Alternator and voltage regulator-exciter for a Brayton cycle space power system. Volume 2 - Unbalanced electromagnetic forces

Unbalanced electromagnetic forces in Brayton cycle turboalternator for space power syste

Local exact exchange potentials within the all-electron FLAPW method and a comparison with pseudopotential results

We present a general numerical approach to construct local Kohn-Sham potentials from orbital-dependent functionals within the all-electron full-potential linearized augmented-plane-wave (FLAPW) method, in which core and valence electrons are treated on an equal footing. As a practical example, we present a treatment of the orbital-dependent exact-exchange (EXX) energy and potential. A formulation in terms of a mixed product basis, which is constructed from products of LAPW basis functions, enables a solution of the optimized-effective-potential (OEP) equation with standard numerical algebraic tools and without shape approximations for the resulting potential. We find that the mixed product and LAPW basis sets must be properly balanced to obtain smooth and converged EXX potentials without spurious oscillations. The construction and convergence of the exchange potential is analyzed in detail for diamond. Our all-electron results for C, Si, SiC, Ge, GaAs semiconductors as well as Ne and Ar noble-gas solids are in very favorable agreement with plane-wave pseudopotential calculations. This confirms the adequacy of the pseudopotential approximation in the context of the EXX-OEP formalism and clarifies a previous contradiction between FLAPW and pseudopotential results.Comment: 12 pages, 7 figures, 5 table

Flexible operation of grid-interfacing converters in distribution networks : bottom-up solutions to voltage quality enhancement

Due to the emerging application of distributed generation (DG), large numbers of DG systems are expected to deliver electricity into the distribution network in the near future. For the most part these systems are not ready for riding through grid disturbances and cannot mitigate unwanted influences on the grid. On the one hand, with the increasing use of sensitive and critical equipment by customers, the electricity network is required to serve high voltage quality. On the other hand, more and more unbalanced and nonlinear equipment, including DG units, is negatively affecting the power quality of distribution networks. To adapt to the future distribution network, the tendency for grid-interfacing converters will be to integrate voltage quality enhancement with DG functionality. In this thesis, the flexible operation of grid-interfacing converters in distribution networks is investigated for the purpose of voltage quality enhancement at both the grid and user sides. The research is carried out in a bottom-up fashion, from the low-level power electronics control, through the realization of individual system functionality, finally arriving at system-level concepts and implementation. Being essential to the control of grid-interfacing converters, both stationaryframe techniques for voltage detection and synchronization in disturbed grids, and asymmetrical current regulation are investigated. Firstly, a group of high performance filters for the detection of fundamental symmetrical sequences and harmonics under various grid conditions is proposed. The robustness of the proposed filters to small grid-frequency variation and their adaptability to large frequency change are discussed. Secondly, multiple reference frame current regulation is explored for dealing with unbalanced grid conditions. As a complement to the existing proportional resonant (PR) controllers, sequence-decoupled resonant (SDR) controllers are proposed for regulating individual symmetric sequences. Based on the modeling of a four-leg grid-connected system in different reference frames, three types of controllers, i.e. PI, PR, and proportional plus SDR controllers are compared. Grid-interactive control of distributed power generation, i.e. voltage unbalance compensation, grid-fault ride-through control and flexible power transfer, as well as the modeling of harmonic interaction, are all investigated. The in-depth study and analysis of these grid interactions show the grid-support possibilities and potential negative impact on the grid of inverter-based DG units, beyond their primary goal of power delivery. In order to achieve a co-operative voltage unbalance compensation based on distributed DG systems, two control schemes, namely voltage unbalance factor based control and negative-sequence admittance control, are proposed. The negativesequence voltages at the grid connection point can be compensated and mitigated by regulating the negative-sequence currents flowing between the grid and DG converters. Flexible active and reactive power control during unbalanced voltage dips is proposed that enables DG systems to enhance grid-fault ride-through capability and to adapt to various requirements for grid voltage support. By changing adaptable weighting factors, the compensation of oscillating power and the regulation of grid currents can be easily implemented. Two joint strategies for the simultaneous control of active and reactive power are derived, which maintain the adaptive controllability that can cope with multiple constraints in practical applications. The contribution of zero-sequence currents to active power control is also analyzed as a complement to the proposed control, which is based on positive- and negative-sequence components. Harmonic interaction between DG inverters and the grid is modeled and analyzed with an impedance-based approach. In order to mitigate the harmonic distortion in a polluted grid, it is proposed to specify output impedance limits as a design constraint for DG inverters. Results obtained from modeling, analysis, and simulations of a distribution network with aggregated DG inverters, show that the proposed method is a simple and effective way for estimating harmonic quasi-resonance problems. By integrating these proposed control strategies in a modified conventional series-parallel structure, we arrived at a group of grid-interfacing system topologies that is suitable for DG applications, voltage quality improvement, and flexible power transfer. A concrete laboratory system details the proposed concepts and specifies the practical problems related to control design. The introduction of multi-level control objectives illustrates that the proposed system can ride through voltage disturbances, can enhance the grid locally, and can continue the power transfer to and from the grid while high voltage quality is maintained for the local loads within the system module. A dual-converter laboratory set-up was built, with which the proposed concepts and practical implementation have been fully demonstrated

Lightning Prediction for Space Launch Using Machine Learning Based Off of Electric Field Mills and Lightning Detection and Ranging Data

Kennedy Space Center and Cape Canaveral Air Station, FL, where the Air Force conducts space launches, are in an area of frequent lightning strikes, which is main obstacle in meeting launch goals. The 45th Weather Squadron (45th WS) ensures that any weather safety requirements are met during pre-launch and actual space launch. Using only summer months from three years’ worth of lightning detection and ranging (LDAR) and electric field mill (EFM) data from KSC, several feedforward neural networks are constructed. Separate models are built for each EFM and trained by adjusting parameters to forecast lightning 30 minutes out in the surrounding area of each field mill

Universal quantum behaviors of interacting fermions in 1D traps: from few particles to the trap thermodynamic limit

We investigate the ground-state properties of trapped fermion systems described by the Hubbard model with an external confining potential. We discuss the universal behaviors of systems in different regimes: from few particles, i.e. in dilute regime, to the trap thermodynamic limit. The asymptotic trap-size (TS) dependence in the dilute regime (increasing the trap size l keeping the particle number N fixed) is described by a universal TS scaling controlled by the dilute fixed point associated with the metal-to-vacuum quantum transition. This scaling behavior is numerically checked by DMRG simulations of the one-dimensional (1D) Hubbard model. In particular, the particle density and its correlations show crossovers among different regimes: for strongly repulsive interactions they approach those of a spinless Fermi gas, for weak interactions those of a free Fermi gas, and for strongly attractive interactions they match those of a gas of hard-core bosonic molecules. The large-N behavior of systems at fixed N/l corresponds to a 1D trap thermodynamic limit. We address issues related to the accuracy of the local density approximation (LDA). We show that the particle density approaches its LDA in the large-l limit. When the trapped system is in the metallic phase, corrections at finite l are O(l^{-1}) and oscillating around the center of the trap. They become significantly larger at the boundary of the fermion cloud, where they get suppressed as O(l^{-1/3}) only. This anomalous behavior arises from the nontrivial scaling at the metal-to-vacuum transition occurring at the boundaries of the fermion cloud.Comment: 20 page

Delving into Semantic Scale Imbalance

Model bias triggered by long-tailed data has been widely studied. However, measure based on the number of samples cannot explicate three phenomena simultaneously: (1) Given enough data, the classification performance gain is marginal with additional samples. (2) Classification performance decays precipitously as the number of training samples decreases when there is insufficient data. (3) Model trained on sample-balanced datasets still has different biases for different classes. In this work, we define and quantify the semantic scale of classes, which is used to measure the feature diversity of classes. It is exciting to find experimentally that there is a marginal effect of semantic scale, which perfectly describes the first two phenomena. Further, the quantitative measurement of semantic scale imbalance is proposed, which can accurately reflect model bias on multiple datasets, even on sample-balanced data, revealing a novel perspective for the study of class imbalance. Due to the prevalence of semantic scale imbalance, we propose semantic-scale-balanced learning, including a general loss improvement scheme and a dynamic re-weighting training framework that overcomes the challenge of calculating semantic scales in real-time during iterations. Comprehensive experiments show that dynamic semantic-scale-balanced learning consistently enables the model to perform superiorly on large-scale long-tailed and non-long-tailed natural and medical datasets, which is a good starting point for mitigating the prevalent but unnoticed model bias.Comment: 47 pages, 26 figures, 12 tables, Published as a conference paper at ICLR 202

Semi-Supervised Learning for Mars Imagery Classification and Segmentation

With the progress of Mars exploration, numerous Mars image data are collected and need to be analyzed. However, due to the imbalance and distortion of Martian data, the performance of existing computer vision models is unsatisfactory. In this paper, we introduce a semi-supervised framework for machine vision on Mars and try to resolve two specific tasks: classification and segmentation. Contrastive learning is a powerful representation learning technique. However, there is too much information overlap between Martian data samples, leading to a contradiction between contrastive learning and Martian data. Our key idea is to reconcile this contradiction with the help of annotations and further take advantage of unlabeled data to improve performance. For classification, we propose to ignore inner-class pairs on labeled data as well as neglect negative pairs on unlabeled data, forming supervised inter-class contrastive learning and unsupervised similarity learning. For segmentation, we extend supervised inter-class contrastive learning into an element-wise mode and use online pseudo labels for supervision on unlabeled areas. Experimental results show that our learning strategies can improve the classification and segmentation models by a large margin and outperform state-of-the-art approaches.Comment: Accepted by ACM Trans. on Multimedia Computing Communications and Applications (TOMM

Statistical methods and applications to animal breeding

This thesis comprises a collection of 39 research papers divided into three groups. The first group discusses the development of statistical methods, especially novel methods of variance component estimation, with general application. The second group examines the potential use of statistical methods in animal breeding studies, ranging from the construction of new experimental designs to the analysis of non-normal data. The third group reports on studies on animal breeding data in beef and dairy cattle.Group I is entitled "Statistical methods, including variance component estimation, with general application". The major theme of this group is the estimation of variance components. Some previous work based on methods for balanced data, gave rise to methods that were neither unique nor efficient and other methods gave results that are inconsistent with the analysis of variance for balanced data. A method was introduced, now known as REML (Residual Maximum Likelihood) that unifies the area. The method was introduced for the analysis of incomplete block designs with unequal block size but was found to have important applications in the analysis of groups of similar trials, time-series and animal breeding. Papers investigating REML estimation for multivariate data, time-series and detecting outliers are included. The relationship of REML to other methods is elucidated, especially for balanced and partially balanced designs. Computational strategies are discussed.The last two papers in the group illustrate a method of analysis of dial lei crosses that involves using multiple copies of the data. This idea of using multiple copies was shown also to be useful in the analysis of rectangular lattice designs and in the interpretation of some recently introduced neighbour analyses of field trials.The next group of papers, Group II, report on "Application of statistical methods to animal breeding studies". The work on variance components has some application in animal breeding and I have built on these links. Four papers consider efficient designs for estimation of genetic parameters, including designs for estimating heritability from data on two generations of data, for estimating maternal genetic variances, for estimating parent-offspri ng regression and for estimating multivariate genetic parameters. These designs can lead to substantial reductions in the variances of the estimates of the parameters, compared with classical designs, halving variances in some cases. Other papers have shown how to efficiently estimate heritability from unbalanced data, both from two generations of data and from more than two generations.Often in animal breeding experiments animals used as parents are not selected at random, but selected on phenotypic measurements, perhaps of relatives. This can cause bias in some methods of estimation. On the other hand REML estimates can take account of the selection process. Selection experiments and the estimation of realised heritability are discussed.REML estimation has found widespread acceptance by animal breeders, partly because some quantities arising in the methods were terms that animal breeders use in evaluating animals. It was shown how to improve one method of evaluation and methods of evaluating sires were reviewedSome work is included on multivariate evaluation. It is shown how the complex multivariate calculations can be reduced to simpler univariate calculations using a canonical transformation, how results on selection indices can be used to interpret multivariate predictions. A simple interpretation of quadratic selection indices is given.Other work considered some parallel problems with non-normal data. In particular for binary data, estimation of heritability, optimal designs for estimation of heritability and prediction of breeding values. It was shown how to estimate genotype frequencies using generalised linear model methods and > h? suggested how to evaluate animals worth and estimate genetic parameters when the data fits a generalised linear model.The last group, Group III, is entitled "Experimental studies". These include reports on a long term study of evaluation of breeds and cross-breeding in beef cattle in Zambia. The section also examines the genetic relationship between meat and milk production in British Friesian cattle. The validity of models used in dairy sire evaluation are investigated including the heterogeneity of heritability of milk yield at different levels of production and the use of a novel model for taking account of environmental variation within herds.GROUP I: STATISTICAL METHODS INCLUDING VARIANCE COMPONENT ESTIMATE WITH GENERAL APPLICATION01. R. THOMPSON. 1969. Iterative estimation of variance components for non-orthogonal data. Biometrics 25, 767-773. || 02. H.D. PATTERSON and R. THOMPSON. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58, 545-554. || 03. H.D. PATTERSON and R. THOMPSON. 1975. Maximum likelihood estimation of components of variance. Proceedings of the 8th International Biometric Conference. Ed. L.C.A. Corsten and T. Postelnicu, 199-207. || 04. R. THOMPSON. 1980. Maximum likelihood estimation of variance components. Math. Operationsforsh. Statist. ljU 545-561. || 05. R. THOMPSON. 1978. The estimation of variance and covariance components with an application when records are subject to culling. Biometrics 29, 527-550. || 06. L.R. SCHAEFFER, J.W. WILTON and R. THOMPSON. 1978. Simultaneous estimation of variance and covariance components from multitrait mixed model equations. Biometrics 34, 199-208. || 07. D.M. COOPER and R. THOMPSON. 1977 . A note on the estimation of the parameters of the autoregressive-moving average process. Biometrika 64, 625-628. || 08. R. THOMPSON. 1985. A note on restricted maximum likelihood estimation with an alternative outlier model. J.R. Statist. Soc. B 47, 53-55. || 09. R. THOMPSON. 1975. A note on the W transformation. Technometrics J7, 511-512. || 10. R. THOMPSON and K. MEYER. 1986. Estimation of variance components : what is missing in the EM algorithm? J. Statist. Comput. Simul. 24 215-230. || 11. D.L. ROBINSON, R. THOMPSON and P.G.N. DIGBY. REML. 1982. A program for the analysis of non-orthogonal data by restricted maximum likelihood. COMPSTAT 1982, II. Eds. H. Cassinus, P. Ettinger and J.R. Mattieu. Physica-Verlag, Wien 231-232. || 12. R. THOMPSON. 1983. Dial lei crosses, partially balanced incomplete block designs with triangular association schemes and rectangular lattices. GENSTAT newsletter JJ3, 16-32. || 13. R. THOMPSON. 1984. The use of multiple copies of data in forming and interpreting analysis of variance. Experimental design, Statistical Methods and Genetic Statistics. Ed. K. Hinkelmann. Marcel Dekker, New York, 155-174.GROUP II: APPLICATION OF STATISTICAL METHODS TO ANIMAL BREEDING STUDIES14. R. THOMPSON. 1976. The estimation of maternal genetic variances. Biometrics 32 903-917. || 15. R. THOMPSON. 1976. Design of experiments to estimate heritability when observations are available on parents and offspring. Biometrics 32 283-304. || 16. W.G. HILL and R. THOMPSON. 1977. Design of experiments to estimate parent-offspring regression using selected parents. Anim. Prod. 24, 163-168. || 17. N.D. CAMERON and R. THOMPSON. 1986. Design of multivariate selection experiments to estimate genetic parameters. Theor. Appl. Genet. 72, 466-476. || 18. R. THOMPSON. 1977. The estimation of heritability with unbalanced data. I. Observations available on parents and offspring. Biometrics 33, 485-495. || 19. R. THOMPSON. 1977. The estimation of heritability with unbalanced data. II. Data available on more than two generations. Biometrics 33, 495-504. || 20. R. THOMPSON. 1977. The estimation of heritability with unbalanced data. III. Unpublished Appendices, 1-17. || 21. R. THOMPSON. 1976. Estimation of quantitative genetic parameters. Proceedings of the International Conference on Quantitative Genetics. Ed. 0. Kempthorne, E. Pollak and T. Bailey. Iowa State University press, Ames, Iowa, 639-657. (vii) || 22. W.G. HILL and R. THOMPSON. 1978. Probabilities of non-positive definite between group or genetic covariance matrices. Biometrics 34, 429-439. || 23. K. MEYER and R. THOMPSON. 1984. Bias in variance and covariance component estimators due to selection on a correlated trait. Z. Tierzucht. Zuchtungsbiol. 101, 33-50. || 24. R. THOMPSON. 1976. Relationship between the cumulative different and best linear unbiased predictor methods of evaluating bulls. Anim. Prod. 23^, 15-24. || 25. R. THOMPSON. 1979. Sire Evaluation. Biometrics 35, 339-353. || 26. R. THOMPSON. 1986. Estimation of realised heritability in a selected population using mixed model methods. Genet. Sel. Evol . 475-484. || 27. R. THOMPSON. 1972. The maximum likelihood approach to the estimate of liability. Anim. Hum. Genet. 36, 221-231. || 28. R. THOMPSON, B.J. McGUIRK and A.R. GILMOUR. 1985. Estimating the heritability of all-or-none and categorical traits by offspring-parent regression. Z. Tierzucht. Zuchtungsbiol. 102, 342-354. || 29. J.L. FOULLEY, D. GIANOLA and R. THOMPSON. 1983. Prediction of genetic merit from data on binary and quantitative variates with an application to calving difficulty, birth weight and pelvic opening. Genet. Sel. Evol. 15, 401-424. || 30. R. THOMPSON and R.J. BAKER. 1981. Composite link functions in generalised linear models. J.R. Statist. Soc. B. 30, 125-131. || 31. R. THOMPSON. 1980. A note on the estimation of economic values for selection indices. Anim. Prod. 31, 115-117.GROUP III: EXPERIMENTAL STUDIES32. W. THORPE, D.K.R. CRUICKSHANK and R. THOMPSON. 1980. Genetic and evironmental influences on beef cattle production in Zambia. Factors affecting weaner production from Angoni, Barotse and Boran dams. Anim. Prod. 30, 217-234. || 33. W. THORPE, D.K.R. CRUICKSHANK and R. THOMPSON. 1980. Genetic and environmental influences on beef cattle production in Zambia. 2. Sire weights for age of purebred and reciprocally crossbred progeny. Anim. Prod. 30, 235-243. || 34. W. THORPE, D.K.R. CRUICKSHANK and R. THOMPSON. 1980. Genetic and environmental influences on beef cattle production in Zambia. 3. Carcass characteristics of purebred and reciprocally crossbred progeny. Anim. Prod. 30, 245-252. || 35. W. THORPE, D.C.K. CRUICKSHANK and R. THOMPSON. 1982. Genetic and environmental influences on beef cattle in Zambia. 4. Weaner production from purebred and reciprocally crossbred progeny. Anim. Prod. 33, 165-177. || 36. W. THORPE, D.K.R. CRUICKSHANK and R. THOMPSON. 1979. The growth and carcass character!- sti cs of crosses of Hereford and Friesian with Angoni, Barotse and Boran cattle in Zambia. J. Agric. Sci., Camb. 93, 423-430. || 37. I.L. MASON, V.E. VIAL and R. THOMPSON. 1972. Genetic parameters of beef characteristics and the genetic relationship between meat and milk production in British Friesian cattle. Anim. Prod. 135-148. || 38. W.G. HILL, M.R. EDWARDS, M-K A. AHMED and R. THOMPSON. 1983. Heritability of milk yield and composition at different levels and variability of production. Anim. Prod. 36, 59-68. || 39. V.P.S. CHAUHAN and R. THOMPSON. 1986. Dairy sire evaluation using a "rolling months" model. Z. Tierzucht. Zuchtungsbiol 103, 321-333