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At least 1,081 records · Page 60

Vibration-Based Method Developed to Detect Cracks in Rotors During Acceleration Through Resonance

In recent years, there has been an increasing interest in developing rotating machinery shaft crack-detection methodologies and online techniques. Shaft crack problems present a significant safety and loss hazard in nearly every application of modern turbomachinery. In many cases, the rotors of modern machines are rapidly accelerated from rest to operating speed, to reduce the excessive vibrations at the critical speeds. The vibration monitoring during startup or shutdown has been receiving growing attention (ref. 1), especially for machines such as aircraft engines, which are subjected to frequent starts and stops, as well as high speeds and acceleration rates. It has been recognized that the presence of angular acceleration strongly affects the rotor's maximum response to unbalance and the speed at which it occurs. Unfortunately, conventional nondestructive evaluation (NDE) methods have unacceptable limits in terms of their application for online crack detection. Some of these techniques are time consuming and inconvenient for turbomachinery service testing. Almost all of these techniques require that the vicinity of the damage be known in advance, and they can provide only local information, with no indication of the structural strength at a component or system level. In addition, the effectiveness of these experimental techniques is affected by the high measurement noise levels existing in complex turbomachine structures. Therefore, the use of vibration monitoring along with vibration analysis has been receiving increasing attention.

Sawicki, Jerzy T.↗

ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures

The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures promise to provide savings in energy efficiency, area, and latency when compared to traditional CPUs for these types of applications — neuromorphic analog and digital technologies provide both low-power and configurable acceleration of challenging artificial intelligence (AI) algorithms. If designed into a heterogeneous system with other accelerators and conventional compute nodes, these technologies have the potential to augment the capabilities of traditional High Performance Computing (HPC) platforms [5]. This expanded computation space requires not only a new approach to physics simulation, but the ability to evaluate and analyze next-generation architectures specialized for AI/ML workloads in both traditional HPC and embedded ND applications. Developing this capability will enable ASC to understand how this hardware performs in both HPC and ND environments, improve our ability to port our applications, guide the development of computing hardware, and inform vendor interactions, leading them toward solutions that address ASC’s unique requirements.

97 MATHEMATICS AND COMPUTING↗

Electronic Bottleneck Suppression in Next‐Generation Networks with Integrated Photonic Digital‐to‐Analog Converters

Digital‐to‐analog converters (DAC) are indispensable functional units in signal processing instrumentation and wide‐band telecommunication links for both civil and military applications. As photonic systems are capable of high data throughput and low latency, an increasingly found system limitation stems from the required domain crossing such as digital to analog and electronic to optical. A photonic DAC implementation, in contrast, enables a seamless signal conversion with respect to both energy efficiency and short signal delay, often requiring bulky discrete optical components and electric–optic transformation, hence introducing inefficiencies. Herein, a novel coherent parallel photonic DAC concept along with a 4‐bit experimental prototype capable of performing this DAC without optic–electric–optic domain crossing is introduced. This new paradigm guarantees a linear intensity weighting among bits when operating at high sampling rates (50 GHz), featuring an exceptional sampling efficiency (> 100 GS ) and small footprint (≈1 mm 2 ) in an 8‐bit implementation. Importantly, this photonic DAC enables seamless interfaces of next‐generation data processing hardware with high relevance in data centers, task‐specific compute accelerators such as neuromorphic engines, and network edge processing applications.

Meng, Jiawei↗

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Towards a More Predictive Framework for Laser-Driven Particle Sources through Experimental Data-Informed Models

Laser-driven particle acceleration (LDPA) has emerged as a critical technology for high-energydensity physics applications since its discovery at Lawrence Livermore National Laboratory twenty years ago. However, realizing the full potential of these particle sources requires understanding the fundamental acceleration mechanisms and developing enhanced target designs for improved performance. This research addressed the need for controllable, high-performance laser-driven proton sources through two complementary approaches: experimentally investigating sheath field dynamics in multi-picosecond laser regimes and developing novel three-dimensional printed microstructured targets to achieve enhanced particle acceleration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ensemble Simulations on Leadership Computing Systems

Scientific productivity can be enhanced through workflow management tools, relieving large High Performance Computing (HPC) system users from the tedious tasks of scheduling and designing the complex computational execution of scientific applications. This paper presents a study on the usage of ensemble workflow tools to accelerate science using the Summit and Frontier supercomputing systems. The research aims to connect science domain simulations using Oak Ridge Leadership Computing Facility (OLCF) supercomputing platforms with ensemble workflow methods in order to accelerate HPC-enabled discovery and boost scientific impact. We present the coupling, porting and optimization of Radical-Cybertools on three applications: Chroma, NAMD and LAMMPS. The tools augment traditional HPC monolithic runs with a pilot scheduler. Lessons-learned are discussed for physics, biology and materials science applications. We discuss intrinsic limitations of coupling and porting ensemble workflow tools to applications that run on large HPC systems. The origins of technical challenges and their solutions developed during the implementation process are discussed. Data management strategies, OLCF’s policies for ensembles, and natively supported workflow tools are also summarized.

Georgiadou, Antigoni [ORNL] (ORCID:000000020977631↗

Selective thermal evolution of native oxide layer in Nb and Nb$_3$Sn-coated SRF grade Nb: An in-situ angular XPS study

This contribution discusses the results of an in-situ angular XPS study on the thermal evolution of the native oxide layer on Nb3Sn and pure Nb. XPS data were recorded with conventional spectrometers using an AlK(alpha) X-ray source for spectra collected up to 600 C, and an MgK(Alpha) X-rays source for temperatures above 600 C. The effect of the thickness, composition, and thermal stability of that oxide layer is relevant to understanding the functional properties of superconducting radiofrequency (SRF) cavities used in particle accelerators. There is a consensus that oxide plays a role in surface resistance (Rs). The focus of this study is Nb3Sn, which is a promising material that is used in the manufacturing of superconducting radiofrequency (SRF) cavities as well as in quantum sensing, and pure Nb, which was included in the study for comparison. The thermal evolution of the oxide layer in these two materials is found to be quite different, which is ascribed to the influence of the Sn atom on the reactivity of the Nb atom in Nb3Sn films. Nb and Sn atoms in this intermetallic solid have different electronegativity, and the Sn atom can reduce electron density around neighbouring Nb atoms in the solid, thus reducing their reactivity for oxygen. This is shown in the thickness, composition, and thermal stability of the oxide layer formed on Nb3Sn. The XPS spectra were complemented by grazing incident XRD patterns collected using the ESRF synchrotron radiation facility. The results discussed herein shed light on oxide evolution in the Nb3Sn compound and guide its processing for potential applications of the Nb3Sn-based SRF cavities in accelerators and other superconducting devices.

Cano, Arely↗

In planta single-molecule imaging and holographic force spectroscopy to study real-time, multimodal turnover dynamics of polysaccharides and associated carbohydrate metabolites

Cellular production of polysaccharides from simple sugar molecules serves critical roles in a variety of metabolic processes essential to the survival of every living organism. In the context of photosynthetically fixed carbon, cell wall polysaccharides synthesis is particularly of interest for increased biomass accumulation for human food, animal feed, and bioenergy related applications. Despite a long history of research in plant cell biology, our understanding of in planta cell wall biosynthesis and its regulation is far from complete due to lack of a comprehensive microscopy toolkit that encompass the multiple spatial and temporal scales in which cell wall polysaccharides fibrils are synthesized and assembled into intricate cell wall networks. In this project, a multidisciplinary team of scientists from Rutgers University, Vanderbilt University, and Oak Ridge National Laboratory carried out innovative multimodal, multiscale microscopy studies of cell wall synthesis using single-molecule force-spectroscopy, super-resolution fluorescence microscopy, and in vivo live cell imaging. Our novel multimodal and holistic imaging approach revealed plant cell wall polysaccharides synthesis processes in unprecedented detail across multiple spatiotemporal scales, from a single-molecule to a single-cell. Besides, the team has made technical and scientific innovations across multiple research fields—microscopy, bioengineering, single-molecule biophysics, and plant biology, etc.—to accomplish the goals. The results from this project will greatly advance the mechanistic and holistic understanding of in planta cell wall synthesis, which will accelerate the development of better transgenic crops for bioenergy applications. Moreover, the new toolbox, combining powerful advanced microscopy assays with cell/protein engineering, will have broader impacts on molecular and cellular biology fields by paving the way for studying cellular processes occurring across multiple physical scales with multimodal microscopy methodologies.

59 BASIC BIOLOGICAL SCIENCES↗

Examples of Mission-driven Data Science from Jefferson Lab and ACES

This presentation details mission-driven data science initiatives at Jefferson Lab and the Joint Institute for Advanced Computing on Environmental Studies (ACES). JLab, a U.S. Department of Energy Office of Science national laboratory, operates the Continuous Electron Beam Accelerator Facility (CEBAF), and is the lead institute for the new High Performance Data Facility (HPDF) Hub. The Joint Institute for ACES brings together interdisciplinary teams in health informatics, climate modeling, computer science, and physics to address environmental challenges, including flood modeling. The Hampton Roads region, particularly Norfolk and Virginia Beach, faces increasing flood risks, motivating the need for rapid, reliable, and risk-aware decision support. ACES’s flooding work has a focus on uncertainty quantification (UQ) and machine learning (ML) for coastal flood management. The work is motivated by the increasing vulnerability of communities such as Norfolk and Virginia Beach, Virginia, to frequent coastal flooding events, and the need for rapid, reliable decision support. The research develops computationally efficient ML surrogate models to forecast water levels and flooding risk. A central theme is the quantification and calibration of predictive uncertainty, especially for out-of-distribution (OOD) scenarios, using techniques such as Monte Carlo Dropout, Deep Ensembles, Gaussian Processes, and Deep Quantile Regression (DQR). The study demonstrates that distance-aware UQ is critical for reliable scientific AI, particularly in high-dimensional, safety-critical, and real-time applications.

McSpadden, Diana [Thomas Jefferson National Accele↗

SRF Resonators for a bi-directional Energy Ramping Upgrade of the Isotope Production Facility Beamline at LANL

The LANL Isotope Production Facility (IPF) is one of the two high-current proton linear accelerators operated under the auspices of the DOE Office of Nuclear Physics Isotope Development and Production for Research Applications Program. The IPF beamline operates with a fixed 100-MeV energy proton beam, diverted from the LANSCE accelerator and guided towards the isotope production target station. The fixed beam energy limits the number of isotopes that can be produced at IPF, and adversely affects the purity of isotopes produced at non-optimal energies. In particular, the IPF program is receiving increasing numbers of requests for high purity isotopes such as Np-236 (national security applications) and Re-186 (medical therapy). These are typically produced via (p,n) and (p,2n) nuclear reactions, requiring very tight control of the incident energies on the production targets to ensure an end product with a high radionuclidic purity. It is well known that this level of energy control cannot be achieved when a 100 MeV beam of mono-energetic protons is degraded to the required energies, typically below 30 MeV, as too much energy spread is acquired. Operating the IPF beamline at lower, mono-energetic beam energies such as at 40 MeV will allow the required tight energy control in target assemblies to ensure a high purity product. In addition, NP has requested a LANL/BNL/ORNL collaboration focus on establishing a national large-scale production capability for the therapy isotope Ac-225. Recent nuclear cross section measurements done at LANL show that due to a steep rise in production cross section towards higher proton energies (See Figure 2), proton beams at energies substantially greater than 100 MeV will be highly beneficial for Ac-225 production [AC255]. Such higher-energy beams cannot be delivered to IPF at present. Lower-energy beams (70 MeV and 40 MeV) can be delivered but only in sole-use mode; all other LANSCE users must be offline during 70 MeV or 40 MeV operation.

07 ISOTOPE AND RADIATION SOURCES↗

Application of a novel multi-stage signal parameter estimator to high dynamic GPS receivers

The performance of a novel multistage estimator when applied to the estimation of the position, velocity, and acceleration of high dynamic Global Positioning System (GPS) receivers is discussed. For the present application, a two-stage specialization of the more general estimation scheme is considered, wherein the first-stage algorithm is selected to be a modified least-squares algorithm operating upon the differential signal model and referred to as differential least-squares (DLS) and the second stage is simply an extended Kalman filter (EKF). In terms of the threshold on received carrier power-to-noise power spectral density ratio (CNR), when compared to the single-stage EKF algorithm, the DLS-EKF algorithm is about 1.5-2.0 dB better in terms of threshold and outperforms the crossproduct AFC (automatic frequency control) loop by 2-5 dB. For the case when data modulation is present, the proposed scheme provides an improvement of about 6 dB in terms of CNR compared to an earlier approximate MLE (maximum likelihood estimation) scheme. There are also very significant improvements in terms of other performance measures.

Kumar, R.↗

A new center for heavy ion research

Progress in cancer therapy with ions heavier than protons, i.e., helium, carbon, oxygen and neon, requires research and development capability. Ion research activity, however, is limited from the absence of U.S. accelerator facilities offering ion beams for therapy – placing the U.S. significantly behind Europe and Asia. With dramatic advances in beam delivery and compact accelerators, the potential exists to create a facility that can play a leadership role in particle therapy and ion-based research. This paper announces summary details of a new center for ion therapy research under construction in Waco, TX, in collaboration with recognized accelerator entities both academic and industrial. The advanced accelerator technologies will produce beams for both clinical and research applications, offering a complete range of ions, intensities and energies required by the medical community, including the capability to perform ultra-high dose irradiation (FLASH) research. FLASH, a recent research initiative, which has the potential of reducing cancer treatment toxicities, is an important if not critical capability for a competitive research center – requiring beam intensities well beyond those provided by current medical accelerators. Building a state-of-the-art cancer research center within a comprehensive facility will provide the resources to promote ion therapy in the U.S, including, preclinical/clinical trials and protocols between modalities, and also support broad ion R&D.

43 PARTICLE ACCELERATORS↗

Topical Group on Application and Industry Community Engagement Frontier Snowmass 2021 (Summary Report)

HEP community leads and operates cutting-edge experiments for the DOE Office of Science which have challenging sensing, data processing, and computing requirements that far surpass typical industrial applications. To make necessary progress in the energy, material, and fundamental sciences, development of novel technologies is often required to enable these advanced detector and accelerator programs. Our capabilities include efficient co-design, which is a prerequisite to enable the deployment of advanced techniques in a scientific setting where development spans from rapid prototyping to robust and reliable production scale. This applies across the design spectrum from the low level fabrication techniques to the high level software development. It underpins the requirement for a holistic approach of innovation that accelerates the cycle of technology development and deployment. The challenges set by the next generation of experiments requires a collaborative approach between academia, industry and national labs. Just a single stakeholder will be unable to deliver the technologies required for the success of the scientific goals. Tools and techniques developed for High Energy Physics (HEP) research can accelerate scientific discovery more broadly across DOE Office of Science and other federal initiatives and also benefit industry applications.

43 PARTICLE ACCELERATORS↗

A Performance and Energy Study of GPU-Resident Preconditioners for Conjugate Gradient Solvers: In the Context of Existing and Novel Approaches

Optimizing a particular subprogram out of the set of Basic (sparse) Linear Algebra Subprograms (BLAS) for a given architecture is a common topic of research. In applications, however, these BLAS functions rarely appear in isolation; usually, many of them are used together, in various combinations and with varying inputs. As the need to solve a large, sparse linear system is ubiquitous throughout HPC applications, linear solvers constitute a realistic, sufficiently complex and well-defined representative use case for composite BLAS routines. To this end, based on a representative set of matrices drawn from a diverse set of fields, we present a framework to study, from the performance and energy perspective, the efficacy of GPU- resident parallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and incomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated by an iterative process. The development of this preconditioner was motivated by solving large graph Laplacian linear systems, for which the existing preconditioners either perform slow on GPU-based platforms or are not applicable. We compare the performance of these preconditioners on different hardware accelerator architectures, i.e., AMD MI250X, MI100, Nvidia A100, V100, and Jetson. Our experiments reveal performance trade-offs and provide information on how to select the best strategy for the given linear system, dictated by its properties, and the platform of interest. We demonstrate the application of our novel preconditioner for solving CG and graph Laplacian systems. Overall, the framework can be utilized as a benchmark to guide informed decisions in choosing a specific preconditioner, i.e., whether it is better to rely on the performance of a triangular solver or on the performance of sparse matrix-vector product. Finally, by considering power consumption to solve the linear systems, we report the energy footprint for the solvers.

Preconditioned Conjugate Gradient, GPUs, iterative↗

SPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G main field

Here, we present measurements of the temperature and E-mode polarization angular power spectra of the cosmic microwave background (CMB) from observations of 4% of the sky with SPT-3G, the current camera on the South Pole Telescope (SPT). The maps used in this analysis are the deepest used in a CMB TT / TE / EE analysis to date. The maps and resulting power spectra have been validated through blind and unblind tests. The measurements of the lensed EE and TE spectra are the most precise to date at ℓ = 1800 – 4000 and ℓ = 2200 – 4000 , respectively. Combining our TT / TE / EE spectra with previously published SPT-3G CMB lensing results, we find parameters for the standard Λ cold dark matter ( Λ CDM ) model consistent with Planck and ACT DR6 with comparable constraining power. We report a Hubble constant of H 0 = 66.66 ± 0.60 km s - 1 Mpc - 1 from SPT-3G alone, 6.2 σ away from local measurements from SH0ES. For the first time, combined ground-based ( SPT + ACT ) CMB primary and lensing data have reached Planck’s constraining power on some parameters, a milestone for CMB cosmology. The combination of these three CMB experiments yields the tightest CMB constraints to date, with H 0 = 67.19 ± 0.38 km s - 1 Mpc - 1 , and the amplitude of clustering σ 8 = 0.8137 ± 0.0037 . CMB data alone show no evidence for physics beyond Λ CDM , however, we observe a 2.8 σ difference in Λ CDM between CMB and baryon acoustic oscillation (BAO) results from DESI-DR2, which is relaxed in extended models. The combination of CMB and BAO yields 2 − 3 σ shifts from Λ CDM in the curvature of the Universe, the amplitude of CMB lensing, or the dark energy equation of state. It also drives mild preferences for models that address the Hubble tension through modified recombination or variations in the electron mass in a nonflat Universe. This work highlights the growing power of ground-based CMB experiments and lays a foundation for further cosmological analyses with SPT-3G.

Camphuis, Etienne [Sorbonne Université; CNRS; Inst↗

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception

This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.

ADVANCED PROPULSION SYSTEMS↗

Application of a lifting surface theory for a helicopter in forward flight

A lifting-surface theory has been developed for a helicopter rotor in forward flight for compressible and incompressible flow. The method utilizes the concept of the linearized acceleration potential and makes use of the doublet lattice procedure. Calculations demonstrating the application of the method are given in terms of the lift distribution on a single rotor, a two-bladed rotor, and a rotor with swept-forward and swept-back tips. In addition, the lift on a rotor which is vibrating in a pitching mode at 4/rev is given. Compressibility effects and interference effects for a two-bladed rotor are discussed.

Runyan, Harry L.↗

High temperature polymer dielectric film-wire insulation

The highlights of the program are outlined including two major accomplishments. TRW identified and demonstrated the potential of two aromatic/heterocyclic polymers to have an outstanding and superior combination of electrical, thermal, and chemical resistance properties versus state-of-the-art Kapton for spacecraft and/or aircraft dielectric insulation applications. (Supporting data is provided in tables.) Feasibility was demonstrated for supporting/enabling technologies such as ceramic coatings, continuous film casting, and conductor wire wrapping, which are designed to accelerate qualification and deployment of the new wire insulation materials for USAF systems applications during the mid- to late-1990's.

Nairus, John G.↗