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Convergence acceleration of iterative solutions of potential and Euler equations, based on Wynn's epsilon-algorithm, is demonstrated. The extra computational work, to apply the technique, is negligible, while the storage requirement is definitely affordable with the present computers, at least, for two-dimensional inviscid flow problems.
The particles and energies commonly used for hadron therapy overlap the low end of the charge and energy range of greatest interest for space radiation applications, Z=1-26 and approximately 100-1000 MeV/nucleon. It has been known for some time that the nuclear interactions of the incident ions must be taken into account both in treatment planning and in understanding and addressing the effects of galactic cosmic ray ions on humans in space. Until relatively recently, most of the studies of nuclear fragmentation and transport in matter were driven by the interests of the nuclear physics and later, the hadron therapy communities. However, the experimental and theoretical methods and the accelerator facilities developed for use in heavy ion nuclear physics are directly applicable to radiotherapy and space radiation studies. I will briefly review relevant data taken recently at various accelerators, and discuss the implications of the measurements for radiotherapy, radiobiology and space radiation research.
Development of robust, transparent, and precise monitoring, reporting, and verification (MRV) technologies and practices is critical for carbon dioxide removal (CDR) project developers to comply with regulatory and permitting requirements, voluntary carbon market (VCM) protocols, and to ensure safety while reducing environmental impacts. Enhanced rock weathering (ERW)-based CDR technologies focus on removing atmospheric carbon through conversion into thermodynamically stable solid or aqueous carbonate forms for permanent storage (i.e., mineralization). This highly durable form of CDR enhances naturally occurring silicate rock weathering cycles by optimizing application of finely-ground silicate rock particles (i.e., from basalt) on terrestrial agricultural lands to accelerate natural silicate rock weathering and mineralization. Enhanced rock weathering may also provide improved crop yields and enhance soil health. A critical aspect for commercialization of these technologies is the development of MRV to quantify the net removal and durable storage of atmospheric CO 2 . For ERW systems, it is essential to accurately characterize the mineral feedstock selected for application to establish the baseline geochemical composition, mineral dissolution rates, and carbon removal potential of the feedstocks to estimate overall net removal. Given the difficulty with conducting MRV for ERW in diverse soil/environment types, over large application areas, and due to complex chemical reaction networks, this project will accelerate understanding towards consensus on best practices for MRV. The overall objectives of the proposed voucher project are to: 1) Characterize and analyze feedstock(s) intended for ERW field application by Lithos Carbon (“Voucher Recipient”/ “CRADA Participant”) to determine overall mineralization potential; 2) Facilitate knowledge transfer and documentation of experimental protocols, instrumentation, and other relevant best practices; and 3) Support the Voucher Recipient’s broader technology commercialization and ERW Research Facility development plans. This work will align with the Voucher Recipient’s MRV plans for field sites and build upon complementary efforts conducted by PNNL on mineralization MRV.
This work presents a model for generating nonthermal power-law tails of particles’ energy probability density functions in turbulent collisionless plasmas, applicable to both nonrelativistic and relativistic scenarios. We propose that strong Alfvénic turbulence energizes plasma particles through curvature acceleration, particularly for particles with Larmor radii comparable to the scales of turbulence. When the energy density of the energized particles increases, the efficiency of the energy exchange process diminishes. As a result, the acceleration process saturates, leading to power-law distributions of particle momentum and energy. In the nonrelativistic case, the momentum probability density function scales as f(p)dp ∝ p −3 dp, while in the ultrarelativistic case, the energy probability density function scales as f(γ)dγ ∝ γ −3 dγ, where γ is the Lorentz factor. This model provides a unified framework for understanding particle acceleration in both energy regimes, complementing existing analytical approaches. The predicted scalings are consistent with available observations of energetic ion distributions in the heliosphere and with the findings from numerical simulations of ultrarelativistic particle acceleration in magnetically dominated plasma turbulence.
Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.
The present conference on the applications of state-of-the-art cryogenic engineering technologies considers topics associated with the development status of the 'Superconducting SuperCollider', superconducting magnetic energy storage methods, large magnets for fusion and other physics researches, cryogenic hardware improvements, and phenomena and applications of superconducting magnet-employing acoustic emission test equipment. Also discussed are design criteria for superconducting magnet stability, heat exchangers and heat transfer to liquid He and N, heat and mass transfer characteristics of He II, refrigeration techniques for magnetic resonance imaging and other small systems, refrigeration for liquefaction and for superconducting fusion as well as for accelerator and generator systems, magnetic refrigeration, cryocooling and refrigeration for space applications, the storage and transfer of cryogenic fluids, the properties of cryogenic liquids, and air liquefaction equipment.
In this work, we design and demonstrate a compact electron source that combines an integrated silicon nanotip photoemitter with a compact silicon-based electrostatic lens. The lens simultaneously accelerates electrons to 30 keV and focuses the resulting beam to a 0.4 μm (RMS) beam diameter with 62 pm-rad normalized emittance at a distance of 20 mm from the cathode. The compact nature of this lens provides a compelling source for dielectric laser accelerator (DLA) beamlines, ultrafast electron diffraction, or ultrafast electron microscopy. Driven by a 220 fs, 1960 nm pulsed laser beam, electron currents up to 28 electrons/pulse at 100 kHz are demonstrated. The electron bunch length is 540 ± 50 fs for photocurrents of <1 electron/pulse, increasing to 700 ± 80 fs for 28 electrons/pulse, as measured by cross correlation with a 220 fs pulsed laser beam. The maximum 5D peak brightness is measured to be 6.8 × 10 13 A/(m 2 rad 2 ) at 28 electrons/pulse. These results represent a significant step toward developing practical benchtop-sized linear accelerators based on DLA technology or compact ultrafast electron microscopy and diffraction applications.
A complete redesign of the LANSCE front-end is currently under development for the Los Alamos Modernization Project (LAMP). This includes the replacement of the traditional Cockroft-Walton injection system to the newer radiofrequency quadrupole (RFQ) standard. LANSCE accelerates both H- and H+ beams and therefore requires an unconventional application for RFQ systems. A new facility could consider using an independent RFQ for each beam species. However, with the tight space of the LANSCE injector facility, it would prove difficult to instrument. Our initial studies have shown that a single RFQ could be used. The negatively- and positively-charged direct current (DC) beams are shaped, bunched, and accelerated out of phase to each other, with very little interaction. This would work for all possible H+ beam gates and most H- Beam gates. However, a challenge arises with the Weapons Neutron Research (WNR) beam structure that requires the acceleration of bunched beams at higher charge density per pulse. The Long Bunch Enable Gate (LBEG) used for the Lujan center is the best example of a standard injector beam gate. The beam gate, or Macro-Pulse (MP), is 625-us long, separated by at least 8.3 ms. A chopper is used to dice the MP into 1750 mini-Pulses (mP), which are 290-ns wide. After chopping, the MP contains 100,000 micro-Pulses (uP), which are generated by the linac acceleration structure modulated at 201.25 MHz; that is, the micro-Pulses are separated 5 ns apart from each other. The H+ beam structure will be very similar once a chopper is added to its transport. However, the Multi-Pulse Enable Gate (MPEG) used for WNR is significantly different in structure. In this case, the mP is chopped to be only 35-ns wide. This width is then rotated into a single 201.25 MHz RF bucket using the Low Frequency Buncher (LFB). This is proving difficult for the RFQ design in the LAMP upgrade. We began investigating the amount of current sent to WNR for two reasons. Firstly, we wanted to find a solution to avoid using the Low Frequency Buncher to simplify the LAMP RFQ design. It is simple to inject and accelerate a 35 mA DC beam in the LAMP RFQ (this is done in numerous accelerator facilities). However, injecting a short bunch with a larger current (once compressed to 5 ns to meet the RFQ frequency) may be difficult. Second, we have a technique called PSR2WNR in which we do not employ the Low Frequency Buncher, but rather accumulate 5 LBEG uP (5 ns) in the PSR and deliver the accumulated beam to WNR every 1.8 us. As a result, we could provide to WNR with five accumulated LBEG uPs every shot. The goal here is to create a rapid kicker with a frequency response of 555 kHz. DARHT-II and other accelerator facilities have constructed kickers of this type for other uses, and our engineers consider this technology as feasible.
The LHeC project studies the design of a future electron-proton collider at CERN that will run in parallel to the standard LHC operation. For this purpose, the existing LHC storage ring will be combined with an Energy Recovery Linac (ERL), to accelerate electrons up to kinetic energy of 50 GeV. This concept - also applicable to the FCC-eh collider and studied at the PERLE project as prototype version - allows a peak luminosity of 10³⁴ cm⁻² s⁻¹. A sophisticated design of the RF structures, linacs, arcs, and interaction region is required. The electrons are accelerated and, after the interaction point, their energy is recovered through the same RF structures. While this energy recovery concept is a very promising approach, severe challenges are set by the layout of the interaction region, the beam separation concept and the design of the linac and arc lattice for the highest possible momentum acceptance. Emittance control and beam-beam effect of both, electron and proton beams, have been studied in front-to-end simulations and will be presented. We summarise the design principles of the ERL, the optimization of the arc lattice, and the main parameters of the project.
The design of a Ride Quality Augmentation System (RQAS) for commuter aircraft is documented. The RQAS is designed for a Cessna 402B, an 8 passenger prop twin representative to this class of aircraft. The purpose of the RQAS is the reduction of vertical and lateral accelerations of the aircraft due to atmospheric turbulence by the application of active control. The detailed design of the hardware (the aircraft modifications, the Ride Quality Instrumentation System (RQIS), and the required computer software) is examined. The aircraft modifications, consisting of the dedicated control surfaces and the hydraulic actuation system, were designed at Cessna Aircraft by Kansas University-Flight Research Laboratory. The instrumentation system, which consist of the sensor package, the flight computer, a Data Acquisition System, and the pilot and test engineer control panels, was designed by NASA-Langley. The overall system design and the design of the software, both for flight control algorithms and ground system checkout are detailed. The system performance is predicted from linear simulation results and from power spectral densities of the aircraft response to a Dryden gust. The results indicate that both accelerations are possible.
Achieving strong focusing of MeV electron beams is a critical requirement for advanced beam applications such as compact laboratory x-ray sources, high gradient accelerators, and ultrafast electron scattering instrumentation. To address these needs, a compact radially magnetized permanent magnetic solenoid (PMS) has been designed, fabricated, and tested. The solenoid provides a compact and inexpensive solution for delivering high axial magnetic fields (1 T) to focus MeV electron beams. Field characterization of the solenoid demonstrates good agreement with analytical models, validating the PMS design. The electron beam test employs a high-brightness photoinjector to study the focusing properties of the PMS. The results indicate a focal length of less than 10 cm and a significant reduction in beam size with small spherical aberrations. Two application cases are evaluated: angular magnification in ultrafast electron diffraction setups and strong focusing for Compton scattering or other microfocus uses.
The many-body correlation function is a fundamental computation kernel in modern physics computing applications, e.g., Hadron Contractions in Lattice quantum chromodynamics (QCD). This kernel is both computation and memory intensive, involving a series of tensor contractions, and thus usually runs on accelerators like GPUs. Existing optimizations on many-body correlation mainly focus on individual tensor contractions (e.g., cuBLAS libraries and others). In contrast, this work discovers a new optimization dimension for many-body correlation by exploring the optimization opportunities among tensor contractions. More specifically, it targets general GPU architectures (both NVIDIA and AMD) and optimizes many-body correlation’s memory management by exploiting a set of memory allocation and communication redundancy elimination opportunities: first, GPU memory allocation redundancy: the intermediate output frequently occurs as input in the subsequent calculations; second, CPU-GPU communication redundancy: although all tensors are allocated on both CPU and GPU, many of them are used (and reused) on the GPU side only, and thus, many CPU/GPU communications (like that in existing Unified Memory designs) are unnecessary; third, GPU oversubscription: limited GPU memory size causes oversubscription issues, and existing memory management usually results in near-reuse data eviction, thus incurring extra CPU/GPU memory communications.
The high efficiency of energy generation inferred from radio observations of quasars and X-ray observations of Seyfert active galactic nuclei (AGNs) is apparently achieved only by the gravitational conversion of the rest mass energy of accreting matter onto supermassive black holes. Evidence for the acceleration of particles to high energies by a central engine is also inferred from observations of apparent superluminal motion in flat spectrum, core-dominated radio sources. This phenomenon is widely attributed to the ejection of relativistic bulk plasma from the nuclei of active galaxies, and accounts for the existence of large scale radio jets and lobes at large distances from the central regions of radio galaxies. Reports of radio jets and superluminal motion from galactic black hole candidate X-ray sources indicate that similar processes are operating in these sources. Observations of luminous, rapidly variable high-energy radiation from active galactic nuclei (AGNs) with the Compton Gamma Ray Observatory show directly that particles are accelerated to high energies in a compact environment. The mechanisms which transform the gravitational potential energy of the infalling matter into nonthermal particle energy in galactic black hole candidates and AGNs are not conclusively identified, although several have been proposed. These include direct acceleration by static electric fields (resulting from, for example, magnetic reconnection), shock acceleration, and energy extraction from the rotational energy of Kerr black holes. The dominant acceleration mechanism(s) operating in the black hole environment can only be determined, of course, by a comparison of model predictions with observations. The purpose of the work proposed for this grant was to investigate stochastic particle acceleration through resonant interactions with plasma waves that populate the magnetosphere surrounding an accreting black hole. Stochastic acceleration has been successfully applied to the problem of ion and electron energization in solar flares, and is capable of accounting for a wide range of both neutral and charged particle emissions. It is also a component in diffusive shock acceleration, since pitch-angle scattering (which is necessary for multiple shock crossings) is accompanied by diffusion in momentum space, which in turn yields a net systematic energy gain; however, stochastic energization will dominate the first-order shock process only in certain parameter regimes. Although stochastic acceleration has been applied to particle energization in the lobes of radio galaxies, its application to the central regions of AGNs has only recently been considered, but not in detail. We proposed to systematically investigate the plasma processes responsible for stochastic particle acceleration in black hole magnetospheres along with the energy-loss processes which impede particle energization. To this end we calculated acceleration rates and escape time scales for protons and electrons resonating with Alfven waves, and for electrons resonating with whistlers. Assuming either a Kolmogorov or Kraichnan wave spectrum, accretion at the Eddington limit, magnetic field strengths near equipartition, and turbulence energy densities approx. 10% of the total magnetic field energy density, we find that Alfven waves accelerate protons to Lorentz factors approx, equals 10(exp 4) - 10(exp 6) before they escape from the system. Acceleration of electrons by fast mode and whistler waves can produce a nonthermal population of relativistic electrons whose maximum energy is determined by a competition with radiation losses.
Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this paper, we survey the algorithmic and software development activities performed under the auspices of ExaGraph from both a combinatorial and an algebraic perspective. In particular, we detail our recent efforts in porting the algorithms to manycore accelerator (GPU) architectures. We also provide a brief survey of the applications that have benefited from the scalable implementations of different combinatorial algorithms to enable scientific discovery at scale. We believe that several applications will benefit from the algorithmic and software tools developed by the ExaGraph team.
Addressing performance portability across diverse accelerator architectures has emerged as a major challenge in the development of application and programming systems for high-performance computing environments. Although recent programming systems that focus on performance portability have significantly improved productivity in an effort to meet this challenge, the problem becomes notably more complex when compute nodes are equipped with multiple accelerator types—each with unique performance attributes, optimal data layout, and binary formats. To navigate the intricacies of multi-accelerator programming, we propose CHARM-SYCL as an extension of our CHARM multi-accelerator execution environment [27]. This environment will combine our SYCL-based performance-portability programming front end with a back end for extremely heterogeneous architectures as implemented with the IRIS runtime from Oak Ridge National Laboratory. Our preliminary evaluation indicates potential productivity boost and reasonable performance compared to vendor-specific programming system and runtimes.
The vast chemical space of high entropy alloys (HEAs) makes trial-and-error experimental approaches for materials discovery intractable and often necessitates data-driven and/or first principles computational insights to successfully target materials with desired properties. In the context of materials discovery for hydrogen storage applications, a theoretical prediction-experimental validation approach can vastly accelerate the search for substitution strategies to destabilize high-capacity hydrides based on benchmark HEAs, e.g. TiVNbCr alloys. Here, in this study, machine learning predictions, corroborated by density functional theory calculations, predict substantial hydride destabilization with increasing substitution of earth-abundant Fe content in the (TiVNb) 75 Cr 25-x Fe x system. The as-prepared alloys crystallize in a single-phase bcc lattice for limited Fe content x < 7, while larger Fe content favors the formation of a secondary C14 Laves phase intermetallic. Short range order for alloys with x < 7 can be well described by a random distribution of atoms within the bcc lattice without lattice distortion. Hydrogen absorption experiments performed on selected alloys validate the predicted thermodynamic destabilization of the corresponding fcc hydrides and demonstrate promising lifecycle performance through reversible absorption/desorption. This demonstrates the potential of computationally expedited hydride discovery and points to further opportunities for optimizing bcc alloy ↔ fcc hydrides for practical hydrogen storage applications.
Spatial display instruments convey information about both the identity and the location of objects in order to assist surgeons, astronauts, pilots, blind individuals, and others in identification, remote manipulations, navigation, and obstacle avoidance. Scientists believe that these instruments have not reached their full potential and that progress toward new applications, including the possibility of restoring sight to the blind, will be accelerated by advancing the understanding of perceptual processes. This stimulating challenge to basic researchers was advanced by Paul Bach-Y-Rita (1972) and by the National Academy of Science (1986) report on Electronic Aids for the Blind. Although progress has been made, new applications of spatial display instruments in medicine, space, aviation, and rehabilitation await improved theoretical and empirical foundations.
Accurate estimates of electroncapture cross sections at energies relevant to the modeling of the transport, acceleration, and interaction of energetic neutral atoms (ENA) in space (approximately few MeV per nucleon) and especially for multi-electron ions must rely on detailed, but computationally expensive, quantum-mechanical description of the collision process. Kuang's semi-classical approach is an elegant and efficient way to arrive at these estimates. Motivated by ENA modeling efforts for apace applications, we shall briefly present this approach along with sample applications and report on current progress.