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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Rapid estimation of earthquake locations using waveform traveltimes

SUMMARY We introduce a new approach for locating earthquakes using arrival times derived from waveforms. The most costly computational step of the algorithm scales as the number of stations in the active seismographic network. In this approach, a variation on existing grid search methods, a series of full waveform simulations are conducted for all receiver locations, with sources positioned successively at each station. The traveltime field over the region of interest is calculated by applying a phase picking algorithm to the numerical wavefields produced from each simulation. An event is located by subtracting the stored traveltime field from the arrival time at each station. This provides a shifted and time-reversed traveltime field for each station. The shifted and time-reversed fields all approach the origin time of the event at the source location. The mean or median value at the source location thus approximates the event origin time. Measures of dispersion about this mean or median time at each grid point, such as the sample standard error and the average deviation, are minimized at the correct source position. Uncertainty in the event position is provided by the contours of standard error defined over the grid. An application of this technique to a synthetic data set indicates that the approach provides stable locations even when the traveltimes are contaminated by additive random noise containing a significant number of outliers and velocity model errors. It is found that the waveform-based method out-performs one based upon the eikonal equation for a velocity model with rapid spatial variations in properties due to layering. A comparison with conventional location algorithms in both a laboratory and field setting demonstrates that the technique performs at least as well as existing techniques.

58 GEOSCIENCES↗
DOE OSTI2016

Compact all-fiber quartz-enhanced photoacoustic spectroscopy sensor with a 30.72 kHz quartz tuning fork and spatially resolved trace gas detection

An ultra compact all-fiber quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor using quartz tuning fork (QTF) with a low resonance frequency of 30.72 kHz was demonstrated. Such a sensor architecture has the advantages of easier optical alignment, lower insertion loss, lower cost, and more compact compared with a conventional QEPAS sensor using discrete optical components for laser delivery and coupling to the QTF. A fiber beam splitter and three QTFs were employed to perform multi-point detection and demonstrated the potential of spatially resolved measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Estimating CO 2 fluxes through integrating spatial and temporal input layers via deep learning algorithms

Background Accurate estimation of net ecosystem exchange of CO 2 fluxes (Fc) is essential for understanding carbon cycle processes and assessing ecosystem carbon budgets. However, conventional modeling approaches often emphasize temporal dynamics while overlooking the pronounced spatial heterogeneity within the footprint of eddy covariance (EC) towers, potentially limiting predictive accuracy and interpretability of Fc estimates. To address this challenge, we developed a spatiotemporal model that integrates high-resolution footprint-weighted spatial information with sequential environmental drivers. Results The integrated model combines a deeper graph convolutional network to characterize fine-scale spatial variability within EC footprints and a gated recurrent unit network to capture temporal dependencies in biophysical conditions. Using multi-year flux tower observations, remote sensing vegetation indices and footprint modeling, we evaluate the proposed method across three land cover types. This spatiotemporal model consistently outperforms temporal-only and spatial-only baselines, achieving the highest overall accuracy (R 2 = 0.9569) and the lowest RMSE (1.8128 μmol m −2 s −1 ) and MAE (1.1939 μmol m −2 s −1 ). Performance gains are particularly evident in ecosystems with strong vegetation heterogeneity, where spatial structure substantially modulates Fc variability. Conclusions This study demonstrates the importance of joint modeling spatial heterogeneity and temporal dynamics for improving Fc estimation and provides a robust method for advancing footprint-based Fc estimates across diverse ecosystems, supporting refined assessments of terrestrial carbon fluxes, and enhancing scientific foundations for carbon studies.

CO2 flux estimate↗
DOE OSTI2025

A Performance Portable, Fully Implicit Landau Collision Operator with Batched Linear Solvers

Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallelism in algorithms that have traditionally run on MPI processes or multiple threads within a single process. Opportunities for batching arise in, for example, kinetic discretizations of magnetized plasmas where collisions are advanced in velocity space at each spatial point independently. This paper builds on previous work on a high-performance, fully nonlinear, Landau collision operator by batching the linear solver, as well as batching the spatial point problems and adding new support for multiple grids for multiscale, multispecies problems. An anisotropic relaxation verification test that agrees well with previously published results and analytical models is presented. The performance results from NVIDIA A100 and AMD MI250X nodes are presented with hardware utilization analysis for each architecture. Finally, the entire implicit Landau operator time advance is implemented in Kokkos for performance portability, running entirely on the device and is available in the PETSc numerical library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Post-Newtonian cosmological dynamics of plane-parallel perturbations and back-reaction

We study the general relativistic non-linear dynamics of self-gravitating irrotational dust in a cosmological setting, adopting the comoving and synchronous gauge, where all the equations can be written in terms of the metric tensor of spatial hyper-surfaces orthogonal to the fluid flow. Performing an expansion in inverse powers of the speed of light, we obtain the post-Newtonian equations, which yield the lowest-order relativistic effects arising during the non-linear evolution. We then specialize our analysis to globally plane-parallel configurations, i.e. to the case where the initial perturbation field depends on a single coordinate. The leading order of our expansion, corresponding to the ''Newtonian background'', is the Zel'dovich approximation, which, for plane-parallel perturbations in the Newtonian limit, represents an exact solution. This allows us to find the exact analytical form for the post-Newtonian metric, thereby providing the post-Newtonian extension of the Zel'dovich solution: this accounts for some relativistic effects, such as the non-Gaussianity of primordial perturbations. An application of our solution in the context of the back-reaction proposal is eventually given, providing a post-Newtonian estimation of kinematical back-reaction, mean spatial curvature, average scale-factor and expansion rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Modifying the strength and strain concentration profile within collagen scaffolds using customizable arrays of poly-lactic acid fibers

Here, the tendon-to-bone junction is a highly specialized tissue which dissipates stress concentrations between mechanically dissimilar tendon and bone. Upon injury, the local heterogeneities across this insertion are not regenerated, leading to poor functional outcomes such as formation of scar tissue at the insertion and re-failure rates exceeding 90%. Although current tissue engineering methods are moving towards the development of spatially-graded biomaterials to begin to address these injuries, significant opportunities remain to engineer the often complex local mechanical behavior of such biomaterials to enhance their bioactivity. Here, we describe the use of three-dimensional printing techniques to create customizable arrays of poly-lactic acid (PLA) fibers that can be incorporated into a collagen scaffold under development for tendon bone junction repair. Notably, we use additive manufacturing concepts to generate arrays of spatially-graded fibers from biodegradable PLA that are incorporated into collagen scaffolds to create a collagen-PLA composite. We demonstrate the ability to tune the mechanical performance of the fiber-scaffold composite at the bulk scale. We also demonstrate the incorporation of spatially-heterogeneous fiber designs to establish non-uniform local mechanical performance of the composite biomaterial under tensile load, a critical element in the design of multi-compartment biomaterials for tendon-to-bone regeneration applications. Together, this work highlights the capacity to use multi-scale composite biomaterials to control local and bulk mechanical properties, and provides key insights into design elements under consideration for mechanically competent, multi-tissue regeneration platforms.

3D printing↗
DOE OSTI2022

Advances in hexagon mesh-based flow direction modeling

Watershed delineation and flow direction representation are the foundations of streamflow routing in spatially distributed hydrologic modeling. A recent study showed that hexagon-based watershed discretization has several advantages compared to the traditional Cartesian (latitude–longitude) discretization, such as uniform connectivity and compatibility with other Earth system model components based on unstructured mesh systems (e.g., oceanic models). Despite these advantages, hexagon-based discretization has not been widely adopted by the current generation of hydrologic models. One major reason is that there is no existing model that can delineate hexagon-based watersheds while maintaining accurate representations of flow direction across various spatial resolutions. In this study, we explored approaches such as spatial resampling and hybrid breaching-filling stream burning techniques to improve watershed delineation and flow direction representation using a newly developed hexagonal mesh watershed delineation model (HexWatershed). We applied these improvements to the Columbia River basin and performed 16 simulations with different configurations. The results show that (1) spatial resampling modulates flow direction around headwaters and provides an opportunity to extract subgrid information; and (2) stream burning corrects the flow directions in mountainous areas with complex terrain features.

58 GEOSCIENCES↗
DOE OSTI2012

Effect of intranasal manganese administration on neurotransmission and spatial learning in rats

The effect of intranasal manganese chloride (MnCl{sub 2}·4H{sub 2}O) exposure on spatial learning, memory and motor activity was estimated in Morris water maze task in adult rats. Three-month-old male Wistar rats received for 2 weeks MnCl{sub 2}·4H{sub 2}O at two doses the following: 0.2 mg/kg b.w. (Mn0.2) or 0.8 mg/kg b.w. (Mn0.8) per day. Control (Con) and manganese-exposed groups were observed for behavioral performance and learning in water maze. ANOVA for repeated measurements did not show any significant differences in acquisition in the water maze between the groups. However, the results of the probe trial on day 5, exhibited spatial memory deficits following manganese treatment. After completion of the behavioral experiment, the regional brain concentrations of neurotransmitters and their metabolites were determined via HPLC in selected brain regions, i.e. prefrontal cortex, hippocampus and striatum. ANOVA demonstrated significant differences in the content of monoamines and metabolites between the treatment groups compared to the controls. Negative correlations between platform crossings on the previous platform position in Southeast (SE) quadrant during the probe trial and neurotransmitter turnover suggest that impairment of spatial memory and cognitive performance after manganese (Mn) treatment is associated with modulation of the serotonergic, noradrenergic and dopaminergic neurotransmission in the brain. These findings show that intranasally applied Mn can impair spatial memory with significant changes in the tissue level and metabolism of monoamines in several brain regions. -- Highlights: ► Intranasal exposure to manganese in rats impairs spatial memory in the water maze. ► Regional changes in levels of neurotransmitters in the brain have been identified. ► Cognitive disorder correlates with modulation of 5-HT, NA and DA neurotransmission.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Europium-doped barium chloride storage phosphor plate synthesized by pulsed laser deposition

In computed radiography, scattering of the stimulation light by the storage phosphor crystals in the imaging plates negatively impacts spatial resolution. Storage phosphor plates with thinner phosphor layers have been developed to reduce scattering distance and increase spatial resolution, although at the expense of reduced x-ray absorption. The authors hypothesize that a transparent or translucent nanostructured film, containing a much higher percentage of storage phosphor crystals than achievable in bulk glass-ceramic materials made by conventional methods, may have acceptable photostimulated luminescence efficiency and imaging performance characteristics greater than commercial imaging plates. Films were produced via pulsed laser deposition by alternating target materials of the storage phosphor BaCl 2 :Eu 2+ and either silica or silicon. X-ray diffraction and photoluminescence characterization were conducted to confirm the presence of BaCl 2 :Eu 2+ crystallites. The films were able to store optical data and be read out to produce x-ray radiographs demonstrating 50-mu m spatial resolution. The performance of the experimental storage phosphor plates was compared to commercially available imaging plates. The authors demonstrate for the first time the synthesis of a glass-ceramic imaging plate for computed radiography by pulsed laser deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Efficient Simulation of Nested Hollow Sphere Intersections: for Dynamically Nested Compartmental Models in Cell Biology

In the particle-based simulation of cell-biological systems in continuous space, a key performance bottleneck is the computation of all possible intersections between particles. These typically rely for collision detection on solid sphere approaches. The behavior of cell biological systems is influenced by dynamic hierarchical nesting, such as the forming of, the transport within, and the merging of vesicles. Existing collision detection algorithms are found not to be designed for these types of spatial cell-biological models, because nearly all existing high performance parallel algorithms are focusing on solid sphere interactions. The known algorithms for solid sphere intersections return more intersections than actually occur with nested hollow spheres. Here we define a new problem of computing the intersections among arbitrarily nested hollow spheres of possibly different sizes, thicknesses, positions, and nesting levels. We describe a new algorithm designed to solve this nested hollow sphere intersection problem and implement it for parallel execution on graphical processing units (GPUs). We present first results about the runtime performance and scaling to hundreds of thousands of spheres, and compare the performance with that from a leading solid object intersection package also running on GPUs.

Koester, Till↗
DOE OSTI2022

Analysis of Compressibility Effects and Nonlinear Property Variations in a Supercritical CO2 Mixing Layer

Calculations are performed using the large eddy simulation technique to qualitatively assess the effects of fluid compressibility and thermodynamic nonlinearities on the dynamics of a supercritical flow field. Resulting data are also used to interrogate instantaneous subfilter-scale fields, as modeled by the mixed-dynamic Smagorinsky closure and gradient diffusion model. A three-dimensional wall-resolved calculation of a spatially evolving mixing layer composed solely of carbon dioxide is performed. This is followed by a coarse grid calculation to examine model performance as a function of resolution. Theoretical analysis indicates that the partial derivatives of density with respect to pressure and temperature are important modulators of the temperature and pressure field evolution, respectively. Results pertaining to subfilter velocity-velocity and velocity-temperature fields indicate that the models are most stressed in the regions where compressibility and thermo-fluid nonlinearities dominate the physics.

42 ENGINEERING↗
DOE OSTI2015

Collimator design for a multipinhole brain SPECT insert for MRI

Purpose: Brain single photon emission computed tomography (SPECT) imaging is an important clinical tool, with unique tracers for studying neurological diseases. Nowadays, most commercial SPECT systems are combined with x-ray computed tomography (CT) in so-called SPECT/CT systems to obtain an anatomical background for the functional information. However, while CT images have a high spatial resolution, they have a low soft-tissue contrast, which is an important disadvantage for brain imaging. Magnetic resonance imaging (MRI), on the other hand, has a very high soft-tissue contrast and does not involve extra ionizing radiation. Therefore, the authors designed a brain SPECT insert that can operate inside a clinical MRI. Methods: The authors designed and simulated a compact stationary multipinhole SPECT insert based on digital silicon photomultiplier detector modules, which have shown to be MR-compatible and have an excellent intrinsic resolution (0.5 mm) when combined with a monolithic 2 mm thick LYSO crystal. First, the authors optimized the different parameters of the SPECT system to maximize sensitivity for a given target resolution of 7.2 mm in the center of the field-of-view, given the spatial constraints of the MR system. Second, the authors performed noiseless simulations of two multipinhole configurations to evaluate sampling and reconstructed resolution. Finally, the authors performed Monte Carlo simulations and compared the SPECT insert with a clinical system with ultrahigh-resolution (UHR) fan beam collimators, based on contrast-to-noise ratio and a visual comparison of a Hoffman phantom with a 9 mm cold lesion. Results: The optimization resulted in a stationary multipinhole system with a collimator radius of 150.2 mm and a detector radius of 172.67 mm, which corresponds to four rings of 34 diSPM detector modules. This allows the authors to include eight rings of 24 pinholes, which results in a system volume sensitivity of 395 cps/MBq. Noiseless simulations show sufficient axial sampling (in a Defrise phantom) and a reconstructed resolution of 5.0 mm (in a cold-rod phantom). The authors compared the 24-pinhole setup with a 34-pinhole system (with the same detector radius but a collimator radius of 156.63 mm) and found that 34 pinholes result in better uniformity but a worse reconstruction of the cold-rod phantom. The authors also compared the 24-pinhole system with a clinical triple-head UHR fan beam system based on contrast-to-noise ratio and found that the 24-pinhole setup performs better for the 6 mm hot and the 16 mm cold lesions and worse for the 8 and 10 mm hot lesions. Finally, the authors reconstructed noisy projection data of a Hoffman phantom with a 9 mm cold lesion and found that the lesion was slightly better visible on the multipinhole image compared to the fan beam image. Conclusions: The authors have optimized a stationary multipinhole SPECT insert for MRI and showed the feasibility of doing brain SPECT imaging inside a MRI with an image quality similar to the best clinical SPECT systems available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

High-order discretization of a gyrokinetic Vlasov model in edge plasma geometry

We describe a new spatial discretization of a continuum gyrokinetic Vlasov model in axisymmetric tokamak edge plasma geometries. The geometries are represented using a multiblock decomposition in which logically distinct blocks are smoothly mapped from rectangular computational domains and are aligned with magnetic flux surfaces to accommodate strong anisotropy induced by the magnetic field. We employ a fourth-order, finite-volume discretization in mapped coordinates to mitigate the computational expense associated with discretization on 4D phase space grids. Applied to a conservative formulation of the gyrokinetic system, a finite-volume approach expresses local conservation discretely in a natural manner involving the calculation of normal fluxes at cell faces. In the approach presented here, the normal fluxes are computed in terms of face-averaged velocity normals in such a way that (i) the divergence-free property of the gyrokinetic velocity is preserved discretely to machine precision, (ii) the configuration space normal velocities are independent of mapping metrics, and (iii) the configuration space normal velocities are computed from exact pointwise evaluation of magnetic field data except for one term. The algorithms described in this paper form the foundation of a continuum gyrokinetic edge code named COGENT, which is used here to perform a convergence study verifying the accuracy of the spatial discretization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Evaluating the Impact of Proprietary Oil & Gas Data on Machine Learning Model Performance Using a Quasi-Experimental Analytical Approach

This study implements a data-intensive supervised ML approach through a quasi-experimental framework with the objective of quantifying the impact of oil and gas operator-specific proprietary data on ML-based predictive model performance relative to using oil and gas datasets that may be more commonly publicly available. The models are designed to jointly predict daily oil, gas, and water production for horizontal wells as a function of bottom-hole pressure drawdown, spatial placement across the study domain, and well completion attributes. Model performance is quantified on holdout test data to evaluate how each dataset affects resulting model variant performance.

02 PETROLEUM↗
DOE OSTI2022

Spinor $GW$ Bethe-Salpeter calculations in BerkeleyGW: Implementation, symmetries, benchmarking, and performance

Computing the GW quasiparticle band structure and Bethe-Salpeter equation (BSE) absorption spectra for materials with spin-orbit coupling have commonly been done by treating GW corrections and spin-orbit coupling (SOC) as separate perturbations to density-functional theory. However, accurate treatment of materials with strong spin-orbit coupling (such as many topological materials of recent interest, and thermoelectrics) often requires a nonperturbative approach using spinor wave functions in the Kohn-Sham equation and GW/BSE. Such calculations have only recently become available, in particular for the BSE. Here, we have implemented this approach in the plane-wave pseudopotential GW/BSE code BerkeleyGW, which is highly parallelized and widely used in the electronic-structure community. We present reference results for quasiparticle band structures and optical absorption spectra of solids with different strengths of spin-orbit coupling, including Si, Ge, GaAs, GaSb, CdSe, Au, and Bi 2 Se 3 . The calculated quasiparticle band gaps of these systems are found to agree with experiment to within a few tens of meV. SOC splittings are found to be generally in better agreement with experiment, including quasiparticle corrections to band energies. The absorption spectrum of GaAs is not significantly impacted by the inclusion of spin-orbit coupling due to its relatively small value (0.2 eV) in the Λ direction, while the absorption spectrum of GaSb calculated with the spinor GW/BSE captures the large spin-orbit splitting of peaks in the spectrum. For the prototypical topological insulator Bi 2 Se 3 , we find a drastic change in the low-energy band structure compared to that of DFT, with the spinorial treatment of the GW approximation correctly capturing the parabolic nature of the valence and conduction bands after including off-diagonal self-energy matrix elements. We present the detailed methodology, approach to spatial symmetries for spinors, comparison against other codes, and performance compared to spinless GW/BSE calculations and perturbative approaches to SOC. This work aims to spur further development of spinor GW/BSE methodology in excited-state research software and enables a more accurate and detailed exploration of electronic and optical properties of materials containing elements with large atomic numbers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Role of Intra-Domain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: An Approach for Spatially Resolving Dynamics and Ion Transport

The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Meso-Scale Fuel Performance Modeling using the MARMOT Code

The in-pile behavior of light-water-reactor (LWR) fuels is governed by the physics from various time and spatial scales. Accordingly, multi-scale modeling and simulation are needed to accurately predict the fuel performance at the engineering scale. To improve the traditional fuel performance modeling, the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program targets at developing multi-scale, multiphysics modeling tools for in-pile fuel behavior prediction under various operating or accident scenarios. In traditional fuel performance modeling, the history of fuel is represented by a single parameter, fuel burn-up. Burn-up measures the energy that has been extracted from fuels. However, it is not an adequate measure of fuel history as it ignores the flux effect, which is critical for the irradiation-induced microstructural evolution in fuels. Moreover, the traditional fuel performance models are usually fitted to experimental data. Their capabilities of being extrapolated to new operating conditions and being extended to new types of fuels are strongly limited by the empirical or semi-empirical nature. To improve the burn-up based models, a microstructure based fuel approach, the MOOSE-BISON-MARMOT (MBM) tool-kit, is being developed under the fuel product line (FPL) of the NEAMS program for predictive fuel performance modeling. In the MBM approach, the evolution of fuel microstructure and changes in fuel properties are described by the MARMOT code. The transient fuel properties obtained from MARMOT are then fed into the BISON code for engineering scale fuel performance modeling. Both BISON and MARMOT are developed within the MOOSE framework, which was developed at Idaho National Laboratory. In this summary, the development and the capabilities of the MARMOT code will be introduced. In the past few years, several materials models have been developed including: (1) a grain growth model that describes the grain size evolution as a function of time, temperature and fuel porosity, considering the effects of impurity and porosity dragging and anisotropic grain boundary energy, (2) a fission gas release model that describes the fission gas diffusion in grain interior, fission gas bubble formation in grain interior and at grain boundaries, and fission gas release to the fuel-cladding gap, (3) a fracture model that describes the fracture initiation and propagation in grain interior and along grain boundaries, and (4) a thermal conductivity model that describes the change in thermal conductivity due to grain growth, gas bubble formation, fracture and radiation damage. Several other models are also being developed in MARMOT for hydride formation in Zr-based cladding, radiation damage and grain size subdivision. In most cases, these materials models are coupled with each other. For instance, to accurate predict the transient thermal conductivity, information on grain size, fission gas density, porosity and fracture is required. Further development is on going to improve all these models. These models are developed primarily for UO{sub 2} fuels used in LWRs. They can be extended to other fuels with possibly new development. All models in MARMOT will be rigorously verified and validated before being applied for fuel performance modeling. A version of MARMOT was recently released in September 2015 with an assessment report. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter

The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗