Flow-related Parameters Research Articles

Effect of singular value decomposition on removing injection variability in 2D quantitative angiography: An in silico and in vitro phantoms study.

Intraoperative 2D quantitative angiography (QA) for intracranial aneurysms (IAs) has accuracy challenges due to the variability of hand injections. Despite the success of singular value decomposition (SVD) algorithms in reducing biases in computed tomography perfusion (CTP), their application in 2D QA has not been extensively explored. This study seeks to bridge this gap by investigating the potential of SVD-based deconvolution methods in 2D QA, particularly in addressing the variability of injection durations. Building on the identified limitations in QA, the study aims to adapt SVD-based deconvolution techniques from CTP to QA for IAs. This adaptation seeks to capitalize on the high temporal resolution of QA, despite its two-dimensional nature, to enhance the consistency and accuracy of hemodynamic parameter assessment. The goal is to develop a method that can reliably assess hemodynamic conditions in IAs, independent of injection variables, for improved neurovascular diagnostics. The study included three internal carotid aneurysm (ICA) cases. Virtual angiograms were generated using computational fluid dynamics (CFD) for three physiologically relevant inlet velocities to simulate contrast media injection durations. Time-density curves (TDCs) were produced for both the inlet and aneurysm dome. Various SVD variants, including standard SVD (sSVD) with and without classical Tikhonov regularization, block-circulant SVD (bSVD), and oscillation index SVD (oSVD), were applied to virtual angiograms. The method was applied on virtual angiograms to recover the aneurysmal dome impulse response function (IRF) and extract flow related parameters such as Peak Height PHIRF, Area Under the Curve AUCIRF, and Mean transit time MTT. Next, correlations between QA parameters, injection duration, and inlet velocity were assessed for unconvolved and deconvolved data for all SVD methods. Additionally, we performed an in vitro study, to complement our in silico investigation. We generated a 2D DSA using a flow circuit design for a patient-specific internal carotid artery phantom. The DSA showcases factors like x-ray artifacts, noise, and patient motion. We evaluated QA parameters for the in vitro phantoms using different SVD variants and established correlations between QA parameters, injection duration, and velocity for unconvolved and deconvolved data. The different SVD algorithm variants showed strong correlations between flow and deconvolution-adjusted QA parameters. Furthermore, we found that SVD can effectively reduce QA parameter variability across various injection durations, enhancing the potential of QA analysis parameters in neurovascular disease diagnosis and treatment. Implementing SVD-based deconvolution techniques in QA analysis can enhance the precision and reliability of neurovascular diagnostics by effectively reducing the impact of injection duration on hemodynamic parameters.

Comprehensive sex-specific and age-dependent analysis of 4D-flow MRI assessed aortic blood flow-related parameters in normal subjects using single-vendor MR systems and single-vendor software.

Aortic blood flow characterization by 4D flow MRI is increasingly performed in aneurysm research. A limited number of studies have established normal values that can aid the recognition of abnormal flow at an early stage. This study aims to establish additional sex-specific and age-dependent reference values for flow-related parameters in a large cohort of healthy adults. 212 volunteers were included, and 191 volunteers completed the full study protocol. All underwent 4D flow MRI of the entire aorta. Quantitative values for velocity, vorticity, helicity, as well as total, circumferential, and axial wall shear stress [WSS] were determined for the aortic root [AoR], ascending aorta [AAo], aortic arch [AoA], descending [DAo], suprarenal [SRA], and infrarenal aorta [IRA]. Vorticity and helicity were indexed for segment volume (mL). The normal values were estimated per sex- and age-group, where significant differences between males (M) and females (F) were found only for specific age groups. More specifically, the following variables were significantly different after applying the false discovery rate correction for multiple testing: 1) velocity in the AAo and DAo in the 60-70 years age group (mean±SD: (M) 47.0 ± 8.2cm/s vs. (F) 38.4 ± 6.9cm/s, p=0.001 and, (M) 55.9 ± 9.9cm/s vs. (F) 46.5 ± 5.5cm/s, p=0.002), 2) normalized vorticity in AoR in the 50-59 years age group ((M) 27539 ± 5042s-1mL-1 vs. (F) 30849 ± 7285s-1mL-1, p=0.002), 3) axial WSS in the Aao in the 18-29 age group ((M) 1098 ± 203 mPa vs. (F) 921 ± 121 mPa, p=0.002). Good to strong negative correlations with age were seen for almost all variables, in different segments, and for both sexes. This study describes reference values for aortic flow-related parameters as acquired by 4D flow MRI. We observed limited differences between males and females. A negative relationship with age was seen for almost all flow-related parameters and segments.

Peristaltic transport of diethylene glycol-based magnesium aluminate nanofluid under the effects of viscous dissipation and Hall current

ABSTRACT The fundamental importance of peristaltic phenomena in numerous biological systems, including dialysis, heart-lung machines, urine transportation, invertebrate locomotion, and the passage of gallbladder bile into the intestines, persuaded scientists to investigate the different aspects of it over the past few years. In addition, peristaltic pumping is an important consideration in industrial processes including, roller pumps used for the transport of sanitary materials, finger pumps, cell separation, and endoscopes. Keeping such inspirational applications in mind, the present investigation is dedicated to exploring the peristaltic transport of a Cross-magneto nanofluid through a curved geometry in the presence of heat transfer. The inspection of the heat transfer is conducted by utilizing variable viscosity and ohmic heating aspects. This study also retains the characteristics of viscous dissipation, heat generation/absorption, and thermal conductivity of nanofluids. Modeling of the 2D, incompressible Cross nanofluid with peristaltic movement is carried out using a curvilinear coordinate system. The basic equations of the problem are mPodeled in the light of physical laws and then simplified by adopting the lubrication theory. The solutions of the resulting nonlinear system are computed numerically. The outcomes of the related flow parameters on the nanofluid’s temperature, pressure gradient, velocity distribution, heat transfer, streamlines pattern, and stresses at the wall are discussed through graphs. The graphical results depict that the rates of heat transfer are augmented by increasing the curvature parameter, Hartmann number, and nanoparticles’ volume fraction while decreasing the Hall parameter and temperature-dependent viscosity parameter. Moreover, the nanofluid’s temperature increases by improving the values of the heat generation parameter, whereas it decreases for the Hall parameter. Furthermore, a reduction in the axial velocity occurs near the center of the channel, when Hartmann number attains higher values.

Measuring arrangement and size distributions of flowing droplets in microchannels through deep learning using DropTrack

In microfluidic systems, droplets undergo intricate deformations as they traverse flow-focusing junctions, posing a challenging task for accurate measurement, especially during short transit times. This study investigates the physical behavior of droplets within dense emulsions in diverse microchannel geometries, specifically focusing on the impact of varying opening angles within the primary channel and injection rates of fluid components. Employing a sophisticated droplet tracking tool based on deep-learning techniques, we analyze multiple frames from flow-focusing experiments to quantitatively characterize droplet deformation in terms of ratio between maximum width and height and propensity to form liquid with hexagonal spatial arrangement. Our findings reveal the existence of an optimal opening angle where shape deformations are minimal and hexagonal arrangement is maximal. Variations of fluid injection rates are also found to affect size and packing fraction of the emulsion in the exit channel. This paper offers insight into deformations, size, and structure of fluid emulsions relative to microchannel geometry and other flow-related parameters captured through machine learning, with potential implications for the design of microchips utilized in cellular transport and tissue engineering applications.

3D Breast Cancer Model on Silk Fibroin-Integrated Microfluidic Chips.

To imitate in vivo environment of cells, microfluidics offer controllable fashions at micro-scale and enable regulate flow-related parameters precisely, leveraging the current state of 3D systems to 4D level through the inclusion of flow and shear stress. In particular, integrating silk fibroin as an adhering layer with microfluidic chips enables to form more comprehensive and biocompatible network between cells since silk fibroin holds outstanding mechanical and biological properties such as easy processability, biocompatibility, controllable biodegradation, and versatile functionalization. In this chapter, we describe design and fabrication of a microfluidic chip, with silk fibroin-covered microchannels for the formation of 3D structures, such as MCF-7 (human breast cancer) cell spheroids as a model system. All the steps performed here are characterized by surface-sensitive tools and standard tissue culture methods. Overall, this strategy can be easily integrated into various high-tech application areas such as drug delivery systems, regenerative medicine, and tissue engineering in near future.

Primary versus iatrogenic (post-PCI) coronary microvascular dysfunction: a wire-based multimodal comparison

BackgroundAlthough there are studies examining each one separately, there are no data in the literature comparing the magnitudes of the iatrogenic, percutaneous coronary intervention (PCI)-induced, microvascular dysfunction (Type-4 CMD) and...

Use of Physics-Based Models for Different Applications of Electrochemical Energy Storage and Conversion Devices

This talk will present the application of physics-based models applied to two different electrochemical storage and conversion systems, viz. Li-ion batteries and Proton Exchange Membrane Fuel Cells (PEMFCs). Battery energy storage system (BESS) is becoming a crucial part of standalone renewable hybrid power systems due to the intermittent nature of power generation and for aiding in various operations like frequency regulation, voltage support, and peak shaving. The lithium-ion battery is a promising choice for BESS due to its high energy density, power density, operating voltage, negligible self-discharge, suitable operating temperature range, modularity, and reliability. A standalone renewable hybrid power system framework with lithium-ion battery energy storage is developed to investigate its performance using physics-based battery models. Power management and control strategies are developed for standalone renewable hybrid power systems. These control strategies can track the MPP of the solar cells and wind turbines while avoiding overcharging the battery and guaranteeing 0% dumping power under different ambient and working conditions. The battery is exposed to harsh ambient conditions in the real world, resulting in the dynamic and continuous capacity fade. A thermal management and control strategy is developed to analyze the effect of temperature on lithium-ion batteries' performance and degradation without using external cooling systems. Dynamic battery degradation analysis and life prediction are essential for better techno-economic estimation of renewable hybrid power systems. The impact of BESS size variation on degradation and the cost of energy generation is analyzed. The developed renewable hybrid power system framework is independent of location and system size and can be extended to incorporate other renewable energy generation sources and energy storage systems.The second part of this talk will focus on using physics-based models to understand the water dynamics and degradation mechanisms inside PEMFC, which is necessary for water management, long-life operation, and cost reduction. PEMFCs have emerged as an alternative green energy technology in various applications such as automobiles, portable and stationary applications, and auxiliary power supplies for space exploration missions. The cost and durability targets remain unmet largely, which restrains the commercialization of the PEMFCs. The major difficulty in modeling lies in the wide scale of dimensions from the millimeter level (flow channel) to the micron level (catalyst layer (CL) thickness). The multi-scale physics-based model enables the life cycle analysis of PEMFC under various operating conditions. The mass transport limitation is the major hurdle in performance enhancement for higher current density operations. It arises from the liquid water generated during the electrochemical reactions, which hinders the reaction sites of CL and oxygen transport reaction sites in the gas diffusion layer, resulting in performance deterioration. Many experimental studies reported the two-phase flow visualization techniques in PEMFCs, viz. neutron imaging, optical visualization, and X-ray radiography. However, the difficulties in conducting experiments for flow visualization and related parameters such as liquid volume fraction have encouraged researchers to adopt numerical simulations that are less expensive and computationally efficient. Understanding liquid water movement inside the cell at the micro-scale help to improve the PEMFC performance at the stack level. Here, we develop a comprehensive 3-D, multiphase, non-isothermal, steady-state physics-based model of the PEMFC that can closely approximate the liquid water flooding and membrane drying. The findings from this work can be used to design an efficient flow configuration and to study membrane deformation due to the shrinking-swelling under humidification and thermal cycling. The ultimate goal of the multi-scale model is to enhance the PEMFC stack output with less degradation.

A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance-A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions.

Towards modeling of phonation and its recovery in unilateral vocal fold paralysis by fluid-structure interaction.

Vocal folds are responsible for sound generation. In unilateral vocal fold paralysis (UVFP), the recurrent laryngeal nerve, which controls the vocal folds, is paralyzed. Medialization laryngoplasty is a surgery in which an implant is inserted to push the paralyzed vocal fold to the centerline to recover phonation. Here, a numerical simulation is used to calculate flow-related parameters to give insight into what happens in healthy and treated(implanted) vocal folds and their enhancement. In the present work, airflow over vocal folds is modeled considering fluid-structure interaction (FSI) and varying inlet pressure. The governing equations are discretized for fluid and solid domains and solved using the Galerkin finite element method. The boundary conditions for healthy and unilaterally paralyzed vocal folds were imposed to agree with real cases behavior. The results showed the effectiveness of medialization laryngoplasty in treating unilateral vocal fold paralysis concerning healthy vocal folds. This simulation provided a better insight into treatment results for patient-specific cases.

Evaluating a Phase-Specific Approach to Aortic Flow: A 4D Flow MRI Study.

Aortic flow parameters can be quantified using 4D flow MRI. However, data are sparse on how different methods of analysis influence these parameters and how these parameters evolve during systole. To assess multiphase segmentations and multiphase quantification of flow-related parameters in aortic 4D flow MRI. Prospective. 40 healthy volunteers (50% male, 28.9 ± 5.0 years) and 10 patients with thoracic aortic aneurysm (80% male, 54 ± 8 years). 4D flow MRI with a velocity encoded turbo field echo sequence at 3 T. Phase-specific segmentations were obtained for the aortic root and the ascending aorta. The whole aorta was segmented in peak systole. In all aortic segments, time to peak (TTP; for flow velocity, vorticity, helicity, kinetic energy, and viscous energy loss) and peak and time-averaged values (for velocity and vorticity) were calculated. Static vs. phase-specific models were assessed using Bland-Altman plots. Other analyses were performed using phase-specific segmentations for aortic root and ascending aorta. TTP for all parameters was compared to TTP of flow rate using paired t-tests. Time-averaged and peak values were assessed using Pearson correlation coefficient. P < 0.05 was considered statistically significant. In the combined group, velocity in static vs. phase-specific segmentations differed by 0.8 cm/sec for the aortic root, and 0.1 cm/sec (P = 0.214) for the ascending aorta. Vorticity differed by 167 sec-1 mL-1 (P = 0.468) for the aortic root, and by 59 sec-1 mL-1 (P = 0.481) for the ascending aorta. Vorticity, helicity, and energy loss in the ascending aorta, aortic arch, and descending aorta peaked significantly later than flow rate. Time-averaged velocity and vorticity values correlated significantly in all segments. Static 4D flow MRI segmentation yields comparable results as multiphase segmentation for flow-related parameters, eliminating the need for time-consuming multiple segmentations. However, multiphase quantification is necessary for assessing peak values of aortic flow-related parameters. 2 TECHNICAL EFFICACY STAGE: 3.

Three-dimensional characterisation of pore networks and fluid flow in segregated heaps in the presence of crushed ore and agglomerates

Due to the differences in ore feeds and stacking procedures, segregated pore networks are commonly observed in industrial heap leaching operations, which strongly affect the pore-scale fluid flow and the resulting metal leaching efficiency. Three segregated models, namely, the agglomeration model or AM with intra-particle pores, the crushed ore model or COM with inter-particle pores and the mixed segregated model or MSM with both intra- and inter-particle pores, are defined in this work. The segregated pore network in the MSM consists of agglomerates and crushed particles. The models were obtained by performing micro-computed tomography scanning experiments in packed beds followed by image processing algorithms. Several fluid flow-related parameters were quantified to understand the effects of segregated pore networks on fluid flow in heap leaching. The isolated and connected pores co-exist in porous ore heaps, and the latter determines heap hydrodynamics. The number of connected pores in the AM is higher than in the COM. However, the connected pores with too small pore throats are very slow in fluid transfer by capillarity, resulting in stagnant regions in ore beds. A smaller tortuosity value was also observed in the COM, resulting in fast-flowing preferential fluid flow paths. These are unfavourable to yield uniform fluid flow distributions in industrial heaps. The results of this work suggest the prerequisites for improving fluid flow distribution in heaps, including well-organised heap construction procedures, controlling the particle size distribution and large-scale studies coupled with non-invasive imaging and flow simulations.

Radiative and dissipative flow of hybrid nanofluid between two coaxial cylinders: A comparative numerical study

Radiation in dissipative flow of hybrid nanofluid TiO2+ Pb/water bounded between two coaxial cylinders is addressed. The hybrid nanomaterial is synthesized by adding nanoparticles lead and titanium dioxide TiO2and Pb in water as conventional fluid. Geometrically the outer cylinder exhibits rotation and the inner cylinder fixed. Constant strength magnetic field is taken radially. Thermal radiation and viscous dissipation describe heat transfer analysis. Mathematical equations (continuity, momentum, and energy) are obtained via mathematical modeling. Bvp4c method is used for solutions development. Influences of flow and heat related parameters on skin friction, velocity, temperature and Nusselt number have been shown. Velocity of fluids (hybrid nanofluid and nanofluid) is controlled by higher magnetic parameter while temperature and skin friction intensifies with it. Higher nanoparticle volume fractions (for both nanoparticles) reduce velocity while skin friction and Nusselt number are intensified. Moreover, higher radiation parameter causes temperature drop. In comparative analysis, the effects of hybrid nanofluid TiO2+ Pb/water are dominant when compared with nanofluid TiO2+ water.

Hemodynamic Effects of Subaortic Stenosis on Blood Flow Characteristics of a Mechanical Heart Valve Based on OpenFOAM Simulation.

Subaortic stenosis (SAS) is a common congenital heart disease that can cause significant morbidity and mortality if not treated promptly. Patients with heart valve disease are prone to complications after replacement surgery, and the existence of SAS can accelerates disease progression, so timely diagnosis and treatment are required. However, the effects of subaortic stenosis on mechanical heart valves (MHV) are unknown. This study aimed to investigate flow characteristics in the presence of subaortic stenosis and computationally quantify the effects on the hemodynamics of MHV. Through the numerical simulation method, the flow characteristics and related parameters in the presence of SAS can be more intuitively observed. Based on its structure, there are three types of SAS: Tunnel-type SAS (TSS); Fibromuscular annulus SAS (FSS); Discrete SAS (DSS). The first numerical simulation study on different types of SAS found that there are obvious differences among them. Among them, the tunnel-type SAS formed a separated vortex structure on the tunnel-type narrow surface, which exhibits higher wall shear force at a low obstacle percentage. However, discrete SAS showed obvious differences when there was a high percentage of obstacles, forming high peak flow, high wall shear stress, and a high-intensity complex vortex. The presence of all three types of SAS results in the formation of high-velocity jets and complex vortices in front of the MHV, leading to increased shear stress and stagnation time. These hemodynamic changes significantly increase the risk of MHV dysfunction and the development of complications. Despite differences between the three types of SAS, the resultant effects on MHV hemodynamics are consistent. Therefore, early surgical intervention is warranted in SAS patients with implanted MHV.

Toward More General Turbulence Models via Multicase Computational-Fluid-Dynamics-Driven Training

The accuracy of machine-learned turbulence models often diminishes when applied to flow cases outside the training data set. In an effort to improve the predictive accuracy of data-driven models for an expanded set of cases, an extension of a computational fluid dynamics (CFD)-driven training framework consisting of three key steps is proposed. Firstly, a list of candidate flow-related parameters is selected to supplement Pope’s general tensor basis hypothesis. Secondly, modeling an additional production term may benefit the overall predictions in certain situations. Finally, the Reynolds-averaged Navier–Stokes (RANS) evaluations of candidate models are performed on several different flows simultaneously during the model training iterations. Five free-shear and five wall-bounded flow cases are chosen to train or test data-driven turbulence models. It is shown that the machine-learned models from the present multicase CFD-driven framework can significantly improve the predictive accuracy for the test cases where the baseline RANS results showed significant error from the ground truth. Meanwhile, for cases in which the baseline produced good results, the new models do not perform worse. Further analysis shows that the new models can adapt to opposite trends of turbulent diffusion required for the different cases with a common correction. Moreover, the trained models can be simplified and still achieve similar improvement as the whole expressions.

Research on transient composition tracking in natural gas condensate pipeline networks

Offshore pipelines are hailed as the “lifeline” of an offshore oil and gas production system and are essential for offshore oil and gas development. Component tracing technologies for the oil and gas multiphase transmission pipeline networks need to be urgently developed to predict the fluid composition changes in pipeline networks. Instead of assuming the fluid components are constant, we consider they varied with flow. The component conservation equations and a phase change model are established. The equation of state of the fluid is adopted to determine the equilibrium state of each component in real time. Considering the macroscopic flow calculation, microscopic fluid components, and phase equilibrium, the component tracking algorithm is established for natural gas condensate pipeline networks, which can dynamically track the fluid composition in pipeline networks and calculate the phase exchange amount and related flow parameters in real time. Three case studies are performed to verify the effectiveness of the algorithm. These findings are of great practical significance for understanding the gas–liquid two-phase flow in pipeline networks, promoting further engineering applications of component tracking on pipeline networks.

Geometric improvement for two bridge pier types to reduce local scour

Local scour around the bridge piers play a critical role in collapse and heavy damages on bridges. Many researchers have studied local scour problem. However, majority of the studies only focused on examination of the complex flow structure and offering new pier geometry designs without any structural restrictions, which ignore construction difficulties. This study attempts to investigate the effect of geometric enhancements on commonly used conventional pier types to reduce scour related flow parameters acting on riverbed. A right triangular implementation that wraps the reference shapes were accordingly applied as non-load bearing curtain walls. Triangular implementation has been parametrized by its leg lengths and successive numerical analyses were conducted to reveal the better option among different modifications. Performance of the modified piers were compared in terms of pressure and the bed shear stresses acting on riverbed representing the two important flow forces that are responsible for triggering and developing scour. The results show that low height values with high width values of conical implementations perform better in terms of reducing maximum pressure and shear stress acting on riverbed.

DETERMINATION OF WALL HEAT FLUX BASED ON BUBBLE DEPARTURE AND LIFT-OFF DIAMETERS FOR VARYING PRESSURE AND FLOW VELOCITY CONDITIONS

In this study, the bubble departure and lift-off (BDL) boiling model has been improved by implementing the subcooling suppression factor and flow-related parameters, with the aim of developing an accurate heat transfer model for various engineering applications. The BDL model has been exploited using a MATLAB program to determine the variation of wall heat flux that controls the boiling curve. Three different parameters, namely, bulk flow velocity, operating pressure, and bulk flow temperature have been considered in this study. Experimental conditions were simulated as per Chen's BDL model algorithm, and the resulting wall heat flux was compared with the measured values. Additionally, different boiling curves for bubble departure and lift diameters were generated and their effect on varying operating conditions was studied. The resultant boiling curves were compared with the experimental data by means of mean absolute error (MAE) and regression coefficient (&lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;) values. In general, with a reasonable margin of error, i.e., MAE &amp;#61; 3.35&amp;#37;, and &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; &amp;#61; 0.99, the algorithm performed well in comparison with the experimental data. The bubble departure and lift diameters were also correlated with the experiment and the predictions were satisfactorily close.

Characteristic analysis of natural circulation residual heat removal in small reactor

In order to study the characteristics of small helium-xenon cooled nuclear reactor that only relies on natural circulation to remove residual heat after shutdown, this paper carries out geometric and physical modeling of helium-xenon cooled nuclear reactor, and uses CFD to simulate the process of natural circulation residual heat removal. Variation laws of the hot spot temperature on the surface of fuel cladding and the mass flow of helium-xenon mixed gas under different working conditions are calculated, and the transient characteristics of temperature, flow and other related parameters in the system loop are analyzed. The calculation results show that during the natural circulation residual heat removal process, the overall change trend of the hot spot temperature on the surface of the fuel cladding, the average temperature of the primary coolant and reactor outlet temperature first rises to the highest value and then decreases, and the mass flow of helium-xenon mixed gas shows an exponential decay trend; Increasing the initial mass flow of helium-xenon mixed gas and reducing the residual heat of the reactor core can reduce the maximum hot spot temperature on the surface of the fuel cladding. The relevant research results provide a useful reference for the optimal design of natural circulation residual heat removal of helium-xenon cooled nuclear reactor.

Estimating Pulsatile Blood Flow Parameters from Digital Subtraction Angiography.

Digital subtraction angiography (DSA) is the gold standard for diagnosing vascular diseases. Much attention had been attracted on estimating blood flow velocity from DSA data, and many techniques to compute the mean flow velocity had been proposed. In this paper, we present a physical model that demonstrates how the pulsatile flow can affect the dispersion of the contrast medium delivered into the blood vessel. Using empirical mode decomposition and angiographic data of 4 patients, we then showed it is feasible to compute pulsatile flow related parameters from routine interventional angiographic acquisitions.Clinical Relevance- This is the first attempt to present a physical model and corresponding method to estimate pulsatile flow related parameters from routine angiographic acquisitions, and has potential to be used for real-time diagnostic and therapeutic monitoring during interventional procedures.

Changes in duplex ultrasound parameters during maturation according to arteriovenous access types in incident hemodialysis patients.

Little is known about the changes in hemodynamic parameters during arteriovenous (AV) access maturation using duplex ultrasound according to radiocephalic fistula (RCF), brachiocephalic fistula (BCF), and AV graft (AVG) in incident hemodialysis (HD) patient. The objective of this study was to evaluate changes and differences in brachial artery flow rate (BAFR) and related parameters affecting maturation by duplex ultrasound in incident HD patients according to access type. This study was an observational study conducted from March 2019 to October 2020. During the study period, 109 incident patients underwent new AV access creation, of which 100 were included in the study. The duplex ultrasound was performed on the day prior to access creation, further, day 1, 2 weeks, and 4 weeks later after access creation in incident HD patients. Among all the patients, 38 (38%) received BCF, while 26 (26%) underwent RCF. Of the patients with AVG, 18 (50%) had a forearm loop AVG. The overall mean age was 62.2 ± 13.8 years (range, 32-89). The BAFR increased about 6.9 times in the RCF, 17.4 times in the BCF, and 19.5 times in the AVG at day 1. The median BAFR measured on day 1 was 580.4 mL/min for RC, 1029.0 mL/min for BC, and 1133.0 mL/min for AVG. Relative to the values measured in week 4, the BAFR on day 1 was 69.5% in RCF, 90.6% in BCF, and 93.9% in AVG. The acceleration decreased most significantly on day 1(p < 0.05). The acceleration time increased significantly on day 1 (p < 0.05) and beyond during maturation in the RCF and BCF. The BAFR of the RCF had a significantly negative correlation with the pulsatility index. The BAFR of the BCF showed a significantly positive correlation with the systolic and diastolic blood pressure but negatively correlated with pulse rate. The BAFR of the AVG showed a significant positive correlation with the diameter of the outflow vein. There were differences in the clinical and duplex parameters during maturation according to access type. The most dramatic changes of duplex parameters were on the day after AV access creation regardless of AV access types. Though RCF had a lower BAFR rate compared to BCF and AVG, it already had a sufficient BAFR required for adequate HD treatment the day after creation. The BAFR of BCF was not different from that of AVG.