Short Data Samples Research Articles

Optimization of ITER Nb3Sn CICCs for coupling loss, transverse electromagnetic load and axial thermal contraction

The ITER cable-in-conduit conductors (CICCs) are built up from sub-cable bundles, wound indifferent stages, which are twisted to counter coupling loss caused by time-changingexternal magnet fields. The selection of the twist pitch lengths has major implications forthe performance of the cable in the case of strain-sensitive superconductors, i.e. Nb3Sn, as the electromagnetic and thermal contraction loads are large but also for theheat load from the AC coupling loss. At present, this is a great challenge for theITER central solenoid (CS) CICCs and the solution presented here could be abreakthrough for not only the ITER CS but also for CICC applications in general.After proposing longer twist pitches in 2006 and successful confirmation by shortsample tests later on, the ITER toroidal field (TF) conductor cable pattern wasimproved accordingly. As the restrictions for coupling loss are more demandingfor the CS conductors than for the TF conductors, it was believed that longerpitches would not be applicable for the conductors in the CS coils. In this paper weexplain how, with the use of the TEMLOP model and the newly developed modelsJackPot-ACDC and CORD, the design of a CICC can be improved appreciably,particularly for the CS conductor layout. For the first time a large improvement ispredicted not only providing very low sensitivity to electromagnetic load and thermalaxial cable stress variations but at the same time much lower AC coupling loss.Reduction of the transverse load and warm-up–cool-down degradation can be reached byapplying longer twist pitches in a particular sequence for the sub-stages, offering a largecable transverse stiffness, adequate axial flexibility and maximum allowed lateral strandsupport. Analysis of short sample (TF conductor) data reveals that increasing the twistpitch can lead to a gain of the effective axial compressive strain of more than 0.3% withpractically no degradation from bending. This is probably explained by the distinctdifference in mechanical response of the cable during axial contraction for short and longpitches. For short pitches periodic bending in different directions with relatively shortwavelength is imposed because of a lack of sufficient lateral restraint of radial pressure.This can lead to high bending strain and eventually buckling. Whereas for cables withlong twist pitches, the strands are only able to react as coherent bundles, beingtightly supported by the surrounding strands, providing sufficient lateral restraintof radial pressure in combination with enough slippage to avoid single strandbending along detrimental short wavelengths. Experimental evidence of goodperformance was already provided with the test of the long pitch TFPRO2-OST2,which is still until today, the best ITER-type cable to strand performance everwithout any cyclic load (electromagnetic and thermal contraction) degradation.For reduction of the coupling loss, specific choices of the cabling twist sequence are neededto minimize the area of linked strands and bundles that are coupled and form loops withthe applied changing magnetic field, instead of simply avoiding longer pitches. In additionwe recommend increasing the wrap coverage of the CS conductor from 50% to at least 70%.A larger wrap coverage fraction enhances the overall strand bundle lateral restraint.The long pitch design seems the best solution to optimize the ITER CSconductor within the given restrictions of the present coil design envelope,only allowing marginal changes. The models predict significant improvementagainst strain sensitivity and substantial decrease of the AC coupling loss inNb3Sn CICCs, but also for NbTi CICCs minimization of the coupling loss can obviously beachieved. Although the success of long pitches to transverse load degradation was alreadydemonstrated, the prediction of the elegant innovative combination with low coupling lossneeds to be validated by a short sample test.

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008.

Estimation of the functional dependence of time series for the class of regression functions partially covered by a finite ε-net

The problem of estimating the functional dependence of time series on the time index is considered in the case of short data sample. The uniform convergence of an empirical risk functional to a theoretical one is proved for the case where the parametric class of regression functions can be partially covered by a finite ?-net for some of its parameters. The functional dependence for the polynomial class of functions is estimated as an example.

Estimating functional dependences based on time series with the use of classes of regression functions of infinite capacity

The problem of estimating the functional dependence of time series on the time index is considered in the case of short data samples. It is proved that empirical risk functional uniformly converges to the theoretical one in the case where regression functions can be approximated by finite-degree polynomials. An example of estimating the functional dependence for a class of trigonometric functions is presented.

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008.

Eulerian laser Doppler vibrometry: Online blade damage identification on a multi-blade test rotor

Laser Doppler vibrometry enables the telemetry-free measurement of online turbomachinery blade vibration. Specifically, the Eulerian or fixed reference frame implementation of laser vibrometry provides a practical solution to the condition monitoring of rotating blades. The short data samples that are characteristic of this measurement approach do however negate the use of traditional frequency domain signal processing techniques. It is therefore necessary to employ techniques such as time domain analysis and non-harmonic Fourier analysis to obtain useful information from the blade vibration signatures. The latter analysis technique allows the calculation of phase angle trends which can be used as indicators of blade health deterioration, as has been shown in previous work for a single-blade rotor. This article presents the results from tests conducted on a five-blade axial-flow test rotor at different rotor speeds and measurement positions. With the aid of artificial neural networks, it is demonstrated that the parameters obtained from non-harmonic Fourier analysis and time domain signal processing on Eulerian laser Doppler vibrometry signals can successfully be used to identify and quantify blade damage from among healthy blades. It is also shown that the natural frequencies of individual blades can be approximated from the Eulerian signatures recorded during rotor run-up and run-down.

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008.

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008.

Applications of grey relational method to river environment quality evaluation in China

Grey relational method (GRM) has emerged in recent years as a new tool to deal with problems of small samples and insufficient information. Inexact data, short sample and incomplete hydrological data in water research are very commonly encountered. Statistical, fuzzy set and rough set theories have been applied to deal with uncertainty problems in hydrology. In this paper, we propose a new algorithm for grey relational degree and apply it to water environment quality evaluation of the Han Jiang River, one of the major branches of the Yangtze River in China. Our proposed method possesses some essential and desirable properties which ensure that translational properties of relational degree do not exist and it will give a more precise and finer grading of the overall water quality. Our empirical applications of GRM have demonstrated that GRM is a useful tool for analysis of inexact data, short sample and incomplete hydrological data.

Quench Tests and FEM Analysis of ${\rm Nb}_{3}{\rm Al}$ Rutherford Cables and Small Racetrack Magnets

In collaboration between NIMS and Fermilab, we have made copper stabilized Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al Rutherford cables, using Nb-matrixed and Ta-matrixed strands. First these cables were investigated at high current in low self field using a flux pump. Using these Rutherford cables, we built and tested small racetrack magnets. The magnet made with the Nb-matrixed strand showed the flux jump instability in low field. The small racetrack magnet wound with the Ta-matrixed Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al Rutherford cable was very stable at 4.5 K operation without any instability, as well as at 2.2 K operation. With the successful operation of the small racetrack magnet up to its short sample data, the feasibility of the Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al strand and its Rutherford cable for their application to high field magnets is established. The characteristics of Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al Rutherford cable is compared with that of the Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn Rutherford cable and the advantages of Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al Rutherford cable are discussed.

Quench Tests of ${\rm Nb}_{3}{\rm Al}$ Small Racetrack Magnets

Two Cu stabilized Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al strands, Fl (Nb matrix) and F3 (Ta matrix), fabricated at NIMS were wound into Rutherford cables at Fermilab in collaboration with NIMS. A small race-track magnet using Fl Rutherford cable, the first Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al dipole magnet in the world, was constructed and tested to full current at Fermilab. This magnet was tested extensively to full short sample data and its quench characteristics were studied and reported. The 3-D magnetic field calculation was done with ANSYS to find the peak field. The quench characteristics of the magnet are explained with the characteristics of the Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al strand and Rutherford cable. The small racetrack magnet built using Ta matrix F3 strand was constructed and will be tested in the near future. The advantages and disadvantages of these Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Al cables are briefly discussed.

Assessing the Credit Risk of CDOs Backed by Structured Finance Securities

The collateralized debt obligation (CDO) market grew strongly in the last several years thanks to a strong U.S. housing market, a low interest rate environment, abundant global excess liquidity, and a healthy U.S. economy. The growth slowed significantly in 2007 amidst an unprecedented housing market turnaround and the sudden performance deterioration of recent-vintage subprime residential mortgage-backed securities (RMBS). CDOs9 large exposure to these subprime RMBS brought them under intense scrutiny. The illiquidity, novelty, and complexity of CDOs made them easy targets of criticism. This paper describes the evolution of CDOs backed by structured finance securities (SF CDOs) and the analytical approaches used by Moody9s to rate SF CDOs. We show that SF CDOs have experienced substantial changes in the last eight years in terms of asset distribution and transaction structure. We find that this sector has been dominated by Aaa-rated securities (about 85% by dollar volume of issuance), which had not experienced any defaults and losses as of the end of 2006. Although recently issued SF CDOs are expected to perform poorly, not all SF CDOs are backed by subprime RMBS and CDO performance is expected to vary significantly across transactions. This paper also describes Moody9s methods for the modeling of four basic components—default probability, recovery rate, asset correlation, and prepayment rate—and the differences and similarities across different rating models for transactions with and without complex waterfalls. Additionally, we analyze the rationale of a number of structural features such as par haircuts on assets with low credit ratings and assets purchased at deep discounts in SF CDOs as well as additional stresses that are designed to protect SF CDO investors. Finally, we note that the changing distribution of CDO assets and the different credit cycles to which these assets have been subjected make it difficult to interpret the average statistics computed for the overall CDO sector during a short data sample period that covers only a part of the credit cycle for each asset type. <b>TOPICS:</b>CLOs, CDOs, and other structured credit, project finance, legal and regulatory issues for structured finance

Assessing the Credit Risk of CDOs Backed by Structured Finance Securities: Rating Analysts' Challenges and Solutions

The CDO market grew strongly in the last several years thanks to a strong U.S. housing market, a low interest rate environment, abundant global excess liquidity, and a healthy U.S. economy. The growth slowed significantly in 2007 amidst an unprecedented housing market turnaround and the sudden performance deterioration of recent-vintage subprime residential mortgages-backed securities (RMBS). CDOs' large exposure to these subprime RMBS brought them under intense scrutiny. The illiquidity, novelty, and complexity of CDOs made them easy targets of criticism. This paper describes the evolution of CDOs backed by structured finance securities (SF CDOs) and the analytical approaches used by Moody's to rate SF CDOs. We show that SF CDOs have experienced substantial changes in the last eight years in terms of asset distribution and transaction structure. We find that this sector has been dominated by AAA-rated securities (about 85% by dollar volume of issuance), which did not experience any defaults and losses as of the end of 2006. Although recently issued SF CDOs are expected to perform poorly, not all SF CDOs are backed by subprime RMBS and CDO performance is expected to vary significantly across transactions. This paper also describes Moody's methods for the modeling of four basic components - default probability, recovery rate, asset correlation, and prepayment rate - and the differences and similarities across different rating models for transactions with and without complex waterfalls. Additionally, we analyze the rationale of a number of structural features such as par haircuts on lowly rated assets and assets purchased at deep discount in SF CDOs and additional stresses that are designed to protect SF CDO investors. Finally, we note that the changing distribution of CDO assets and the different credit cycles to which these assets have been subjected make it difficult to interpret the average statistics computed for the overall CDO sector during a short data sample period that covers only a part of the credit cycle for each asset type.

The design and performance of a Bi-2223/Ag magnet cooled by a single-stagecryocooler

The design and fabrication of a split coil Bi-2223/Ag tape superconducting magnet cooledby a single-stage cryocooler is presented. The magnet consists of six double-woundpancakes impregnated by epoxy resin with inner diameter 50 mm and outer diameter98 mm. Critical currents of individual pancakes, double pancakes and the whole magnet aremeasured, calculated and discussed. The magnet’s performance was tested at liquid heliumand nitrogen temperatures as well as at solid nitrogen temperatures and cooled by anAL230 single-stage Gifford-McMahon cycle cryorefrigerator. The measured magnetcurrents are compared with those estimated by calculations using short sample data.

Field Dependence of the Critical Current and Its Relation to the Anisotropy of BSCCO Conductors and Coils

The design of HTS magnets is often based on the properties of a number of short samples that are presumed to be representative of the conductor to be used. Variability in conductor properties and inhomogeneity in the magnetic field distribution within the magnets, coupled with conductor anisotropy, provide a significant challenge to accurately predict the field dependence of the magnet critical current. This work is based on measured superconducting properties of Bi-2212 and Bi-2223 conductors at 4.2 K in parallel and perpendicular magnetic fields up to 33 T. Properties of double pancake units and stacks, from the same or similar conductor batches, are presented, based on measurements at self-field and in applied co-axial background magnetic fields up to 19 T. Modeling of this data is based on short sample properties in perpendicular field; the average grain misalignment is used as the parameter to quantify the anisotropy. Correlations and discrepancies between the measured data and models based on short sample data are discussed for Bi-2212 and Bi-2223 conductors.

Transient Thermal Characteristics of Cryocooler-Cooled HTS Coil for SMES

Thermal behavior of high-temperature super-conducting (HTS) coil is exceedingly different from that of low-temperature superconducting (LTS) coil. Therefore for the sake of the application of HTS coil to practical use, establishment of a new stability criterion for coil design becomes indispensable. In this study, a small-sized cryocooler-cooled HTS coil wound with Bi-2223/Ag tape was constructed and tested to evaluate the electromagnetic and thermal characteristics in the cryocooler-cooled HTS coil. We carried out experiments subjected to pulse current operation supposing SMES for power system stabilization. The simulation by a newly developed computer program based on the finite element method (FEM) agreed well with experimental results. In the computer program, short-sample data concerning the E-J characteristics, which depend on the orientation of applied magnetic field to the wide face of Bi-2223Ag tape, was adopted. By using the computer program, we also evaluate the thermal behavior of HTS coil graded according to the magnetic field distribution.

Comparison of AC Losses of HTS Pancake Winding With Single Tape and Multi-Stacked Tape

AC losses generated in the HTS winding differ from that of the short sample because each turn of winding is magnetically affected by adjacent turns. In this paper, we calculated the AC loss of HTS pancake windings. Numerical calculation was carried out to figure out the magnetic field in the windings. During the AC loss calculation of both windings, AC losses were obtained by using the short sample AC losses data. According to the results of calculation, loss calculation by using the short sample data of multi-stacked tape was more approached to winding loss than that by using the single tape data. To prove the effectiveness of the calculations, AC losses of windings was measured and compared. Finally the single phase HTS transformer with multi-stacked tape was constructed and tested.

Method of Analogs in Prediction of Short Time Series: An Expert-statistical Approach

Prediction of the time series from short data samples was considered. An expert-statistical approach based on specially designed methods for joint use of the subjective and objective data was proposed for handling this problem. Its solution relies on the scheme of expert-statistical processing called the analog method.

Direction of arrival estimation based on temporal and spatial processing using a direct data domain (D/sup 3/) approach

The purpose of this paper is to estimate the direction of arrival (DOA) of the signal of interest (SOI) in the presence of both coherent and noncoherent interferences and multipath components utilizing a combined temporal and spatial processing technique based on a direct data domain approach. The concept of cyclostationarity, which deals with the temporal information of the SOI, is used to extract signals having the same cycle frequency and null out the co-channel interferences and additive noise. Hence, the signal detection capability can be significantly increased over conventional filtering when the length of the data record is limited. The main contribution of the paper is that by combining temporal and spatial processing based on a direct data domain approach one can handle number of signals along with their various coherent and noncoherent multipaths and interferences which can exceed the number of antenna elements. Hence, this methodology may be advantageous over conventional spatial processing when the number of degrees of freedom can never exceed the number of antenna elements in the array. However, the number of multipaths and interferers at the same cycle frequency has to be less than approximately 66 % of the antenna elements. Since we do not form a covariance matrix of the data, this method is quite suitable for short data lengths or when the environment is quite dynamic. Hence, in the proposed algorithm, while the estimation of the cyclic array covariance matrix is avoided, we develop a new matrix form using extremely short data samples. As a result, the computational load in the proposed approach is relatively reduced and the robustness of the estimation of SOI is significantly improved when the number of available snapshots is extremely limited. Numerical results are presented to illustrate the efficiency and accuracy of this method.

Self-organising Modelling as a Part of Simulation Process

At present GMDH algorithms give us an explicit model description (equations, rules, patterns) of complex ill-defined systems in the case of very short and noisy data samples. Therefore this is a necessary supplement to simulation methodology. Self-organising modelling and in special the GMDH approach is suitable and valuable as a part of the whole simulation process, which is demonstrated in macroeconomic simulation. More than this the paper will give an overview about the sources of traditional GMDH and about further development of self-organising modelling which is implemented in KnowledgeMiner.