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At least 325 records · Page 18

Zeolite-promoted platinum catalyst for efficient reduction of nitrogen oxides with hydrogen

Internal combustion engine fueled by carbon-free hydrogen (H 2 -ICE) offers a promising alternative for sustainable transportation. Herein, we report a facile and universal strategy through the physical mixing of Pt catalyst with zeolites to significantly improve the catalytic performance in the selective catalytic reduction of nitrogen oxides (NO x ) with H 2 (H 2 -SCR), a process aiming at NO x removal from H 2 -ICE. Via the physical mixing of Pt/TiO 2 with Y zeolite (Pt/TiO 2 + Y), a remarkable enhancement of NO x reduction activity and N 2 selectivity was simultaneously achieved. The incorporation of Y zeolite effectively captured the in-situ generated water, fostering a water-rich environment surrounding the Pt active sites. This environment weakened the NO adsorption while concurrently promoting the H 2 activation, leading to the strikingly elevated H 2 -SCR activity and N 2 selectivity on Pt/TiO 2 + Y catalyst. This study provides a unique, easy and sustainable physical mixing approach to achieve proficient heterogeneous catalysis for environmental applications.

36 MATERIALS SCIENCE↗

Bias Correction in Urban Building Energy Modeling for Chicago Using Machine Learning

Urban-scale building energy modeling (UBEM) holds promise for optimizing energy usage across extensive geographic regions. However, there is a recognized bias between simulated energy consumption and actual measured data. This study, based on building data from Chicago, delved into bias correction techniques for enhancing the accuracy of UBEM energy consumption estimates. Initially, the AutoBEM simulation yielded a normalized mean bias error (NMBE) of 1.1% and 51% of Coefficient of the Variation of the Root Mean Square Error (CVRMSE) after outlier exclusion. To address this, three bias correction methods were deployed: Average Mean Bias Error based bias correction, Quantile mapping bias correction, and Machine learning-based bias correction using Linear Regression and Random Forest models. Post-correction results exhibited marked improvement. The NMBE values were diminished to 0 for Average MBE-based, 0.36 for Quantile Mapping, and 0 for Machine Learning-based corrections. Concurrently, the CVRMSE values registered reductions from an original 51 to 50.8 for Quantile Mapping, and 38.56 for Machine Learning-based corrections, pointing towards the effectiveness of specific bias correction methods in refining the precision of UBEM energy predictions. Such accurate estimations are paramount for informed energy planning and urban policy-making.

Chowdhury, Shovan↗

Combustion of solid fuel in very low speed oxygen streams

In reduced gravity, the combustion of solid fuel in low-speed flow can be studied. The flame behavior in this low-speed regime will fill a void in our understanding of the flow effect on combustion. In addition, it is important for spacecraft fire safety considerations. In this work, modeling and experimental work on low-speed forced-concurrent-flow flame spread are carried out. In addition, experiments on reduced-gravity buoyant-flow flame spread are performed.

Tien, James S.↗

Geodata Modeling and Query in Geographic Information Systems

Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.

Adam, Nabil↗

Transitioning the NASA SLR Network to Event Timing Mode for Reduced Systematics, Improved Stability and Data Precision

NASA's legacy Satellite Laser Ranging (SLR) network produces about one-third of the global SLR data to support spacegeodesy. This network of globally distributed stations has been using Time Interval Units (TIU) for range measurements for thelast 25 + years. To improve the reliability of the SLR network and satisfy the need for stable millimeter precision data, a phasedreplacement of the TIUs in the network with picosecond-precise Event Timer Modules was initiated in 2015. This schemeallowed the time of flight and laser transmit epoch measurement to one picosecond resolution. For a network with globalscientific impact, transitioning to a new data generation metrological scheme requires significant data scrutiny and long-termscience data validation. Any long-term testing/measurement has the potential to interrupt the station's daily operational dataflow to the International Laser Ranging Service (ILRS) as the station under test will have to put its test data into quarantine.We have demonstrated a very effective way to test and implement the new device without removing the old hardware andwithout the need for the orbit analysis. This operationally noninvasive scheme performed concurrent test measurements enablinguninterrupted operational data flow to the users, while allowing simultaneous test data capture for short- and long-termsystematics and stability analysis. Extensive analysis of the test data was performed by the NASA SLR engineering team andthe ILRS Analysis Standing Committee, to uncover biases and any dependencies on the satellite ranges (for nonlinear scaleissues). Multi-ETM comparison was also performed at two of the SLR stations through the interchange of hardware to establishthe inter-device range biases and stability. Such benchmarked hardware was subsequently sent to the remaining stationsto allow traceability and normalize the network performance. The range bias intercomparison performed using the multiyearSLR data analysis agreed well with the engineering changes, thus validating the approach to flush out station-specific rangingsystematics affecting precise orbit determination. Such an improvement and rebalancing of the current network will allowan orderly transition of the current NASA SLR network operating at a maximum rate of 10 Hz to the NASA next generationSpace Geodesy Satellite Laser Ranging (SGSLR) network operating at 2 kHz (McGarry et al. in J Geod, 2018. https ://doi.org/10.1007/s0019 0-018-1191-6; Merkowitz et al. in J Geod, 2018. https ://doi.org/10.1007/s0019 0-018-1204-5).

Varghese, Thomas↗

Passive Microwave Remote Sensing of Rainfall Considering the Effects of Wind and Nonprecipitating Clouds

It has long been shown both in theory and in observation that emission from rain drops in a raining cloud results in upwelling brightness temperature above that caused by the sea surface alone. High brightness temperatures at microwave frequencies (e.g. 37 and 19 GHz) have usually been quantitatively associated with rainfall using physical or statistical models. By comparing concurrent special sensor microwave/imager and radar data, however, we noticed many cases where there is no appreciable rainfall in a field of view (FOV) which exhibits high brightness temperature (T(sub B)) at 37 and 19 GHz. On the basis of calculations and past literature it is shown that such high brightness temperatures can be caused by nonprecipitating clouds and by wind. The effect of the wind is to create wave and high-emissivity foam on the sea surface. A model is developed to relate T(sub B) to the fractional coverage of rain, f, within a FOV. The parameters of the model are calibrated by fitting the model to the observed brightness temperature and fractional rain coverage data. The critical parameter of the model, T(sub B min.), which is the threshold brightness temperature for the presence of rain, depends on the strength of the storm. The strength of the storm is characterized by the fraction of the FOVs within a large area that have T(sub B) higher than 240 K, which is readily obtainable from satellite data alone. The instantaneous FOV rain rate R can then be obtained through the f approximately R relationship which is empirically derived using radar data. An algorithm has been proposed based on the T(sub B) approximately f and f approximately R relationship. Application of the algorithm to TOGA-COARE and Darwin storms results in reasonable instantaneous FOV rain estimate. When averaged over the entire radar scan, a more accurate and unbiased areal rain estimate can be achieved.

Qihang Li.↗

Thermal Hall effect in a van der Waals triangular magnet FeCL 2

Thermal transport is a pivotal probe for studying low-energy, charge-neutral quasiparticles in insulating magnets. In this Letter, we report an observation of large magnetothermal conductivity and thermal Hall effect (THE) in a van der Waals antiferromagnet FeCl 2 . The magnetothermal conductivity reaches over ~700%, indicating strong magnon-phonon coupling. Furthermore, we find an appreciable thermal Hall signal which changes sign concurrently with the spin-flip transition from the antiferromagnetic state to the polarized ferromagnetic state. Our theoretical calculations suggest that, in addition to the Berry curvature induced at the anticrossing points of the hybridized magnon and acoustic phonon modes of FeCl 2 , other mechanisms are needed to account for the magnitude of the observed THE.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The effects of task difficulty and resource requirements on attention strategies

The patterns of attention strategies for task difficulty/resource tasks for which experimental results are presented and analyzed support the hypothesis that subjects may adopt an alternating (rather than concurrent one) when compelled to do so by either the size or the complexity of a visual display. According to the multiple resource model, if subjects had been performing the two tasks concurrently, the cost of this strategy would have been shown by a decrement in the spatial format, rather than the verbal format, due to competition for the same resource. Subjects may apply different strategies as a function of task difficulty and/or resource demand.

King, Teresa↗

Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.

alloys↗

The effect of variable calcium and very low calcium diets on human calcium metabolism

The effects of a very low calcium diet, with variable high and low protein intake, on the dynamics of calcium metabolism and the mechanism of calciuretics, are examined. The experiment, using male subjects, was designed to study the role of intestinal calcium absorption on urinary calcium excretion, and the rate of production of endogeneously secreted calcium in the gastrointestinal tract. The study showed an average of 70% fractional absorption rate during very low calcium intake, and that a decrease in renal tubular reabsorption of calcium is responsible for calciuretic effects of high protein intake. The study also indicates that there is a tendency to develop osteoporosis after long periods of low calcium intake, especially with a concurrent high protein intake.

Chu, J.↗

Human Factors Research Problems in Electronic Voice Warning System Design

The speech messages issued by voice warning systems must be carefully designed in accordance with general principles of human decision making processes, human speech comprehension, and the conditions in which the warnings can occur. The operator's effectiveness must not be degraded by messages that are either inappropriate or difficult to comprehend. Important experimental variables include message content, linguistic redundancy, signal/noise ratio, interference with concurrent tasks, and listener expectations generated by the pragmatic or real world context in which the messages are presented.

C A Simpson↗

Pulsed Plasma Thruster (PPT) Technology: Earth Observing-1 PPT Operational and Advanced Components Being Developed

In 2002 the pulsed plasma thruster (PPT) mounted on the Earth Observing-1 spacecraft was operated successfully in orbit. The two-axis thruster system is fully incorporated in the attitude determination and control system and is being used to automatically counteract disturbances in the pitch axis of the spacecraft. The first tests conducted in space demonstrated the full range of PPT operation, followed by calibration of control torques from the PPT in the attitude control system. Then the spacecraft was placed in PPT control mode. To date, it has operated for about 30 hr. The PPT successfully controlled pitch momentum during wheel de-spin, solar array acceleration and deceleration during array rewind, and environmental torques in nominal operating conditions. Images collected with the Advanced Landsat Imager during PPT operation have demonstrated that there was no degradation in comparison to full momentum wheel control. In addition, other experiments have been performed to interrogate the effects of PPT operation on communication packages and light reflection from spacecraft surfaces. Future experiments will investigate the possibility of orbit-raising maneuvers, spacecraft roll, and concurrent operation with the Hyperion imager. Future applications envisioned for pulsed plasma thrusters include longer life, higher precision, multiaxis thruster configurations for three-axis attitude control systems or high-precision, formationflying systems. Advanced components, such as a "dry" mica-foil capacitor, a wear-resistant spark plug, and a multichannel power processing unit have been developed under contract with Unison Industries, General Dynamics, and C.U. Aerospace. Over the last year, evaluation tests have been conducted to determine power processing unit efficiency, atmospheric functionality, vacuum functionality, thruster performance evaluation, thermal performance, and component life.

Pencil, Eric J.↗

Thickness and Fuel Preheating Effects on Material Flammability in Microgravity from the BASS Experiment

The Burning and Suppression of Solids (BASS) experiment was performed on the International Space Station. Microgravity combustion tests burning thin and thick flat samples, acrylic spheres, and candles were conducted. The samples were mounted inside a small wind tunnel which could impose air flow speeds up to 40 cms. The wind tunnel was installed in the Microgravity Science Glovebox which supplied power, imaging, and a level of containment. The effects of air flow speed, fuel thickness, fuel preheating, and nitrogen dilution on flame appearance, flame growth, and spread rates were determined in both the opposed and concurrent flow configuration. In some cases, a jet of nitrogen was introduced to attempt to extinguish the flame. Microgravity flames were found to be especially sensitive to air flow speed in the range 0 to 5 cms. The gas phase response is much faster compared to the solid and so as the flow speed is changed, the flame responds with almost no delay. At the lowest speeds examined (less than 1 cms) all the flames tended to become dim blue and very stable. However, heat loss at these very low convective rates is small so the flames can burn for a long time. At moderate flow speeds (between about 1 and 5 cms) the flame continually heats the solid fuel resulting in an increasing fuel temperature, higher rate of fuel vaporization, and a stronger, more luminous flame as time progresses. Only the smallest flames burning acrylic slabs appeared to be adversely influenced by solid conductive heat loss, but even these burned for over 5 minutes before self-extinguishing. This has implications for spacecraft fire safety since a tiny flame might be undetected for a long time. While the small flame is not particularly hazardous if it remains small, the danger is that it might flare up if the air convection is suddenly increased or if the flame spreads into another fuel source.

Combustion↗

Combustion of Solids in Microgravity: Results from the BASS-II Experiment

The Burning and Suppression of Solids-II (BASS-II) experiment was performed on the International Space Station. Microgravity combustion tests burned thin and thick flat samples, acrylic slabs, spheres, and cylinders. The samples were mounted inside a small wind tunnel which could impose air flow speeds up to 53 cms. The wind tunnel was installed in the Microgravity Science Glovebox which supplied power, imaging, and a level of containment. The effects of air flow speed, fuel thickness, fuel preheating, and oxygen concentration on flame appearance, growth, spread rate, and extinction were examined in both the opposed and concurrent flow configuration. The flames are quite sensitive to air flow speed in the range 0 to 5 cms. They can be sustained at very low flow speeds of less than 1 cms, when they become dim blue and stable. In this state they are not particularly dangerous from a fire safety perspective, but they can flare up quickly with a sudden increase in air flow speed. Including earlier BASS-I results, well over one hundred tests have been conducted of the various samples in the different geometries, flow speeds, and oxygen concentrations. There are several important implications related to fundamental combustion research as well as spacecraft fire safety. This work was supported by the NASA Space Life and Physical Sciences Research and Applications Division (SLPSRA).

Combustion↗

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

Mission Assurance↗

The Missing Economic Risks in Assessments of Climate Change Impacts

Economic assessments of the potential future risks of climate change have been omitting or grossly underestimating many of the most serious consequences for lives and livelihoods because these risks are difficult to quantify precisely and lie outside of human experience. Political and business leaders need to understand the scale of these ‘missing risks’ because they could have drastic and potentially catastrophic impacts on citizens, communities and companies. Scientists are growing in confidence about the evidence for the largest potential impacts of climate change and the rising probability that major thresholds in the Earth’s climate system will be breached as global mean surface temperature rises, particularly if warming exceeds 2°C above the pre-industrial level. These impacts include: (1) Destabilisation of ice sheets and glaciers and consequent sea level rise. (2) Stronger tropical cyclones. (3) Extreme heat impacts. (4) More frequent and intense floods and droughts. (5) Disruptions to oceanic and atmospheric circulation. (6) Destruction of biodiversity and collapse of ecosystems. Many of these impacts will grow and occur concurrently across the world as global temperature climbs. Some of these impacts involve thresholds in the climate system beyond which major impacts accelerate, or become irreversible and unstoppable. When a threshold is breached, it might cause one or more other thresholds to be exceeded as well, leading to a cascade of impacts. Many of these impacts could exceed the capacity of human populations to adapt, and would significantly affect and disrupt the lives and livelihoods of hundreds of millions, if not billions, of people worldwide. These impacts would also undermine economic growth and development, exacerbate poverty and destabilise communities. Economic assessments fail to take account of the potential for large concurrent impacts across the world that would cause mass migration, displacement and conflict, with huge loss of life. Economic assessments that are expressed solely in terms of effects on output (e.g. gross domestic product), or that only extrapolate from past experience, or that use inappropriate discounting, do not provide a clear indication of the potential risks to lives and livelihoods. It is likely that there are additional risks that we are not yet anticipating simply because scientists have not yet detected their possibility, as we have entered a period of climate change that is unprecedented in human history. Some advances are being made in improving economic assessments of climate change impacts but much more progress is required if assessments are to offer reliable guidance for political and business leaders on the biggest risks. The lack of firm quantifications is not a reason to ignore these risks, and when the missing risks are taken into account, the case for strong and urgent action to reduce greenhouse gas emissions becomes even more compelling.

DeFries, Ruth↗

Atacama Cosmology Telescope measurements of a large sample of candidates from the Massive and Distant Clusters of WISE Survey: Sunyaev-Zeldovich effect confirmation of MaDCoWS candidates using ACT

Context. Galaxy clusters are an important tool for cosmology, and their detection and characterization are key goals for current and future surveys. Using data from the Wide-field Infrared Survey Explorer (WISE), the Massive and Distant Clusters of WISE Survey (MaDCoWS) located 2839 significant galaxy overdensities at redshifts 0.7 . z . 1.5, which included extensive follow-up imaging from the Spitzer Space Telescope to determine cluster richnesses. Concurrently, the Atacama Cosmology Telescope (ACT) has produced large area millimeter-wave maps in three frequency bands along with a large catalog of Sunyaev-Zeldovich (SZ)-selected clusters as part of its Data Release 5 (DR5). Aims. We aim to verify and characterize MaDCoWS clusters using measurements of, or limits on, their thermal SZ effect signatures. We also use these detections to establish the scaling relation between SZ mass and the MaDCoWS-defined richness. Methods. Using the maps and cluster catalog from DR5, we explore the scaling between SZ mass and cluster richness. We do this by comparing cataloged detections and extracting individual and stacked SZ signals from the MaDCoWS cluster locations. We use complementary radio survey data from the Very Large Array, submillimeter data from Herschel, and ACT 224 GHz data to assess the impact of contaminating sources on the SZ signals from both ACT and MaDCoWS clusters. We use a hierarchical Bayesian model to fit the mass-richness scaling relation, allowing for clusters to be drawn from two populations: one, a Gaussian centered on the mass-richness relation, and the other, a Gaussian centered on zero SZ signal. Results. We find that MaDCoWS clusters have submillimeter contamination that is consistent with a gray-body spectrum, while the ACT clusters are consistent with no submillimeter emission on average. Additionally, the intrinsic radio intensities of ACT clusters are lower than those of MaDCoWS clusters, even when the ACT clusters are restricted to the same redshift range as the MaDCoWS clusters. We find the best-fit ACT SZ mass versus MaDCoWS richness scaling relation has a slope of p1 = 1.84+0.15 −0.14, where the slope is defined as M ∝ λ p1 15 and λ15 is the richness. We also find that the ACT SZ signals for a significant fraction (∼57%) of the MaDCoWS sample can statistically be described as being drawn from a noise-like distribution, indicating that the candidates are possibly dominated by low-mass and unvirialized systems that are below the mass limit of the ACT sample. Further, we note that a large portion of the optically confirmed ACT clusters located in the same volume of the sky as MaDCoWS are not selected by MaDCoWS, indicating that the MaDCoWS sample is not complete with respect to SZ selection. Finally, we find that the radio loud fraction of MaDCoWS clusters increases with richness, while we find no evidence that the submillimeter emission of the MaDCoWS clusters evolves with richness. Conclusions. We conclude that the original MaDCoWS selection function is not well defined and, as such, reiterate the MaDCoWS collaboration’s recommendation that the sample is suited for probing cluster and galaxy evolution, but not cosmological analyses. We find a best-fit mass-richness relation slope that agrees with the published MaDCoWS preliminary results. Additionally, we find that while the approximate level of infill of the ACT and MaDCoWS cluster SZ signals (1–2%) is subdominant to other sources of uncertainty for current generation experiments, characterizing and removing this bias will be critical for next-generation experiments hoping to constrain cluster masses at the sub-percent level.

large↗

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗