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At least 451 records · Page 25

Integrated System and Application Continuous Performance Monitoring and Analysis Capability

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia's Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia's ElectroMagnetic Plasma In Realistic Environments ( EMPIRE ) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia's HPC users.

97 MATHEMATICS AND COMPUTING↗

Development of a Thin Film Primary Surface Heat Exchanger for Advanced Power Cycles

This project objective is to develop a high-temperature design upgrade for an existing primary surface heat exchanger so that the redesigned hardware is capable of operation in CO 2 at temperatures up to 1,510°F (821°C) and pressure differentials up to 130 psi (9 bar). The heat exchanger is proposed for use as a recuperator in an advanced low-pressure oxy-fuel Brayton cycle that is predicted to achieve over 50% thermodynamic efficiency, although the heat exchanger could also be used in other high-temperature, low-differential pressure cycles. This report describes the progress to date, which includes continuing work performed to select and test new candidate materials for the recuperator redesign, final mechanical and thermal performance analysis results of various redesign concepts, and the preliminary design of a test loop for the redesigned recuperator including a budgetary estimate for detailed test loop design, procurement, and test operation. A materials search was performed in order to investigate high-temperature properties of many candidate materials, including high-temperature strength and nickel content. These properties were used to rank the candidate materials, resulting in a reduced list of nine materials for corrosion testing. Multiple test rigs were considered and analyzed for short-term corrosion testing and Thermal Gravimetric Analysis (TGA) was selected as the most cost-effective option for evaluating corrosion resistance of the candidate materials. In addition, tantalum, niobium, and chromium coatings were identified as potential options for increased corrosion resistance. The test results show that many materials exhibit relatively low weight gain rates, and that niobium and tantalum coatings may improve corrosion resistance for many materials, while chromium coatings appear to oxidize and debond quickly. Metallurgical analysis of alloys was also performed, showing evidence of intergranular attack in 282 that may cause long-term reliability problems in CO 2 service at these temperatures. However, long-term testing in a flowing environment is recommended in order to understand accurately the severity of the attack. Detailed economic modeling of the existing air cycle recuperator and CO 2 cycle recuperator options was also completed, including costs for material, fabrication, fuel, maintenance, and operation. The analysis results show that the increased capital cost for high-temperature materials may be offset by higher cycle efficiencies, decreasing the overall lifetime cost of the system. The economic analysis also examines costs associated with increased pressure drop and material changes for two redesign options. These results show that, even with slightly reduced performance and/or higher material costs, the lifetime cost per energy production may still be reduced by over 12%. The existing recuperator design information was provided by Solar Turbines, Inc. via several models, drawings, and design handoff meetings. Multiple fluid/thermal and structural models were created in order to analyze critical recuperator performance and mechanical strength in critical areas throughout the redesign process. These models were analyzed for a baseline condition (consistent with current Mercury 50 operation) for validation purposes. Results are presented for heat transfer coefficients and pressure drops, matching well with the existing operational data. Simulation of higher-temperature CO 2 conditions was also performed, showing a slight expected increase in both heat transfer and pressure drop. Mechanical analysis results for critical areas on the cross-flow and counter-flow sheets have also been obtained for air and CO 2 cases. These results show similar stresses in both cases but significantly reduced safety factors for the CO 2 case due to reduced yield and creep rupture strengths of alloy 625 at the higher temperatures. A concept brainstorm session and initial down-selection were completed in order to identify promising redesign options for further analysis. Detailed analysis of all promising redesign options was performed via finite element and computational fluid dynamic simulations in order to characterize mechanical and thermal-fluid performance of each option. These options included material change, various sheet thickness configurations, pitch and phasing of cross-flow and counter-flow sheets, and separator sheets. The analysis results have identified two viable redesign options that maintain existing safety margins optimally through a material change to Haynes 282 and (A) sheet thickness increases of 40% on the counter-flow sheet and 75% on the hot side cross-flow corrugation sheet or (B) addition of a separator sheet in the counter-flow section while maintaining the original counter-flow sheet thickness and increasing the cross-flow corrugation sheet thickness by 90% to account for the increase in cell height. While both options satisfy mechanical stress constraints, the separator sheet design has a higher part count, slightly reduced heat transfer, and slightly higher pressure drop than the first option and is not preferred. Finally, several test loop concepts have been developed for different full-scale and reduced-scale recuperator testing options. For each option, various loop components, such as heat exchangers, valves, heaters, and compressors, were evaluated in an effort to maximize utilization of existing resources. All concepts utilize an existing 3-MW CO 2 compressor, heater, and loop coolers, but the concepts vary by incorporating different amounts of new equipment for achieving various flow rates (all concepts operate at design pressure and temperature). The third concept achieves a 1 kg/s test without purchasing any costly equipment (coolers, heaters, blowers, etc.). Since the stacked cell design of the recuperator results in the same flow conditions at each core cell (even for a reduced-scale test). Thus, test loop Concept #3 was selected for the preliminary design. This loop design is detailed within the report, culminating in a budgetary estimate of $1,013,000.00 for the detailed design, construction, commissioning, and operation of a high-temperature recuperator test loop.

03 NATURAL GAS↗

De-Risking Large-Scale PV Systems Through Data Analytics

Large-scale photovoltaic system performance analysis is being conducted within the US Department of Energy's-sponsored PV Fleet Performance Data Initiative. This collaboration with commercial PV system owners collects and evaluates PV field performance data, and provides reports on aggregated results. Drawing on over 2200 sites across the US and over 24,000 separate PV inverters we have collected in excess of 8.3 gigawatts (GW) of performance data, representing 6-7% of the entire US installed PV capacity. A mixture of utility-scale and large commercial systems are represented, averaging 4.1 megawatts (MW) in size and 5 years in age. Initial results show average system degradation rates at -0.75% / year, which is slightly higher than historically reported module-level values of -0.5%/year. We also found that the availability of systems averaged 97.7%, which is lower than the typical 99% uptime assumed by many project economic forecasts. Given these results, we compared monthly performance with expected production values, based on satellite weather data and a simple PVWatts performance model. We found that systems were performing within 10% of monthly expectation over 90% of the time, with a fleet average vs expected monthly value of 0.994. We also evaluated the impact of extreme weather events on system performance, and found a range of short-term and longer-term performance effects ranging from grid outage, system downtime, module damage and accelerated long-term degradation rate.

analysis↗

Active Measurement of Memory Resource Consumption

Hierarchical memory is a cornerstone of modern hardware design because it provides high memory performance and capacity at a low cost. However, the use of multiple levels of memory and complex cache management policies makes it very difficult to optimize the performance of applications running on hierarchical memories. As the number of compute cores per chip continues to rise faster than the total amount of available memory, applications will become increasingly starved for memory storage capacity and bandwidth, making the problem of performance optimization even more critical. We propose a new methodology for measuring and modeling the performance of hierarchical memories in terms on the application’s utilization of the key memory resources: capacity of a given memory level and bandwidth between two levels. This is done by actively interfering with the application’s use of these resources. The application’s sensitivity to reduced resource availability is measured by observing the effect of interference on application performance. The resulting resource-oriented model of performance both greatly simplifies application performance analysis and makes it possible to predict an application’s performance when running with various resource constraints. This is useful to predict performance for future memory-constrained architectures.

97 MATHEMATICS AND COMPUTING↗

Experimental Breeder Reactor II (EBR-II) Level 1 Probabilistic Risk Assessment

The National Academy of Sciences Study of the USDOE Category A Reactors recommended that a Probabilistic Risk Assessment (PRA) should be performed on the EBR-11 Reactor. In January 1989, a Level 1 PRA was initiated. This report documents work performed in completing the Level 1 PRA except for seismic analysis; it describes the methodology used, assumptions made, the analysis performed, and the final results. The seismic risk assessment is in progress. It will be separately documented.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Design-Space Data: Informing Common Design Decisions with Pre-Simulated Data

Design Space Exploration (DSE) analysis techniques represent a data-centric approach to integrating performance analysis in early design phases when there is the greatest potential to cheaply improve the energy efficiency of a building. We focus on a novel extension of DSE called Universal Design Space Exploration (UDSE), which leverages massive databases of pre-simulated analysis that represent all possible outcomes of common analysis workflows. These databases, called Design Spaces, become “universal” when a single pre-simulated design space can be re-applied to future unknown projects. Unlike current simulation methods, which require a design to exist before it can be analyzed and often take minutes or hours to simulate, UDSE leverages pre-simulation to deliver rapid and relevant insight as new designs are conceptualized. The data underpinning UDSE enables advanced statistical and Artificial Intelligence methods, allowing UDSE to deliver a greater understanding of the larger problem being explored, rather than simply delivering analysis of several pre-conceived design options. We believe that UDSE can provide instantaneous, relevant analysis for all building design projects at negligible cost. This paper has two main goals, to develop a relevant Universal Design Space that showcases the potential of UDSE and to release this data freely to industry and academia; thereby lowering the barrier to entry to digital literacy in statistics, ML and AI within the architecture, engineering, construction (AEC) industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-Temperature Latent Heat Storage System using Transportable Heat Pipes for Versatile Integration with Emerging Microreactors

With the growing interest in the development of micro nuclear reactors and their application to microgrid, high-temperature thermal energy storage (TES) has also been receiving great attention as a technology to reinforce the energy utilization and profitability of this class of reactors. Given the importance and research needs of the TES technology, a research project is underway at Idaho National Laboratory (INL) to develop high-temperature TES that can be easily interfaced with emerging micro nuclear reactors. Currently under development is the Heat pipe-Integrated Thermal Battery (HITB), a novel latent heat storage design that enables flexible and robust integration with any design of currently considered micro nuclear reactors. The development of detailed design based on the proposed TES concept, HITB, requires not only development and validation of modeling and simulation capabilities, but also research that spans thermal performance analysis, component- and system-scale design optimization, and experimental demonstrations including high-temperature feasibility testing. The current research efforts (and plans) are divided into the following four areas: (i) Thermal and structural modeling and analysis at both system- and component-scales for evaluating performance and conducting design optimization, (ii) Small-scale experimental demonstrations for the key components of the proposed HITB design, (iii) Modelica-based dynamic model development for developing a control strategy under dynamic operation within integrated energy systems configuration, (iv) Integrated experimental testing and demonstration. This paper introduces the overall research efforts that have been and are being conducted to develop and demonstrate the novel design of the high-temperature latent heat storage device, HITB. The key design features, ongoing research efforts including the development of modeling and simulation capabilities, small-scale demonstrations of the HITB’s key functionalities prior to scaled-up experimental demonstration, are discussed. Then, this paper concludes with a remark on the future research plans for this project.

25 ENERGY STORAGE↗

Selected results from full-core hydrogen redistribution asymptotic analysis in YH-moderated heat-pipe cooled microreactor

Yttrium hydride is the main candidate for moderation of high temperature nuclear microreactors . This is due to its high thermal stability and relatively high hydrogen retention at temperatures exceeding 870 C. One of the main issues associated with the use of yttrium hydride is that, when exposed to temperature, stress, or concentration gradients, the hydrogen contained in the metallic matrix tends to redistribute and leak from the moderating elements, potentially leading to reactivity losses and power swings. This paper is focused on presenting selected results from the asymptotic hydrogen redistribution analysis performed on the Simplified Microreactor Benchmark Assessment (SiMBA) problem, a microreactor core conceptual design developed at INL. The analysis is based on full core analysis, relies uniquely on Bison to perform hydrogen redistribution calculations, and discusses the physical causes of the reactivity feedback. It was found that the feedback is negative, but it is one order of magnitude lower than the one found for the empire reactor unit-cell. This is due to the lower axial temperature gradient together with the effect of the reflector.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evidence of an oxidation induced phase transformation for a delta phase plutonium-gallium alloy

The oxidation of an ~1.5 at% Ga plutonium metal alloy in dry air as a function of time was studied using a combination of FIB-SEM, AES, and XRD. Analysis of SEM images of FIB cross-sections of the oxide allowed for direct measurement of the oxide thickness as well as determination of heterogeneity in the extent of the oxide. AES analysis performed on cross-sections of the oxide allowed for quantitative analysis of the atomic composition and semi-quantitative analysis of the chemical composition. Initial preparation of the sample was found to induce a martensitic transformation to α' - Pu with an average thickness of 233 nm. Electropolishing was found to be sufficient to fully remove the α' layer with creation of only a minimum oxide layer. Growth of the oxide in dry air was found to initially follow parabolic kinetics, with a parabolic rate constant orders of magnitude higher than expected for δ-Pu but in-line with values extrapolated to room temperature for α-Pu. Following complete oxidation of the initial α` layer, further regions of plutonium metal depleted in gallium were observed to form at the oxide / metal interface. However, gallium, as Ga 2 O 3 , was found to be enriched at the surface and present in the oxide in an amount comparable to the relative Ga:Pu ratio of the bulk metal alloy. Finally, the results presented here serve to bridge a diverse array of previous experimental and theoretical data and provide the first comprehensive view of the fate of the δ-stabilizer during formation of an oxide.

36 MATERIALS SCIENCE↗

Ethanol to diesel: a sustainable alternative for the heavy-duty transportation sector

The combustion of middle distillates (diesel and jet fuel) is responsible for the emission of more than 2 GTon of CO 2 per year worldwide. While sustainable alternatives exist for gasoline and jet fuel, we still lack sustainable alternatives for diesel. This fact is especially relevant if we consider that electrification of sectors where diesel is used is challenging. One sustainable approach for diesel production is the catalytic upgrading of ethanol. While most work in this field has focused on the dehydration/oligomerization of ethanol, this approach is limited to producing fuels that have a high degree of branching and low cetane number. Another approach is the sequential use of ethanol Guerbet coupling, leading to higher alcohols, followed by etherification, leading to large ethers which, importantly, result in a product with high cetane number. In this work, we explore the catalytic upgrading of ethanol into diesel following an approach based on the initial Guerbet coupling of ethanol followed by etherification. The results presented are a collaborative and synergic effort among process and systems engineers, experimentalist in the area of catalysis, and fuel property modelers. Here, we demonstrate experimentally the feasibility of upgrading ethanol into a diesel fuel with properties that surpass its fossil counterpart. The diesel produced has a predicted cetane number of ~70 and outstanding cold flow properties, while maintaining other properties (viscosity, density, and flash point) within expected ranges. A technoeconomic analysis performed based on a detailed biorefinery model shows that the MFSP is ~5.89$ per Gal in 2021 dollars when lignocellulosic ethanol is used, with the most relevant economic driver the cost of the ethanol feedstock. The upgrading process can be performed with a net energy gain (EROI = 1.49 > 1). An LCA analysis of greenhouse gas (GHG) emissions reveals that the use of lignocellulosic ethanol may lead to more than 50% reduction in GHG emissions compared to fossil diesel. Depending on the CO 2 emissions associated with the production of ethanol we show that in some instances the production of carbon neutral diesel fuel is possible.

09 BIOMASS FUELS↗

Chemical potential shift in organic field-effect transistors identified by soft X-ray operando nano-spectroscopy

A chemical potential shift in an organic field effect transistor (OFET) during operation has been revealed by soft X-ray operando nano-spectroscopy analysis performed using a three-dimensional nanoscale electron-spectroscopy chemical analysis system. OFETs were fabricated using ultrathin (3 ML or 12 nm) single-crystalline C10-DNBDT-NW films on SiO{sub 2} (200 nm)/Si substrates with a backgate electrode and top source/drain Au electrodes, and C 1s line profiles under biasing at the backgate and drain electrodes were measured. When applying −30 V to the backgate, there is C 1s core level shift of 0.1 eV; this shift can be attributed to a chemical potential shift corresponding to band bending by the field effect, resulting in p-type doping.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Parallel analysis tools and new visualization techniques for ultra-large climate data set

ParVis was a project funded under LAB 10-05: “Earth System Modeling: Advanced Scientific Visualization of Ultra-Large Climate Data Sets”. Argonne was the lead lab with partners at PNNL, SNL, NCAR and UC-Davis. This report covers progress from January 1st, 2013 through Dec 1st, 2014. Two previous reports covered the period from Summer, 2010, through September 2011 and October 2011 through December 2012, respectively. While the project was originally planned to end on April 30, 2013, personnel and priority changes allowed many of the institutions to continue work through FY14 using existing funds. A primary focus of ParVis was introducing parallelism to climate model analysis to greatly reduce the time-to-visualization for ultra-large climate data sets. Work in the first two years was conducted on two tracks with different time horizons: one track to provide immediate help to climate scientists already struggling to apply their analysis to existing large data sets and another focused on building a new data-parallel library and tool for climate analysis and visualization that will give the field a platform for performing analysis and visualization on ultra-large datasets for the foreseeable future. In the final 2 years of the project, we focused mostly on the new data-parallel library and associated tools for climate analysis and visualization.

54 ENVIRONMENTAL SCIENCES↗

Hardware-Based Emulator with Deep Learning Model for Building Energy Control and Prediction Based on Occupancy Sensors’ Data

Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber-physical system (CPS). In this paper, we aim to build a hardware-based emulation platform to study the occupancy data’s features, which can be further extracted by using machine learning models. In particular, we propose two hardware-based emulators to investigate the use of wired/wireless communication interfaces for occupancy sensor-based building CPS control, and the use of deep learning to predict the building energy consumption with the sensor data. We hypothesize is that the building energy consumption may be predicted by using the occupancy data collected by the sensors, and question what type of prediction model should be used to accurately predict the energy load. Another hypothesis is that an in-lab hardware/software platform could be built to emulate the occupancy sensing process. The machine learning algorithms can then be used to analyze the energy load based on the sensing data. To test the emulator, the occupancy data from the sensors is used to predict energy consumption. The synchronization scheme between sensors and the HVAC server will be discussed. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies, and used an enhanced deep learning model—which has sequence-to-sequence long short-term memory (Seq2Seq LSTM)—with an attention model to predict the building energy consumption with the preservation of the intrinsic patterns. Because the long-range temporal dependencies are captured, the Seq2Seq models may provide a higher accuracy by using LSTM architectures with encoder and decoder. Meanwhile, LSTMs can capture the temporal and spatial patterns of time series data. The attention model can highlight the most relevant input information in the energy prediction by allocating the attention weights. The communication overhead between the sensors and the HVAC control server can also be alleviated via the attention mechanism, which can automatically ignore the irrelevant information and amplify the relevant information during CNN training. Our experiments and performance analysis show that, compared with the traditional LSTM neural network, the performance of the proposed method has a 30% higher prediction accuracy.

Ye, Zhijing↗

Consideration of alternative coolants in AGR-like FHR designs

Replacing carbon-dioxide coolant in AGR-like reactor with molten salt significantly affects the reactor performance characteristics. Hence, a new core design is needed. In this work, a Multi-Objective Particle Swarm Optimisation is used to identify the most favourable configurations for a new system layout. The performed analysis examines each configuration with respect to its thermal-hydraulic performance to assess the power uprate potential which is limited by multiple temperature constraints (e.g. fuel centreline and cladding temperatures as well as the coolant freezing/boiling). The estimated maximum power was then used in the fuel burnup calculations, from which a discharge burnup and cycle average Coolant Temperature Coefficients (CTC) were obtained. As a result of the optimisation process, several families of possible solutions were identified, which form an optimal Pareto Front. The most attractive configurations in terms of achievable power density, however, were not necessarily on the Pareto front. Several coolant options are examined and compared in this paper. The newly identified design options have the potential to achieve power density that is higher than that of a typical AGR by up to a factor of five while maintaining negative CTC through the burnup cycle. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Analysis of cell-based diffusion acceleration for the slice balance approach

In this work, we perform analysis on the use of cell-based diffusion acceleration methodologies to accelerate the convergence of transport solutions discretized with the slice balance approach (SBA) on unstructured polygonal grids.We investigated both linear diffusion synthetic acceleration (DSA) and non linear diffusion acceleration (NDA), including its partial-current variant (pNDA). DSA and NDA were both shown to diverge for intermediate ranges of mesh optical thicknesses. However, pNDA and Krylov methods like GMRES and Broyden stabilized the acceleration schemes, including problems with degenerate cells formed by mesh refinement. (author)

42 ENGINEERING↗

Enabling Structured Exploration of Workflow Performance Variability in Extreme-Scale Environments

Workflows are taking an Workflows are taking an increasingly important role in orchestrating complex scientific processes in extreme scale and highly heterogeneous environments. However, to date we cannot reliably predict, understand, and optimize workflow performance. Sources of performance variability and in particular the interdependencies of workflow design, execution environment and system architecture are not well understood. While there is a rich portfolio of tools for performance analysis, modeling and prediction for single applications in homogenous computing environments, these are not applicable to workflows, due to the number and heterogeneity of the involved workflow and system components and their strong interdependencies. In this paper, we investigate workflow performance goals and identify factors that could have a relevant impact. Based on our analysis, we propose a new workflow performance provenance ontology, the Open Provenance Model-based WorkFlow Performance Provenance, or OPM-WFPP, that will enable the empirical study of workflow performance characteristics and variability including complex source attribution.

Enabling structured workflows↗

Integrated System and Application Continuous Performance Monitoring and Analysis Capability (Final)

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia’s Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia’s ElectroMagnetic Plasma In Realistic Environments (EMPIRE) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia’s HPC users.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The importance of experimental design on measurement of dynamic interfacial tension and interfacial rheology in diffusion-limited surfactant systems

Pendant bubble and drop devices are invaluable tools in understanding surfactant behavior at fluid–fluid interfaces. The simple instrumentation and analysis are used widely to determine adsorption isotherms, transport parameters, and interfacial rheology. However, much of the analysis performed is developed for planar interfaces. Moreover, the application of a planar analysis to drops and bubbles (curved interfaces) can lead to erroneous and unphysical results. We revisit this analysis for a well-studied surfactant system at air–water interfaces over a wide range of curvatures as applied to both expansion/contraction experiments and interfacial elasticity measurements. The impact of curvature and transport on measured properties is quantified and compared to other scaling relationships in the literature. Our results provide tools to design interfacial experiments for accurate determination of isotherm, transport and elastic properties.

36 MATERIALS SCIENCE↗