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The main challenge in the field of water distribution systems (WDS) is (re)designing the network in order to achieve savings. In many water systems, there are pumping stations designed for much larger flows than what would be observed under normal operating conditions. On the other hand, reducing the diameter of the water pipes has become the main saving method. Designers very often forget to design the network so that it can be used for fire protection purposes. The computer modelling of water networks supports the decision-making process by identifying the optimal compromise between cost and performance (e.g., flow, velocity, pressure). Computer models help in the selection of optimal values of hydraulic pumps, preparation of the pump control method and selection of energy-optimized pumping systems, ensuring the efficiency and pressure of the WDS during normal operation and in fire conditions. The article presents the results of optimization of the pump station in terms of efficiency and pressure in the system, and optimization of pump energy consumption. Computer simulations of the water supply system, measurements of pressure and flow, hydrant flow tests, and model calibration were used in the research.

Temperature sensors are used for a wide variety of industrial, scientific, medical and domestic purposes, and differ by their design and/or operating principles to better suit a particular application. Measuring temperature distribution requires use of many sensors, and their selection should balance cost, accuracy and convenience of networking. Most accurate are resistance temperature detectors (RTDs), of which most commonly used are Pt100 and Pt1000 platinum RTDs. These sensors are expensive, require a separate electronic driver for each RTD and complicated networking. Thermistors are the least expensive on their own but ensuring accurate measurement requires their individual calibration, provisions to shield them from noise and complicated networking. Semiconductor temperature sensors frequently integrate an appropriate electronic driver and provide a standardised interface, which eases of their networking, at a medium price point. However, their accuracy is usually specified rather conservatively by the manufacturers.\ud \ud In this study we compared readings, collected every 19 seconds from Pt100 and DS18B20 temperature sensors, placed in a cardboard box close to each other in a typical dwelling, over several months’ period. For periods of time both sensors were placed inside the same plastic bag, or were wrapped around with packaging materials for thermal insulation, or were left exposed to the environment on their own.\ud \ud The vast majority of collected data show that the DS18B20 provided substantially better accuracy than the one specified by the manufacturer (+-0.5°C) when the sensors were close to each other and well insulated. Their readings were well correlated over time even when the absolute readings were notably biased. These and some other past and present observations, to be presented at the conference, led us to the conclusion that DS18B20 sensors, after some suitable calibration, can reduce complexity and cost of the temperature distribution measurement networks.

Refrigeration and air conditioning consume 15% of the total generated electricity. Vapor condensation devices need a heat sink which may come in the form of absorption cycles devices. Two fluids, which change phase and concentration, flow through these devices. These changes take place amid a two-phase flow in contact with a solid phase. Hence, an extended study of the velocity profiles across the thin liquid layer is necessary, which is assumed to be conducted by a laser Doppler anemometer. The preliminary studies concerning the calibration of this anemometer are reported.

A wavelength multiplexing procedure for color transmission volume holograms of diffusing objects recorded in Bayfol® HX200 photopolymer is proposed. For the recording, three lasers of 442 nm, 532 nm and 633 nm, and a Spectralon® diffusing object were used for monochromatic and polychromatic calibration. Monochromatic calibration shows that the maximum index modulation obtained for each wavelength was not enough to give 100% efficiency, although the efficiency values achieved in the case of monochromatic recordings with diffusing objects were high, at around 90% for 633 nm and 532 nm recordings, and 60% for 442 nm. The efficiency values obtained for multiplexed holograms were 19.1% for the 442 nm hologram, 25.9% for the 532 nm hologram and 15.2% for the 633 nm. This research was funded by the “Diputación General de Aragón-Fondo Social Europeo” (TOL research group, E44_17R), the “Generalitat de Catalunya” (2017FI_B2_00127 and 2017 SGR 1276) and the “Ministerio de Ciencia e Innovación” (PID2019-108598GB-I00, PID2019-111536RB-I00 and PID2021-114311RA-I00)

One of the most important steps in the retrofitting process of a building is to understand its pre-retrofitting stage energy performance. The best choice for carrying this out is by means of a calibrated building energy simulation (BES) model. Then, the testing of different retrofitting solutions in the validated model allows for quantifying the improvements that may be obtained, in order to choose the most suitable solution. In this work, based on the available detailed building drawings, constructive details, building operational data and the data sets obtained on a minute basis (for a whole year) from a dedicated energy monitoring system, the calibration of an in-use office building energy model has been carried out. It has been possible to construct a detailed white box model based on Design Builder software. Then, comparing the model output for indoor air temperature, lighting consumption and heating consumption against the monitored data, some of the building envelope parameters and inner building inertia of the model were fine tuned to obtain fits fulfilling the ASHRAE criteria. Problems found during this fitting process and how they are solved are explained in detail. The model calibration is firstly performed on an hourly basis for a typical winter and summer week; then, the whole year results of the simulation are compared against the monitored data. The results show a good agreement for indoor temperature, lighting and heating consumption compared with the ASHRAE criteria for the mean bias error (MBE). This research was supported by the A2PBEER project “Affordable and Adaptable Public Buildings through Energy Efficient Retrofitting” under grant number 609060 funded by the European Commission for providing resources for the monitoring system. The APC was funded by the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund through the project called “Investigation of monitoring techniques of occupied buildings for their thermal characterization and methodology to identify their key performance indicators”, project reference: RTI2018-096296-B-C22 (MCIU/AEI/FEDER, UE).

An interlaboratory comparison for European radon calibration facilities was conducted to evaluate the establishment of a harmonized quality level for the activity concentration of radon in air and to demonstrate the performance of the facilities when calibrating measurement instruments for radon. Fifteen calibration facilities from 13 different European countries participated. They represented different levels in the metrological hierarchy: national metrology institutes and designated institutes, national authorities for radiation protection and participants from universities. The interlaboratory comparison was conducted by the German Federal Office for Radiation Protection (BfS) and took place from 2018 to 2020. Participants were requested to measure radon in atmospheres of their own facilities according to their own procedures and requirements for metrological traceability. A measurement device with suitable properties was used to determine the comparison values. The results of the comparison showed that the radon activity concentrations that were determined by European calibration facilities complying with metrological traceability requirements were consistent with each other and had common mean values. The deviations from these values were normally distributed. The range of variation of the common mean value was a measure of the degree of agreement between the participants. For exposures above 1000 Bq/m3, the variation was about 4% for a level of confidence of approximately 95% (k=2). For lower exposure levels, the variation increased to about 6%.

This paper describes a method for calibrating multi camera and multi laser 3D triangulation systems, particularly for those using Scheimpflug adapters. Under this configuration, the focus plane of the camera is located at the laser plane, making it difficult to use traditional calibration methods, such as chessboard pattern-based strategies. Our method uses a conical calibration object whose intersections with the laser planes generate stepped line patterns that can be used to calculate the camera-laser homographies. The calibration object has been designed to calibrate scanners for revolving surfaces, but it can be easily extended to linear setups. The experiments carried out show that the proposed system has a precision of 0.1 mm.

Subject calibration has been demonstrated to improve the accuracy in high-performance eye trackers. However, the true weight of calibration in off-the-shelf eye tracking solutions is still not addressed. In this work, a theoretical framework to measure the effects of calibration in deep learning-based gaze estimation is proposed for low-resolution systems. To this end, features extracted from the synthetic U2Eyes dataset are used in a fully connected network in order to isolate the effect of specific user’s features, such as kappa angles. Then, the impact of system calibration in a real setup employing I2Head dataset images is studied. The obtained results show accuracy improvements over 50%, probing that calibration is a key process also in low-resolution gaze estimation scenarios. Furthermore, we show that after calibration accuracy values close to those obtained by high-resolution systems, in the range of 0.7°, could be theoretically obtained if a careful selection of image features was performed, demonstrating significant room for improvement for off-the-shelf eye tracking systems.

Article number 3762 This work deals with the application of femtosecond-laser-inscribed fiber Bragg gratings (FsFBGs) for monitoring the internal high-temperature surface distribution (HTSD) in solar receivers of concentrating solar power (CSP) plants. The fiber-optic sensor system is composed of 12 FsFBGs measuring points distributed on an area of 0.4 m2 , which leads to obtain the temperature map at the receiver by means of two-dimensional interpolation. An analysis of the FsFBG performance in harsh environment was also conducted. It describes the influence of calibration functions in high-temperature measurements, determines a required 10 nm spectral interval for measuring temperatures in the range from 0 to 700 ◦C, and reveals wavelength peak tolerances in the FsFBG fabrication process. Results demonstrate the viability and reliability of this measuring technique, with temperature measurements up to 566 ◦C FEDER INTERCONNECTA 2016 ITC-20161223

This paper presents a built-in calibration procedure of a 10-to-20 GHz polarimeter aimed at measuring the I, Q, U Stokes parameters of cosmic microwave background (CMB) radiation. A full-band square waveguide double directional coupler, mounted in the antenna-feed system, is used to inject differently polarized reference waves. A brief description of the polarimetric microwave radiometer and the system calibration injector is also reported. A fully polarimetric calibration is also possible using the designed double directional coupler, although the presented calibration method in this paper is proposed to obtain three of the four Stokes parameters with the introduced microwave receiver, since V parameter is expected to be zero for the CMB radiation. Experimental results are presented for linearly polarized input waves in order to validate the built-in calibration system. The authors would like to thank The Spanish Ministry of Science and Innovation for financial support provided through the grants ESP2015-70646-C2-2-R, ESP2017-83921-C2-2-R and PID2019-110610RB-C22

Parano&aacute, Lake, Federal District (DF), Brazil, is one of the most important urban lakes in the country and it receives inputs from basins with different characteristics, from natural and preserved to intensely urbanized and agricultural areas. The study of the hydrological processes in these basins, as well as the water balance in each of them, is fundamental for planning current and future water uses in Parano&aacute, Lake. Using an extensive database (35 years) and the Soil and Water Assessment Tool (SWAT) model, we modelled five sub-basins. The outflow rates of the model for each sub-basin served as input for determining the water balance of Parano&aacute, Lake, which recently became part of the DF public water supply system. Despite extensive flow monitoring in the main lake tributaries, about 20% of the lake basin is composed of direct contribution or non-monitored tributaries. Additionally, the lake outflow is composed of a spillway and a hydropower generation unit that does not have proper flow measurements, and thus a correct basin hydrological simulation is essential for water balance aiming to water management scenarios. The results show an average long-term balance of 18.073 m3/s, with minimum flows around 13 m3/s and maximum flows close to 30 m3/s. This is a pioneering study that associates the extensive monitored database and the hydrological simulation of all affluent basins with the water balance of Parano&aacute, Lake. The results obtained are essential to water management and hydrodynamic modeling of the lake.

Water leakages are one of the most significant uncertainties affecting water supply system (WSSs) modelling. Due to the dependence between water losses and pressure, the WSSs characterised by high values of pressure in the distribution network are strongly affected by this problem. High-pressure conditions are typical of WSSs in the mountain areas. In this study, a real WSS of the Alpine region is analysed through simultaneous calibration of water losses and pressure-reducing valves with a genetic algorithm. The demand is represented by a uniformly distributed along the network pipes scheme, dealing with the water request separately from the losses.

Biomechanics measurement in boxing is becoming increasingly important for the analysis of boxing technique in order to promote exciting and safer boxing at both amateur and professional levels. Despite this interest, there have been few experiments within this field of research that have utilised a non-embedded in-glove sensor to measure the resultant power generated by a boxing punch. The aim of this study was to develop a dynamic measurement system, utilising a non-embedded in-glove sensor system. Two sensors were utilised; a tri-axial accelerometer to measure acceleration and a piezo-resistive force sensor hand wrap to measure the impact force of a boxer’s punch. The piezo-resistive system was calibrated using a static measurement system utilising simple load cells for force and laser displacement sensors for glove speed measurements. The system was tested on 31 novice boxing athletes participating in the study. A mean impact force of 2.31 kN ± 3.28 kN, an instantaneous velocity prior to impact of 4.73 m/s ± 0.35 m/s, an impact acceleration of 91 g ± 11 g, deceleration immediately following impact of 223 g ± 21 g and a maximum power dissipation of 11.2 kW ± 2.05 kW were measured. These values correspond well with prior studies using alternate measurement approaches. The calibration of the non-embedded in-glove piezo-resistive force sensor on the static measurement system yielded a correlation coefficient of 0.85.

[Abstract] Rainfall simulators are useful tools for controlling the main variables that govern natural rainfall. In this study, a new drop-forming rainfall simulator, which consists of pressure-compensating dripper grids above a horizontal mesh that breaks and distributes raindrops, was developed to be applied in wash-off experiments in a large-scale physical model of 36 m2. The mesh typology and size, and its distance to drippers, were established through a calibration where rain uniformity and distributions of raindrop sizes and velocities were compared with local natural rainfall. Finally, the rain properties of the final solution were measured for the three rain intensities that the rainfall simulator is able to generate (30, 50 and 80 mm/h), obtaining almost uniform rainfalls with uniformity coefficients of 81%, 89% and 91%, respectively. This, together with the very suitable raindrop size distribution obtained, and the raindrop velocities of around 87.5% of the terminal velocity for the mean raindrop diameter, makes the proposed solution optimal for wash-off studies, where rain properties are key in the detachment of particles. In addition, the flexibility seen in controlling rain characteristics increases the value of the proposed design in that it is adaptable to a wide range of studies. The first author was in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant FPU14/01778. The project was partially funded by the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU).

Pasture quality monitoring is a key element in the decision making process of a farm manager. Laboratory reference methods for assessing quality parameters such as crude protein (CP) or fibers (neutral detergent fiber: NDF) require collection and analytical procedures involving technicians, time, and reagents, making them laborious and expensive. The objective of this work was to evaluate two technological and expeditious approaches for estimating and monitoring the evolution of the quality parameters in biodiverse Mediterranean pastures: (i) near infrared spectroscopy (NIRS) combined with multivariate data analysis and (ii) remote sensing (RS) based on Sentinel-2 imagery to calculate the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). Between February 2018 and March 2019, 21 sampling processes were carried out in nine fields, totaling 398 pasture samples, of which 315 were used during the calibration phase and 83 were used during the validation phase of the NIRS approach. The average reference values of pasture moisture content (PMC), CP, and NDF, obtained in 24 tests carried out between January and May 2019 in eight fields, were used to evaluate the RS accuracy. The results of this study showed significant correlation between NIRS calibration models or spectral indices obtained by remote sensing (NDVIRS and NDWIRS) and reference methods for quantifying pasture quality parameters, both of which open up good prospects for technological-based service providers to develop applications that enable the dynamic management of animal grazing.

Dialkyl diketene dimers are used as sizing agents in the manufacture of paper and board for food contact applications to increase wetting stability. Unbound residues can hydrolyze and decarboxylate into dialkylketones. These non-intentionally added substances (NIAS) have potential to migrate to fatty foods in contact with those packaging materials. In Germany, the Federal Institute for Risk Assessment (BfR) established a specific migration limit (SML) of 5 mg/kg for the transfer of these dialkylketones into foodstuffs. In order to investigate the differences between simulants and real foods, an analytical method was optimized for extraction and quantification of dialkylketones in edible oils and fatty foods by gas chromatography coupled with flame ionization detection (GC-FID), and additionally by gas chromatography with mass spectrometry (GC-MS), to confirm their identification and to quantify them in case of interferences. Dialkylketones are separated from the extracted fat by alkaline saponification of the triglycerides. Dialkylketones migration from paper-based food contact articles into organic solvents isooctane and dichloromethane, in olive and sunflower oils, and in fatty foods (croissants, Gouda, cheddar cheese, and salami was studied). As a result, it was found that the simulating tests, including the edible oil extraction tests, gave migration values that exceeded the SML largely, while the migration with the food samples were largely below the SML. Antía Lestido Cardama is grateful for her predoctoral grant “Programa de axudas á etapa predoutoral” da Xunta de Galicia (Consellería de Cultura, Educación e Ordenación Universitaria) SI

Currently, the mineral industry makes iron ore beneficiation processes in humid or natural moisture. Excessive moisture in iron ore can affect the beneficiation process, causing loss of productivity and transport issues, as well as reducing the efficiency of dewatering subprocesses and safety. The traditional technic for measuring iron ore moisture is the standard oven method, which is very accurate, but not very representative. Furthermore, it has a high time response: up to 24 h for each mineral sample. Consequently, corrective and preventive actions to the process become inefficient. Alternative technics, such as the microwave method, perform online moisture measurements but with low accuracy. Recently, we developed a high accuracy capacitive sensor for measuring ore moisture but not online (bench device). This paper refers to the development of a capacitive, non-invasive, coplanar-electrode transducer for iron ore moisture measurement, designed for online applications. To achieve this, we constructed a signal conditioning system, based on an 8-bit microcontroller and a driven shield for the sensor element. The system transmits the processed data via radio frequency to a computer. Moreover, it applies a statistical filter to the measurements, based on standard deviation and moving average, as a way for minimizing electromagnetic interference. The statical calibration results reached a coefficient of determination of 98.41%. The coplanar, non-invasive approach of the transducer offers the advantage of preserving the physical integrity of the sensor electrodes as well as a future online application.

Data collection plays an important role in pavement health monitoring, which is usually performed using costly devices, including point-based lasers and laser scanners. The main aim of this study is measuring pavement characteristics using an RGB-D sensor. By recording the depth and color images simultaneously, the sensor benefits the data fusion. By mounting the sensor on a moving cart, and fixing the vertical distance from the ground, data was collected along 100 m of the asphalt pavement using MATLAB. At each stop point, multiple frames were captured and the central region of interests was stored followed by applying low pass filters. To create a 3D dimensional surface of the pavement, sensor calibration was performed to map the RGB and depth infrared images. The SURF (Speeded-up Robust Features) and MSAC (M-estimator Sample Consensus) algorithm were used to match the stitched images along the longitudinal profile. A case study of measuring roughness and rutting is applied to test the validity of the method. The result confirms that the proposed system is capable of measuring such indices with acceptable accuracy.

An inertial measurement unit (IMU) typically has three accelerometers and three gyroscopes. The output of those inertial sensors is used by the inertial navigation system to calculate the navigation solution. Since the sensor measurements contain noise, the navigation solution drifts over time. When considering low cost sensors, multiple IMUs can be used to improve the performance of a single unit. In this paper, we describe our designed 32 multi-IMU (MIMU) architecture and present experimental results of this system. To analyze the sensory data, a dedicated software tool, capable of addressing MIMUs inputs, was developed. Using our MIMU hardware and software tool we examined the possibility of using MIMUs instead of a single IMU for: 1) navigation solution 2) outlier rejection 3) calibration performance 4) coarse alignment accuracy and 5) the effect of different MIMUs locations in the architecture. Our results show that 32 IMUs obtained better performance than a single IMU for all testcases examined. In addition, we show that performance was improved gradually as the number of IMUs was increased in the architecture.

Dissolved carbon dioxide (dCO2) evaluation is very important in many different fields. In this work, a new, integrated, colorimetric-optical fiber-based system for dCO2 monitoring in aquaculture industry was developed. The sensing chemistry is based on colorimetric changes of the used indicator—poly p-nitrophenol (pNPh)—in contact with CO2. Preliminary tests were done in a laboratory environment (calibration) and in a laboratory Recirculating Aquaculture System (RAS) with controlled CO2 injection. The results have shown the suitability of the new sensor for assessing dCO2 dynamics in RAS and its fast detection of low dCO2 concentrations in an appropriate operation range.

Producción Científica, Pseudo-Invariant Calibration Sites (PICS) have been widely used by the remote sensing community in recent decades for post-launch absolute calibration, cross-calibration, and the monitoring of radiometric stability. The Committee on Earth Observation Satellites (CEOS) has established several official PICS for these purposes. Of these, Libya-4 is the most commonly used, due to its high uniformity and stability. The site was chosen as a large-area site for medium resolution sensors, and with high-resolution sensors now common, smaller sites are being identified. This work has identified an improved area of interest (AOI) within Libya-4 by using combined Landsat 8 and Sentinel 2 data. The Optimized Ground Target (OGT) was determined by calculating the coefficient of variation along with the use of a quasi-Newton optimization algorithm combined with the Basin–Hopping global optimization technique to constrain a search area small enough to perform a final brute-force refinement. The Coefficient of Variation CV of the proposed OGT is significantly lower than that in the original CEOS area, with differences between the CV of both zones in the order of 1% in the visible near-infrared (VNIR) bands. This new AOI has the potential to improve the cross-calibration between high-resolution sensors using the PICS methodology through an OGT with more homogeneous and stable characteristics.

This study proposes a new preprocessing technique that combines Chebyshev filtering with baseline correction technique Asymmetric Least Squares (ALS) and Savitzky-Golay transformation (SGT) to improve the prediction of Glucose from near Infrared (NIR) spectra through linear regression models Partial Least Squares (PLS) and Principal Component Regression (PCR). To investigate the performance of the proposed technique, a calibration model was first developed and then validated through prediction of Glucose from NIR spectra of a mixture of glucose, urea, and triacetin in a phosphate buffer solution where the component concentrations are within their physiological range in blood. Results indicate that the proposed technique improves the performance of both PLS and PCR and achieves standard error of prediction (SEP) as low as 12.76 mg/dL which is in the clinically acceptable level and comparable to the existing literature.

Numerous non-ideal effects can distort the functionality of sensor interfaces and have to be considered during the design phase. In order to relax the requirements for the analog circuit components, adaptive filtering and digital calibration are used in this work to detect and correct different gain- and offset-errors. The error detection is performed by transmitting a test signal through the sensor interface continuously and in parallel to the sensor signal. In the digital domain, variations of the test signal are evaluated and present errors can be determined and eliminated. In this way, an on-line error correction is realized, which makes the sensor interface more robust against static and dynamic non-idealities. The proposed concept is demonstrated by correcting different gain- and offset-errors in a 65nm CMOS sensor interface.

Among sensors using magnetic fluids, inclinometers are seriously addressed by the scientific community. This paper deals with an optical inclinometer exploiting a ferrofluid (FF) mass, a magnetic shaping system and an InfraRed (IR) readout strategy. A dedicated paradigm is also proposed, with the aim of defining a calibration model relating the inclinometer output quantity to the imposed tilt. The working range of the inclinometer is [−15°–15°]; the sensor accuracy and resolution are 0.61° and 0.005°, respectively. Moreover, the device shows a span-to-resolution ratio of 6 × 103.

We propose to use an integration process based on Transducer Electronic Data Sheets applied to a magnetic sensor system for the realization of artificial landmarks. Magnetic sensors provide an advantageous alternative in surroundings where GPS and optical sensors do not work. These landmarks can be used by passing autonomous vehicles, e.g., drones, for re-orientation and re-calibration. To facilitate the usage of these landmarks also by any vehicle, known or unknown, a standardized process for automatic connection and identification of the landmarks is suggested. During this process, all necessary information such as protocols, calibration data etc. is made known to the vehicle passing by. Based on the provided information, the vehicle itself can decide whether and how to use the provided sensory information.

The control electronics for low field pulsed NMR systems, commonly referred to as the console, are designed to be wide band and highly programmable. The process of making spin lattice relaxation time (T1) measurements with such a pulsed system usually use recovery sequences that will typically take many minutes to give a single T1 value. A simple transient effect method for the determination of the spin-lattice relaxation time using continuous wave NMR with a marginal oscillator, known as TEDSpiL, was recently reported (doi:10.1002/mrc.4594). Such a system measures a parameter, called Tx, that is related to T1 and allows T1 to be determined with the aid of calibration samples. For such a system, the process of making the Tx measurement only takes a few seconds and does not require variable parameters so is ideal for implementing in microcontroller code. In this presentation, we demonstrate that TEDSpiL may be automated using two microcontrollers from the Teensy family. One microcontroller is used to generate a magnetic field sweep voltage and a trigger pulse for the second microcontroller that is used to record the data and calculate the value of Tx. Whilst the Tx value is not a direct equivalent for T1, there are applications where such a method may provide a suitable cost effective, low power and portable measurement technique.

The present article describes the methodology used to design and calibrate a 6-component balance. This balance is utilized in an instrumented bike measuring the forces applied on the handlebars. This instrumentation bike maps all riders induced loads. In the designing process, Finite Element Analysis was used. Calibrating the balance was done using the Least Square Regression Method which allows combining multiple loads during calibration and thus requires less samples. The balance operates with a maximum full scale error of 0.53%.

Ultrasonic transducers are used in many fields of application, including medical imaging/treatment, non-destructive testing and material characterization. To assure the quality of the ultrasonic investigation transducers require regular checks for possible deterioration and accurate calibration. Current methods rely on point-by-point scanning of the ultrasound field with a needle hydrophone, which is expensive and time consuming. Recently, we have developed a new concept, in which a fast full-field visualization of the radiation field is achieved through Acoustically induced PiezoLuminescence (APL). Here, we report on an improved ultrasonic beam visualization and provide further insights into the mechanism underlying APL and mechanoluminescence.

NASA RapidScat is the first Ku-Band wind scatterometer that flown in non-Sun-synchronous orbit. RapidScat is capable of measuring ocean vector winds over the full diurnal cycle, instead of observing a given location at a fixed time of day. The RapidScat operated onboard the International Space Station between September 2014 and August 2016. This unique platform facilitated global contiguous geographical sampling between the ±56 latitude. Non-Sun-synchronous orbit also enables the overlap with other satellite instruments that have been flying in Sun-synchronous orbits. To serve as a cross-calibration reference with other instruments, RapidScat must be carefully calibrated. This paper presents the double-difference methodology to scatterometry. The methodology has been adopted for the cross-instrument calibration between RapidScat and QuikScat scatterometers simultaneously orbiting the Earth on- board two independent satellite platforms. The statistical analysis and measurements biases have been evaluated between the two scatterometers. Calculated biases may be used for measurement correction and reprocessing. This work summarizes the comparison measurements data in the period from January 2015 to August 2016. This research was performed under the grant from the NASA Headquarters and oth RapidScat and QuikScat datasets were provided by the NASA Physical Oceanography Distributed Active Archive Center (PODAAC) at the Jet Propulsion Laboratory.

This work was included in a wider project oriented to the improvement of residual neuromuscular skills in disabled athletes playing wheelchair rugby: the wheelchair rugby Italian national team was involved and tests allowed to analyse the impact loads on a rugby wheelchair frame. The frame of a rugby wheelchair offensive model, made by OffCarr Company, was instrumented with four strain gauge bridges in four different points. Then, three test types were conducted in laboratory: two static calibrations with the application of known loads, the first with horizontal load and the second with vertical load, and a dynamic horizontal calibration, impacting against a fix load cell in order to validate the results of horizontal static calibration. Finally, a test session took place in the field with the collaboration of two team players. The test consisted in voluntary frontal impacts between the two players, starting from 6 meters distance each other. The opponent of the instrumented wheelchair was a defender. From this test, the value of the horizontal load received by the frame in the impact instant was quantified. Moreover, also the vertical load acting on the wheelchair during the rebound of the player after the hit was evaluated: these informations were useful to the wheelchair frame manufacturer for the proper static, impact and fatigue design.

This paper presents an approach to estimate the attitude of skis for an entire ski jump using wearable, MEMS-based, low-cost Inertial Measurement Units (IMUs). First of all, a kinematic attitude model based on rigid-body dynamics and a sensor error model considering bias and scale factor error are established. Then, an extended Rauch-Tung-Striebel (RTS) smoother is used to combine measurement data provided by both gyroscope and magnetometer to achieve an attitude estimation. Moreover, parameters for the bias and scale factor error in the sensor error model and the initial attitude are determined via a maximum-likelihood principle based parameter estimation algorithm. By implementing this approach, an attitude estimation of skis is achieved without further sensor calibration. Finally, results based on both the simulated reference data and the real experimental measurement data are presented, which proves the practicability and the validity of the proposed approach.

Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been continuously powered to increase the stability of the sensing layer. However, continuous power is not feasible in many battery-operated applications due to power consumption limitations or the intended intermittent device operation. This work benchmarks two low-power, duty-cycling, and on-demand modes against the continuous power one. The duty-cycling mode periodically turns the sensors on and off and represents a trade-off between power consumption and stability. On-demand operation achieves the lowest power consumption by powering the sensors only while taking a measurement. Twelve thermally modulated SB-500-12 (FIS Inc. Jacksonville, FL, USA) sensors were exposed to low concentrations of carbon monoxide (0–9 ppm) with environmental conditions, such as ambient humidity (15–75% relative humidity) and temperature (21–27 °C), varying within the indicated ranges. Partial Least Squares (PLS) models were built using calibration data, and the prediction error in external validation samples was evaluated during the two weeks following calibration. We found that on-demand operation produced a deformation of the sensor conductance patterns, which led to an increase in the prediction error by almost a factor of 5 as compared to continuous operation (2.2 versus 0.45 ppm). Applying a 10% duty-cycling operation of 10-min periods reduced this prediction error to a factor of 2 (0.9 versus 0.45 ppm). The proposed duty-cycling powering scheme saved up to 90% energy as compared to the continuous operating mode. This low-power mode may be advantageous for applications that do not require continuous and periodic measurements, and which can tolerate slightly higher prediction errors.

Mathematical models are the basic tool that simulates the operation of the Water Distribution System (WDS). Building such a tool is a complex task that requires as much detail as possible. The information needed to build a model can be divided into two categories: network data and WDS operating data. The first group includes pipe and node attributes, such as pipe length, pipe diameter, pipe roughness, junction elevation, and junction demand. The second category includes data specifying network performance such as pump characteristics, water demand patterns, and controls. The quality of these data will reflect the quality (compatibility) of the model. In WDS modeling—especially dynamic modeling—water demand patterns will have a significant impact on model accuracy. The appearance of each pattern may be different; it depends on the type of consumption (domestic, industrial) or the period analyzed. Consumption patterns define the operational work of the WDSs. Changes in water demand patterns may affect the accuracy of the model calibration. Real WDS models were used in this paper. Three simulations were analyzed, with each corresponding to a different period: one year, six months, and one month. Junction demand and water demand patterns were generated from a GIS (Geographic Information System) and SCADA (Supervisory Control and Data Acquisition) database.

The type of wheeled mobile robots (WMRs) may affect the level of positional errors during motion. The errors are inevitable, as caused by imperfections in design to fabrication, and need to be rectified using calibration techniques. This paper uses the odometry method to provide improved short-term accuracy with high sampling rates. Odometry is economical and requires fewer landmarks and simpler sensory system to localize WMRs, compared to other existing techniques such as 3D camera error detection. The context introduces an odometry-based method to correct the motion of a WMR with two-wheeled mechanism. Experimental results showed that positional errors were significantly improved after applying outcome of the calibration.

International audience; We report on a micro-hotplate technology platform optimized for the calibration of Scanning Thermal Microscopy probes (SThM) used in surface temperature measurement mode. The three chips designed include the same heating area with a calibration area of 10 × 10 µm2 where the SThM probes can land. The 1st design allows to study the influence of the nature of the material on the SThM probes thermal contact resistance. The 2nd design includes a resistive temperature sensor (RTD) integrated on the contact area, which is dedicated to evaluate the capability of a probe to measure a surface temperature. The 3rd design has a contact area made of a suspended platinum membrane for coupling SThM probes with optical thermal measurements. The thermal response of a thermocouple (TC) SThM probe was extracted demonstrating the relevance of these chips for SThM probes characterization and calibration.

Cement composites with nano-additions have been vastly studied for their functional applications, such as strain and damage sensing. The capacity of a carbon nanofiber (CNF) cement paste has already been tested. However, this study is focused on the use of CNF cement composites as sensors in regular concrete samples. Different measuring techniques and humidity conditions of CNF samples were tested to optimize the strain and damage sensing of this material. In the strain sensing tests (for compressive stresses up to 10 MPa), the response depends on the maximum stress applied. The material was more sensitive at higher loads. Furthermore, the actual load time history did not influence the electrical response, and similar curves were obtained for different test configurations. On the other hand, damage sensing tests proved the capability of CNF cement composites to measure the strain level of concrete samples, even for loads close to the material’s strength. Some problems were detected in the strain transmission between sensor and concrete specimens, which will require specific calibration of each sensor one attached to the structure. The authors wish to thank the Spanish Ministry of Science and Innovation for their economic support on this research (grant Mat 2009-10866) and Generalitat Valenciana (grant PROMETEO/2013/035).

Almost automatic quantitative analysis of biofluids is now behind only a few clicks from sample to EXCEL table after minimal sample preparation (move 0.3 ml sample into NMR tube and add buffer), without separations, calibration and reference materials, even for unknown compounds! Each organic compound with protons gives a highly diagnostic and unique NMR spectrum which is practically identical with any spectrometer operating at certain field. A distinctive feature of high-resolution 1D NMR spectra is that even the most complex spectrum of a compound can be described by a few spectral parameters within experimental accuracy, employing a quantum mechanical theory. The NMR spectral parameters offer also a very efficient way to store the spectra in Adaptive Spectral Libraries (ASL), instead of variable quality experimental spectra. Once metabolite spectra have been measured and modelled in one magnetic field strength using Quantum Mechanical Spectral Analysis (QMSA), the spectra can be simulated in every detail in any other field and mixtures – to be used in quantification of the mixtures with ChemAdder software. The protocol has been applied so far to plasma [1], volatile fatty acids from biowaste [2] and slaughterhouse waste [3]. These projects and the software (see http://chemadder.com) are described in our presentation. [1] M. Tiainen, P. Soininen, R. Laatikainen, Quantitative Quantum Mechanical Spectral Analysis (qQMSA) of 1H NMR Spectra of Complex Mixtures and Biofluids, J.Magn.Reson., 242, 67 (2014); [2] E. den Boer, A. Łukaszewska, W. Kluczkiewicz, D. Lewandowska, K. King, T. Reijonen, T. Kuhmonen, A. Suhonen, A. Jaaskelainen, A. Heitto, R. Laatikainen, E. Hakalehto. Volatile fatty acids as an added value from biowaste, Waste Management, Available online, http://dx.doi.org/10.1016/j.wasman.2016.08.006; [3] S. Schwede, E. Thorin, J. Lindmark, P. Klintenberg, A. Jaaskelainen, A. Suhonen, R. Laatikainen, E. Hakalehto. Using slaughterhouse waste in a biochemical based biorefinery -results from pilot scale tests. Environmental Technology, Available online, http://dx.doi.org/10.1080/09593330.2016.1225128

This paper describes the design, development and evaluation tests of an integrated force sensor prototype for portable Coordinate Measuring Arms (CMAs or AACMMs). The development is based on the use of strain gauges located on the surface of the CMAs’ hard probe. The strain gauges as well as their cables and connectors have been protected with a custom case, made by Additive Manufacturing techniques (Polyjet 3D). The same method has been selected to manufacture an ergonomic handle that includes trigger mechanics and the electronic components required for synchronizing the trigger signal when probing occurs. The paper also describes the monitoring software that reads the signals in real time, the calibration procedure of the prototype and the validation tests oriented towards increasing knowledge of the forces employed in manual probing. Several experiments read and record the force in real time comparing different ways of probing (discontinuous and continuous contact) and measuring different types of geometric features, from single planes to exterior cylinders, cones, or spheres, through interior features. The probing force is separated into two components allowing the influence of these strategies in probe deformation to be known. The final goal of this research is to improve the probing technique, for example by using an operator training programme, allowing extra-force peaks and bad contacts to be minimized or just to avoid bad measurements, The authors thank the Spanish Ministry of Economy and Competitiveness for its financial support of the project Quality assurance and knowledge modelling applied to portable coordinate measuring systems, ref. DPI2012-36642, through FEDER (ERDF) funds. This work was also supported by two student grants awarded by the University Institute of Industrial Technology of Asturias (IUTA, ref. SV-13-GIJON-1.8 and SV-14-GIJON1.4)

Background: Active coating is an important unit operation in the pharmaceutical industry. The quality, stability, safety and performance of the final product largely depend on the amount and uniformity of coating applied. Active coating is challenging regarding the total amount of coating and its uniformity. Consequently, there is a strong demand for tools, which are able to monitor and determine the endpoint of a coating operation. In previous work, it was shown that Raman spectroscopy is an appropriate process analytical tool (PAT) to monitor an active spray coating process in a pan coater [1]. Using a multivariate model (Partial Least Squares) the Raman spectral data could be correlated with the coated amount of the API diprophylline. While the multivariate model was shown to be valid for the process in a mini scale pan coater (batch size: 3.5kg cores), the aim of the present work was to prove the robustness of the model by transferring the results to tablets coated to a micro scale pan coater (0.5kg). Method: Coating experiments were performed in both, a mini scale and a micro scale pan coater. The model drug diprophylline was coated on placebo tablets. The multivariate model, established for the process in the mini scale pan coater, was applied to the Raman measurements of tablets coated in the micro scale coater for 6 different coating levels. Then, the amount of coating, which was predicted by the model, was compared with measurements using UV spectroscopy. Results: For all the 6 coating levels the predicted coating amount was equal to the amounts obtained by UV spectroscopy within the statistical error. Thus it was possible to predict the total coating amount with an error smaller than 3.6%. The root mean square of errors for calibration and prediction (RMSEC and RMSEP) was 0.335mg and 0.392mg which means that the model's predictive power is not dependent on the scale or the equipment. Conclusion: The scale-down experiment showed that it was possible to transfer the model developed on a mini scale coater to a micro scale coater. References: [1] J. Muller et al., Feasibility of Raman spectroscopy as PAT tool in active coating, Drug Dev Ind Pharm (2010) 36, 234-243. Acknowledgment: This work was supported by TAMOP-4.2.1/B-09/1/KONV-2010-0005(Hungary), P-MOB/817 (Hungary) and DAAD Project PPP Ungarn 50430305 (Germany).

Laboratory spectroscopy has proved its reliability for estimating soil organic carbon (SOC) by exploiting the relationship between electromagnetic radiation and key spectral features of organic carbon located in the VIS-NIR-SWIR (350&ndash, 2500 nm) region. While this approach provides SOC estimates at specific sampling points, geo-statistical or interpolation techniques are required to infer continuous spatial information. UAS-based proximal or remote sensing has the potential to provide detailed and spatially explicit spectral sampling of the topsoil at the field or even watershed scale. However, the factors affecting the quality of spectral acquisition under outdoor conditions need to be considered. In this study, we investigate the capabilities of two portable hyperspectral sensors (STS-VIS and STS-NIR), and two small-form multispectral cameras with narrow bands in the VIS-NIR region (Parrot Sequoia and Mini-MCA6), to predict SOC content. We collected spectral data under both controlled laboratory and outdoor conditions, with the latter being affected by variable illumination and atmospheric conditions and sensor-sample distance. We also analysed the transferability of the prediction models between different measurement setups by aligning spectra acquired under different conditions (laboratory and outdoor) or by different instruments. Our results indicate that UAS-compatible small-form sensors can be used to reliably estimate SOC. The results show that: (i) the best performance for SOC estimation under outdoor conditions was obtained using the VIS-NIR range, while the addition of the SWIR region decreased the prediction accuracy, (ii) prediction models using only the narrow bands of multispectral cameras gave similar or better performances than those using continuous spectra from the STS hyperspectral sensors, and (iii) when used in outdoor conditions, the micro hyperspectral sensors substantially benefitted from a laboratory model calibration followed by a spectral transfer using an internal soil standard. Based on this analysis, we recommend VIS-NIR portable instruments for estimating spatially distributed SOC data. The integration of these sensors in UAS-mapping devices could represent a cost-effective solution for soil research and precision farming applications when high resolution data are required.

The high-pressure, high-temperature behavior of iron was investigated to 140 GPa and 3500 K with in situ synchrotron X-ray diffraction. Iron samples were compressed in diamond-anvil cells and heated up with the double-sided laser-heating system installed at the high-pressure ID27 of the European Synchrotron Radiation Facility (ESRF). Three different structures, namely α-bcc, γ-fcc or ε-hcp Fe were identified as a function of pressure and temperature in the domain we explored. At pressures above 90 GPa, it is clearly shown that ε-iron is the single stable solid phase up to 160 GPa at high temperatures. The analysis of the P-V-T relationship allows us to propose a reliable experimental thermal equation of state (EoS) for iron. We also show that the addition of low pressure points to our EoS refinement yields more robust constrain on the determination of the reference volume V0 of the ε-hcp structure, which has important implications on the final parametrization of the equation of state. The extrapolation of the proposed EoS to core pressure conditions indicates that a pure iron core would have an excess of density of 3% compared to the PREM density profile.