Nonlinear Dynamics of Beams with Stochastic Parameter Variations

The aim of this paper is to investigate the steady state response of beams under the action of random support motions. The study is of relevance in the context of earthquake response of extended land based structures such as pipelines and long span bridges, and, secondary systems such as piping networks in nuclear power plant installations. The following complicating features are accounted for in the response analysis: (a) differential support motions: this is characterized in terms of cross power spectral density functions associated with distinct support motions, (b) nonlinear support conditions, and (c) stochastically inhomogeneous stiffness and mass variations of the beam structure; questions on non-Gaussian models for these variations are considered. The method of stochastic finite elements is combined with equivalent linearization technique and Monte Carlo simulations to obtain response moments.

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

An improved sapce phasor based current hysteresis controller with reduced switching frequency variations using variable parabolic bands

A current error space phasor based simple hysteresis controller is proposed in this paper to control the switching frequency variation in two-level pulsewidth-modulation (PWM) inverter-fed induction motor (IM) drives. A parabolic boundary for the current error space phasor is suggested for the first time to obtain the switching frequency spectrum for output voltage with hysteresis controller similar to the constant switching frequency voltage-controlled space vector PWM-based IM drive. A novel concept of online variation of this parabolic boundary, which depends on the operating speed of motor, is presented. A generalized technique that determines the set of unique parabolic boundaries for a two-level inverter feeding any given induction motor is described. The sector change logic is self-adaptive and is capable of taking the drive up to the six-step mode if needed. Steady-state and transient performance of proposed controller is experimentally verified on a 3.7-kW IM drive in the entire speed range. Close resemblance of the simulation and experimental results is shown.

Inverse models to analyze the spatiotemporal variations of chemical weathering fluxes in a granito-gneissic watershed: Mule Hole, South India

Water-rock reactions are driven by the influx of water, which are out of equilibrium with the mineral assemblage in the rock. Here a mass balance approach is adopted to quantify these reactions. Based on field experiments carried out in a granito-gneissic small experimental watershed (SEW), Mule Hole SEW (similar to 4.5 km(2)), quartz, oligoclase, sericite, epidote and chlorite are identified as the basic primary minerals while kaolinite, goethite and smectite are identified as the secondary minerals. Observed groundwater chemistry is used to determine the weathering rates, in terms of `Mass Transfer Coefficients' (MTCs), of both primary and secondary minerals. Weathering rates for primary and secondary minerals are quantified in two steps. In the first step, top red soil is analyzed considering precipitation chemistry as initial phase and water chemistry of seepage flow as final phase. In the second step, minerals present in the saprolite layer are analyzed considering groundwater chemistry as the output phase. Weathering rates thus obtained are converted into weathering fluxes (Q(weathering)) using the recharge quantity. Spatial variability in the mineralogy observed among the thirteen wells of Mule Hole SEW is observed to be reflected in the MTC results and thus in the weathering fluxes. Weathering rates of the minerals in this silicate system varied from few 10 mu mol/L (in case of biotite) to 1000 s of micromoles per liter (calcite). Similarly, fluxes of biotite are observed to be least (7 +/- 5 mol/ha/yr) while those of calcite are highest (1265 791 mol/ha/yr). Further, the fluxes determined annually for all the minerals are observed to be within the bandwidth of the standard deviation of these fluxes. Variations in these annual fluxes are indicating the variations in the precipitation. Hence, the standard deviation indicated the temporal variations in the fluxes, which might be due to the variations in the annual rainfall. Thus, the methodology adopted defines an inverse way of determining weathering fluxes, which mainly contribute to the groundwater concentration. (C) 2011 Elsevier B.V. All rights reserved.

Modeling of the Effects of Process Variations on Circuit Delay at 65nm

A novel methodology for modeling the effects of process variations on circuit delay performance is proposed by relating the variations in process parameters to variations in delay metric of a complex digital circuit. The delay of a 2-input NAND gate with 65nm gate length transistors is extensively characterized by mixed-mode simulations which is then used as a library element. The variation in saturation current Ionat the device level, and the variation in rising/falling edge stage delay for the NAND gate at the circuit level, are taken as performance metrics. A 4-bit x 4-bit Wallace tree multiplier circuit is used as a representative combinational circuit to demonstrate the proposed methodology. The variation in the multiplier delay is characterized, to obtain delay distributions, by an extensive Monte Carlo analysis. An analytical model based on CV/I metric is proposed, to extend this methodology for a generic technology library with a variety of library elements.

Mechanism design problems in carbon economics

Reduction of carbon emissions is of paramount importance in the context of global warming and climate change. Countries and global companies are now engaged in understanding systematic ways of solving carbon economics problems, aimed ultimately at achieving well defined emission targets. This paper proposes mechanism design as an approach to solving carbon economics problems. The paper first introduces carbon economics issues in the world today and next focuses on carbon economics problems facing global industries. The paper identifies four problems faced by global industries: carbon credit allocation (CCA), carbon credit buying (CCB), carbon credit selling (CCS), and carbon credit exchange (CCE). It is argued that these problems are best addressed as mechanism design problems. The discipline of mechanism design is founded on game theory and is concerned with settings where a social planner faces the problem of aggregating the announced preferences of multiple agents into a collective decision, when the actual preferences are not known publicly. The paper provides an overview of mechanism design and presents the challenges involved in designing mechanisms with desirable properties. To illustrate the application of mechanism design in carbon economics,the paper describes in detail one specific problem, the carbon credit allocation problem.

Monitoring of seasonal snow cover in Bhutan using remote sensing technique

All major rivers in Bhutan depend on snowmelt for discharge. Therefore, changes in snow cover due to climate change can influence distribution and availability of water. However, information about distribution of seasonal snow cover in Bhutan is not available. The MODIS snow product was used to study snow cover status and trends in Bhutan. Average snow cover area (SCA) of Bhutan estimated for the period 2002 to 2010 was 9030 sq. km, about 25.5% of the total land area. SCA trend of Bhutan for the period 2002-2010 was found to decrease (-3.27 +/- 1.28%). The average SCA for winter was 14,485 sq. km (37.7%), for spring 7411 sq. km (19.3%), for summer 4326 sq. km (11.2%), and for autumn 7788 sq. km (20.2%), mostly distributed in the elevation range 2500-6000 m amsl. Interannual and seasonal SCA trend both showed a decline, although it was not statistically significant for all sub-basins. Pho Chu sub-basin with 19.5% of the total average SCA had the highest average SCA. The rate of increase of SCA for every 100 m elevation was the highest (2.5%) in the Pa Chu sub-basin. The coefficient of variance of 1.27 indicates high variability of SCA in winter.