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At least 325 records · Page 18

Fault-Tolerant and Elastic Streaming MapReduce with Decentralized Coordination

The MapReduce programming model, due to its simplicity and scalability, has become an essential tool for processing large data volumes in distributed environments. Recent Stream Processing Systems (SPS) extend this model to provide low-latency analysis of high-velocity continuous data streams. However, integrating MapReduce with streaming poses challenges: first, the runtime variations in data characteristics such as data-rates and key-distribution cause resource overload, that inturn leads to fluctuations in the Quality of the Service (QoS); and second, the stateful reducers, whose state depends on the complete tuple history, necessitates efficient fault-recovery mechanisms to maintain the desired QoS in the presence of resource failures. We propose an integrated streaming MapReduce architecture leveraging the concept of consistent hashing to support runtime elasticity along with locality-aware data and state replication to provide efficient load-balancing with low-overhead fault-tolerance and parallel fault-recovery from multiple simultaneous failures. Our evaluation on a private cloud shows up to 2:8 improvement in peak throughput compared to Apache Storm SPS, and a low recovery latency of 700 -1500 ms from multiple failures.

97 MATHEMATICS AND COMPUTING↗

Impact of fabrication methods on binder distribution and charge transport in composite cathodes of all-solid-state batteries

Abstract The manufacturing process of all-solid-state batteries necessitates the use of polymer binders. However, these binders, being ionic insulators by nature, can adversely affect charge transport within composite cathodes, thereby impacting the rate performance of the batteries. In this work, we aim to investigate the impact of fabrication methods, specifically the solvent-free dry process versus the slurry-cast wet process, on binder distribution and charge transport in composite cathodes of solid-state batteries. In the dry process, the binder forms a fibrous network, while the wet process results in binder coverage on the surface of cathode active materials. The difference in microstructure leads to a notable 20-fold increase in ionic conductivity in the dry-processed cathode. Consequently, the cells processed via the dry method exhibit higher capacity retention of 89% and 83% at C/3 and C/2 rates, respectively, in comparison to 68% and 58% for the wet-processed cells at the same rate. These findings provide valuable insights into the influence of fabrication methods on binder distribution and charge transport, contributing to a better understanding of the binder’s role in manufacturing of all-solid-state batteries.

Emley, Benjamin↗

Ion distribution measurements to probe target and plasma processes in electronegative magnetron discharges. II. Positive ions

Spectra of the ion mass and energy distributions of positive ions in reactive (Ar/O{sub 2}) and nonreactive (Ar) dc magnetron sputtering discharges have been investigated by energy-resolved mass spectrometry. The results of three sputter target materials, i.e., Cu, In, and W are compared to each other. Besides the main gas constituents, mass spectra reveal a variety of molecular ions which are dependent on the target material. In reactive mode, ArO{sup +} is always observed in Ar/O{sub 2} but molecules containing Ar and the metal were exclusively found for the Cu target. The occurrence of the different ions is explained in the context of their bond strengths obtained from density functional theory calculations. The energy spectra generally contain the known low-energy peak corresponding to the plasma potential. Differently extended high-energy tails due to sputtered material were observed for the different targets. Besides these, high-energetic ions were detected with up to several 100 eV. Their energies are significantly different for Ar{sup +} and O{sup +} with Ar{sup +} strongly depending on the target material. The spectra are discussed together with results from transport of ions in matter (TRIM) calculation to elucidate the origin of these energetic ions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Iron distribution in silicon after solar cell processing: Synchrotron analysis and predictive modeling

The evolution during silicon solar cell processing of performance-limiting iron impurities is investigated with synchrotron-based x-ray fluorescence microscopy. We find that during industrial phosphorus diffusion, bulk precipitate dissolution is incomplete in wafers with high metal content, specifically ingot border material. Postdiffusion low-temperature annealing is not found to alter appreciably the size or spatial distribution of FeSi{sub 2} precipitates, although cell efficiency improves due to a decrease in iron interstitial concentration. Gettering simulations successfully model experiment results and suggest the efficacy of high- and low-temperature processing to reduce both precipitated and interstitial iron concentrations, respectively.

36 MATERIALS SCIENCE↗

Bayesian reconstruction of the velocity distribution of weakly interacting massive particles from direct dark matter detection data

In this paper, we extended our earlier work on the reconstruction of the (time-averaged) one-dimensional velocity distribution of Galactic Weakly Interacting Massive Particles (WIMPs) and introduce the Bayesian fitting procedure to the theoretically predicted velocity distribution functions. In this reconstruction process, the (rough) velocity distribution reconstructed by using raw data from direct Dark Matter detection experiments directly, i.e. measured recoil energies, with one or more different target materials, has been used as ''reconstructed-input'' information. By assuming a fitting velocity distribution function and scanning the parameter space based on the Bayesian analysis, the astronomical characteristic parameters, e.g. the Solar and Earth's Galactic velocities, will be pinned down as the output results.

79 ASTRONOMY AND ASTROPHYSICS↗

WE-AB-204-02: Molecular-Imaging Based Assessment of Liver Complications for Yttrium-90 Microsphere Treatments: Can Existing NTCP Models Explain Clinical Outcomes?

Purpose: To evaluate weather the current radiobiological models can predict the normal liver complications of radioactive Yttrium-90 ({sup 90}Y) selective-internal-radiation-treatment (SIRT) for metastatic liver lesions based on the post-infusion {sup 90}Y PET images. Methods: A total of 20 patients with metastatic liver tumors treated with SIRT that received a post-infusion {sup 90}Y-PET/CT scan were analyzed in this work. The 3D activity distribution of the PET images was converted into a 3D dose distribution via a kernel convolution process. The physical dose distribution was converted into the equivalent dose (EQ2) delivered at 2 Gy based on the linear-quadratic (LQ) model considering the dose rate effect. The biological endpoint of this work was radiation-induce liver disease (RILD). The NTCPs were calculated with four different repair-times (T1/2-Liver-Repair= 0,0.5,1.0,2.0 hr) and three published NTCP models (Lyman-external-RT, Lyman 90Y-HCC-SIRT, parallel model) were compared to the incidence of RILD of the recruited patients to evaluate their ability of outcome prediction. Results: The mean normal liver physical dose (avg. 51.9 Gy, range 31.9–69.8 Gy) is higher than the suggested liver dose constraint for external beam treatment (∼30 Gy). However, none of the patients in our study developed RILD after the SIRT. The estimated probability of ‘no patient developing RILD’ obtained from the two Lyman models are 46.3% to 48.3% (T1/2-Liver-Repair= 0hr) and <1% for all other repair times. For the parallel model, the estimated probability is 97.3% (0hr), 51.7% (0.5hr), 2.0% (1.0hr) and <1% (2.0hr). Conclusion: Molecular-images providing the distribution of {sup 90}Y enable the dose-volume based dose/outcome analysis for SIRT. Current NTCP models fail to predict RILD complications in our patient population, unless a very short repair-time for the liver is assumed. The discrepancy between the Lyman {sup 90}Y-HCC-SIRT model predicted and the clinically observed outcomes further demonstrates the need of an NTCP model specific to the metastatic liver SIRT.

60 APPLIED LIFE SCIENCES↗

12 GeV Upgrade and the study of 3D imaging of nucleon

The 12 GeV upgrade of Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab will enable a new experimental program with substantial discovery potential in hadronic and nuclear physics. One of the flagship science programs is the study of multidimensional images of hadrons. A broad experimental program has been developed to map the nucleon's intrinsic correlated spin and momentum distribution through measurement of deeply exclusive and semi- inclusive processes. These multidimensional distributions open a new window on the elusive spin content of the nucleon through observables that are directly related to the orbital angular momentum of quarks and gluons. An overview of the 12 GeV upgrade with focus on the study of the multidimensional imaging of hadrons with the CLAS12 detector will be presented.

Elouadrhiri, Latifa↗

Distribution of tunnelling times for quantum electron transport

In electron transport, the tunnelling time is the time taken for an electron to tunnel out of a system after it has tunnelled in. We define the tunnelling time distribution for quantum processes in a dissipative environment and develop a practical approach for calculating it, where the environment is described by the general Markovian master equation. We illustrate the theory by using the rate equation to compute the tunnelling time distribution for electron transport through a molecular junction. The tunnelling time distribution is exponential, which indicates that Markovian quantum tunnelling is a Poissonian statistical process. The tunnelling time distribution is used not only to study the quantum statistics of tunnelling along the average electric current but also to analyse extreme quantum events where an electron jumps against the applied voltage bias. The average tunnelling time shows distinctly different temperature dependence for p- and n-type molecular junctions and therefore provides a sensitive tool to probe the alignment of molecular orbitals relative to the electrode Fermi energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Distribution of High-Rate Data Processing from CERN to Remote HPC Data Centers

The prompt reconstruction of the data recorded from the Large Hadron Collider (LHC) detectors has always been addressed by dedicated resources at the CERN Tier-0. Such workloads come in spikes due to the nature of the operation of the accelerator and in special high load occasions experiments have commissioned methods to distribute (spill-over) a fraction of the load to sites outside CERN. The present work demonstrates a new way of supporting the Tier-0 environment by provisioning resources elastically for such spilled-over workflows onto the Piz Daint Supercomputer at CSCS. Furthermore, this is implemented using containers, tuning the existing batch scheduler and reinforcing the scratch file system, while still using standard Grid middleware. ATLAS, CMS and CSCS have jointly run selected prompt data reconstruction on up to several thousand cores on Piz Daint into a shared environment, thereby probing the viability of the CSCS high performance computer site as on demand extension of the CERN Tier-0, which could play a role in addressing the future LHC computing challenges for the high luminosity LHC.

97 MATHEMATICS AND COMPUTING↗

Economic risk analysis for the capture of a distributed energy resource using modular chemical process intensification

Recent advances in the chemical process industry have allowed for the intensification of reactors and unit operations, by enhancing heat and mass transfer or combining multiple unit operations. Process intensification can enable chemical plants to be constructed in a more compact, modular fashion, offering improvements over conventional on-site approaches to capital construction, operations and maintenance. This modular chemical process intensification (MCPI) offers several benefits over conventional stick-built (CSB) plant construction in terms of reduced footprint, reduced energy consumption, lower cost, less waste and improved safety and quality control. However, acceptance of MCPI over CSB construction practices within the chemical industry can be impeded by the uncertain risks associated with investing in new technology. Furthermore, the work here documents a case study during the development of a modular chemical plant for capturing distributed energy resources within chemical production. This MCPI approach to plant construction is contrasted with a CSB approach for producing the same chemical product. Data collection tools were developed, based on a literature review, and data was collected from the technology developer to understand the process technology. Sensitivity analysis was then conducted to analyze the business rationale for the application of MCPI over CSB across several market scenarios. It was found that MCPI would be better suited for capacities up to 150 000 metric tons per year, but that improvement in payback period was needed. Additionally, for MCPI approach to achieve acceptable payback periods, efforts are needed to reduce the cost of capital equipment and compress the schedule for ramping up modular production.

42 ENGINEERING↗

EJFAT Scientific Perspective

Presented new computing model to the test by deploying the EJFAT system alongside a data-stream processing framework running the production-level CLAS12 event reconstruction application. In this experiment, a continuous stream of CLAS12 Level-1 identified events was processed in real-time using the EJFAT load balancer, distributing the workload across 90 computing nodes located across the U.S. This marks the first-ever large-scale, real-time distributed data stream processing experiment, demonstrating that scientific data-streaming pipelines can efficiently scale across four dimensions, thanks to EJFAT’s advanced hardware and software capabilities.

Gyurjyan, Vardan [Thomas Jefferson National Accele↗

A distributed cellulosic biorefinery system in the US Midwest based on corn stover

Corn stover supply chains in a distributed biorefinery system are explored here. The distributed cellulosic biorefinery uses pre-processed and densified cellulosic feedstock from a geographically separated facility (a depot) as raw material. A network of small-scale depot facilities supplies pre-processed feedstock to a distributed biorefinery. Depot facilities are assumed to be located at existing grain elevators, while distributed biorefineries are located adjacent to coal-fired power plants in areas with high gasoline consumption (urban areas) in the Midwest. The county level corn stover projections in 2022 by the US Billion-Ton Update report (2011) are used to estimate ethanol selling price and greenhouse gas (GHG) emissions of the ethanol fuel. The supply chain for each distributed biorefinery is determined by minimizing the ethanol selling price. Approximately ten distributed biorefineries based on corn stover could be established in the Midwest. Over 700 individual depot facilities participate in supplying the distributed biorefinery systems which collectively can produce greater than 12 hm3 of ethanol (3.3 billion gallons) per year. Ethanol selling price in the distributed system ranges from US$\$ $0.66 to US$\$ $1.03 per liter. Some distributed biorefineries are economically competitive with a centralized biorefinery. However, not every region can support a distributed biorefinery system due to inadequate corn stover availability. Cradle-to-gate GHG emissions of ethanol in the distributed systems are 22.1–46.6 g CO 2 per MJ. The external energy consumption in the depot facilities is the major GHG source. Optimizing process energy use in the depot facility is required to reduce both operation costs and GHG emissions.

09 BIOMASS FUELS↗

Frequency mismatch in stimulated scattering processes: An important factor for the transverse distribution of scattered light

A 2D cylindrically symmetric model with inclusion of both diffraction and self-focus effects is developed to deal with the stimulated scattering processes of a single hotspot. The calculated results show that the transverse distribution of the scattered light is sensitive to the longitudinal profiles of the plasma parameters. The analysis of the evolution of the scattered light indicates that it is the frequency mismatch of coupling due to the inhomogeneity of plasmas that determines the transverse distribution of the scattered light.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Distributed Approach to Maximum Power Point Tracking for Photovoltaic Submodule Differential Power Processing

This paper presents the theory and implementation of a distributed algorithm for controlling differential power processing converters in photovoltaic (PV) applications. This distributed algorithm achieves true maximum power point tracking of series-connected PV submodules by relying only on local voltage measurements and neighbor-to-neighbor communication between the differential power converters. Compared to previous solutions, the proposed algorithm achieves reduced number of perturbations at each step and potentially faster tracking without adding extra hardware; all these features make this algorithm well-suited for long submodule strings. The formulation of the algorithm, discussion of its properties, as well as three case studies are presented. The performance of the distributed tracking algorithm has been verified via experiments, which yielded quantifiable improvements over other techniques that have been implemented in practice. Both simulations and hardware experiments have confirmed the effectiveness of the proposed distributed algorithm.

Qin, SB↗

Improving Transparency in Electric Distribution System Planning to Support Affordability [Slides]

This resource identifies opportunities for communities to participate in the distribution system planning process to achieve their energy goals, including affordability. It begins with background information on the distribution system and distribution system planning, and then focuses on topical areas where communities could focus their engagement (e.g., non-wires alternatives, DER forecast, scenario analysis). The report concludes with illustrative examples of how communities have engaged in distribution system planning. The appendix provides procedural guidance on engagement in utility planning processes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

TYPE Ia SUPERNOVAE AS SITES OF THE p-PROCESS: TWO-DIMENSIONAL MODELS COUPLED TO NUCLEOSYNTHESIS

Beyond Fe, there is a class of 35 proton-rich nuclides, between {sup 74}Se and {sup 196}Hg, called p-nuclei. They are bypassed by the s and r neutron capture processes and are typically 10-1000 times less abundant than the s- and/or r-isotopes in the solar system. The bulk of p-isotopes is created in the 'gamma processes' by sequences of photodisintegrations and beta decays in explosive conditions in both core collapse supernovae (SNe II) and in Type Ia supernovae (SNe Ia). SNe II contribute to the production of p-nuclei through explosive neon and oxygen burning. However, the major problem in SN II ejecta is a general underproduction of the light p-nuclei for A < 120. We explore SNe Ia as p-process sites in the framework of a two-dimensional SN Ia delayed detonation model as well as pure deflagration models. The white dwarf precursor is assumed to have reached the Chandrasekhar mass in a binary system by mass accretion from a giant/main-sequence companion. We use enhanced s-seed distributions, with seeds directly obtained from a sequence of thermal pulse instabilities both in the asymptotic giant branch phase and in the accreted material. We apply the tracer-particle method to reconstruct the nucleosynthesis by the thermal histories of Lagrangian particles, passively advected in the hydrodynamic calculations. For each particle, we follow the explosive nucleosynthesis with a detailed nuclear reaction network for all isotopes up to {sup 209}Bi. We select tracers within the typical temperature range for p-process production, (1.5-3.7) x 10{sup 9} K, and analyze in detail their behavior, exploring the influence of different s-process distributions on the p-process nucleosynthesis. In addition, we discuss the sensitivity of p-process production to parameters of the explosion mechanism, taking into account the consequences on Fe and alpha elements. We find that SNe Ia can produce a large amount of p-nuclei, both the light p-nuclei below A = 120 and the heavy-p nuclei, at quite flat average production factors, tightly related to the s-process seed distribution. For the first time, we find a stellar source able to produce both light and heavy p-nuclei almost at the same level as {sup 56}Fe, including the debated neutron magic {sup 92,} {sup 94}Mo and {sup 96,} {sup 98}Ru. We also find that there is an important contribution from the p-process nucleosynthesis to the s-only nuclei {sup 80}Kr, {sup 86}Sr, to the neutron magic {sup 90}Zr, and to the neutron-rich {sup 96}Zr. Finally, we investigate the metallicity effect on p-process production in our models. Starting with different s-process seed distributions for two metallicities Z = 0.02 and Z = 0.001, running two-dimensional SN Ia models with different initial composition, we estimate that SNe Ia can contribute to at least 50% of the solar p-process composition. A more detailed analysis of the role of SNe Ia in Galactic chemical evolution of p-nuclei is in preparation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗

Martensite crystallography and chemistry in dual phase and fully martensitic steels

Highlights: • Lath martensite islands and bands were indexed in variations of dual-phase steels. • Detail insight was obtained by combined EBSD, APT, TEM, nano-indentation analysis. • The islands predominantly consist of one main packet with all six variants. • The bands are composed of connected domains, each largely made of one main packet. • Tempering at ~450 °C causes carbon partition to lath boundaries and dislocation cores. - Abstract: Lath martensite is important in industry because it is the key strengthening component in many advanced high strength steels. The study of crystallography and chemistry of lath martensite is extensive in the literature, however, mostly based on fully martensitic steels. In this work, lath martensite in dual phase steels is investigated with a focus on the substructure identification of the martensite islands and microstructural bands using electron backscattered diffraction, and on the influence of the accompanied tempering process during industrial coating process on the distribution of alloying elements using atom probe tomography. Unlike findings for the fully martensitic steels, no martensite islands with all 24 Kurdjumov-Sachs variants have been observed. Almost all martensite islands contain only one main packet with all six variants and minor variants from the remaining three packets of the same prior austenite grain. Similarly, the martensite bands are typically composed of connected domains originating from prior austenite grains, each containing one main packets (mostly with all variants) and few separate variants. The effect of tempering at ~450 °C (due to the industrial zinc coating process) has also been investigated. The results show a strong carbon partitioning to lath boundaries and Cottrell atmospheres at dislocation core regions due to the thermal process of coating. In contrast, auto-tempering contributes to the carbon redistribution only in a limited manner. The substitutional elements are all homogenously distributed. The phase transformation process has two effects on the material: mechanically, the earlier-formed laths are larger and softer and therefore more ductile (as revealed by nanoindentation); chemically, due to the higher dislocation density inside the later-formed laths, which are generally smaller, carbon Cottrell atmospheres are predominantly observed.

36 MATERIALS SCIENCE↗