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The dynamic charging performances of a cool energy storage system with coil pipes were studied. The n-tetradecane was taken as phase change material and the aqueous ethylene glycol solution of 25% volumetric concentration was considered as a heat transfer fluid. A numerical model based on energy balance equations of the phase change material and the heat transfer fluid was developed to investigate the variations of temperatures of the phase change material and heat transfer fluid, solid fraction and cool storage rate with time during the charging process. The effects of the inlet temperatures and the flow rates of the heat transfer fluid on the outlet temperature of the heat transfer fluid, cool storage rate, and solid fraction were discussed. It is concluded that the higher flow rate of the heat transfer fluid or the lower inlet temperature of the heat transfer fluid result in the higher cool storage rate and less time for the charging process. It took about 5 h for the charging process with the...

The dynamic characteristics of a solar thermal storage system using a packed bed with spherical capsules during the discharging process are studied. According to the energy balance of a solar thermal storage system, the dynamic discharging processes model of a packed bed with spherical capsules is presented. Paraffin is taken as a phase change material and water is used as a heat transfer fluid. The temperatures of phase change material and heat transfer fluid, solid fraction, and heat released rate are investigated. The effects of inlet temperature of heat transfer fluid and flow rate of heat transfer fluid on the time for discharging and heat released rate are also discussed.

Water shortage resulting from both natural conditions and human activities has been proved to be a bottleneck that chokes development in arid and semiarid regions. Systems analysis provides an effective way of clarifying conflicts between water supply and demand. In this study, an arid/semiarid region water management (ASRWM) model is developed for sound planning of a water resources system. The proposed model is founded on interval-fuzzy multiobjective programing (IFMOP) for effectively reflecting complexities of the study system and expediently facilitating solution of the model. Member-ship functions for modeling objectives and constraints are formulated to reflect uncertainties in different system components and their interrelationships. To evaluate the applicability of the proposed model, a case study for the Luopu County in northwestern China has been undertaken. The modeling outputs generated through scenario analyses are based on in-depth examination of several sensitive issues including farming, ...

In this study, a hybrid GIS-supported watershed modelling system is developed for integrated planning of water pollution control in the Lake Erhai basin, China. The system comprises a GIS-supported database, simulation/optimization models, and user interfaces developed through Arc/Info and Arc View. An inexactfuzzy multi-objective optimization model is developed for assessing a variety of system objectives and generating desired decision alternatives. It can effectively reflect uncertain, interactive and multi-objective features of the study system, and its solutions provide decision makers with a flexible decision space. The GIS technology is used for managing spatial and non-spatial data, linking models, and providing interfaces between the models and their users. The developed modelling system allows regional planners to obtain desired plans of human activities under a variety of objectives and constraints and to examine consequences and impacts resulting from alternative management practices.

A current-expansion technique is proposed to analyze the waveguide discontinuities of irregular shape. Roof-top and rectangular-pipe sub-domain functions are used in an electric-field integral-equation formulation to adequately expand the three-dimensional current densities of an irregularly-shaped conductor. It is therefore applicable to quite general discontinuity configurations. Numerical results for a variety of waveguide discontinuities including open-ends, bends, and T junctions have been demonstrated and verified by the available published data.

The digitization of mathematically unknown free-form curves is frequently required. Current industrial practice relies on the experience of an operator to determine the direction of a CMM probe's approaching vector and the number of samples to represent a complex curve. An automatic procedure is proposed to generate recursively the approaching vector direction as well as the sampling rate. Several techniques including a linear prediction, a polynomial prediction, and a spline interpolation method have been presented and compared. Experimental results show that the spline interpolation method provides the best digitization accuracy and requires the least number of sampling points.

Nine eumenorrheic women were studied at five separate times each month for a minimum of 2 months. Fasting bloods and 1-day food records were obtained from all women at these times to describe the pattern and magnitude of within-person variation in selected nutrient and lipid indicators attributable to menstrual cyclicity. Serum cholesterol, beta-carotene, 17 beta-estradiol (E2), and dietary selenium intakes exhibited significant periodic regressions against time. For the group as a whole, however, only serum cholesterol and E2 measures exhibited significantly strong consistent periodicities. Future studies with a larger sample of women are warranted to confirm these findings. Unless strict blood sampling protocols are followed, variation attributable to menstrual cyclicity may mitigate the reliability of the serum cholesterol screenings advocated in the past few years.

A new approach to trajectory control of an industrial robot is proposed which aims to reduce the error in the trajectory, under the assumption that the position of the hand is known or can be measured in Cartesian space. An on-line system identification technique, referred to as the adaptive linear modelling technique, and a forecasting algorithm to generate corrective commands were used. A laser measurement system with a laser source and a photodetector was developed to detect the error between the actual and desired trajectories in Cartesian space. By implementing the proposed methods a 70% improvement in controlling the trajectory error was achieved.

Discretization of a continuous autoregressive moving average process at an equispaced sampling interval results in a discrete autoregressive moving average process. The relationship between the continuous and the discrete parameters yields a simple method of maximum likelihood estimation of the continuous parameters from a discretely sampled data. A technique is described for modeling of continuous processes from discrete observations and is illustrated with analysis of the yearly Wolfer's sunspot numbers data.

A multivariate time series procedure of modeling closed-loop systems from operating data is outlined and illustrated by real life data from a paper-making process. The procedure does not require a priori knowledge, sample correlations or spectra for guessing the model form. The paper also illustrates a simple method of obtaining the minimum mean squared error control equation and ascertaining the performance of the existing control strategy.

The behavior of uniformly sampled queues simulated under different dispatching policies are modeled and interpreted using time series techniques. Queue behavior is shown to be adequately described by a first order autoregressive AR(1) model if the job selection discipline does not depend on operation processing time. In those cases where processing time was used in job selection, a second order autoregressive AR(2) model is adequate to characterize the queues. Queue behavior under different selection disciplines is then interpreted via the models as a convolution of the specific selection policy on the basic first come, first served (FCFS) queue. This analysis also demonstrates the inability of linear differential equations to describe queue fluctuation in systems where processing time based selection rules are employed.

A new modeling technique is introduced for on-line sensor time constant identification, both for the resistance temperature detector (RTD) and for the pressure sensor using power plant operational data. The sensor's time constant is estimated from a real characteristic root of the fitted autoregressive moving average model. The RTD's time constant values were identified to be 8.4 s, with a standard deviation of 1.2 s. The pressure sensor time constant was identified to be 28.6 ms, with a standard deviation of 3.5 ms.

A number of chart's are presented to facilitate the identification and estimation of the second order moving average and mixed first order autoregressive-moving average models. Two chart's are presented which show the patterns in the correlation and partial correlation functions over the admissible parameter regions for these models to aid in their interpretation and identification. The pure autoregressive form is used to interpret the models. Charts are developed to provide initial estimates of the parameters of t'he models. Methods of obtaining approximate confidence regions by graphs are given and their adequacy discussed. An example is presented to illustrate the use of the charts.

A simplified model describing the complicated boiling water reactor (BWR) kinetics is developed by combining two different approaches: the analytical and the experimental, the latter based on the dynamic data system methodology. This model is capable of adequately representing the BWR main dynamics, which can be, in turn, conveniently used to predict its kinetics. Although the system exhibits some highly nonlinear characteristics, it is approximated by a linear model. By using Peach Bottom-2 real operating data without perturbation, the dynamics of the BWR are experimentally identified, and the results are found to be in close agreement with those obtained by the General Electric Company.

A statistical approach to model a papermaking process and to control paper basis weight is presented. The process behavior is described by a mathematical model which takes into consideration both the input-output dynamics and disturbances coming into the system. The model building procedure was based on a three-step approach of identification, estimation and diagnostic checking. The disturbance model is accounted for by a discrete time series model, whereas the dynamic model is a discrete transfer function model. The simplicity of the modeling process lies in the fact that only the input-outpul data are necessary without recourse to a complicated analysis of the physical system itself. An optimal control equation was arrived at whereby the basis weight of the paper was to be controlled at a specified target value. Confirmation runs were conducted to check the effectiveness of the control equation.

An algorithm for the determination of the economic design of -charts based on Duncan's model is described in this paper. This algorithm consists of solving an implicit equation in design variables n (sample size) and k (control limit factor) and an explicit equation for h (sampling interval). The use of this algorithm not only yields the exact optimum but also provides valuable information so that the sensitivity of the optimum loss-cost (L*) can be evaluated. Loss-cost contours are used to discuss the nature of the loss-cost surface and the effect of the design variables. The effect of two parameters, the delay factor (e), and the average time for an assignable cause to occur (1/λ), on the optimum design is evaluated. Numerical examples are used for illustrations.

A set of pressure data recorded from the primary coolant system of a pressurized water reactor under normal operation is examined. For pressure sensors under study, it is found that the range of sampling intervals adequate to abstract pressure dynamics is about 0.2 to 0.8 ms. The estimated time constant of the pressure sensor for operating data is 1.83 ms.