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54 records · Page 3

Integrated fluorescence light microscopy-guided cryo-focused ion beam-milling for in situ montage cryo-ET

Cryogenic-electron tomography (cryo-ET) permits the in situ visualization of biological macromolecules at the molecular level. Owing to the variable thickness of cells, tissues and organisms, frozen specimens may need to be thinned by cryo-focused ion beam (FIB) milling to produce thin (<500 nm) cryo-lamellae suitable for cryo-ET. Locating regions of interest remains a challenge because untargeted milling can lead to inadvertent ablation and removal of regions of interest. Correlative light and electron microscopy, combined with cryo-FIB milling, can guide the identification of labeled targets in the cellular milieu. Multiple transfers between cryo-imaging instruments, cumbersome correlation algorithms, limited accuracy and low throughput have hindered the routine adoption of cryo-FIB milling within a multimodal correlative workflow for in situ structural biology. Here, in this study, we present a workflow for 3D correlative cryo-fluorescence light microscopy-FIB-ET that streamlines fluorescence light microscopy-guided FIB milling, improving throughput while preserving both structural and contextual information. The complete integration of hardware and software described here minimizes sample contamination from cross-platform exchanges and greatly enhances the efficiency of 3D targeting in cryo-milling. We then describe procedures for implementing montage parallel array cryo-ET (MPACT), which can be easily adapted to any modern life-science transmission electron microscope. MPACT supports high-throughput cryo-ET acquisitions (10 tilt series in 1.5 h) for structure determination and comprehensive contextual understanding of macromolecules within their native surroundings. A complete session from sample preparation to MPACT data processing takes 5−7 d for an individual experienced in both cryo-EM and cryo-FIB milling.

Yang, Jie E. [Univ. of Wisconsin, Madison, WI (Uni↗

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗

EdgeAI: Machine learning via direct attached accelerator for streaming data processing at high shot rate x-ray free-electron lasers

We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific user facilities such as the Linac Coherent Light Source-II x-ray Free-Electron Laser. We discuss how a low-latency inference model operating at the data acquisition edge can capitalize on the naturally stochastic nature of such sources. We simulate the method of attosecond angular streaking to produce representative results whereby simulated input data reproduce high-resolution ground truth probability distributions. By minimizing the mean-squared error between the decoded output of the latent representation and the ground truth distributions, we ensure that the encoding layers and resulting latent representation maintains full fidelity for any downstream task, be it classification or regression. We present throughput results for data-parallel inference of various batch sizes, some with throughput exceeding 100 k images per second. We also show in situ training below 10 s per epoch for the full encoder–decoder model as would be relevant for streaming and adaptive real-time data production at our nation’s scientific light sources.

97 MATHEMATICS AND COMPUTING↗

BM3DORNL

BM3DORNL is a high-performance, open-source library for removing streak and ring artifacts from computed-tomography (CT) data, developed for neutron imaging at Oak Ridge National Laboratory's Spallation Neutron Source (VENUS beamline) and applicable to X-ray CT as well. Ring artifacts — concentric rings in reconstructed slices caused by detector pixel-to-pixel response non-uniformities — appear as vertical streaks in the sinogram and degrade both image quality and quantitative analysis. BM3DORNL operates in the sinogram domain using an adaptation of the BM3D (block-matching and 3D collaborative filtering) algorithm (Dabov et al., 2007). It provides a dedicated streak-removal mode, a true multi-scale BM3D variant (after Mäkinen et al., 2021) that suppresses wide streaks single-scale methods miss, and an alternative Fourier–SVD method (~2.6× faster) combining FFT-based energy detection with rank-1 SVD. The computationally intensive core is implemented in Rust with parallel (Rayon) block matching, integral-image pre-screening, and optimized transforms, and is exposed through a simple Python API (with an optional GUI) so it integrates directly into existing tomography reconstruction pipelines. It processes both 2D sinograms and 3D sinogram stacks, is pip-installable for Linux and macOS, and is documented at https://bm3dornl.readthedocs.io.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗

Livermore tomography tools: Accurate, fast, and flexible software for tomographic science

Livermore Tomography Tools (LTT) is a customizable scientific software package that enables a broad range of research and development efforts into computed tomography (CT). Here, it was developed to process x-ray and neutron CT data accurately and rapidly from raw detector counts to reconstructed volumes with the flexibility to handle many special cases. LTT fulfills long-term CT software goals to provide quantitatively accurate results reported in physical units (e.g., mm -1 or cm -1 ) while exploiting all available computational advantages to maximize speed. Written in C/C++ with support for multiple CPUs and GPUs, LTT runs on many computing platforms (Linux/Unix, Windows, and Mac; laptops to supercomputers). As a result, LTT can:process data acquired from various custom-built and commercially available CT scanners, model and simulate x-ray and neutron interactions to encourage algorithm prototyping, and allow for rapid insertion of the latest algorithms.We describe LTT’s software architecture, user interfaces, and its 88 algorithms (as of this writing) for pre-processing, reconstruction, post-processing, and simulation that support many scanner geometries (parallel-, fan-, cone-beam, and custom). Several applications are presented that illustrate LTT’s accuracy, speed, and flexibility relative to other solutions.

36 MATERIALS SCIENCE↗

Hyperspectral and Nanosecond Temporal Resolution Widefield Infrared Photothermal Heterodyne Imaging

Label-free, bond-selective imaging offers new opportunities for fundamental and applied studies in chemistry, biology, and materials science. Preventing its broader application to investigating spectrally congested specimens are issues related to low sensitivity as well as low spatial and temporal resolution. Here, we demonstrate a widefield, mid-infrared (MIR) photothermal imaging technique, called widefield Infrared Photothermal Heterodyne imaging (wIR-PHI), that massively parallelizes acquisition of MIR absorption data through use of a high-speed complementary metal-oxide-semiconductor camera. wIR-PHI possesses notable features that include: spatial resolution significantly below the MIR diffraction limit, hyperspectral imaging capabilities, high sensitivity, and ~100 ns temporal resolution. Here, the first two features are highlighted by hyperspectral imaging of proximally close poly(methyl methacrylate) (PMMA) and polystyrene (PS) nanoparticles where clear, bond-specific imaging of nanoparticles, separated by less than the MIR diffraction limit, is demonstrated. Sensitivity is highlighted by imaging individual PMMA and PS nanoparticles with radii between r = 97-556 nm. This leads to a current, peak absorption cross-section limit-of-detection of σ abs = 1.9× 10 –16 cm 2 . wIR-PHI's 100 ns temporal resolution is simultaneously demonstrated by observing the decay of photothermal contrast on individual nanoparticles on a ~200-6000 ns timescale. In whole, wIR-PHI’s dramatic increase in acquisition speed opens opportunities for future MIR kinetic imaging and spectroscopic studies of important chemical, biological, and material processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scalable and accurate multi-GPU-based image reconstruction of large-scale ptychography data

Abstract While the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological specimens, the corresponding experiments can yield terabyte-scale volumes of data that can impose a heavy burden on the computing platform. Although graphics processing units (GPUs) provide high performance for such large-scale ptychography datasets, a single GPU is typically insufficient for analysis and reconstruction. Several works have considered leveraging multiple GPUs to accelerate the ptychographic reconstruction. However, most of these works utilize only the Message Passing Interface to handle the communications between GPUs. This approach poses inefficiency for a hardware configuration that has multiple GPUs in a single node, especially while reconstructing a single large projection, since it provides no optimizations to handle the heterogeneous GPU interconnections containing both low-speed (e.g., PCIe) and high-speed links (e.g., NVLink). In this paper, we provide an optimized intranode multi-GPU implementation that can efficiently solve large-scale ptychographic reconstruction problems. We focus on the maximum likelihood reconstruction problem using a conjugate gradient (CG) method for the solution and propose a novel hybrid parallelization model to address the performance bottlenecks in the CG solver. Accordingly, we have developed a tool, called PtyGer ( Pty chographic G PU(multipl e )-based r econstruction), implementing our hybrid parallelization model design. A comprehensive evaluation verifies that PtyGer can fully preserve the original algorithm’s accuracy while achieving outstanding intranode GPU scalability.

97 MATHEMATICS AND COMPUTING↗

Estimating biofuel contaminant concentration from 4D ERT with mixing models

Here, we present the results of a lab-scaled feasibility study to assess the performance of electrical resistivity tomography for detection, characterization, and monitoring of fuel grade ethanol releases to the subsurface. Further, we attempt to determine the concentration distribution of the ethanol from the electrical resistivity tomography data using mixing-models. Ethanol is a renewable fuel source as well as an oxygenate fuel additive currently used to replace the known carcinogen methyl tert-butyl ether; however, ethanol is preferentially biodegraded and a cosolvent. When introduced to areas previously impacted by nonethanol-based fuels, it will facilitate the persistence of carcinogenic fuel compounds like benzene and ethylbenzene, as well as remobilize them to the ground water. These compounds would otherwise be retained in the soil column undergoing active or passive remediation processes such as soil vapor extraction or natural attenuation. Here, we introduce ethanol to a saturated Ottawa sand in a tank instrumented for four-dimensional geoelectrical measurements. Forward model results suggest pure phase ethanol released into a water saturated silica sand should present a detectable target for electrical resistivity tomography relative to a saturated silica sand only. We observe the introduction of ethanol to the closed hydraulic system and subsequent migration over the duration of the experiment. One-dimensional and three–dimensional temporal data are assessed for the detection, characterization, and monitoring of the ethanol release. Results suggest one-dimensional geoelectrical measurements may be useful for monitoring a release, while three-dimensional geoelectrical field imaging would be useful to characterize, monitor, and design effective remediation approaches for an ethanol release, assuming field conditions do not preclude the application of geoelectrical methods. We then attempt to use predictive mixing models to calculate the distribution of ethanol concentration within the measurement domain. For this study we examine four different models: a nested parallel mixing model, a nested cubic mixing model, the complex refractive index model (CRIM), and the Lichtenecker-Rother (L-R) model. The L-R model, modified to include an electrical formation factor geometry term, provided the best agreement with expected EtOH concentrations.

09 BIOMASS FUELS↗

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hubble Space Telescope Observations within the Sphere of Influence of the Powerful Supermassive Black Hole in PKS 0745-191

We present Space Telescope Imaging Spectrograph observations from the Hubble Space Telescope of the supermassive black hole (SMBH) at the center of PKS 0745-191, a brightest cluster galaxy (BCG) undergoing powerful radio-mode active galactic nucleus (AGN) feedback (P cav ~ 5 × 10 45 erg s -1 ). These high-resolution data offer the first spatially resolved map of gas dynamics within an SMBH's sphere of influence under such powerful feedback. Our results reveal the presence of highly chaotic, nondrotational ionized gas flows on subkiloparsec scales, in contrast to the more coherent flows observed on larger scales. While radio-mode feedback effectively thermalizes hot gas in galaxy clusters on kiloparsec scales, within the core, the hot gas flow may decouple, leading to a reduction in angular momentum and supplying ionized gas through cooling, which could enhance accretion onto the SMBH. This process could, in turn, lead to a self-regulating feedback loop. Compared to other BCGs with weaker radio-mode feedback, where rotation is more stable, intense feedback may lead to more chaotic flows, indicating a stronger coupling between jet activity and gas dynamics. Additionally, we observe a sharp increase in velocity dispersion near the nucleus, consistent with a very massive M BH ~ 1.5 × 10 10 M ⊙ SMBH. The density profile of the ionized gas is also notably flat, paralleling the profiles observed in X-ray gas around galaxies where the Bondi radius is resolved. These results provide valuable insights into the complex mechanisms driving galaxy evolution, highlighting the intricate relationship between SMBH fueling and AGN feedback within the host galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

Utah FORGE: Well 16B(78)-32 Logs from Schlumberger Technologies

This dataset is a collection of well logs provided by Schlumberger Technologies from the Utah FORGE well 16B(78)-32 drilling project. Information here includes critical borehole information collected by an ultrasonic borehole imager (UBI) and a fullbore formation microimager (FMI). Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The total depth measured 10,947 feet and the vertical depth measured 8,357 feet.

11.5 inch intermediate casing logs↗

Early Results from GLASS-JWST. II. NIRCam Extragalactic Imaging and Photometric Catalog

We present the reduced images and multiwavelength catalog of the first JWST NIRCam extragalactic observations from the GLASS Early Release Science Program, obtained as coordinated parallels of the NIRISS observations of the Abell 2744 cluster. Images in seven bands (F090W, F115W, F150W, F200W, F277W, F356W, and F444W) have been reduced using an augmented version of the official JWST pipeline; we discuss the procedures adopted to remove or mitigate defects in the raw images. We obtain a multiband catalog by means of forced aperture photometry on point-spread function (PSF)-matched images at the position of F444W-detected sources. The catalog is intended to enable early scientific investigations, and it is optimized for faint galaxies; it contains 6368 sources, with limiting magnitude 29.7 at 5 σ in F444W. We release both images and catalog in order to allow the community to become familiar with the JWST NIRCam data and evaluate their merit and limitations given the current level of knowledge of the instrument.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitatively Monitoring Bubble-Flow at a Seep Site Offshore Oregon: Field Trials and Methodological Advances for Parallel Optical and Hydroacoustical Measurements

Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm 3 /s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (~1,700 m 2 ) that ranged from 4.98 to 8.33 L/min (5.38 × 10 6 to 9.01 × 10 6 CH 4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.

54 ENVIRONMENTAL SCIENCES↗

A Parameterization of Sub-grid Topographical Effects on Solar Radiation in the E3SM Land Model (Version 1.0): Implementation and Evaluation Over the Tibetan Plateau

Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth System Models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the performance of ELM. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover and surface temperature especially in the high-elevation and snow-cover regions over the TP. Topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20 W/m 2 , 10 W/m 2 , and 5 W/m 2 , respectively. The differences in land surface albedo, snow cover fraction, and surface temperature between TOP and PP exceed 0.1, 20%, and 1K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations, and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are more significant with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

58 GEOSCIENCES↗

A parameterization of sub-grid topographical effects on solar radiation in the E3SM Land Model (version 1.0): implementation and evaluation over the Tibetan Plateau

Abstract. Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth system models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes that the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to compare with the ELM simulations. The results show that topography has non-negligible effects on surface energy budget, snow cover, snow depth, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20, 10, and 5 W m−2, respectively. The differences in land surface albedo, snow cover fraction, snow depth, and surface temperature between TOP and PP exceed 0.1, 0.1, 10 cm, and 1 K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are larger with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover, and surface temperature, especially in the high-elevation and snow-covered regions over the TP. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

Hao, Dalei (ORCID:0000000334979774)↗

High-count rate effects in event processing for XRISM/ Resolve X-ray microcalorimeter: I. Ground test

The spectroscopic performance of an X-ray microcalorimeter is compromised at high count rates. We utilize the Resolve X-ray microcalorimeter onboard the XRISM satellite to examine the effects observed during high-count rate measurements and propose modeling approaches to mitigate them. We specifically address the following instrumental effects that impact performance: CPU limit, pile-up, and untriggered electrical cross-talk. Experimental data at high count rates were acquired during ground testing using the flight model instrument and a calibration X-ray source. In the experiment, data processing not limited by the performance of the onboard CPU was run in parallel, which cannot be done in orbit. This makes it possible to access the data degradation caused by limited CPU performance. We use these data to develop models that allow for a more accurate estimation of the aforementioned effects. To illustrate the application of these models in observation planning, we present a simulated observation of GX 13+1. Understanding and addressing these issues is crucial to enhancing the reliability and precision of X-ray spectroscopy in situations characterized by elevated count rates.

47 OTHER INSTRUMENTATION↗

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗