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At least 289 records · Page 16

Entangling-gate error from coherently displaced motional modes of trapped ions

Entangling gates in trapped-ion quantum computers are most often applied to stationary ions with initial motional distributions that are thermal and close to the ground state, while those demonstrations that involve transport generally use sympathetic cooling to reinitialize the motional state prior to applying a gate. Future systems with more ions, however, will face greater nonthermal excitation due to increased amounts of ion transport and exacerbated by longer operational times and variations over the trap array. In addition, pregate sympathetic cooling may be limited due to time costs and laser access constraints. In this paper, we analyze the impact of such coherent motional excitation on entangling-gate error by performing simulations of Mølmer-Sørenson (MS) gates on a pair of trapped-ion qubits with both thermal and coherent excitation present in a shared motional mode at the start of the gate. Here, we quantify how a small amount of coherent displacement erodes gate performance in the presence of experimental noise, and we demonstrate that adjusting the relative phase between the initial coherent displacement and the displacement induced by the gate or using Walsh modulation can suppress this error. We then use experimental data from transported ions to analyze the impact of coherent displacement on MS-gate error under realistic conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

US Fallout Shelter

Being indoors (sheltering) reduces radiation exposures resulting from nuclear fallout or a power-plant accident. However, most US building types, particularly non-residential buildings, lack quantitative estimates. We provide here a high-level modeling analysis of modern US building protection based on a novel radiation protection building attribute taxonomy, a new building protection model, compilation of prior experimental results, and nationally representative building survey data. This approach provides a consistent, quantitative understanding of US building protection and, when combined with the distribution of people among different buildings, can assist in selecting emergency response strategies. We find that indoor radiation protection varies by orders of magnitude. Most people in non-residential buildings are adequately protected, particularly below ground or in the building center. Residential buildings are less protective and those with lighter weight walls lack adequate, above ground protection. This work also highlights key areas where further investigation will improve the current results. These include the improving the understanding of residential basement protection, additional experimental data on non-residential buildings (particularly schools and industrial buildings), and the frequency of brick veneer and stucco exterior residential buildings.

61 RADIATION PROTECTION AND DOSIMETRY↗

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II - Clustering Extremely High-Dimensional Grid-Based Data

Building an accurate surrogate model for the spatio-temporal outputs of a computer simulation is a challenging task. A simple approach to improve the accuracy of the surrogate is to cluster the outputs based on similarity and build a separate surrogate model for each cluster. This clustering is relatively straightforward when the output at each time step is of moderate size. However, when the spatial domain is represented by a large number of grid points, numbering in the millions, the clustering of the data becomes more challenging. In this report, we consider output data from simulations of a jet interacting with high explosives. These data are available on spatial domains of different sizes, at grid points that vary in their spatial coordinates, and in a format that distributes the output across multiple files at each time step of the simulation. We first describe how we bring these data into a consistent format prior to clustering. Borrowing the idea of random projections from data mining, we reduce the dimension of our data by a factor of thousand, making it possible to use the iterative k-means method for clustering. We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set. Our approach makes clustering of extremely high dimensional data tractable, generating meaningful cluster assignments for our problem, despite the approximation introduced in the random projections.

97 MATHEMATICS AND COMPUTING↗

Towards Non-Intrusive Real-Time Monitoring of Behind the Meter Residential Distributed Energy Resources

The growing adoption of residential distributed energy resources (DERs) introduces more uncertain variability in power grid operation. More importantly, the residential DERs operate behind customers’ energy meters, and therefore, the utility cannot “directly” monitor them. Prior approaches to enable visibility into behind-the-meter (BTM) DERs either depend on estimations or require intrusive instrumentation on the customer side. To address the critical need for direct real-time monitoring of BTM DERs, in this paper, we propose a novel approach for utility-side direct real-time monitoring of residential BTM DERs. We utilize high-frequency (> 10kHz) conducted electromagnetic interference (EMI) from residential DERs’ grid-tied inverters to monitor their power generation. We discuss the working principle of our approach and present supporting results using three of-the-shelf grid-tied inverters.

14 SOLAR ENERGY↗

Distributed out-of-memory NMF on CPU/GPU architectures

We propose an efficient distributed out-of-memory implementation of the non-negative matrix factorization (NMF) algorithm for heterogeneous high-performance-computing systems. The proposed implementation is based on prior work on NMFk, which can perform automatic model selection and extract latent variables and patterns from data. In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems. The resulting algorithm is optimized for out-of-memory problems where the memory required to factorize a given matrix is greater than the available GPU memory. Memory complexity is reduced by batching/tiling strategies, and sparse and dense matrix operations are significantly accelerated with GPU cores (or tensor cores when available). Input/output latency associated with batch copies between host and device is hidden using CUDA streams to overlap data transfers and compute asynchronously, and latency associated with collective communications (both intra-node and inter-node) is reduced using optimized NVIDIA Collective Communication Library (NCCL) based communicators. Benchmark results show significant improvement, from 32X to 76x speedup, with the new implementation using GPUs over the CPU-based NMFk. Good weak scaling was demonstrated on up to 4096 multi-GPU cluster nodes with approximately 25,000 GPUs when decomposing a dense 340 Terabyte-size matrix and an 11 Exabyte-size sparse matrix of density 10 -6 .

97 MATHEMATICS AND COMPUTING↗

The Illumination of Thunderclouds by Lightning: 4. Volumetric Thunderstorm Imagery

Optical instruments such as the Geostationary Lightning Mapper (GLM) detect lightning based on transient changes in cloud illumination. The horizontal location of lightning is determined from the coordinates of the pixels on the imaging array illuminated during the flash. However, the vertical position of the lightning pulses (approximated by GLM “groups”) below the cloud top cannot be routinely measured from a single space-based instrument. In our prior work, we have developed a machine learning algorithm that can infer optical source altitude for a given pulse based on how the optical energy is distributed across the group footprint and the local Advanced Baseline Imager Cloud-Top Height (CTH). In this fourth part of our thundercloud illumination study, we leverage these source altitudes to generate volumetric GLM imagery of a Colombia thunderstorm. We find that 3D versions of the current GLM meteorological imagery products (that describe thunderstorm kinematics) and thundercloud imagery products (that depict how the flashes appear from space) provide additional insights into lightning activity in the thunderstorm that are lost in the vertical integration used to generate the current 2D GLM gridded products. This new volumetric imaging capability provides a more comprehensive picture of where lightning occurs in the storm, how its physical characteristics vary across three-dimensional space, and how its optical emissions interact with surrounding the cloud medium.

54 ENVIRONMENTAL SCIENCES↗

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗

Performance Evaluation of Multi-Vendor Grid-Forming Inverters for Grid-Connected Operation Through Hardware Experimentation: Preprint

Existing real-world projects of GFM inverters that operate in parallel to power grids typically are sized between dozens and a few hundreds Megawatt (MW) scale according to a recent NERC GFM inverter white paper. These large systems are often difficult to evaluate prior to deployments because of their large size. The performance of smaller GFM inverters (dozens to a few hundreds MW) that operate parallel with power grids (distribution systems) is even less understood. There is an opportunity to better understand these systems through hardware testing under controlled laboratory conditions. Therefore, this paper presents the functional performance evaluation tests of multiple (three) commercial GFM inverters when they operate in parallel with the grid through hardware experiments. The goal of these tests is to explore the GFM inverters' functionalities and dynamic response when in parallel with power grids to eventually develop universal specifications for GFM inverters. Both steady state (changing the inverter's frequency and voltage droop) and transient (adding step change in grid's frequency/voltage) tests are performed for each GFM inverter with the same testing circuit and testing protocol. The experimental results indicate the bench-marked performance that: 1) the GFM inverters can be dispatched through frequency and voltage droop intercepts to output the target power when paralleled to the grid; 2) the GFM inverters automatically respond to system frequency and voltage events to output the needed power, however, the GFM inverters all show stability issues when absorbing reactive power from the grid.

grid-forming inverters↗

Doping engineering: Next step toward room temperature performance of terahertz quantum cascade lasers

We hereby offer a comprehensive analysis of various factors that could potentially enable terahertz quantum cascade lasers (THz QCLs) to achieve room temperature performance. We thoroughly examine and integrate the latest findings from recent studies in the field. Our work goes beyond a mere analysis; it represents a nuanced and comprehensive exploration of the intricate factors influencing the performance of THz QCLs. Through a comprehensive and holistic approach, we propose novel insights that significantly contribute to advancing strategies for improving the temperature performance of THz QCLs. This all-encompassing perspective allows us not only to present a synthesis of existing knowledge but also to offer a fresh and nuanced strategy to improve the temperature performance of THz QCLs. We draw new conclusions from prior works, demonstrating that the key to enhancing THz QCL temperature performance involves not only optimizing interface quality but also strategically managing doping density, its spatial distribution, and profile. This is based on our results from different structures, such as two experimentally demonstrated devices: the spit-well resonant-phonon and the two-well injector direct-phonon schemes for THz QCLs, which allow efficient isolation of the laser levels from excited and continuum states. In these schemes, the doping profile has a setback that lessens the overlap of the doped region with the active laser states. Our work stands as a valuable resource for researchers seeking to gain a deeper understanding of the evolving landscape of THz technology. Furthermore, we present a novel strategy for future endeavors, providing an enhanced framework for continued exploration in this dynamic field. This strategy should pave the way to potentially reach higher temperatures than the latest records reached for T max of THz QCLs.

47 OTHER INSTRUMENTATION↗

Project Title: Development of a Pipe Crawler Inspection Tool for Fossil Energy Power Plants (Final Report)

This research effort focuses on the development of a pipe crawler inspection tool for fossil energy power plants. The pipe crawler is tethered and can navigate through 2 inch pipes that are often found in various systems within a power plant. The crawler can navigate through straight pipes and 180 degree elbows and includes instrumentation that can assess the integrity of the pipes. The sensors include a UT sensor for measuring the thickness of the pipe, a range finder and a camera. An additional module is used to prep the surface of the pipe prior to taking thickness measurements. Both bench scale and engineering scale testing was conducted to demonstrate the concept. Multiple crawlers were created and tethered together to distribute the load of the tether so that the crawler can navigate longer pipe distances.

01 COAL, LIGNITE, AND PEAT↗

Total kinetic energy release in the fast neutron induced fission of actinide nuclei

The total kinetic energy release and fission mass distributions for the fast neutron (En = 3–100 MeV) induced fission of 232 Th, 233 U, 235 U, 237 Np, 239 Pu, 240 Pu, and 242 Pu have been measured using the LANSCE facility. The neutron energies were deduced from time-of- flight measurements. The fission fragments were detected using Si PIN diode detectors, giving us the fragment energies. The actinide targets were made by vapor deposition leading to high-quality targets, that were thin and uniform with reduced impurities. Corrections were made to the data for pulse height defect and the fragment energy loss in the target and its backing. The TKE distributions were Gaussian in shape and their mean value as a function of incoming neutron energy could be fitted with second order polynomials. In the case of 233 U and 235 U, our measurements agree with prior work. Our measurements for 232 Th are unique. Our data agree with Viola scaling. The constant position of the heavy mass peak is interpreted as being due to the influence of the N = 88 and Z = 50 shells. The GEF model predictions agree with the data in general as do the CGMF model predictions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Longitudinal changes in red blood cell distribution width decades after radiation exposure in atomic–bomb survivors

Red blood cell distribution width (RDW), which generally increases with age, is a risk marker for morbidity and mortality in various diseases. We investigated the association between elevated RDW and prior radiation exposure by examining longitudinal RDW changes in 4204 atomic-bomb survivors over 15 years. A positive association was found between RDW and radiation dose, wherein RDW increased by 0·18%/Gy. This radiation-associated effect increased as the participants aged. Elevated RDW was also associated with higher all-cause mortality. The biological mechanisms underlying these observed associations merit further investigation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Thermal Conductivity of AM Fabricated Stainless Steel 316L Part

Thermal properties are an integral part of many diverse engineering applications, and additive manufacturing (AM), particularly laser powder bed fusion (LPBF) is shown to affect thermal properties due to the laser processing parameters. For 316L stainless steel, there is little prior research to determine the effects of the process on thermal properties. In this work, the temperature gradient is shown to create uniform, chess board-like distributions of grains in the build direction. These zones create dislocations which were visualized with EBSD techniques. Processing parameters cause hierarchal grain size distribution, with localized concentrations of small grains and large grains. Thermomechanical stresses in the rapid solidification increases dislocation density during grain formation. Previous research shows a higher density of dislocations decreases local thermal conductivity. Local and bulk thermal conductivity are shown in this work to have statistically lowered values to an average of 10-12 W/m-K compared to 14 W/m-K for conventional 316L.

36 MATERIALS SCIENCE↗

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗

Installation and imaging of thousands of minirhizotrons to phenotype root systems of field-grown plants

Roots are vital to plant performance because they acquire resources from the soil and provide anchorage. However, it remains difficult to assess root system size and distribution because roots are inaccessible in the soil. Existing methods to phenotype entire root systems range from slow, often destructive, methods applied to relatively small numbers of plants in the field to rapid methods that can be applied to large numbers of plants in controlled environment conditions. Much has been learned recently by extensive sampling of the root crown portion of field-grown plants. But, information on large-scale genetic and environmental variation in the size and distribution of root systems in the field remains a key knowledge gap. Minirhizotrons are the only established, non-destructive technology that can address this need in a standard field trial. Prior experiments have used only modest numbers of minirhizotrons, which has limited testing to small numbers of genotypes or environmental conditions. This study addressed the need for methods to install and collect images from thousands of minirhizotrons and thereby help break the phenotyping bottleneck in the field. Over three growing seasons, methods were developed and refined to install and collect images from up to 3038 minirhizotrons per experiment. Modifications were made to four tractors and hydraulic soil corers mounted to them. High quality installation was achieved at an average rate of up to 84.4 minirhizotron tubes per tractor per day. A set of four commercially available minirhizotron camera systems were each transported by wheelbarrow to allow collection of images of mature maize root systems at an average rate of up to 65.3 tubes per day per camera. This resulted in over 300,000 images being collected in as little as 11 days for a single experiment. The scale of minirhizotron installation was increased by two orders of magnitude by simultaneously using four tractor-mounted, hydraulic soil corers with modifications to ensure high quality, rapid operation. Image collection can be achieved at the corresponding scale using commercially available minirhizotron camera systems. Along with recent advances in image analysis, these advances will allow use of minirhizotrons at unprecedented scale to address key knowledge gaps regarding genetic and environmental effects on root system size and distribution in the field.

54 ENVIRONMENTAL SCIENCES↗

Modeling nanoparticle charge distribution in the afterglow of non-thermal plasmas and comparison with measurements

Particle charging in the afterglows of non-thermal plasmas typically take place in a non-neutral space charge environment. We model the same by incorporating particle-ion collision rate constant models, developed in prior work by analyzing particle-ion trajectories calculated using Langevin Dynamics simulations, into species transport equations for ions, electrons and charged particles in the afterglow. A scaling analysis of particle charging and additional Langevin Dynamics calculations of the particle-ion collision rate constant are presented to extend the range of applicability to ion electrostatic to thermal energy ratios of 300 and diffusive Knudsen number (that scales inversely with gas pressure) up to 2000. The developed collision rate constant models are first validated by comparing predictions of particle charge against measured values in a stationary, non-thermal DC plasma from past PK-4 campaigns published in Phys. Rev. Lett. 93(8): 085001 and Phys. Rev. E 72(1): 016406). The comparisons reveal excellent agreement within ±35% for particles of radius 0.6,1.0,1.3 μm in the gas pressure range of ~20-150 Pa. The experiments to probe particle charge distributions by Sharma et al. (J. Physics D: Appl. Phys. 53(24): 245204) are modeled using the validated particle-ion collision rate constant models and the calculated charge fractions are compared with measurements. The comparisons reveal that the ion/electron concentration and gas temperature in the afterglow critically influence the particle charge and the predictions are generally in qualitative agreement with the measurements. Along with critical assessment of the modeling assumptions, several recommendations are presented for future experimental design to probe charging in afterglows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In situ high-temperature 3D imaging of the damage evolution in a SiC nuclear fuel cladding material

Silicon carbide (SiC)-based nuclear fission fuel rod cladding has been considered as one of the possible designs for accident tolerant fuels. It is in the form of a SiC fibre reinforced SiC matrix composite tube (SiC f -SiC m ) with monolithic SiC outer and/or inner coating layers. This study focuses on the deformation and fracture processes in this material using in situ X-ray micro-computed tomography (XCT) at room temperature (RT) and 1200 °C in an inert gas environment in a C-ring compression loading configuration. Prior to testing, local properties and residual stresses were characterised using nanoindentation and Raman spectroscopy since they can impact the mechanical behaviour of the material. The 3D strain distribution, crack formation and propagation processes including the toughening mechanisms (e.g., crack deflection, micro-cracking, crack bridging and bifurcation) are investigated in the coating and underlying composites at RT and 1200 °C. There is no particular sequence which toughening mechanism occurs first – this is very different from the conventional toughening theory in ceramic-matrix composites under uniaxial tension loading. Indeed, no evidence of fibre pull-out or fibre fracture was observed in this SiC f -SiC m nuclear cladding material in the current C-ring compression configuration. The correlation between local measurements and bulk mechanical behaviour are discussed.

3D imaging↗