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DOE OSTI2018

NSTX-U advances in real-time deterministic PCIe-based internode communication

Distributing control mechanisms across modern commercial off the shelf (COTS) GNU/Linux systems often introduces difficult to mitigate non-deterministic behavior. Existing methods to address this problem involve non-real-time technologies such as Remote Direct Memory Access (RDMA) over Infiniband or custom Ethernet solutions, such as RDMA over Converged Ethernet (RoCE) or userspace Ethernet drivers, that trade determinism for ease of use or lower cost. The National Spherical Torus Experiment Upgrade (NSTX-U) is pursuing a new design that allows direct communication between heterogeneous systems with scalable, microsecond latency with 1 μs of jitter on that latency, outside of the constant transmission delay at the physical layer. The future design of the NSTX-U Real-time Communication System will utilize direct PCIe-to-PCIe communication with kernel support tuned for low overhead, allowing two (or more, through a switch) real-time (RT) systems to communicate and share resources as one larger entity. As a result, this greatly increases the processing capability of the primary Plasma Control System (PCS), turning previously insurmountable computational challenges into a more manageable divide and conquer parallel task.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Towards Highly Scalable Ab Initio Molecular Dynamics (AIMD) Simulations on the Intel Knights Landing Manycore Processor

The Ab Initio Molecular Dynamics (AIMD) method allows scientists to treat the dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. This extremely important method has tremendous computational requirements, because the electronic Schr¨odinger equation, approximated using Kohn-Sham Density Functional Theory (DFT), is solved at every time step. With the advent of manycore architectures, application developers have a significant amount of processing power within each compute node that can only be exploited through massive parallelism. A compute intensive application such as AIMD forms a good candidate to leverage this processing power. In this paper, we focus on adding thread level parallelism to the plane wave DFT methodology implemented in NWChem. Through a careful optimization of tall-skinny matrix products, which are at the heart of the Lagrange multiplier and nonlocal pseudopotential kernels, as well as 3D FFTs, our OpenMP implementation delivers excellent strong scaling on the latest Intel Knights Landing (KNL) processor. We assess the efficiency of our Lagrange multiplier kernels by building a Roofline model of the platform, and verify that our implementation is close to the roofline for various problem sizes. Finally, we present strong scaling results on the complete AIMD simulation for a 64 water molecules test case, that scales up to all 68 cores of the Knights Landing processor.

Environmental Molecular Sciences Laboratory↗

NASA NTRS1994

Inclusion of the second Umkehr in the conventional Umkehr retrieval analysis as a means of improving ozone retrievals in the upper stratosphere

The Umkehr method for retrieving the gross features of the vertical ozone distribution requires measurements of the ratio of zenith-sky radiances at two wavelengths in the near-UV region while the solar zenith angle (SZA) changes from 60 to 90 degrees. A Brewer spectrophotometer was used for taking such measurements extending the SZA range down to 96 degrees. Analyzed data from the Spring of 1991 imply that observations at twilight are of great significance in improving ozone retrievals in the upper stratosphere. Judged by the variance reduction for Umkehr layers 9 to 12 (25-30 percent for layer 11) and the increase in separation and amplitude of the averaging kernels for the relevant layers, the ozone retrievals in the upper stratosphere are shown to be in better agreement with climatological means.

Gioulgkidis, Konstantinos↗

DOE OSTI2022

Disentangling long and short distances in momentum-space TMDs

The extraction of nonperturbative TMD physics is made challenging by prescriptions that shield the Landau pole, which entangle long- and short-distance contributions in momentum space. The use of different prescriptions then makes the comparison of fit results for underlying nonperturbative contributions not meaningful on their own. We propose a model-independent method to restrict momentum-space observables to the perturbative domain. This method is based on a set of integral functionals that act linearly on terms in the conventional position-space operator product expansion (OPE). Artifacts from the truncation of the integral can be systematically pushed to higher powers in Λ QCD /k T . We demonstrate that this method can be used to compute the cumulative integral of TMD PDFs over k T ≤ k$^{cut}_{T}$ in terms of collinear PDFs, accounting for both radiative corrections and evolution effects. This yields a systematic way of correcting the naive picture where the TMD PDF integrates to a collinear PDF, and for unpolarized quark distributions we find that when renormalization scales are chosen near k$^{cut}_{T}$, such corrections are a percent-level effect. We also show that, when supplemented with experimental data and improved perturbative inputs, our integral functionals will enable model-independent limits to be put on the non-perturbative OPE contributions to the Collins-Soper kernel and intrinsic TMD distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Formation energy puzzle in intermetallic alloys: Random phase approximation fails to predict accurate formation energies

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke- Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) meta-GGA. In addition, we utilized two nonlocal DFT functionals, the hybrid HSE06, and the state-of-the-art random phase approximation (RPA). The nonlocal functionals such as HSE06 and RPA yield accurate formation energies of binary alloys with completely-filled d-band metals, where semilocal functionals underperform. The accuracy at the nonlocal functionals is greatly reduced when a partially-filled d-band metal is present in an alloy, while PBE-GGA outperforms in these cases. We show that the accurate prediction of formation energies by any DFT method depends on its ability to predict the accurate electronic properties, e.g., valence d-band contribution to the density of states (DOS). The SCAN meta-GGA often corrects the PBE-DOS, however, it does not provide accurate formation energies compared to PBE. This is assumed to be due to the lack of proper error cancellation that should be expected due to the similar bulk nature of both alloys and their constituents, which may improve with the modification of meta-GGA ingredients. RPA yields too negative formation energies of alloys with partially-filled d-band metals. RPA results can be corrected by restoring the exchange-correlation kernel, thereby improving the short-range electron-electron correlation in metallic densities.

36 MATERIALS SCIENCE↗

DOE OSTI2015

SU-D-201-02: Prediction of Delivered Dose Based On a Joint Histogram of CT and FDG PET Images

Purpose: To investigate whether pre-treatment images can be used in predicting microsphere distribution in tumors. When intra-arterial radioembolization using Y90 microspheres was performed, the microspheres were often delivered non-uniformly within the tumor, which could lead to an inefficient therapy. Therefore, it is important to estimate the distribution of microspheres. Methods: Early arterial phase CT and FDG PET images were acquired for patients with primary liver cancer prior to radioembolization (RE) using Y90 microspheres. Tumor volume was delineated on CT images and fused with FDG PET images. From each voxel (3.9×3.9×3.3 mm3) in the tumor, the Hounsfield unit (HU) from the CT and SUV values from the FDG PET were harvested. We binned both HU and SUV into 11 bins and then calculated a normalized joint-histogram in an 11×11 array.Patients also underwent a post-treatment Y90 PET imaging. Radiation dose for the tumor was estimated using convolution of the Y90 distribution with a dose-point kernel. We also calculated a fraction of the tumor volume that received a radiation dose great than 100Gy. Results: Averaged over 40 patients, 55% of tumor volume received a dose greater than 100Gy (range : 1.1 – 100%). The width of the joint histogram was narrower for patients with a high dose. For patients with a low dose, the width was wider and a larger fraction of tumor volume had low HU. Conclusion: We have shown the pattern of joint histogram of the HU and SUV depends on delivered dose. The patterns can predict the efficacy of uniform intra-arterial delivery of Y90 microspheres.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Fuel Specification for Uranium Monocarbide FAST Fuel Specimens

This specification outlines the fabrication requirements for kernel compact uranium monocarbide (UC) fuel to be fabricated at General Atomics (GA) and is already issued in EDMS and is going thru LRS so that it can be shared with the Vendor. The UC fuel will be irradiated in the Advanced Test Reactor (ATR) using the Irradiation System for High-Throughput Acquisition (ISHA-1). The primary objective of the ISHA-1 capsule design is to deliver to Idaho National Lab (INL) a semi-universal drop-in capsule that can facilitate the irradiation of both fissile and structural materials in a variety of ATR positions. This irradiation experiment will support the need for development of Accelerated Fuel Qualification (AFQ) methods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Scalable Static and Dynamic Community Detection Using Grappolo

Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detection are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.

Community Detection↗

DOE OSTI2026

Linking spout fluidization hydrodynamics to pyrolytic carbon deposition characteristics in a fluidized bed chemical vapor deposition reactor

Spout fluidized bed chemical vapor deposition (SFB-CVD) is the dominant method for producing pyrolytic carbon (PyC) coatings on tristructural-isotropic (TRISO) fuel particles, yet the relationship between gas injector design, fluidization hydrodynamics, and resulting coating quality remains poorly quantified. Here, in this work, three spout fluidized bed (SFB) nozzle geometries were designed and fabricated to empirically investigate how injector-driven changes in particle circulation influence PyC deposition. The geometries were first evaluated in a room temperature fluidization apparatus using time-resolved particle image velocimetry, which highlighted distinct differences in particle velocity fields, circulation pathways, and overall fluidization quality. Graphite versions of each injector geometry were subsequently implemented in a laboratory-scale SFB-CVD reactor to deposit PyC onto surrogate fuel kernels under similar conditions. Post-deposition characterization included particle morphology, coating thickness, porosity distribution, optical anisotropy, and microindentation mechanical testing. Overall, the results show clear differences in coating microstructure as a function of changing injector geometry, despite mechanical testing indicating comparable elastic modulus values across all coatings. This study provides one of the first fully experimental, quantitative mappings between SFB nozzle geometry, fluidization hydrodynamics, and resulting PyC coating structure. The framework established here supports rational injector design and offers a pathway toward improved coating control in future pilot- and production-scale TRISO fuel fabrication systems.

Coated particle fuel↗

DOE OSTI2014

TU-F-18C-07: Hardware Advances for MTF Improvement in Dedicated Breast CT

Purpose: In this study, we have designed and implemented a prototype dedicated breast CT system (bCT) to improve the spatial resolution characteristics, in order to improve detection of micro-calcifications. Methods: A 10.8 kW water-cooled, tungsten anode x-ray tube, running up to 240 mA at 60 kV, coupled with an x-ray generator specifically designed for this application, and 0.3 mm of added copper filter was used to generate x-ray pulses. A CsI CMOS flat panel detector with a pixel pitch of 0.075 mm in native binning mode was used. The system geometry was designed in a way to achieve an FOV on par with similar bCT prototypes, resulting in a magnification factor of 1.39. A 0.013 mm tungsten wire was used to generate point spread functions. Multiple scans were performed with different numbers of projections, different reconstruction kernel sizes and different reconstruction filters to study the effects of each parameter on MTF. The resulting MTFs were then evaluated quantitatively using the generated PFSs. Duplicate scans with the same parameters were performed on two other dedicated breast CT systems to compare the performance of the new prototype. Results: The results of the MTF experiments demonstrate a significant improvement in the spatial resolution characteristics. In the new prototype, using the pulsed x-ray source results in a restoration of the azimuthal MTF degradation, due to motion blurring previously seen in other bCT systems. Moreover, employing the higher resolution x-ray detector considerably improves the MTF. The MTF at 10% of the new system is at 3.5 1/mm, a factor of 4.36 greater than an earlier bCT scanner. Conclusion: The MTF analysis of the new prototype bCT shows that using the new hardware and control results in a significant improvement in visualization of finer detail. This suggests that the visualization of micro-calcifications will be significantly improved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Detecting Anomalies in Time Series Using Kernel Density Approaches

This paper introduces a novel anomaly detection approach tailored for time series data with exclusive reliance on normal events during training. Our key innovation lies in the application of kernel-density estimation (KDE) to scrutinize reconstruction errors, providing an empirically derived probability distribution for normal events post-reconstruction. This non-parametric density estimation technique offers a nuanced understanding of anomaly detection, differentiating it from prevalent threshold-based mechanisms in existing methodologies. In post-training, events are encoded, decoded, and evaluated against the estimated density, providing a comprehensive notion of normality. In addition, we propose a data augmentation strategy involving variational autoencoder-generated events and a smoothing step for enhanced model robustness. The significance of our autoencoder-based approach is evident in its capacity to learn normal representation without prior anomaly knowledge. Through the KDE step on reconstruction errors, our method addresses the versatility of anomalies, departing from assumptions tied to larger reconstruction errors for anomalous events. Our proposed likelihood measure then distinguishes normal from anomalous events, providing a concise yet comprehensive anomaly detection solution. The extensive experimental results support the feasibility of our proposed method, yielding significantly improved classification performance by nearly 10% on the UCR benchmark data.

Frehner, Robin↗

DOE OSTI2016

SU-F-T-287: A Preliminary Study On Patient Specific VMAT Verification Using a Phosphor-Screen Based Geometric QA System (Raven QA)

Purpose: The RavenQA system (LAP Laser, Germany) is a QA device with a phosphor screen detector for performing the QA tasks of TG-142. This study tested if it is feasible to use the system for the patient specific QA of the Volumetric Modulated Arc Therapy (VMAT). Methods: Water equivalent material (5cm) is attached to the front of the detector plate of the RavenQA for dosimetry purpose. Then the plate is attached to the gantry to synchronize the movement between the detector and the gantry. Since the detector moves together with gantry, The ’Reset gantry to 0’ function of the Eclipse planning system (Varian, CA) is used to simulate the measurement situation when calculating dose of the detector plate. The same gantry setup is used when delivering the treatment beam for feasibility test purposes. Cumulative dose is acquired for each arc. The optical scatter component of each captured image from the CCD camera is corrected by deconvolving the 2D spatial invariant optical scatter kernel (OSK). We assume that the OSK is a 2D isotropic point spread function with inverse-squared decrease as a function of radius from the center. Results: Three cases of VMAT plans including head & neck, whole pelvis and abdomen-pelvis are tested. Setup time for measurements was less than 5 minutes. Passing rates of absolute gamma were 99.3, 98.2, 95.9 respectively for 3%/3mm criteria and 96.2, 97.1, 86.4 for 2%/2mm criteria. The abdomen-pelvis field has long treatment fields, 37cm, which are longer than the detector plate (25cm). This plan showed relatively lower passing rate than other plans. Conclusion: An algorithm for IMRT/VMAT verification using the RavenQA has been developed and tested. The model of spatially invariant OSK works well for deconvolution purpose. It is proved that the RavenQA can be used for the patient specific verification of VMAT. This work is funded in part by a Maryland Industrial Partnership Program grant to University of Maryland and to JPLC who owns the Raven technology. John Wong is a co-founder of JPLC.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2002

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗

NASA NTRS2010

Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study

The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods

Das, Santanu↗

NASA NTRS2025

Robust Trajectory Optimization for NRHO Rendezvous Using SPICE Kernel Relative Motion

In this paper, robust optimization is performed on trajectory correction maneuvers during the lunar lander return phase of an Artemis mission, treating the trajectory from one hour after low lunar orbit departure to arrival in the vicinity of the lunar Gateway as a relative motion problem. To enable rapid stochastic optimization techniques requiring many candidate trajectories, SPICE kernel relative motion as implemented by the Quadratic Interpolated State Transition (QIST) system is used as the underlying dynamics propagation. The optimization is performed with a genetic optimizer using linear covariance (LinCov) software in a simplified operational context, taking into account the availability of navigation sensors with varying measurement models, ranges, and accuracies. No numerical integration is used, since the relative motion around Gateway is fully characterized with the a priori computation of the QIST coefficients. Maneuver placements are computed to optimize the minimum 3σ delta-v of the trajectory, the position dispersion at a target point, and a convex combination of these two metrics. An order of magnitude runtime improvement is provided over legacy methods with less than 10% error introduced. All QIST results are shown to be in-family with legacy methods. The tradespace for optimal delta-v design is found to range from 77.0 to 93.9 m/s, while the range of optimal dispersion is between 1.4 and 11.7 km.

Relative Motion↗

DOE OSTI2014

TU-F-18A-09: CT Number Stability Across Patient Sizes Using Virtual-Monoenergetic Dual-Energy CT

Purpose: Virtual-monoenergetic imaging uses dual-energy CT data to synthesize images corresponding to a single photon energy, thereby reducing beam-hardening artifacts. This work evaluated the ability of a commercial virtual-monoenergetic algorithm to achieve stable CT numbers across patient sizes. Methods: Test objects containing a range of iodine and calcium hydroxyapatite concentrations were placed inside 8 torso-shaped water phantoms, ranging in lateral width from 15 to 50 cm, and scanned on a dual-source CT system (Siemens Somatom Force). Single-energy scans were acquired from 70-150 kV in 10 kV increments; dual-energy scans were acquired using 4 energy pairs (low energy: 70, 80, 90, and 100 kV; high energy: 150 kV + 0.6 mm Sn). CTDIvol was matched for all single- and dual-energy scans for a given phantom size. All scans used 128×0.6 mm collimation and were reconstructed with 1-mm thickness at 0.8-mm increment and a medium smooth body kernel. Monoenergetic images were generated using commercial software (syngo Via Dual Energy, VA30). Iodine contrast was calculated as the difference in mean iodine and water CT numbers from respective regions-of-interest in 10 consecutive images. Results: CT numbers remained stable as phantom width varied from 15 to 50 cm for all dual-energy data sets (except for at 50 cm using 70/150Sn due to photon starvation effects). Relative to the 15 cm phantom, iodine contrast was within 5.2% of the 70 keV value for phantom sizes up to 45 cm. At 90/150Sn, photon starvation did not occur at 50 cm, and iodine contrast in the 50-cm phantom was within 1.4% of the 15-cm phantom. Conclusion: Monoenergetic imaging, as implemented in the evaluated commercial system, eliminated the variation in CT numbers due to patient size, and may provide more accurate data for quantitative tasks, including radiation therapy treatment planning. Siemens Healthcare.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

Key results from irradiation and post-irradiation examination of AGR-1 UCO Triso fuel - 18576

The AGR-1 irradiation experiment was performed as the first test of tri-structural isotropic (TRISO) fuel in the US Advanced Gas Reactor Fuel Development and Qualification Program. The experiment consisted of 72 right cylinder fuel compacts containing approximately 3 x 10{sup 5} coated fuel particles with uranium oxide/uranium carbide (UCO) fuel kernels. The fuel was irradiated in the Advanced Test Reactor for a total of 620 effective full power days. Fuel burnup ranged from 11.3 to 19.6% fissions per initial metal atom and time average, volume average irradiation temperatures of the individual compacts ranged from 955 to 1136 deg. C. This paper focuses on key results from the irradiation and post-irradiation examination, which revealed a robust fuel with excellent performance characteristics under the conditions tested and have significantly improved the understanding of UCO coated particle fuel irradiation behavior. The fuel exhibited zero TRISO coating failures (failure of all three dense coating layers) during irradiation and post-irradiation safety testing at temperatures up to 1700 deg. C. Advanced PIE methods have allowed particles with SiC coating failure that were discovered to be present in a very-low population to be isolated and meticulously examined, which has elucidated the specific causes of SiC failure in these specimens. The level of fission product release from the fuel during irradiation and post-irradiation safety testing has been studied in detail. Results indicated very low release of krypton and cesium through intact SiC and modest release of europium and strontium, while also confirming the potential for significant silver release through the coatings depending on irradiation conditions. Focused study of fission products within the coating layers of irradiated particles down to nanometer length scales has provided new insights into fission product transport through the coating layers and the role various fission products may have on coating integrity. The broader implications of these results and the application of lessons learned from AGR-1 to fuel fabrication and post-irradiation examination for subsequent fuel irradiation experiments as part of the US fuel program are also discussed. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗