993 resultados para Barometric pressure sensor, Setra CS100


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Snow height was measured by the Snow Depth Buoy 2013S8, an autonomous platform, drifting on Antarctic sea ice, deployed during POLARSTERN cruise ANT-XXIX/6 (PS81). The resulting time series describes the evolution of snow height as a function of place and time between 2013-07-09 and 2014-01-05 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on first year ice. In addition to snow height, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow height occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). Records without any snow height may still be used for sea ice drift analyses.

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Snow height was measured by the Snow Depth Buoy 2013S7, an autonomous platform, drifting on Antarctic sea ice, deployed during POLARSTERN cruise ANT-XXIX/6 (PS81). The resulting time series describes the evolution of snow height as a function of place and time between 2013-07-06 and 2013-09-13 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on first year ice. In addition to snow height, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow height occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). Records without any snow height may still be used for sea ice drift analyses.

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Snow height was measured by the Snow Depth Buoy 2014S15, an autonomous platform, drifting on Arctic sea ice, deployed during POLARSTERN cruise ARK-XXVIII/4 (PS87). The resulting time series describes the evolution of snow depth as a function of place and time between 2014-08-29 and 2014-12-31 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). The buoy was installed on multi year ice. In addition to snow depth, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Records without any snow depth may still be used for sea ice drift analyses. Note: This data set contains only relative changes in snow depth, because no initial readings of absolute snow depth are available.

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Snow height was measured by the Snow Depth Buoy 2014S17, an autonomous platform, drifting on Antarctic sea ice, deployed during POLARSTERN cruise ANT-XXX/2 (PS89). The resulting time series describes the evolution of snow depth as a function of place and time between 2014-12-20 and 2015-02-01 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on first year ice. In addition to snow depth, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow depth occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). In this data set, diurnal variations occur in the data set, although the sonic readings were compensated for temperature changes. Records without any snow depth may still be used for sea ice drift analyses.

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Snow height was measured by the Snow Depth Buoy 2014S24, an autonomous platform, installed close to Neumayer III Base, Antarctic during Antarctic Fast Ice Network 2014 (AFIN 2014). The resulting time series describes the evolution of snow depth as a function of place and time between 2014-03-07 and 2014-05-16 in sample intervals of 1 hour. The Snow Depth Buoy consists of four independent sonar measurements representing the area (approx. 10 m**2) around the buoy. The buoy was installed on the ice shelf. In addition to snow depth, geographic position (GPS), barometric pressure, air temperature, and ice surface temperature were measured. Negative values of snow depth occur if surface ablation continues into the sea ice. Thus, these measurements describe the position of the sea ice surface relative to the original snow-ice interface. Differences between single sensors indicate small-scale variability of the snow pack around the buoy. The data set has been processed, including the removal of obvious inconsistencies (missing values). Records without any snow depth may still be used for sea ice drift analyses. Note: This data set contains only relative changes in snow depth, because no initial readings of absolute snow depth are available.

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El reciente desarrollo de la instrumentación diseñada para proporcionar datos de aceleraciones y movimientos del cajón número 8 del dique Botafoc (Ibiza), perteneciente a la Autoridad Portuaria de Baleares (Puertos del Estado), en conjunción con datos procedentes de una instrumentación compuesta por sensores de presión existente en el paramento vertical, proporciona un novedoso medio para analizar la respuesta estructural del cajón, no sólo ante la acción del oleaje, sino también ante los efectos producidos por las maniobras de los buques en el muelle. Como la medición de estas aceleraciones y velocidades angulares se hace a altas frecuencias (de hasta 400 Hz), podemos proporcionar datos válidos acerca del comportamiento estructural y de los movimientos reales del cajón, tratando de correlacionar este comportamiento con los resultados obtenidos por el grupo de trabajo PROVERBS (Probabilistic design of vertical breakwaters, MAST III EU Programme), y generando una base de datos estadística de movimientos que deben considerarse para enriquecer los conocimientos en este ámbito. Además, la posibilidad de registrar los efectos causados por las maniobras de atraquedesatraque-estancia de los buques, abre un nuevo punto de vista al diseño estructural de un dique-muelle, siendo también de gran interés para los diseñadores de obras marítimas y para la correcta definición de las maniobras del buque en el muelle. The recent deployment of new instrumentation designed to provide accelerations and angular velocities from caisson #8 at Botafoc seawall, Ibiza, along with an existing pressure sensor instrumentation at the vertical wall, provides a way to record and process data of the structural response, not only to waves, but also to effects caused by ship mooring operations at Botafoc seawall. As the measurement of these angular speeds and accelerations is programmed with sampling frecuencies up to 400 Hz, and by integrating all data through time we may provide suitable data of the structural behaviour of the caisson. This behaviour is tried to be correlated with the PROVERBS working group achievements (Probabilistic design of vertical breakwaters, MAST III EU Programme), generating a statistical movement database that must be used to improve knowledge on this subject. Also the possibility to record the effects caused by the different ship mooring operations is a new point of view of the complete structural design of a seawall-wharf, which is considered an interesting matter for coastal designers as well for a correct ship mooring processes definition.

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Este trabajo presenta un estudio sobre el funcionamiento y aplicaciones de las células de combustible de membrana tipo PEM, o de intercambio de protones, alimentadas con hidrógeno puro y oxigeno obtenido de aire comprimido. Una vez evaluado el proceso de dichas células y las variables que intervienen en el mismo, como presión, humedad y temperatura, se presenta una variedad de métodos para la instrumentación de tales variables así como métodos y sistemas para la estabilidad y control de las mismas, en torno a los valores óptimos para una mayor eficacia en el proceso. Tomando como variable principal a controlar la temperatura del proceso, y exponiendo los valores concretos en torno a 80 grados centígrados entre los que debe situarse, es realizado un modelo del proceso de calentamiento y evolución de la temperatura en función de la potencia del calentador resistivo en el dominio de la frecuencia compleja, y a su vez implementado un sistema de medición mediante sensores termopar de tipo K de respuesta casi lineal. La señal medida por los sensores es amplificada de manera diferencial mediante amplificadores de instrumentación INA2126, y es desarrollado un algoritmo de corrección de error de unión fría (error producido por la inclusión de nuevos metales del conector en el efecto termopar). Son incluidos los datos de test referentes al sistema de medición de temperatura , incluyendo las desviaciones o error respecto a los valores ideales de medida. Para la adquisición de datos y implementación de algoritmos de control, es utilizado un PC con el software Labview de National Instruments, que permite una programación intuitiva, versátil y visual, y poder realizar interfaces de usuario gráficas simples. La conexión entre el hardware de instrumentación y control de la célula y el PC se realiza mediante un interface de adquisición de datos USB NI 6800 que cuenta con un amplio número de salidas y entradas analógicas. Una vez digitalizadas las muestras de la señal medida, y corregido el error de unión fría anteriormente apuntado, es implementado en dicho software un controlador de tipo PID ( proporcional-integral-derivativo) , que se presenta como uno de los métodos más adecuados por su simplicidad de programación y su eficacia para el control de este tipo de variables. Para la evaluación del comportamiento del sistema son expuestas simulaciones mediante el software Matlab y Simulink determinando por tanto las mejores estrategias para desarrollar el control PID, así como los posibles resultados del proceso. En cuanto al sistema de calentamiento de los fluidos, es empleado un elemento resistor calentador, cuya potencia es controlada mediante un circuito electrónico compuesto por un detector de cruce por cero de la onda AC de alimentación y un sistema formado por un elemento TRIAC y su circuito de accionamiento. De manera análoga se expone el sistema de instrumentación para la presión de los gases en el circuito, variable que oscila en valores próximos a 3 atmosferas, para ello es empleado un sensor de presión con salida en corriente mediante bucle 4-20 mA, y un convertidor simple corriente a tensión para la entrada al sistema de adquisición de datos. Consecuentemente se presenta el esquema y componentes necesarios para la canalización, calentamiento y humidificación de los gases empleados en el proceso así como la situación de los sensores y actuadores. Por último el trabajo expone la relación de algoritmos desarrollados y un apéndice con información relativa al software Labview. ABTRACT This document presents a study about the operation and applications of PEM fuel cells (Proton exchange membrane fuel cells), fed with pure hydrogen and oxygen obtained from compressed air. Having evaluated the process of these cells and the variables involved on it, such as pressure, humidity and temperature, there is a variety of methods for implementing their control and to set up them around optimal values for greater efficiency in the process. Taking as primary process variable the temperature, and exposing its correct values around 80 degrees centigrade, between which must be placed, is carried out a model of the heating process and the temperature evolution related with the resistive heater power on the complex frequency domain, and is implemented a measuring system with thermocouple sensor type K performing a almost linear response. The differential signal measured by the sensor is amplified through INA2126 instrumentation amplifiers, and is developed a cold junction error correction algorithm (error produced by the inclusion of additional metals of connectors on the thermocouple effect). Data from the test concerning the temperature measurement system are included , including deviations or error regarding the ideal values of measurement. For data acquisition and implementation of control algorithms, is used a PC with LabVIEW software from National Instruments, which makes programming intuitive, versatile, visual, and useful to perform simple user interfaces. The connection between the instrumentation and control hardware of the cell and the PC interface is via a USB data acquisition NI 6800 that has a large number of analog inputs and outputs. Once stored the samples of the measured signal, and correct the error noted above junction, is implemented a software controller PID (proportional-integral-derivative), which is presented as one of the best methods for their programming simplicity and effectiveness for the control of such variables. To evaluate the performance of the system are presented simulations using Matlab and Simulink software thereby determining the best strategies to develop PID control, and possible outcomes of the process. As fluid heating system, is employed a heater resistor element whose power is controlled by an electronic circuit comprising a zero crossing detector of the AC power wave and a system consisting of a Triac and its drive circuit. As made with temperature variable it is developed an instrumentation system for gas pressure in the circuit, variable ranging in values around 3 atmospheres, it is employed a pressure sensor with a current output via 4-20 mA loop, and a single current to voltage converter to adequate the input to the data acquisition system. Consequently is developed the scheme and components needed for circulation, heating and humidification of the gases used in the process as well as the location of sensors and actuators. Finally the document presents the list of algorithms and an appendix with information about Labview software.

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We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems.

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The short sediment temperature probe were deployed and recovered with the LOOME observatory in 2009 and 2010, respectively. In addition to temperature, the loggers also recorded bottom water pressure at a sampling interval of 20 minutes. Even though the data obtained from the short temperature probe was strongly disturbed by leakage through a corroded connector, the data shows clearly that the probe was pulled out of the sediment on October 26, 2009, presumably by advancing mud flows.

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Senior thesis written for Oceanography 445