Real-time Flow Rate Research Articles

Calibration of flow differential pressure coefficients on pump-turbine by thermodynamic method

On-line monitoring of flow rate is rather important to evaluate the water consumption of the pump-turbine and the overall efficiency of the pumped storage station. Flow rate can be worked out based on the flow differential pressure measured in the flow passage and coefficients determined on model test. But the coefficients must be calibrated to obtain the reliable flow rate. As thermodynamic method is a common way to measure the discharge of prototype pump-turbine, site test is carried out on a vertical pump-turbine with 600 m rated head to calibrated the coefficients in this paper. Measuring devices are designed to satisfy both the turbine and pump operating conditions, and test results of flow rate at both turbine and pump operating conditions are presented and show that the calibrated coefficients are different to the predicted values. The calibrated results indicate the importance of site calibration on prototype turbine to ensure the monitoring validity on real-time flow rate.

Measurement of air-water counter-current flow rates in vertical annulus using multiple differential pressure signals and machine learning

Abstract Gas–liquid counter-current flow in vertical annulus is involved in several industrial fields such as petroleum engineering. For example, in coalbed methane wells with liquid pump drainage, obtaining the real-time flow rate of gas–liquid two-phase in the annulus is crucial for the development management of coalbed methane wells. However, due to complex flow conditions, this demand is difficult to achieve through traditional flow metering means. Therefore, this paper proposes a flow prediction method based on multi-group differential pressure signals and machine learning technology. Air-water two-phase flow experiments were carried out on a vertical annulus pipeline with inner and outer diameters of 75 mm/125 mm and adjustable eccentricity. The probability density function and power spectrum density of 3 groups of differential pressure signals collected at different height intervals in the annulus were used as model inputs. A gas–liquid two-phase flow prediction model was constructed based on the artificial neural network model, and the model hyper-parameters were optimized using Bayesian optimization. The results show that on the 440-group test dataset under the combined conditions of air superficial velocity of 0.06–5.04 m s−1, water superficial velocity of 0.03–0.25 m s−1, and pipeline eccentricity of 0, 0.25, 0.5, 0.75, 1, etc. This model can achieve average prediction errors of 9.12% and 29.34% for gas and water flow rates respectively. This method can be applied to the non-throttling, non-invasive measurement of phase flow rate under the condition of annulus air-liquid counter-current flow.

Extraction of crop canopy features and decision-making for variable spraying based on unmanned aerial vehicle LiDAR data

Implementation of precision agriculture aerial applications using unmanned aerial vehicles (UAVs) represents a pivotal technological aspect in precision agriculture. However, current UAV applications are still far from realizing true precision variable spraying. The use of UAVs to analyze and model crop growth, pest and disease conditions, and other pertinent information to enable targeted precision spraying poses a formidable challenge. Herein, a UAV variable-rate spray system with adaptive flow control based on crop canopy morphology was developed using a UAV equipped with a light detection and ranging (LiDAR) sensor to support precision spraying of cotton. Point cloud data captured by the LiDAR sensor initially undergo processing using the simple morphological filter (SMRF) algorithm and feature extraction function. Subsequently, cotton canopy volumes measured by the alpha shape algorithm, convex hull by slices shape algorithm, and voxel-based method were compared with manual measurements with coefficient of determination R2 values of 0.89, 0.78, and 0.82, respectively. The results of the validation experiments denote that the cotton canopy volume obtained using the alpha shape algorithm is in good agreement with that obtained using manual measurements; thus, this algorithm is employed for volume calculations in this design. Models were constructed to relate UAV flight parameters, cotton canopy volume, and spraying parameters to the duty cycle of variable control signals, which enabled the UAV to adjust the flow rate in real time to match the cotton canopy structure. In addition, a polygonal prescription map decoding algorithm based on the cotton canopy morphology was introduced. This algorithm is used for real-time decoding of prescription maps and extraction of flow, latitude, and longitude information. Finally, field experiments were conducted, and the results indicate that the UAV variable-rate spray system designed in this study exhibits biological efficacy (effective application thresholds provided by the pesticide manufacturer) comparable to that of the constant-rate spray system at a lower application rate. Furthermore, it exhibited superior spray deposition efficiency and coverage compared with the constant-rate spray system. Notably, the use of the variable-rate spray system in cotton crops resulted in a 43.37% reduction in spray volume while maintaining high application quality, providing an opportunity for pesticide and labor cost savings.

Development and experimental testing of an innovative nondestructive thermal sensor utilizing the thermal interrogation method for detecting leakage in water plastic pipes

Leak detection in water pipelines is still an important issue in real-world industrial systems. Thus, a new nondestructive thermal sensor design based on the thermal interrogation method has been developed to detect and estimate the real-time leaks in water plastic pipes without environmental interference. The proposed thermal interrogation method utilizes a combination of heat flux and temperature measurements on the upstream and downstream outside plastic pipe surfaces. These measurements are obtained by using heat flux sensors and thermocouples that are covered by thin-film polyimide electric heaters. The interrogation method approach delivers that at constant input heat flux, the difference in sensor temperature values is dependent on the leakage volume flow rates. The sensor was tested over a range of water leakage volume flow rate from 0.1 m3/h to 1.3 m3/h and a range of water temperature from 21 °C to 25 °C. The water leakage volume flow rates were correlated to the difference in temperature values between the upstream and downstream sensors. The measurement results reveal that this sensor can be used to detect and estimate the real-time water leakage volume flow rate with high accuracy and repeatability for plastic pipes.

Real-time embedded pressure and flow rate sensor in polydimethylsiloxane-based microchannel using fiber Bragg grating technique

Polydimethylsiloxane (PDMS) has attracted huge interest as the soft material for microchannel fabrication, due to its high biocompatibility, durability and low cost. The rheological properties of the fluid and the deformable properties of PDMS substrate have imposed significant impacts on the fluid flow in the microchannel, therefore it is of critically importance to develop sensing methods for the accurate flow rate monitoring and the flow-induced pressure measurement without disturbing the fluid flow in the microchannel. This paper presents an embedded and miniaturized pressure sensor based on the Fiber Bragg Grating (FBG) technique for the measurement of both flow rate and flow-induced pressure in PDMS-based microchannel. This method has demonstrated a pressure sensitivity of 0.06 p.m./Pa and the Limit of Detection (LoD) for pressure is 19.5 Pa. The linearity between flow-induced pressure and flow rate in PDMS-based microchannel is about 4.86 Pa(ml/h)−1 based on simulation results and is within the range between 4.33 Pa(ml/h)−1 and 6.67 Pa(ml/h)−1 obtained from experimental results. The LoD of flow rate using this method is within the range between 2.9 ml/h and 4.5 ml/h. The random instability induced by the operation of the reconnection of syringe back to the liquid flow system was identified and the calibration of this instability is also presented in this paper. Using this method, the pressure and flow rate within PDMS-based microchannel can be monitored with high reliability and high sensitivity, and this will benefit the application of PDMS-based microfluidics in areas that require highly precise control in flow conditions, e.g. biosensing, cell culture, and drug delivery.

Enhancing virtual flow metering on offshore oil platforms through parallel computing and data reconciliation

Technological advances in recent years have facilitated data accessibility and increased computational resources; consequently, more remarkable numerical performances in data analysis and computational tests have become possible. In this context, parallel computing techniques are considered relevant tools in applications necessitating reduced computational time, such as online and real-time monitoring of industrial processes. For these reasons, the present work develops and implements online and real-time monitoring of offshore oil and gas production, using parallel computing to improve the performance of the data reconciliation methodology implemented, which will estimate the virtual flow metering with more reliability and in real time. To achieve this, three optimization methods (DA, L-BFGS-B, and SLSQP) and two approaches of parallelization schemes were considered: (1) parallelization of the simulations of each production well; (2) parallelization of the numerical gradient, performed by the deterministic optimization method. Parallel implementations allowed the reduction of up to 80% (type 1) and up to 89% (type 2) of the simulation time compared to their serial counterparts. Hence, the parallel execution of type 2 exhibited more promising results, while type 1 demonstrated greater adaptability to optimization methods. Finally, the results indicate that parallel computing techniques facilitate data reconciliation in real-time, enabling online monitoring in a much shorter time and more accurately than achieved with similar sequential procedures. Moreover, the implemented methodology has proven effective for virtual flow metering of each well’s flow rates of oil, water, and gas. In this context, parallelism techniques present the potential for developing the global monitoring of the virtual flow meters for real-time oil, water, and gas flow rates in each well.

Optimizing dialysis water treatment based on medical planning requirements

This paper introduces a new approach to improving hemodialysis and peritoneal dialysis processes. This maintains compatibility between the water treatment unit and active dialysis machines. Identification of different deviations in the patient’s requirements to classify the suitable flow rate (FR) of the pure water can be created through an Adaptive Neuro-Fuzzy Inference System (ANFIS). Four types of categories are classified: quarter load, half load, three-quarter load, and full load. This includes two main steps: identifying the dialysis categories with patients and measuring the suitable FR for each category. The effective FR of water was computed to indicate how the number of pumps rose as the number of patients treated within the dialysis unit increased. The introduced prediction method was tested against artificial neural networks to predict alum doses (ANN-AD) method, artificial intelligence as a combinatorial optimization strategy (AN-COS) using peach-palm waste in a solid-state fermentation environment, expert system applications (ESA) in chronic kidney disease management (MDSSs), prescription optimization for automated peritoneal dialysis (BCPH). In this work, pumping system parameter estimation was utilized to assess the performance of the introduced systems based on input voltage, input current, rotor speed, and electromagnetic torque waveforms of the pumping drive. This method uses the ANFIS algorithm to construct a high-performance pumping system to evaluate and predict the flow rate of dialysis machines based on input–output estimates. The flow rate values for each patient in critical care units can be controlled by the presented algorithm according to the time of dialysis. A good predictive model based on integrating the experience and decision making of medical planners was implemented. The proposed method not only improves accuracy but also saves time in the dialysis unit. The presented fuzzy classifier uses the ratio of the number of predicted true positives and false positives to the total number of anticipated positives. The simulation results show that the proposed technique can be successfully used to classify the suitable FR of the water according to the hemodialysis load. One of the advantages of the presented technique is the ability to predict the value of FR in real time with reliability, low computational complexity, and a high accuracy of 98.01%, which simplifies the dialysis process for many patients while at the same time leading to improved performance of hemodialysis. The presented method can be implanted in online FR estimation and analysis hardware for hemodialysis, is easy to calculate and run in real time, minimizes hemodialysis costs, and saves run time.

Experimental study on heat transfer performance of a series combined microchannel heat dissipation system based on Al2O3 nanofluid

The thermal power of each subsystem of loaders is relatively high, and the machine performance is seriously affected by temperature changes of each component. Therefore, developing an efficient heat dissipation system is of great significance for improving the working performance of the machine. In this paper, a pioneering series combined microchannel heat dissipation system with microchannel heat sinks as the principal components is proposed, and the feasibility was verified through experiments. Results show that the number of microchannel heat sink series combinations and the fan control voltage can be adjusted according to the feedback of the real-time temperature and flow rate parameters of the working medium under different working conditions of the system, which can improve the heat exchange efficiency and reduce the energy consumption. Furthermore, the incorporation of Al2O3 nanoparticles into the working medium yields a substantial improvement in the heat transfer performance of the system. Relative to pure water, the system utilizing an Al2O3 nanofluid with a mass fraction of 0.7% demonstrates a noteworthy 11.17% enhancement in heat transfer power and a commendable 6.40% increase in energy consumption ratio. This study holds significant importance in the exploration of an efficient and energy-saving heat dissipation system for loaders.

MEASUREMENT OF LINEAR VELOCITY USING A MOBILE ROBOTIC PLATFORM WITH COMPUTER VISION

This article presents an approach to integrating computer vision algorithms into the control system of traction electric drives in rail transport. It demonstrates the utilization of computer vision algorithms for calculating linear velocity as an alternative to conventional sensors like wheel odometers, GPS, DGPS and inertial sensors, which may prove ineffective on slippery surfaces and at low speeds. As a result, this article focuses on employing linear velocity as feedback within the control system to enhance power efficiency during starting and stopping and to prevent wheel slip. The electric drive control system has been successfully implemented and tested on a robotics platform designed for simulating dynamic behaviors in real rail transports scenarios. The article details the development process of this robotics platform, which is employed to mimic real-world dynamic conditions in rail transport. The proposed control algorithm for speed estimation is assessed using a specially designed test bench, revealing its capability to predict speed with a relatively high degree of accuracy. Additionally, an optical flow algorithm for velocity estimation is introduced and evaluated through a specially designed test rig, indicating a strong correlation between the predicted vehicle speed and the measurements from precision optical encoders. The study also determines the optimal feature window size for real-time optical flow rate estimation. In summary, this approach exhibits significant potential for accurate speed estimation. Ongoing experiments are being conducted under various real-world conditions, with future research aimed at developing a dependable autonomous system for speed measurement. The integration of modern digital computer vision technologies not only enhances the traction characteristics of electric drives but also extends the capabilities of traction electric drives to meet the rigorous demands of industrial equipment.

Study on monitoring infusion rate based on computer vision

A computer vision based infusion monitoring method and system is proposed to solve a series of technical problems such as inconvenient use of the existing infusion monitoring system. The technical scheme includes video capture module, voice alarm module and main control module. The video capture module is used to collect the real-time image information of the drip pot part of the infusion equipment and transmit the collected image information to the main control module. The main control module processes the image information transmitted by the video capture module, uses the computer vision principle and self-designed algorithm to judge the real-time flow rate of the infusion equipment, judges whether the infusion is completed according to the preset conditions, and timely controls the voice alarm to give an alarm. The system uses computer vision technology to accurately judge whether the infusion equipment has completed infusion and give an alarm. It is simple to use, does not hinder traditional manual monitoring, and provides convenience for unattended patients, patient families, and nurses.

A soft, bioinspired artificial lymphatic system for interactive ascites transfer.

Low-flow removal of refractory ascites is critical to treating cirrhosis and digestive system tumor, and thus, commercial ascites pump emerged lately. The rigid structure of clinically available pumps rises complication rate and lack of flow rate monitoring hinders early warning of abnormalities. Herein, a soft artificial system was proposed inspired by lymph for interactive ascites transfer with great biocompatibility. The implantable system is composed of pump cavity, valves and tubes, which are soft and flexible made by silica gel. Therefore, the system possesses similar modulus to tissues and can naturally fit surrounding tissues. The cavity with magnetic tablet embedded is driven by extracorporeal magnetic field. Subsequently, the system can drain ascites with a top speed of 23 mL min-1, much higher than that of natural lymphatic system and state-of-art devices. Moreover, integrated flexible sensors enable wireless, real-time flow rate monitoring, serving as proof of treatment adjustment, detection and locating of malfunction at early stage. The liver function of experimental objects was improved, and no severe complications occurred for 4 weeks, which proved its safety and benefit to treatment. This artificial lymphatic system can serve as a bridge to recovery and pave the way for further clinical research.

Rapid calculation method for water flow rate at gas drilling site based on pressure drop

Water production in the bottom hole is a frequent occurrence during gas drilling, posing a significant threat to the safety of the process. Obtaining the water flow rate quickly is critical to making further engineering decisions. This paper proposes a rapid calculation method of water flow rate based on the principle of pressure drop. The method can quickly identify the multiphase flow pattern and calculate the flow pressure drop, thereby establishing the relationship between the gas injection pressure and the water flow rate. At the gas drilling site, the gas injection pressure is continuously monitored in real-time, which enables rapid acquisition of the real-time water flow rate. The concept of ultimate water-carrying kinetic energy is introduced, which combined with the boundary of annular flow to other flow patterns, can determine the maximum water-carrying flow rate. The feasibility of this method is validated using the field-measured data of well X8-3.

Measuring gas permeability in tight cores at high pressure: Insights into supercritical carbon dioxide seepage characteristics.

This study introduces a new, more accurate instrument for measuring gas permeability in tight cores at high pressure, surpassing the accuracy of conventional methods. Using the steady-state method, the study tested the permeability of carbon dioxide (CO2) in tight cores at various pressure conditions. We observed that, similar to nitrogen, CO2 permeability initially conformed to the Klinkenberg slip theory, but began to deviate as back pressure increased. Supercritical CO2 exhibited a slight increase in permeability, which contrasts with both nitrogen behavior and the Klinkenberg slip theory. Accurate measurement of CO2 permeability in tight rocks is crucial for assessing the feasibility and efficiency of CO2 injection and storage, which could help reduce greenhouse gas emissions and drive energy transformation. The innovative measurement approach can assist in identifying the ideal production pressure drops, injection pressures, and flow rate parameters, thus improving the recovery rate of tight oil reservoirs. Nevertheless, the study had some limitations, including prolonged stable flow time, lack of real-time flow rate display, and reliance on theoretical viscosity calculations, all of which could affect the accuracy of permeability measurements. Further research is needed to investigate CO2 permeability under diverse conditions and to deepen our understanding of CO2 transport and storage in tight cores, which could lead to improvements in CO2 sequestration and the efficiency of enhanced oil recovery.

Energy saving and carbon emission reduction potential for cold store with new dynamic linkage control strategy

Management optimization is economical and effective to reduce energy consumption and carbon emission for cold stores in service, needing more appropriate control strategy. The state of different components of refrigeration system affects each other, which indicates control strategies based on matching characteristics are essential. This study compared the operating data before and after control upgrade for an actual cold store that had the ability to adjust capacity stage. To better evaluate the input-output ability of air coolers, a new parameter, cooling efficiency, was calculated to represent their refrigeration per power consumption. New control strategy based on the matching operation of compressors and air coolers was put forward as dynamic linkage control strategy (DICS) with real-time flow rate and refrigeration capacity calculation to improve system efficiency. Through system control optimization, the coefficient of performance (COP) of the refrigeration system was increased by 29%, and the cooling efficiency of the air coolers (CEAC) was increased by 37%. The average power consumption decreased by 21.15%, and carbon emission was reduced by 320.840 tonnes at a decreasing rate of 19.95% per year for the whole cold store.

Prognostic Role of Metabolic Exercise Testing in Heart Failure

Heart failure is a clinical syndrome with significant heterogeneity in presentation and severity. Serial risk-stratification and prognostication can guide management decisions, particularly in advanced heart failure, when progression toward advanced therapies or end-of-life care is warranted. Each currently utilized prognostic marker carries its own set of challenges in acquisition, reproducibility, accuracy, and significance. Left ventricular ejection fraction is foundational for heart failure syndrome classification after clinical diagnosis and remains the primary parameter for inclusion in most clinical trials; however, it does not consistently correlate with symptoms and functional capacity, which are also independently prognostic in this patient population. Utilizing the left ventricular ejection fraction as the sole basis of prognostication provides an incomplete characterization of this condition and is prone to misguide medical decision-making when used in isolation. In this review article, we survey and exposit the important role of metabolic exercise testing across the heart failure spectrum, as a complementary diagnostic and prognostic modality. Metabolic exercise testing, also known as cardiopulmonary exercise testing, provides a comprehensive evaluation of the multisystem (i.e., neurological, respiratory, circulatory, and musculoskeletal) response to exercise performance. These differential responses can help identify the predominant contributors to exercise intolerance and exercise symptoms. Additionally, the aerobic exercise capacity (i.e., oxygen consumption during exercise) is directly correlated with overall life expectancy and prognosis in many disease states. Specifically in heart failure patients, metabolic exercise testing provides an accurate, objective, and reproducible assessment of the overall circulatory sufficiency and circulatory reserve during physical stress, being able to isolate the concurrent chronotropic and stroke volume responses for a reliable depiction of the circulatory flow rate in real time.

Accuracy assessment and error decomposition of internet of things sensor: Low-flow conditions in Dorimcheon stream

In recent years, a significant shift towards automation has arisen in the field of flow measurement. This study presents an Internet of Things (IoT) sensor-based flow measurement system designed to accurately measure and collect real-time flow rate data while reducing the need for manual labor and increasing safety. The system was tested in a stream located in Dorimcheon, where two different sensors were compared: the YF-S201 and Sontek FlowTracker2. The results indicate that the IoT sensor (YF-S201) is a viable option for measuring flow rate under low-flow conditions. However, it should be noted that the accuracy of the YF-S201 sensor is limited, with a standard uncertainty of 9.5% under low-flow conditions., while the FlowTracker2 had an uncertainty of 7.7%. An error decomposition analysis revealed that changes in the instrument accuracy were the largest contributors to the uncertainty in the YF-S201 sensor. The study also employed an ultrasonic sensor for measuring water levels, and the uncertainty analysis indicated that the sensor was suitable for this purpose with an acceptable level of accuracy.

A non-nuclear inline densitometer for multiphase flows

Multiphase flowmeters are used in the oil-and-gas industry to measure real-time flow rates of oil, gas, and brine, flowing simultaneously as a non-homogeneous mixture, in a pipeline from wellhead to separator. Since these flow rates cannot be measured directly, they are inferred from other measurements including mixture density. Mixture density is commonly measured using nuclear densitometers which can be problematic in terms of safety and maintenance. This paper details the development—concept and experimental validation—of a non-nuclear inline densitometer that measures multiphase mixture density using pressure sensors. A comprehensive flow-loop test was conducted at a commercial facility to evaluate the technology under a wide range of flow conditions—flow rates 1000 to 10000 bpd, gas fractions 0% to 96%, water cuts 0% to 100%, with a synthetic oil as liquid hydrocarbon, methane as gas medium, two water salinities—totaling nearly 300 test points. The results from this experimental validation—specifically, the technology’s accuracy and operating envelope—point to a groundbreaking practical solution to a long-standing problem.

Application Research of Borehole Cleaning Evaluation System Based on Cuttings Weighing

Due to complex working conditions and cuttings migration mechanism and other factors, cuttings bed is easy to form in deviated well section and extended reach horizontal well section, and too high cuttings bed is easy to cause a series of complex downhole accidents, such as bit mud bag, wall collapse, stuck drilling and holding in drilling. The borehole cleaning evaluation system based on cuttings weighing can collect the cuttings returned in real time. The system combines the real-time cuttings flow rate, theoretical cuttings volume, actual cuttings volume and other data to evaluate the borehole cleaning situation and provide guidance for field drilling construction. At the same time, the drilling optimization analysis module is designed in the system. The module adopts the combination of comprehensive logging data and geological logging data, combining the advantages of comprehensive logging and geological logging, which can realize the real-time drilling time optimization analysis to the maximum extent. In this paper, the evaluation system of borehole cleaning based on cuttings weighing is studied and corresponding engineering application examples are given. It has high practical application value for borehole cleaning monitoring and evaluation, drilling aging optimization analysis and reducing non-productive time.

Signal Modeling of Permanent Magnet Sodium Flowmeter With Embedded Vortex Generator Based on Transit Time Series

The permanent magnet sodium flowmeter with embedded vortex generator (PMSF-VG) monitors the liquid metal sodium flow rate in real time in order to ensure the safe operation of the fast neutron reactor. The previous literature studied how to improve the in-situ calibration accuracy of the flowmeter from the perspective of signal processing. This paper studies this issue from the perspective of signal source. According to the experimental data, the transit time series is calculated by using the generalized cross-correlation method, its characteristics are analyzed, and a moving average (MA) model is established for predicting and improving the accuracy of the in-situ calibration. This model is composed of a steady-state component and a fluctuation component. The former reflects the ideal value of the cross-correlation flow rate in the in-situ calibration, and is related to the meter linearity and indication error, which determines the upper limit of the measurement accuracy. The latter determines the repeatability error of the in-situ calibration. Aiming at its feature, a two-stage moving average filtering method is adopted to reduce the repeatability error of measuring the transit time and improve the accuracy of the in-situ calibration.

Feasibility and safety of trans-biliary cryoablation: Preclinical evaluation of a novel flexible cryoprobe

Cryoablation, as a well-characterized technology, has multifarious clinical applications in solid malignancy. However, trans-biliary cryoablation for malignant biliary obstruction has not been reported yet. Thus, this study aimed to determine the efficacy and safety of trans-biliary cryoablation with a novel CO2 gas-based flexible cryoprobe in standardized preclinical settings. For fresh porcine liver ex vivo, the freezing efficacy of cryoablation was evaluated by using fresh porcine liver. The real-time CO2 flow rate, freezing temperature and freezing range were examined and the frozen appearance was visualized. In vivo study, acute and chronical effects were investigated by using the models of canine bile duct. Histopathology and laboratory examination were performed. The lowest temperature that the electrode could deliver to the tissue was −60.7 °C. At 60s after freezing, the tissue temperature dropped to −22.6 °C and −4.3 °C at 0.1 and 0.2 cm from the electrode center, respectively. The frozen size was greater in liver tissue ex vivo than that in bile duct tissue in vivo. No biliary hemorrhage, perforation, stricture, obstruction, and adjacent organ injury were observed. With histopathologic examination, acute intercellular vacuoles were observed in the lamina propria adjacent to the lumen. Chronic changes, including uneven coagulative necrosis, fibro-proliferation, inflammatory infiltration and connective tissue thickening were observed in the lamina propria of the all biliary samples. The results demonstrated CO2 gas-based trans-biliary cryoablation is safe and efficacious. These findings may provide a potential new modality for primary malignant biliary obstruction and malignant obstruction within a biliary stent and contribute to cryoablation of clinical practice.