ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / This paper shows the design and testing of a test bed at Morgan State University as part of the development of a Link Dependent Adaptive Radio (LDAR). It shows the integration of variable rate QAM/OFDM modulation and a variable rate Punctured Convolutional Coder. It also shows a dynamic aeronautical channel simulator developed to capture the dynamics of these channels. Performance results are show for combinations of modulation, coding and channel variations that provide motivation for the potential of the LDAR system.

Submitted by Marcia Silva (marcia@latec.uff.br) on 2016-10-10T18:53:23Z No. of bitstreams: 1 Dissert Adriana Vidal França de Carvalho.pdf: 2829879 bytes, checksum: 20647d41336cf9b355d364ab38963b35 (MD5) / Approved for entry into archive by Biblioteca da Escola de Engenharia (bee@ndc.uff.br) on 2017-01-26T13:49:06Z (GMT) No. of bitstreams: 1 Dissert Adriana Vidal França de Carvalho.pdf: 2829879 bytes, checksum: 20647d41336cf9b355d364ab38963b35 (MD5) / Made available in DSpace on 2017-01-26T13:49:06Z (GMT). No. of bitstreams: 1 Dissert Adriana Vidal França de Carvalho.pdf: 2829879 bytes, checksum: 20647d41336cf9b355d364ab38963b35 (MD5) Previous issue date: 2016-04-18 / O impacto na qualidade do ar causado pela emissão de poluentes atmosféricos tem sido um problema ambiental crescente, especialmente nos centros urbanos e nas áreas industriais. O ozônio, formado por reações fotoquímicas, é um dos principais componentes do smog fotoquímico. Devido às suas características oxidantes ele é prejudicial à saúde e ao meio ambiente. Por ser um poluente secundário, o controle dos níveis de ozônio na troposfera deve ser realizado a partir da redução dos seus principais precursores: COVs e óxidos de nitrogênio. Refinarias de petróleo são importantes fontes de COVs, especialmente de emissões fugitivas de componentes de linhas de processo e, portanto, são fontes onde há potencial para reduzir estas emissões. Além disso, as licenças ambientais das refinarias também exigem a redução de emissões fugitivas de COVs. A metodologia LDAR, baseada no uso de um analisador portátil para identificação de vazamentos em componentes de linhas de processo, vem sendo utilizada nos Estados Unidos desde a década de 70 para a redução das emissões fugitivas de COVs em refinarias de petróleo. É uma metodologia bastante intensiva em mão de obra e tem custo elevado, uma vez que exige o monitoramento individual de milhares de componentes existentes em uma planta industrial para a detecção de vazamentos. Porém, estudos mostram que o controle com foco nos grandes vazamentos permite uma redução mais efetiva das emissões fugitivas e com menor custo. A metodologia Smart LDAR, que consiste no uso de imagem ótica de infravermelho para visualização de gases, permite a identificação dos grandes vazamentos, que são os que mais contribuem para as emissões fugitivas, sem que haja necessidade de medição de todos os componentes das linhas de processo. O objetivo desta pesquisa é avaliar as metodologias LDAR (Leak Detection and Repair) e Smart LDAR, utilizadas para o controle de emissões fugitivas de compostos orgânicos voláteis (COVs) em refinaria de petróleo, utilizando o conceito de custo-efetividade. Os resultados obtidos a partir das avaliações realizadas mostraram que a metodologia Smart LDAR tem melhor relação custo efetividade para o controle de emissões fugitivas de COVs em comparação à metodologia LDAR convencional / The impact on air quality caused by air pollutants emissions has proven to be a growing environmental problem, mainly at urban centers and industrial areas. The ozone, formed through photochemical reactions, is the photochemical smog’s major component. Due its oxidizing characteristics, it is harmful to the healthy and to the environment. Due to de fact to be a secondary pollutant, the ozone control in the troposphere must be achieved by reducing emissions from its main precursors: VOCs and nitrogen oxides. Petroleum refineries are significant sources of VOCs, especially of fugitive emissions from process lines’ components, so they are sources with potential to reduce these emissions. Furthermore, the petroleum refineries’ environmental licenses also demand the reduction of VOCs’ fugitive emissions. The LDAR methodology, which is based on the application of a portable analyzer to identify leaks in process lines’ components, has been used in the US since the 70s to reduce VOCs’ fugitive emissions in petroleum refineries. This methodology is quite intensive hand labor and costly, since an industrial plant has thousands of components that must be measured individually to detect leaks. However, studies show that the control focusing on large leaks allows the reduction of fugitive emissions more effectively and with low costs. The methodology known as Smart LDAR, which uses infrared optical image for gas leaks view, has the potential to identify great leaks, that most contribute to the fugitive emissions, without requirement to measure all process lines’ components. The purpose of this research is evaluate the methodologies LDAR (Leak Detection and Repair) and Smart LDAR, used to control volatile organic compounds’ (VOCs) fugitive emissions in petroleum refineries, using the concept of cost-effective analysis. The results obtained from the evaluations of this study showed that the Smart LDAR methodology has the best cost effective relation to control fugitive emissions compared to the LDAR conventional methodology

A comparison of flash parameters from the National Lightning Detection Network (NLDN) is made with data obtained from the Houston Lightning Detection and Ranging II (LDAR) network. This research focuses on relating the peak current and number of strokes in a negative flash (multiplicity) of lightning with the spatial extent and mean altitude of three-dimensional lightning in 1407 flashes as mapped by the LDAR network. It is shown that increasing negative multiplicities over the range two through ten exhibit, on average, a higher flash extent with higher multiplicities. Singlestroke flashes have mean heights of nearly 2 km greater. Higher order multiplicities (2 to 10+) were correlated with mean source heights near 8 km. Increasing multiplicity tends to be associated with greater flash extents increasing more horizontally than vertically with a 50% to 70% increase in flash extent. No obvious relationship between peak current and flash extent was observed. Examining peak current and mean height shows that low current flashes (<10kA) exhibit higher mean heights. However, this may be due to intra-cloud only flashes being reported as cloud to ground events by the NLDN. Bipolar flashes do not show much variation with height and flash extent with the exception of negative-first bipolar flashes, which exhibited mean flash extents twice that of other types. Finally, the flash detection efficiency is 99.7% within 60 km of the network center.

This paper focuses on the design of a simple Time Division Multiple Access (TDMA) signaling structure for the Link Dependent Adaptive Radio (LDAR) prototype wireless radio communication system to meet the timing requirements of the iNET standard. Built for aeronautical telemetry, LDAR adapts its modulation and coding scheme based on the channel condition in real time. In this paper, a simple protocol for transmission of Command Message and Data Message between Ground Station and Test Article is discussed. This protocol includes all analysis for the continuous adaptation of modulation scheme and coding rate to maximize throughput while ensuring a minimum level of link quality. This project was a collaborative effort between Morgan State University and Georgia Tech Research Institute and is a continuation of our previously published work on LDAR.

The NASA Kennedy Space Center (KSC) is situated along the east coast of central Florida, where a high frequency of lightning occurs annually. Although cloud-to-ground (CG) lightning forecasting using radar echoes has been thoroughly analyzed, few studies have examined intracloud (IC) and/or total (IC CG) lightning. In addition to CG lightning, IC flashes are of great concern to KSC launch operations. Four years (2006-2009) of summer (June, July, August) daytime (about 14-00 Z) Weather Surveillance Radar – 1988 Doppler data for Melbourne, FL were analyzed. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to CG lightning data from the National Lightning Detection Network (NLDN), as well as grouped IC flash data acquired from the KSC Lightning Detection and Ranging (LDAR) networks I and II. Pairs of reflectivity values (30, 35, and 40 dBZ) at isothermal levels (-10, -15, -20 and updraft -10 degrees C), as well as a vertically integrated ice (VII) product were used to optimize criteria for radar-based forecasting of both IC and CG lightning within storms. Results indicate that the best radar-derived predictor of CG lightning according to CSI was 25 dBZ at -20 degrees C, while the best reflectivity at isothermal predictor for IC was 25 dBZ at -15 degrees C. Meanwhile, the best VII predictor of CG lightning was the 30th percentile (0.840 kg m-2), while the best VII predictor of IC was the 5th percentile (0.143 kg m-2), or nearly 6 times lower than for CG! VII at both CG and IC initiation was higher than at both CG and IC cessation. VII was also found to be lower at IC occurrence, including at initiation, than at CG occurrence. Seventy-six percent of cells had IC initiation before CG initiation; using the first IC flash as a predictor of CG occurrence also statistically outperformed other predictors of CG lightning. Even though average lead time for using IC as a predictor of CG was only 2.4 minutes, when taking into account automation processing and radar scan time for the other methods, lead times are much more comparable.

Advancement in infrared imaging technology has allowed the thermal imaging to detect and visualize several gases, mostly hydrocarbon gases. In addition, infrared cameras could potentially be used as a non-contact temperature measurement for gas and vapor. However, current application of infrared imaging techniques for gas measurements are still limited due to several uncertainties in their performance parameters. The aim of this research work was to determine the key factors in the application of infrared imaging technology for gas visualization and a non-contact temperature measurement. Furthermore, the concentration profile and emission rate of the gas are predicted by combining the application of the infrared imaging method with gas dispersion modeling. In this research, infrared cameras have been used to visualize liquefied natural gas (LNG) plumes from LNG spills on water. The analyses of the thermograms showed that the apparent temperatures were different from the thermocouple measurement which occurred due to the assumption of that the object emissivity was always equal to unity. The emissivity for pure methane gas and a mixture of methane and atmospheric gases were then evaluated in order to obtain the actual temperature distribution of the gas cloud. The results showed that by including the emissivity value of the gas, the temperature profile of the dispersed gas obtained from a thermal imaging measurement was in good agreement with the measurement using the thermocouples. Furthermore, the temperature distribution of the gas was compared to the concentration of a dispersed LNG vapor cloud to obtain a correlation between the temperature and the concentration of the cloud. Other application of infrared imaging technique was also conducted for leak detection of natural gas from a pipeline. The capability of an infrared camera to detect a fugitive gas leak was combined with the simulation of vapor discharge and dispersion in order to obtain a correlation between the emission rates and the sizes of the gas plume to the minimum detectable concentration. The relationship of the methane gas cloud size to the gas emission rate was highly dependent to the prevailing atmospheric condition. The results showed that the correlation were best to predict the emission rate less than 0.2 kg/s. At higher emission rate, the increase in gas release rate did not change the size of the cloud significantly.

During the last two decades, innovations that contribute to sustainable development has received increasing attention in the markets and academia. The diffusion of sustainable innovations is a key element in society’s transformation toward a greener and more sustainable economy. Within industries that utilize industrial gases in their operations, there are thousands of fugitive emission sources that puts strain on the safety of the plant and the personnel. As most gases are combustible and hazardous to humans and the environment, these companies must have effective leak detection and repair (LDAR) programs. In recent years, a new gas detection technology called Optical Gas Imaging have emerged which can identify gas compounds safer and more efficient compared to older leak detection technologies. However, the rate of diffusion of the innovation has been slow and limited to oil and gas industries, even though many other industries such as steel, paper and pulp and chemical industries utilize gases as well. As such, this research has aimed to identify factors that influence the adoption of sustainable innovations within gas-utilizing industries. The qualitative data was gathered through semi structured interviews with gas-utilizing companies in Sweden and analyzed with interpretive methods. The results show that regulatory factors are a strong driver for the diffusion of sustainable innovations while characteristics of price, availability and type of innovationdecision works as barriers. The generated knowledge may contribute on how innovators of a sustainable innovations can overcome these barriers and improve the rate of adoption of sustainable innovations. / Under de senaste två decennierna har innovationer som bidrar till hållbar utveckling fått ökad uppmärksamhet på marknaden och inom forskningen. Diffusionen av hållbara innovationer är ett viktig del av samhällets omvandling mot ett mer hållbart samhälle. Inom branscher som använder industriella gaser i sin verksamhet finns det tusentals flyktiga utsläppskällor som belastar anläggningen och personalens säkerhet. Eftersom de flesta gaser är brännbara och farliga för människor och miljö, är det viktigt att dessa företag har effektiva läckedetekterings- och reparationsprogram (LDAR). Under de senaste åren har en ny gasdetekteringsteknologi, Optical Gas Imaging, kommit fram som kan identifiera gasföreningar säkrare och effektivare jämfört med äldre tekniker för läckedetektering. Däremot, har diffusionsgraden för innovationen varit långsam och begränsad till olje- och gasindustrin, även om många andra industrier så som stål, papper och massa, och kemiska industrier också använder gaser som energi. Därför har syftet med denna stuie varit att identifiera faktorer som påverkar diffusionen av hållbara innovationer inom industrier som använder gaser. Den kvalitativa datan samlades in genom semistrukturerade intervjuer med företag i Sverige som använder gaser, där datan analyserades med tolkningsmetoder. Resultatet visar att lagar och regler är en stark drivkraft för diffusionen av hållbara innovationer medan innovationsegenskaper såsom ”pris” och nyckelfaktorerna ”tillgänglighet” och ”innovationsbeslut” agerar som hinder. Den genererade kunskapen från denna studie kan bidra till hur en hållbar innovationskapare kan åtgärda dessa hinder och förbättra dess diffusion i marknaden.