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Scalar excursions in large-eddy simulations
Here, the range of values of scalar fields in turbulent flows is bounded by their boundary values, for passive scalars, and by a combination of boundary values, reaction rates, phase changes, etc., for active scalars. The current investigation focuses on the local conservation of passive scalar concentration fields and the ability of the large-eddy simulation (LES) method to observe the boundedness of passive scalar concentrations. In practice, as a result of numerical artifacts, this fundamental constraint is often violated with scalars exhibiting unphysical excursions. The present study characterizes passive-scalar excursions in LES of a shear flow and examines methods for diagnosis and assesment of the problem. The analysis of scalar-excursion statistics provides support of the main hypothesis of the current study that unphysical scalar excursions in LES result from dispersive errors of the convection-term discretization where the subgrid-scale model (SGS) provides insufficient dissipation to produce a sufficiently smooth scalar field. In the LES runs three parameters are varied: the discretization of the convection terms, the SGS model, and grid resolution. Unphysical scalar excursions decrease as the order of accuracy of non-dissipative schemes is increased, but the improvement rate decreases with increasing order of accuracy. Two SGS models are examined, the stretched-vortex and a constant-coefficient Smagorinsky. Scalar excursions strongly depend on the SGS model. The excursions are significantly reduced when the characteristic SGS scale is set to double the grid spacing in runs with the stretched-vortex model. The maximum excursion and volume fraction of excursions outside boundary values show opposite trends with respect to resolution. The maximum unphysical excursions increase as resolution increases, whereas the volume fraction decreases. The reason for the increase in the maximum excursion is statistical and traceable to the number of grid points (sample size) which increases with resolution. In contrast, the volume fraction of unphysical excursions decreases with resolution because the SGS models explored perform better at higher grid resolution.
Artificial Neural Network Representation of Dynamic Criticality Excursion Experiment Data
This paper outlines time dependent considerations in applying the artificial neural network (ANN) paradigm to dynamic nuclear criticality excursion experiment data. The ANN amongst a variety of uses, can apply to function fitting of multiple input-multiple output data sets, pattern recognition, cluster analysis, and time series prediction. The ANN is a component of Machine Learning (ML) data analysis. The practical application of ML to criticality safety has been funded through the Y-12 Plant Directed Research and Demonstration (PDRD) program to support criticality safety and emergency planning efforts. The initial effort considered function fitting of criticality excursion data. Recent efforts successfully extended the ANN to criticality safety code validation. The initial ANN work applied to criticality excursions centered around multivariate function fitting of static (tabular) data taken from the French Consequences Radiologiques d'un Accident de Criticite (CRAC) and SILENE reactor campaigns. The former report (LeCorche) summarized important tabular data for the first 44 CRAC experiments. The initial ANN was trained to specific time-independent inputs, then applied to predict peak fission rate and total fissions for a wide variety of fissile solutions process conditions. This work extends that effort to apply the ANN paradigm to dynamic prediction of time-dependent criticality excursion experiment data. A dynamic criticality excursion in fissile solution represents a complex multiphysics phenomenon. Factors include among other things, coupled neutronic, multiphase fluid flow, temperature, pressure, acoustic shock, boiling heat transfer, reactivity feedback, and radiolytic gas considerations. There have been many efforts to model (over time) as coupled ordinary and (space) as partial differential equations (ODE, PDE). The ANN representation noted here does not rely on solving explicit ODE or PDEs. Rather the intent is to demonstrate that as a time series, the criticality excursion can be predicted by training specific ANN architectures to experimental input and output time series exclusively. The rationale for extending this work to the time-dependent regime is important in developing a 'criticality excursion emulator' solely on the basis of learning characteristics from experiment dynamic data. An emulator is different than a computer code simulator driven by the solution of ODEs and PDEs given select 'tuning parameters' that match outputs to experiments. A criticality excursion emulator, derived exclusively from an ANN or ML, could predict most likely excursion characteristics, trained from historic dynamic experiment data, presented with input values within the range of those experiments. The work noted shows that generic time-series ANN architectures can be satisfactorily applied to the prediction of dynamic, extremely chaotic criticality excursion power given an initial time dependent input series. In reality, an excursion emulator could be driven by user-supplied initial (t=0), time independent or constant values to generate time dependent outputs. Thus ongoing work includes developing a custom ANN such that initial dynamic conditions would be predicted. Those results then serve as inputs to a customized ANN architecture currently in development. (author)
Large isotopic variability at the micron-scale in ‘Shuram’ excursion carbonates from South Australia
Ediacaran-aged (635–541 million years ago) marine sediments contain a large negative carbon isotope (δ 13 C) excursion, in which carbonate δ 13 C values reach -12‰ (VPDB). Known as the ‘Shuram’ excursion, many workers have interpreted this δ 13 C record as an unprecedented perturbation to the global carbon cycle, leading to speculation about a causal connection to the broadly contemporaneous rise of animal life. Others have interpreted the δ 13 C signal as a product of diagenesis, thereby minimizing its relevance for understanding the evolution of metazoans. In this work, we present SEM imaging and in-situ δ 13 C and δ 18 C values measured by secondary ion mass spectrometry (SIMS) to assess these competing hypotheses in the Wonoka Formation of South Australia. Our results from the minimum of the excursion show that rounded sedimentary grains of calcite have δ 13 C values between -12.8 to -10.6‰ and δ 18 C values between 17.8 to 15.5‰ (VPDB). Euhedral dolomite that appears to have grown unimpeded in open sedimentary pore spaces also is present. These early-stage dolomites are interpreted as early authigenic in origin and have δ 13 C values that reach +5‰, requiring a formation fluid with a substantially different δ 13 C composition from basin waters or bulk sediment. Together, these results provide little evidence for the hypothesis that a late diagenetic overprint has generated the ‘Shuram’ excursion in the Wonoka. Instead, they suggest the presence of a large carbon isotopic gradient in the surface environment, with shallow waters capable of precipitating carbonates with very low δ 13 C (down to 12‰) and deeper shelf and/or marine pore waters generating carbonates with positive carbon isotope values (up to +5‰). Because negative isotope excursions of similar magnitude are found in widely dispersed Ediacaran basins, it is likely that this gradient was characteristic of shelf environments of this period and that a still-unknown global process led to the ‘Shuram’ excursion in shallow water carbonates.
Dynamic mitigation of EDFA power excursions with machine learning
Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. In conclusion, we also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm.
Excursion sets and non-Gaussian void statistics
Primordial non-Gaussianity (NG) affects the large scale structure (LSS) of the Universe by leaving an imprint on the distribution of matter at late times. Much attention has been focused on using the distribution of collapsed objects (i.e. dark matter halos and the galaxies and galaxy clusters that reside in them) to probe primordial NG. An equally interesting and complementary probe however is the abundance of extended underdense regions or voids in the LSS. The calculation of the abundance of voids using the excursion set formalism in the presence of primordial NG is subject to the same technical issues as the one for halos, which were discussed e.g. in Ref. [51][G. D'Amico, M. Musso, J. Norena, and A. Paranjape, arXiv:1005.1203.]. However, unlike the excursion set problem for halos which involved random walks in the presence of one barrier {delta}{sub c}, the void excursion set problem involves two barriers {delta}{sub v} and {delta}{sub c}. This leads to a new complication introduced by what is called the 'void-in-cloud' effect discussed in the literature, which is unique to the case of voids. We explore a path integral approach which allows us to carefully account for all these issues, leading to a rigorous derivation of the effects of primordial NG on void abundances. The void-in-cloud issue, in particular, makes the calculation conceptually rather different from the one for halos. However, we show that its final effect can be described by a simple yet accurate approximation. Our final void abundance function is valid on larger scales than the expressions of other authors, while being broadly in agreement with those expressions on smaller scales.
A new model for the dynamic of criticality excursions in fissile solutions - 14446
A recent international inter-code comparison exercise for criticality excursion analysis demonstrated that the transient criticality codes participating the exercise are showed to reproduce well the initial peak power compared with measurements performed with TRACY and SILENE reactors. However the oscillatory behavior after peak power is less well reproduced. The integrated behavior in term of energy release is quite well reproduced. The recent experiments performed with TRACY JAEA's reactor and the analytic interpretation of void clustering during prompt critical have suggested a simplified vibration model of a damped oscillator. Finally a recent ICNC paper by present authors offered a perfect correlation between peak pressure and peak power. Owing to these three facts the present paper aims at proposing a new system of equations for the dynamic of a critical excursion taking into account gas bubble generation after exceeding the solubility threshold of dissolved radiolytic gas. The model explains why the simple vibration model of the JAEA school fairly represent pressure dynamic records at moderate peak pressure as measured with SILENE reactor. Also, an important parameter of the proposed model, namely the rate of transfer from dissolved gas to gas bubbles, is fixed by the correlation between peak pressure and peak power. Thus the model has one less tunable parameter and can predict a large range of critical low pressure excursions. After presentation of the model and discussion of some of its important features, some numerical simulations are made based upon SILENE and TRACY transient experiments ranging from tenths of kPa to several bars and comparisons are presented between calculated results and experimentally recorded one's. (authors)
Excursion Processes Associated with Elliptic Combinatorics
Researching elliptic analogues for equalities and formulas is a new trend in enumerative combinatorics which has followed the previous trend of studying q-analogues. Recently Schlosser proposed a lattice path model in the square lattice with a family of totally elliptic weight-functions including several complex parameters and discussed an elliptic extension of the binomial theorem. In the present paper, we introduce a family of discrete-time excursion processes on ℤ starting from the origin and returning to the origin in a given time duration 2T associated with Schlosser’s elliptic combinatorics. The processes are inhomogeneous both in space and time and hence expected to provide new models in non-equilibrium statistical mechanics. By numerical calculation we show that the maximum likelihood trajectories on the spatio-temporal plane of the elliptic excursion processes and of their reduced trigonometric versions are not straight lines in general but are nontrivially curved depending on parameters. We analyze asymptotic probability laws in the long-term limit T→∞ for a simplified trigonometric version of excursion process. Emergence of nontrivial curves of trajectories in a large scale of space and time from the elementary elliptic weight-functions exhibits a new aspect of elliptic combinatorics.
Undulator Changes Due To Temperature Excursions
The temperature of the LCLS undulators has not been controlled during storage. The effects of the temperature excursions are documented in this note. After a number of LCLS undulators were tuned, fiducialized, and placed in storage anticipating their use, a test was made to ensure that their properties had not changed. The test revealed, however, that indeed the undulators had changed. Detailed study of this problem followed. We now believe that the gap of the undulators changes permanently when the undulators go through temperature excursions. We have tested the other possible cause, transportation, and do not see gap changes. In this note, we document how the undulators have changed since they were originally tuned. The undulators were tuned and fiducialized in the Magnetic Measurement Facility (MMF). Afterward, many of them (approximately 18) were taken to building 750 for storage during summer and fall 2007. Building 750 had no temperature control. The undulator temperatures went from 20 C, used for tuning, down to approximately 11 C during the winter. In January 2008, three of the undulators were brought back to the MMF for a check. All three undulators showed similar changes. Trajectories, phases, and most undulator properties stayed the same, but the fiducialization (beam axis position relative to tooling balls on the undulator) had changed. Further investigation showed that the undulator gap was altered in a periodic way along the magnetic axis with a net average gap change causing the fiducialization change. A new storage location in building 33 was found and future undulators were placed there. A failure in the temperature control, however, caused the undulators to get too hot. Again the gap changed, but with a different periodic pattern. This note documents the measured changes in the undulators. In particular, it shows the detailed history of undulator 39 which went through both negative and positive temperature excursions.
One and Two-Dimensional Excursion Modeling of GODIVA-IV and CALIBAN Using the MRKJ Code
A technique is described that presents how to perform 2-dimensional nuclear excursion simulations of GODIVA-IV and CALIBAN using the coupled neutronic-hydrodynamic method as part of the MRKJ code to study metal criticality excursions. The 2-D thermoelastic equations were incorporated into the MRKJ code to extend the physics and modeling effort into 2-D (cylindrical) geometry. By making some simplifying modeling assumptions, results were obtained for controlled prompt-critical excursions of GODIVA-IV and CALIBAN. These results will be compared later to legacy data and future measurements that are to be made with both critical assemblies as part of a joint collaboration between CEA/Valduc and US DOE/Los Alamos National Laboratory to improve computational tools to study metal criticality accidents.
Dark-matter halo assembly bias: Environmental dependence in the non-Markovian excursion-set theory
In the standard excursion-set model for the growth of structure, the statistical properties of halos are governed by the halo mass and are independent of the larger-scale environment in which the halos reside. Numerical simulations, however, have found the spatial distributions of halos to depend not only on their mass but also on the details of their assembly history and environment. Here we present a theoretical framework for incorporating this 'assembly bias' into the excursion-set model. Our derivations are based on modifications of the path-integral approach of Maggiore and Riotto that models halo formation as a non-Markovian random-walk process. The perturbed density field is assumed to evolve stochastically with the smoothing scale and exhibits correlated walks in the presence of a density barrier. We write down conditional probabilities for multiple barrier crossings and derive from them analytic expressions for descendant and progenitor halo mass functions and halo merger rates as a function of both halo mass and the linear overdensity δ {sub e} of the larger-scale environment of the halo. Our results predict a higher halo merger rate and higher progenitor halo mass function in regions of higher overdensity, consistent with the behavior seen in N-body simulations.
Statistics of dark matter halos in the excursion set peak framework
We derive approximated, yet very accurate analytical expressions for the abundance and clustering properties of dark matter halos in the excursion set peak framework; the latter relies on the standard excursion set approach, but also includes the effects of a realistic filtering of the density field, a mass-dependent threshold for collapse, and the prescription from peak theory that halos tend to form around density maxima. We find that our approximations work excellently for diverse power spectra, collapse thresholds and density filters. Moreover, when adopting a cold dark matter power spectra, a tophat filtering and a mass-dependent collapse threshold (supplemented with conceivable scatter), our approximated halo mass function and halo bias represent very well the outcomes of cosmological N-body simulations.
Power Excursion Mitigation for Flexgrid Defragmentation With Machine Learning
Flexgrid optical networking relies on spectrum defragmentation to groom channel wavelengths and improve spectral efficiency. Various defragmentation methods—hop, make-before-break, and sweep—interact with the power dynamics of erbium-doped fiber amplifiers (EDFA) differently and result in undesired power excursions that exacerbate the post-EDFA power variance. Here we present a machine learning engine that characterizes the channel dependence of power excursions from historical data. We further demonstrate that post-EDFA power variance during hop, make-before-break, and sweep defragmentation methods can be greatly mitigated by the trained machine learning engine with automated and expedited power adjustment predictions.
Validation of the U.S. NRC coupled code system TRITON/TRACE/PARCS with the special power excursion reactor test III (SPERT III)
The Special Power Excursion Reactor Test III (SPERT III) was a series of reactivity insertion experiments conducted in the 1950's. This paper describes the validation of the U.S. NRC Coupled Code system TRITON/PARCS/TRACE to simulate reactivity insertion accidents (RIA) by using several of the SPERT III tests. The work here used the SPERT III E-core configuration tests in which the RIA was initiated by ejecting a control rod. The resulting super-prompt reactivity excursion and negative reactivity feedback produced the familiar bell shaped power increase and decrease. The energy deposition during such a power peak has important safety consequences and provides validation basis for core coupled multi-physics codes. The transients of five separate tests are used to benchmark the PARCS/TRACE coupled code. The models were thoroughly validated using the original experiment documentation. (authors)
Predicting Thermal Excursions During in situ Oxidative Regeneration of Packed Bed Catalytic Fast Pyrolysis Catalyst
Ex situ catalytic fast pyrolysis (CFP) uses a secondary reactor to upgrade biomass pyrolysis vapors to stabilized CFP oils with reduced oxygen content. In one configuration, the secondary reactor is operated as a packed-bed swing reactor system which allows coke-deactivated beds to be decarbonized in situ while other beds remain online for vapor upgrading. In situ decarbonization must be done carefully to avoid irreversible deactivation and/or physical degradation of catalyst pellets. Given that packed bed reactors are well known to have poor heat transfer characteristics, this is a critical issue impacting scaleability and commercial viability of the technology. To predict thermal excursions during regeneration, finite element computational models have been built to assist in scaling up oxidative decarbonization of a Pt/TiO2 CFP catalyst (0.5 mm spheres) from a bench scale packed bed with 100 g of catalyst to a pilot scale packed bed with 2 kg of catalyst and internal cooling tubes. Based on transient measurements of outlet temperature and effluent CO2 concentration, and using an assumed coke profile and activation energy, this paper demonstrates that specific combinations of effective thermal conductivity and wall heat transfer coefficient can fit bench scale oxidative regeneration data equally well. For the upscaled 2 kg bed, four bench-scale “best fit” parameter pairs give different predictions for location and magnitude of thermal excursions, with the maximum computed bed temperature gradients ranging from 30 °C cm-1 to as high as 3000 °C cm-1. The larger the fraction of heat removal by conduction through the cooling tubes, the greater the differences between the parameter pairs. The modelling results presented in this paper cast doubt on the industrial viability of the proposed combination of catalyst, bed and regeneration process, and point to the need for alternate reactor designs. However, there is considerable uncertainly in some of the key model parameters. The reliability of model predictions can be increased by adding more temperature measurements at key bed locations, testing additional variations in process conditions, performing careful bed dissections to determine the true coke profile, and perhaps most importantly, directly measuring the effective thermal conductivity of the catalyst pellets.
Observable gravitational waves from inflation with small field excursions
The detection of primordial gravitational waves, or tensor perturbations, would be regarded as compelling evidence for inflation. The canonical measure of this is the ratio of tensor to scalar perturbations, r. For single-field slow-roll models of inflation with small field excursions, the Lyth bound dictates that if the evolution of the slow-roll parameter ε is monotonic, the tensor-to-scalar ratio must be below observationally detectable levels. We describe how non-monotonic evolution of ε can evade the Lyth bound and generate observationally large r, even with small field excursions. This has consequences for the scalar power spectrum as it necessarily predicts an enhancement in the spectrum at very small scales and significant scale-dependent running at CMB scales. This effect has not been appropriately accounted for in previous analyses. We describe a mechanism that will generically produce the required behaviour in ε and give an example of this mechanism arising in a well-motivated small-field model. This model can produce r ≥ 0.05 while satisfying all current observational constraints.
U–Pb Geochronology and Stable Isotope Geochemistry of Terrestrial Carbonates, Lower Cretaceous Cedar Mountain Formation, Utah: Implications for Synchronicity of Terrestrial and Marine Carbon Isotope Excursions
The terrestrial Lower Cretaceous Cedar Mountain Formation, Utah, is a critical archive of paleoclimate, tectonics, and vertebrate ecology and evolution. Early Cretaceous carbon cycle perturbations associated with ocean anoxia have been interpreted from this succession, as expressed in stable carbon isotopes. However, refining the timing of the observed stable isotope excursions remains a key challenge in understanding how marine anoxia affects the Earth system, and is ultimately recorded in the terrestrial realm. The geochronology and geochemistry of a terrestrial carbonate near the base of this succession, which potentially records the Ap7 global carbon isotope excursion, is studied here. Petrographic and geochemical analyses are used to test plausible mechanisms for U incorporation into the calcite lattice in this sample. Using these methods, the hypothesis that the incorporation of U was at or close to the timing of carbonate precipitation is evaluated. U–Pb geochronology of calcite indicates a plausible Early Cretaceous age. However, comparison of the new U–Pb ages of calcite with detrital zircon maximum depositional ages immediately beneath the studied sample indicates a disparity in the apparent sedimentation rates if both types of geochronologic information are interpreted as reflecting the timing of sediment deposition. The totality of data supports an early, and high-temperature, diagenetic timing of U incorporation, with potential for minor leaching of U in subsequent fluid–rock interaction. The most likely mechanism for U transport and immobilization in these samples is hydrothermal fluid–rock interaction. Therefore, the radiometric ages, and corresponding stable isotope composition of U-bearing carbonate domains in this sample, indicate early subsurface fluid–rock interactions and not a record of atmosphere–soil geochemical reactions.
Bound on largest r ∼< 0.1 from sub-Planckian excursions of inflaton
In this paper we will discuss the range of large tensor to scalar ratio, r, obtainable from a sub-Planckian excursion of a single, slow roll driven inflaton field. In order to obtain a large r for such a scenario one has to depart from a monotonic evolution of the slow roll parameters in such a way that one still satisfies all the current constraints of \texttt(Planck), such as the scalar amplitude, the tilt in the scalar power spectrum, running and running of the tilt close to the pivot scale. Since the slow roll parameters evolve non-monotonically, we will also consider the evolution of the power spectrum on the smallest scales, i.e. at P{sub s}(k ∼ 10{sup 16} Mpc{sup −1})∼< 10{sup −2}, to make sure that the amplitude does not become too large. All these constraints tend to keep the tensor to scalar ratio, r ∼< 0.1. We scan three different kinds of potential for supersymmetric flat directions and obtain the benchmark points which satisfy all the constraints. We also show that it is possible to go beyond r ∼> 0.1 provided we relax the upper bound on the power spectrum on the smallest scales.