Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Sensitivity analysis in conjunction with evidence theory representations of epistemic uncertainty

Three applications of sampling-based sensitivity analysis in conjunction with evidence theory representations for epistemic uncertainty in model inputs are described: (i) an initial exploratory analysis to assess model behavior and provide insights for additional analysis; (ii) a stepwise analysis showing the incremental effects of uncertain variables on complementary cumulative belief functions and complementary cumulative plausibility functions; and (iii) a summary analysis showing a spectrum of variance-based sensitivity analysis results that derive from probability spaces that are consistent with the evidence space under consideration.     

Construction Robot Path-Planning for Earthwork Operations

In developing an intelligent mobile construction robot, a navigation system that can provide an effective and efficient path-planning algorithm is a very important element. The purpose of a path-planning method for a mobile construction robot is to find a continuous collision-free path from the initial position of the construction robot to its target position. This paper presents an improved Bug-based algorithm, called SensBug, which can produce an effective path in an unknown environment with both stationary and movable obstacles. The contributions, which make it possible to generate an effective and short path, are an improved method to select local directions, a reverse mode, and a simple leaving condition. Some emerging technologies that can be used for implementing an intelligent construction robot are introduced in this paper.     

Electrostatic Droplet Growth in a Neutrally Buoyant Emulsion

Droplet growth is examined in a water-in-oil type emulsion where the droplets are subjected exclusively to viscous and dielectrophoretic forces. The latter are produced by the interaction of the droplets with an otherwise uniformly imposed electric field. Theoretical considerations are presented as a basis for understanding and interpreting the experiments. An emulsion consisting of deionized water droplets in a silicone oil of specific gravity I is subjected to a uniform 60 Hz, ac electrostatic field. Initially, the droplets are fairly monodisperse with mean diameters of approximately 25 , sm. The changes in droplet size distributions with time are examined with a laser diffraction system for water volume fractions ranging from 0.001 to 0.1 and applied fields ranging from 52 to 520 kVm-1. The average droplet size increases exponentially with time; we examine the exponent's dependence on average field strength and droplet volume fraction.     

Towards real CAD

Present-day computer-aided design (CAD) packages play only a small part in the area of mechanical engineering design, which involves the synthesis and embodiment of physical components to perform a pre-determined function without unwanted side effects. The computer cannot properly help the designer in this task until it is able to capture and process the function requirements of the design. This paper describes the computer system being developed for this purpose at the Engineering Design Centre at Cambridge University Engineering Department. The paper also explores some of the geometrical and programming implications raised.     

A 0.25-/spl mu/m CMOS quad-band GSM RF transceiver using an efficient LO frequency plan

This paper describes a single-chip CMOS quad-band (850/900/1800/1900 MHz) RF transceiver for GSM/GPRS applications. It is the most important design issue to maximize resource sharing and reuse in designing the multiband transceivers. In particular, reducing the number of voltage-controlled oscillators (VCOs) required for local oscillator (LO) frequency generation is very important because the VCO and phase-locked loop (PLL) circuits occupy a relatively large area. We propose a quad-band GSM transceiver architecture that employs a direct conversion receiver and an offset PLL transmitter, which requires only one VCO/PLL to generate LO signals by using an efficient LO frequency plan. In the receive path, four separate LNAs are used for each band, and two down-conversion mixers are used, one for the low bands (850/900 MHz) and the other for the high bands (1800/1900 MHz). A receiver baseband circuit is shared for all four bands because all of their channel spaces are the same. In the transmit path, most of the building blocks of the offset PLL, including a TX VCO and IF filters, are integrated. The quad-band GSM transceiver that was implemented in 0.25-/spl mu/m CMOS technology has a size of 3.3/spl times/3.2 mm/sup 2/, including its pad area. From the experimental results, we found that the receiver provides a maximum noise figure of 2.9 dB and a minimum IIP3 of -13.2dBm for the EGSM 900 band. The transmitter shows an rms phase error of 1.4/spl deg/ and meets the GSM spectral mask specification. The prototype chip consumes 56 and 58 mA at 2.8 V in the RX and TX modes, respectively.     

Genetic algorithms in engineering electromagnetics

This paper presents a tutorial and overview of genetic algorithms for electromagnetic optimization. Genetic-algorithm (GA) optimizers are robust, stochastic search methods modeled on the concepts of natural selection and evolution. The relationship between traditional optimization techniques and the GA is discussed. Step-by-step implementation aspects of the GA are detailed, through an example with the objective of providing useful guidelines for the potential user. Extensive use is made of sidebars and graphical presentation to facilitate understanding. The tutorial is followed by a discussion of several electromagnetic applications in which the GA has proven useful. The applications discussed include the design of lightweight, broadband microwave absorbers, the reduction of array sidelobes in thinned arrays, the design of shaped-beam antenna arrays, the extraction of natural resonance modes of radar targets from backscattered response data, and the design of broadband patch antennas. Genetic-algorithm optimization is shown to be suitable for optimizing a broad class of problems of interest to the electromagnetic community. A comprehensive list of key references, organized by application category, is also provided     

Optical imaging of anatomical maps derived from magnetic resonanceimages using time-independent optical sources

Presents a model suitable for computing images of absorption cross sections of thick tissue structures illuminated at near infrared (NIR) wavelengths from tomographic projection data. Image reconstruction is accomplished by solving a system of linear equations derived from transport theory. Reconstruction results using different algebraic solvers are shown for anatomical maps of the breast, derived from magnetic resonance imaging data, containing two simulated pathologies, in which case qualitatively good reconstructions were obtained. Evaluation of magnetic resonance (MR) data to optimize NIR optical tomographic imaging methods and to assess the feasibility of a combined MR-optical measurement scheme is discussed     

Computational medicine: bioelectric field problems

Applications of large-scale computer modeling and simulation to a class of bioelectric field problems in a variety of biomedical research areas, from single cells to full human structures, are described. The authors focus on a specific subset of bioelectric field problems that have applications in electrocardiography and electroencephalography. The physics and physiology of bioelectric volume conductors are introduced. A specific computational example and the authors' view on the future direction of computational medicine are presented