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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25

Probing Strong-Field QED with Doppler-Boosted Petawatt-Class Lasers

In this work, we propose a scheme to explore regimes of strong-field quantum electrodynamics (SF QED) otherwise unattainable with the currently available laser technology. The scheme relies on relativistic plasma mirrors curved by radiation pressure to boost the intensity of petawatt-class laser pulses by Doppler effect and focus them to extreme field intensities. We show that very clear SF QED signatures could be observed by placing a secondary target where the boosted beam is focused.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Matched Guiding and Controlled Injection in Dark-Current-Free, 10-GeV-Class, Channel-Guided Laser-Plasma Accelerators

Here we measure the high-intensity laser propagation throughout meter-scale, channel-guided laser-plasma accelerators by adjusting the length of the plasma channel on a shot-by-shot basis, showing high-quality guiding of 500 TW laser pulses over 30 cm in a hydrogen plasma of density n 0 ≈ 1 X 10 17 cm -3 . We observed transverse energy transport of higher-order modes in the first ≈ 12 cm of the plasma channel, followed by quasimatched propagation, and the gradual, dark-current-free depletion of laser energy to the wake. We quantify the laser-to-wake transfer efficiency limitations of currently available petawatt-class lasers and demonstrate via simulation how control over the laser mode can significantly improve beam parameters. Using 21.3 J of laser energy, and triggering localized electron injection, we observed electron bunches with single, quasimonoenergetic peaks up to 9.2 GeV with charge extending beyond 10 GeV.

43 PARTICLE ACCELERATORS↗

Raman spectroscopy of thermally perturbed carbon fibers: Discriminating spectral responses of modulus classes and defect types

The mechanical strength properties of carbon fibers are generally thought to be correlated with the presence of underlying atomic-level defects. These defects serve to break the underlying translational symmetry of the graphitic or graphene subunits of the fiber construction, resulting in the emergence of new Raman-active spectral features. However, historical attempts to classify the precise origin of defect contributions to the Raman spectra have been challenging because of indistinct and overlapping features in the carbon fiber Raman spectra. Further, while substantial research exists on high-temperature exposure in inert atmospheres for carbon fiber composites, comparatively less addresses microscale behaviors and Raman spectral alterations to monofilament carbon fibers exposed to high-temperature atmospheric environments. Here, we report Raman spectral responses of nine commercially available high-performance, polyacrylonitrile-based carbon fibers exposed to various atmospheric heat treatments. In this work, we introduce a model-independent characterization method, the integrated absolute difference, to quantify the spectral responses to heat treatment of different fiber modulus classes. We combine this new method with a newly reported strategy to standardize spectral fitting for carbon fibers. With this approach, we show that atomic-scale defects in the underlying fiber microstructure manifest in measurably distinct manners and have distinct responses to thermal perturbation. These combined approaches may lay the foundation for disentangling contributions from specific defects in the Raman spectra of carbon fibers.

36 MATERIALS SCIENCE↗

Trends in spatial correlations, two-phase coexistence, and criticality in a class of type-2 Schloegl models for autocatalysis

A class of type-2 Schloegl models is considered for particles on a square lattice with variable-range cooperativity. These models involve: (i) spontaneous particle annihilation at rate p; (ii) autocatalytic particle creation at unoccupied sites (i, j) with n ⩾ 2 particles within a specified neighborhood, Ω 𝑁 (i, j), of sites at rate $k_n$ = $\frac{^{(^n_2)}}{_{(^N_2)}}$ = $\frac{n{(n-1)}}{_{N(N-1)}}$; and (iii) possible spontaneous particle creation at unoccupied sites at “small” rate ɛ ⩾ 0. In some cases, Ω 𝑁 just includes all symmetry-equivalent sites at a single specific distance 𝑑 (in units of lattice constants) from the unoccupied site, e.g., 𝑑 = 1 (nearest-neighbor sites) where 𝑁 = 4, or 𝑑 = √5 (or √13 or…) where 𝑁 = 8. In other cases, Ω 𝑁 includes sites multiple distances from the unoccupied site, e.g., 𝑑 = {1,√2}, where 𝑁 = 8. Kinetic Monte Carlo (KMC) simulation reveals that these models exhibit a nonequilibrium discontinuous phase transition between high- and low-density states below a critical point, ɛ < ɛ c , with generic two-phase coexistence (2PC) at least for smaller 𝑁. With some exceptions, there is an approach toward mean-field behavior with increasing 𝑁 (so the regime of generic 2PC shrinks, and ɛ c approaches the mean-field value of 1/27). Additional insight into trends is provided by analysis of the exact master equations for the models via hierarchical truncation. These truncations utilize suitably tailored pair approximations which reflect the dominant nonequilibrium spatial correlations. These correlations in turn are shown to reflect the details of the autocatalytic particle creation process. For spatially heterogeneous states, the truncations produce coupled sets of lattice differential equations (LDE) which can describe orientation-dependent propagation of an interface between high- and low-density steady states for ɛ < ɛ c . Pair approximation values of 𝑝 = 𝑝 eq where the interface is stationary, and its orientation-dependence, are in semiquantitative agreement with KMC results. In conclusion, this comparison accounts for propagation failure in the LDE which complicates interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Scaling Ultrahigh-Resolution E3SM Land Model for Leadership-Class Supercomputers

This paper presents advancements in scaling the ultrahigh-resolution E3SM Land Model (uELM) for deployment on leadership-class supercomputers, addressing the increased demand for km-scale Earth system modeling. By focusing on km-scale ELM simulations, we enhance predictive capabilities for climate interactions, facilitating improved responses to climate change impacts on energy systems, agriculture, and water resources. Our approach leverages innovative software architecture optimizations, sophisticated data handling techniques, and advanced parallel processing, achieving strong scalability on two leadership supercomputers (2400 nodes (105,600 cores) on Summit, and 1200 nodes (76,800 cores) on Frontier). Results from extensive scalability assessments on the Summit and Frontier also demonstrate outstanding I/O performance (close to 400 GB/s write throughput) and the model's ability to efficiently handle increasing computational demands. This study not only establishes uELM's capability for high-resolution simulations over vast geographical domains, but also sets a foundation for future Earth system modeling breakthroughs.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗

An Evaluation of the Effect of Network Cost Optimization for Leadership Class Supercomputers

Dragonfly-based networks are an extensively deployed network topology in large-scale high-performance computing due to their cost-effectiveness and efficiency. The US will soon have three Exascale supercomputers for leadership class workloads deployed using dragonfly networks. Compared to indirect networks of similar scale, the dragonfly network has considerably reduced cable lengths, cable counts, and switch counts, resulting in significant network cost savings for a given system size, however, these cost reductions result in reduced global minimal paths and more challenging routing. Additionally, large scale dragonfly networks often require a taper at the global link level, resulting in less bisection bandwidth than is achievable in other traditional non-blocking topologies of equivalent scale. While dragonfly networks have been extensively studied, they have yet to be fully evaluated in an extreme scale (i.e., exascale) system that targets capability workloads. In this paper, we present the results of the first large scale evaluation of a dragonfly network on an exascale system (Frontier) and compare its behavior to a similar scale fat-tree network on a previous generation TOP500 system (Summit). This evaluation aims to determine the effect of network cost optimizations by measuring a tapered topology’s impact on capability workloads. Our evaluation is based on a collection of synthetic microbenchmarks, mini-apps, and full scale applications. It compares the scaling efficiencies of each benchmark between the dragonfly-based Frontier and the fat-tree-based Summit systems. Our results show that a dragonfly network is $\sim \mathbf{3 0 \%}$ more cost efficient than a fat-tree topology, which amortizes to $\sim 3 \%$ of an exascale system cost. Furthermore, while tapered dragonfly networks impose significant tradeoffs, the impacts are not as broad as initially thought and are mostly seen in applications with global communication patterns, particularly all-to-all (e.g., FFT-based algorithms), but also local communication patterns (e.g., nearest-neighbor algorithms) that are sensitive to network performance variability.

Khan, Awais↗

Design and Performance Characterization of RADICAL-Pilot on Leadership-Class Platforms

Many extreme scale scientific applications have workloads comprised of a large number of individual highperformance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders and late-binding. As such, suitable implementations of the Pilot abstraction can support the collective execution of large number of tasks on supercomputers. We introduce RADICAL-Pilot (RP) as a portable, modular and extensible Pilot enabled runtime system. We describe RP's design, architecture and implementation. We characterize its performance and show its ability to scalably execute workloads comprised of tens of thousands heterogeneous tasks on DOE and NSF leadership-class HPC platforms. Specifically, we investigate RP's weak/strong scaling with CPU/GPU, single/multi core, (non)MPI tasks and python functions when using most of ORNL Summit and TACC Frontera. RADICAL-Pilot can be used stand-alone, as well as the runtime for third-party workflow systems.

97 MATHEMATICS AND COMPUTING↗

New classes of topological crystalline insulators having surface rotation anomaly

We discover new types of quantum anomalies in two-dimensional systems with time-reversal symmetry (T) and discrete rotation symmetry with order of n = 2, 4, and 6 (C n ). The new anomalous states have n flavors of massless Dirac fermions protected by T and C n , whereas any two-dimensional lattices having the two symmetries must have a multiple of 4, 8, and 12 Dirac cones for n = 2, 4, and 6, respectively. We show that these anomalous states are physically realized on the surface of new classes of topological crystalline insulators, normal to the rotation axis. Moreover, these topological crystalline insulators support n gapless one-dimensional helical mode on the otherwise fully gapped side surface, connecting the anomalous two-dimensional states on the top and bottom surfaces. The presence of these helical modes enables a new quantum device made from a topological crystalline insulator nanorod, a “helical nanorod,” which has a quantized longitudinal conductance of ne 2 /h.

Science & Technology - Other Topics↗

A New Class of AMG Interpolation Methods Based on Matrix-Matrix Multiplications

A new class of distance-two interpolation methods for algebraic multigrid (AMG) that can be formulated in terms of sparse matrix-matrix multiplications is presented and analyzed. Compared with similar distance-two prolongation operators, the proposed algorithms exhibit improved efficiency and portability to various computing platforms, since they allow one to easily exploit existing high-performance sparse matrix kernels. The new interpolation methods have been implemented in hypre, a widely used parallel multigrid solver library. With the proposed interpolations, the overall time of hypre's BoomerAMG setup can be considerably reduced, while sustaining equivalent, sometimes improved, convergence rates. Numerical results for a variety of test problems on parallel machines are presented that support the superiority of the proposed interpolation operators over the existing ones in hypre.

97 MATHEMATICS AND COMPUTING↗

Performance and Durability of Hybrid Fuel Cell Systems for Class-8 Long Haul Trucks

Hybrid fuel cell-battery configurations are investigated that overcome thermal management issues in fuel cell powertrains for heavy-duty Class 8 trucks. The battery is sized so that it has sufficient capacity to provide supplemental power and energy on a hill climb transient at end-of-life. A dynamic load sharing strategy is developed to distribute the power demand between the fuel cell system (FCS) and the energy storage system in a manner that optimizes their lifetimes. The FCS end-of-life is identified as the terminal point beyond which the stack cannot generate the rated power with target power density at 0.7 V and 40 °C ambient temperature. Reaching the target lifetime with a-Pt/C cathode catalyst in one hybrid configuration requires voltage clipping to 813 mV, idle power limited to 50 kW, catalyst overloading to 0.45 mg cm -2 total Pt in anode and cathode, and 44% active membrane area oversizing. The stack and FCS drive cycle efficiencies decrease by 4.2% and 5.4%, respectively, during the electrode lifetime. Further, the FCS performance, durability and cost are compared with the targets of 68% peak efficiency, 0.30 mg cm -2 total Pt loading, 2.5 kW/g PGM Pt group metal (PGM) loading, 750 mW cm -2 power density, 25,000-h lifetime and $80/kW cost.

33 ADVANCED PROPULSION SYSTEMS↗

Pulse compressor architecture to enable next-generation high-energy petawatt-class lasers

The maximum energy obtainable within a single aperture of a high-energy petawatt-class (HEPW) laser is typically limited by the pulse compressor. This work evaluates the potential impact of two new pulse compression grating technologies (HELD gratings and TM polarization) on HEPW laser systems. A compressor architecture is proposed that implements these grating advancements in order to support ∼6× higher pulse energies than currently demonstrated. This increase in energy and intensity could have substantial benefits to high-flux secondary sources and enable new applications.

47 OTHER INSTRUMENTATION↗

Stacked-mosaic amplifier and diode delivery concept for kJ-class inertial fusion energy laser driver

We report on a laser amplifier architecture designed as a modular element for scaling to multi-megajoule laser facilities intended for inertial fusion energy (IFE) power plants. This kilojoule-class module features a stacked mosaic of gain media integrated with a diode delivery system for efficient optical pumping of the mosaic-structured gain medium, enabling high-repetition-rate operation at high wall plug efficiencies, necessary for an IFE driver. Details of a diode delivery system capable of pumping the mosaic architecture are presented. Comprehensive numerical modeling demonstrates that the stacked-mosaic approach reduces transverse gain by five orders of magnitude compared to a conventional full-aperture Yb:YAG based amplifier, substantially suppressing transverse amplified spontaneous emission (TASE) and enabling enhanced longitudinal energy extraction. Detailed analysis of thermal management and wavefront distortion in a 4 × 4 mosaic array indicates that temperature gradients and thermally induced aberrations are effectively controlled using gas cooling and commercially available phase-plate and deformable mirror technologies. We further discuss the applicability of a stacked-mosaic architecture to direct-drive IFE schemes, where broad spectral bandwidth is critical, and its compatibility with frequency conversion modules for up-conversion to blue wavelengths. Finally, an example point design for a 10 kJ, 10 Hz Yb:YAG module operating at 175 K with wall-plug efficiency exceeding 10 % is presented, underscoring the feasibility of this approach for next-generation high-energy lasers for IFE drivers. The results establish the stacked-mosaic amplifier as a scalable, robust platform not only for IFE but also for a broad range of advanced scientific and industrial laser applications.

Lasers↗

Joule-class THz pulses from microchannel targets

Inference of joule-class THz radiation sources from microchannel targets driven with hundreds of joule, picosecond lasers is reported. Here, THz sources of this magnitude are useful for nonlinear pumping of matter and for charged-particle acceleration and manipulation. Microchannel targets demonstrate increased laser–THz conversion efficiency compared to planar foil targets, with laser energy to THz energy conversion up to ~0.9% in the best cases.

47 OTHER INSTRUMENTATION↗

Diversity, taxonomy, and evolution of archaeal viruses of the class Caudoviricetes

The archaeal tailed viruses (arTV), evolutionarily related to tailed double-stranded DNA (dsDNA) bacteriophages of the class Caudoviricetes , represent the most common isolates infecting halophilic archaea. Only a handful of these viruses have been genomically characterized, limiting our appreciation of their ecological impacts and evolution. Here, we present 37 new genomes of haloarchaeal tailed virus isolates, more than doubling the current number of sequenced arTVs. Analysis of all 63 available complete genomes of arTVs, which we propose to classify into 14 new families and 3 orders, suggests ancient divergence of archaeal and bacterial tailed viruses and points to an extensive sharing of genes involved in DNA metabolism and counterdefense mechanisms, illuminating common strategies of virus–host interactions with tailed bacteriophages. Coupling of the comparative genomics with the host range analysis on a broad panel of haloarchaeal species uncovered 4 distinct groups of viral tail fiber adhesins controlling the host range expansion. The survey of metagenomes using viral hallmark genes suggests that the global architecture of the arTV community is shaped through recurrent transfers between different biomes, including hypersaline, marine, and anoxic environments.

59 BASIC BIOLOGICAL SCIENCES↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗