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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Removal of Selenium Oxyanions from Aqueous Solutions by Ion Exchange: Equilibrium, Kinetics, and Mechanistic Modeling

Selenium (Se) is an essential micronutrient but toxic at high concentrations, posing challenges for water treatment. This study investigated the removal of selenate (SeO 4 2– ) and selenite (SeO 3 2– ) using the strong-base anion-exchange resin IRA-900, particularly in the presence of competing sulfate (SO 4 2– ). The performance of the commercially available resin IRA-900 was systematically investigated. The batch equilibrium behavior was studied in both single- and binary-component systems, and the kinetic behavior was investigated in single-component systems. Results confirmed a selectivity order of SeO 4 2– > SO 4 2– > SeO 3 2– , indicating preferential SeO 4 2– removal over competing SO 4 2– but lower affinity for SeO 3 2– . The maximum total exchange capacity was determined to be 2.04 mequiv/g. Furthermore, SeO 3 2– uptake was found to be pH-dependent, whereas SeO 4 2– uptake remained stable across a broad pH range. From a modeling perspective, the Law of Mass Action model effectively described equilibrium data, and a transport–reaction modeling framework captured removal kinetics of oxyanions including film and intraparticle diffusion. Finally, X-ray photoelectron spectroscopy confirmed ion exchange between chloride and Se oxyanions as the primary removal mechanism. These findings provide fundamental insights into the removal of Se oxyanions from aqueous solutions by ion exchange.

IRA-900↗
DOE OSTI2022

Anodic Shock-Triggered Exsolution of Metal Nanoparticles from Perovskite Oxide

Nanoparticles decorated electrodes (NDEs) are useful in fuel cells, electrolyzers, water treatment, and chemical synthesis. Here, in this study, we show that by rapidly bringing a mixed ionic-electronic conductor outside its electrochemical stability window, one can achieve uniform dispersion of metallic nanoparticles inside its bulk and at the surface and improve its electrocatalytic performance when back under normal functional conditions. Surprisingly, this can happen under anodic as well as cathodic current/voltage shocks in an ABO 3 perovskite oxide, La 0.4 Ca 0.4 Ti 0.88 Fe 0.06 Ni 0.06 O 3-δ (LCTFN), across a wide range of H 2 /O 2 gas environments at 800 °C. One possible mechanism for bulk Fe 0 /Ni 0 precipitation under anodic shock condition is the incomplete oxygen oxidation (O 2 – → O α– , 0 < α < 2), migration and escape of oxygen to interfaces, and “whiplash” transition-metal reduction due to low electronic conductivity. We show that both cathodic and anodic shocks can produce NDEs to enhance electrocatalytic performance, potentially improving the flexibility of this approach in practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Donnan potential revealed

Selective transport of solutes across a membrane is critical for many biological, water treatment and energy conversion and storage systems. When a charged membrane is equilibrated with an electrolyte, an unequal distribution of ions arises between phases, generating the so-called Donnan electrical potential at the solution/membrane interface. The Donnan potential results in the partial exclusion of co-ion, providing the basis of permselectivity. Although there are well-established ways to indirectly estimate the Donnan potential, it has been widely reported that it cannot be measured directly. Here we report the first direct measurement of the Donnan potential of an ion exchange membrane equilibrated with salt solutions. Our results highlight the dependence of the Donnan potential on external salt concentration and counter-ion valence, and show a reasonable agreement with current theoretical models of IEMs, which incorporate ion activity coefficients. By directly measuring the Donnan potential, we eliminate ambiguities that arise from limitations inherent in current models.

25 ENERGY STORAGE↗
DOE OSTI2023

Substantial lifetime enhancement for Si-based photoanodes enabled by amorphous TiO2 coating with improved stoichiometry

Abstract Amorphous titanium dioxide (TiO 2 ) film coating by atomic layer deposition (ALD) is a promising strategy to extend the photoelectrode lifetime to meet the industrial standard for solar fuel generation. To realize this promise, the essential structure-property relationship that dictates the protection lifetime needs to be uncovered. In this work, we reveal that in addition to the imbedded crystalline phase, the presence of residual chlorine (Cl) ligands is detrimental to the silicon (Si) photoanode lifetime. We further demonstrate that post-ALD in-situ water treatment can effectively decouple the ALD reaction completeness from crystallization. The as-processed TiO 2 film has a much lower residual Cl concentration and thus an improved film stoichiometry, while its uniform amorphous phase is well preserved. As a result, the protected Si photoanode exhibits a substantially improved lifetime to ~600 h at a photocurrent density of more than 30 mA/cm 2 . This study demonstrates a significant advancement toward sustainable hydrogen generation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tailoring polyvinyl alcohol-sodium alginate (PVA-SA) hydrogel beads by controlling crosslinking pH and time

Abstract Hydrogel-encapsulated catalysts are an attractive tool for low-cost intensification of (bio)-processes. Polyvinyl alcohol-sodium alginate hydrogels crosslinked with boric acid and post-cured with sulfate (PVA-SA-BS) have been applied in bioproduction and water treatment processes, but the low pH required for crosslinking may negatively affect biocatalyst functionality. Here, we investigate how crosslinking pH (3, 4, and 5) and time (1, 2, and 8 h) affect the physicochemical, elastic, and process properties of PVA-SA-BS beads. Overall, bead properties were most affected by crosslinking pH. Beads produced at pH 3 and 4 were smaller and contained larger internal cavities, while optical coherence tomography suggested polymer cross-linking density was higher. Optical coherence elastography revealed PVA-SA-BS beads produced at pH 3 and 4 were stiffer than pH 5 beads. Dextran Blue release showed that pH 3-produced beads enabled higher diffusion rates and were more porous. Last, over a 28-day incubation, pH 3 and 4 beads lost more microspheres (as cell proxies) than beads produced at pH 5, while the latter released more polymer material. Overall, this study provides a path forward to tailor PVA-SA-BS hydrogel bead properties towards a broad range of applications, such as chemical, enzymatic, and microbially catalyzed (bio)-processes.

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

Effects of film thickness on electrochemical properties of nanoscale polyethylenedioxythiophene (PEDOT) thin films grown by oxidative molecular layer deposition (oMLD)

Poly(3,4-ethylene dioxythiophene) (PEDOT) has a high theoretical charge storage capacity, making it of interest for electrochemical applications including energy storage and water desalination. Nanoscale thin films of PEDOT are particularly attractive for these applications to enable faster charging. Recent work has demonstrated that nanoscale thin films of PEDOT can be formed using sequential gas-phase exposures via oxidative molecular layer deposition, or oMLD, which provides advantages in conformality and uniformity on high aspect ratio substrates over other deposition techniques. But to date, the electrochemical properties of these oMLD PEDOT thin films have not been well-characterized. In this work, we examine the electrochemical properties of 5–100 nm thick PEDOT films formed using 20–175 oMLD deposition cycles. We find that film thickness of oMLD PEDOT films affects the orientation of ordered domains leading to a substantial change in charge storage capacity. Interestingly, we observe a minimum in charge storage capacity for an oMLD PEDOT film thickness of ~30 nm (60 oMLD cycles at 150 °C), coinciding with the highest degree of face-on oriented PEDOT domains as measured using grazing incidence wide angle X-ray scattering (GIWAXS). Thinner and thicker oMLD PEDOT films exhibit higher fractions of oblique (off-angle) orientations and corresponding increases in charge capacity of up to 120 mA h g -1 . Electrochemical measurements suggest that higher charge capacity in films with mixed domain orientation arise from the facile transport of ions from the liquid electrolyte into the PEDOT layer. Greater exposure of the electrolyte to PEDOT domain edges is posited to facilitate faster ion transport in these mixed domain films. In conclusion, these insights will inform future design of PEDOT coated high-aspect ratio structures for electrochemical energy storage and water treatment.

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

Enhancing the electron mobility in Si-doped (010) β-Ga 2 O 3 films with low-temperature buffer layers

We demonstrate a new substrate cleaning and buffer growth scheme in β-Ga 2 O 3 epitaxial thin films using metal–organic vapor phase epitaxy (MOVPE). For the channel structure, a low-temperature (LT, 600 °C) un-doped Ga 2 O 3 buffer was grown, followed by a transition layer to a high-temperature (HT, 810 °C) Si-doped Ga 2 O 3 channel layers without growth interruption. The (010) Ga 2 O 3 Fe-doped substrate cleaning uses solvent cleaning, followed by additional hydrofluoric acid (49% in water) treatment for 30 min before the epilayer growth. This step is shown to compensate the parasitic Si channel at the epilayer–substrate interface that originates from the substrate polishing process or contamination from the ambient. From secondary ion mass spectroscopy (SIMS) analysis, the Si peak atomic density at the substrate interface is found to be several times lower than the Fe atomic density in the substrate—indicating full compensation. The elimination of the parasitic electron channel at the epi–substrate interface was also verified by electrical (capacitance–voltage profiling) measurements. In the LT-grown (600 °C) buffer layers, it is seen that the Fe forward decay tail from the substrate is very sharp, with a decay rate of ∼9 nm/dec. X-ray off-axis rocking curve ω-scans show very narrow full width at half maximum (FWHM) values, similar to the as-received substrates. These channels show record high electron mobility in the range of 196–85 cm 2 /V⋅s in unintentionally doped and Si-doped films in the doping range of 2 × 10 16 –1 × 10 20 cm −3 . Si delta-doped channels were also grown utilizing this substrate cleaning and the hybrid LT buffers. Record high electron Hall mobility of 110 cm 2 /V⋅s was measured for sheet charge density of 9.2 × 10 12 cm −2 . This substrate cleaning, combined with the LT buffer scheme, shows the potential of designing Si-doped β-Ga 2 O 3 channels with exceptional transport properties for high-performance Ga 2 O 3 -based electron devices.

Bhattacharyya, Arkka↗
DOE OSTI2023

Mechanism of monovalent and divalent ion mobility in Nafion membrane: An atomistic simulation study

Polymer cation exchange membranes (CEMs) are widely used in water treatment processes. The fundamental factors that control the separation and selectivity of cations with different valences in CEMs are not fully understood. In this study, we use atomistic molecular dynamics simulations to investigate the underlying molecular mechanisms that control the mobility of cations with different valences in Nafion membranes. Our results indicate structural differences in binding of monovalent and divalent cations, which gives rise to differences in ion diffusion in Nafion. Monovalent cations are shown to be “territorially” bound, i.e., bound while partially hydrated, to the fixed charge groups whereas divalent cations are shown to be “site” bound, i.e., bound while fully dehydrated, to the charge groups on the polymer. This difference in binding structure gives rise to differences in transport characteristics of cations in Nafion.

Chemistry↗
DOE OSTI2025

Interfacial electroneutrality controls transport of asymmetric salts through charge-patterned mosaic membranes

Membranes that selectively enhance target solute permeation while rejecting competing species are essential for precision separations. This study introduces charge-patterned mosaic membranes (CMMs) that selectively transport divalent asymmetric salts by leveraging a net-neutral membrane–solution interface. This mechanism, dictated by the charge ratio of positive and negative domains on the membrane surface and the balance of cations and anions in the salt, is supported by analytical, numerical, and experimental results. Analytical solutions identified cationic domain coverages (f + ) of 33%, 50%, and 66% as optimal for the selective transport of +2:−1 salts, +1:−1 salts, and +1:−2 salts, respectively, under conditions where the pattern size (L) is significantly larger than the Debye length. Numerical simulations and experiments using CMMs with alternating charged-stripes inkjet-printed onto nanostructure copolymer substrates confirmed these findings. By varying stripe widths to control f + , pressure-driven filtration experiments demonstrated selective enrichment of MgCl 2 and K 2 SO 4 at the predicted f + values, with deviations from these values leading to salt rejection. These results highlight the pivotal role of a net-neutral interface in enabling asymmetric salt enrichment. This study positions CMMs as a versatile platform for tuning ion selectivity, addressing challenges in resource recovery, water treatment, and precision separations.

additive manufacturing↗
DOE OSTI2023

Adaptive Online Multivariate Signal Extraction With Locally Weighted Robust Polynomial Regression

High-frequency, multivariate data collected in real-time and used to control or make decisions regarding a process’ operation often contain some noise and outliers. Thus, a method to extract the signal is needed in order to reduce the number and magnitude of control-based adjustments that are implemented. Such a method must be (i) online, depending only on past and current observations; (ii) fast, producing a smooth value more quickly than the measurement frequency; (iii) robust, ignoring brief bursts of erroneously measured values; (iv) multivariate, ignoring observations that are jointly unusual; (v) adaptive, adjusting to periods of rapid fluctuation in the signal versus periods of stability; and (vi) purely data-driven, not incorporating any information about the process from which the data are collected. Most existing methods are only able to address a subset of these six features. Furthermore, we also require the method to be nonlinear, providing a local nonlinear estimate of the signal. In this work, we propose a novel, real-time signal extraction method based on a local, robust polynomial fit. We demonstrate the performance of our method compared to a state-of-the-art competitor through simulation. For illustration, the methodology is applied to data collected from a reverse osmosis water treatment process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Losing Control of Your Linear Network? Try Resilience Theory

Resilience of cyber-physical networks to unexpected failures is a critical need widely recognized across domains. For instance, power grids, telecommunication networks, transportation infrastructures, and water treatment systems have all been subject to disruptive malfunctions and catastrophic cyberattacks. Following such adverse events, we investigate scenarios where a node of a linear network suffers a loss of control authority over some of its actuators. These actuators are not following the controller's commands and are instead producing undesirable outputs. The repercussions of such a loss of control can propagate and destabilize the whole network despite the malfunction occurring at a single node. To assess system vulnerability, we establish resilience conditions for networks with a subsystem enduring a loss of control authority over some of its actuators. Furthermore, we quantify the destabilizing impact on the overall network when such a malfunction perturbs a nonresilient subsystem. We illustrate our resilience conditions on two academic examples, on an islanded microgrid and on the linearized IEEE 39-bus system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Comparative physiological and genomic characterization of a novel Nitrobacter vulgaris strain from a nitrate-contaminated subsurface

Nitrite-oxidizing bacteria (NOB) represent a crucial node in the global nitrogen cycle. By catalyzing the second step of nitrification—the oxidation of nitrite to nitrate to generate energy for growth—NOB activity controls the fate of nitrite (NO 2 - ) in aerobic environments. Despite thriving in diverse environments, including soils, freshwater, marine ecosystems, subsurface habitats, and water treatment systems, organisms capable of nitrite oxidation are confined to Nitrobacter, Nitrospira, Nitrospina, Nitrotoga, and a few other specific lineages. The genus Nitrobacter, recognized for its facultative heterotrophic metabolism, is often associated with high-nitrogen environments. Here, we report the physiological characterization of a novel strain, Nitrobacter vulgaris strain MLSD-S22, isolated from a nitrate- and heavy-metal-contaminated subsurface. Growth inhibition experiments revealed that strain MLSD-S22 and the N. vulgaris type strain Z exhibited similar sensitivities to nitrite and nitrate, with nitrite being the most inhibitory. Microrespirometry demonstrated that the two N. vulgaris strains and Nitrobacter winogradskyi Nb-255 possessed higher affinities for nitrite and oxygen than previously reported for Nitrobacter, suggesting potential to compete in low-substrate environments. Long-read DNA sequencing provided a complete genome for strain MLSD-S22, revealing two plasmids and an intact nitrous oxide (N 2 O) reduction operon—an unexpected feature for Nitrobacter. While N 2 O reduction activity was not observed under the tested conditions, this discovery raises questions about the contribution of Nitrobacter NOB to the N 2 O sink. These findings broaden the physiological and genomic diversity of Nitrobacter, offering new insights into their adaptation strategies and providing a framework for future evaluation of their potential roles in nitrogen loss.

Nitrobacter↗
DOE OSTI2022

Compact, High-Power Superconducting Electron Linear Accelerators for MW Industrial Applications

Fermilab has developed a novel concept for an industrial electron linac using Nb₃Sn coating technology and conduction cooling. We will show the range of multi-cavity linac designs targeted toward various applications. We will also discuss technology development status with results on conduction cooling of SRF cavities based on cryocoolers, which removes the need for liquid Helium, thus making SRF technology accessible to industrial applications. These conduction-cooled linacs can generate electron beam energies up to 10 MeV in continuous-wave operation and can reach higher power (>=1 MW) by combing several modules. Compact and light enough to mount on mobile platforms, our machine is anticipated to enable new in-situ environmental remediation applications such as waste-water treatment for urban areas, X-ray medical device sterilization, and innovative pavement applications. We also show cost-economics and key R&D areas that much be addressed for a practical machine.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Sequim Campus Master Plan

Based in Richland, Washington, Pacific Northwest National Laboratory (PNNL) is one of ten U.S. Department of Energy (DOE) Office of Science (SC) national laboratories. PNNL is DOE’s premier chemistry, earth sciences, and data analytics laboratory, delivering vital mission impacts in energy resiliency and national security. PNNL has 19 core capabilities, each a powerful combination of world-class staff, state-of-the- art equipment, and mission-ready facilities. These capabilities represent a collective set of skills and a body of world-leading scientific and engineering work that provides exceptional value and mission delivery to DOE, the National Nuclear Security Administration (NNSA), the U.S. Department of Homeland Security (DHS), and other federal agencies and industry through strategic partnership projects on a not-to-interfere basis. Currently operated by Battelle Memorial Institute, PNNL occupies more than 2.3 million gross square feet (GSF) of buildings and employs approximately 4,700 staff members. PNNL has implemented a rolling 10-year campus strategy, initiated in fiscal year 2013, designed to deliver the foundation for the multidisciplinary science and engineering expertise, equipment, instrumentation, facilities, and infrastructure required to continue providing exceptional value and mission delivery. This strategy is incorporated into PNNL’s annual Laboratory Plan, which serves as DOE-SC’s equivalent of the Five- Year Site Plan required by DOE Order 430.1C Chg. 1, Real Property Asset Management. The PNNL Sequim Campus is located in Clallam County, just outside of Sequim, Washington. PNNL Sequim builds upon a rich history of research related to marine and coastal resources, environmental chemistry, water resources modeling, ecotoxicology, biotechnology, and national security. Facilities at the PNNL Sequim Campus were designed to take advantage of two unique locational assets: the pristine coastal ocean water in Sequim Bay and the region’s exceptionally clean air. Research facilities on the waterfront are supplied with up to 200 gallons per minute (gpm) of seawater and/or groundwater that enables research on aquatic systems ranging from fully seawater to fresh water, with an onsite water treatment system that removes all biological and hazardous chemical residues prior to discharge. Multiple large seawater tanks outside the waterfront laboratories, along with a boat ramp, pier, and floating dock, enable lab-to-field research. The uplands facility takes advantage of the amazing air quality and is built and operated to enable ultratrace chemical/radiological analytical chemistry. This combination of capabilities is not available at any other marine laboratory in the nation.

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

Application of Machine Learning to Improve Biobased Glucaric Acid Production (CRADA 504)

The Agile Biofoundry (ABF) is a multi-national lab consortium funded by the DOE Bioenergy Technologies Office that has developed a biofoundry that enables the rapid deployment of bioproducts into the market. Working with four ABF laboratory members (National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), Lawrence Berkeley National Laboratory (LBNL), and Argonne National Laboratory (ANL)), Kalion will use advanced high throughput techniques, advanced analytics, and machine learning to optimize the production environment for glucaric acid. Low-cost, high-purity glucaric acid enables products in a wide range of fields to improve the chemical properties of products and applications ranging from water treatment, polymers & textiles, coatings, detergents, and pharmaceuticals. With its broad range of applications, glucaric acid has the potential to demonstrate how such bio-based materials offer great benefit to the US economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗