Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Effects of hot carrier induced interface state generation insubmicron LDD MOSFET's

A two-dimensional numerical simulation including a new interface state generation model has been developed to study the performance variation of a LDD MOSFET after a dc voltage stress. The spatial distribution of hot carrier induced interface states is calculated with a breaking silicon-hydrogen bond model. Mobility degradation and reduction of conduction charge due to interface traps are considered. A 0.6 μm LDD MOSFET was fabricated. The drain current degradation and the substrate current variation after a stress were characterized to compare the simulation. A reduction of the substrate current at V_g ≃0.5 V_d in a stressed device was observed from both the measurement and the simulation. Our study reveals that the reduction is attributed to a distance between a maximum channel electric field and generated interface states     

P-N double quantum well resonant interband tunneling diode withpeak-to-valley current ratio of 144 at room temperature

The current-voltage characteristics of the P-N double quantum well resonant interband tunneling (RIT) diodes in InAlAs-InGaAs system have been improved in this letter. The peak-to-valley current ratio (PVCR) is as high as 144 at room temperature. As we know, this is the highest room temperature PVCR ever reported in any tunneling devices. Moreover, the influence of the central barrier thickness varying from 10 Å to 30 Å on the device characteristics is also studied     

Integration of mobile vehicles for automated material handlingusing Profibus and IEEE 802.11 networks

This paper focuses on a method to integrate mobile devices such as a mobile robot, automated guided vehicle, and unmanned container transporter to form an automated material handling system. In this paper, the stationary devices are connected via a Profibus network while the mobile devices are communicating via an IEEE 802.11 wireless LAN. In order to integrate these two networks, a protocol converter is developed on a PC platform that runs two interacting processes with shared internal buffers. The protocol converter performs a role of translator between two different protocols by converting the format of a data frame. In addition to this basic conversion function, the protocol converter has a virtual polling algorithm to reduce the uncertainty involved in accessing the wireless network. Finally, the integrated network. of Profibus and IEEE 802.11 is experimentally evaluated for its data latency and throughput, which shows the feasibility of the Profibus-IEEE 802.11 network for industrial applications involving mobile devices     

Low RF noise and power loss for ion-implanted Si having an improved implantation process

Very-low-transmission line noise of <0.25 dB at 18 GHz and low power loss /spl les/0.6 dB at 110 GHz have been measured on transmission lines fabricated on proton-implanted Si. In contrast, a standard Si substrate gave much higher noise of 2.5 dB and worse power loss of 5 dB. The good RF integrity of proton-implanted Si results from the high isolation impedance to ground, as analyzed by an equivalent circuit model. The proton implantation is also done after forming the transmission lines at a reduced implantation energy of /spl sim/4 MeV. This enables easier process integration into current VLSI technology.     

Automation model of sewerage rehabilitation planning.

The major steps of sewerage rehabilitation include inspection of sewerage, assessment of structural conditions, computation of structural condition grades, and determination of rehabilitation methods and materials. Conventionally, sewerage rehabilitation planning relies on experts with professional background that is tedious and time-consuming. This paper proposes an automation model of planning optimal sewerage rehabilitation strategies for the sewer system by integrating image process, clustering technology, optimization, and visualization display. Firstly, image processing techniques, such as wavelet transformation and co-occurrence features extraction, were employed to extract various characteristics of structural failures from CCTV inspection images. Secondly, a classification neural network was established to automatically interpret the structural conditions by comparing the extracted features with the typical failures in a databank. Then, to achieve optimal rehabilitation efficiency, a genetic algorithm was used to determine appropriate rehabilitation methods and substitution materials for the pipe sections with a risk of mal-function and even collapse. Finally, the result from the automation model can be visualized in a geographic information system in which essential information of the sewer system and sewerage rehabilitation plans are graphically displayed. For demonstration, the automation model of optimal sewerage rehabilitation planning was applied to a sewer system in east Taichung, Chinese Taiwan.     

Modeling Temperature in Coupled Electrical and Thermal Simulations of the Electroconsolidation® Process

Electroconsolidation® is a process for densifying complex-shaped parts by using electrically conductive particulate solids as a pressure-transmitting medium. The part is immersed in a bed of the particulate medium contained in a die chamber. Sintering temperature is achieved by resistive heating of the medium while applying compaction pressure. The process is capable of ultrahigh temperatures and short cycle times and offers the potential for low processing costs.

Control of the process and selection of process conditions require knowledge of the temperatures within the die. Temperature gradients exist because of the high heating rate and because of variations of density and electrical resistivity of the medium due to the presence of the part. Direct measurement of temperature with thermocouples or other conventional means is impractical because of the high temperatures, high currents, and high pressures that are involved. Therefore, a computer model was developed to predict temperature as a function of time and applied voltage for any location in the die. The computer model is composed of three parts: a geometrical model to approximate the density and resistivity variations in the medium, a finite-element model to calculate the rate of resistive heating within each element, and a finite-difference model to calculate the temperature distribution based on solution of the heat-transfer equations. Predicted temperatures have been shown to be in excellent agreement with measurements, and numerical simulation provided encouraging consistency and reasonably accurate predictions of temperature profiles within the die. The model demonstrated the feasibility of a new process to achieve simultaneous application of pressure and heat to powder densification in Electroconsolidation.     

The Effect of Run Time on the Inter-Unit Uniformity of Aqueous Film Coating Applied to Glass Beads in a Hi-Coater

Coating experiments were conducted to assess the inter-unit uniformity using individual weight gains of glass beads. Applying more aqueous film coating and prolonging the film-coating process by diluting the coating suspension did improve the coating variability among glass beads. It appears that run time is an important underlying factor which affecting the inter-unit coating uniformity.     

On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.