Recurrent geomagnetic phenomena and solar centers <phenomenes geomagnetiques recurrents et centres solaires<
Recurrent geomagnetic storms effected by solar activity centers having emitted type IV radio bursts
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Recurrence in truncated Boussinesq models for nonlinear waves in shallow water
The rapid spatial recurrence of weakly nonlinear and weakly dispersive progressive shallow-water waves is examined using a numerical integration technique on the discretized and truncated form of the Boussinesq equations. This study primarily examines recurrence in wave fields with Ursell number O(1) and characterizes the sensitivity of recurrence to initial spectral shape and number of allowed frequency modes. It is shown that the rapid spatial recurrence is not an inherent property of the considered Boussinesq systems for evolution distances of 10-50 wavelengths. The main result of the study is that highly truncated Boussinesq models of resonant shallow-water ocean surface gravity waves predict rapid multiple recurrence cycles, but that this is an artifact dependent on the number of allowed modes. For initial conditions consisting of essentially all energy concentrated in a single mode, damping of the recurrence cycles increases as the number of low-power background modes increases. When more than 32 modes are allowed, the recurrence behavior is relatively insensitive to the number of allowed modes.
Elgar, Steve↗
IUE observations of galactic and extragalactic recurrent novae
A collection of International Ultraviolet Explorer (IUE) light curves and sample spectra for the galactic recurrent novae observed in the ultraviolet are presented. These data are compared to that of the Nova LMC (Large Magellanic Cloud) 1990 number 2 which is shown to also be a recurrent novae. Based on the analysis of the outburst of N LMC 1990 number 2 it is suggested that all of the recurrent novae observed in the ultraviolet have luminosities at maximum light which exceed the Eddington limit. V745 Sco and RS Oph, the two recurrent novae with late type giant companions, show strong Mg II throughout the outburst. Those with low luminosity companions, U Sco and V394 CrA do not show Mg II but do show strong He II 1640 earlier in the outburst. Typical emission line velocities are greater than those observed in many of the classical novae. These characteristics suggest that the white dwarfs in recurrent novae systems are close to the Chandrasekhar limit.
Shore, Steven N.↗
Earthquake recurrence on the southern San Andreas modulated by fault-normal stress
Earthquake recurrence data from the Pallett Creek and Wrightwood paleoseismic sites on the San Andreas fault appear to show temporal variations in repeat interval. We investigate the interaction between strike-slip faults and auxiliary reverse and normal faults as a physical mechanism capable of producing such variations. Under the assumption that fault strength is a function of fault-normal stress (e.g. Byerlee's Law), failure of an auxiliary fault modifies the strength of the strike-slip fault, thereby modulating the recurrence interval for earthquakes. In our finite element model, auxiliary faults are driven by stress accumulation near restraining and releasing bends of a strike-slip fault. Earthquakes occur when fault strength is exceeded and are incorporated as a stress drop which is dependent on fault-normal stress. The model is driven by a velocity boundary condition over many earthquake cycles. Resulting synthetic strike-slip earthquake recurrence data display temporal variations similar to observed paleoseismic data within time windows surrounding auxiliary fault failures. Our simple model supports the idea that interaction between a strike-slip fault and auxiliary reverse or normal faults can modulate the recurrence interval of events on the strike-slip fault, possibly producing short term variations in earthquake recurrence interval.
Palmer, Randy↗
Flight Trajectory Prediction Based on Hybrid-Recurrent Networks
The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing the limited available spectrum for communications among aircraft and ground systems. Emerging approaches to autonomous allocation of aviation spectrum mostlyrely on machine learning techniques, where 4D (longitude, latitude, altitude, time) trajectory prediction is an important data input to enable real-time resource allocation. This study explores and evaluates effective data sources and deep recurrent neural network techniques when determining flight trajectories. Specifically, data are collected and evaluated in a 100-day and 14-day period. Sources of data include NASA Sherlock Data Warehouse, MIT Lincoln Labs Corridor Integrated Weather Service (CIWS), and assorted NOAA weather datasets. Deep learning models for 4D predictions all utilize a hybrid-recurrent technique. A baseline model is considered via the convolutional-LSTM design from the existing literature. The modified design considers Gated Recurrent Units (GRU), Independently Recurrent Neural Networks (IndRNN), and stand-alone self-attention layers. Results indicatethe effectiveness of LSTM and GRUcells for state-of-the-art data processing (interpolation). Additionally, GRUs may be quickly trained with limited data, allowing for exacting improvements with optimizer selection. Attention mechanisms provide notable performance improvements to convolutional layers and may extend dimensional capabilities of a learning model. Finally, NOAA measurements provide only a supplemental value, requiring support from tailored measurements for Air Traffic Management.
Nathan Schimpf↗
The recurrent nature of type 1 noise active regions during 1965 through 1969
The recurrent tendency of type I noise sources in metric frequencies is studied during the period from 1965 to 1969. It is shown that their recurrent period is slightly longer than 27.0 days and that the number of such recurrent trends for those noise sources is generally four. Discussion is given on the close relationship between those sources and the active regions where proton flares occur.
Sakurai, K.↗
Symbolic computation of recurrence equations for the Chebyshev series solution of linear ODE's
If a linear ordinary differential equation with polynomial coefficients is converted into integrated form then the formal substitution of a Chebyshev series leads to recurrence equations defining the Chebyshev coefficients of the solution function. An explicit formula is presented for the polynomial coefficients of the integrated form in terms of the polynomial coefficients of the differential form. The symmetries arising from multiplication and integration of Chebyshev polynomials are exploited in deriving a general recurrence equation from which can be derived all of the linear equations defining the Chebyshev coefficients. Procedures for deriving the general recurrence equation are specified in a precise algorithmic notation suitable for translation into any of the languages for symbolic computation. The method is algebraic and it can therefore be applied to differential equations containing indeterminates.
Geddes, K. O.↗
Gamma-ray burster recurrence time scales
In the decade since gamma-ray bursters (GRBs) were discovered by Klebesadel et al. (1973), many models have been proposed to explain the GRB phenomenon. A difficulty is related to the small number of predictions which would make it possible to evaluate the models. One verifiable prediction is the recurrence time scale, tau-gamma. One method to measure tau-gamma is to look for possible cases of recurrence as indicated by overlapping error boxes. The analysis considered in the present investigation is composed of three procedures. One of these involves a search through known error regions for cases where the error regions overlap. In addition, the number of overlaps expected by chance coincidence alone has been determined, and a calculation has been performed regarding the number of overlaps which are expected due to recurrence for various assumed tau-gamma and luminosity functions.
Schaefer, B. E.↗
The Nazca-South American convergence rate and the recurrence of the great 1960 Chilean earthquake
The seismic slip rate along the Chile Trench estimated from the slip in the great 1960 earthquake and the recurrence history of major earthquakes has been interpreted as consistent with the subduction rate of the Nazca plate beneath South America. The convergence rate, estimated from global relative plate motion models, depends significantly on closure of the Nazca - Antarctica - South America circuit. NUVEL-1, a new plate motion model which incorporates recently determined spreading rates on the Chile Rise, shows that the average convergence rate over the last three million years is slower than previously estimated. If this time-averaged convergence rate provides an appropriate upper bound for the seismic slip rate, either the characteristic Chilean subduction earthquake is smaller than the 1960 event, the average recurrence interval is greater than observed in the last 400 years, or both. These observations bear out the nonuniformity of plate motions on various time scales, the variability in characteristic subduction zone earthquake size, and the limitations of recurrence time estimates.
Stein, S.↗
Observations and simulations of recurrent novae: U Sco and V394 CrA
Observations and analysis of the Aug. 1987 outburst of the recurrent nova V394 CrA are presented. This nova is extremely fast and its outburst characteristics closely resemble those of the recurrent nova U Sco. Hydrodynamic simulations of the outbursts of recurrent novae were performed. Results as applied to the outbursts of V394 CrA and U Sco are summarized.
Starrfield, S.↗
Coalescence of recurrent streams of different sizes and amplitudes
Two corotating streams per solar rotation, separated by the heliospheric plasma sheet, were observed at 1 AU during 1974, and the streams recurred four times during the interval from day 145 to day 255. A single compound stream per solar rotation was observed at 5.5 - 6.0 AU during the corresponding interval from day 165 to day 275, indicating that the two recurrent streams observed at 1 AU coalesced between 1 AU and 6 AU. The average maximum speed of one of the recurrent streams was 805 km/s while that of the other recurrent stream was 705 km/s. The compound stream was not formed by the overtaking of the slow stream by the fast stream. Rather, it was probably formed by a process involving both filtering (due to the fact that the slow stream was 50 percent wider than the fast stream) and a geometrical effect.
Burlaga, L. F.↗
Parameter estimation in space systems using recurrent neural networks
The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.
Parlos, Alexander G.↗
Core reactivity estimation in space reactors using recurrent dynamic networks
A recurrent multilayer perceptron network topology is used in the identification of nonlinear dynamic systems from only the input/output measurements. The identification is performed in the discrete time domain, with the learning algorithm being a modified form of the back propagation (BP) rule. The recurrent dynamic network (RDN) developed is applied for the total core reactivity prediction of a spacecraft reactor from only neutronic power level measurements. Results indicate that the RDN can reproduce the nonlinear response of the reactor while keeping the number of nodes roughly equal to the relative order of the system. As accuracy requirements are increased, the number of required nodes also increases, however, the order of the RDN necessary to obtain such results is still in the same order of magnitude as the order of the mathematical model of the system. It is believed that use of the recurrent MLP structure with a variety of different learning algorithms may prove useful in utilizing artificial neural networks for recognition, classification, and prediction of dynamic systems.
Parlos, Alexander G.↗
Recurrent novae
Recurrent novae seem to be a rather inhomogeneous group: T CrB is a binary with a M III companion; U Sco probably has a late dwarf as companion. Three are fast novae; two are slow novae. Some of them appear to have normal chemical composition; others may present He and CNO excess. Some present a mass-loss that is lower by two orders of magnitude than classical novae. However, our sample is too small for saying whether there are several classes of recurrent novae, which may be related to the various classes of classical novae, or whether the low mass-loss is a general property of the class or just a peculiarity of one member of the larger class of classical novae and recurrent novae.
Hack, Margherita↗
Recurrence times and periodicities in 4U 1608-52 as observed by Vela 5B
We report on the Vela 5B 10 year history of the soft X-ray transient 4U 1608-52, and on the characteristics of its soft X-ray outbursts. The Vela 5B satellite observed the four known outbursts in 1975, 1977, and 1979, and four new outbursts in 1970 and 1971, altering the recurrence pattern of outbursts from this source. One of the 1970 outbursts is symmetric in its intensity profile, while the two outbursts in 1971 have short exponential profiles separated by 80 days. Despite suggestive recurrence periods of approximately 85 and approximately 150 days evident in the time intervals between the outbursts, there is no single statistically significant recurrence time on which the outbursts recur consistently. In the 1970 symmetric event, there is evidence for a period of either 4.10 or 5.19 days. Drawing upon the analogy with SU Ursa Majoris dwarf novae, we suggest that the short period is orbital and any longer period would be associated with a precession period of the accretion disk.
Lochner, James C.↗
Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network
The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis
Yao, Weigang↗
Recurrence Rate and Magma Effusion Rate for the Latest Volcanism on Arsia Mons, Mars
Magmatism and volcanism have evolved the Martian lithosphere, surface, and climate throughout the history of Mars. Constraining the rates of magma generation and timing of volcanism on the surface clarifies the ways in which magma and volcanic activity have shaped these Martian systems. The ages of lava flows on other planets are often estimated using impact crater counts, assuming that the number and size-distribution of impact craters per unit area reflect the time the lava flow has been on the surface and exposed to potential impacts. Here we show that impact crater age model uncertainty is reduced by adding stratigraphic information observed at locations where neighboring lavas abut each other, and demonstrate the significance of this reduction in age uncertainty for understanding the history of a volcanic field comprising 29 vents in the 110-kilometer-diameter caldera of Arsia Mons, Mars. Each vent within this caldera produced lava flows several to tens of kilometers in length; these vents are likely among the youngest on Mars, since no impact craters in their lava flows are larger than 1 kilometer in diameter. First, we modeled the age of each vent with impact crater counts performed on their corresponding lava flows and found very large age uncertainties for the ages of individual vents, often spanning the estimated age for the entire volcanic field. The age model derived from impact crater counts alone is broad and unimodal, with estimated peak activity in the field around 130Ma (megaannum, 1 million years). Next we applied our volcano event age model (VEAM), which uses a directed graph of stratigraphic relationships and random sampling of the impact crater age determinations to create alternative age models. Monte Carlo simulation was used to create 10,000 possible vent age sets. The recurrence rate of volcanism is calculated for each possible age set, and these rates are combined to calculate the median recurrence rate of all simulations. Applying this approach to the 29 volcanic vents, volcanism likely began around 200-300Ma then first peaked around 150Ma, with an average production rate of 0.4 vents per Myr (million years). The recurrence rate estimated including stratigraphic data is distinctly bimodal, with a second, lower peak in activity around 100Ma. Volcanism then waned until the final vents were produced 10-90Ma. Based on this model, volume flux is also bimodal, reached a peak rate of 1-8 cubic kilometers per million years by 150Ma and remained above half this rate until about 90Ma, after which the volume flux diminished greatly. The onset of effusive volcanism from 200-150Ma might be due to a transition of volcanic style away from explosive volcanism that emplaced tephra on the western flank of Arsia Mons, while the waning of volcanism after the 150Ma peak might represent a larger-scale diminishing of volcanic activity at Arsia Mons related to the emplacement of flank apron lavas.
Richardson, Jacob A.↗
M31N 2008-12a-The Remarkable Recurrent Nova in M31-Panchromatic Observations of the 2015 Eruption
The Andromeda Galaxy recurrent nova M31N 2008-12a had been observed in eruption 10 times, including yearly eruptions from 2008 to 2014. With a measured recurrence period of Prec = 351+/-13 days (we believe the true value to be half of this) and a white dwarf very close to the Chandrasekhar limit, M31N 2008-12a has become the leading pre-explosion supernova type Ia progenitor candidate. Following multi-wavelength follow-up observations of the 2013 and 2014 eruptions, we initiated a campaign to ensure early detection of the predicted 2015 eruption, which triggered ambitious ground- and space-based follow-up programs. In this paper we present the 2015 detection, visible to near-infrared photometry and visible spectroscopy, and ultraviolet and X-ray observations from the Swift observatory. The LCOGT 2 m (Hawaii) discovered the 2015 eruption, estimated to have commenced at August 28.28 +/- 0.12 UT. The 2013-2015 eruptions are remarkably similar at all wavelengths. New early spectroscopic observations reveal short-lived emission from material with velocities approx. 13,000 km/s, possibly collimated outflows. Photometric and spectroscopic observations of the eruption provide strong evidence supporting a red giant donor. An apparently stochastic variability during the early supersoft X-ray phase was comparable in amplitude and duration to past eruptions, but the 2013 and 2015 eruptions show evidence of a brief flux dip during this phase. The multi-eruption Swift/XRT spectra show tentative evidence of high-ionization emission lines above a high-temperature continuum. Following Henze et al. (2015a), the updated recurrence period based on all known eruptions is Prec 174 +/- 10 days, and we expect the next eruption of M31N 2008-12a to occur around 2016 mid-September.
cataclysmic variables – stars: individual (M31N ↗