Flow Sensor Research Articles

Comprehensive overview of microfluidic flow sensors: principles, materials, and fabrication

Comprehensive overview of microfluidic flow sensors: principles, materials, and fabrication

Self-adaptive epidermal blood flow sensor for high-flux vascular access monitoring of hemodialysis patients

Well-functioning vascular access (VA) is essential for hemodialysis treatment in patients with end-stage renal disease (ESRD). However, continuous and accurate monitoring of blood flow to assess high-flux VA during hospitalization or at home is not feasible for either clinical instruments or wearable sensors. Here, we report the design and preclinical validation of a high-precision, long-term, epidermal blood flow sensor that self-adapts to unavoidable sensor-mounting deviations on the skin and is compatible with individual tissue differences. Specifically, the technology is based on thermal dissipation of the skin, and improves the signal-to-error ratio surpassing 4 times when measuring high-flux blood (100–600 mL/min). In preclinical validation, the sensor is compared with the Doppler ultrasound and demonstrate a blood flow resolution of 10–50 mL/min. Furthermore, it is highly-integrated and wearable, measuring 36 × 50 mm2. The sensor paves the way for accurate, convenient, high-flux blood monitoring, offering significant potential to extend the lives of patients with ESRD.

CMOS-Compatible MEMS 2D Thermal Flow Sensor With High Sensitivity and Low Power Consumption

CMOS-Compatible MEMS 2D Thermal Flow Sensor With High Sensitivity and Low Power Consumption

An Optimization Design of Piezoelectric Hair Sensor for Oscillatory Flow Detection

Abstract Biological hair is widely found in nature, and they are responsible for sensing and responding to environmental stimuli in living organisms. By simulating biological hair characteristics, they develop hair flow sensor to achieve high sensitivity detection of environmental factors such as small motion and fluid flow field. Output signal is the key indicator of hair flow sensor, and the improvement of output signal is important to the design of hair flow sensor. The existing hair flow sensor sensing structure is generally straight hair, and the output signal is limited by the structure, and the response is small. Using the direct piezoelectric fiber as the initial configuration, we form a new piezoelectric curved fiber by modeling the secondary spline curve and control point. We propose an optimization model for piezoelectric functional hair design using axial strain as a target function. At 100Hz and 500Hz, the output voltage of the optimized model is much higher than that of straight, 10 times and 7 times that of straight, respectively; An optimized curved hair configuration is obtained in a specific frequency band from 1 Hz to 500 Hz, whose average voltage magnitude of 3.1×10−3 V is 4 times greater than that of the straight hair of 7.8×10−4 V with the same size. The curved hair flow sensor breaks the output limitation of traditional straight hair configuration.

House FIRSTLIFE in student contest and in Living Lab

Abstract The paper comments on selected measurements and observations related to the FIRSTLIFE house demonstration unit, which was prepared by the team of the Czech Technical University for the international competition Solar Decathlon Europe 21/22 with its final at the Solar Campus in Wuppertal, Germany. The paper comments on the measurement results obtained during the competition in the field of building physics (thermal and moisture comfort, measurement of air permeability, measurement of sound insulation of the perimeter wall and dynamic co-heating test). The second part of the paper describes selected follow-up activities. For the purposes of the Living Lab, eight of the competition houses remained on the Solar Campus for at least another 3 years. This allowed long-term monitoring and targeted experiments to be carried out and some of the earlier measurements to be repeated under different climatic boundary conditions. For this phase, additional sensors were added in the Czech house, such as a meteorological station and temperature and heat flow sensors in the perimeter wall. Part of the data comes directly from the building management system. The paper comments on first results from Living Lab period.

Fuzzy Logic-based Current Control Logic for Proportional Flow Control Valve System of Medical Ventilators

The critical control parameters in ventilators that provide life support to patients are the flow of air and oxygen. Ventilators typically use Proportional Flow Control Valves (PFCV) and flow sensors to achieve precise flow accuracy. Maintaining accurate flow from the PFCV is essential to minimize the thrust exerted on the patient's lungs. Fuzzy logic is particularly well-suited for this task, as it effectively captures the subjective human judgments often required in clinical settings. This study aimed to develop a fuzzy logic algorithm to control pressure support ventilation. The research describes the fuzzy logic algorithm and presents experimental studies that evaluated the flow accuracy of a commercially used PFCV in ventilators. Additionally, the reduction in output flow due to thermal effects was investigated. A correlation between the solenoid coil current (measured as voltage across the coil) and the actual output flow through the PFCV was experimentally established using a current sensing circuit. Based on the characteristic curves obtained from the test setup, a Fuzzy Logic system was developed to minimize the error in the PFCV's flow. The implementation of PFCV using this Fuzzy Logic-based current control approach demonstrated a significant reduction in error, from 10% to 3%, in airflow delivery across its operating range, with additional sample results discussed. This reduction in flow error is crucial for assessing the suitability of PFCVs in infant ventilators. The described methodology can be experimentally applied to any PFCV variant before its use in medical ventilator applications to enhance delivered flow accuracy.

THERMAL TECHNOLOGICAL CONDITION OF IVG.1M RESEARCH REACTOR CORE UNDER VARIOUS OPERATING MODES

The relevance of the study is related to the determination of the thermal characteristics of the IVG.1M research reactor core with the low enriched uranium fuel under the nominal and design operating modes. The thermal technological condition of the IVG.1M research reactor during the start-up are determined by the readings of the temperature, pressure and coolant flow sensors of the information and measuring system. The indirect methods including the computer simulating ones are used to determine the temperature of the core structural materials and the distribution of the coolant temperature by the height of the fuel assembly. The research has been carried out using the method of the finite element analysis using the ANSYS Fluent software package. The study goal was to verify the adequacy of the calculation methodology and obtain the calculated data on the temperature distribution in the fuel assembly in the reactor power range from the nominal to design one. The article presents a description of the IVG.1M reactor, the research methodology, computer model, simulation results and the comparison of the calculated data with the experimental ones. The study scientific novelty consists in determining the temperature conditions of the fuel rods during the reactor operation at various levels of the design capacity with a conservative approach to the cooling conditions. The significance of the research results lies in the fact that a computer model can be used to determine the characteristics of the IVG.1M reactor core under the reactor various operating modes and to analyze the thermohydraulic processes in the fuel assembly.

Understanding the limitations of grain yield monitor technology to inform on‐farm research

AbstractYield monitoring technology (YM) is a valuable tool to evaluate crop performance in on‐farm research (OFR). However, limited information exists on utilizing this technology to accurately inform OFR. The objectives of this study were to evaluate the ability of grain yield monitor mass flow sensors to detect changes in corn (Zea mays L.) yield for different plot lengths, provide a recommended minimum plot length to utilize YM in OFR, and determine if differences in estimating yield existed between YMs. Six treatment lengths that varied in distance of intentional yield differences (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were created by alternating high‐yield (202 kg N/ha application) and low‐yield (0 kg N/ha application) plots. A total of four grain YMs with impact‐style mass flow sensors were used within two commercially available combines. Yield comparisons were made between the plot combine and YMs to evaluate the accuracy of each technology for detecting the magnitude of yield change across lengths using analysis of variance and exponential regression curves. Results indicated that the mass flow sensors were not sensitive enough to detect quickly changing flow rates for alternating yield changes in small plot lengths. Minimum plot lengths ranged from 43 to 107 m depending on YM. Significant differences were observed between grain YMs from different manufacturers. Future work could evaluate the influence additional crops or smaller yield differences have on the optimum OFR plot length.

Flexible curved multi-functional sensors for air flow and vibration signal measurement of train bogie

Abstract The fluid-solid coupling effects with the aerodynamic noise and structural vibration signal have great part in measurement accuracy and fault diagnosis of the train bogie. It is important to collect aerodynamic noise and structural vibration data for safety evaluation and on-line structural health monitoring (SHM) of the bogie, which brings new challenges to the integration and installation of the sensors in the limited space and complicated operation condition of the train bogie. Flexible curved multifunctional sensors (FCMFS) integrated with the hot film and structural vibration sensor units is designed to the air flow and structural vibration measurement of the train bogie. Bogie vibration and wind tunnel test platforms with FCMFS are built to the air flow velocity and vibration data measurement on the bogie surface under different operation conditions. Piezoelectric Polyvinylidene fluoride(PVDF) sensors have significant output in the wind tunnel and vibration experiments, and the hot film sensor is only sensitive to the air flow signal. The effect of vibration signal to the hot film sensor could be ignored, which is applied to decouple the aerodynamic noise and structural vibration signals for improving the measurement accuracy of the train bogie. The dynamic performance of FCMFS is verified in Rail Transmit Base of East China Jiaotong University, which is applied to SHM and rapid fault diagnosis of train bogie. The air flow distribution and vibration data are collected to safety assessment and fault diagnosis of train bogie, which would promote the intelligent maintenance level of the train bogie.

Development of a Novel High Temperature Continuous Particle Mass Flow Measurement Device for Particle-Based CSP Applications

Particle-based concentrating solar power (CSP) technology is one of the generation three (Gen3) CSP technologies that has potential for lowering the levelized cost of electricity produced by this solar thermal power systems. Commercially available ceramic particles, which are rated for high temperature applications up to 1200 °C, were selected for this study. This medium is commonly used as an energy carrier or heat transfer medium in Gen3 CSP research and development efforts [1]. Prior studies at the National Solar Thermal Test Facility (NSTTF) have investigated and evaluated various mass flow measurement methods, and a simple gravimetric temporal load measurement method was chosen as the best candidate for the research purpose [2]. This mass flow measurement method is a batch process and is not a viable solution for commercial-scale power generation applications based on cost, space, process control, and practical system integration factors. In-line and continuous particle mass flow measurement will play an integral role in efficient and cost effective Gen3 CSP particle technologies. Process parameters, including energy absorbed by the particles, receiver efficiency, temperature dependent flow phenomena, and general high temperature measurement reliability are all rely on repeatable and accurate measurement of particle mass flow under various operating conditions. Ceramic particles, like those used in this application, are not conventionally used as an energy carrier. A novel concept for continuous particle mass flow at a wide range of operating temperatures is currently under development and planned to be tested at the NSTTF, called the Particle In-LinE (PILE) mass flow sensor.

Merkel cells and corpuscles of Stannius as putative targets for polyethylene terephthalate microfibers in sheepshead minnow larvae

Polyethylene terephthalate (PET) fibers are contaminated in wastewater from various primary sources, such as washing textile waters. PET fibers in the environment can be degraded into microfibers because of weathering processes such as sunlight, physical wear, and heat. Although recent studies reported adverse effects of PET microfibers on aquatic organisms, the lack of information on their toxicity and mode of action hampers the risk assessment of PET microfibers. Therefore, this study aimed to investigate the biological effects of PET microfibers and their underlying mechanisms in early-staged sheepshead minnows (Cyprinodon variegatus). PET microfibers (about 13 μm diameter × 106 μm length) were prepared by cutting PET threads and treated to sheepshead minnow larvae at 10 and 100 mg/L for 10 days. No acute toxicity was found in the minnow, but PET microfibers significantly produced reactive oxygen species and reduced behavioral responses of traveled distance and maximum velocity. The transcriptomic data suggested that Merkel cells (flow sensors) and corpuscles of Stannius (calcium regulator) are putative targets, which were derived from oxidative stress, sensory neuropathy, cognitive impairment, and movement disorders. These findings underscore that although PET microfibers are not directly lethal to sheepshead minnows, they could impact their survival by damaging swimming-related key genes. This study provides new insights into how PET microfibers are toxic to aquatic organisms and disrupt ecosystems beyond survival and pathological changes.

IMPLEMENTASI SISTEM MONITORING AIR DENGANSENSOR ULTRASONIK HC-SR04 DAN WATER FLOW DI ASONE HIDROPONIK BERBASIS INTERNET OF THINGS (IoT) MENGGUNAKAN ENERGI PANEL SURYA(PLTS)

The cultivation system using hydroponics is now widely popular among the community because it does not require large areas of land. Using the hydroponic system results in faster and optimal harvests. However, the busy activities of urban communities often cause them to fail in implementing it due to constraints in controlling and monitoring hydroponic plants. Additionally, PLN electricity is essential for operating the water pump, and the electricity load and tariff increases, along with sudden blackouts, significantly impact business actors. To address this problem, this research creates an Internet of Things (IoT)-based water monitoring system for ACONE Hydroponics partners with solar panel (PLTS) energy sources as an alternative energy in the event of a sudden PLN power outage. The sensors used in this system include the HCR-04 ultrasonic sensor to monitor water availability and the water flow sensor to measure water flow (discharge). Sensor data is processed by the ESP32 microcontroller and sent to the Blynk cloud platform via an internet connection and displayed on an LCD. System testing shows that the system can send sensor data to the cloud platform stably and in real-time. Data visualization on the cloud platform is easy to understand and helps hydroponic owners monitor water conditions in hydroponic systems. This water monitoring system can help users optimize water use in hydroponic systems.

Fish-inspired tracking of underwater turbulent plumes

Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of ocean environments by actively steering towards areas of high scientific value. Inspired by the ability of aquatic animals to navigate via flow sensing, this work investigates hydrodynamic cues for accomplishing targeted sampling using a palm-sized robotic swimmer. As proof-of-concept analogy for tracking hydrothermal vent plumes in the ocean, the robot is tasked with locating the center of turbulent jet flows in a 13,000-liter water tank using data from onboard pressure sensors. To learn a navigation strategy, we first implemented RL on a simulated version of the robot navigating in proximity to turbulent jets. After training, the RL algorithm discovered an effective strategy for locating the jets by following transverse velocity gradients sensed by pressure sensors located on opposite sides of the robot. When implemented on the physical robot, this gradient following strategy enabled the robot to successfully locate the turbulent plumes at more than twice the rate of random searching. Additionally, we found that navigation performance improved as the distance between the pressure sensors increased, which can inform the design of distributed flow sensors in ocean robots. Our results demonstrate the effectiveness and limits of flow-based navigation for autonomously locating hydrodynamic features of interest.

Oxygen-sensor-based 2-DOF PI air-flow controller of fuel cell system

Oxygen starvation may occur when oxygen is not replenished quickly after a sudden increase of load in fuel-cell-powered vehicles, leading to permanent damage to the fuel cell membrane. To avoid this phenomenon, the oxygen excess ratio (OER) is usually estimated through observers as it cannot be measured directly. Since observers may suffer from model mismatches that lead to inaccurate OER estimation, a possible modification to the fuel cell system is proposed in this work by including an oxygen flow sensor at its exhaust. Yet the response of this sensor is slow, and to compensate for the slow response of the sensor, a novel two-degree-of-freedom PI controller and a state observer are designed to provide a robust, accurate, and quick estimation and control of the OER.

Hydrodynamic pressure sensing for a biomimetic robotic fish caudal fin integrated with a resistive pressure sensor

Micro-sensors, such as pressure and flow sensors, are usually adopted to attain actual fluid information around swimming biomimetic robotic fish for hydrodynamic analysis and control. However, most of the reported micro-sensors are mounted discretely on body surfaces of robotic fish and it is impossible to analyzed the hydrodynamics between the caudal fin and the fluid. In this work, a biomimetic caudal fin integrated with a resistive pressure sensor is designed and fabricated by laser machined conductive carbon fibre composites. To analyze the pressure exerted on the caudal fin during underwater oscillation, the pressure on the caudal fin is measured under different oscillating frequencies and angles. Then a model developed from Bernoulli equation indicates that the maximum pressure difference is linear to the quadratic power of the oscillating frequency and the maximum oscillating angle. The fluid disturbance generated by caudal fin oscillating increases with an increase of oscillating frequency, resulting in the decrease of the efficiency of converting the kinetic energy of the caudal fin oscillation into the pressure difference on both sides of the caudal fin. However, perhaps due to the longer stability time of the disturbed fluid, this conversion efficiency increases with the increase of the maximum oscillating angle. Additionally, the pressure variation of the caudal fin oscillating with continuous different oscillating angles is also demonstrated to be detected effectively. It is suggested that the caudal fin integrated with the pressure sensor could be used for sensing thein situflow field in real time and analyzing the hydrodynamics of biomimetic robotic fish.

A multi-sensor fusion SLAM algorithm for indoor aerial robots

Nowdays, existing Light Detection and Ranging (LiDAR) based unknown-space-exploration Simultaneous Localization and Mapping (SLAM) methods have the problems of unstable mapping in feature-degraded environments and poor estimation accuracy in the vertical direction. To solve these problems, this study presents a multi-sensor fusion SLAM algorithm for indoor aerial robots as well as Unmanned Aerial Vehicles (UAVs). The sensors used in the multi-sensor fusion algorithm include optical flow sensor, barometer, Inertial Measurement Unit (IMU), and LiDAR. The proposed algorithm is named LiDAR-IMU-optical flow odometry fusion algorithm (Lioo). We derived and established a tightly coupled multi-sensor fusion framework based on factor graph optimisation. The IMU-optical flow pre-integration factor is proposed, and the barometer factor to the algorithm is added innovatively. Engineering applications are also realised in this paper. Flight experiments demonstrated that the proposed algorithm achieves more precise mapping and localisation of UAVs in indoor environments.

On-Site Sensor Sensitivity Adjustment Technique for a Maintenance-Free Heat Flow Monitoring in Building Systems

In this paper, an advanced solution for measuring heat flow through opaque building elements is presented. The solution is based on the implementation of a computer-aided technique for continuous monitoring of heat flow sensor performance and silent checking of their accuracy. In principle, the technique provides an ex-post compensation of potential deviations and inaccuracies detected during the measurement, which can be done without interfering with the ongoing experiment. As a consequence, traditional ‘non-smart’ sensors can be turned into advanced sensors with self-sensing or self-adjustment features at nearly zero additional costs. The high efficiency of the proposed approach was validated against experimental data obtained from an independent set of advanced high-sensitive sensors. Considering the validation results, the proposed technique brings an entirely new potential for maintenance-free applications for thermal performance monitoring in the building sector, typically for long-term experiments or measurements under dynamic environments.

Verifying an improved intermittent water distribution network analysis method based on EPA-SWMM

ABSTRACT Modelling Intermittent Water Supply (IWS) presents challenges, as traditional hydraulic methods based on EPANET are often inadequate due to their inability to simulate the network filling process. While EPA-SWMM (EPA's Storm Water Management Model)-based methods enhance IWS analysis, they remain network-specific and lack universal applicability. This study aims to calibrate and verify an improved EPA-SWMM-based model on a 6 m × 5 m laboratory-scale IWS. Experiments were conducted to capture flow rate data from demand nodes under various conditions. The EPA-SWMM model, based on uncontrolled outlets with flow rate varying by pressure, was calibrated using, an automated procedure that integrated the Genetic Algorithm (GA) into the SWMM-toolkit for optimizing minor loss and pipe roughness coefficients. Comparing model results with experimental data demonstrated the model's capability to simulate the laboratory-scale IWS system behaviour. The model was also applied to a real case study, with results closely aligning with field data, affirming its reliability. The proposed IWS modelling method offers a versatile tool for applications, such as design and scenario analysis for tackling IWS challenges and managing IWS systems. Future research should focus on a large-scale laboratory experiment with pressure and flow sensors, considering air presence in the network to mitigate errors.

Self-powered, multi-angle gas flow sensing based on photovoltaics with porous graphite electrodes

A self-powered, multi-attack angle gas/air flow sensor without azimuth directional constraints has been designed and developed in this study. Two essential components, the porous graphite cathode and the perovskite photovoltaics, work synergistically in the device. The gas flow penetrates the bulky porous cathode, causing the pressure differences between the upper and lower sides of the nano/micro sheets, leading to the micro lift-force (Bernoulli theory) or dynamic pressure, consequently breaking or forming the electrically conductive paths among the nano/micro sheets. Therefore, the altered electrical conductivity of the cathode prompts a change in the output photocurrent of the perovskite photovoltaic unit. The thin film photovoltaic device design eliminates the requirement for external power sources, enabling multi-attack angle sensing without any azimuth directional limitations.It's important to highlight the scarcity of micro airfoil structures in the gas flow sensing domain by utilizing the nano/micro graphite sheets as the electrode and the thin film photoelectrical device as the power source, which challenges the conventional design typically based on macro-mechanical theory. It is expected that this study could provide researchers with a fresh and distinct perspective for designing and advancing the next generation of multi-angle gas-flow sensors.

SIMULATION OF AN AUTONOMOUS HYDROSTATIC DRIVE

The features of the application of autonomous electrohydraulic drives for power engineering are considered. The classification of linear actuators is given, the analysis of design and layout solutions of developers of autonomous steering actuators for general engineering is performed. The analysis of disadvantages is carried out and the directions of improvement of autonomous drives are presented. A scheme of an autonomous electrohydraulic drive with an automatic power control system based on the use of information from pressure, flow and displacement sensors is proposed. A mathematical model of an autonomous electrohydraulic drive with a power regulator has been developed, which makes it possible to estimate a random change in the load on the executive hydraulic motor and optimize the pump supply in accordance with the required task. The obtained research results confirm that an autonomous hydraulic drive with a power regulator is a promising technical solution that contributes to the development of high-precision power drives and controllability for general mechanical engineering.