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At least 595 records · Page 33

ER@CEBAF: A test of 5-pass energy recovery at CEBAF

Jefferson Lab personnel have broad expertise in the design, commissioning, and operation of multiple energy recovery linacs (ERLs): the CEBAF Front-End Test (early 1990s), CEBAF-ER (2003), the IR Free Electron Laser (FEL) Demo, the IR FEL Upgrade, and the UV FEL Driver (1997-2014). Continued development of this core competency has led to this collaborative proposal to explore the forefronts of ERL technology at high energy in a unique expansion of CEBAF capability to a 5-pass ERL with negligible switchover time and programmatic impact to the CEBAF physics program. Such a capability would enable world-class studies of open issues in high-energy ERL beam dynamics that are relevant to future facilities such as electron-ion colliders (EICs). This proposal requests support from the CEBAF Program Advisory Committee to seek funding for hardware installation, and a prospective 12 days of beam time circa Fall 2018 for commissioning this high-energy multi-pass ERL experiment in CEBAF.

43 PARTICLE ACCELERATORS↗

Estimation of Future PM2.5- and Ozone-related Mortality over the Continental United States in a Changing Climate: An application of High-resolution Dynamical Downscaling Technique

This paper evaluates the PM2.5- and ozone-related mortality at present (2000s) and in the future (2050s) over the continental United States by using the Environmental Benefits Mapping and Analysis Program (BenMAP-CE). Atmospheric chemical fields are simulated by WRF/CMAQ (horizontal resolution: 12 × 12km), applying the dynamical downscaling technique from global climate-chemistry models under the Representative Concentration Pathways scenario (RCP 8.5). Future air quality results predict that the annual mean PM2.5 concentrations in continental US will decrease nationwide, especially in the eastern US and west coast. However, the ozone concentration is projected to decrease in the Eastern US but increase in the Western US. Future mortality is evaluated under two scenarios (1) holding future population and baseline incidence rate at the present level and (2) decreasing the future baseline incidence rate but increasing the future population. For PM2.5, the entire continental US presents a decreasing trend of PM2.5-related mortality by the 2050s in Scenario (1), primarily resulting from the emissions reduction. While in Scenario (2), almost half of the continental states show a rising tendency of PM2.5-related mortality, due to the dominant influence of population growth. In particular, the highest PM2.5-related deaths and the biggest discrepancy between present and future PM2.5-related deaths will both occur in California in 2050s. For the ozone-related premature mortality, the simulation shows nation-wide rising tendency in 2050s under both two scenarios, mainly due to the increase of ozone concentration and population in the future. Furthermore, the uncertainty analysis shows that the effect of the all causes mortality is much larger than for specific causes. This assessment is the result of the accumulated uncertainty of generating datasets. The uncertainty range of ozone-related all cause premature mortality is narrower than the PM2.5-related all cause mortality, due to its smaller standard deviation of beta parameter.

BenMAP-CE↗

Power-traffic coordinated operation for bi-peak shaving and bi-ramp smoothing – A hierarchical data-driven approach

The power distribution system and urban transportation system are two networked system bare their own operation constraints, such peak load in power systems and traffic congestion in transportation system. With the increasing number of electrical vehicles and charging/discharging stations, two systems are become tightly coupled. However, to optimize the two systems target using electrical vehicles as decision control variables cannot be easily solved using a uniformed optimization frame work. Thus we propose a hierarchical optimization approach to address this problem, which consists of a higher and a lower level. In the higher level, the power distribution system and urban transportation system are treated together to minimize the social cost. Meanwhile, the electrical vehicles and the charging/discharging stations are treated as customers to minimize their own expenditures. Then, an equilibrium is designed to determine the optimal charging/discharging price. In the lower level, the models of power distribution system and urban transportation system are developed to provide a detailed analysis. Specifically, in power distribution system, the three-phase unbalanced optimal power flow problem is relaxed with the semidefinite relaxation programming, and solved with alternating direction method of multiplier. A dynamic user equilibrium problem is formulated for the urban transportation system. For electrical vehicles, the state of charge is considered to optimize the charging/discharging schedule and reduce the impacts of power distribution systems. We conducted the simulation and numerical analysis using the IEEE 8500-bus distribution system and the Sioux Falls system with about 10,000 cars. The results demonstrate the feasibility and effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

59 BASIC BIOLOGICAL SCIENCES↗

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Shape-Shifting Peptide Nanomaterials: Surface Asymmetry Enables pH-Dependent Formation and Interconversion of Collagen Tubes and Sheets

The fabrication of dynamic, transformable biomaterials that respond to environmental cues represents a significant step forward in the development of synthetic materials that rival their highly functional, natural counterparts. In this work, we describe the design and synthesis of crystalline supramolecular architectures from charge-complementary heteromeric pairs of collagen-mimetic peptides (CMPs). Under appropriate conditions, CMP pairs spontaneously assemble into either 1D ultraporous (pore diameter >100 nm) tubes or 2D bilayer nanosheets due to the structural asymmetry that arises from heteromeric self-association. Crystalline collagen tubes represent a heretofore unobserved morphology of this common biomaterial. In-depth structural characterization from a suite of biophysical methods, including TEM, AFM, high-resolution cryo-EM, and SAXS/WAXS measurements, reveals that the sheet and tube assemblies possess a similar underlying lattice structure. The experimental evidence suggests that the tubular structures are a consequence of the self-scrolling of incipient 2D layers of collagen triple helices and that the scrolling direction determines the formation of two distinct structural isoforms. Furthermore, we show that nanosheets and tubes can spontaneously interconvert through manipulation of the assembly pH and systematic adjustment of the CMP sequence. Altogether, we establish initial guidelines for the construction of dynamically responsive 1D and 2D assemblies that undergo a structurally programmed morphological transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temporal information encoding in dynamic memristive devices

We show temporal and frequency information can be effectively encoded in memristive devices with inherent short-term dynamics. Ag/Ag{sub 2}S/Pd based memristive devices with low programming voltage (∼100 mV) were fabricated and tested. At weak programming conditions, the devices exhibit inherent decay due to spontaneous diffusion of the Ag atoms. When the devices were subjected to pulse train inputs emulating different spiking patterns, the switching probability distribution function diverges from the standard Poisson distribution and evolves according to the input pattern. The experimentally observed switching probability distributions and the associated cumulative probability functions can be well-explained using a model accounting for the short-term decay effects. Such devices offer an intriguing opportunity to directly encode neural signals for neural information storage and analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coordinated Planning Strategy for Integrated Energy Systems in a District Energy Sector

With the ever-growing integration of diverse distributed energy resources, modern district energy sectors are transitioning into integrated energy systems (IESs), which generally consist of various energy carriers such as electric power, natural gas, and heat. Instead of modeling individual energy carriers, the emergence of IESs requires comprehensive consideration of all involved energy systems in both planning and operation phases. This paper proposes a comprehensive planning strategy for a district energy sector to address the challenges of IES planning considering the coupling of power, gas, and heat systems. The proposed planning model contains an operational module that develops a steady-state optimal multi-energy flow (OMEF) for the IES considered and a multi-stage expansion module that optimizes the investment decisions. To efficiently solve the proposed planning model, which is formulated as a mixed-integer nonlinear programming problem, an improved generalized Benders decomposition algorithm that utilizes dynamic dual multipliers to improve the convergence speed is employed. The effectiveness of the proposed planning model and the feasibility of the improved Benders decomposition algorithm are verified in case studies.

coordinated planning↗

Task-based Parallel Computation of the Density Matrix in Quantum-based Molecular Dynamics using Graph Partitioning

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms. These constraints arise due to expensive self-consistent ground-state electronic structure calculations that can often scale cubically with the number of atoms. Linearly scaling methods depend on computing the density matrix P from the Hamiltonian matrix H by exploiting the sparsity in both matrices. The second-order spectral projection (SP2) algorithm is an O(N) algorithm that computes P with a sequence of 40 - 50 matrix-matrix multiplications. In this paper, we present task-based implementations of a recently developed data-parallel graph-based approach to the SP2 algorithm, G-SP2. We represent the density matrix P as an undirected graph and use graph partitioning techniques to divide the computation into smaller independent tasks. The partitions thus obtained are generally not of equal size and give rise to undesirable load imbalances in standard MPI-based implementations. This load-balancing challenge can be mitigated by dynamically scheduling parallel computations at runtime using task-based programming models. We develop task-based implementations of the data-parallel G-SP2 algorithm using both Intel's Concurrent Collections (CnC) as well as the Charm++ programming model and evaluate these implementations for future use. Scaling and performance results of our implementations are investigated for representative segments of QMD simulations for solvated protein systems containing more than 10,000 atoms.

97 MATHEMATICS AND COMPUTING↗

Replacement of tritiated water from irradiated fuel storage bay

Recently, AECL developed a novel method to reduce tritium emissions (to groundwater) and personnel doses at the NRU (National Research Universal) reactor irradiated fuel storage bay (also known as rod or spent fuel bay) through a water swap process. The light water in the fuel bay had built up tritium that had been transferred from the heavy water moderator through normal fuel transfers. The major advantage of the thermal stratification method was that a very effective tritium reduction could be achieved by swapping a minimal volume of bay water and warm tritiated water would be skimmed off the bay surface. A demonstration of the method was done that involved Computational Fluid Dynamics (CFD) modeling of the swap process and a test program that showed excellent agreement with model prediction for the effective removal of almost all the tritium with a minimal water volume. Building on the successful demonstration, AECL fabricated, installed, commissioned and operated a full-scale system to perform a water swap. This full-scale water swap operation achieved a tritium removal efficiency of about 96%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A system-level model for the microbial regulatory genome

Microbes can tailor transcriptional responses to diverse environmental challenges despite having streamlined genomes and a limited number of regulators. Here, we present data-driven models that capture the dynamic interplay of the environment and genome-encoded regulatory programs of two types of prokaryotes: Escherichia coli (a bacterium) and Halobacterium salinarum (an archaeon). The models reveal how the genome-wide distributions of cis-acting gene regulatory elements and the conditional influences of transcription factors at each of those elements encode programs for eliciting a wide array of environment-specific responses. We demonstrate how these programs partition transcriptional regulation of genes within regulons and operons to re-organize gene–gene functional associations in each environment. The models capture fitness-relevant co-regulation by different transcriptional control mechanisms acting across the entire genome, to define a generalized, system-level organizing principle for prokaryotic gene regulatory networks that goes well beyond existing paradigms of gene regulation. An online resource (http:// egrin2.systemsbiology.net) has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

Thermal Neutron Scattering Research and Development at Oak Ridge National Laboratory [Slides]

This presentation provides an overview of the project, specifically describing how neutron cross sections can be broken up into several regions. It also discusses how thermal scattering law (TSL) $\textit{S(α, β)}$ is related to dynamic structure factor $\textit{S(q, E)}$ and how $\textit{S(q, E)}$ can be broken up into 2 primary components, incoherent and coherent, and how it can be calculated in several ways, including density functional theory (DFT) and molecular dynamics (MT). Additionally, it states that ENDF currently stores coherent elastic (Bragg edges), incoherent elastic and incoherent inelastic. Also discussed are the experimental capabilities, evaluations, and uncertainty quantification of the project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of a Pre-Combustion CO 2 Capture Process Using High-Temperature PBI Hollow-Fiber Membranes

The overall objective of this project was to evaluate the advantages of transformational polybenzimidazole (PBI) polymer hollow-fiber membrane (HFM)-based, carbon dioxide (CO 2 ) capture and purification technology at bench-scale using an actual coal-derived syngas stream from a coal gasification facility. The project was carried out over two budget periods. The technical objectives in Budget Period 1 (BP1) included preparing HFs and modules and upgrading the available skid for field testing. The technical objectives for BP2 were to field-test the skid unit with actual coal-derived syngas from an oxygen-blown gasifier to obtain performance data, update the Techno-Economic Analysis (TEA) that would assist with future process scale-up, and provide information on the design of a small pilot-scale test unit. The goal was to advance the PBI-HFM CO 2 capture and gas separation system for pre-combustion applications beyond second-generation economic performance predictions and make progress toward meeting overall fossil energy performance goals of CO 2 capture with 95% CO 2 purity at a cost of electricity (COE) 30% less than baseline capture approaches. The research program was designed with progressive technical tasks leading to both dynamic and steady-state testing of the PBI-HFM skid with actual coal-derived syngas. The work plan was to: (1) fabricate sufficient Generation-2 (GEN-2) fibers for module fabrication; (2) upgrade the fiber skid to accommodate large fiber modules for bench-scale field testing; (3) conduct dynamic and steady-state testing with coal-derived syngas from an oxygen-blown gasifier and obtain system performance data; (4) perform a TEA and environmental, health, and safety (EH&S) assessment; (5) update the State-Point Data Table, Technology Gap Analysis (TGA), and Technology Maturation Plan (TMP); (6) uninstall and return the test skid to the Recipient’s facilities; and (7) submit a Final Report that describes the results and analysis of the project research effort.

03 NATURAL GAS↗

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

Nobody is better suited to “describe” data than the scientist who created it. This “description” about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL’s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME’s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS’s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE’s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT).Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user’s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files.As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive.How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)?The ORNL DAAC is one of NASA’s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data.OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links:USGS OME: http://mercury.ornl.gov/OME/NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ARM OME: http://archive2.ornl.gov/armome/Contact: Ranjeet Devarakonda (devarakondar@ornl.gov)References:[1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998.[2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.[3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata.[4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.

FGDC CSDGM↗

A New Fast Fluid Dynamics Model for Data-Center Floor Plenums

A raised-floor plenum is often used to distribute cooling airflow in data centers. Traditional Computational Fluid Dynamics (CFD) can accurately model airflow distribution in plenums, but it is expensive (computationally and financially) and is, therefore, often not accessible to the data center designer or operator. This paper presents an alternative CFD methodology based on Fast Fluid Dynamics (FFD), which is faster, more parallelizable, and simpler to program. The improvement in computational speed afforded by FFD is particularly important for multiple-iteration optimization, transient simulations, or applications for which near-real-time performance is required. Here, the potential speed improvements of FFD have been widely documented; however, it has been generally accepted that this benefit is accompanied by a modest loss of accuracy relative to traditional CFD. We show here that this is not necessarily true. Plenum airflow predictions by our FFD implementation, which utilizes a first-order upwind rather than Semi-Lagrangian advection scheme of previous research, are extremely close to those predicted by traditional CFD - provided the same turbulence model and computational grid are used consistently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of Thermal Scattering Law and Cross Sections of Hydrogen in Paraffin Wax

Paraffin wax is frequently used as a neutron moderator and shielding material. The main component of paraffin wax is straight-chain alkanes (n-alkanes). The deposition of paraffin wax is primarily attributed to the crystallization of n-alkanes. It is important to gain a deeper understanding of the mechanisms underlying the behavior of paraffin wax, which would impact the thermal scattering Law (TSL) and cross sections and affect the analysis of neutronic and critical systems. In this work, a classical molecular dynamics (CMD) simulation model was used in LAMMPS to create the TSL and cross sections at room temperature and pressure. To generate the required velocity autocorrelation functions (VACF), previously published data were used to validate the approach and models by comparing them with key model parameters. The phonon density of state (DOS) was calculated using Fourier transformation of the normalized VACF. This DOS was used as the primary input to estimate the TSL (S($a$, $β$)) and cross sections of hydrogen in paraffin wax. The TSL and cross sections of hydrogen were estimated using the Full Law Analysis Scattering System Hub (FLASSH) code. The cross section of hydrogen in paraffin wax is consistent with other hydrocarbon materials such as polyethylene with deviations due to structure in the lowest energy region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper II: Local Geometry and Metric Structure

This paper develops the geometric sector of the replication-driven cosmogenesis framework introduced in Paper I. Starting from a pre-geometric spectral substrate and a minimal set of replication axioms, we show how coherent self-replicating units generate a spatial adjacency graph whose continuum limit acquires an effective Riemannian structure. The replication dynamics determines a characteristic correlation length that seeds the local metric, while overlap relations among coherent units produce an isotropic neighborhood geometry with an emergent dimensionality $d_{\rm eff}\simeq 3$ across a broad range of replication factors. As replication slows and causal order stabilizes, a limiting signal speed $c_\ast$ appears, providing the basis for the Lorentzian structure of spacetime without assuming a pre-existing light cone. We derive conditions under which the adjacency graph converges to a smooth three-dimensional manifold, describe the transition from Euclidean to Lorentzian propagation, and identify geometric invariants controlled by the replication parameters. This work establishes the geometric and causal layer of the replication cosmogenesis program, bridging the spectral axioms of Paper I to the cosmological dynamics explored in Paper III.

79 ASTRONOMY AND ASTROPHYSICS↗

Single-particle dynamics in a nonlinear accelerator lattice: attaining a large tune spread with octupoles in IOTA

Fermilab is constructing the Integrable Optics Test Accelerator (IOTA) as the centerpiece of the Accelerator R&D Program towards high-intensity circular machines. One of the factors limiting the beam intensity in present circular accelerators is collective instabilities, which can be suppressed by a spread of betatron frequencies (tunes) through the Landau damping mechanism or by an external damper, if the instability is slow enough. The spread is usually created by octupole magnets, which introduce the tune dependence on the amplitude and, in some cases, by a chromatic spread (tune dependence on particle's momentum). The introduction of octupoles usually lead to a resonant behavior and a reduction of the dynamic aperture. One of the goals of the IOTA research program is to achieve a high betatron tune spread, while retaining a large dynamic aperture using conventional octupole magnets in a special but realistic accelerator configuration. In this report, we present results of computer simulations of an electron beam in the IOTA by particle tracking and the Frequency Map Analysis. The results show that the ring's octupole magnets can be configured to provide a betatron tune shift of 0.08 (for particles at large amplitudes) with the dynamical aperture of over 20 beam sigma for a 150-MeV electron beam. The influence of the synchrotron motion, lattice errors, and magnet imperfections is insignificant for the parameters and levels of tolerances set by the design of the ring. Here, the described octupole insert could be beneficial for suppression of space-charge induced instabilities in high intensity machines.

43 PARTICLE ACCELERATORS↗