed current yield above 90%, while a yttria-stabilized zirconia solid oxide membrane (SOM) anode experiment showed 84% current yield. G-METS distillation is an important component of the envisioned process. It can potentially lower costs and energy use considerably compared with conventional magnesium distillation. Techno-economic analysis including detailed mass and energy balances shows that this electrolyte composition could lower costs by utilizing CaO, which is the primary impurity in MgO, as the Hall-Héroult process uses the sodium impurity in alumina. Analysis options include: raw material types (magnesite rock vs. brine or seawater), drying and calcining using electricity vs. natural gas, and carbon vs. SOM anode type. Using SOM inert anodes results in a cost premium around 10%–15%, mostly due to higher electrical energy usage resulting from membrane resistance, and reduces GHG emissions by approximately 1 kg CO₂/kg Mg product. Capital and operating cost estimates, and cradle to gate greenhouse gas (GHG) emissions analysis under several raw material and process technology scenarios, show comparable costs and emissions to those of aluminum production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermal Activation of Zirconium(IV) Acetylacetonate Catalysts to Enhance Polyurethane Synthesis and Reprocessing

Carbamate formation and exchange catalysts enable efficient polyurethane (PU) manufacturing, as well as emerging recycling and reprocessing methods for PU thermosets. Zirconium β-diketonate complexes, such as Zr acetylacetonate [Zr(acac) 4 ], are effective alternatives to toxic organotin catalysts that have been used for PU reprocessing. Here, we report that Zr(acac) 4 undergoes a thermally activated process in the PU network during reprocessing that transforms it into a more active carbamate exchange catalyst. This process is associated with the irreversible loss of acetylacetonate ligands and is not observed for the more sterically hindered Zr 2,2,6,6-tetramethyl-3,5-heptanedione [Zr(tmhd) 4 ] complex. Crossover experiments between PU thermoplastics indicated enhanced carbamate exchange after the thermal activation of Zr(acac) 4 in the presence of one of the PUs, whereas a sample of Zr(acac) 4 activated in the absence of the PU had no catalytic activity. Thermal gravimetric analysis suggested that this process is associated with the loss of one protonated acac ligand. Stress relaxation analysis of PU thermosets indicated a distinct change in the characteristic relaxation time associated with the thermal activation of Zr(acac) 4 at temperatures above 140 °C; no such change was observed for samples reprocessed using Zr(tmhd) 4 . Density functional theory and molecular experiments suggest that irreversible ligand exchange of acac with alkoxide or carbamate reduces the activation energy for urethane formation and reversion. Furthermore, the Zr(acac) 4 catalyst activated in the presence of a PU’s polyol precursor provided more porous and less dense PU foams compared to those made using the unactivated Zr(acac) 4 catalyst. Furthermore, these findings are important for developing improved PU synthesis and recycling processes. Thermally activating a catalyst during reprocessing may provide more nuanced control of the in-use and reprocessing characteristics of PU thermosets.

Alcohols↗
DOE OSTI2020

RAMSeS: Rapid Analysis of Mission Software Systems

Over the past few decades, software has become ubiquitous as it has been integrated into nearly every aspect of society, including household appliances, consumer electronics, industrial control systems, public utilities, government operations, and military systems. Consequently, many critical national security questions can no longer be answered convincingly without understanding software, including its purpose, its capabilities, its flaws, its communication, or how it processes and stores data. As software continues to become larger, more complex, and more widespread, our ability to answer important mission questions and reason about software in a timely way is falling behind. Today, to achieve such understanding of third-party software, we rely predominantly on the ability of reverse engineering experts to manually answer each particular mission question for every software system of interest. This approach often requires heroic human effort that nevertheless fails to meet current mission needs and will never scale to meet future needs. The result is an emerging crisis: a massive and expanding gap between the national security need to answer mission questions about software and our ability to do so. Sandia National Laboratories has established the Rapid Analysis of Mission Software Systems (RAMSeS) effort, a collaborative long-term effort aimed at dramatically improving our nation’s ability to answer mission questions about third-party software by growing an ecosystem of tools that augment the human reverse engineer through automation, interoperability, and reuse. Focusing on static analysis of binary programs, we are attempting to identify reusable software analysis components that advance our ability to reason about software, to automate useful aspects of the software analysis process, and to integrate new methodologies and capabilities into a working ecosystem of tools and experts. We aim to integrate existing tools where possible, adapt tools when modest modifications will enable them to interoperate, and implement missing capability when necessary. Although we do hope to automate a growing set of analysis tasks, we will approach this goal incrementally by assisting the human in an ever-widening range of tasks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Assessment of small mechanical wastewater treatment plants: Relative life cycle environmental impacts of construction and operations

Many slow growing and shrinking rural communities struggle with aging or inadequate wastewater treatment plants (WWTPs), and face challenges in constructing and operating such facilities. Although existing literature has provided insight into the environmental sustainability of large facilities, including both the construction and operational phases, these studies have not examined small, rural facilities treating less than 7,000 m 3 /d (1.8 MGD) of wastewater in adequate depth and breadth. In this study, a detailed inventory of the construction and operational data for 16 case studies of small WWTPs was developed to elucidate their environmental life cycle impacts. Conventional LCA framework was followed. The results show that the environmental impacts of both the construction and operational phases are considerable. Operational impacts are highly related to energy usage. Improving energy efficiency of a plant may reduce the environmental impacts related to operations. Construction impacts can vary considerably between facilities. Process-related factors (e.g., concrete and reinforcing steel used in basins) are typically sized using the design flow; thus much of the variability in construction impacts among plants stems from the non-process related infrastructure. Multiple regression analysis was used as an exploratory tool to identify which non-process related plant aspects contribute to the variable environmental impact of small WWTPs. These factors include aluminum, cast iron, and the capacity utilization ratio (defined as the ratio of average flow to design flow). Furthermore, industry practitioners should consider these factors when aiming to reduce the environmental impacts of a small WWTP related to construction. Scenario sensitivity analyses found that the environmental impact of construction became smaller with longer design life, and the end-of-life consideration does not heavily influence the environmental sustainability of a WWTP.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Resveratrol Ameliorates Lipopolysaccharide-Induced Sudden Sensorineural Hearing Loss in In Vitro Model through Multitarget Antiapoptotic Mechanism Based on Network Pharmacology and Molecular Docking

Objective. To explore the effects of resveratrol (RSV) on hair cell apoptosis caused by sudden sensorineural hearing loss (SSNHL) and its effect on lipopolysaccharide-induced apoptosis of HEI-OC1 cells. Methods. We used the network pharmacology method to screen molecules related to RSV for the treatment of SSNHL and analyzed these molecules and their enriched biological processes and signaling pathways through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. We selected hub genes related to apoptosis using protein-protein interaction (PPI) analysis for in vitro and molecular docking verification. Results. Eighty overlapping genes were identified as potential targets for RSV treatment of SSNHL. Further GO analysis showed that the biological processes were mainly related to toxicity, cell proliferation, and lipopolysaccharide reactions. KEGG analysis showed that the AGE-RAGE signaling pathway in diabetic complications, Kaposi’s sarcoma-associated herpesvirus infection, FoxO signaling pathway, PI3K-Akt signaling pathway, and other inflammatory signaling pathways were concentrated. AKT1, STAT3, JUN, TNF, TP53, MAPK3, CASP3, and VEGFA were screened as HUB genes using PPI analysis. The apoptosis-related proteins TNF, CASP3, AKT1, and TP53 were selected for in vitro experiments, which showed that mRNA was significantly different before and after RSV intervention, confirming that the corresponding protein receptors could bind well with RSV. Conclusion. RSV mainly affects the prognosis of SSNHL through anti-inflammatory effects and may improve hair cell apoptosis caused by inflammatory factors through multitargeted interventions involving TNF, CASP3, AKT1, and TP53.

Ye, Shiming↗
DOE OSTI2020

Extracting dependencies between network assets using deep learning

A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.

Carroll, Thomas E.↗
DOE OSTI2021

Enabling Load Following Capability in the Transatomic Power MSR

This project is dedicated towards designing a fuel processing system that enables liquid-fueled molten salt reactors (MSR) to load follow by removing the dissolved xenon in the fuel salt. As one of the Gen-IV nuclear reactor concepts, the molten salt reactor receives increasing development interests in the recent years. One distinguishing feature of the liquid-fueled molten salt reactor is its improved ability to operate in a load-following mode by including the unique online fission product removal system. Load-following means that the reactor changes its power output based on the demand on the grid. Most of the current operating nuclear reactors have limited load-following ability and operate as the base load on the grid. Due to the rapid increase of solar energy, the requirement on load-following capacity is significantly increased because of the varying power output of the solar panels, yet the traditional load-following capacity is expected to decrease as the decarbonization of the grid continues. Therefore, the ability to perform load-following operation for the nuclear reactors will greatly enhance the resilience of the grid and make nuclear energy more economically competitive. This load-following feature is included in many commercial molten salt reactor designs, such as the designs by Transatomic Power, Terrestrial Energy, and Flibe Energy. Unfortunately, detailed analysis of the fuel processing system for commercial scale MSRs is still lacking, as well as how the fuel processing quantitively impacts the load-following operation. Moreover, experimental data for many of the underlying physics of fuel processing is limited. This project aims to pave the way for the fuel processing technology to advance to the commercial stage by performing combined experimental and simulation research. During the project period, four interconnected aspects of the development of the fuel processing system in liquid-fueled molten salt reactors are investigated. These aspects are the simulation and analysis of the fission product removal system, the fuel cycle simulation, the coupled reactor neutronics and thermal hydraulics transient simulation, and the gaseous fission product removal experiment. Multiphase CFD simulations are performed for components of the processing systems, and simplified air-water experiments are carried out to provide validation data. It is concluded that the CFD simulation can satisfactorily predict the system level performance of the components, and engineering models are constructed based on this success. Fuel cycle analysis is performed for two representative MSR design, the MSBR and the Transatomic Power MSR. Open-source code SaltProc is developed to incorporate the unique fuel processing system of the MSRs. It is concluded that the removal of xenon is essential for load-following operation in thermal spectrum MSR and Molten Salt Breeder Reactor. For the Transatomic Power MSR, the xenon poisoning effect is negligible due to its relatively fast neutron spectrum, though the overall fuel cycle economics still benefits from the removal of xenon. Coupled reactor neutronics and thermal hydraulics transient simulation is performed specifically for the Transatomic Power MSR. It is concluded that the reactor core design could perform power ramping fast enough to satisfy load-following operation. Combining the findings from each aspect, it is concluded that the load-following operation of a thermal neutron MSR is dependent upon the removal of xenon, which could be achieved for a commercial sized reactor using continuous inert gas sparging in a separate system with reasonable dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗