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At least 595 records · Page 33

Closing the Loops on Solar Photovoltaics Modules: An Agent-Based Modeling Approach for the Study of Circular Economy Strategies

Solar photovoltaics (PV) installed capacity have grown exponentially since the early 2000s (average annual growth rate of 50%). With 4,700 GW projected installed capacity by 2050, the volume of PV panels waste is also expected to become substantial. Though renewables are a sine qua non to the establishment of a truly circular economy (CE), the issue arising from their end-of-life management needs to be resolved. The management of PV end-of-life also represent a singular opportunity to create value, from recovered valuable, rare or critical materials (e.g. silver, tellurium, indium). Moreover, the PV case illustrates some of the current barriers to CE; for instance, the need for a common definition of waste (PV are defined as e-waste in the European Union but as general waste in the United States) and potential loss of innovations' advantages (PV average efficiency has continuously grown the past 10 years). In this study, an agent-based modeling (ABM) approach is proposed to simulate PV end-of-life management in the United States. The model explores how the decisions of the various actors involved in handling PV waste affect the quantities of PV that are reused, recycled, or land-filled. In the model, manufacturers, residential, and nonresidential PV owners, installers, and recyclers are represented by agents while governmental policies and regulations are treated as exogenous variables. PV-market data are used to define agents' characteristics (e.g., installed PV capacities or producing costs). Agents' decision rules draw on the literature related to industrial symbiosis (IS) and peoples' waste behaviors as they appear as the most widely used model to implement CE principles at a meso level. Specifically, the concepts of mutual trust between IS actors and knowledge about the IS philosophy are yielded to define the agents' decision process. The primary outputs of the ABM are the costs and volume of waste associated with each end-of-life pathway. Preliminaries results indicate recycling of residential PV is affected by the cost, perceived difficulty of recycling behaviors, and social norms. Moreover, the type of network connecting agents and the initial recycling rate strongly influence results. The model also highlights the crucial role of recycling behavior adoption: in case of early failure of PV, recycled volumes increase by about 40%. This represents an additional 5.7 billion USD from potential recovered silver. Finally, although results for the PV case are presented here, the developed ABM aims at being a general tool for the study of CE strategies and the CE transition. Furthermore, steps of this research include extending the model to encompass circular economy strategies (e.g., design for recycling or lifetime extension) and validating its general architecture from various case studies.

14 SOLAR ENERGY↗

Durable Module Materials Consortium (DuraMAT) FY 2021 Annual Report: New Results and a Renewed Consortium

The Durable Module Materials Consortium (DuraMAT) is a multi-lab consortium led by the National Renewable Energy Laboratory, with Sandia National Laboratories, SLAC National Accelerator Laboratory, and Lawrence Berkeley National Laboratory as core research labs. DuraMAT's overarching goal is to discover, develop, de-risk, and enable the rapid commercialization of improved materials, designs, predictive tests, and models for photovoltaic (PV) modules that increase performance, extend lifetime, and enable new applications. Technical results are highlighted throughout this report, and the new projects awarded for FY 2022 address many of the challenges to making 50-year, high-energy-yield modules that were identified in these working groups.

backsheet↗

Counts of galaxies in a merger model

A model for the photometric evolution of galaxies has been developed and has been applied to the problem of galaxy counts. The integrated colors of galaxies are calculated using the most recently computed evolutionary tracks from Maeder and collaborators complemented with evolutionary tracks derived by other authors. The asymptotic giant branch lifetime is left as a free parameter. A series of cosmological models using different values of the cosmological constant, lambda(sub 0), and the density parameter, omega(sub 0), have been computed. The universality hypothesis of the luminosity function of galaxies has been abandoned. The influence of galaxy merging on the counts has been considered in a simple manner by assuming that the number of strongly interacting galaxies in a comoving volume increases with redshift as a power law given by (1 + z)(exp 3.8). Taking a Schechter parametrization for the luminosity function of the different types of galaxies, we are able to reproduce the observations reasonably well. We have also considered models with a Gaussian distribution for the luminosity function of the brighter galaxies that provide a poorer fit to the observations. It is shown that galaxy count data are not yet able to make unambiguous cosmological statements since evolutionary assumptions are critical. In particular, an omega(sub 0) = 1, lambda(sub 0) = 0 cosmology is shown to be consistent with the data.

Colin, P.↗

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗

Degradation Characterization of Unsteady Pressure-Sensitive Paint Under Various Pressures

The lifetime and intensity techniques are two distinct methods used to measure the surface pressure of wind tunnel models with pressure-sensitive paint (PSP). When exposed to 405 nm light for extended periods, both the luminescence and the lifetime ratio were observed to decrease, affecting perceived pressure values. To help further the implementation of the uPSP, this paper describes the efforts to characterize the degradation of both the intensity of the paint and its lifetime ratio, as well as the change in intensity calibration. It was found that the paint degrades at different rates depending on the partial pressure of oxygen during excitation. It was also found that the calibration curves exhibit greater changes when under higher oxygen concentrations, both indicating photodegradation due to photodecomposition and photo-oxidation processes. These effects are observed on models in a subsonic 14” × 14” wind tunnel. The work provides insight into the dynamic degradation behavior of PSP and uPSP, paving the way to reduce the error in pressure measurements obtained through these techniques.

Pressure-Sensitive Paint↗

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

battery↗

A Team Mental Model Perspective of Pre-Quantitative Risk

This study was conducted to better understand how teams conceptualize risk before it can be quantified, and the processes by which a team forms a shared mental model of this pre-quantitative risk. Using an extreme case, this study analyzes seven months of team meeting transcripts, covering the entire lifetime of the team. Through an analysis of team discussions, a rich and varied structural model of risk emerges that goes significantly beyond classical representations of risk as the product of a negative consequence and a probability. In addition to those two fundamental components, the team conceptualization includes the ability to influence outcomes and probabilities, networks of goals, interaction effects, and qualitative judgments about the acceptability of risk, all affected by associated uncertainties. In moving from individual to team mental models, team members employ a number of strategies to gain group recognition of risks and to resolve or accept differences.

Cooper, Lynne P.↗

Benefits of Fast Battery Formation in a Model System

Lithium-ion battery formation affects battery cost, energy density, and lifetime. An improved understanding of the first cycle of solid-electrolyte interphase (SEI) growth on carbonaceous negative electrodes could aid in the design of optimized formation protocols. In this work, we systematically study SEI growth during the formation of carbon black negative electrodes in a standard carbonate electrolyte. We show that the initial ethylene carbonate (EC) reduction reaction occurs at ~0.5-1.2 V during the first lithiation, except under fast lithiation rates (≥10C). The products of this EC reduction reaction do not passivate the electrode; only the SEI formed at lower potentials affects the second-cycle Coulombic efficiency. Thus, cycling quickly through the voltage regime of this reaction can decrease both formation time and first-cycle capacity loss, without an increase in subsequent-cycle capacity loss. We also show that the capacity consumed by this reaction is minimized at low temperatures and low salt concentrations. Finally, we discuss the mechanism behind our experimental results. This work reveals the fundamental processes underlying initial SEI growth on carbonaceous negative electrodes and provides insights for both optimizing the battery formation process and enabling novel electrolytes.

25 ENERGY STORAGE↗

Characterization of Photodegredation in Unsteady Pressure-Sensitive Paint Under Varying Pressures

The lifetime and intensity techniques are two distinct methods used to measure the surface pressure of wind tunnel models with pressure-sensitive paint (PSP). When exposed to 405 nm light for extended periods, both the luminescence and the lifetime ratio were observed to decrease, affecting perceived pressure values. To help further the implementation of the unsteady pressure-sensitive paint (uPSP), this paper describes the efforts to characterize how photo degradation affects the intensity of the paint signal and its lifetime ratio, as well as the intensity calibration's response and how these changes vary with different pressure environments. It was found that the paint photo degrades at different rates depending on the partial pressure of oxygen during excitation. It was also found that the calibration curves exhibit greater changes when exposed to excitation light in higher pressure environments, both indicating photo degradation due to photo decomposition and photo-oxidation processes. These effects are observed on models in a subsonic 14” × 14” wind tunnel as well as a large-scale 11’ x 11’ transonic wind tunnel. The work provides analysis into the photo degradation behavior of PSP and uPSP, paving the way to reduce the error in pressure measurements obtained through these techniques.

Pressure-Sensitive Paint↗

How fast can protons decay?

Current laboratory bounds imply that protons are extremely long-lived. However, this conclusion may not hold for all time and in all of space. We find that the proton lifetime can be ∼ 15 orders of magnitude shorter in the relatively recent past on Earth or at the present time elsewhere in the Milky Way. A number of terrestrial and astrophysical constraints are examined and potential signals are outlined. We also sketch possible models that could lead to spatial or temporal variations in the proton lifetime. A positive signal could be compelling evidence for a new long range force of nature, with important implications for the limitations of fundamental inferences based solely on laboratory measurements. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Near‐Unity Superradiant Emission from Delocalized Frenkel Excitons in a Two‐Dimensional Supramolecular Assembly

Abstract Three general effective strategies are shown to mitigate nonradiative losses in the superradiant emission from supramolecular assemblies. J‐aggregates of 5,5′,6,6′‐tetrachloro‐1,1′‐diethyl‐3,3′‐di(4–sulfobutyl)‐benzimidazolocarbocyanine (TDBC) are used to elucidate the nature of nonradiative processes. Self‐annealing at room temperature (RT), photo‐brightening, and purification of the dye monomers are shown to all lead to substantial increases in emission quantum yields (QYs) and a concomitant lengthening of the emission lifetime, with purification having the largest effect. Structural and optical measurements are used to support a microscopic model that emphasizes the deleterious effects of a small number of impurity and defect sites that serve as nonradiative recombination centers. This understanding has yielded a molecular fluorophore in solution at RT with an unprecedented combination of fast emissive lifetime and high QY. Superradiant emission with a QY of 82% and a lifetime of 174 ps is obtained from J‐aggregates of TDBC in solution at RT. This combination of high QY and fast lifetime at RT makes supramolecular assemblies of purified TDBC a model system for the study of fundamental superradiance phenomena. High QY J‐aggregates are uniquely suited for the development of applications that require high speed and high brightness fluorophores such as devices for high‐speed optical communication.

36 MATERIALS SCIENCE↗

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

Analytical Expression for DC Link Capacitor Current in a Cascaded H-Bridge Multi-Level Active Front-End Converter

Medium-voltage grid-tied systems often use a cascaded H-bridge multi-level active front-end. In this converter, dc link bus capacitors play an important role in stabilizing the converter and enabling both active and reactive power injections. The present work provides analytical expressions for the capacitor current, which are essential for optimizing system design (especially capacitor size vs. lifetime). Then, the expression is incorporated into the grid connected bidirectional power system model. Consequently, this work contributes to the guiding principles to choose accurate dc link capacitor ratings against grid-side power delivery requirements. The analytical results have been validated with detailed simulations and hardware results.

cascaded H-bridge, carrier-based PWM, dc-link capa↗

Status of NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 50,000 h and 900 kg Throughput

The NASA's Evolutionary Xenon Thruster (NEXT) project is developing the next-generation solar electric propulsion ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system in order to provide future NASA science missions with enhanced propulsion capabilities. As part of a comprehensive thruster service life assessment, the NEXT Long-Duration Test (LDT) was initiated in June 2005 to demonstrate throughput capability and validate thruster service life modeling. The NEXT LDT exceeded its original qualification throughput requirement of 450 kg in December 2009. To date, the NEXT LDT has set records for electric propulsion lifetime and has demonstrated 50,170 hours of operation, processed 902 kg of propellant, and delivered 34.9 MN-s of total impulse. The NEXT thruster design mitigated several life-limiting mechanisms encountered in the NSTAR design, dramatically increasing service life capability. Various component erosion rates compare favorably to the pretest predictions based upon semi-empirical ion thruster models. The NEXT LDT either met or exceeded all of its original goals regarding lifetime demonstration, performance and wear characterization, and modeling validation. In light of recent budget constraints and to focus on development of other components of the NEXT ion propulsion system, a voluntary termination procedure for the NEXT LDT began in April 2013. As part of this termination procedure, a comprehensive post-test performance characterization was conducted across all operating conditions of the NEXT throttle table. These measurements were found to be consistent with prior data that show minimal degradation of performance over the thruster's 50 kh lifetime. Repair of various diagnostics within the test facility is presently planned while keeping the thruster under high vacuum conditions. These diagnostics will provide additional critical information on the current state of the thruster, in regards to performance and wear, prior to destructive post-test analyses performed on the thruster under atmosphere conditions.

Life test↗

Status of NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 50,000 h and 900 kg Throughput

The NASA's Evolutionary Xenon Thruster (NEXT) project is developing the next-generation solar electric propulsion ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system in order to provide future NASA science missions with enhanced propulsion capabilities. As part of a comprehensive thruster service life assessment, the NEXT Long-Duration Test (LDT) was initiated in June 2005 to demonstrate throughput capability and validate thruster service life modeling. The NEXT LDT exceeded its original qualification throughput requirement of 450 kg in December 2009. To date, the NEXT LDT has set records for electric propulsion lifetime and has demonstrated 50,170 h of operation, processed 902 kg of propellant, and delivered 34.9 MN-s of total impulse. The NEXT thruster design mitigated several life-limiting mechanisms encountered in the NSTAR design, dramatically increasing service life capability. Various component erosion rates compare favorably to the pretest predictions based upon semi-empirical ion thruster models. The NEXT LDT either met or exceeded all of its original goals regarding lifetime demonstration, performance and wear characterization, and modeling validation. In light of recent budget constraints and to focus on development of other components of the NEXT ion propulsion system, a voluntary termination procedure for the NEXT LDT began in April 2013. As part of this termination procedure, a comprehensive post-test performance characterization was conducted across all operating conditions of the NEXT throttle table. These measurements were found to be consistent with prior data that show minimal degradation of performance over the thruster's 50 kh lifetime. Repair of various diagnostics within the test facility is presently planned while keeping the thruster under high vacuum conditions. These diagnostics will provide additional critical information on the current state of the thruster, in regards to performance and wear, prior to destructive post-test analyses performed on the thruster under atmosphere conditions.

Ion thruster↗

Advanced Global Atmospheric Gases Experiment (AGAGE): MIT Contribution

We describe in detail the instrumentation and calibrations used in the ALE, GAGE and AGAGE experiments and present a history of the majority of the anthropogenic ozone- depleting and climate-forcing gases in air based on these experiments. Beginning in 1978, these three successive automated high frequency in-situ experiments have documented the long-term behavior of the measured concentrations of these gases over the past twenty years, and show both the evolution of latitudinal gradients and the high frequency variability due to sources and circulation. We provide estimates of the long-term trends in total chlorine contained in long- lived halocarbons involved in ozone depletion. We summarize interpretations of these measurements using inverse methods to determine trace gas lifetimes and emissions. Finally, we provide a combined observational and modeled reconstruction of the evolution of chlorocarbons by latitude in the atmosphere over the past sixty years which can be used as boundary conditions for interpreting trapped air in glaciers and oceanic measurements of chlorocarbon tracers of the deep oceanic circulation. Some specific conclusions are: (a) International compliance with the Montreal Protocol is so far resulting in chlorofluorocarbon and chlorocarbon mole fractions comparable to target levels, (b) Mole fractions of total chlorine contained in long-lived halocarbons (CCl2F2, CCl3F, CH3CCl3, CCl4, CHClF2, CCl2FCClF2, CH3Cl, CH2Cl2, CHCl3, CCl2=CCl2) in the lower troposphere reached maximum values of about 3.6 ppb in 1993 and are beginning to slowly decrease in the global lower atmosphere, (c) The chlorofluorocarbons have atmospheric lifetimes consistent with destruction in the stratosphere being their principal removal mechanism, (d) Multi-annual variations in chlorofluorocarbon and chlorocarbon emissions deduced from ALUGAGWAGAGE data are consistent approximately with variations estimated independently from industrial production and sales data where available (CCl2F2 (CFC-12) and CCl2FCClF2 (CFC-113) show the greatest discrepancies), (e) The mole fractions of the hydrochlorofluorocarbons and hydrofluorocarbons, which are replacing the regulated halocarbons, are rising very rapidly in the atmosphere but, with the exception of the much longer manufactured CHClF2 (HCFC-22), they are not yet at levels sufficient to contribute significantly to atmospheric chlorine loading. These replacement species could in the future provide independent estimates of the global weighted-average OH concentration provided their industrial emissions are accurately documented, (f) In the future, analysis of pollution events measured using high frequency in-situ measurements of chlorofluorocarbons and their replacements may enable emission estimates at the regional level which, together with industrial end-use data, are of sufficient accuracy to be capable of identifying regional non-compliance with the Montreal Protocol.

Kurylo, Michael↗

Validating corrosion models: Influence of physical properties

In chloride containing environments, two metals in physical contact can undergo galvanic corrosion limiting the lifetime of components. Being able to accurately predict galvanic corrosion damage distributions over time has not been widely presented in literature. Therefore, Finite Element Method (FEM) corrosion models were experimentally validated for two galvanic couples as a function of governing equations, environment, anode material, anode:cathode ratio, and time. Carbon steel/stainless steel (CS/SS) and zinc/stainless steel (Zn/SS) galvanic couples were exposed to NaCl solutions at room temperatures for up to 14 days. For the galvanic couples and environments, the Laplace equation with variable conductivity and reactions was sufficient to model the experimental corrosion damage. Increasing the chloride concentration for the CS/SS galvanic couple, regardless of the anode:cathode ratio, decreased the observed and modeled corrosion damage. Decreasing the anode:cathode ratio (i.e., increasing the cathode length), increased the experimentally observed and modeled corrosion damage. For small anode:cathode ratios, the governing equations deviate over long time periods with the Nernst-Plank equation being conservative. For the Zn/SS galvanic couple, the cathode length controls the dominant cathodic reduction reaction. For small cathode lengths, the hydrogen evolution reaction is dominant. For larger cathode lengths, the oxygen reduction reaction is dominant. The results are discussed with regard to the influence of solution chemistry, ohmic drop, and governing reactions. Overall, validated FEM models were presented, and the resultant models, physics, and mechanisms can be applied to other corrosion scenarios with confidence.

Carbon steel↗