451 research outputs found
Time Fractional Cable Equation And Applications in Neurophysiology
We propose an extension of the cable equation by introducing a Caputo time
fractional derivative. The fundamental solutions of the most common boundary
problems are derived analitically via Laplace Transform, and result be written
in terms of known special functions. This generalization could be useful to
describe anomalous diffusion phenomena with leakage as signal conduction in
spiny dendrites. The presented solutions are computed in Matlab and plotted.Comment: 10 figures. arXiv admin note: substantial text overlap with
arXiv:1702.0532
Firms in International Trade: Importers and Exporters Heterogeneity in the Italian Manufacturing Industry
This paper offers a portrait of Italian firms that trade goods. Combining data on firms' structural characteristics and economic performance with data on their exporting and importing activity, we uncover evidence supporting recent theories on firm heterogeneity and international trade, together with some new facts. In particular, we find that importing can be as important as exporting as a source of firm heterogeneity. First, we document that trade is more concentrated than employment and sales, and we show that import is even more concentrated than export both within sectors and along the sector and country extensive margins. Second, while supporting the fact that firms involved in both importing and exporting (two-way traders) are the best performers, we also find that firms involved only in importing activities perform better than those involved only in exporting. We submit that this may have to do with being mainly importers of high-tech capital goods. Third, the performance premia of internationalized firms correlate relatively more with the degree of geographical and sectoral diversification of imports.Heterogeneous firms; Exports; Imports
Resonance contributions to nucleon spin structure in Holographic QCD
We study polarized inelastic electron-nucleon scattering at low momentum
transfer, in the Witten-Sakai-Sugimoto model of holographic QCD. We focus in
particular on resonance production contributions to the nucleon spin structure
functions. Our analysis includes both spin and spin low-lying
nucleon resonances with positive and negative parity. We determine, in turn,
the helicity amplitudes for nucleon-resonance transitions and the resonance
contributions to the neutron and proton generalized spin polarizabilities.
Extrapolating the model parameters to realistic QCD data, our analysis,
triggered by recent experimental results from Jefferson Lab, agrees with the
observation that the resonance gives the dominant contribution
to the forward spin polarizabilities at low momentum transfer. The contribution
is negative and increases towards zero as the momentum transfer increases. As
expected, the contribution of the to the longitudinal-transverse
polarizabilities is instead negligible. Our analysis shows that different spin
resonances give different contributions, in sign and magnitude, to the
generalized longitudinal-transverse spin polarizabilities. In the proton case
they globally give rise to a positive function which decreases towards zero as
the momentum transfer increases. In the neutron case, the net effect produces a
negative increasing function. These features are in qualitative agreement with
experimental data.Comment: 43 pages, 17 figures, 2 table
Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement
The measurement of the rotational speed of rotating machinery is typically performed based on mechanical adherence; for example, in encoders. Nevertheless, it can be of interest in various types of applications to develop contactless vision-based methodologies to measure the speed of rotating machinery. In particular, contactless rotor speed measurement methods have several potential applications for wind turbine technology, in the context of non-intrusive condition monitoring approaches. The present study is devoted exactly to this problem: a ground level video-tachometer measurement technique and an image analysis algorithm for wind turbine rotor speed estimation are proposed. The methodology is based on the comparison between a reference frame and each frame of the video through the covariance matrix: a covariance time series is thus obtained, from which the rotational speed is estimated by passing to the frequency domain through the spectrogram. This procedure guarantees the robustness of the rotational speed estimation, despite the intrinsic non-stationarity of the system and the possible signal disturbances. The method is tested and discussed based on two experimental environments with different characteristics: the former is a small wind turbine model (with a 0.45 m rotor diameter) in the wind tunnel facility of the University of Perugia, whose critical aspect is the high rotational speed (up to the order of 1500 RPM). The latter test case is a wind turbine with a 44 m rotor diameter which is part of an industrial wind farm: in this case, the critical point regards the fact that measurements are acquired in uncontrolled conditions. It is shown that the method is robust enough to overcome the critical aspects of both test cases and to provide reliable rotational speed estimates
Multi-Scale Wind Turbine Bearings Supervision Techniques Using Industrial SCADA and Vibration Data
Timely damage diagnosis of wind turbine rolling elements is a keystone for improving
availability and eventually diminishing the cost of wind energy: from this point of view, it is a
priority to integrate high-level practices into the real-world operation and maintenance of wind
farms. On this basis, the present study is devoted to the formulation of reliable methodologies for the
supervision of wind turbine bearings, which possibly can be integrated in the industrial practice. For
this reason, this study is a collaboration between a company (ENGIE Italia), the University of Perugia
and the Politecnico di Torino. The analysis is based on the exploitation of the data types which are
available to wind farm managers from industrial control systems: SCADA (Supervisory Control
And Data Acquisition) and TCM (Turbine Condition Monitoring). Due to the intrinsic sampling
time difference between SCADA and TCM data (a few minutes the former, up to the millisecond for
the latter), the proposed methodology is designed as multi-scale. At first, historical SCADA data
are processed and the behavior of the oil filter pressure is analyzed for all the wind turbines in the
farm: this provides preliminary advice for identifying presumably healthy wind turbines from those
suspected of damage. A second step for the SCADA analysis is then represented by the study of the
temperature trends of the bearings through a Support Vector Regression: the incoming damage is
individuated from the analysis of the mismatch between measurements and estimates provided by
the normal behavior model. Finally, the healthy units are selected as the reference and the faulty as
the target for the analysis of TCM vibration data in the time domain: statistical features are computed
on independent chunks of the signals and, using a Novelty Index, it was possible to distinguish the
damaged wind turbines with respect to the reference ones. In light of the interest in application of
the proposed methodology, good practice criteria in selecting and managing the data are discussed
as well
Overconfidence in the art market: a bargaining pricing model with asymmetric disinformation
This paper develops a Nash bargaining model of price formation in the art market. Agents can be naĆÆve, if they are overconfident and either overestimate artistic quality or underestimate their uncertainty of artistic quality, or sophisticated, if they correctly use all the available information. Overconfidence turns out to have a positive impact on both the price and the average quality of the artworks traded in the market. The impact of overconfidence on expected quality is weaker than the corresponding price increase, so sellers overcharge buyers. In addition, the buyerās (sellerās) overconfidence has a positive (negative) impact on the likelihood of trade. If many pairs of agents may bargain simultaneously, we find that sellerās market power is negatively affected by the number of sellers and positively affected by the number of buyers. If sophisticated and naĆÆve buyers coexist, naĆÆve buyers exert a negative externality on the sophisticated ones, increasing the price the latter pay
Emergence of Fractional Kinetics in Spiny Dendrites
Fractional extensions of the cable equation have been proposed in the
literature to describe transmembrane potential in spiny dendrites. The
anomalous behavior has been related in the literature to the geometrical
properties of the system, in particular, the density of spines, by experiments,
computer simulations, and in comb-like models.~The same PDE can be related to
more than one stochastic process leading to anomalous diffusion behavior. The
time-fractional diffusion equation can be associated to a continuous time
random walk (CTRW) with power-law waiting time probability or to a special case
of the Erd\'ely-Kober fractional diffusion, described by the ggBm. In this
work, we show that time fractional generalization of the cable equation arises
naturally in the CTRW by considering a superposition of Markovian processes and
in a {\it ggBm-like} construction of the random variable.Comment: 8 page
A systems approach to analyze the robustness of infrastructure networks to complex spatial hazards
Ph. D. ThesisInfrastructure networks such as water supply systems, power networks, railway networks, and road networks provide essential services that underpin modern societyās health, wealth, security, and wellbeing. However, infrastructures are susceptible to damage and disruption caused by extreme weather events such as floods and windstorms. For instance, in 2007, extensive disruption was caused by floods affecting a number of electricity substations in the United Kingdom, resulting in an estimated damage of GBPĀ£3.18bn (US125bn (GBPĀ£99.35bn) in damage due to the resulting floods and high winds. The magnitude of these impacts is at risk of being compounded by the effects of Climate Change, which is projected to increase the frequency of extreme weather events. As a result, it is anticipated that an estimated US$3.7tn (GBPĀ£2.9tn) in investment will be required, per year, to meet the expected need between 2019 and 2035.
A key reason for the susceptibility of infrastructure networks to extreme weather events is the wide area that needs to be covered to provide essential services. For example, in the United Kingdom alone there are over 800,000 km of overhead electricity cables, suggesting that the footprint of infrastructure networks can be as extended as that of an entire Country. These networks possess different spatial structures and attributes, as a result of their evolution over long timeframes, and respond to damage and disruption in different and complex ways.
Existing approaches to understanding the impact of hazards on infrastructure networks typically either (i) use computationally expensive models, which are unable to support the investigation of enough events and scenarios to draw general insights, or (ii) use low complexity representations of hazards, with little or no consideration of their spatial properties. Consequently, this has limited the understanding of the relationship between spatial hazards, the spatial form and connectivity of infrastructure networks, and infrastructure reliability.
This thesis investigates these aspects through a systemic modelling approach, applied to a synthetic and a real case study, to evaluate the response of infrastructure networks to spatially complex hazards against a series of robustness metrics.
In the first case study, non-deterministic spatial hazards are generated by a fractal method which allows to control their spatial variability, resulting in spatial configurations that very closely resemble natural phenomena such as floods or windstorms. These hazards are then superimposed on a range of synthetic network layouts, which have spatial structures consistent
with real infrastructure networks reported in the literature. Failure of network components is initially determined as a function of hazard intensity, and cascading failure of further components is also investigated. The performance of different infrastructure configurations is captured by an array of metrics which cover different aspects of robustness, ranging from the proneness to partitioning to the ability to process flows in the face of disruptions.
Whereas analyses to date have largely adopted low complexity representations of hazards, this thesis shows that consideration of a high complexity representation which includes hazard spatial variability can reduce the robustness of the infrastructure network by nearly 40%. A āsmall-worldā network, in which each node is within a limited number of steps from any other node, is shown to be the most robust of all the modelled networks to the different structures of spatial hazard.
The second case study uses real data to assess the robustness of a power supply network operating in the Hull region in the United Kingdom, which is split in high and low voltage lines. The spatial hazard is represented by a high-resolution wind gust model and tested under current and future climate scenarios. The analysis reveals how the high and low voltage lines interact with each other in the event of faults, which lines would benefit the most from increased robustness, and which are most exposed to cascading failures. The second case study also reveals the importance of the spatial footprint of the hazard relative to the location of the infrastructure, and how particular hazard patterns can affect low voltage lines that are more often located in exposed areas at the edge of the network. The impact of Climate Change on windstorms is highly uncertain, although it could further reduce network robustness due to more severe events.
Overall the two case studies provide important insights for infrastructure designers, asset managers, the academic sector, and practitioners in general. In fact, in the first case study, this thesis defines important design principles, such as the adoption of a small-world network layout, that can integrate the traditional design drivers of demand, efficiency, and cost. In the second case study, this thesis lays out a methodology that can help identify assets requiring increased robustness and protection against cascading failures, resulting in more effective prioritized infrastructure investments and adaptation plans
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