Search NASA⌕ Search

SEARCH · Search NASA

Results for “behavioral economics”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Characterizing Drought Behavior in the Colorado River Basin Using Unsupervised Machine Learning

Drought is a pressing issue for the Colorado River Basin (CRB) due to the social and economic value of water resources in the region and the significant uncertainty of future drought under climate change. Here, we use climate simulations from various Earth System Models (ESMs) to force the Variable Infiltration Capacity hydrologic model and project multiple drought indicators for the sub-watersheds within the CRB. We apply an unsupervised machine learning (ML) based on Non-Negative Matrix Factorization using K-means clustering (NMFk) to synthesize the simulated historical, future, and change in drought indicators. The unsupervised ML approach can identify sub-watersheds where key changes to drought indicator behavior occur, including shifts in snowpack, snowmelt timing, precipitation, and evapotranspiration. While changes in future precipitation vary across ESMs, the results indicate that the Upper CRB will experience increasing evaporative demand and surface-water scarcity, with some locations experiencing a shift from a radiation-limited to a water-limited evaporation regime in the summer. Large shifts in peak runoff are observed in snowmelt-dominant sub-watersheds, with complete disappearance of the snowmelt signal for some sub-watersheds. The work demonstrates the utility of the NMFk algorithm to efficiently identify behavioral changes of drought indicators across space and time and to quickly analyze and interpret hydro climate model results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

What matters the most? Understanding individual tornado preparedness using machine learning

Scholars from various disciplines have long attempted to identify the variables most closely associated with individual preparedness. Therefore, we now have much more knowledge regarding these factors and their association with individual preparedness behaviors. However, it has not been sufficiently discussed how decisive many of these factors are in encouraging preparedness. In this article, we seek to examine what factors, among the many examined in previous studies, are most central to engendering emergency preparedness in individuals particularly for tornadoes by utilizing a relatively uncommon machine learning technique in disaster management literature. Using unique survey data, we find that in the case of tornado preparedness the most decisive variables are related to personal experiences and economic circumstances rather than basic demographics. Our findings contribute to scholarly endeavors to understand and promote individual tornado preparedness behaviors by highlighting the variables most likely to shape tornado preparedness at an individual level.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Fire behavior and risk analysis in spacecraft

Practical risk management for present and future spacecraft, including space stations, involves the optimization of residual risks balanced by the spacecraft operational, technological, and economic limitations. Spacecraft fire safety is approached through three strategies, in order of risk: (1) control of fire-causing elements, through exclusion of flammable materials for example; (2) response to incipient fires through detection and alarm; and (3) recovery of normal conditions through extinguishment and cleanup. Present understanding of combustion in low gravity is that, compared to normal gravity behavior, fire hazards may be reduced by the absence of buoyant gas flows yet at the same time increased by ventilation flows and hot particle expulsion. This paper discusses the application of low-gravity combustion knowledge and appropriate aircraft analogies to fire detection, fire fighting, and fire-safety decisions for eventual fire-risk management and optimization in spacecraft.

Friedman, Robert↗
DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simultaneous x-ray and neutron 4D tomographic study of drying-driven hydro-mechanical behavior of cement-based materials at moderate temperatures

The drying of cement-based materials is intimately related to their durability, which has significant economic, social and environmental repercussions. The evolution of the saturation of the pore network and the associated drying shrinkage are in fact leading causes of cracking and of the ensuing penetration of aggressive chemicals. This process is highly heterogeneous, due to the thermo-hydric spatial gradients developing in the material from the exposed surfaces to its core and because of local effects, driven by the intrinsically heterogeneous micro-structure (e.g., by the distribution of pores and aggregates). It follows that macroscopic, sample-scale measurements cannot fully disclose the complexity of the underlying processes. In the last few decades, significant advances in full-field techniques have allowed an unprecedented insight into these local processes. For cement-based materials, x-ray and neutron tomography lend themselves as ideal, and highly complementary, tools for the study of their thermo-hydro-mechanical behavior. Notably, the high sensitivity to density variations of x-ray imaging gives access to the developments of fractures, in 4D (3D + time). On the other hand, neutron tomography allows the study of the evolution of the moisture field in 4D, thanks to its high hydrogen sensitivity. The combination of these two techniques provides a unique insight in thermo-hydro-mechanical couplings, e.g., the effect of cracks on the water content field. This contribution presents novel 5D datasets (3D tomographies along time, plus truly simultaneous x-ray and Neutron rapid acquisitions) in-operando of a cement paste and of a concrete sample heated at moderate temperatures (up to 140{sup ∘}C). The analysis of this 5D data-set (once aligned in time and across modalities) allows for example a quantification of the 4D moisture profiles which were found to predict an overall water loss at hydric equilibrium coherent with the corresponding analytical analysis. In the cement paste sample, the x-ray dataset captures the evolution of an extensive cracking network, opening and propagation toward the core of the sample. A novel analysis procedure is here proposed which allows the extraction of these fractures and the analysis of their interplay with local drying as captured through neutron imaging. This for example reveals the depth of penetration of drying in the vicinity of the fractures along time, which is essential for the assessment and calibration of hydro-mechanical coupled models.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Demonstration of a Probabilistic Technique for the Determination of Economic Viability of Very Large Transport Configurations

Over the past few years, modem aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This report contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft concept may be assessed. The assessment is evaluated with the FPI technique to determine the cumulative probability distributions of the design space, as bound by economic objectives and performance constraints. These distributions were compared to established targets for a comparable large capacity aircraft, similar in size to the Boeing 747-400. The conventional baseline configuration design space was determined to be unfeasible and marginally viable, motivating the infusion of advanced technologies, including reductions in drag, specific fuel consumption, wing weight, and Research, Development, Testing, and Evaluation costs. The resulting system design space was qualitatively assessed with technology metric "k" factors. The infusion of technologies shifted the VLT design into regions of feasibility and greater viability. The study also demonstrated a method and relationship by which the impact of new technologies may be assessed in a more system focused approach.

Mavris, Dimitri N.↗
DOE OSTI2025

New directions and principles for solvent extraction for recovery of lithium from aqueous brines and mineral leachates: A brief review

Increasing demand for lithium for manufacturing of batteries is fueling the unprecedented search for improved recovery and alternative sources. Wider source distribution, lower energy consumption, and greater sustainability make extraction of lithium from brines, both natural and process-derived, an attractive alternative to mineral ores. Solvent extraction, used industrially for production of metals, salts, and pharmaceuticals, has been investigated as a methodology for lithium recovery for several decades. However, industrial application of solvent extraction for lithium recovery has so far been limited. In contrast, direct lithium extraction using adsorbents based on inorganic minerals has rapidly advanced from research to commercialization. A comparison of solvent extraction processes to adsorption highlights these issues and explains the preference for adsorbents. Although the application of solvent extraction has been criticized for use of large amounts of acid, alkali, and organic solvents, steady progress has been made to improve its potential for industrial lithium production, spurred on generally by the advantages of solvent extraction in selectivity and throughput. Previously developed beta-diketone, organophosphate, and crown ether ligands are being adapted and improved. Their novel use with ionic liquids, deep eutectic solvents, and membrane technologies promises to expand capabilities for extraction of lithium from dilute aqueous sources while improving sustainability. Possibilities for further discovery and innovation abound. In this review, we provide a unique perspective from the field of solvent extraction starting with fundamentals such as ion-transfer theory and apply them to understanding lithium selectivity and extraction behavior. In conclusion, the results are cast in the light of the practical realities of developing economical solvent extraction processes.

Brine↗
NASA NTRS1979

Thermochemical modeling

The prediction of smoke behavior of a material using only the thermochemical properties geometry and flow, was investigated to determine economical methods for producing better materials. Spinoff, and honeycomb sandwich structures are discussed.

Ramohalli, K.↗
DOE OSTI2021

Improvement of the $\mathrm{BISON U_3Si_2}$ modeling capabilities based on multiscale developments to modeling fission gas behavior

Uranium silicide (U 3 Si 2 ) is a concept explored as a potential alternative to UO 2 fuel used in light water reactors (LWRs) since it may improve accident tolerance and economics due to its higher thermal conductivity and increased uranium density. U 3 Si 2 has been previously used in research reactors in the form of dispersion fuel, but operated at lower temperatures than commercial LWRs. The research reactor data illustrated that significant gaseous swelling occurs as the fuel burnup increases. Therefore, it is imperative to understand the fission gas behavior of U 3 Si 2 under higher temperature LWR operating conditions. In this work, molecular dynamics and phase-field modeling techniques are used to reduce the uncertainty in select modeling assumptions made in developing the fission gas behavior model for U 3 Si 2 in the BISON fuel performance code. These lower length scale informed models are then utilized in the validation of BISON U 3 Si 2 modeling capabilities to simulate the ATF-1 experiments irradiated in the Advanced Test Reactor (ATR). Sensitivity analysis (SA) and uncertainty quantification (UQ) are included as part of the validation process to identify where further experiments and lower length scale modeling would be beneficial. Here, the multiscale modeling approach utilized in this work can be applied to new fuel concepts being explored for both LWRs and advanced reactors (e.g., uranium nitride, uranium carbide).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Hydro-mechanical behavior of heated bentonite buffer for geologic disposal of high-level radioactive waste: A bench-scale X-ray computed tomography investigation

The behavior of heated bentonite buffer is critical for the security and long-term performance of a geological repository for high-level radioactive waste (HLW). While laboratory column experiments have been conducted to investigate compacted bentonite and coupled THMC (thermal-hydro-mechanical and chemical) processes for a moderate temperature range of up to 100 °C, data for a higher temperature range are limited. Understanding bentonite behavior and coupled THMC processes under higher temperatures (e.g., up to 200 °C) could allow for a more economic repository design and would expand the data and knowledge base for more reliable modeling. In this study, a bench-scale experiment was conducted in a compacted bentonite column experiencing both heating up to 200 °C in the center and hydration from a sand-clay boundary surrounding the column. During the experiment run for 1.5 years, frequent X-ray computed tomography (CT) scanning of bentonite provided insights into the spatiotemporal evolution of (1) hydration/dehydration, (2) clay swelling/shrinkage, (3) displacement, and (4) mineral precipitation. After the experiment, a comprehensive post-dismantling characterization of bentonite samples was conducted. Results showed that the bentonite hydration was axi-symmetrical despite the initial heterogeneity due to packing, confirming the ability of bentonite to seal fast flow/transport paths. Further, compared to a non-heated control experiment, the heated column showed greater CT density variations along the radial distance, indicating that homogenization of bentonite might be more difficult if a temperature gradient is maintained in the repository. Precipitation of an anhydrite layer occurred in the inner hot zone, pointing to potential concerns about salt precipitation causing canister corrosion. Ultimately, the experiments provided a high-resolution window into the strongly dynamic and coupled behavior of bentonite exposed to heating, hydration and swelling, which will be valuable for improving modeling of coupled processes, especially for the early state of a HLW repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1974

Fault tolerant programmable digital attitude control electronics study

The attitude control electronics mechanization study to develop a fault tolerant autonomous concept for a three axis system is reported. Programmable digital electronics are compared to general purpose digital computers. The requirements, constraints, and tradeoffs are discussed. It is concluded that: (1) general fault tolerance can be achieved relatively economically, (2) recovery times of less than one second can be obtained, (3) the number of faulty behavior patterns must be limited, and (4) adjoined processes are the best indicators of faulty operation.

Sorensen, A. A.↗
NASA NTRS2021

Geospatial Cluster Analysis of the State, Duration and Severity of Drought Over Paraíba State, Northeastern Brazil

Droughts threaten water resources, agriculture, socio-economic activities and the population at the global and regional level, so identifying areas with homogeneous drought behaviors is an important consideration in improving the management of water resources. The objective of this study is to identify homogenous zones over Paraíba State in relation to the state, duration and severity of droughts that have occurred over the last 20 years (1998–2017) using hierarchical cluster analysis based on both gauge-measured and Tropical Rainfall Measuring Mission (TRMM) estimated rainfall data (TMPA 3B42). The drought series were calculated using the Standardized Precipitation Index (SPI) based on eight time scales and were grouped according to drought state, duration and severity time series. The integrated results of state, duration and severity of droughts indicate that there is a basis for dividing Paraíba State into two major regions (a) Zone I, formed by Mata Paraibana and Agreste Paraibano, and (b) Zone II, composed by Borborema and Sertão Paraibano. This division is evident when assessing short-term droughts, but in the case of long-term droughts, Paraíba State has a high similarity in terms of drought state, duration, and severity. Factors such as proximity to the ocean, active climatic systems, and the local relief configuration were identified as influencing the drought regime. Finally, it is concluded that TMPA rainfall estimates represent a valuable source of data to regionalize and identify drought patterns over this part of Brazil and that other studies of this type should be carried out to monitor these phenomena based on other satellite-based rainfall data, including the Global Precipitation Mission (GPM).

SPI↗
DOE OSTI2021

A Circular Economy for Solar Photovoltaic System Materials: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As PV capacity increases, owners are also decommissioning older system assets. Estimates based on a 30-year lifetime assumption found that cumulative U.S. end-of-life (EoL) PV modules could total one million metric tons (Mt) by 2030 and up to 10 million Mt by 2050 (Weckend, Wade, and Heath 2016). Beyond maintenance replacements, early retirements that are due to efficiency upgrades and extreme weather, as well as PV deployment beyond earlier expectations, would increase these projections. PV system owners must evaluate equipment management options for used modules and system components retired during maintenance activities, refurbishment, repowering and system decommissioning. PV manufacturers must also evaluate material management options from customer returns, defects, and scrap. Management options for early retired and EoL PV system material include reuse, repair for reuse, recycling-based resource recovery, storage, and disposal. Disposal of PV system material increases the burden on landfill capacity, while reuse, repair for reuse, and recycling-based resource recovery (reuse/repair/recovery) options salvage valuable materials and provide secondary market opportunities and ancillary benefits (Weckend, Wade, and Heath 2016; EPA 2019c; SWEEP 2019). PV system owners may also decide store used modules and components as spares, or in the interim before a reuse or EoL management decision is made. Despite potential secondary market opportunities and the potential benefits associated with the repair/reuse/recovery of PV system material, anecdotal evidence suggests that in the United States decommissioned PV modules are stored, landfilled or otherwise disposed of (Salim et al. 2019; CPUC 2019b; DTSC 2019b; NREL 2019a). Some modules are being disposed of in municipal nonhazardous landfills and federally regulated hazardous treatment, storage, and disposal facilities, and others are being stored in warehouses until economically viable repair/reuse/recycling becomes available (CPUC 2019b; DTSC 2019b; NREL 2019a; Libby and Shaw 2018). As awareness of current practices grows, and the demand for critical PV module material increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for PV system materials. Circular economy principles attempt to transition from a "take-make-consume-dispose" linear economic system to a circular system that allows for the long life, and the reuse/repair/recovery of products and materials (Ellen MacArthur Foundation 2020). We begin this report by summarizing the drivers, barriers, and enablers to a circular economy for PV system materials in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the repair/reuse/recovery of PV materials, and potential civil and criminal liabilities associated with noncompliance. We then discuss state policies and initiatives in the United States that expressly address PV system decommissioning and repair/reuse/recovery of PV materials. We conclude by providing case studies of U.S. business models for the repair/reuse/recovery of PV system materials. Our results are based on legal and literature-based research and interviews with solar industry stakeholders, regulators, and policymakers.

14 SOLAR ENERGY↗
DOE OSTI2024

Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction

Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.

09 BIOMASS FUELS↗
NASA NTRS1996

A Framework for Modeling Human-Machine Interactions

Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

Shafto, Michael G.↗
NASA NTRS2014

Characterization and Comparison of Vibration Transfer Paths in a Helicopter Gearbox and a Fixture Mounted Gearbox

Health monitoring of rotorcraft components, currently being performed by Health and Usage Monitoring Systems through analyses of vibration signatures of dynamic mechanical components, is very important for their safe and economic operation. HUMS analyze vibration signatures associated with faults and quantify them as condition indicators to predict component behavior. Vibration transfer paths are characterized by frequency response functions derived from the input/output relationship between applied force and dynamic response through a structure as a function of frequency. With an objective to investigate the differences in transfer paths, transfer path measurements were recorded under similar conditions in the left and right nose gearboxes of an AH-64 helicopter and in an isolated left nose gearbox in a test fixture at NASA Glenn Research Center. The test fixture enabled the application of measured torques-common during an actual operation. An impact hammer as well as commercial and lab piezo shakers, were used in conjunction with two types of commercially available accelerometers to collect the vibration response under various test conditions. The frequency response functions measured under comparable conditions of both systems were found to be consistent. Measurements made on the fixture indicated certain real-world installation and maintenance issues, such as sensor alignments, accelerometer locations and installation torques, had minimal effect. However, gear vibration transfer path dynamics appeared to be somewhat dependent on the presence of oil, and the transfer path dynamics were notably different if the force input was on the internal ring gear rather than on the external gearbox case.

structures↗
DOE OSTI2022

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

A review of rare earth elements and yttrium in coal ash: Content, modes of occurrences, combustion behavior, and extraction methods

Rare earth elements and yttrium (REY) have attracted considerable attention over the last decade because of their vital roles in clean energy, consumer product, national defense and security applications, among other uses. Due to the retention of REY during coal burning, coal combustion ash is considered as potential alternative sources for REY. Understanding the content, speciation, retention and/or transformation behavior of REY during coal combustion not only expands our knowledge of the combustion behavior of the trace elements in coal, but also provides basis for modeling REY partitioning during coal combustion and for developing economically viable REY recovery technologies. This review makes a critical summary of recent progress in the study of REY in coal ash. The contents and the extraction potentials of REY in coal ash derived from 15 major coal-producing countries worldwide were summarized and evaluated. Various analytical methods for determining REY bulk contents and speciation, together with the solid sample pretreatment, analytical accuracy and precision, advantages and disadvantages were summarized and compared. Modern analytical approaches combined indirect methods (e.g., sequential extraction) shed light on the physical distribution, mineralogy, and the chemical state of REY in coal ash. Three types of REY occurrences in coal ash, including Si-Al glassy association, discrete minerals or compounds, and organic association (bound with unburned carbon) were defined in the review. The glassy association can be further divided into REY minerals closely bound to glass phases and dispersed throughout the glassy structure. REY partitioning in various emission streams, the size distribution, and their enrichment behavior in coal ash were discussed. Additionally, thermal behavior and transformation of various REY forms in coal during combustion process, including organic-associated REY, REY phosphates, REY carbonates, clay-bound REY and among others were summarized. Two possible retention mechanisms of REY by aluminosilicate glass at boiler temperature were proposed: the incorporation of the individual REY phases into the glass as inclusions and the diffusion of REY phases throughout Si-Al glass structures in the melting process. Feed coal mineral types, mineral-mineral associations, boiler conditions, and other factors control the retention process. After coal combustion, the speciation of REY in fly ash may be modified by the reactions of REY phases with flue gas components. Further, an overview of REY transformation mechanisms during coal combustion was deeply discussed. Finally, current extraction techniques for REY recovery from coal combustion ash were introduced. Future outlooks and research problems were also identified.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗