Results for “integrated modeling approach” — Page 2

NASA NTRS2010

The Application of Modeling and Simulation in Capacity Management within the ITIL Framework

Tightly integrating modeling and simulation techniques into Information Technology Infrastructure Library (ITIL) practices can be one of the driving factors behind a successful and cost-effective capacity management effort for any Information Technology (IT) system. ITIL is a best practices framework for managing IT infrastructure, development and operations. Translating ITIL theory into operational reality can be a challenge. This paper aims to highlight how to best integrate modeling and simulation into an ITIL implementation. For cases where the project team initially has difficulty gaining consensus on investing in modeling and simulation resources, a clear definition for M&S implementation into the ITIL framework, specifically its role in supporting Capacity Management, is critical to gaining the support required to garner these resources. This implementation should also help to clearly define M&S support to the overall system mission. This paper will describe the development of an integrated modeling approach and how best to tie M&S to definitive goals for evaluating system capacity and performance requirements. Specifically the paper will discuss best practices for implementing modeling and simulation into ITIL. These practices hinge on implementing integrated M&S methods that 1) encompass at least two or more predictive modeling techniques, 2) complement each one's respective strengths and weaknesses to support the validation of predicted results, and 3) are tied to the system's performance and workload monitoring efforts. How to structure two forms of modeling: statistical and simUlation in the development of "As Is" and "To Be" efforts will be used to exemplify the integrated M&S methods. The paper will show how these methods can better support the project's overall capacity management efforts.

Rahmani, Sonya↗

DOE OSTI2025

Reduce Revenue Versus Increase Expenditure: Fires and Plant Invasion Drive Soil Carbon Loss With Different Mechanisms in a Mediterranean Shrubland

Fires and plant invasions threaten Mediterranean ecosystems substantially, particularly in the context of changing climate. Our study utilized a data-model integration approach to assess the response of soil organic carbon (SOC) to fires and plant invasion under three Shared Socio-Economic Pathway (SSP) scenarios (SSP1-26, SSP2-45, and SSP5-85). We parameterized the CLM-Microbe model and then investigated the individual and interactive impacts of fires and plant invasion on soil C by comparing factorial simulations of initialization (fire/no wildfire in 2021), fire module on/off, and with and without plant invasion during 2023–2100 in a Mediterranean ecosystem. The simulations indicated a marked C loss due to the 2021 wildfire, projected fires, and plant invasion across all future climate scenarios. Specifically, the 2021 wildfire, projected fires, and plant invasion reduced the SOC (0–30 cm) by 0.12, 0.26, and 0.15 kg C m −2 under SSP1-26, 0.12, 0.30, and 0.12 kg C m −2 under SSP2-45, and 0.12, 0.24, and 0.13 kg C m −2 under SSP5-85, respectively. However, fires and plant invasion decreased SOC through distinct mechanisms. The effects of the 2021 wildfire occurred due to its negative legacy on soil microbial community and, thus, litter accumulation, suppressing the formation of soil carbon via decomposition. Influences of projected fires happen via consuming fuel and suppressing carbon input to soils. In contrast, the impacts of plant invasions were due to enhanced microbial respiration, leading to C loss. In conclusion, these findings emphasize the need for tailored C sequestration strategies considering the disparate effects of fires and plant invasions in the Mediterranean climate.

microbe↗

DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗

NASA NTRS1993

From minerals to rocks: Toward modeling lithologies with remote sensing

High spectral resolution imaging spectroscopy will play an important role in future planetary missions. Sophisticated approaches will be needed to unravel subtle, super-imposed spectral features typically of natural systems, and to maximize the science return of these instruments. Carefully controlled laboratory investigations using homogeneous mineral separates have demonstrated that variations due to solid solution, changes in modal abundances, and the effects of particle size are well understood from a physical basis. In many cases, these variations can be modeled quantitatively using photometric models, mixing approaches, and deconvolution procedures. However, relative to the spectra of individual mineral components, reflectance spectra of rocks and natural surfaces exhibit a reduced spectral contrast. In addition, soils or regolith, which are likely to dominate any natural planetary surface, exhibit spectral properties that have some similarities to the parent materials, but due to weathering and alteration, differences remain that cannot yet be fully recreated in the laboratory or through mixture modeling. A significant challenge is therefore to integrate modeling approaches to derive both lithologic determinations and include the effects of alteration. We are currently conducting laboratory investigations in lithologic modeling to expand upon the basic results of previous analyses with our initial goal to more closely match physical state of natural systems. The effects of alteration are to be considered separately.

Mustard, John F.↗

NASA NTRSDate not supplied

Community Noise Impact of Urban Air Mobility Vehicle Operations

Advanced air mobility (AAM) missions, carried out by electrically driven air vehicles, are characterized by ranges of less than about 300-500 nm (about 500-900 km) and include both rural and urban operations. The missions may include public transportation, cargo delivery, air taxi, and emergency response. While the urban air mobility (UAM) subset of AAM is projected to have high economic benefit, it is also the most difficult to develop because it must overcome many barriers, including those associated with the airspace system, safety, and community noise. This presentation focuses on the utilization of UAM source noise data for assessment of community noise impact. Although a limited number of acoustic flight measurement campaigns have been made to characterize the source noise of prototype and preproduction UAM aircraft, prediction-based approaches are primarily considered herein. Following conceptual design, in which the vehicle is appropriately sized for its intended mission, a comprehensive analysis must be performed for a range of operating conditions spanning the flight envelope to determine the corresponding configurations of the vehicle, that is, the trimmed states. For each trimmed state, the noise produced by each source, for example, steady and unsteady rotor noise, may be computed and so-called source noise (hemi)spheres generated. These source data may subsequently be used in various community noise impact analyses. Several use cases are presented including those supporting noise certification and those for auralizations that may, in turn, be used as part of a perception-influenced design process. Land use planning tools for generating noise exposure maps, including those using simulation and integrated modeling approaches, are also presented. Finally, use cases supporting development of low noise flight operations, including an acoustic flight simulator and acoustically aware flight control, are considered.

aircraft community noise↗

DOE OSTI2021

An Integrative Model for Soil Biogeochemistry and Methane Processes. II: Warming and Elevated CO 2 Effects on Peatland CH 4 Emissions

Peatlands are one of the largest natural sources for atmospheric methane (CH 4 ), a potent greenhouse gas. Climate warming and elevated atmospheric carbon dioxide (CO 2 ) are two important environmental factors that have been confirmed to stimulate peatland CH 4 emissions; however, the mechanisms underlying enhanced emissions remain elusive. A data-model integration approach was applied to understand the CH 4 processes in a northern temperate peatland under a gradient of warming and doubled atmospheric CO 2 concentration. We found that warming and elevated CO 2 stimulated CH 4 emissions through different mechanisms. Warming initially stimulated but then suppressed vegetative productivity while stimulating soil organic matter (SOM) mineralization and dissolved organic carbon (DOC) fermentation, which led to higher acetate production and enhanced acetoclastic and hydrogenotrophic methanogenesis. Warming also enhanced surface CH 4 emissions, which combined with warming-caused decreases in CH 4 solubility led to slightly lower dissolved CH 4 concentrations through the soil profiles. Elevated CO 2 enhanced ecosystem productivity and SOM mineralization, resulting in higher DOC and acetate concentrations. Higher DOC and acetate concentrations increased acetoclastic and hydrogenotrophic methanogenesis and led to higher dissolved CH 4 concentrations and CH 4 emissions. Both warming and elevated CO 2 had minor impacts on CH 4 oxidation. A meta-analysis of warming and elevated CO 2 impacts on carbon cycling in wetlands agreed well with a majority of the modeled mechanisms. Finally, this mechanistic understanding of the stimulating impacts of warming and elevated CO 2 on peatland CH 4 emissions enhances our predictability on the climate-ecosystem feedback.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗

DOE OSTI2021

Modeling airborne pathogen transport and transmission risks of SARS-CoV-2

An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g., airflow/ventilation), and face coverings. The CFD results were combined with infectivity models to determine probability of infection, which is a function of the spatial-temporal aerosol concentrations, viral load, infectivity rate, viral viability, lung-deposition probability, and inhalation rate. Uncertainty distributions were determined for these parameters from the literature. Probabilistic analyses were performed to determine cumulative distributions of infection probabilities and to determine the most important parameters impacting transmission. This modeling approach has relevance to both pathogen and pollutant dispersion from expelled aerosol plumes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Modeling and Experimental Demonstration of Flux Spreading in Light Trapping Planar-Cavity Solar Enclosed Particle Receivers

This study experimentally validates and numerically models the flux-spreading effect in a light-trapping planar-cavity solar receiver) for particle-based concentrating solar power systems. The receiver's shallow cavity with vertical planar walls redistributes concentrated solar flux, reducing peak intensity and achieving uniform heat flux. On-sun tests at National Renewable Energy Laboratory's High-Flux Solar Furnace under flux up to 1500 kW/m2 measured cavity wall temperatures, which were compared with Monte Carlo ray-tracing (SolTrace) and computational numerical simulations. Three angular absorptance models were evaluated: constant absorptance, a Pyromark-based directional model, and a Fresnel-based Cr2O3 model. The Fresnel-derived model showed the best agreement with experiments, achieving high correlation (PC > 0.85), structural similarity (SSIM > 0.98), and signal-to-noise ratios (PSNR > 40 dB), with temperature prediction errors of 1-11%. Results confirm that flux spreading mitigates local overheating and validate the integrated modeling approach, supporting the solar receiver scalability for high-efficiency, high-temperature concentrating solar power applications.

14 SOLAR ENERGY↗

DOE OSTI2021

Estimating viscoelastic compliance of desiccating cementitious materials using drying prism tests

Highlights: • Determining relative humidity and degree of reaction of desiccating cementitious materials via an integrated method • Extracting moisture diffusion coefficient of cement mortar using the mass loss data of the prism specimens • Estimating uniaxial viscoelastic compliance of cement mortar using the shrinkage strain data of the prism specimens An integrated modeling approach to determining internal relative humidity and degree of reaction of desiccating cementitious materials has been developed. By simultaneously accounting for both self-desiccation and external drying, the model is capable of predicting the evolution of material properties of desiccating cementitious materials. Using the mass loss data of the prism specimens, the moisture diffusion coefficient of a nonlinear model for cement mortar was determined. Additionally, a previous poroviscoelastic shrinkage model was modified and extended. Through comparison of predicted and measured axial strain of the prism specimens, the viscoelastic compliance of cement mortar was extracted. The present work revealed that it is possible to use a simple drying prism test to fit the moisture diffusion coefficient and creep compliance of cementitious materials, though the comparison of the extracted viscoelastic compliance with measured compliance was only reasonable if the outer layer of the drying mortar was presumed to have microcracking.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Integrated modeling analysis of estuarine responses to extreme hydrological events and sea-level rise

Estuaries are vulnerable to climate change and are particularly sensitive to extreme river discharge (RD) and sea-level rise (SLR). To understand the effects of extreme RD and SLR on estuaries, an integrated modeling approach is adopted to simulate hydrodynamic changes in the Yangtze River Estuary. Model results showed that SLR will intensify the estuarine hydrodynamics in water level, currents, and salinity. Water level, current speed, and salinity increased linearly with the magnitude of SLR. The hydrological model suggested a lower RD in the future. This will increase the saltwater intrusion, which will be more severe during the lower RD and drought extreme hydrological event (EHE) conditions. Model results also suggested that the saltwater intrusion is more sensitive to RD than SLR. In addition, the interplay between the RD and SLR will exacerbate the impacts of coastal oceans on estuarine hydrodynamics, especially during extremely low RD conditions. Moreover, the decrease of RD and deepening of the channel due to human activities will also amplify the effects of SLR on the Estuary, increasing the risk of coastal disasters.

3-D hydrodynamic model, extreme climate, draught, ↗

DOE OSTI2021

Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land

Using land already enrolled in the Conservation Reserve Program (CRP) in the eastern region of the U.S. for producing energy crops for bioenergy while reducing land rental payments offers the potential for lowering the program costs, increasing returns to CRP landowners, and displacing greenhouse gas (GHG) emissions from fossil fuels. We develop an integrated modeling approach to analyze the combination of biomass prices and CRP land rental payment reductions that can incentivize energy crop production on CRP land and its potential to increase soil carbon stocks and displace fossil fuel emissions. Here, we find that conversion of 3.4 million ha in the CRP can be economically viable at a minimum biomass price of 75 Mg –1 with full CRP land rental payment or at 100 Mg –1 with 75% of this land rental payment; this conversion can result in savings of 0.52 and 1.25 billion Mg CO 2 -eq in life-cycle emissions through the displacement of energy-equivalent fossil fuels and coal-based electricity, respectively, and an additional 0.11 billion Mg CO 2 -eq soil carbon sequestration relative to the status quo, with CRP left unharvested over the 2016–2030 period. The soil carbon debt due to the transition from unharvested CRP land to energy crops is short-lived and more than offset by the reduction in fossil fuel emissions. The net discounted benefits from producing energy crops on CRP land through a reduced need for government payments to maintain existing enrollment, higher returns to CRP landowners, and the value of the reduction in GHG emissions could be as high as 16–30 billion by using them for cellulosic biofuels to displace gasoline and 35–68 billion by displacing coal-based electricity over the 2016–2030 period if biomass prices are 75–125 Mg –1 and land rental payments are reduced by 25%.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

How extreme rainfall and failing dams unleashed the Derna flood disaster

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. Here, we show that the collapse of aging flood control infrastructures, compounded by inadequate risk assessment and emergency preparedness, dramatically escalated the disaster’s impact. Our findings underscore the urgent need for systematic dam safety evaluations, enhanced flood forecasting, and adaptive risk management strategies that address climate extremes and infrastructure vulnerabilities.

Hydrology↗

DOE OSTI2024

Integrated ab initio modelling of atomic ordering and magnetic anisotropy for design of FeNi-based magnets

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Self-consistent modeling of tokamak edge plasma transport with lithium sources

Magnetic confinement fusion devices require effective heat and particle exhaust solutions on the divertor plates to operate sustainably, especially under reactor-relevant conditions. Liquid lithium divertors have been proposed to address two major challenges: control of excessive heat flux to plasma-facing components through vapor shielding and minimization of core plasma contamination from impurities. The National Spherical Torus Experiment-Upgrade (NSTX-U) will explore lithium as a divertor material due to its potential to meet both objectives. We present a self-consistent coupling framework between the plasma boundary transport code UEDGE and the lithium wall transport code Wall–Li to evaluate the feasibility and operational limits of lithium-based divertors. The model aims to optimize lithium sourcing levels to prevent core plasma contamination via fuel dilution while ensuring divertor protection through vapor shielding. This integrated framework, applicable to any tokamak with lithium sources, dynamically adjusts lithium sourcing based on local plasma conditions and surface temperature. The coupled model is tested using NSTX-like geometry and plasma conditions to assess its performance and reliability. Wall–Li calculates lithium fluxes from plasma-facing components, incorporating physical sputtering, thermally enhanced sputtering, and evaporation driven by surface temperature and ion flux. These fluxes are reintroduced into UEDGE as neutral lithium atoms, enabling simulation of their transport and distribution within the plasma. UEDGE computes plasma and neutral transport, surface heat flux, and iteratively feeds this information back to Wall–Li. A small time step is employed to ensure numerical stability and convergence, enabling accurate simulations over typical tokamak discharge durations. This integrated modeling approach provides a robust tool for identifying operational regimes that balance effective lithium sourcing with minimal core plasma contamination, offering critical insights for optimizing lithium-based divertor systems in current and future fusion devices.

Magnetic confinement fusion↗