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At least 721 records · Page 40

Improved guided-wave acoustic defect detection and localization in pipes under varying temperature conditions using deep learning

Early defect detection in pipelines is critical across industries, particularly in the oil and gas sector, where failures result in significant maintenance costs and operational disruptions. Acoustic guided-wave techniques are widely used for nondestructive evaluation of pipeline defects due to their long-distance propagation capability. However, environmental variations, sensitivity limitations, and complex signal interpretation challenges limit the effectiveness of traditional signal processing approaches with guided-wave signals. Recent advances in deep learning methods have demonstrated remarkable success in solving complex real-world problems in many fields. In particular, deep-learning-based signal processing holds substantial promise to overcome limitations and challenges of conventional signal processing. This study presents a deep learning framework for pipeline inspection using acoustic guided-wave signals under temperature varying environments. The proposed framework employs a dual-path one-dimensional convolutional autoencoder that combines defect detection, localization, and temperature prediction functions. The proposed system utilizes multi-mode and broadband acoustic waves with an optimized number of sensors that provide high accuracy while retaining practical simplicity. Experimental validation is performed on a carbon steel pipe. The results indicate exceptional defect detection accuracy and precise defect localization with a mean absolute error of 66 mm. The proposed technique also predicts the effective average temperature of the pipe with a mean absolute error of 0.2°C. Comparative analysis shows superior performance of the proposed method over a traditional method previously developed by the authors' team. These results highlight the potential of integrating deep learning methods into guided-wave pipeline inspection systems to improve reliability under varying environmental conditions.

42 ENGINEERING↗

Data Covariances from R-Matrix Analyses of Light Nuclei

After first reviewing the parametric description of light-element reactions in multichannel systems using R-matrix theory and features of the general LANL R-matrix analysis code EDA, we describe how its chi-square minimization procedure gives parameter covariances. This information is used, together with analytically calculated sensitivity derivatives, to obtain cross section covariances for all reactions included in the analysis by first-order error propagation. Examples are given of the covariances obtained for systems with few resonances ({sup 5}He) and with many resonances ({sup 13}C ). We discuss the prevalent problem of this method leading to cross section uncertainty estimates that are unreasonably small for large data sets. The answer to this problem appears to be using parameter confidence intervals in place of standard errors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Use of Physics to Improve Solar Forecast: Physics-Informed Persistence Models for Simultaneously Forecasting GHI, DNI, and DHI

Observation-based statistical models have been widely used in forecasting solar energy; however, existing models often lack a clear relation to physics and are limited largely to global horizontal irradiance (GHI) forecasts over relatively short time horizons (< 1 hour). Incorporating physics into observation-based models, increasing forecast time horizons and developing a model system for forecasting not only GHI but also direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) remain challenging, especially under cloudy conditions because of complex cloud-radiation interactions. This work attempts to address these challenges by developing a hierarchy of four new physics-informed persistence models that can be used to simultaneously forecast GHI, DNI and DHI. The decade-long measurements (1998 to 2014) at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM)'s Southern Great Plains (SGP) Central Facility site are used to evaluate the performance of the new models. Overall, the results show that the new physics-informed forecast models generally outperform the simple and smart persistence models, and improve the forecast accuracy at lead times from 1.25 hours up to 6 hours. Further analysis reveals that the forecast error is highly related to the error and temporal variability of the assumed cloud predictor. The best model for forecasting different radiative components can be explained by the relationship between solar irradiances and cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Ab Initio Molecular Dynamics Spectra for Characterization of Hydrated Al 2 O 3 Supported MoO x

The structure of supported MoO x /Al 2 O 3 catalysts is investigated using ab initio molecular dynamics (AIMD) and density-functional theory (DFT). Phase diagrams were computed to understand the hydroxylation coverage as a function of the temperature, H 2 O partial pressure, and MoO x loading. We relate the shifts in experimental Raman vibrational frequencies under hydrated conditions to hydrogen bonding interactions and the MoO x anchoring location. We showcase that the use of AIMD as a benchmark for DFT can provide insight into how, under certain hydrated conditions, DFT excels as an inexpensive method for computing vibrational frequencies, while, under dehydrated conditions, it is susceptible to the largest errors. Additionally, to facilitate the analysis of the hydroxyl region of experimental infrared spectra, we compute the power spectra of individual hydroxyls and see a strong relationship between OH stretching frequencies and the surrounding coordination environment, which are also impacted by anchored MoO x . Here, we compare computational and experimental IR and Raman spectra of catalysts synthesized herein under the same conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

Critical analysis and remedy of switching failures in straintronic logic using Bennett clocking in the presence of thermal fluctuations

Straintronic logic is a promising platform for beyond Moore's law computing. Using Bennett clocking mechanism, information can propagate through an array of strain-mediated multiferroic nanomagnets, exploiting the dipolar coupling between the magnets without having to physically interconnect them. Here, we perform a critical analysis of switching failures, i.e., error in information propagation due to thermal fluctuations through a chain of such straintronic devices. We solved stochastic Landau-Lifshitz-Gilbert equation considering room-temperature thermal perturbations and show that magnetization switching may fail due to inherent magnetization dynamics accompanied by thermally broadened switching delay distribution. Avenues available to circumvent such issue are proposed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Molecular electric moments calculated by using natural orbital functional theory

The molecular electric dipole, quadrupole, and octupole moments of a selected set of 21 spin-compensated molecules are determined employing the extended version of the Piris natural orbital functional 6 (PNOF6), using the triple-ζ Gaussian basis set with polarization functions developed by Sadlej, at the experimental geometries. The performance of the PNOF6 is established by carrying out a statistical analysis of the mean absolute errors with respect to the experiment. The calculated PNOF6 electric moments agree satisfactorily with the corresponding experimental data and are in good agreement with the values obtained by accurate ab initio methods, namely, the coupled-cluster single and doubles and multi-reference single and double excitation configuration interaction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crosstalk in microwave SQUID multiplexers

Low-temperature detector technologies provide extraordinary sensitivity for applications ranging from precision measurements of the cosmic microwave background to high-resolution, high-rate x-ray, and γ-ray spectroscopy. To utilize this sensitivity, new instruments are being built, and new instruments are imagined, with ever greater pixel counts, but the scale of these instruments is limited by the capability of the readout electronics. Microwave SQUID multiplexing addresses the needs of these future instruments, exploiting gigahertz of bandwidths of coaxial cables and broadband components to combine hundreds to thousands of signals on a single readout line. A key feature of any multiplexer is the level of crosstalk between input channels. This crosstalk can degrade the sensitivity of the instrument, introduce systematic error, or simply confound data analysis. In this letter, we explain the primary mechanisms of crosstalk in a microwave SQUID multiplexer, calculate and measure their magnitude, and consider their effect and methods of mitigation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations

The high computational scaling with the basis set size and the number of correlated electrons is a bottleneck limiting applications of coupled cluster algorithms, in particular for calculations based on two- or four-component relativistic Hamiltonians, which often employ uncontracted basis sets. This problem may be alleviated by replacing canonical Hartree–Fock virtual orbitals by natural orbitals (NOs). Here, in this paper, we describe the implementation of a module for generating NOs for correlated wavefunctions and, in particular, second order Møller–Plesset perturbation frozen natural orbitals (MP2FNOs) as a component of our novel implementation of relativistic coupled cluster theory for massively parallel architectures [Pototschnig et al. J. Chem. Theory Comput. 17, 5509, (2021)]. Our implementation can manipulate complex or quaternion density matrices, thus allowing for the generation of both Kramers-restricted and Kramers-unrestricted MP2FNOs. Furthermore, NOs are re-expressed in the parent atomic orbital (AO) basis, allowing for generating coupled cluster singles and doubles NOs in the AO basis for further analysis. By investigating the truncation errors of MP2FNOs for both the correlation energy and molecular properties—electric field gradients at the nuclei, electric dipole and quadrupole moments for hydrogen halides HX (X = F–Ts), and parity-violating energy differences for H 2 Z 2 (Z = O–Se)—we find MP2FNOs accelerate the convergence of the correlation energy in a roughly uniform manner across the Periodic Table. It is possible to obtain reliable estimates for both energies and the molecular properties considered with virtual molecular orbital spaces truncated to about half the size of the full spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recent Studies on the Asymptotic Convergence of the Spatial Discretization for Two-Dimensional Discrete Ordinates Solutions

In this paper, four types of quadrature schemes are used to define discrete directions in the solution of a two-dimensional fixed-source discrete ordinates problem in Cartesian geometry. Such schemes enable generating numerical results for averaged scalar fluxes over specified regions of the domain with high number (up to 105) of directions per octant. Two different nodal approaches, the ADO and AHOT-N0 methods, are utilized to obtain the numerical results of interest. The AHOT-N0 solutions on a sequence of refined meshes are then used to develop an asymptotic analysis of the spatial discretization error in order to derive a reference solution. It was more clearly observed that the spatial discretization error converges asymptotically with second order for the source region with all four quadratures employed, while for the other regions refined meshes along with tighter convergence criterion must be applied to evidence the same behavior. Although, in that case, some differences among the four quadrature schemes results were found.

97 MATHEMATICS AND COMPUTING↗

THE M31 VELOCITY VECTOR. I. HUBBLE SPACE TELESCOPE PROPER-MOTION MEASUREMENTS

We present the first proper-motion (PM) measurements for the galaxy M31. We obtained new V-band imaging data with the Hubble Space Telescope ACS/WFC and the WFC3/UVIS instruments of three fields: a spheroid field near the minor axis, an outer disk field along the major axis, and a field on the Giant Southern Stream. The data provide five to seven year time baselines with respect to pre-existing deep first-epoch observations of the same fields. We measure the positions of thousands of M31 stars and hundreds of compact background galaxies in each field. High accuracy and robustness is achieved by building and fitting a unique template for each individual object. The average PM for each field is obtained from the average motion of the M31 stars between the epochs with respect to the background galaxies. For the three fields, the observed PMs ({mu}{sub W}, {mu}{sub N}) are, in units of mas yr{sup -1}, (- 0.0458, -0.0376) {+-} (0.0165, 0.0154), (- 0.0533, -0.0104) {+-} (0.0246, 0.0244), and (- 0.0179, -0.0357) {+-} (0.0278, 0.0272), respectively. The ability to average over large numbers of objects and over the three fields yields a final displacement accuracy of a few thousandths of a pixel, corresponding to only 12 {mu}as yr{sup -1}. This is comparable to what has been achieved for other Local Group galaxies using Very Long Baseline Array observations of water masers. Potential systematic errors are controlled by an analysis strategy that corrects for detector charge transfer inefficiency, spatially and time-dependent geometric distortion, and point-spread function variations. The robustness of the PM measurements and uncertainties are supported by the fact that data from different instruments, taken at different times and with different telescope orientations, as well as measurements of different fields, all yield statistically consistent results. Papers II and III of this series explore the implications of the new measurements for our understanding of the history, future, and mass of the Local Group.

79 ASTRONOMY AND ASTROPHYSICS↗

Material identification in x-ray microscopy and micro CT using multi-layer, multi-color scintillation detectors

We demonstrate that a dual-layer, dual-color scintillator construct for microscopic CT, originally proposed to increase sensitivity in synchrotron imaging, can also be used to perform material quantification and classification when coupled with polychromatic illumination. We consider two different approaches to data handling: (1) a data-domain material decomposition whose estimation performance can be characterized by the Cramer-Rao lower bound formalism but which requires careful calibration and (2) an image-domain material classification approach that is more robust to calibration errors. The data-domain analysis indicates that useful levels of SNR (>5) could be achieved in one second or less at typical bending magnet fluxes for relatively large amounts of contrast (several mm path length, such as in a fluid flow experiment) and at typical undulator fluxes for small amount of contrast (tens of microns path length, such as an angiography experiment). The tools introduced could of course be used to study and optimize parameters for a wider range of potential applications. The image domain approach was analyzed in terms of its ability to distinguish different elemental stains by characterizing the angle between the lines traced out in a two-dimensional space of effective attenuation coefficient in the front and back layer images. As a result, this approach was implemented at a synchrotron and the results were consistent with simulation predictions.

36 MATERIALS SCIENCE↗

New axion and hidden photon constraints from a solar data global fit

We present a new statistical analysis that combines helioseismology (sound speed, surface helium and convective radius) and solar neutrino observations (the {sup 8}B and {sup 7}Be fluxes) to place upper limits to the properties of non standard weakly interacting particles. Our analysis includes theoretical and observational errors, accounts for tensions between input parameters of solar models and can be easily extended to include other observational constraints. We present two applications to test the method: the well studied case of axions and axion-like particles and the more novel case of low mass hidden photons. For axions we obtain an upper limit at 3σ for the axion-photon coupling constant of g{sub aγ} < 4.1 · 10{sup −10} GeV{sup −1}. For hidden photons we obtain the most restrictive upper limit available accross a wide range of masses for the product of the kinetic mixing and mass of χ m < 1.8 ⋅ 10{sup −12} eV at 3σ. Both cases improve the previous solar constraints based on the Standard Solar Models showing the power of using a global statistical approach.

79 ASTRONOMY AND ASTROPHYSICS↗

PROSPECTS FOR MEASURING THE RELATIVE VELOCITIES OF GALAXY CLUSTERS IN PHOTOMETRIC SURVEYS USING THE KINETIC SUNYAEV-ZEL'DOVICH EFFECT

We consider the prospects for measuring the pairwise kinetic Sunyaev-Zel'dovich (kSZ) signal from galaxy clusters discovered in large photometric surveys such as the Dark Energy Survey (DES). We project that the DES cluster sample will, in conjunction with existing mm-wave data from the South Pole Telescope (SPT), yield a detection of the pairwise kSZ signal at the 8{sigma}-13{sigma} level, with sensitivity peaking for clusters separated by {approx}100 Mpc distances. A next-generation version of SPT would allow for a 18{sigma}-30{sigma} detection and would be limited by variance from the kSZ signal itself and the residual thermal Sunyaev-Zel'dovich (tSZ) signal. Throughout our analysis, we assume photometric redshift errors that wash out the signal for clusters separated by {approx}<50 Mpc; a spectroscopic survey of the DES sample would recover this signal and allow for a 26{sigma}-43{sigma} detection, and would again be limited by kSZ/tSZ variance. Assuming a standard model of structure formation, these high-precision measurements of the pairwise kSZ signal will yield detailed information on the gas content of the galaxy clusters. Alternatively, if the gas can be sufficiently characterized by other means (e.g., using tSZ, X-ray, or weak lensing), then the relative velocities of the galaxy clusters can be isolated, thereby providing a precision measurement of gravity on 100 Mpc scales. We briefly consider the utility of these measurements for constraining theories of modified gravity.

79 ASTRONOMY AND ASTROPHYSICS↗

Limiting masses and radii of neutron stars and their implications

We combine the equation of state of dense matter up to twice nuclear saturation density 𝑛 sat obtained using chiral effective field theory (𝜒⁢EFT) and recent observations of neutron stars to gain insights about the high-density matter encountered in their cores. A key element in our study is the recent Bayesian analysis of correlated EFT truncation errors based on order-by-order calculations up to next-to-next-to-next-to-leading order in the 𝜒⁢EFT expansion. We refine the bounds on the maximum mass imposed by causality at high densities and provide stringent limits on the maximum and minimum radii of ∼1.4M ⊙ and ∼2.0M ⊙ stars. Including 𝜒⁢EFT predictions from 𝑛sat to 2𝑛 sat reduces the permitted ranges of the radius of a ~1.4M ⊙ star, 𝑅 1.4 , by ∼3.5km. If observations indicate 𝑅 1.4 < 11.2km, then our study implies that either the squared speed of sound 𝑐$^{2}_{𝑠}$ > 1/2 for densities above 2𝑛 sat or that 𝜒⁢EFT breaks down below 2𝑛 sat . Here, we also comment on the nature of the secondary compact object in GW190814 with mass ≃ 2.6M ⊙ and discuss the implications of massive neutron stars > 2.1⁢M ⊙ ⁡(2.6M ⊙ ) in future radio and gravitational-wave searches. Some form of strongly interacting matter with 𝑐$^{2}_{𝑠}$ > 0.35⁢(0.55) must be realized in the cores of such massive neutron stars. In the absence of phase transitions below 2𝑛 sat , the small tidal deformability inferred from GW170817 lends support for the relatively small pressure predicted by 𝜒⁢EFT for the baryon density 𝑛 B in the range 1–2𝑛 sat . Together they imply that the rapid stiffening required to support a high maximum mass should occur only when 𝑛 B ≳ 1.5–1.8 𝑛 sat .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

3D-printed sheet jet for stable megahertz liquid sample delivery at X-ray free-electron lasers

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Localization of Southern Resident Killer Whales Using Two Star Arrays to Support Marine Renewable Energy

Tidal power has been identified as one of the most potential commercial-scale renewable energy sources. Puget Sound, Washington, is a potential site to deploy tidal power generating devices. The risk of injury for killer whales needs to be managed before the deployment of these types of devices can be approved by regulating authorities. A passive acoustic system consisting of two star arrays, each with four hydrophones, was designed and implemented for the detection and localization of Southern Resident killer whales. Deployment of the passive acoustic system was conducted at Sequim Bay, Washington. A total of nine test locations were chosen, within a radius of 250 m around the star arrays, to test our localization approach. For the localization algorithm, a least square solver was applied to obtain a bearing location from each star array. The final source location was determined by the intersection of the bearings given by each of the two star arrays. Bearing and distance errors were obtained to conduct comparison between the calculated and true (from Global Positioning System) locations. The results indicated that bearing errors were within 1.04º for eight of the test locations; one location had bearing errors slightly larger than expected due to the strong background noise at that position. For the distance errors, six of the test locations were within the range of 1.91 to 32.36 m. The other two test locations were near the intersection line between the centers of the two star arrays, which were expected to have large errors from the theoretical sensitivity analysis performed.

Passive acoustic system, localization, star array,↗

A Bloom Filter Based Scalable Data Integrity Check Tool for Large-Scale Dataset

Large scale HPC applications are becoming increasingly data intensive. At Oak Ridge Leadership Computing Facility (OLCF), we are observing the number of files curated under individual project are reaching as high as 200 millions and project data size is exceeding petabytes. These simulation datasets, once validated, often needs to be transferred to archival system for long term storage or shared with the rest of the research community. Ensuring the data integrity of the full dataset at this scale is paramount important but also a daunting task. This is especially true considering that most conventional tools are serial and file-based, unwieldy to use and/or can't scale to meet user's demand.To tackle this particular challenge, this paper presents the design, implementation and evaluation of a scalable parallel checksumming tool, fsum, which we developed at OLCF. It is built upon the principle of parallel tree walk and work-stealing pattern to maximize parallelism and is capable of generating a single, consistent signature for the entire dataset at extreme scale. We also applied a novel bloom-filter based technique in aggregating signatures to overcome the signature ordering requirement. Given the probabilistic nature of bloom filter, we provided a detailed error and trade-off analysis. Using multiple datasets from production environment, we demonstrated that our tool can efficiently handle both very large files as well as many small-file based datasets. Our preliminary test showed that on the same hardware, it outperforms conventional tool by as much as 4×. It also exhibited near-linear scaling properties when provisioned with more compute resources.

97 MATHEMATICS AND COMPUTING↗