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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modeling Effects of Annealing on Coal Char Reactivity to O 2 and CO 2 , Based on Preparation Conditions

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive computational fluid dynamics (CFD) simulations are valuable tools in evaluating and deploying oxyfuel and other carbon capture technologies, either as retrofit technologies or for new construction. However, accurate predictive combustor simulations require physically realistic submodels with low computational requirements. A recent sensitivity analysis of a detailed char conversion model (Char Conversion Kinetics (CCK)) found thermal annealing to be an extremely sensitive submodel. In the present work, further analysis of the previous annealing model revealed significant disagreement with numerous datasets from experiments performed after that annealing model was developed. The annealing model was accordingly extended to reflect experimentally observed reactivity loss, because of the thermal annealing of a variety of coals under diverse char preparation conditions. The model extension was informed by a Bayesian calibration analysis. In addition, since oxyfuel conditions include extraordinarily high levels of CO 2 , the development of a first-ever CO 2 reactivity loss model due to annealing is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗
DOE OSTI2019

Design and analysis of graphene–MoS{sub 2} hybrid layer based SPR biosensor with TiO{sub 2}–SiO{sub 2} nano film for formalin detection: numerical approach

In this paper, a Surface Plasmon Resonance (SPR) biosensor has been numerically developed that used Graphene–MoS{sub 2}–Au–TiO{sub 2}–SiO{sub 2} hybrid structure for the detection of formalin. This developed sensor has been sensed the presence the formalin based on attenuated total reflection (ATR) method by observing the change of “surface plasmon resonance angle-the change of minimum reflectance attributor” and “the resonance frequency characteristics (RFC)-maximum transmittance attributor”. Chitosan has been used as probe sensing medium to accelerate particular reaction with the formalin. Here, graphene is used as biomolecular recognition element because of its high adsorption ability and optical characteristics which helps to improve sensor sensitivity, MoS{sub 2} used for it has larger band gap, high fluroscence quenching ability, higher optical absorption efficiency, TiO{sub 2}–SiO{sub 2} bilayer as the improvement of sensitivity and Gold (Au) as the sharp SPR curve. Numerical results give the impression that the variation of RFC and SPR angle for improper sensing of formalin is quiet negligible that confirms no formalin is detected whereas for proper sensing these change are considerably countable that confirms the detection of formalin. From the sensor sensitivity analysis, owing to add TiO{sub 2}–SiO{sub 2} bilayer with Graphene–MoS{sub 2} Hybrid layer, maximum sensitivity of 85.375% has been numerically resulted. This high sensor performance is for taking advantages of Graphene surface high selectively which detect bio molecular compounds through pi-stacking force, larger work function (5.1 eV) of MoS{sub 2} which allows the high sensitive detection of bio targets and Rich plasmon happens at the TiO{sub 2}–SiO{sub 2} interface.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Environmental life cycle assessment methods applied to amine-ionic liquid hybrid CO 2 absorbents

A hybrid solvent mixture of triethyl(octyl)phosphonium cyanopyrrolide [P2228][2-CNPyr] and aqueous monoethanolamine (MEA) has the potential for absorbing CO 2 from post combustion flue gas. However, previous studies have found that the production of phosphonium based ionic liquids (IL) had significantly higher potential environmental impacts compared to MEA. Literature attributes these higher environmental impacts to the phosphine and phosgene-based intermediates required to produce the phosphonium ion of the ionic liquid. This study proposes a novel synthesis pathway that eliminates the need for phosphine and phosgene intermediates in the production of [P2228][2-CNPyr]. The environmental impacts of producing 1kg of the ionic liquid through this novel synthesis route was evaluated using the TRACI 2.1 methodology within the life cycle assessment (LCA) framework. Additionally, the environmental impacts for the production of 1kg of a hybrid solvent was also evaluated and compared against MEA. The life cycle inventory for the production of the IL and its hybrid solvent were calculated based on the stoichiometry and then scaled up. This study found that the IL and its hybrid solvents had higher environmental impacts among 9 of the 10 environmental impact categories calculated by the TRACI 2.1 methodology, except for the ecotoxicity potential. A sensitivity analysis indicated that these solvents were more sensitive to the assumptions of the material requirements of the phosphonium cation than the overall energy or transportation requirements. Despite this sensitivity, both the solvents demonstrated a lower Ecotoxicity Potential compared to MEA, the rest of the environmental impacts were still found to be higher than that of MEA, thereby underscoring the need to investigate novel synthesis routes for the production of phosphonium cation. The uncertainty analysis performed confirmed the findings that the IL has a higher environmental impact potentials across all categories except ecotoxicity potential. The uncertainty analysis also confirms that the phosphonium cation is a major hotspot in production route of these solvents and a source of uncertainty in the model compared to the anion. Altogether, this study underscores the need for investigating novel green chemistry pathway for the synthesis of phosphonium based ionic liquids, such as [P2228][2-CNPyr], to ensure that the these ILs can be a truly green alternative to MEA by not only offering superior CO₂ capture capacity compared to MEA but also being sustainably produced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Measurement of thermal gap conductance using the laser flash method

Thermal gap conductance refers to overall heat conductance through a gas-filled gap as interface thermal resistance between the gas and surface has to be considered. The analysis of new ATR (Advanced Test Reactor) fuel experiments requires experimental data and models for the gap conductance of the cladding/fuel capsule gap, which typically varies from 5 μm to 50 μm and is filled with He at 1-3 atm. Although past research has studied the gap conductance between UO{sub 2} fuel and Zircaloy cladding, new experiments are needed to provide the gap conductance data between HT9 and stainless steel 316, and between advanced fuels and advanced cladding in the Accident Tolerant Fuels program. In this paper, the laser flash method is modified to measure the gap conductance. The gap is formed by welding two stainless steel 316 disks with three spacers. The temperature at the rear surface, after exposure to the laser pulse at the front surface, is modeled with 1D heat transfer through three layers. The analytic solution is then fitted with the measured temperature to determine gap conductance. The sensitivity analysis based on the 1D assumption and 3D numerical simulations were performed to assess the sensitivity and uncertainty of the measurement. It is concluded the heat capacity of the gas in the gap has minimal impact on the measurement, which indicates that the thermal property determined by this method is the thermal conductance, instead of the thermal diffusivity. Convective heat loss through sidewalls under the current experimental design has insignificant influences. Heat transfer through spacers may cause up to 10% overestimation of thermal gap conductance, but the effects can be mostly eliminated by the design of grooves on samples. The result established a pathway for gap conductance determination. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Detailed high-accuracy megavoltage transmission measurements: A sensitive experimental benchmark of EGSnrc

Purpose: There are three goals for this study: (a) to perform detailed megavoltage transmission measurements in order to identify the factors that affect the measurement accuracy, (b) to use the measured data as a benchmark for the EGSnrc system in order to identify the computational limiting factors, and (c) to provide data for others to benchmark Monte Carlo codes. Methods: Transmission measurements are performed at the National Research Council Canada on a research linac whose incident electron parameters are independently known. Automated transmission measurements are made on-axis, down to a transmission value of {approx}1.7%, for eight beams between 10 MV (the lowest stable MV beam on the linac) and 30 MV, using fully stopping Be, Al, and Pb bremsstrahlung targets and no fattening filters. To diversify energy differentiation, data are acquired for each beam using low-Z and high-Z attenuators (C and Pb) and Farmer chambers with low-Z and high-Z buildup caps. Experimental corrections are applied for beam drifts (2%), polarity (2.5% typical maximum, 6% extreme), ion recombination (0.2%), leakage (0.3%), and room scatter (0.8%)-the values in parentheses are the largest corrections applied. The experimental setup and the detectors are modeled using EGSnrc, with the newly added photonuclear attenuation included (up to a 5.6% effect). A detailed sensitivity analysis is carried out for the measured and calculated transmission data. Results: The developed experimental protocol allows for transmission measurements with 0.4% uncertainty on the smallest signals. Suggestions for accurate transmission measurements are provided. Measurements and EGSnrc calculations agree typically within 0.2% for the sensitivity of the transmission values to the detector details, to the bremsstrahlung target material, and to the incident electron energy. Direct comparison of the measured and calculated transmission data shows agreement better than 2% for C (3.4% for the 10 MV beam) and typically better than 1% for Pb. The differences can be explained by acceptable photon cross section changes of Less-Than-Or-Slanted-Equal-To 0.4%. Conclusions: Accurate transmission measurements require accounting for a number of influence quantities which, if ignored, can collectively introduce errors larger than 10%. Accurate transmission calculations require the use of the most accurate data and physics options available in EGSnrc, particularly the more accurate bremsstrahlung angular sampling option and the newly added modeling of photonuclear attenuation. Comparison between measurements and calculations implies that EGSnrc is accurate within 0.2% for relative ion chamber response calculations. Photon cross section uncertainties are the ultimate limiting factor for the accuracy of the calculated transmission data (Monte Carlo or analytical).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Performance assessment modeling of a generic SNF/HLW repository in salt with coupled thermal-hydrologic effects - 15423

This paper describes advances in performance assessment modeling of deep geologic repositories facilitated by a massively parallel, high-performance computing (HPC) environment. Our new Generic Disposal System Analysis (GDSA) Framework utilizes the massively parallel PFLOTRAN multi-physics code to simulate repository performance in the presence of coupled thermal-hydrologic-chemical processes, linked to DAKOTA, an HPC uncertainty sampling and propagation code that provides nested parallelism for multi-realization performance assessment and sensitivity analysis. This enhanced performance assessment (PA) modeling capability is demonstrated with deterministic and probabilistic simulations of a generic repository for SNF and HLW in bedded salt host rock, by comparing repository performance between a case with heat-generating waste ('thermal' case) and a case without heat generation ('isothermal' case). The simulation results provide preliminary insights into the effect of multi-physics processes and thermal-hydrologic coupling on the long-term behavior of a reference-case salt repository. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Parameter estimation in a thermoelastic composite problem via adjoint formulation and model reduction

Advances in nondestructive material characterization are providing a wealth of information that could be exploited to gain insight into general aspects of material performance and, in particular, discover relationships between microstructure and thermo-mechanical properties in polycrystalline and other complex composite materials. Here, in order to facilitate the integration of such measurements into existing models, as well as inform new physics-based predictions, we developed a C++/MPI computational framework for sensitivity analysis and parameter estimation. The framework utilizes a micro-mechanical modeling based on fast Fourier transforms, direct and adjoint formulations, and Markov chain Monte Carlo sampling techniques. We illustrate the characteristics of this framework and demonstrate its utility by computing the residual stresses arising from thermal expansion of an elastic composite and using data from simulated experiments. Lastly, we show that the availability of nondestructive 3-D measurements is crucial to reduce the uncertainty in predictions, emphasizing the importance of an integrated experimental/modeling/data analysis approach for improved material characterization and design.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Evaluation of Maximum Radionuclide Groundwater Concentrations for Basement Fill Model. Zion Station Restoration Project

ZionSolutions is in the process of decommissioning the Zion Nuclear Power Plant in order to establish a new water treatment plant. There is some residual radioactive particles from the plant which need to be brought down to levels so an individual who receives water from the new treatment plant does not receive a radioactive dose in excess of 25 mrem/y⁻¹. The objectives of this report are: (a) To present a simplified conceptual model for release from the buildings with residual subsurface structures that can be used to provide an upper bound on contaminant concentrations in the fill material; (b) Provide maximum water concentrations and the corresponding amount of mass sorbed to the solid fill material that could occur in each building for use in dose assessment calculations; (c) Estimate the maximum concentration in a well located outside of the fill material; and (d) Perform a sensitivity analysis of key parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Using Nuclear Theory, Data and Uncertainties in Monte Carlo Transport Applications

These are slides for a presentation on using nuclear theory, data and uncertainties in Monte Carlo transport applications. The following topics are covered: nuclear data (experimental data versus theoretical models, data evaluation and uncertainty quantification), fission multiplicity models (fixed source applications, criticality calculations), uncertainties and their impact (integral quantities, sensitivity analysis, uncertainty propagation).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2024

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗
NASA NTRS1995

Shape optimization of single- and two-element airfoils on multiblock grids

A multiblock, discrete sensitivity analysis method is used to couple a direct optimization method and a flow analysis method. The domain is divided into smaller subdomains for which the sensitivities are obtained separately. Then, an effective sensitivity equation is solved to complete the coupling of all the sensitivity information. The flow analysis is based on the thin-layer Navier-Stokes equations solved by an implicit, upwind-biased, finite-volume method. The method of feasible directions is used for the present gradient-based optimization approach. First, a transonic airfoil is optimized to investigate the behavior of the method in highly nonlinear flows as well as the effect of different blocking strategies on the procedure. A supercritical airfoil is produced from an initially symmetric airfoil with multiblocking affecting the path but not the final shape. Secondly, a two-element airfoil is shape optimized in subsonic flow to demonstrate the present method's capability of shaping aerodynamically interfering elements simultaneously. For a very low and a very high Reynolds number cases, the shape of the main airfoil and the flap are optimized to yield improved lift-to-drag ratios.

Lacasse, James M.↗
DOE OSTI2015

Thermodynamic analysis of tar reforming through auto-thermal reforming process

Fixed bed gasification is a simple and suitable technology for small scale power generation. One of the disadvantages of this technology is producing tar. So far, tar is not utilized yet and being waste that should be treated into a more useful product. This paper presents a thermodynamic analysis of tar conversion into gas producer through non-catalytic auto-thermal reforming technology. Tar was converted into components, C, H, O, N and S, and then reacted with oxidant such as mixture of air or pure oxygen. Thus, this reaction occurred auto-thermally and reached chemical equilibrium. The sensitivity analysis resulted that the most promising process performance occurred at flow rate of air was reached 43% of stoichiometry while temperature of process is 1100°C, the addition of pure oxygen is 40% and preheating of oxidant flow is 250°C. The yield of the most promising process performance between 11.15-11.17 kmol/h and cold gas efficiency was between 73.8-73.9%.The results of this study indicated that thermodynamically the conversion of tar into producer gas through non-catalytic auto-thermal reformingis more promising.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Statistical Methods for Effective Spatial and Temporal Scaling in Support of Probabilistic Performance Assessments - 17340

Performance assessments (PAs) for the disposal of low-level radioactive waste have traditionally been performed in a deterministic manner, with inputs specified as single values as if they carry no uncertainty. Modern PAs, however, explicitly incorporate uncertainty through use of probability distributions for inputs instead of single values. While this is clearly an improvement, challenges remain in specifying appropriate distributions, many of which relate to capturing the appropriate spatial and/or temporal scale given the PA model, and matching the scale(s) of data and information to that specified by the model. More careful attention to scaling will lead to more defensible characterizations of physical variability and uncertainty in model inputs, thus leading to more defensible information regarding outcomes of interest to be used in decision making, and hence more defensible decisions. This work introduces general strategies and considerations for explicitly incorporating considerations of scale into distribution development. The strategies are explained as a series of steps and then presented with an example that starts to illustrate the new statistical concepts. This work frames the problem in terms of hierarchical statistical modeling, providing important connections to current statistical approaches to formally and rigorously account for temporal and spatial scaling. The larger goal is to build a more formal and unified approach to distribution development to help teams of modelers, subject matter experts, and statisticians work together to develop distributions and justify the choices made in the process, ultimately leading to more informed decision-making. Without this rigor, statistical distributions are not specified correctly and can have unexpected consequences for modeling and sensitivity analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2011

Cost-Effectiveness Analysis of Stereotactic Body Radiotherapy and Radiofrequency Ablation for Medically Inoperable, Early-Stage Non-Small Cell Lung Cancer

Purpose: The standard management of medically inoperable Stage I non-small-cell lung cancer (NSCLC) conventionally has been fractionated three-dimensional conformal radiation therapy (3D-CRT). The relatively poor local control rate and inconvenience associated with this therapy have prompted the development of stereotactic body radiotherapy (SBRT), a technique that delivers very high doses of irradiation typically over 3 to 5 sessions. Radiofrequency ablation (RFA) has also been investigated as a less costly, single-day therapy that thermally ablates small, peripheral tumors. The cost-effectiveness of these three techniques has never been compared. Methods and Materials: We developed a Markov model to describe health states of 65-year-old men with medically inoperable NSCLC after treatment with 3D-CRT, SBRT, and RFA. Given their frail state, patients were assumed to receive supportive care after recurrence. Utility values, recurrence risks, and costs were adapted from the literature. Sensitivity analyses were performed to model uncertainty in these parameters. Results: The incremental cost-effectiveness ratio for SBRT over 3D-CRT was $6,000/quality-adjusted life-year, and the incremental cost-effectiveness ratio for SBRT over RFA was $14,100/quality-adjusted life-year. One-way sensitivity analysis showed that the results were robust across a range of tumor sizes, patient utility values, and costs. This result was confirmed with probabilistic sensitivity analyses that varied local control rates and utilities. Conclusion: In comparison to 3D-CRT and RFA, SBRT was the most cost-effective treatment for medically inoperable NSCLC over a wide range of treatment and disease assumptions. On the basis of efficacy and cost, SBRT should be the primary treatment approach for this disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Global Sampling for Integrating Physics-Specific Subsystems and Quantifying Uncertainties of CO 2 Geological Sequestration

The risk of CO 2 leakage from a deep storage reservoir into a shallow aquifer through a fault is assessed and studied using physics-specific computer models. The hypothetical CO 2 geological sequestration system is composed of three subsystems: a deep storage reservoir, a fault in caprock, and a shallow aquifer, which are modeled respectively by considering sub-domain-specific physics. Supercritical CO 2 is injected into the reservoir subsystem with uncertain permeabilities of reservoir, caprock, and aquifer, uncertain fault location, and injection rate (as a decision variable). The simulated pressure and CO 2 /brine saturation are connected to the fault-leakage model as a boundary condition. CO 2 and brine fluxes from the fault-leakage model at the fault outlet are then imposed in the aquifer model as a source term. Moreover, uncertainties are propagated from the deep reservoir model, to the fault-leakage model, and eventually to the geochemical model in the shallow aquifer, thus contributing to risk profiles. To quantify the uncertainties and assess leakage-relevant risk, we propose a global sampling-based method to allocate sub-dimensions of uncertain parameters to sub-models. The risk profiles are defined and related to CO 2 plume development for pH value and total dissolved solids (TDS) below the EPA's Maximum Contaminant Levels (MCL) for drinking water quality. A global sensitivity analysis is conducted to select the most sensitive parameters to the risk profiles. The resulting uncertainty of pH- and TDS-defined aquifer volume, which is impacted by CO 2 and brine leakage, mainly results from the uncertainty of fault permeability. Subsequently, high-resolution, reduced-order models of risk profiles are developed as functions of all the decision variables and uncertain parameters in all three subsystems.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of the social factors in success of solar photovoltaic reuse and recycle programmes

By 2050, the cumulative mass of end-of-life photovoltaic (PV) modules may reach 80 Mt globally. The impacts could be mitigated by module recycling, repair and reuse; however, previous studies of PV circularity omit the consideration of critical social factors. Here we used an agent-based model to integrate social aspects with techno-economic factors, which provides a more realistic assessment of the circularity potential for previously studied interventions that assesses additional interventions that cannot be analysed using techno-economic analysis alone. We also performed a global sensitivity analysis using a machine-learning metamodel. We show that to exclude social factors underestimates the effect of lower recycling prices on PV material circularity, which highlights the relevance of considering social factors in future studies. Interventions aimed at changing customer attitudes about used PV boost the reuse of modules, although used modules can only satisfy one-third of the US demand during 2020–2050, which suggests that reuse should be complemented by recycling.

14 SOLAR ENERGY↗