Flow Sensor Research Articles

Agronomic response, transpiration and water productivity of four almond production systems under different irrigation regimes

In recent years, more intensive production systems have been developed, coinciding with a growing scarcity of water resources. This context underscores the imperative of prioritizing water productivity (WP) as a critical factor in choosing the optimal production system to minimize agricultural water use. This study aims to contribute by evaluating WP in almond orchards under four production systems: open vase with severe pruning (open vase), open vase with minimal pruning (open vase (MP)), central axis and hedgerow. Three irrigation treatments were applied over two consecutive growing seasons: fully irrigated, mild stress and severe stress. Crop transpiration was monitored over the two years using both sap flow sensors and the two-source energy balance (TSEB) model with remote sensing. The severe stress treatment exhibited a notable reduction in kernel yield and nut load of 31.6 % and 34.5 %, respectively, in the second year of water deficit. The hedgerow system tended to have similar kernel yield to the open vase (MP) and central axis systems, and higher compared to the open vase system. Additionally, both transpiration measurement methods revealed that hedgerow exhibited lower transpiration rates across all irrigation treatments. Therefore, the highest WP was observed in the hedgerow system throughout both studied years. Similar findings were derived from the analysis of long-term data. Our findings indicate that the hedgerow production system had the highest WP, averaging 0.43 kg m−3 historically, compared to 0.33 kg m−3 for the open vase, 0.34 kg m−3 for the open vase (MP), and 0.36 kg m−3 for the central axis systems.

Characterization of Gas-Liquid Two-Phase Slug Flow Using Distributed Acoustic Sensing in Horizontal Pipes.

This article discusses the use of distributed acoustic sensing (DAS) for monitoring gas-liquid two-phase slug flow in horizontal pipes, using standard telecommunication fiber optics connected to a DAS integrator for data acquisition. The experiments were performed in a 14 m long, 5 cm diameter transparent PVC pipe with a fiber cable helically wrapped around the pipe. Using mineral oil and compressed air, the system captured various flow rates and gas-oil ratios. New algorithms were developed to characterize slug flow using DAS data, including slug frequency, translational velocity, and the lengths of slug body, slug unit, and the liquid film region that had never been discussed previously. This study employed a high-speed camera next to the fiber cable sensing section for validation purposes and achieved a good correlation among the measurements under all conditions tested. Compared to traditional multiphase flow sensors, this technology is non-intrusive and offers continuous, real-time measurement across long distances and in harsh environments, such as subsurface or downhole conditions. It is cost-effective, particularly where multiple measurement points are required. Characterizing slug flow in real time is crucial to many industries that suffer slug-flow-related issues. This research demonstrated the DAS's potential to characterize slug flow quantitively. It will offer the industry a more optimal solution for facility design and operation and ensure safer operational practices.

Flow-Independent Thermal Conductivity and Volumetric Heat Capacity Measurement of Pure Gases and Binary Gas Mixtures Using a Single Heated Wire.

Among the different techniques for monitoring the flow rate of various fluids, thermal flow sensors stand out for their straightforward measurement technique. However, the main drawback of these types of sensors is their dependency on the thermal properties of the medium, i.e., thermal conductivity (k), and volumetric heat capacity (ρcp). They require calibration whenever the fluid in the system changes. In this paper, we present a single hot wire suspended above a V-groove cavity that is used to measure k and ρcp through DC and AC excitation for both pure gases and binary gas mixtures, respectively. The unique characteristic of the proposed sensor is its independence of the flow velocity, which makes it possible to detect the medium properties while the fluid flows over the sensor chip. The measured error due to fluctuations in flow velocity is less than ±0.5% for all test gases except for He, where it is ±6% due to the limitations of the measurement setup. The working principle and measurement results are discussed.

Detection of H2O2 and catalase on a paper-based flow sensor constructed with borate cross-linked PVA hydrogel

The detections of H2O2 and catalase play an important role in daily life. This study introduces a paper-based flow sensor that is specifically designed to detect H2O2 and catalase. The sensor utilizes a hydrogel composed of cross-linked 4-carboxyphenylboronic acid and polyvinyl alcohol. When H2O2 is in contact with the hydrogel, the B–C bonds of the hydrogel undergo a reactive process, causing decomposition of the hydrogel. The pH indicator strip enables the visual monitoring of the viscosity change that occurs during the gel-sol transition. The quantification of H2O2 is accomplished by assessing the proportion of water coverage on the pH indicator strip. The sensor shows a detection limit of 0.077 wt% and is applicable for the quantitative measurement of H2O2 in routinely used disinfectants. Furthermore, the presence of catalase is effectively identified and the detection of catalase in milk is successfully fulfilled. In summary, this work proposes a simple, user-friendly, label-free, and cost-effective method for constructing a paper-based flow sensor using borate cross-linked polyvinyl alcohol hydrogel, showing great potential for detecting H2O2 and catalase in various practical scenarios.

External Jet Nebulization and Measured Ventilator Performance.

During invasive ventilation, external flow jet nebulization results in increases in displayed exhaled tidal volumes (VT). We hypothesized that the magnitude of the increase is inaccurate. An ASL 5000 simulator measured ventilatory parameters over a wide range of adult settings: actual VT, peak inspiratory pressure (PIP), and time to minimum pressure. Ventilators with internal and external flow sensors were tested by using a variety of volume and pressure control modes (the target VT was 420 mL). Patient conditions (normal, COPD, ARDS) defined on the ASL 5000 were assessed at baseline and with 3.5 or 8 L/min of added external flow. Patient-triggering was assessed by reducing muscle effort to the level that resulted in backup ventilation and by changing ventilator sensitivity to the point of auto-triggering. Results are reported as percentage change from baseline after addition of 3.5 or 8 L/min external flow. For ventilators with internal flow sensors, changes in displayed exhaled VT ranged from 10% to 118%, however, when using volume control, actual increases in actual VT and PIP were only 4%-21% (P = .063, .031) and 6%-24% (P = .25, .031), respectively. Changes in actual VT correlated closely with changes in PIP (P < .001; R2 = 0.68). For pressure control, actual VT decreased by 3%-5% (P = .031) and 4%-9% (P = .031) with 3.5 and 8 L/min respectively, PIP was unchanged. With external flow sensors at the distal Y-piece junction, volume and pressure changes were statistically insignificant. The time to minimum pressure increased at most by 8% (P = .02) across all modes and ventilators. The effects on muscle pressure were minimal (∼1 cm H2O), and ventilator sensitivity effects were nearly undetectable. External flow jet nebulization resulted in much smaller changes in volume than indicated by the ventilator display. Statistically significant effects were confined primarily to machines with internal flow sensors. Differences approached the manufacturer-reported variation in ventilator baseline performance. During nebulizer therapy, effects on VT can be estimated at the bedside by monitoring PIP.

Impact of Fruit Load on the Replenishment Dynamics of Internal Water Reserves in Olive Trees

Stem refilling has been studied in many forest species, but its impact on olive trees remains underexplored. This study aims to examine the effect of varying fruit loads on stem refilling rates in olive trees. The experiment was conducted in a commercial olive orchard over two years, characterized by a biennial bearing cycle with minimal fruit production in 2021 (“OFF” year) and maximal fruit production in 2022 (“ON” year). Sap flow sensors measured the water volume differences traversing the apex and base of main branches in two experimental trees. Tree water status was monitored using psychrometers, and soil moisture content was continuously recorded. Results suggest that alternate bearing significantly affects the stem refilling process, while soil moisture availability also plays a pivotal role. During the “ON” year, water reserve consumption increased to 63.6% compared to the “OFF” year to meet the water requirements of developing fruits. Replenishment occurred at various times throughout the 24 h period, including early morning, afternoon, and night when stomatal conductance measurements indicated stomatal closure. During the “ON” year, olive trees experienced intense nocturnal replenishment of reserves, regardless of soil moisture, water vapor pressure deficit, or fruit development stage. These findings offer novel insights into olive trees’ rehydration dynamics that can be used to optimize irrigation scheduling and improve water use efficiency.

Optimizing an Autonomous Robot’s Path to Increase Movement Speed

The goal of this study is to address the challenges associated with identifying and planning a mobile land robot’s path to optimize its speed in a stationary environment. Our focus was on devising routes that navigate around obstacles in various spatial arrangements. To achieve this, we employed MATLAB R2023b for trajectory simulation and optimization. On-board data processing was conducted, while obstacle detection relied on the omnidirectional video processing system integrated into the robot. Odometry was facilitated by engine encoders and optical flow sensors. Additionally, an external video system was utilized to verify the experimental data pertaining to the robot’s movement. Last but not least, the algorithms and hardware equipment used enabled the robot to go along the path at greater speeds. Limiting the amount of time and energy required to travel allowed us to avoid obstacles.

Industrial-Based GSM Water Leakage Detection, Monitoring and Controlling System: A case of North Rift Valley Water Agency in Kenya

The current system for detecting and monitoring water leaks in Kenyan industries is manual and costly. Despite emerging new technological trends, many industries lack automated systems to detect, monitor, and control water leakage due to the high cost of maintenance and installation. This study's objective was to develop an automatic, remote, and real-time detection, monitoring, and, control system for water leaks. The system is made up of two nodes, one at the source and one at the destination or tap. The two nodes are made up of an ESP microcontroller, which is used to control all the connected components. The use of the ESP 32 microcontroller was efficient due to its ability to provide WI-FI. Aside from the solenoid valve, which was used to turn the water flow on or off in the event of leaks, the system also includes the FY-201 water flow sensor, which was used to gauge the amount of water flowing through the pipe. Water leakage is detected when the volume of water passing through the two sensors differs in terms of volume, indicating that a water leakage has just occurred. Thing-Board, an IoT-based platform used to monitor and visualize data from various devices connected, was used for real-time monitoring, visualization, and control. The developed system was tested with different water service providers, and the results showed that the system responds positively to water leakage parameters with capability of monitoring water leakages in a real time.

On-chip resistive microfluidic flow sensor with reduced analysis time using transient analysis

On-chip resistive microfluidic flow sensor with reduced analysis time using transient analysis

IOT based water flow meter using ThingSpeak

The Large scale manufacturing companies are fully automated. Soft Drink Industries and Chemical industries have to constantly measure and quantify the liquids that they are handling during this automation process, and the most common sensor used to measure the flow of a liquid is a Flow Sensor. By using a flow sensor with a microcontroller like NodeMCU, we can calculate the flow rate, and check the volume of liquid that has passed through a pipe, and control it as required. Apart from manufacturing industries, flow sensors can also be found in the agriculture sector, food processing, water management, mining industry, water recycling, coffee machines etc. Further, a water flow sensor will be a good addition to projects like Automatic water dispenser and smart irrigation systems where we need to monitor and control the flow of liquids. In this project, we are going to build a water flow meter using NodeMCU. We will interface the water flow sensor with NodeMCU and LCDI2C, and program it to display the volume of water, which has passed through the valve. For this particular project, we are going to use the YF-S201 water flow sensor, which uses a hall effect to sense the flow rate of the liquid. The measured values are also communicated to the ThingSpeak cloud. The parameters can be monitored remotely form any part of the world. When the volume exceeds the threshold value, Thingspeak will activate the Thingspeak react to send a message to the responsible person with help of the IFTTT applet.

Effectiveness of Nursing Strategies on Risk for Pneumonia Among Patients Connected to Mechanical Ventilator in Intensive Care Unit

It has been reported that the incidence of nosocomial infections in the ICU is about 2–5 times higher than in the general in-patient hospital population. The study's objective was to evaluate the effectiveness of Nursing Strategies on Risk for Pneumonia among Patients connected to Mechanical Ventilator in Intensive Care Unit. The study adopted randomized controlled trial. Forty patients were enrolled in the study after screening using CPIS scale. If the score &lt;6 the patients were included in the study and eligibility criteria were age between 25 to 60 years, duration of ventilator 48 hours and medical patients with respiratory, renal, MODS, and sepsis diagnosis. Patients subjected to surgery and connected with non-invasive ventilation were excluded from the study. Standardized questionnaire such as demographic variables, clinical variables, and Clinical Pulmonary Infection Scoring (CPIS). The data was analyzed using descriptive statistics, independent ‘t’ test, paired t test and ANOVA were used to analyze the data. Seven (35%) of them were in the age group of 51-60 years in the study group, whereas six (30%) of the patients were in the age group of 61-70 years in the control group. 12(60%) of the patients were male and eight (40%) of them were female in the study group and 10(50%) of patients were male and female respectively in the control group. Regarding mode of ventilation, 12(50%) and six (30%) of patients ventilator setting were CMV and ASV respectively, in the study group, whereas seven (35%) and six (30%) of patients ventilator settings were ASV and CMV respectively in the control group. The pretest CPIS mean score was 4.40 with a standard deviation of 0.59 and the posttest III mean value was 2.60 with a standard deviation of 0.58 and the mean difference was 1.80 between the pretest and the posttest III, which was statistically significant at p&lt;0.001 in the study group. Nursing strategies such as demand suctioning, second hourly position change, changing ventilator flow sensor every 72 hours, and oral care every fourth hour with chlorhexidine help reduce ventilator-associated pneumonia.

Portable Low-Cost Home Sleep Monitor using Wemos D1 Mini

Sleeps disorders are a common disease overlooked by many people. Sleep disorder have many types and kinds and often associated with other severe illness such as diabetes, stroke, obesity and many others. Sleep monitors are one of many ways to read all parameters related to sleep and detect sleep disorders the subject has, however access to sleep monitor still expensive and tough to come by. Because of that accessibility, countless development of home sleep monitor occured around the world. However, most of that device still hard to operate and some of them gives error readings of parameters. Based on this, a portable low-cost home sleep monitor was developed using Wemos D1 mini as a microcontroller, MAX30102 as an oxygen level sensor, MPU6050 as an accelerometer, DS18B20 as a breathing flow sensor, and MAX9814 as a microphone. Each of the sensors read and give value to microcontroller and store the data to cloud and display the result in user’s gadget. The aim of this development is to detect sleep disorders associated with each reading of sensors used and determine sleep quality as an early detection of symptoms before referring to professional relaled to sleep disorders or doctors.

Characterization of Sand and Dust Pollution Degradation Based on Sensitive Structure of Microelectromechanical System Flow Sensor.

The effect of sand and dust pollution on the sensitive structures of flow sensors in microelectromechanical systems (MEMS) is a hot issue in current MEMS reliability research. However, previous studies on sand and dust contamination have only searched for sensor accuracy degradation due to heat conduction in sand and dust cover and have yet to search for other failure-inducing factors. This paper aims to discover the other inducing factors for the accuracy failure of MEMS flow sensors under sand and dust pollution by using a combined model simulation and sample test method. The accuracy of a flow sensor is mainly reflected by the size of its thermistor, so in this study, the output value of the thermistor value was chosen as an electrical characterization parameter to verify the change in the sensor's accuracy side by side. The results show that after excluding the influence of heat conduction, when sand particles fall on the device, the mutual friction between the sand particles will produce an electrostatic current; through the principle of electrostatic dissipation into the thermistor, the principle of measurement leads to the resistance value becoming smaller, and when the sand dust is stationary for some time, the resistance value returns to the expected level. This finding provides theoretical guidance for finding failure-inducing factors in MEMS failure modes.

Experimental study of dynamic pressure disturbances in cylindrical pipes filled with liquid

Diagnostics of the condition of main pipelines is an important task to ensure the safe operation of fuel and energy complex facilities. Many technological processes, including emergency ones, cause disturbances in the flow of the pumped liquid, resulting in dynamic disturbances propagating through the pipeline. Using pressure measuring instruments, wave parameters are recorded, by analyzing which it is possible to determine the location of the source and the reason causing this disturbance. In this work, dynamic pressure disturbances propagating through the pipeline of the laboratory installation “Stand with a variable profile for the study of non-stationary processes arising in multiphase hydrocarbon flows” created at Transneft R&amp;D were investigated. Dynamic disturbances are formed due to the selection of part of the pumped liquid into the reservoir. The data obtained during the experiment, from pressure and flow sensors, were processed according to the original method proposed by the authors in order to determine the location of the source of disturbance. A series of experiments was also carried out to assess the accuracy of localization of the disturbance source depending on the amplitude of the pressure wave.

A high-sensitivity calorimetric digital flow meter for respiratory monitoring and proximal flow measurement in neonatal ventilation

In this paper, a high-sensitivity digital flow meter, featuring a low-power Thermo-resistive Micro Calorimetric Flow (TMCF) sensor fabricated by CMOS-MEMS technology, is presented for respiratory monitoring and neonatal ventilator-assisted ventilation. The packaging of the TMCF sensor has been meticulously optimized to achieve a 1.5-fold increase in sensitivity, resulting in a high sensitivity of 76.5 mV/SLM in the linear range of −7.5SLM to 7.5SLM, and its heating power is only 2.23 mW. The developed digital flow meter is quantized into a 14 bit output within the flow measurement range of −40SLM to 40SLM, providing a high resolution down to 0.005SLM. With a remarkable response time of less than 11.5 ms, corresponding to a bandwidth of 13.8 Hz, and equipped with a 2 kHz data update rate, our proposed digital flow meter excels in capturing abrupt changes in breathing and high-frequency respiratory signals. Furthermore, boasting a noise level below 0.0025SLM, the sensor system demonstrates the capability to identify subtle variations in respiratory flow. Based on its outstanding performance, the high-sensitivity digital flow meter effectively identifies simulated abnormal respiratory patterns, including apnea, polypnea, and hypopnea, and successfully performs closed-loop ventilation measurements for neonates on a ventilator. Therefore, it holds promising potential as a crucial sensing component with high precision, high sensitivity, and low power consumption in respiratory monitoring and neonatal ventilation therapy.

Printed bioinspired piezoelectric nano-hair for ultrahigh sensitive airflow detection

Micro/nanoscale hairs found in living organisms combine many inspiring properties such as miniaturization, low power consumption, adaptability, and the sensing of signals. Mimicking these excellent biological hairs provided an effective way to develop advanced artificial sensing sensors. Here, a printed bioinspired piezoelectric nano-hair with ultra-high sensitivity was developed for airflow detection. A novel nanoscale electrohydrodynamic jet 3D printing method was developed to fabricate PZT nano-hair with controllability, fast, and inexpensive characteristics. Various PZT nano-hairs down to the scale of 200 nm with high aspect ratio features of 523 were directly printed. Herein, the printed PZT nano-hair exhibited pure perovskite structures, excellent mechanical properties, and a high piezoelectric coefficient. This bioinspired PZT hair sensor demonstrated that the novel printed PZT hair airflow sensor showed ultra-high detection sensitivity to low-speed airflow (0.02 m s−1). This novel nanoprinting strategy and the printed PZT nano-hair indicate the development of functional nanostructures inaccessible by traditional manufacturing methods.

IOT Based Smart Agriculture System For Crop Monitoring And Management

The aim of this project presents a Low Cost GSM Based Automated Irrigation System Using Arduino, Sensors and GSM Module. We use GSM Module so the Module sending the data to the Thing-speak server where it acts as front end to observe the sensor dynamic values and we can check the status of the water pump. It also acts as back end to store the data. The prototype is design in such a way that it will pump the water into the field as per our requirement depending on the weather conditions. The sensors used in the system are DHT11 Sensor (for sensing both humidity and temperature), Water Flow Sensor, Soil Moisture Sensor. Key Words: Temperature, Humidity, Soil Moisture Sensor, Relay, Water Pump motor, Internet of things, Sim 800gsm module, etc.

An Optical Fiber Multiphase Flow Sensor Based on Identification of Bubble Collision and Bounce

An Optical Fiber Multiphase Flow Sensor Based on Identification of Bubble Collision and Bounce

Effect of vertical stopcock position on start-up fluid delivery in syringe pumps used for microinfusions

The purpose of this in vitro study was to evaluate the impact of the vertical level of the stopcock connecting the infusion line to the central venous catheter on start-up fluid delivery in microinfusions. Start-up fluid delivery was measured under standardized conditions with the syringe outlet and liquid flow sensors positioned at heart level (0 cm) and exposed to a simulated CVP of 10 mmHg at a set flow rate of 1 ml/h. Flow and intraluminal pressures were measured with the infusion line connected to the stopcock primarily placed at vertical levels of 0 cm, + 30 cm and − 30 cm or primarily placed at 0 cm and secondarily, after connecting the infusion line, displaced to + 30 cm and − 30 cm. Start-up fluid delivery 10 s after opening the stopcock placed at zero level and after opening the stopcock primarily connected at zero level and secondary displaced to vertical levels of + 30 cm and – 30 cm were similar (− 10.52 [− 13.85 to − 7.19] µL; − 8.84 [− 12.34 to − 5.33] µL and − 11.19 [− 13.71 to − 8.67] µL (p = 0.469)). Fluid delivered at 360 s related to 65% (zero level), 71% (+ 30 cm) and 67% (− 30 cm) of calculated infusion volume (p = 0.395). Start-up fluid delivery with the stopcock primarily placed at + 30 cm and − 30 cm resulted in large anterograde and retrograde fluid volumes of 34.39 [33.43 to 35.34] µL and − 24.90 [− 27.79 to − 22.01] µL at 10 s, respectively (p < 0.0001). Fluid delivered with the stopcock primarily placed at + 30 cm and − 30 cm resulted in 140% and 35% of calculated volume at 360 s, respectively (p < 0.0001). Syringe infusion pumps should ideally be connected to the stopcock positioned at heart level in order to minimize the amounts of anterograde and retrograde fluid volumes after opening of the stopcock.

High-Performance Airflow Sensors Based on Suspended Ultralong Carbon Nanotube Crossed Networks.

Airflow sensors are in huge demand in many fields such as the aerospace industry, weather forecasting, environmental monitoring, chemical and biological engineering, health monitoring, wearable smart devices, etc. However, traditional airflow sensors can hardly meet the requirements of these applications in the aspects of sensitivity, response speed, detection threshold, detection range, and power consumption. Herein, this work reports high-performance airflow sensors based on suspended ultralong carbon nanotube (CNT) crossed networks (SCNT-CNs). The unique topologies of SCNT-CNs with abundant X junctions can fully exhibit the extraordinary intrinsic properties of ultralong CNTs and significantly improve the sensing performance and robustness of SCNT-CNs-based airflow sensors, which simultaneously achieved high sensitivity, fast response speed, low detection threshold, and wide detection range. Moreover, the capability for encapsulation also guaranteed the practicality of SCNT-CNs, enabling their applications in respiratory monitoring, flow rate display and transient response analysis. Simulations were used to unveil the sensing mechanisms of SCNT-CNs, showing that the piezoresistive responses were mainly attributed to the variation of junction resistances. This work shows that SCNT-CNs have many superiorities in the fabrication of advanced airflow sensors as well as other related applications.