Literature and Conference proceedings

A 3D-printed venturi tube is presented as a rapid method for measuring flow rates of small fans commonly used in electronics cooling. The fluid dynamical theory, design, and testing behind the venturi device are introduced, strictly adhering to the performance test code on flow measurement, PTC 19.5-2004, prescribed by the American Society of Mechanical Engineers (ASME). The diameter of the venturi inlet was designed to fit a small 80mm fan blowing axially down the tube. The throat of the tube was designed to be 57mm, resulting in a diameter ratio of 0.75. The Arduino platform serves as the control and acquisition points for the ensuing analysis, where the fan speed was changed based on a pulse-width modulated duty cycle. Barometric pressure, differential pressure , and ambient temperature were all acquired using two external sensors. A computational fluid dynamics (CFD) simulation was used to compare flow rates across similar pressure differentials of the venturi tube. The incompressible venturi equation agreed with the CFD model to within 0.7% across the range of Reynolds numbers and pressure differentials recorded during the experiments. The error established between the CFD model and the venturi equation were far below the inherent error of the measurement devices, indicating that the venturi equation suffices for the current tube geometry and range of pressures. The maximum volumetric flow rate measured using the 3D printed venturi tube was found to be within 4% of the manufacturer's cited flow rate, indicating that the 3D printed venturi tube is an accurate instrument for determining flow rate.

Soil moisture can be measured using a variety of different techniques: gravimetric, nuclear, electromagnetic, tensiometric, hygrometric, among others. The technique explored here uses a gravimetric technique to calibrate a capacitive-type electromagnetic soil moisture sensor. Capacitive soil moisture sensors exploit the dielectric contrast between water and soil, where dry soils have a relative permittivity between 2-6 and water has a value of roughly 80. Accurate measurement of soil water content is essential for applications in agronomy and botany - where the under- and over-watering of soil can result in ineffective or wasted resources. With water occupying up to 60% of certain soils by volume, depending on the specific porosity of the soil, calibration must be carried out in every environment to ensure accurate prediction of water content. Fortunately, the accuracy of measurement devices has been increasing while the cost of the sensors has been decreasing. In this experiment, the Arduino platform is used to program a microcontroller to read the analog signal from the capacitive sensor, which in turn outputs a voltage. The inverse of this voltage can be linearly fit to approximate volumetric soil moisture content via gravimetric methods. This is done by measuring the volume and weighing dry and wet soil across a range of moistures. This is the process carried out in this paper.

Quantifying the Heat Stored in Urban Environments Using Remote Sensing Technology

Hrisko, Joshua; Ramamurthy, Prathap; Gonzalez, Jorge E.

Estimating the urban storage heat flux is one of the long standing unresolved issues in Earth and Environmental sciences. It is hypothesized to be the dominant term in the urban surface energy budget; the heterogeneity of the urban landcover and lack of observational technique have thus far proved to be the foremost impediments in quantifying the heat stored in cities. With more than half of the world’s current population living in cities, it is of utmost importance to close the urban surface energy budget, which influences energy use, local to global climate, human health and security. The primary motivation of this research is to quantify the contribution of storage heat flux to the urban surface energy budget. To accomplish this goal, remote sensing data will be integrated with landcover and ground based measurements. The recently released NOAA GOES-16 satellite will be used for this analysis. The GOES-16 satellite has a spatial resolution of 2 km in the infrared bands and more importantly has a temporal resolution of 5 minutes. This enables the use of satellite-based remote sensing data at meteorologically-relevant temporal scales. The satellite data will be coupled with high resolution landcover and land use information to estimate the storage flux and will be validated using ground-based measurements. New York City (NYC) is currently used as a test case for the study. Our preliminary analysis shows that the GOES-16 satellite data is reasonably correlated with ground-based sensors. Surface temperatures over 45˚C are observed during the summer months in parts of NYC. Additionally, the satellite images reproduce the spatial variability reasonably well. In the next phase, satellite images will be downscaled to higher resolution and integrated with a high-resolution landcover and land use database to estimate the storage heat flux.

Satellite based remote sensing data are increasingly used for urban meteorological applications, particularly to study urban heat island impacts. However, the land surface temperature, a critical variable used to characterize the urban thermal state has never been calibrated for urbanized landcover. This will in turn escalate the uncertainties in various applications (like weather forecasting in urban areas) which use remote sensing data. This research focuses on the development and testing of an Arduino-based, GPS-enabled, non-contact passive infrared temperature sensor that provides ground-truth temperature validation of the Geostationary Operational Environmental Satellite, GOES-16, and its LST operational product. It is posited that high-resolution, multi-point, near-surface temperature information will improve LST algorithms and ultimately advance the application of satellite data to study urban climate. New York City (NYC) is used as a test site for the temperature sensor along with its geographically-respective satellite calibration points. The analysis anticipates expansion into several U.S. cities, pending preliminary evaluation and testing in NYC. GIS tools will be used to visualize data points atop geographic maps, with the intention of correlating more built-up landcover regions with temperature differences quantified by the ground-based sensor and the GOES-16 LST data. The Arduino sensor is equipped with a thermocouple to provide real-time calibration measurements on the encountered surfaces to ensure that parameters such as emissivity are captured, as well as accurate and repeatable infrared temperature readings. The enhancement of satellite information improves the well-being of the general public, which can save lives during extreme weather events such as heat waves. The research presented here intends to broaden the LST calibration network available to satellites by providing a ground-based, portable sensor framework that is implementable across cities and urban areas.

An urban air temperature model is presented using GOES-16 land surface temperature. The Automated Surface Observing System (ASOS) serves as ground truth air temperature for calibration and testing of the model. The National Land Cover Database (NLCD) is used to calculate a weighted distribution of 20 land classifications for each satellite pixel surrounding a nearby ASOS station. A time-match algorithm aligns the ground and satellite measurements within 5-minutes of one another, and the resulting matched LST and air temperature are compared over nine months to investigate their cross-correlation. A model is constructed by fitting their difference using a gaussian profile. Landcover, latitude, longitude, local time, and elevation are inputted into an artificial regressive neural network to fit each unique GOES-16 pixel. Over 100 urban stations and satellite pixels throughout the continental U.S. are used to construct the diurnal gaussian model and approximate air temperature. Early statistics indicate favorable results, competing with other studies with more complicated and intensive calculations. The presentation of this model is intended to simplify the calculation of air temperature from satellite LST and create a successful model that performs well in urban environments. The improvement of urban air temperature calculations will also result in improved satellite land surface products such as relative humidity and heat index.

Since the launch of the GOES-16 satellite, scientists have been scrambling to find ways to harness the new technology and advance their understanding of weather in the western hemisphere. Provisional land surface temperature (LST) data was provided by the National Oceanic and Atmospheric Administration (NOAA) to validate the satellite’s performance and improve prediction of urban weather events. The dataset contains 5-minute temporal and 2km spatial snapshots of the continental United States, and spans from June 20 – November 16, 2017. Validation steps are carried out using several ground stations across the country. Furthermore, the data was downscaled against the MODIS satellite to improve spatial resolution and resolve atmospheric trends in compact urban areas. The goal of this research is to produce a dataset dense enough to accurately estimate the urban surface energy budget and improve weather prediction across cities. Initial results indicate good agreement when compared with ground stations in New York City, and a statistical analysis of the satellite data is presented as part of the evaluation. One of NOAA’s missions is to prepare the nation for extreme weather events, and this research serves as a starting point for improving weather models in urban areas, ultimately leading to a more weather ready nation.

An inexpensive, open-source, crowdsensing carbon dioxide data acquisition system is presented and tested against a Campbell IRGASON open-path gas analyzer. The sparsity of accurate and affordable remote sensing devices in the Internet of Things (IoT) sparked the creation of this device and resulted in the selection of four main components: an Arduino board, MH-Z14A NDIR CO2 module, an SD card adapter, and Bluetooth module. The entire system costs roughly $60 USD and the software is entirely open-source and easy to use. The sensor shows good agreement when compared to the Campbell gas analyzer, and a statistical analysis and correction algorithm is presented. The device is battery powered and compact for taking measurements in real-time, however, certain complications arise due to the response time of the sensor, the geometry of the inlet area, and inherent resolution of the CO2 module. This crowdsensing device is designed to create a more diverse set of carbon dioxide data points for monitoring pollution. The sensor will likely be most important in cities, where micro-climates dominate, which is why the device is smartphone compatible and completely autonomous. Hopefully, this type of acquisition system will become part of a series of voluntary geographic information products that help overcome the scarcity of data in the atmospheric community, and contribute to the protection of the environment as a whole.

Stability Effects on Turbulent Transport of Heat and Momentum in Urban Environments

-Hrisko, Joshua; Ramamurthy, Prathap

Impacts of shear and buoyancy are investigated in the urban surface layer (USL) using the eddy covariance technique. The Obukhov length is used to delineate convective periods, which are further subdivided into weakly unstable, unstable and very unstable. Our results indicate dissimilarity in the transport of heat and momentum, particularly as the instability increases. Heat transport was found to be very sensitive to increased instability while momentum transport was mute. Further analysis of primary quadrant sweeps and ejections indicate deviations from conventional theory, alluding that ejections dominate during convective periods for heat transport, but equally contribute with sweeps for momentum transfer. Frequency domain methods are also employed to quantify energy production and dominant length scales. Cospectra for both momentum and heat experience shifts in frequency and energy, suggesting that the efficiency of transport and eddy production in urban atmospheric flows are non-linearly dependent upon the height and instability. Collectively, these results demonstrate similarity breakdown for heterogeneous terrain, and reaffirm that revised and improved methods for characterizing buoyancy and shear transport in urban areas is needed. This breakdown in similarity could ultimately advance weather prediction and estimation of scalar transport for urban areas by producing more accurate empirical models to predict the behavior of atmospheric flows over complex terrain.

Variability of Particulate Matter and Air Quality at Street Level in New York City
 

-Parker, Granville; Castaldi, Ottavio; Sanchez, Justin; Ramamurthy, Prathap; Hrisko, Joshua

Measurements were taken at street level using air quality sensors that measure particulate matter, temperature, and humidity. The research goal is to combine hands-on data acquisition at high spatial resolution with GIS post-processing to quantify the spatial and temporal variability of particulate matter concentration (PM 2.5) along crowded streets in New York City. Due to their fine size and low density, PM 2.5 remains in the atmosphere for longer periods of time and can bypass the biological filters of the human nose and throat and penetrate deep into the lungs and potentially enter the circulatory system. PM 2.5 is a by-product of automobile combustion and is believed to be a primary cause of respiratory malfunction in urban environments. Street level concentration of PM2.5 is observed across two different routes that witness significant pedestrian traffic in Manhattan; observations will be conducted along these routes at various time periods. The study used the AirBeam community air quality monitor that simultaneously tracks PM 2.5 concentration along with GPS, air temperature and relative humidity.

Vertical Structure of Heat and Momentum Transport in the Urban Surface Layer

-Hrisko, Joshua; Ramamurthy, Prathap; Gonzalez, Jorge

Vertical transport of heat and momentum is investigated in the urban surface layer (USL) using air temperature and 3-component velocity measurements logged by a 40-m tall flux tower consisting of five sonic anemometers, each sampling at 10Hz. The Obukhov length is used to delineate dominantly convective periods, which are further subdivided into stability categories (weakly unstable, very unstable, etc.). Eddy covariance techniques are then used to calculate turbulent fluxes to reveal the effects of instability and height (AGL) on vertical momentum and heat transfer. During periods of increased instability the vertical heat flux deviates from the results given by the accepted theory. Further analysis of primary quadrant sweeps and ejections also indicate deviations from the theory, alluding that ejections dominate during convective periods for sensible heat, but equally contribute with sweeps for momentum transfer. Lastly, frequency domain methods are employed to quantify energy production and dominant length scales. Cospectra for both momentum and heat experience shifts in frequency and energy, suggesting that the efficiency of transport and eddy production in urban atmospheric flows are non-linearly dependent upon the height and instability. Collectively, these results demonstrate similarity breakdown for heterogeneous terrain, and reaffirm that revised and improved methods for characterizing heat and momentum transport in urban areas is needed. These implications could ultimately advance weather prediction and estimation of scalar transport for urban areas susceptible to weather hazards and large amounts of pollution.

Multiple Chip Module Cooling Using Vapor Chamber

Escobar-Vargas, Sergio; Kumari, Niru; Ferrer, Ernesto; Shih, Rocky; Anthony, Sarah; Hrisko, Joshua; Wan, Zhimin

This document describes the characterization of vapor chambers as cooling devices for multiple chip modules. The work consists of experiments and theory of vapor chambers. It includes developing and building the testing system, selecting the control and monitoring parameters, designing the vapor chamber, performing experiments, analyzing measurements, and drawing recommendations for vapor chamber selection and operation. The experiments include typical operation conditions found in electronics e.g. power dissipations up to 250 W, power densities up to 100 W/cm^2, and operating temperatures up to 45 C among other parameters. The main outcome of this work is that vapor chamber performs better than a solid heat spreader under specific conditions and the guidelines are included in the conclusions section; other outcomes include correlations and quantification of vapor chamber thermal resistance functionality to the control parameters.

Detectability Prediction for a Thermoacoustic Sensor in the Breazeale Nuclear Reactor Pool
 

-Hrisko, Joshua; Smith, James A.; Garrett, Steven L.

This thesis reports the first quantitative measurements of the vibroacoustic background noise levels and the reverberation time in the 70,000 gallon (265 m^3) pool used to cool the Breazeale Nuclear Reactor on Penn State's University Park campus. These measurements are used to provide an estimate for the detectability of a pure tone generated by a thermoacoustic engine that will be placed in the E-6 fuel position within that reactor's core to act as a self-powered, acoustically-telemetered thermoacoustic sensor (TAC Sensor) capable of measuring coolant temperature (based on the radiated frequency) and neutron
flux (based on the radiated amplitude).

The vibroacoustical environment in two nuclear reactors

-Hrisko, Joshua; Garrett, Steven L.; Smith, Robert W.; Smith, James A.; Agarwal, Vivek

Laboratory experiments have suggested that thermoacoustic engines can be incorporated within nuclear fuel rods. Such engines would radiate sounds that could be used to measure and acoustically-telemeter information about the operation of the nuclear reactor (e.g., coolant temperature or fluxes of neutrons or other energetic particles) or the physical condition of the nuclear fuel itself (e.g., changes in porosity due to cracking, swelling, evolved gases, and temperature) that are encoded as the frequency and/or amplitude of the radiated sound [IEEE Measurement and Instrumentation 16(3), 18–25 (2013)]. For such acoustic information to be detectable, it is important to characterize the vibroacoustical environments within reactors. We will present measurements of the background noise spectra (with and without coolant pumps) and reverberation times within the 70,000 gallon pool that cools and shields the fuel in the 1 MW research reactor on Penn State’s campus using two hydrophones, a piezoelectric projector, and an accelerometer. Background vibrational measurement taken at the 250 MW Advanced Test Reactor, located at the Idaho National Laboratory, from accelerometers mounted outside the reactor’s pressure vessel and on plumbing, will also be presented to determine optimal thermoacoustic frequencies and predict signal-to-noise ratios under operating conditions. [Work supported by the U.S. Department of Energy.]