A Wide Tuning Range Voltage Controlled Oscillator with a High Tunable Active Inductor

This paper presents a wide tuning range CMOS voltage controlled oscillator (VCO) with a high-tunable active inductor circuit. In this VCO circuit, the coarse frequency is achieved by tuning the integrated active inductor circuit. The VCO circuit is designed in 0.18  \(\upmu \hbox {m}\) CMOS process and simulated with Cadence Spectra. The simulation results show the frequency tuning range from 120 MHz to 2 GHz resulting in a tuning range of 94 %. The phase noise variation is from \(-\) 80 to \(-\) 90 dBc/Hz at a 1 MHz frequency offset, and output power variation is from \(-\) 4.7 to \(+\) 11.5 dBm. The active inductor power consumption is 2.2 mW and the total power dissipation is 7 mW from a 1.8 V DC power supply. By comparing the proposed VCO circuit with the general VCO topology, the results show that this VCO architecture by using the novel, high-tunable and low power active inductor circuit, presents a better performance regarding low chip size, low power consumption, high tuning range and high output power.     

Recent Advances on Vibration Control of Structures Under Dynamic Loading

In this paper, a review of recent journal articles on passive, active, semi-active, and hybrid vibration control of structures subjected to dynamic loading is presented. Passive systems reviewed include tuned mass damper (TMD), tuned liquid column damper (TLCD), tuned liquid column ball damper (TLCBD), circular TLCD (CTLCD), and pendulum TLCD (PTLCD). Active control systems include active tuned mass dampers (ATMD) and piezoelectric actuators. Semi-active systems include magnetorheological (MR) damper, negative stiffness devices (NSD), magneto-rheological damper TMD (MR-TMD), variable stiffness semi-active TMD (VS-STMD), variable damper STMD (VD-STMD), and recentering variable friction device (RVFD). Hybrid systems include active base isolation system and semi-active MR dampers with nonlinear base isolators. The current frontier of research is semi-active control of structures as well hybridization of various control systems. The problem is complex requiring integration of several different hardware and software technologies with structural design such as smart materials, adaptive dampers, actuators, sensors, and control and signal processing algorithms. This complexity also makes it an exciting area of research and development.     

Object-Oriented Model for Freeway Work Zone Capacity and Queue Delay Estimation

Abstract:   Existing computer models used to estimate queue delay upstream of the work zone have a number of shortcomings. They do not provide any model to estimate work zone capacity, which has a significant impact on the congestion and traffic queue delays. They cannot be used to perform scenario analysis for work zones with various characteristics such as work zone layout, number of closed lanes, work intensity, and work time. In this article, an object-oriented (OO) model is presented for freeway work zone capacity and queue delay and length estimation. The model is implemented into an interactive software system, called IntelliZone, using Microsoft Foundation Classes (MFC) and a hierarchy of multiple specialized frameworks. A three-layer application architecture is created to separate the application functions and classes from MFC classes. The high-level application domain layer is divided into packages. IntelliZone's capacity estimation engine is based on pattern recognition and neural network models incorporating a large number of factors impacting the work zone capacity. This research provides the foundation for a new generation of advanced decision support systems for effective management of traffic at work zones .     

Hybrid CPN–Neural Dynamics Model for Discrete Optimization of Steel Structures

Abstract: In practical design of steel structures, the designer usually must choose from a limited number of commercially available shapes such as the widely used wide flange shapes. In this article, we present a hybrid counterpropagation-neural dynamics model and a new neural network topology for discrete optimization of large structures subjected to the AISC ASD specifications. The constrained structural optimization problem is formulated in terms of a neural dynamics model with constraint and variable layers. The counterpropagation part of the model consists of the competition and interpolation layers. The CPN network is trained to learn the relationship between the cross-sectional area and the radius of gyration of the available sections. The robustness of the hybrid computational model is demonstrated by application to three examples representing the exterior envelope of high-rise and super-high-rise steel building structures, including a 147-story structure with 8904 members.     

Life‐cycle cost optimization of steel structures

This article addresses the life‐cycle cost optimization of steel structures. The main factors influencing the life‐cycle cost of a structure are delineated and their effects on various cost functions are discussed. A four‐criteria optimization model is presented for the life‐cycle cost optimization of steel structures. These criteria are (i) select discrete commercially available sections with the lowest cost, (ii) select commercially available sections with the lightest weight, (iii) select the minimum number of different types of commercially available sections, and (iv) select commercially available sections with the minimum total perimeter length. The last criterion models a representative type of cost incurred over the life of the structure, that is, preventative maintenance in the form of periodic painting of an exposed steel structure to avoid corrosion. The life‐cycle cost optimization model is based on fuzzy logic with the goal of formalizing the life‐cycle design process but with some input from the design engineer through introduction of weighting coefficients reflecting the relative importance of various criteria. The model is applied to a large steel structure with over 3300 members. Copyright © 2002 John Wiley & Sons, Ltd.     

Wavelet Packet-Autocorrelation Function Method for Traffic Flow Pattern Analysis

Abstract:   Accurate and timely forecasting of traffic flow is of paramount importance for effective management of traffic congestion in intelligent transportation systems. A detailed understanding of the properties of traffic flow is essential for building a reliable forecasting model. The discrete wavelet packet transform (DWPT) provides more coefficients than the conventional discrete wavelet transform (DWT), representing additional subtle details of a signal. In wavelet multiresolution analysis, an important decision is the selection of the decomposition level. In this research, the statistical autocorrelation function (ACF) is proposed for the selection of the decomposition level in wavelet multiresolution analysis of traffic flow time series. A hybrid wavelet packet-ACF method is proposed for analysis of traffic flow time series and determining its self-similar, singular, and fractal properties. A DWPT-based approach combined with a wavelet coefficients penalization scheme and soft thresholding is presented for denoising the traffic flow. The proposed methodology provides a powerful tool in removing the noise and identifying singularities in the traffic flow. The methods created in this research are of value in developing accurate traffic-forecasting models .     

A Reconfigurable Low-Noise Amplifier Using a Tunable Active Inductor for Multistandard Receivers

A reconfigurable low-noise amplifier (LNA) based on a high-value active inductor (AI) is presented in this paper. Instead of using a passive on-chip inductor, a high-value on-chip inductor with a wide tuning range is used in this circuit and results in a decrease in the physical silicon area when compared to a passive inductor-based implementation. The LNA is a common source cascade amplifier with RC feedback. A tunable active inductor is used as the amplifier output load, and for input and output impedance matching, a source follower with an RC network is used to provide a 50 Ω impedance. The amplifier circuit has been designed in 0.18 µm CMOS process and simulated using the Cadence Spectra circuit simulator. The simulation results show a reconfigurable frequency from 0.8 to 2.5 GHz, and tuning of the frequency band is achieved by using a CMOS voltage controlled variable resistor. For a selected 1.5 GHz frequency band, simulation results show S ₂₁ (Gain) of 22 dB, S ₁₁ of ?18 dB, S ₂₂ of ?16 dB, NF of 3.02 dB, and a minimum NF (NFmin) of 1.7 dB. Power dissipation is 19.6 mW using a 1.8 V dc power supply. The total LNA physical silicon area is (200×150) µm².     

Impacts of Receding of the Lakes Located in the Arid and Semi-arid Areas on the Coastal Groundwater: Integrated Modeling and Experimental Study

The dropping of the water level of the lakes located in the arid lands leads to salt concentration increase. In this study, a combined experimental-computational method is developed to explore the effect of seawater concentration on the elevation of groundwater table and the rate of saltwater intrusion, while the lake water level is dropping. At the laboratory tank scale, we have collected experimental data by varying the saltwater concentration by 2.0 and 2.5 times its initial value while measuring the height of the groundwater table. Our simulation has shown an unexpected increase in height of groundwater by 5.0 and 13.0% relative to the head difference at the boundaries of the domain. Also, the intrusion rate of saltwater wedge increased by 2.0 and 3.0 times, respectively. We have used the verified model for a field state and found that if density variations are neglected in simulation, the calculated groundwater level is affected more than 2 times in response to fluctuation of lake water level (relative to simulations by including the effect of fluid density changes). Based on the results density variations can counteract; even reverse, the effect of water table changes. Remarkably, our simulations have shown that despite a severe decrease in the water level of a saline lake over time, the saltwater wedge has indeed intruded further because of the substantial increase in the density of the lake water due to the rising salinity. Based on the findings, to reach a reasonable result in the study of interaction between saline water of shrinking lakes with coastal groundwater, saltwater concentration as well as saline water density in the modeling must be considered.