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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Pathways to IEC Standards for Heliostat Design Qualification and Site Acceptance in Central Receiver CSP Applications

This paper surveys the existing landscape of standards relevant to heliostats, identifies their gaps, and proposes a path forward to a comprehensive set of heliostat guidelines, technical specifications, and standards under the framework of International Electrotechnical Commission (IEC) TC 117. Gaps in existing guidelines and standards are surveyed using a three-tiered taxonomy: component-level, heliostat-level, and field-level. At each level, the gap analysis is followed by a proposal for a coordinated path forward on the development of standards. At the component level, advances in the understanding of wind loading should inform a technical specification for drives and structures. Reflectors require consolidation of measurement guidelines into existing standards documents. Communications & controls require technical standards to inform their selection and secure implementation. At the heliostat level, IEC 62817 (solar trackers) adequately characterizes drive systems, structures, and electronics, but requires adaptation to heliostats' use patterns, operating modes, and expected life cycles. IEC 62817 does not address heliostat beam quality and pointing accuracy, but the process for determining both is elaborated in the SolarPACES Guideline for Heliostat Performance Testing. This SolarPACES document requires two main modifications: adaptation to IEC language and inclusion of testing after heliostats which have undergone accelerated weathering and mechanical cycling (to understand performance degradation). At the field level, IEC 62862-4-2 addresses the function and control of heliostat fields but does not cover the statistically rigorous testing of heliostat groups, or field performance factors like security and soiling. The addition of documents under IEC-62862-4 is proposed to address this gap.

beam↗
DOE OSTI2023

Measurements of sound propagation in Mars' lower atmosphere

Acoustics has become extraterrestrial and Mars provides a new natural laboratory for testing sound propagation models compared to those ones on Earth. Owing to the unique combination of a microphone and two sound sources, the Ingenuity helicopter and the SuperCam laser-induced sparks, the Mars 2020 Perseverance rover payload enables the in situ characterization of unique sound propagation properties of the low-pressure CO 2 -dominated Mars atmosphere. In this study, we show that atmospheric turbulence is responsible for a large variability in the sound amplitudes from laser-induced sparks. This variability follows the diurnal pattern of turbulence. In addition, acoustic measurements acquired over one Martian year reveal a variation of the sound intensity by a factor of 1.8 from a constant source due to the seasonal cycle of pressure and temperature that significantly modifies the acoustic impedance and shock-wave formation. Finally, we show that the evolution of the Ingenuity tones and laser spark amplitudes with distance is consistent with one of the existing sound absorption models, which is a key parameter for numerical simulations applied to geophysical experiments on CO 2 -rich atmospheres. Overall, these results demonstrate the potential of sound propagation to interrogate the Mars environment and will therefore help in the design of future acoustic-based experiments for Mars or other planetary atmospheres such as Venus and Titan.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing

Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magnetic domain wall (DW) propagation in a patterned nanotrack and firing tied to the resistance change of a magnetic tunnel junction (MTJ), captured in the domain wall-magnetic tunnel junction (DW-MTJ) device. Leaking, relaxation of a neuron when it is not under stimulation, is also predicted to be implemented based on DW drift as a DW relaxes to a low energy position, but it has not been well explored or demonstrated in device prototypes. Here, in this work, we study DW-MTJ artificial neurons capable of leaky integrate-and-fire (LIF) behavior and demonstrate geometry-dependent leaking dynamics that results in repeatable, tunable LIF operation. Studying the behavior of five different device designs, we show tuning the geometry, stimulating fields and currents, and location of electrical contacts results in a wide range of neuron behavior. Additionally, implementation of an asymmetric notch allows for nonlinear pinning which increased expressivity without sacrificing leaking. The measured behavior is implemented in a simulated spiking neural network that outperforms a 1D model of continuous DW motion and approaches the performance of an ideal LIF activation function. The results show that the analog LIF capability of DW-MTJ neurons combines many desirable neuron functions into a single device, which can result in varied forms of multifunctional neuromorphic computing.

42 ENGINEERING↗
DOE OSTI2026

Imaging supermoiré relaxation in helical trilayer graphene

In twisted van der Waals materials, local atomic relaxation can alter the underlying electronic structure. Characterizing lattice reconstruction and its susceptibility to strain is essential for understanding emergent electronic states, especially in multilayers in which interference between moiré lattices yields larger supermoiré patterns whose energy is highly sensitive to local stacking. Here, in this study, we image spatial modulations in the electronic character of helical trilayer graphene, which indicate relaxation into a superstructure of large domains with uniform moiré periodicity. We show that the supermoiré domain size is increased by strain and can be altered in the same device while preserving the local properties within each domain. Finally, we observe a higher conductance at the domain boundaries, consistent with predictions that they host counterpropagating edge modes. Our work provides a real-space visualization of moiré-periodic domains, reveals two independently tunable length scales and demonstrates strain engineering as a route towards designing correlated topological networks at the supermoiré scale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cross-correlation analysis of X-ray photon correlation spectroscopy to extract rotational diffusion coefficients

Coefficients for translational and rotational diffusion characterize the Brownian motion of particles. Emerging X-ray photon correlation spectroscopy (XPCS) experiments probe a broad range of length scales and time scales and are well-suited for investigation of Brownian motion. While methods for estimating the translational diffusion coefficients from XPCS are well-developed, there are no algorithms for measuring the rotational diffusion coefficients based on XPCS, even though the required raw data are accessible from such experiments. In this paper, we propose angular-temporal cross-correlation analysis of XPCS data and show that this information can be used to design a numerical algorithm (Multi-Tiered Estimation for Correlation Spectroscopy [MTECS]) for predicting the rotational diffusion coefficient utilizing the cross-correlation: This approach is applicable to other wavelengths beyond this regime. We verify the accuracy of this algorithmic approach across a range of simulated data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-Driven Template Discovery Using Graph Convolutional Neural Networks

Modeling adversarial activities is a critical component of developing high-con?dence indicators of efforts to acquire, fabricate, proliferate, and/or deploy weapons of mass terror (WMTs). Current approaches to generating representative patterns of interest (a.k.a templates) from the real-world domains involve a Subject Matter Expert (SME)-guided manual process. The goal of Data-Driven Template Discovery (DDTD) is to use a (potentially small) set of SME generated templates to discover other previously unknown and interesting templates in an attributed graph. A template is an activity pattern describing a set of interactions among a group of nodes in the graph. The motivation behind DDTD is to expand the original set of templates, without having SMEs craft all the templates by hand. DDTD also provides seed templates to SMEs, to help them construct larger, high-?delity, and scenario-oriented templates. In these cases, obtaining a larger set of templates that are related (contain similar signals) to the original set is of great value. In this work, we propose to use Graph Convolutional Neural Networks (GCNs) to discover new templates that are heavily related to the original set. GCNs are a family of Neural Network (NN) architectures especially designed to work directly on graphs. In contrast to the traditional NNs, that require considerable amounts of labeled data, GCNs do not require a big labeled training set because they can directly leverage the graph structure instead. This property makes GCNs the perfect tool for creating activity templates.

Joaristi, Mikel↗
DOE OSTI2020

AGC 3 Irradiated Material Properties Analysis

This report documents the analysis of the irradiated material property data from the Advanced Graphite Creep (AGC)-3 graphite specimens. This is the third in a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades. The AGC-3 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 800°C, beginning with irradiation Cycle 152B on November 28, 2012 and ending with Cycle 155B on April 12, 2014, with a total received dose range of 0.9–3.7 dpa. Larger creep and control specimens located more centrally in the capsule received a dose of 1.0 – 3.7 dpa. AGC-3 was designed to provide irradiation conditions similar to AGC-1 and AGC-2 capsules (similar graphite grades tested, specimen dimensions, mechanical loading conditions) but at a different nominal irradiation temperature of 800°C. AGC-3 was irradiated for a short duration to provide material property values at lower dose levels. AGC-4 will have a longer duration and provide material property values at higher dose levels. After irradiation, material property and dimensional strain measurements were conducted on all AGC-3 specimens (from 11 nuclear graphite grades) using the same equipment and approved standards as were conducted before irradiation. The specimen loading configuration for all graphite grades within AGC-3 followed a similar pattern as earlier AGC capsules to provide easy future comparison of all irradiated material property data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The large-area hybrid-optics CLAS12 RICH: First years of data-taking

The CLAS12 deep-inelastic scattering experiment at the upgraded 12 GeV continuous electron beam accelerator facility of Jefferson Lab conjugates luminosity and wide acceptance to study the 3D nucleon structure in the yet poorly explored valence region, and to perform precision measurements in hadron spectroscopy. A large area ring-imaging Cherenkov detector has been designed to achieve the required hadron identification in the momentum range from 3 GeV/c to 8 GeV/c, with the kaon rate about one order of magnitude lower than the rate of pions and protons. The adopted solution comprises aerogel radiator and composite mirrors in a novel hybrid optics design, where either direct or reflected light could be imaged in a high-packed and high-segmented photon detector. The first RICH module was assembled during the second half of 2017 and installed at the beginning of January 2018, in time for the start of the experiment. The second RICH module, planned with the goal to be ready for the beginning of the operation with polarized targets, has been timely built despite the complications caused by the pandemic crisis and successfully installed in June 2022. Finally, the detector performance is here discussed with emphasis on the operation and stability during the data-taking, calibration and alignment procedures, reconstruction and pattern recognition algorithms, and particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Performance of a triple-GEM detector with capacitive-sharing 3-coordinate (X–Y–U)-strip anode readout

The concept of capacitive-sharing readout, described in detail in a previous study, offers the possibility for the development of high-performance three-coordinates (X--Y--U)-strip readout for Micro Pattern Gaseous Detectors (MPGDs) using simple standard PCB fabrication techniques. Capacitive-sharing (X--Y--U)-strip readout allows simultaneous measurement of the Cartesian coordinates x and y of the position of the particles together with a third coordinate u along the diagonal axis in a single readout PCB. This provides a powerful tool to address multiple-hit ambiguity and enable pattern recognition capabilities in moderate particle flux environment of collider or fixed target experiments in high energy physics HEP) and nuclear physics (NP). We present in this paper the performance of a 10 cm × 10 cm triple-GEM detector with capacitive-sharing (X--Y--U)-strip anode readout. Spatial resolutions of the order of $\sigma_{x}^{res}$ = 71.6 $\pm$ 0.8 $\mu$m for X-strips, $\sigma_{y}^{res}$ = 56.2 $\pm$ 0.9 $\mu$m for Y-strips and $\sigma_{u}^{res}$ = 75.2 $\pm$ 0.9 $\mu$m for U-strips have been obtained at a beam test at Thomas Jefferson National Accelerator Facility (Jefferson Lab). Modifications of the readout design of future prototypes to improve the spatial resolution and challenges in scaling to large-area MPGDs are discussed.

(X-Y-U) strip↗
DOE OSTI2021

Floodplain Wetland Channel Planform, Cross-Sectional Morphology, and Sediment Characteristics Along an Estuarine to Tidal River Gradient

The formation of wetland channel networks on coastal river floodplains is affected by spatial transitions in tidal-fluvial processes. This study evaluated sedimentation patterns in tidal marshes on the 147-km tidal Columbia River and its 87-km estuary and characterized the cross-sectional geometry and planform morphometry of tidal wetlands along the estuarine to riverine gradient. Tidal marshes were predominantly depositional (median 0.7 cm yr-1, primarily silt), consistent with late-Holocene rates. Marsh sediment accretion rate increased with annual maximum 7-day average daily maximum water depth. Elevation was negatively correlated with accretion rate in the tidal river and positively correlated with total organic carbon (TOC%) in the tidal river and estuary. TOC% was greater in the estuary and, like percent fines, greater farther from the main-channel Columbia River. For four single-channel and six channel-network planforms of tidal marsh, shrub-dominated, and forested wetlands: (1) Spatial patterns of cross-sectional morphology conformed to typical coastal wetland morphology in estuarine reaches up to the tidal river. (2) Reach-based and common slope linear models for channel perimeter on wetland area were predictive in the estuary (R2 > 0.81) and differed between island (n = 144) and mainland (n = 164) wetlands. No planform linear models were predictive for the entire study area or the tidal river. No models for channel outlets were acceptable. (3) Channel perimeter, surface area, and outlets were all highly variable within and among estuarine–riverine reaches. Analyses of sediment, cross-section, and planform support the use of a “natural network paradigm” for wetland-restoration design on tidal river floodplains.

channel morphology↗
DOE OSTI2025

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗
DOE OSTI2020

Identifying geologic characteristics and operational decisions to meet global carbon sequestration goals

Geologic carbon sequestration is the process of injecting and storing CO 2 in subsurface reservoirs and is an essential technology for global environmental security (e.g., climate change mitigation) and economic security (e.g., CO 2 tax credits). To meet energy, economic, and environmental goals, society will have to identify vast volumes of high-capacity, low-cost, and viable storage reservoirs for sequestering CO 2 . In turn, this requires understanding how major geologic characteristics (such as reservoir depth, thickness, permeability, porosity, and temperature) and design and operational decisions (such as injection well spacing) impact CO 2 injection rates, storage capacity, and economics. Although many numerical simulation tools exist, they cannot repeat the required thousands or millions of simulations to identify ideal reservoir properties and the sensitivity and interaction between geologic parameters and operational decisions. Here, we use SCO 2 T—a fast-running, reduced-order modeling framework—to explore the sensitivity of major geologic parameters and operational decisions to engineering (CO 2 injection rates, plume dimensions, and storage capacities and effectiveness) and costs. Our results show, for the first time, benefits and impacts such as allowing CO 2 plumes to overlap, how different well spacing patterns affect CO 2 sequestration, the effects on costs of including brine treatment and disposal, and the effect of restricting injection rates to 1 MtCO 2 per y based on well limitations. We reveal multiple novel and unintuitive findings including: (i) deeper reservoirs have reduced carbon sequestration costs until injection rates reach 1 MtCO 2 per y, at which point deeper reservoirs become more expensive, (ii) thicker formations allow for increased injection rates and storage capacity, but thickness barely impacts plume areas, (iii) higher geothermal gradients result in reduced sequestration costs, unless brine treatment/disposal costs are included, at which point reservoirs having lower geothermal gradients are more economical because they produce less brine for each unit of injected CO 2 , and (iv) allowing plumes to overlap has a significantly positive impact of increasing storage capacities but has only a small influence on reducing sequestration costs. Altogether, our results illustrate new scientific conclusions to help identify suitable sites to inject and store CO 2 , to help understand the complex interaction between geology and resulting costs, and to help support the pursuit of meeting global sequestration targets.

58 GEOSCIENCES↗
DOE OSTI2023

A Mobile Edge Computing Framework for Traffic Optimization At Urban Intersections Through Cyber-Physical Integration

The stop-and-go traffic pattern on urban roads often results in excessive energy consumption because of unnecessary vehicle braking, idling, and accelerations. With the widespread and increased use of automobiles, this traffic pattern creates many negative impacts (e.g., delayed travel time, air pollution, and additional carbon emission) on the sustainability of our cities. Taking advantage of the recent emerging Internet of Things (IoT) and edge computing paradigms, we propose a mobile edge computing framework that integrates the capability of real-time vehicle-to-infrastructure communication and intelligent speed optimization algorithms into a mobile app to optimize individual vehicles' driving speed at signalized intersections. The optimization aims to mitigate the stop-and-go traffic pattern and its undesirable consequences in urban transportation systems. The framework consists of (1) a cyberinfrastructure-enabled dynamic messaging system for retrieving and delivering real-time traffic and signal phase and timing information from IoT-connected signal controllers and sensors, (2) a real-time speed optimization algorithm for generating intelligent speed advisory using vehicle's information (e.g., GPS and driving directions from mobile sensing) and corresponding signal and traffic information, and (3) an ad-hoc mobile computing environment that converts drivers' smartphones into edge devices to host the speed optimization algorithms for enabling intelligent advisory on the vehicle's driving speed within signalized corridors. The paper presents the design and implementation of the proposed framework. Finally, we demonstrate the feasibility, usefulness, and energy-saving benefits of our proposed framework and its prototyping mobile app on urban transportation systems through traffic simulation, real-vehicle laboratory experiments, an evaluative survey, and field communication tests. The simulation-based energy evaluation results show that the 100% usage of the mobile app can achieve 24% energy savings in the transportation system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

DEMOS (Demographic Microsimulator Tool for Longitudinal Synthetic Population) [SWR-25-135] related to NLR SWR-26-076

The Demographic Microsimulator (DEMOS) is an agent-based simulation framework used to model the evolution of population demographic characteristics and lifecycle events, such as education attainment, marital status, and other key transitions. DEMOS modules are designed to capture the interdependencies between short-term and long-term lifecycle events, which are often influential in downstream transportation and land-use modeling. A key feature of DEMOS is its ability to track changes in an agent’s demographic status from year t to year t + 1. This structure allows the model to evolve populations over any user-defined time horizon. As a result, DEMOS is well suited for analyzing medium- and long-term transportation-related decisions, including household vehicle transactions (e.g., purchasing, selling, or replacing vehicles) and work location choices. Core features of DEMOS include the modeling of more than ten lifecycle events, behaviorally realistic patterns informed by long-running panel data, explicit representation of interdependencies among lifecycle processes, and a flexible, modular simulation architecture. A technical memorandum describing DEMOS is available here. The memorandum provides an overview of the framework’s functionality, model structure, input and output data, and its applications in transportation planning and broader policy analysis contexts. Interested readers are also encouraged to consult the paper listed below for additional details on the DEMOS methodology. Sun, Bingrong, Shivam Sharda, Venu M. Garikapati, Mohamed Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas de Lima, Ling Jin, C. Anna Spurlock, and Paul Waddell. "Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life." Transportation Research Record (2025): 03611981251333339.

Sun, Bingrong [National Laboratory of the Rockies ↗
DOE OSTI2021

Nickel-based superalloy single crystals fabricated via electron beam melting

Additive manufacturing technologies have emerged as potential disruptive processes whose possible impacts range from supply chain logistics, prototyping, and novel materials synthesis. Numerous works illustrate the ability to control mi- crostructure in fusion based processes and a few recent authors have even produced single crystals. However, a number of open questions remain regarding the process window which enables printing of single crystals. Furthermore, it has been observed that these additively manufactured single crystals exhibit a preferred $\langle$011$\rangle$ secondary orientation. In this work we investigate fabrication conditions which enable printing of single crystals via electron beam melting. A space filling design of experiments is utilized to efficiently explore the fabrication space. Single crystals were success- fully obtained using both commercially available powders and custom melt alloys. Microstructures obtained via these exploratory experiments exhibited a continuum of columnar structures ranging from weakly textured polycrystals, near single crystal, and fully single crystalline material. Complex geometry experiments are performed to study the grain selection mechanism. We find that the grain selection mechanism is independent of the bulk scale geometry and must therefore by driven by local heat transfer and solidification dynamics. Furthermore, grain selection is shown to be driven by competing driving forces; one which prefers epitaxial growth and another which is driven by the imposed scan pattern geometry. Finally, a mechanism is proposed for the anomalous secondary orientation preference.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multibeam Electron Diffraction

One of the primary uses for transmission electron microscopy (TEM) is to measure diffraction pattern images in order to determine a crystal structure and orientation. In nanobeam electron diffraction (NBED), we scan a moderately converged electron probe over the sample to acquire thousands or even millions of sequential diffraction images, a technique that is especially appropriate for polycrystalline samples. However, due to the large Ewald sphere of TEM, excitation of Bragg peaks can be extremely sensitive to sample tilt, varying strongly for even a few degrees of sample tilt for crystalline samples. In this paper, we present multibeam electron diffraction (MBED), where multiple probe-forming apertures are used to create multiple scanning transmission electron microscopy (STEM) probes, all of which interact with the sample simultaneously. We detail designs for MBED experiments, and a method for using a focused ion beam to produce MBED apertures. We show the efficacy of the MBED technique for crystalline orientation mapping using both simulations and proof-of-principle experiments. We also show how the angular information in MBED can be used to perform 3D tomographic reconstruction of samples without needing to tilt or scan the sample multiple times. Finally, we also discuss future opportunities for the MBED method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Direct Visualization of Current-Stimulated Oxygen Migration in YBa 2 Cu 3 O 7–δ Thin Films

The past years have witnessed major advancements in all-electrical doping control on cuprates. In the vast majority of cases, the tuning of charge carrier density has been achieved via electric field effect by means of either a ferroelectric polarization or using a dielectric or electrolyte gating. Unfortunately, these approaches are constrained to rather thin superconducting layers and require large electric fields in order to ensure sizable carrier modulations. In this work, we focus on the investigation of oxygen doping in an extended region through current-stimulated oxygen migration in YBa 2 Cu 3 O 7–δ superconducting bridges. The underlying methodology is rather simple and avoids sophisticated nanofabrication process steps and complex electronics. Here, a patterned multiterminal transport bridge configuration allows us to electrically assess the directional counterflow of oxygen atoms and vacancies. Importantly, the emerging propagating front of current-dependent doping δ is probed in situ by optical microscopy and scanning electron microscopy. The resulting imaging techniques, together with photoinduced conductivity and Raman scattering investigations, reveal an inhomogeneous oxygen vacancy distribution with a controllable propagation speed permitting us to estimate the oxygen diffusivity. These findings provide direct evidence that the microscopic mechanism at play in electrical doping of cuprates involves diffusion of oxygen atoms with the applied current. The resulting fine control of the oxygen content would permit a systematic study of complex phase diagrams and the design of electrically addressable devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Studying visual search without an eye tracker: an assessment of artificial foveation

Abstract Eye tracking is a useful tool for studying human cognition, both in the laboratory and in real-world applications. However, there are cases in which eye tracking is not possible, such as in high-security environments where recording devices cannot be introduced. After facing this challenge in our own work, we sought to test the effectiveness of using artificial foveation as an alternative to eye tracking for studying visual search performance. Two groups of participants completed the same list comparison task, which was a computer-based task designed to mimic an inventory verification process that is commonly performed by international nuclear safeguards inspectors. We manipulated the way in which the items on the inventory list were ordered and color coded. For the eye tracking group, an eye tracker was used to assess the order in which participants viewed the items and the number of fixations per trial in each list condition. For the artificial foveation group, the items were covered with a blurry mask except when participants moused over them. We tracked the order in which participants viewed the items by moving their mouse and the number of items viewed per trial in each list condition. We observed the same overall pattern of performance for the various list display conditions, regardless of the method. However, participants were much slower to complete the task when using artificial foveation and had more variability in their accuracy. Our results indicate that the artificial foveation method can reveal the same pattern of differences across conditions as eye tracking, but it can also impact participants’ task performance.

47 OTHER INSTRUMENTATION↗