Comparison of Nonactive Powers for the Detection of Dominant Harmonic Sources in Power Systems

This paper deals with an innovative technique for the detection of disturbing loads in distorted power systems. The technique is a single-point strategy based on a comparison among different “nonactive” power quantities already proposed in the literature, which are measured at the same metering section. In this paper, the effectiveness of the strategy is discussed, which also considered the errors of the measurement transducers; the analysis is supported by simulation tests, which were carried out on both a simple single-phase system and an IEEE standard three-phase test power system. The latter was used by other authors as a benchmark system for the analysis of multipoint measurement techniques for harmonic pollution monitoring.      

Verschleiß – eine Systemeigenschaft Auswirkungen auf die Verschleißprüfung

Wear — a System Property. Consequences on Wear Testing . Wear research, wear testing and wear reduction are based on the principle that wear is a property of a system consisting of structural and loading parameters. Wear characteristics can therefore only be determined with reference to the system, and wear test methods must be modelled on the practical system considered. Wear systems are investigated by means of laboratory tests on testpieces, components and complete assemblies as well as service tests. Despite their drawbacks, test-piece and component tests under particular conditions are valuable in the development of practical wear systems. As an example, a device for testing test-pieces and components is described. Sliding wear processes are simulated under mixed and boundary friction conditions. Static and dynamic wear conditions can be simulated.     

Calibration and optimization of an electric vehicle powertrain system

ABSTRACT

The problem of insufficient driving performance in existing electric vehicle (EV) powertrain systems is solved in this paper by presenting the EV as the reference object. The system model of the EV is established based on the powertrain system layout, technical parameters, and performance requirements, and the vehicle dynamic property and pure electric drive economy are evaluated. On the basis of the component models and total outputted power, the driving range is considered as the optimization target, and the input simulation parameters are considered as the optimized variables. Therefore, the optimal variable parameters are determined by multiple simulation analysis. In view of the test bench results, the rationality of the parameters of the simulation result is verified. Generally speaking, with the flexible configuration of the designed powertrain system and the optimized parameters of dynamic programming, the automobile performance can be improved.     

Surveillance test policy optimization through genetic algorithms using non-periodic intervention frequencies and considering seasonal constraints

In order to maximize systems average availability during a given period of time, it has recently been developed a non-periodic surveillance test optimization methodology based on genetic algorithms (GA). The fact of allowing non-periodic tests turns the solution space much more flexible and schedules can be better adjusted, providing gains in the overall system average availability, when compared to those obtained by an optimized periodic test scheme. This approach, however, turns the optimization problem more complex. Hence, the use of a powerful optimization technique, such as GA, is required.Considering that some particular features of certain systems can turn it advisable to introduce other specific constraints in the optimization problem, this work investigates the application of seasonal constraints for the set of the Emergency Diesel Generation of a typical four-loop pressurized water reactor in order to planning and optimizing its surveillance test policy. In this analysis, the growth of the blackout accident probability during summer, due to electrical power demand increases, was considered. Here, the used model penalizes surveillance test interventions when the blackout probability is higher.Results demonstrate the ability of the method in adapting the surveillance test policy to seasonal constraints. The knowledge acquired by the GA during the searching process has lead to test schedules that drastically minimize test interventions at periods of high blackout probability. It is compensated by more frequent redistributed tests through the periods of low blackout probability in order to improve on the overall average availability at the system level.     

Performances of adsorption systems for ambient heating and air conditioning: Performances de systèmes à adsorption pour le chauffage et le conditionnement d'air d'ambiance

Two adsorption systems are considered: zeolite–water and activated carbon–methanol, both consisting of two ‘uniform temperature' adsorbent beds operating with internal heat recovery by a heat carrier circuit. Regarding the zeolite–water system, the performance obtained with a new adsorbent bed, with good heat transfer properties, is compared with a traditional tube and fin exchanger embedded with zeolite pellets. The performances were calculated by using a dynamic model developed and validated previously. Results show that the system based on the new adsorber has a higher specific power and the same Coefficient of Performance. Results of simulation for adsorbers consisting of finned tube heat exchangers and utilising the activated carbon–methanol pair are also presented.     

The robustness of markov reliability models

Markov models are an established part of current systems reliability and availability analysis. They are extensively used in various applications, including, in particular, electrical power supply systems. One of their advantages is that they considerably simplify availability evaluation so that the availability of very large and complex systems can be computed. It is generally assumed, with some justification, that the results obtained from such Markov reliability models are relatively robust. It has, however, been known for some time, that practical time to failure distributions are frequently non-exponential, particular attention being given in much reliability work to the Weibull family. Morover, recently additional doubt has been case on the validity of the Markov approach, both because of the work of Professor Kline and others on the non-exponentiality of practical repair time distribution, and because of the advantages to be obtained in terms of modelling visibility of the alternative simulation approach. In this paper we employ results on the ability of the k-out-of-n systems to span the coherent set to investigate the robustness of Markov reliability models based upon a simulation investigation of coherent systems of up to 10 identical components. We treat the case where adequate repair facilities are available for all components. The effects upon the conventional transient and steady-state measures of Weibull departures from exponentiality are considered. In general, the Markov models are found to be relatively robust, with alterations to failure distributions being more important than those to repair distributions, and decreasing hazard rates more critical than increasing hazard rates. Of the measures studied, the mean time to failure is most sensitive to variations in distributional shape.     

Assessment of low probability events of dynamical systems by controlled Monte Carlo simulation

Various procedures to extend the applicability and to increase the efficiency of Monte Carlo simulation (MCS) for the analysis of complex dynamical systems are discussed. In particular, the capabilities of the methods denoted Russian Roulette and Splitting (RR&S) and Double and Clump (D&C) are reviewed with regard to their capabilities to analyze such systems. In this context, the difficulties in identifying the ‘important' regions for simulation are detailed. It is shown that these difficulties may be circumvented by a newly introduced ‘distance controlled' MCS. This procedure, which allows the prediction of very low probability events and the analysis of systems of higher dimension, is applicable not only to mechanical systems and structures but also to complex dynamical systems encountered, for example, in economics, physics, etc. The procedure is shown to be particularly suited to cases where exact analytical methods and direct Monte Carlo simulation are infeasible, hence, being well suited for practical application.     

A Bayesian framework for accelerated reliability growth testing with multiple sources of uncertainty

Reliability growth tests are often used for achieving a target reliability for complex systems via multiple test‐fix stages with limited testing resources. Such tests can be sped up via accelerated life testing (ALT) where test units are exposed to harsher‐than‐normal conditions. In this paper, a Bayesian framework is proposed to analyze ALT data in reliability growth. In particular, a complex system with components that have multiple competing failure modes is considered, and the time to failure of each failure mode is assumed to follow a Weibull distribution. We also assume that the accelerated condition has a fixed time scaling effect on each of the failure modes. In addition, a corrective action with fixed ineffectiveness can be performed at the end of each stage to reduce the occurrence of each failure mode. Under the Bayesian framework, a general model is developed to handle uncertainty on all model parameters, and several special cases with some parameters being known are also studied. A simulation study is conducted to assess the performance of the proposed models in estimating the final reliability of the system and to study the effects of unbiased and biased prior knowledge on the system‐level reliability estimates.     

Effect of Ultrasonic Output Power on Refining the Crystal Structures of Ingots and Its Experimental Simulation

In this study, a series of tests were conducted by using aluminum-based alloy to determine the formation of grain refining structure based on the ultrasonic vibration (UV). Furthermore, the simulation test and effect of ultrasonic output power were studied using ammonium chloride. Finally, the mechanism of grain refinement was investigated. The results show that: (1) By applying the UV to aluminum-base alloy, the grain refining rate of ingots tended to increase with the increase of the output value of UV. (2) It was confirmed that time from after the pour to the beginning of crystallization as well as cloudiness tended to decrease with increasing the ultrasonic power value of UV. Moreover, it can be seen from each cooling curve that a uniform temperature gradient existed in the melt as the power of UV increased, that made the melt strongly stirred. (3) It was also considered that the grain refining effect of ingots, which was observed from the simulation tests, resulted from nucleation action and stirrin     

Robust asymptotic tests for the equality of multivariate coefficients of variation

In order to easily compare several populations on the basis of more than one feature, multivariate coefficients of variation (MCV) may be used as they allow to summarize relative dispersion in a single index. However, up to date, no test of equality of one or more MCVs has been developed in the literature. In this paper, several classical and robust Wald-type tests are proposed and studied. The asymptotic distributions of the test statistics are derived under elliptical symmetry, and the asymptotic efficiency of the robust versions is compared to the classical tests. Robustness of the proposed procedures is examined through partial and joint influence functions of the test statistic, as well as by means of power and level influence functions. A simulation study compares the performance of the classical and robust tests under uncontaminated and contaminated schemes, and the difference with the usual covariance homogeneity test is highlighted. As a by-product, these tests may also be considered in the univariate context where they yield procedures that are both robust and easy-to-use. They provide an interesting alternative to the numerous parametric tests existing in the literature, which are, in most cases, unreliable in presence of outliers. The methods are illustrated on a real data set.     

Single-fibre Broutman test: fibre–matrix interface transverse debonding

The single-fibre Broutman test was used to study the fibre–matrix interface debonding behaviour when subjected to a transverse tensile stress. During testing, damage was detected using both visual observation under polarized light and acoustic emission (AE) monitoring. Separation of failure mechanisms, based on AE events, was performed using time domain parameters (amplitude and event width) and fast Fourier transform (FFT) frequency spectra of the AE waveforms. The latter can be considered as a fingerprint allowing to discriminate fibre failure, matrix cracking, fibre–matrix interface debonding, friction and ‘parasite noise’. Stresses in the specimens were evaluated using a two-dimensional finite element model (FEM) and monochromatic photoelasticity was used to verify the simulated stress distribution.Two failure mechanisms appeared to be in competition in the Broutman test: fibre failure under compressive stresses and fibre–matrix interface debonding under transverse tensile stresses. For systems in which the interfacial adhesion is not so ‘good’, like glass fibre–polyester systems for instance, fibre–matrix debonding was observed, and the progression of the debonding front with the interfacial transverse stress was recorded. Thermal stresses are also discussed, and a FEM simulation shows that they encourage fibre failure under compressive stresses.     

A Monte Carlo Study Comparing Various Two-Sample Tests for Differences in Mean

A study was conducted on eight tests for differences in means under a variety of simulated experimental situations. Estimates were made of the power of the tests and measures of the extent to which they gave similar results. In particular the performance of a new quick test developed by Neave was studied and was found to be satisfactory: in fact it was by far the best of the quick tests considered. However some of the classical and more general nonparametric tests, such as the runs and the Kolmogorov-Smirnov tests, were found to be less useful when testing for differences in means. Over the range of situations investigated, the Normal Scores test gave the most satisfactory results, followed closely by the Wilcoxon rank-sum test. Even when the populations were normally distributed, these tests were only very slightly inferior to the t-test, and naturally were much superior in the cases of non-normal populations.     

Three-dimensional flow and lift characteristics of a hovering ruby-throated hummingbird

A three-dimensional computational fluid dynamics simulation is performed for a ruby-throated hummingbird (Archilochus colubris) in hovering flight. Realistic wing kinematics are adopted in the numerical model by reconstructing the wing motion from high-speed imaging data of the bird. Lift history and the three-dimensional flow pattern around the wing in full stroke cycles are captured in the simulation. Significant asymmetry is observed for lift production within a stroke cycle. In particular, the downstroke generates about 2.5 times as much vertical force as the upstroke, a result that confirms the estimate based on the measurement of the circulation in a previous experimental study. Associated with lift production is the similar power imbalance between the two half strokes. Further analysis shows that in addition to the angle of attack, wing velocity and surface area, drag-based force and wing–wake interaction also contribute significantly to the lift asymmetry. Though the wing–wake interaction could be beneficial for lift enhancement, the isolated stroke simulation shows that this benefit is buried by other opposing effects, e.g. presence of downwash. The leading-edge vortex is stable during the downstroke but may shed during the upstroke. Finally, the full-body simulation result shows that the effects of wing–wing interaction and wing–body interaction are small.     

Semi-Markovian reliability models for systems with testable components and general test/outage times

Semi-Markov models for systems undergoing periodic test and maintenance are developed. In particular, systems undergoing specific changes of state at predetermined instances of time and transiting to states with generally distributed sojourn times are considered. Problems addressed by the models are those concerned with optimum assessment of test intervals, and allowable outage times. Equivalent Markovian models allowing for the decomposition of a system of dimensionality N+M into two smaller problems of dimensionality N and M, respectively are developed. The general model is also specialized to systems with instantaneously testable components, unmonitored components undergoing tests (repair, maintenance) of fixed duration, and systems containing components characterized by limited allowable outage time (under test, or repair). Approximate equivalent Markov models are derived in these cases. Simple numerical examples are also presented.     

New two-sample tests for skewed populations and their connection to theoretical power of Bootstrap-<Emphasis Type="Italic">t</Emphasis> test

Various tests are available to compare the means of two populations. Tests for skewed data, however, are not well studied even though they are often needed in pharmaceutical study and agricultural economics. In particular, there is no available result to give power and sample size calculation for a two-sample Bootstrap-t test in skewed populations. In this paper, we propose easy-to-compute new tests and study their theoretical properties. The proposed work starts with derivation of a second-order Edgeworth expansion for the pooled two-sample t-statistic. Then new test rejection regions are formed based on Cornish–Fisher expansion of quantiles. The new tests account for first-order and second-order population skewnesses that were ignored in two-sample t test. We report the theoretical type I error accuracy and power of the newly proposed tests and the large sample t test. We also provide the detailed conditions under which the proposed tests give better power than the two-sample large sample test. Our new tests, \(\hbox {TCF}_1\) and TCF, are asymptotically equivalent to Bootstrap-t test up to \(O(N^{-1})\) and \(O(N^{-3/2})\), respectively. Compared with commonly used two-sample parametric and nonparametric tests, the new tests are computationally efficient, give better power for skewed data with moderate sample size, and provide sample size calculation to achieve desired power at a given significance level. Empirical studies confirmed our theoretical results.     

A lean-based ORR system for non-repetitive manufacturing

Lean implementations are no longer limited to high-volume production and are becoming increasingly common in low-volume, high-variety non-repetitive companies. Such companies, usually with make-to-order or engineer-to-order production, have normally been modelled with a job shop production system, but many of them actually have a dominant flow in production. Moreover, one of the main characteristics of lean implementation is that it streamlines production flow, makes it unidirectional and reduces setup and lot size. Consequently, a significant number of production systems are better modelled as flow shops, rather than as job shops. This has an impact on production management approaches, and in particular on order review and release systems. In fact, ORR systems have been designed with job shops in mind, because they are the most complex systems to manage, and because they are considered the optimal system for non-repetitive production. We believe that job shop designed ORR systems are not the best ones for flow shop systems. We consequently propose a new ORR system designed for non-repetitive production in flow shops and based on lean principles. The simulation campaign run to test the new model shows that it yields lower lead times and increases output.     

Structure-preserved power-frequency slow dynamics simulation of interconnected ac/dc power systems with AGC consideration

A structure-preserved power-frequency slow dynamics simulation model is suggested for interconnected ac/dc power systems with automatic generation control (AGC) consideration, which will be applied to study relevant emergency control in future so that the bulk system viability crisis caused by load-frequency slow dynamics can be released. In the model, the network structure of interconnected power systems is entirely preserved, and the multi-area dynamic load flow (DLF) is developed for simulation. The generator speed governor and rotor dynamics, load-frequency characteristics, simplified models for high voltage direct current (HVDC) transmission and flexible ac transmission systems (FACTS) device thyristor controlled series capacitor (TCSC) suitable for long-term dynamics are considered with their AGC interfaces kept for future emergency-AGC study. However, at this stage, the sub-problem of reactive power and voltage is neglected for modelling simplicity and dc load flow is thus used for network solution. The concept of area centre of inertia (ACOI) is used based on the assumption of uniform frequency in each control area similar to that of the conventional single-area DLF calculation. The application of ACOI concept is attractive because the signal can be obtained from wide-area measurement systems (WAMSs) in real time and used to enhance long-term frequency stability through advanced control in future. The computer test results from 2-area 4-machine and IEEE 30-bus power systems demonstrated the validity and effectiveness of the suggested model and corresponding algorithm.     

Positive input observer‐based controller design for blood glucose regulation for type 1 diabetic patients: A backstepping approach

In practice, there are many physical systems that can have only positive inputs, such as physiological systems. Most conventional control methods cannot ensure that the main system input is positive. A positive input observer‐based controller is designed for an intravenous glucose tolerance test model of type 1 diabetes mellitus (T1DM). The backstepping (BS) approach is employed to design the feedback controller for artificial pancreas (AP) systems, based on the Extended Bergman''s Minimal Model (EBMM). The EBMM represents the T1DM in terms of the blood glucose concentration (BGC), insulin concentration, and plasma level and the disturbance of insulin during medication due to either meal intake or burning sugar by doing some physical exercise. The insulin concentration and plasma level are estimated using observers, and these estimations are applied as feedback to the controller. The asymptotic stability of the observer‐based controller is proved using the Lyapunov theorem. Moreover, it is proved that the system is bounded input‐bounded output (BIBO) stable in the presence of uncertainties generated by uncertain parameters and external disturbance. For realistic situations, we consider only the BGC to be available for measurement and additionally inter‐and intra‐patient variability of system parameters is considered.     

Linear Hypothesis Testing With Functional Data

In real data analysis, it is often interesting to consider a general linear hypothesis testing (GLHT) problem for functional data, which includes the one-way ANOVA, post hoc, or contrast analysis as special cases. Existing tests for this GLHT problem include an L²-norm-based test and an F-type test but their theoretical properties have not been investigated. In addition, for functional one-way ANOVA, simulation studies in the literature indicate that they are less powerful than the globalizing pointwise F (GPF) test and the F_max?-test. The GPF and F_max?-test enjoy several other good properties. They are scale-invariant in the sense that their test statistics do not change if we multiply each of functional curves with a nonzero function of the observed locations. In this article, the GPF and F_max?-test are adapted to the above GLHT problem. Their theoretical properties, for example, root-n consistency as well as those of the L²-norm-based and F-type tests are established. Intensive simulation studies are carried out to compare the finite-sample behavior of the tests under consideration in scenarios reflecting various practical characteristics of functional data. Simulation results indicate that the GPF test has higher power than other tests when the functional data are less correlated, and the F_max?-test has higher power than other tests when the functional data are moderately or highly correlated. These results are also confirmed by application of the GPF and F_max? tests to the corneal surface data coming from medical industry. This application suggests the new methods may help to make more clear and sure decisions in practice. For a convenient application of the considered testing procedures, their implementation is developed in the R programming language. Supplementary materials for the article are available online.     

Testing for Poisson arrivals in INAR(1) processes

In the framework of integer-valued autoregressive processes of order 1 [INAR(1)], two new tests for the null hypothesis of Poisson-distributed innovations are developed. The tests focus on time reversibility, as this feature is shown to be satisfied exclusively by Poisson INAR(1) processes. The necessary asymptotic variances are explicitly calculated using the joint cumulants of these processes. The finite-sample behavior of the test statistics and the power of the tests are investigated in a simulation study. The results show that the newly developed tests perform better than existing ones in certain situations.