Method for detection and correction of errors in speech pitch period estimates

A method of detecting and correcting received values of a pitch period estimate of a speech signal for use in a speech coder or the like. An average is calculated of the nonzero values of received pitch period estimate since the previous reset. If a current pitch period estimate is within a range of 0.75 to 1.25 times the average, it is assumed correct, while if not, a correction process is carried out. If correction is required successively for more than a preset number of times, which will most likely occur when the speaker changes, the average is discarded and a new average calculated

Sonic Layer Depth estimated from XBT temperatures and climatological salinities

Sonic layer depth (SLD) plays an important role in antisubmarine warfare in terms of identifying the shadow zones for submarine safe parking. SLD is estimated from sound velocity profiles (SVP) which is in turn obtained from temperature and salinity (T/S) profiles. Given the limited availability of salinity data in comparison to temperature, SVPs need to be obtained from alternate methods. In the present work, to make use of voluminous temperature data sets from XBT, CTD and other source for estimating SLD, we propose a method of utilizing XBT measurements and World Ocean Atlas climatological salinities to compute SVP and then extract SLD. This approach is demonstrated by utilizing T/S data from Argo floats in the Arabian Sea (40° – 80° E and 0 – 30° N). SLD is estimated from SVP obtained from Argo T/S profiles first and again by replacing the Argo salinity with climatological salinity. It is found that in more than 90% of cases, SLD matched exactly, with the root mean square deviation ranging from 3 – 12 m with an average of 7 m

Field Deployment and Integration of Wireless Communication & Operation Support System for the Landscape Irrigation Runoff Mitigation System

The study of water conservation technologies is critically important due to the rapid growth in urban population leading to a shortage in potable water supplies throughout the world. Current water supplies are not expected to meet the water demand in the coming decades; this could seriously affect human lives and socio-economic stability. About 30 percent of the current municipal supplies are being used for outdoor irrigation such as gardening and landscaping. These numbers are increasing due to the increase in urban population. Due to the current inefficient or improper landscape irrigation practices, substantial amounts of water are lost in the form of runoff or due to evaporation. Runoff occurs when the irrigation precipitation rate exceeds the infiltration rate of the soil, which depends on the soil and site characteristics such as soil type and the slope of the site. Runoff being an obvious water wastage, it also poses a great problem to the environment with its potential for transporting fertilizers and pesticides into storm sewers and, eventually, surface waters. Thus, this study focuses on designing a smart operational support system for landscape irrigation that has the potential to reduce runoff and also decrease water losses in the form of evaporation. The system consists of two main units, the landscape irrigation runoff mitigation system (LIRMS) and an operational support system (OSS). The combined system is referred to as the second-generation LIRMS. The LIRMS is installed at the border of a field/lawn. The LIRMS consists of a central controller unit and a runoff sensor. Based on the feedback from the runoff sensor, the controller unit pauses and resumes irrigation as needed in order to reduce runoff. The main purpose of OSS is to automate the scheduling of the irrigation process. A multilayer perceptron based OSS was designed and implemented on a dedicated web-server. The OSS processes historical irrigation data and the environmental/weather data to choose an optimal schedule to irrigate on a given day. The OSS aims to reduce irrigation water losses due to natural environmental factors such as evaporation and rain. A wireless communication link is established between LIRMS and OSS for monitoring and analyzing irrigation events. The second-generation LIRMS was installed in the Texas A&M Turfgrass Research Field Laboratory, College Station, TX for performing irrigation tests. The preliminary results show that the average soil wetting efficiency has increased with the use of the operational support system when compared to previous tests performed without the operational support system. Also the results suggest that the second generation LIRMS has comparable runoff reductions when compared to the first-generation LIRMS. Yet, more tests are required to quantify the overall water savings

Characterization of wind power resource in the United States

Wind resource in the continental and offshore United States has been reconstructed and characterized using metrics that describe, apart from abundance, its availability, persistence and intermittency. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) boundary layer flux data has been used to construct wind profile at 50 m, 80 m, 100 m, 120 m turbine hub heights. The wind power density (WPD) estimates at 50 m are qualitatively similar to those in the US wind atlas developed by the National Renewable Energy Laboratory (NREL), but quantitatively a class less in some regions, but are within the limits of uncertainty. The wind speeds at 80 m were quantitatively and qualitatively close to the NREL wind map. The possible reasons for overestimation by NREL have been discussed. For long tailed distributions like those of the WPD, the mean is an overestimation and median is suggested for summary representation of the wind resource. The impact of raising the wind turbine hub height on metrics of abundance, persistence, variability and intermittency is analyzed. There is a general increase in availability and abundance of wind resource but there is an increase in intermittency in terms of level crossing rate in low resource regions.Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Chang

The Potential Wind Power Resource in Australia: A New Perspective

Australia’s wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia’s electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia’s energy mix, this study sets out to analyze and interpret the nature of Australia’s wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast’s electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it’s intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale.Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Chang

Technical Report on Argo Data Processing

In this document, details of Argo program, data acquisition system and data processing are documented to serve as a reference for Argo data. Several plots are included to serve as quick reference. The data will be useful to describe major thermo-haline features in the Indian Ocean. In conjunction with other sources of data from various platforms, the data can be used for studying meso-scale structure and dynamics of upper ocean process. At smaller scales, the float temperature and salinity data will be useful to document the seasonal to intra seasonal variability of temperature, salinity and various other derived parameters. This temperature and salinity data can be useful for updating the climatology and for assimilation into ocean model for better forecasts

Aerosol-Cloud interactions : a new perspective in precipitation enhancement

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 171-184).Increased industrialization and human activity modified the atmospheric aerosol composition and size-distribution during the last several decades. This has affected the structure and evolution of clouds, and precipitation from them. The processes and mechanisms by which clouds and precipitation are modified by changes in aerosol composition and size-distribution are very intricate. The objective of this thesis is to improve the understanding of the processes and mechanisms through which the changes in aerosol concentrations impact the evolution of deep convective clouds and precipitation formation. We develop a new coupled model in which a very detailed model of aerosol activation is coupled to a three-dimensional cloud resolving model. This coupled model can accurately represent different kinds of aerosol populations. This coupled model is used to investigate the impact of changing aerosol concentrations on the dynamics, microphysical evolution and precipitation formation in deep convective clouds. We examine the theories of aerosol activation, and the representation of aerosol activation in cloud models. The limitations of the extant methods of representation of aerosol activation in cloud models are evaluated. Then we descibe the components of the coupled model - Modified Eulerian and Lagrangian Aerosol Model (MELAM) and the Cloud Resolving Model (CRM). The features of these two component models with respect to aersol activation and cloud formation are discussed. The evaluation of the coupled model by simulation of a deep convertive event observed during the INDian Ocean EXperiment (INDOEX) by statistcal comparison of observed and simulated cloud fields shows that the coupled model can simulate deep convective events reasonably well. We present a study of the senstivity of the model to initial thermodynamic conditions (CAPE). Different initial thermodynamic conditons sampled during the INDOEX are used to initialize the coupled model and, the structure and evolution of the deep convective event are discussed. The study sheds new light on the respone of deep convection to CAPE. It is found that when the atmosphere has moderate CAPE, the precipitation forming processes are very active and when the CAPE is (cont.) low or high, they are comparatively less efficient.As the most important part of our study, we examine the response of deep convection to changing initial aerosol concentration. Different aerosol concentrations from those representing pristine to polluted atmospheres are considered. We look at the buoyancy of the cloud and the microphysical evolution. It is found that the dynamics and microphysics are tightly coupled and we infer that to understand aerosol-cloud interactions in deep convective clouds, both - dynamics and microphysics - and their interaction have to be taken into consideration. Our results show that the response of a deep convective cloud to changing aerosol concentration is very different from the much well understood reponse of shallow clouds or small cumulus clouds. In general, increase in aerosol concentratin is seen to invigorate convection and lead to greater condensate. Although the cloud droplet size decreases, collision-coalescence is not completely inefficient. The precipitation in high aerosol regime is seen to occure in short spells of intense rain. A very interesting anomalous response of deep convection to initial aerosol concentration is observed at intermediate aerosol concentrations. The cloud lifetime, and precipitation are seen to increase in this regime. A possible mechanism to explain this anomalous behavior is proposed and the available circumstantial support for the mechanism from extant observations is presented. It is proposed that the efficient collection of rain and cloud droplets by ice and graupel particles in the middle troposphere is primarily responsible for this increased cloud lifetime and precipitation.by Udaya Bhaskar Gunturu.Ph.D

The Potential Wind Power Resource in Australia: A New Perspective

Australia is considered to have very good wind resources, and the utilization of this renewable energy resource is increasing. Wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia’s electricity generation in 2030. This study uses a recently published methodology to address the limitations of previous wind resource analyses, and frames the nature of Australia’s wind resources from the perspective of economic viability, using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes whether these differ with higher wind turbine hub heights. We also assess the extent to which wind intermittency can potentially be mitigated by the aggregation of geographically dispersed wind farms. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast’s electricity grid and large population centers, and often are not connected or located near enough to high capacity electricity infrastructure, all of which would decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate its intermittency through aggregation.The authors gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a number of federal agencies and industrial sponsors including US Department of Energy grant DE-FG02-94ER61937

Modeling and Optimization of Product Profiles in Biomass Pyrolysis

Biomass feed comes in many varieties, but have common chief constituents of hemicellulose, cellulose, and lignin. As the relative proportions of these constituents may vary, customization of the pyrolysis process conditions is required to produce a desired product profile. By recognizing the sources of variation, the reactor settings may be intelligently controlled, to achieve optimal operation. These considerations include biomass classification, feed rate, moisture content, particle size, and inter-particle thermal gradients (which arise during pyrolysis based on heating rate and temperature distribution). This chapter addresses the optimization of product profiles during biomass pyrolysis from a modeling perspective. Fundamental models for packed bed and fluidized bed pyrolyzers are developed, using kinetics from existing literature. The proposed optimization approach (inclusive of the kinetic and process models) can guide practical achievement of desired product profiles of the biomass pyrolysis process

Inferring mixed-layer depth variability from Argo observations in the western Indian Ocean

The seasonal and spatial variability of mixed layer depth (MLD) was examined in the Western Indian Ocean (WIO) (30E – 80E and 10S – 30N) for three consecutive years starting from June 2002 – May 2005 using Argo temperature and salinity (T/S) profiles. These were compared with MLD estimates from World Ocean Atlas 2001 (WOA01) T/S data. Temporal and spatial variability of MLD estimated from Argo T/S profiles were found to correspond well with the MLD obtained from WOA01 T/S data. However, slight deviations in the form of months of occurrence of minima and maxima MLDs were observed. MLD from WOA01 climatology is underestimated compared to MLD from Argo for almost the entire three years of study. It is also observed that MLD variability features as brought out by both the data sets followed the dynamics that govern the mixed layer variability in this region