In-field Measurements Research Articles

Method for wind turbine selection basing on in-field measurements

Method for wind turbine selection basing on in-field measurements

GreenLoading: Using the citizens band radio for energy-efficient offloading of shared interests

Cellular networks are susceptible to being severely capacity-constrained during peak traffic hours or at special events such as sports and concerts. Many other applications are emerging for LTE and 5G networks that inject machine-to-machine (M2M) communications for Internet of Things (IoT) devices that sense the environment and react to diurnal patterns observed. Both for users and devices, the high congestion levels frequently lead to numerous retransmissions and severe battery depletion. However, there are frequently social cues that could be gleaned from interactions from websites and social networks of shared interest to a particular region at a particular time. Cellular network operators have sought to address these high levels of fluctuations and traffic burstiness via the use of offloading to unlicensed bands, which may be instructed by these social cues. In this paper, we leverage shared interest information in a given area to conserve power via the use of offloading to the emerging Citizens Broadband Radio Service (CBRS). Our GreenLoading framework enables hierarchical data delivery to significantly reduce power consumption and user fairness variation and includes a Broker Priority Assignment (BPA) algorithm to select data brokers for users. With the use of in-field measurements and web-based Google data across four diverse U.S. cities, we show an order of magnitude power savings via GreenLoading over a 24-hour period, on average, and power savings up to 97% at peak traffic times. Finally, we consider the role that a relaxation of wait times can play in the power efficiency of a GreenLoading network.

Evaluating maize and soybean grain dry-down in the field with predictive algorithms and genotype-by-environment analysis

A delayed harvest of maize and soybean crops is associated with yield or revenue losses, whereas a premature harvest requires additional costs for artificial grain drying. Accurately predicting the ideal harvest date can increase profitability of US Midwest farms, but today’s predictive capacity is low. To fill this gap, we collected and analyzed time-series grain moisture datasets from field experiments in Iowa, Minnesota and North Dakota, US with various maize (n = 102) and soybean (n = 36) genotype-by-environment treatments. Our goal was to examine factors driving the post-maturity grain drying process, and develop scalable algorithms for decision-making. The algorithms evaluated are driven by changes in the grain equilibrium moisture content (function of air relative humidity and temperature) and require three input parameters: moisture content at physiological maturity, a drying coefficient and a power constant. Across independent genotypes and environments, the calibrated algorithms accurately predicted grain dry-down of maize (r2 = 0.79; root mean square error, RMSE = 1.8% grain moisture) and soybean field crops (r2 = 0.72; RMSE = 6.7% grain moisture). Evaluation of variance components and treatment effects revealed that genotypes, weather-years, and planting dates had little influence on the post-maturity drying coefficient, but significantly influenced grain moisture content at physiological maturity. Therefore, accurate implementation of the algorithms across environments would require estimating the initial grain moisture content, via modeling approaches or in-field measurements. Our work contributes new insights to understand the post-maturity grain dry-down and provides a robust and scalable predictive algorithm to forecast grain dry-down and ideal harvest dates across environments in the US Corn Belt.

Updated Emission Factors from Diffuse Combustion Sources in Sub-Saharan Africa and Their Effect on Regional Emission Estimates.

Diffuse emission sources outside of kitchen areas are poorly understood, and measurements of their emission factors (EFs) are sparse for regions of sub-Saharan Africa. Thirty-one in-field emission measurements were taken in northern Ghana from combustion sources common to rural regions worldwide. Sources sampled included commercial cooking, trash burning, kerosene lanterns, and diesel generators. EFs were calculated for carbon monoxide (CO), carbon dioxide (CO2), as well as carbonaceous particulate matter, specifically elemental carbon (EC) and organic carbon (OC). EC and OC emissions were measured from kerosene lighting events (EFEC = 25.1 g/kg-fuel SD = 25.7, EFOC = 9.5 g/kg-fuel SD = 10.0). OC emissions from trash burning events were large and highly variable (EFOC = 38.9 g/kg-fuel SD = 30.5). Combining our results with other recent in-field emission factors for rural Ghana, we explored updated emission estimates for Ghana using a region specific emissions inventory. Large differences are calculated for all updated source emissions, showing a 96% increase in OC and 78% decrease in EC compared to prior estimates for Ghana's emissions. Differences for carbon monoxide were small when averaged across all updated source types (-1%), though the household wood use and trash burning categories individually show large differences.

Comparison of 3D Imaging Technologies for Wheat Phenotyping

The in-field measurement of phenotypes or traits of wheat such as ear size is important data for use in the development of newer wheat varieties. The data is currently gathered manually from hundreds of test plots by random sampling of the what within each plot. To improve the data quality and data collection speed, we investigate and compare the use three different 3D imaging technologies: multistereo imaging, time-of-flight and structured light laser scanning to produce point clouds of a wheat plant in-situ. Measurements of the wheat plant’s ear is made from the generated point clouds.

Relative Radiometric Calibration of Airborne LiDAR Data for Archaeological Applications

Airborne laser scanning (ALS) data can provide more than just a topographic data set for archaeological research. During data collection, laser scanning systems also record radiometric information containing object properties, and thus information about archaeological features. Being aware of the physical model of ALS scanning, the radiometric information can be used to calculate material information of the scanned object. The reflectance of an object or material states the amount of energy it reflects for a specific electromagnetic wavelength. However, the collected radiometric data are affected by several factors that cause dissimilar values to be recorded for the same object. Radiometric calibration of such data minimizes these differences in calculated reflectance values of objects, improving their usability for feature detection and visualization purposes. Previous work dealing with calibration of radiometric data in archaeological research has relied on corresponding in-field measurements to acquire calibration values or has only corrected for a limited number of variables. In this paper, we apply a desk-based approach in which radiometric calibration is conducted through the selection of homogenous areas of interest, without the use of in-field measurements. Together with flight and scan parameters, radiometric calibration allows for the estimation of reflectance values for returns of a single full-waveform ALS data collection flight. The resulting data are then processed into a raster reflectance map that approximates a monochromatic illumination-independent true orthoimage at the wavelength of the laser scanner. We apply this approach to data collected for an archaeological research project in western Sicily and discuss the relative merits of the uses of radiometric data in such locations as well as its wider applicability for present and future archaeological and environmental research. In order to make the approach more accessible, we have developed a freely available tool that allows users to apply the calibration procedure to their own data.

Impacts of traffic noise on roadside secondary schools in a prototype large Chinese city

This study investigated impact of urban traffic on the acoustic comfort of roadside schools through both in-field measurements and on-site survey questionnaires. Six secondary schools were targeted, which are located near various types of roads in a prototype major city, Taiyuan, in the northern China. Noise levels were measured in front of the schools, in the schoolyard, and in the classrooms. The results indicated that noise pollution in these roadside schools was quite serious, and the school noise levels significantly correlated with the road traffic noise. The maximum measured equivalent A-weighted sound level (LAeq, 20min, LAeq) was 74.2 dB(A) near an expressway, which is 35% higher than the exterior threshold value (55.0 dB(A)) recommended by the World Health Organization. The on-site questionnaires revealed that all the students felt being disturbed by the road traffic noise and the degree of disturbance increased with the traffic level. Other noises (e.g., those from adjacent classrooms and that produced by student activities) were found acceptable. Further correlation analysis demonstrated a strong linear correlation between the level of road noise and highly disturbed respondents (R2: 0.928, p < 0.05). Consequently, the road noise level is a key factor that influences the acoustic comfort of roadside schools.

Flavonol Polymer Technology for Encapsulation of Liquid Phosphorus Fertilizers for Enabling A Slow-Release Process in Soil to Extend Usability and Reduce Leaching

ABSTRACTA proprietary Flavonol Polymer Technology (FPT), designed by AgroLiquid, is an agent for encapsulating different chemistries on the polymer by impregnation to provide extended release of nutrients and optimize yield. Based on FPT, FPT-Product (Pro-Germinator®) a 9-24-3 (% N, % P2O5, and % K2O w/w) manufactured to slow the phosphorus release process in soil and extends its usability by the plant. Phosphorus release was evaluated using micro-lysimeters installed in soil and used as a tool for the collection of the plant-usable phosphorus dissolved in the soil solution. A rate of 22 kg of P2O5/hectare of liquid formulations was banded in-furrow with four phosphorus liquid fertilizer treatments: (1) orthophosphate (9-18-9), (2) ammonium polyphosphate (10-34-0), (3) FPT-Product (9-24-3), and (4) a control. In-field measurements were collected at 20–60 days after the application for two successive years (2015 and 2016). In both years, averages of measured dissolved phosphorus in the soil solution and exchangeable soil phosphorus at 10-cm soil depth, 20–60 days after planting reported higher values in the FPT-Product treatments while lower values were measured in the other treatments. The results proved that the FPT extended the release mechanism for phosphorus in the FPT-Product at 10 cm depth in the soil, and rendered phosphorus in both the soil and the solution to be used by plants for an extended period after corn planting.

Multiphase mineral identification and quantification by laser-induced breakdown spectroscopy

Quantitative mineral analysis (QMA) performed using energy-dispersive x-ray spectrometry and scanning electron microscopes (EDS-SEM) provide reliable information on the mineral abundance and texture of prepared rocks. This information helps in the optimization of the mining and milling processes, and to define the value of a deposit. Real-time analysis of coarse rock streams would greatly enhance the decision-making processes driving the mining operation efficiency; however electron-microscope-based instruments are not yet adaptable for in-field measurements. Laser-induced breakdown spectroscopy (LIBS) has been used for elemental analysis in many environments but has not been employed for true mineral quantification and identification. This work presents a new method for mineral identification and quantification using LIBS, which could be scalable to perform automated mineralogy measurement in coarse rock streams. A set of rock tiles from mining operations in Australia had QMA performed using an EDS-SEM instrument and the resulting data were used to guide and validate the results obtained by LIBS. The use of a multivariate curve resolution – alternating least square (MCR-ALS) method applied to the LIBS data allowed the identification, quantification and imaging of minerals on rock tiles, even in the presence of mixed mineral phases within the laser spot area. Mineral abundance and imaging are obtained with success for the mineral phases selected in the present work, which includes bornite, chalcopyrite, pyrite, molybdenite, quartz, chlorite, K-feldspar, albite, fluorite and calcite. The method presented a mineral quantification root mean square error below 10% for the main minerals. In addition, mineral quantification by point-counting using single laser shots per LIBS measurement is demonstrated, achieving absolute errors below 3.5% for major minerals and below 1% for minor minerals.

An Evaluation Methodology for Spectrum Usage in LTE-A Networks: Traffic Volume and Resource Utilization Perspective

Rising popularity of online gaming and video streaming applications are making tremendous data demands on cellular networks. With higher resolutions, novel multimedia services, and ubiquitous video streaming, the objective to fulfill the quality constraints becomes critical and challenging. It is important that a network operator is able to optimize its resource usage while being able to guarantee the quality of service (QoS) to its subscribers. To this regard, we first propose a methodology to evaluate the upper limits on the traffic volume and the usage of resource blocks for a single cell to ensure seamless video streaming in dense urban environments. By applying these upper limits to the cells distributed in a large area, we subsequently investigate if the deployed spectrum of a network operator is sufficient to address the traffic demands without compromising the QoS. In particular, the upper limits are evaluated by considering practical resource usage pattern of video streaming along with the spectral efficiency analysis. Our statistical study is based on real time, in-field measurements from live LTE-A systems in Seoul, South Korea. Moreover, using system level simulations we forecast the average spectral efficiency of a cell which can be utilized to predict the cell traffic volume per hour. The understanding of current practical resource usage in LTE-A systems along with the methodology proposed in this paper can help network operators for efficient future spectrum deployments.

A cost effective solution for the deployment of wireless sensor networks

The paper presents a framework for the design and implementation of dynamic sensor networks. The focus is on minimising the costs associated with deploying such networks, while at the same time making available a fully fledged set of functions. This is achieved by leveraging a modular design based on an easily programmable, cost-effective micro-controller that can be interfaced with a set of heterogeneous sensors and wireless technologies. A real-world implementation of the proposed architecture is described. Our preliminary in-field performance measurements show that such a system can manage, with a high degree of precision and in real-time, a sustained rate of data gathered from mobile units.

Differential Spatial Gradients of Wheat Streak Mosaic Virus into Winter Wheat from a Central Mite-Virus Source.

The wheat curl mite (WCM), Aceria tosichella Keifer, transmits three potentially devastating viruses to winter wheat. An increased understanding of mite movement and subsequent virus spread through the landscape is necessary to estimate the risk of epidemics by the virus in winter wheat. Owing to the small size of WCMs, their dispersal via wind is hard to monitor; however, the viruses they transmit produce symptoms that can be detected with remote sensing. The objective of this study was to characterize the spatial dispersal of the virus from a central mite-virus source. Virus infection gradients were measured spatially by using aerial remote sensing, ground measurements, geostatistics, and a geographic information system between 2006 and 2009. The red edge position vegetation index as measured via aerial imagery was significantly correlated with in-field biophysical measurements. The occurrence of virus symptoms extended differentially in all directions from mite-virus source plots, and predictions from cokriging revealed an oval pattern surrounding the source but displaced to the southeast. The variable dispersal in different directions appeared to be influenced by the mite source density and wind direction and speed, but temperature also seemed likely to have affected mite spread. The spatial spread revealed in this study may be used to estimate the potential sphere of influence of mite-infested volunteer wheat in production fields. These risk parameter estimates require further validation, but they may potentially aid growers in making better virus management decisions regarding differential virus spread potential away from a central source.

Proper Monitoring Methods for Safety Management of Tailings Dam

This study has focused on analysis factors affecting safety monitoring system at tailings sites, and the evaluation equipment to monitor the factors. Twenty sites at eighteen mines with unsafe conditions were selected to examine the equipment. There were three main factors influenced safety in the sites including surface erosion, piping, and slope instability. In detail, the surface erosion was divided into three sub-factors (planting, soil-topping layer, and tailings), piping into three sub-factors (liner, rain protection facility and leachate), and slop instability was also divided into three sub-factors (slop, concrete wall, and reinforcing wall). As results of in-field measurement, a CCTV was the most effective facility, and electrical resistivity survey, acoustic sensing, thermal liner sensor, structure inclinometer, rainfall meter, and flowmeter were also highly effective. According to applications of the facilities in the unstable tailings, structural defects were mainly found in the piping, which was the most important monitoring factor for safety management of tailings sites.

Heat capacity and magnetocaloric effect in CoS1.84Se0.16

Abstract The first order paramagnetic (PM)-ferromagnetic (FM) transition in CoS 1.84 Se 0.16 is studied using in-field heat capacity measurement. From the low temperature C P data at zero field, the coefficient of electronic contribution to heat capacity ( γ ) and Debye temperature ( θ D ) are found to be 25 mJ/mol-K2 and 490 K, respectively. Heat capacity shows a sharp, symmetric peak at the magnetic transition ≈ 67 K in the absence of applied magnetic field and peak position shifts towards high temperature with magnetic field. The entropy of the transition is found to be ≈ 0.68 J/mol-K which is dominated by electronic contribution. In-field heat capacity measurement allowed us to estimate all the magnetocaloric (MCE) parameters relevant for magnetic refrigeration i.e. isothermal change in entropy ( - Δ S th ), adiabatic change in temperature ( Δ T ad ), relative cooling power (RCP), cooling capacity (q) etc. Temperature dependence of both - Δ S th and Δ T ad show a table-top like behaviour with almost field independent maxima above 4 Tesla.

In-field measurement of vertical and horizontal forces in ski-jumping: Evaluation of a portable two-dimensional force plate

Various methods for measuring ground reaction forces during ski-jumping have been developed and applied. The main limitations of the current systems are the restriction to the measurement of single phases (parts of the in-run and take-off) and single force components (vertical component only). Therefore, the purpose of this study was to assess a recently developed force measurement system (JH-SJ), which records forces in the vertical (compression and tension) and horizontal (anterior and posterior) directions over the entire hill jumping sequence. Comparing the values between the JH-SJ and calibrated reference systems in a static and ski-jumping-specific condition provided a means of validating the use of JH-SJ. Hill jumps were performed to evaluate the system regarding the feasibility of application and plausibility of the obtained data. Mean absolute difference during static validity evaluation was 3.5 N (2.7%). Root mean square errors during ski-jumping-specific validity evaluation were less than 11.9 N. Vertical forces acted as compression during all phases of the hill jump except for the flight phase, when tension forces were also recorded. Horizontal force acted as friction on the system during in-run, take-off and landing. The small deviation of the measurement system compared to the reference systems suggests high validity of the JH-SJ measurement system. Qualitative analysis of the forces during hill jumps delivered plausible results for all phases, similar to previous studies. Based on this study, the JH-SJ system measures forces with a high degree of accuracy and precision in real conditions (hill jumps), while contributing new insights into ski-jumping kinetics.

Are water footprints accurate enough to be useful? A case study for maize (Zea mays L.)

The application of water footprint accounting is mostly done at large scales, but the estimation of crop- and region-specific water footprints for up-scaling is dependent on accurate and representative in-field measurements of evapotranspiration (ET), yield and irrigation. In a field trial we assessed the influence of maize (Zea mays L.) ET estimates using soil water balance accounting, remote sensing with satellite imagery (SEBAL model), eddy covariance measurements and three crop models (SWB, CROPWAT, SAPWAT) on water footprint estimates. We simultaneously assessed the influence of yield spatial variability as measured by a precision harvester. Seasonal ET estimations differed by as much as 15% for the different methods, and yield differed by as much as 42%, representing the error which can be introduced as a result of point measurements. Using a combination of the highest/lowest ET estimates and the 5th/95th percentile yield, water footprint values differed by as much as 100%, ranging from 338-680 m3 t−1. Applying spatially-linked SEBAL ET estimates and precision harvester yield at the 30 × 30 m scale reduced the range of estimated water footprints to 493-663 m3 t -1, with an average of 547 m3 t-1. This was 15% higher than the water footprint estimated using average SEBAL ET and average yield for the whole pivot (467 m3 t -1). Any error introduced at this stage of water footprint accounting can be transferred during up-scaling of the results. For example, based on the minimum and maximum estimated water footprints, maize production was expected to consume between 4.4 and 8.3%, respectively, of the Orange River (South Africa’s largest river) flow during the season in that region. Biophysical scientists have the role of providing high quality data for accurate water consumption estimates. Thereafter, their application by various stakeholders should be done with caution.

Module Temperature Dispersion Within a Large PV Array: Observations at the Amareleja PV Plant

In-field photovoltaic (PV) module and array characterization is becoming increasingly important within the particular framework of quality assurance procedures at large commercial PV plants. In this context, the correct measurement of the module temperature is critical in order to reduce uncertainty and increase repeatability of results. In the case of large PV array characterization, the measurement provided by the sensors may not be representative of the PV array as a whole given the great diversity of operating conditions occurring throughout its surface area. Spatial temperature differences within a PV array of less than 5 K are typically considered in practice. However, the temperature differences observed at a commercial PV plant in Amareleja (Portugal) are more than twice those typically assumed. Such high differences may considerably increase the uncertainty in the determination of the PV array operating temperature and, hence, in its standard test conditions power characterization. This paper quantifies the uncertainty associated with the in-field measurement of the operating temperature of large PV arrays and their individual PV modules as a function of the type, number, and location of the temperature sensors used. Furthermore, the incident irradiance and particular wind speed conditions over the PV array have been clearly identified as the main causes of these temperature differences, showing that the optimum conditions to perform the PV array characterization do not correspond to low wind speed conditions, as recommended by many authors.

Optimizing the performance of a commercial electrochemical ethylene sensor via controlled ethylene generation in situ

Ethylene, which regulates fruit ripening processes in some species, is a molecule of central interest to postharvest researchers and technologists. There is a need for a portable, inexpensive, accurate, and repeatable sensor for infield or storeroom measurements. To help ensure repeatable results, we developed a field calibration protocol for a portable electrochemical gas sensor that combines ethephon (2-chloroethylphosphonic acid) with a buffering agent to release a controlled amount of ethylene gas (1–4 μL/L). The ethephon reaction provides an economical source of standard gas for device calibration. This work addresses device selectivity issues through the use of an inline aqueous trap to remove polar volatile organics (50% reduction, as reported by an electrochemical sensor), interfering with the ethylene detection. A complementary gas chromatographic (GC) assay provided an independent validation of these results. A post-harvest study of ethylene production of apples as detected by the electrochemical sensor illustrates significant improvements in the accuracy and precision of these measurements.

Student Led Campus Desire Path Evaluation Using Pictometry® Neighborhood Imagery

A student led evaluation of desire paths (e.g., paths created by pedestrians on an open landscape) across the Stephen F. Austin State University (SFASU) campus was performed within a senior level spatial science course in order to create a method for mitigation of desire paths and for campus beautification. Each desire path on campus was identified with the length of each path measured in the field and categorized by the condition of the path in order to assess and determine a necessary solution for each path identified. In addition, Pictometry® high spatial resolution digital imagery was used to determine if the categorization of the conditions of the desire paths, as well as the length of each desire path, could be identified and quantified without the need to measure each individual desire path in the field. Students, within an interactive hands-on classroom environment, compared in-field desire path measurements with Pictometry® on-screen measurements to determine the effectiveness of remotely sensed Pictometry® imagery to identify and quantify desire path location and length respectfully.

Replacing Manual Rising Plate Meter Measurements with Low-cost UAV-Derived Sward Height Data in Grasslands for Spatial Monitoring

Non-destructive methods to derive spatial information on the development of forage mass are of key importance in managed grasslands. Established methods are rising plate meter (RPM) and rapid pasture meter, which both require in-field work, are rather time consuming, and do not provide spatially continuous data. Therefore, the overall objective of this study is to investigate low-cost unmanned aerial vehicle (UAV)-based RGB image acquisition for grassland monitoring. The idea of this paper is to transfer the successfully introduced approach of crop surface models (CSMs) for ultrahigh resolution analysis of plant height to managed grasslands. The study area is the Rengen Long-term Grassland Experiment, Germany, which is a two-cut experiment and was established in 1941. We conducted RPM and UAV-based data acquisition over six growth periods in 2014, 2015, and 2016. In 3 years, 26 RPM and 46 UAV campaigns were conducted under varying weather conditions (cloudy/sunny). The UAV-based RGB imagery was photogrammetrically processed with Structure from Motion and Multi-view Stereopsis techniques, producing multi-temporal CSMs for grassland sward height analysis. The regression analysis of UAV-derived sward height (CSM-SH) against RPM-measured sward height (RPM-SH) resulted in R2 of 0.91, 0.87, and 0.83 for 2014, 2015, and 2016, respectively. The pooling of the data for all 3 years resulted in an R2 of 0.86. These findings prove the successful transfer of the CSM approach for grassland monitoring and the potential of UAV-based monitoring to replace manual or in-field measurements with RPM or rapid pasture meter.