Deviation Of Pressure Research Articles

Optimizing Cardiovascular Health Monitoring with IoT-Enabled Sensors and AI: A Focus on Obesity-Induced Cardiovascular Risks in Young Adults

With shifts in lifestyle and dietary patterns, obesity has become an increasing health issue among younger demographics, particularly affecting young adults. This trend is strongly associated with a heightened risk of developing chronic diseases, especially cardiovascular conditions. However, conventional health monitoring systems are often limited to basic parameters such as heart rate, pulse pressure (PP), and systolic blood pressure (SBP), which may not provide a comprehensive assessment of cardiac health. This study introduces an intelligent heart health monitoring system that leverages the Internet of Things (IoT) and advanced sensor technologies. By incorporating IoT-based sensors, this system aims to improve the early detection and continuous monitoring of cardiac function in young obese women. The research employed a TERUMO ES-P2000 to measure blood pressure and a PhysioFlow device to assess noninvasive cardiac hemodynamic parameters. Through precise sensor data collection, the study identified key indicators for monitoring cardiovascular health. Machine learning models and big data analysis were utilized to predict cardiac index (CI) values based on the sensor-derived inputs. The findings indicated that young obese women showed significant deviations in blood pressure (SBP and PP) and cardiac hemodynamic metrics (SVI, EDV, and ESV) at an early stage. The implementation of signal processing techniques and IoT sensors enhanced the CI prediction accuracy from 33% (using basic parameters like heart rate, PP, and SBP) to 66%. Moreover, the integration of extra sensor-based parameters, such as Stroke Volume Index (SVI) and Cardiac Output (CO), along with the use of color space transformations, successfully improved the prediction accuracy of the original data by 36.68%, increasing from 53.33% to 90.01%. This represents a significant improvement of 30.01% compared to the existing technology’s accuracy of 60%. These results underscore the importance of utilizing sensor-derived parameters as critical early indicators of cardiac function in young obese women. This research advances smart healthcare through early cardiovascular risk assessment using AI and noninvasive sensors.

The role of third-body collision efficiency in autoignition of hydrogen–air mixtures

Numerical simulations of autoignition of lean (6% H2), stoichiometric, and rich (90% H2) hydrogen–air mixtures have been performed to examine the influence of third-body efficiency (chaperon efficiency, CE) on the value of ignition delay, τ. The temperature ranges explored in the computations are 850–1000 K for P0 = 1 bar and 1000–1200 K for P0 = 6 bar. By using a detailed kinetic mechanism, it has been found that the sensitivity of ignition delay to CE is the highest for the reaction step H + O2 + M = HO2 + M, which can lead to a variation in τ by a factor of 2 to 3. A pressure increase or deviation from stoichiometry reduces the sensitivity. The influence of CE is qualitatively different and weaker for the reaction step OH + OH + M = H2O2 + M.

Comparing methods for reducing artificial pressure fluctuations using large eddy simulation in high-rise building wind load assessment

Reducing artificial pressure fluctuations (RAPF) is one of the key challenges in simulating atmospheric boundary layer turbulence. This study, based on the synthetic turbulence method, compares the performance of three RAPF methods: inlet mass correction (IMC), divergence-free correction (DFC), and local pressure correction (LPC). First, large eddy simulations of an empty domain show that the IMC and DFC methods effectively suppress unrealistic pressure fluctuations throughout the flow field. As the turbulence develops downstream, the pressure fluctuations decay rapidly and become almost insignificant. Conversely, the LPC method only reduces local nonphysical pressure fluctuations by adjusting the pressure reference location, but as the distance from the reference point increases, the pressure fluctuations gradually increase. Moreover, the IMC and DFC methods adjust the initial turbulent field to meet inlet mass balance or divergence-free conditions, which results in changes to the initial turbulence characteristics. However, the LPC method avoids modifying the initial turbulence, allowing it to better maintain the original turbulence properties. Finally, the simulations for wind loads on the high-rise building indicate that the application of the IMC, DFC, and LPC methods results in reasonable mean, standard deviation and peak values of pressures on the building surfaces, as well as accurate calculations of the integrated base forces and moments.

Deep learning-enhanced aerodynamics design of high-load compressor cascade at low Reynolds numbers

This study addresses the challenges of designing high-efficiency compressors for long-endurance, high-altitude unmanned aerial vehicles (UAVs) under low Reynolds number (Re) and high load conditions, exploring the aerodynamic performance limits of compressor blades under extreme conditions. The research integrates advanced numerical simulations, experimental methods, and deep learning technologies to minimize profile losses and deviation angle on compressor blades. An orthogonal experimental design systematically explored the impact of key geometric factors on aerodynamic performance. A deep learning model incorporating neural networks with spatial attention mechanisms was developed to significantly enhance the accuracy of aerodynamic predictions. This model adeptly captured the complex nonlinear interactions between aerodynamic and geometric parameters. Sobol sensitivity analysis revealed that the dimensionless maximum thickness is the most critical factor, accounting for 44 % of the total variance in total pressure loss and deviation angle. The position of maximum thickness and the aspect ratio of the elliptical leading edge also significantly influenced performance. The optimized high-load compressor blade profile was validated through experimental data and detailed computational fluid dynamics analysis using large eddy simulation methods. This analysis revealed flow separation and reattachment mechanisms, shedding light on turbulence and vortex dynamics critical to performance. This research deepens the theoretical understanding of compressor cascade fluid dynamics and provides practical insights for designing more efficient compressors, especially for micro axial compressors in high-altitude UAVs.

Perioperative blood pressure variability as a risk factor for postoperative delirium in the patients receiving cardiac surgery

BackgroundDelirium is one of the most common neurological complications after cardiac surgery. The purpose of our study was to assess the relationship between perioperative blood pressure variability (BPV) and postoperative delirium (POD) in the patients undergoing cardiac surgery.MethodsAdult patients received cardiac surgery and stayed in Cardiovascular Intensive Care Unit (ICU) for more than 24 h after surgery during the study period between June 2019 and December 2022 were included in this study. Baseline characteristics, perioperative hemodynamic variables and postoperative laboratory results of the cardiac patients were collected and analyzed. Perioperative BPV was quantified by calculating the standard deviation (SD) and average real variability (ARV) of blood pressure. Assessment of delirium was based on the mental status of the patients and CAM-positive. The relationship between perioperative BPV and POD was analyzed by LASSO and logistic regression using R (R package, 4.3.2).ResultsThe incidence of POD was 15.0% (324/2164) in the patients receiving cardiac surgery, and the average day for POD occurred at day 3 after surgery. Patients with POD had statistically lower levels of intraoperative mean blood pressure (P = 0.015) and blood pressure ARV (P < 0.001) as well as mean blood pressure at 24 h postoperatively (P = 0.003) when compared to those without. Whereas, ARV for systolic blood pressure (8.64 vs. 7.91 mmHg, P < 0.001), diastolic blood pressure (4.00 vs. 3.77 mmHg, P = 0.014) and mean blood pressure (5.23 vs. 4.94 mmHg, P = 0.001) at 24 h postoperatively was significantly higher in the patients with POD than those without. LASSO regression and further logistic regression revealed that intraoperative blood pressure ARV (OR:0.92, P < 0.001), mean central venous pressure (OR:1.05, P = 0.048) and ARV of systolic blood pressure (OR:1.17, P = 0.002) at 24 h postoperatively were independent risk factors for POD.ConclusionsPerioperative ARV, especially postoperative high ARV exposure, was associated with POD in the patients receiving cardiac surgery. Maintaining a relatively stable blood pressure after cardiac surgery might be beneficial to avoid POD in those patients.

Intelligent control system and operational performance optimization of a municipal solid waste incineration power plant

This study proposed an integrated intelligent control system in one municipal solid waste incineration power plant to improve the system's control accuracy, economic performance and environmental impact, including the intelligent combustion, intelligent denitrification, intelligent desulfurization and intelligent soot-blowing control subsystems. The precise detection and adjustment of the key operational parameters was achieved by integrating these modules into the existing distributed control system. A comparative analysis of the operation data between pre-optimization and post-optimization states was conducted to assess the changes in the key operational and economic parameters. The results indicate that the introduction of the intelligent control module can significantly improve the system stability and parameter control accuracy, thereby enhancing the economic efficiency of the waste incineration power plant and reducing the operation workload and the pollutants emissions. Specifically, the standard deviations of main steam flowrate and pressure decreased by 45.1 % and 60.7 %, respectively. Furthermore, the consumptions of the ammonia water and lime slurry were reduced by 38.2 % and 23.2 %, respectively, while the auxiliary power consumption rate declined by two percentage points, and the power generation per ton of waste increased by 4.2 %. These improvements not only strengthen the economic benefits but also effectively reduce the pollutants emissions.

The mechanical response of polymeric gyroid structures in an optimised orthotic insole.

This study aims to explore the mechanical behaviour of polymeric gyroid structures under compression within the context of orthotic insoles, focussing on custom optimisation for lower peak plantar pressures. This research evaluates the compressive response of gyroid structures using a combination of experimental testing and numerical modelling. Stereolithography was used to manufacture gyroid samples for experimental tests, and explicit finite element analysis was used to model the gyroid's response numerically. Hyperfoam, first-order polynomial, and second-order polynomial hyperelastic constitutive models were considered to homogenise the mechanical response of the structure. The homogenised properties of the structure were then implemented in an optimisation algorithm to obtain the optimal gyroid structure for a given subject by minimising the standard distribution of plantar pressures. Findings indicate that the compressive response polymeric gyroid structures can be represented with a homogeneous material. The hyperfoam model was chosen due to its accuracy and interpolation quality. The optimisation process successfully identified configurations that maximise the mechanical advantages of gyroid lattices, demonstrating significant improvements in plantar pressure distributions. The optimised insole showed a 30% reduction in the standard deviation of the plantar pressure and a 10% reduction in the peak stress. The optimisation method reduced peak pressures by 12.2 kPa compared to a traditional medium-density Poron orthotic insole, and 94.3 kPa compared barefoot conditions. The mechanical response of gyroid structures has successfully been modelled, analysed and homogenised. The study concludes that custom gyroid-based orthotic insoles offer a promising solution for personalised foot care.

Comparative study on the performance of fresh concrete comprising manufactured sand vs. river sand during full-scale long-distance pumping

The shift from river sand (RS) to manufactured sand (MS) as a fine aggregate in concrete is driven by environmental sustainability concerns. However, negative impacts of MS on concrete workability have raised doubts about its suitability for long-distance pumping in construction projects. This study evaluates the performance of MS concrete compared to RS concrete of the same strength grade during long-distance pumping. A full-scale coiled pipeline with measured length of 348 m was built, twelve batches of C30 and C60 concrete were prepared, and pumping tests were conducted at discharge rates of 2.5–18.9 liter per second (L/s). The workability and rheological parameters were assessed before and after pumping. The measured and predicted pumping pressure were analyzed and calculated based on rheological parameters and lubricating layer (LL) parameters. Results indicate that MS increased the yield stress and decreased the LL thickness index of C30 concrete, while it decreased the viscosity coefficient of C60 concrete. Post-pumping, the change in yield stress was similar for both MS and RS concrete, but MS reduced the plastic viscosity change in C60 concrete. MS did not significantly affect the pumping pressure loss, but influenced the pumping pressure prediction deviation by influencing the thixotropy. The classic pumping pressure prediction model developed by Kapan obviously overestimated the pumping pressure during long-distance pumping, and the deviation was more prominent in high-strength concrete pumping. MS increased the thixotropy of C30 concrete and reduced the prediction deviation of pumping pressure, but had the opposite effect on C60 concrete.

Junction conditions for one-dimensional network hemodynamic model for total cavopulmonary connection using physically informed deep learning technique

Abstract This paper presents a novel methodology utilizing physics-informed neural network (PINN) as a junction condition for a 1D network model of blood flow in total cavopulmonary connection generated by the Fontan procedure. The technique integrates a 3D mesh generation process based on the parameterization of the junction geometry, along with a sophisticated physically regularized neural network architecture. Synthetic datasets are produced using 3D steady Stokes simulations within fixed boundaries. We use a physically informed feedforward neural network that utilizes a physically regularized loss function, which incorporates the principle of mass conservation. Our PINN achieves a tolerance of 6% on the test set. We develop a 1D-PINN multiscale model based on a previously developed method for multiscale 1D–3D simulations. Comparison with 1D–3D Stokes based model and 3D Navier–Stokes based model verifies the 1D-PINN model. In the first and second comparison, the maximum deviations of the averaged pressures and flows do not exceed 1.48% and 12.26%, respectively.

Numerical Simulation of the Flow Field Stabilization of a Pressure-Regulating Device

In sprinkler irrigation systems in hilly areas, pressure-regulating devices can improve the uneven pressure distribution on branch pipes and consequently improve the irrigation uniformity. A pressure-regulating device for sprinkler irrigation systems was developed; the variation characteristics of the internal pressure field and velocity field distribution over time, variation law of the elastic diaphragm of the pressure-regulating device with respect to the inlet pressure, and pressure-regulating and flow stabilizing mechanisms were assessed. The results show that the pressure regulation and flow stabilization of the pressure-regulating device were affected by the deformation of the elastic diaphragm. When the elastic diaphragm deforms, the main factors of pressure regulation and flow stabilization in the pressure regulation device gradually shift from the side channel and compensation chamber to the side channel and secondary channel. The channel structure plays a crucial role in the entire fluid system. A comparison and analysis of the changes in cross-sectional pressure and flow velocity of the flow channel under different inlet pressures revealed that increasing the height of the side flow channel baffle and auxiliary flow channel effectively improved the pressure-regulating and flow-stabilizing performance of the pressure-regulating device. The results can be useful to optimize the structure of pressure regulation devices and to solve the problem of excessive pressure deviation in sprinkler irrigation systems in hilly areas.

Experimental analysis of pressure deviation-induced film cooling effectiveness deviation in pressure sensitive paint measurement

The use of the Pressure Sensitive Paint (PSP) measurement method allows for obtaining dense, completely adiabatic film cooling effectiveness (η) results. In order to adapt to the increasing trend of high-speed and complexity in the application scenarios of film cooling, the pressure deviation-induced film cooling effectiveness deviation in PSP measurements needs to be quantified and corrected. Initially, two different jets of specific materials were injected into a dual-hole flat plate test piece. The pressure difference at corresponding positions of the two jet flows was measured to demonstrate that, compared to air, a ternary oxygen mixed gas better simulated the pressure field of the foreign gas. This illustrates the feasibility of the Test3-OM correction method. Building upon this, the influence of pressure deviation on the accuracy of measurement results was quantitatively evaluated in various scenarios, including a flat circular hole, film holes with a compound angle, a converging slot hole, and film holes at three positions on the blade. The results indicate that the pressure deviation-induced η deviation is non-negligible under conditions of high blowing ratios in most positions. Particularly in the low η region, there is a higher sensitivity to pressure deviation. Generally, there is a negative deviation region near the hole downstream, and a positive deviation region slightly downstream. The generation of deviations stems from variations in density, resulting in different flow patterns of the jet near the wall surface.

Performance assessment of a high-efficiency indirect dew-point evaporative cooler through three-dimensional modeling

The escalating demand for eco-friendly air cooling, driven by concerns over global warming, necessitates sustainable alternatives to air conditioners. Dew-point evaporative coolers offer a green alternative yet face challenges due to high flow resistances caused by the U-turn of the working air. Recently, we have developed a new compact counterflow dew-point cooler that eliminates the U-turn of the working air, mitigating flow resistance. In this paper, a precise three-dimensional simulation, based on fluid dynamics, heat transfer and mass transportation, is developed to assess the cooler's performance. The validation against experiments shows maximum 8 % deviation in input pressure and 3 % in product air temperature. The simulation provides insights into the cooler's operation, efficiency, and performance, which are not easily obtained experimentally. Optimal cooling coefficients of performance occurs at working ratios of 0.5–0.6. Notably, while metallic channel separator excels at higher flow rates, plastic ones like high-density polyethylene and polycarbonate match performance at lower rates. Furthermore, the cooler performs better in hotter, drier climates. In locales like Xian and New Delhi, the cooler is suitable for standalone use, while in regions like Dubai, Texas, Singapore, Beijing, and Monterrey, it can be coupled with air conditioners to enhance the ventilation and energy efficiency.

Liquid Rocket Engine Performance Characterization Using Computational Modeling: Preliminary Analysis and Validation

The need to refuel future missions to Mars and the Moon via in situ resource utilization (ISRU) requires the development of LOX/LCH4 engines, which are complex and expensive to develop and improve. This paper discusses how the use of digital engineering—specifically physics-based modeling (PBM)—can aid in developing, testing, and validating a LOX/LCH4 engine. The model, which focuses on propulsion performance and heat transfer through the engine walls, was created using Siemens’ STAR-CCM+ CFD tool. Key features of the model include Eulerian multiphase physics (EMP), complex chemistry (CC) using the eddy dissipation concept (EDC), and segregated solid energy (SSE) for heat transfer. A comparison between the complete GRI 3.0 and Lu’s reduced combustion mechanisms was performed, with Lu’s mechanism being chosen for its cost-effectiveness and similar output to the GRI mechanism. The model’s geometry represents 1/8th of the engine’s volume, with a symmetric rotational boundary. The performance of this engine was investigated using NASA’s chemical equilibrium analysis (CEA) and STAR-CCM+ simulations, focusing on thrust levels of 125 lbf and 500 lbf. Discrepancies between theoretical predictions and simulations ranged from 1.4% to 28.5%, largely due to differences in modeling assumptions. While NASA CEA has a zero-dimensional, steady-state approach based on idealized conditions, STAR-CCM+ accounts for real-world factors such as multiphase flow, turbulence, and heat loss. For the 125 lbf case, a 9.2% deviation in combustion chamber temperature and a 15.0% difference in thrust were noted, with simulations yielding 113.48 lbf compared to the CEA’s 133.52 lbf. In the 500 lbf case, thrust reached 488 lbf, showing a 2.4% deviation from the design target and an 8.6% increase over CEA predictions. Temperature and pressure deviations were also observed, with the highest engine wall temperature at the nozzle throat. Monte Carlo simulations revealed that substituting LNG for LCH4 affects combustion dynamics. The findings emphasize the need for advanced modeling approaches to enhance the prediction accuracy of rocket engine performance, aiding in the development of digital twins for the CROME.

Study on shock wave load characteristics from condensed phase explosive detonations in deep-water explosions

This study investigates shock wave load characteristics from condensed phase explosive detonations in deep-water environments using a high-order compressible multiphase solver. Spatial terms of the solver are discretized by fifth-order weighted essentially non-oscillatory reconstruction in characteristic space, while a third-order total variation diminishing Runge–Kutta method is adopted to deal with the temporal terms. The level-set method captures multiphase interfaces, while a programed burn model describes detonation wave generation. Numerical and experimental validations focus on shock waves in explosives interacting with water. Validations across shallow and deep-water conditions align numerical results with theoretical and experimental values. The solver examines shock wave characteristics across varied charge masses and water depths, revealing peak pressure deviations under identical conditions. The numerical simulation results indicate that the similarity of shock wave loads in underwater explosions is evident not only in peak pressures but also in the pressure–time history curves. Through extensive comparative analysis of results, it has been found that existing formulas for calculating shock wave positive pressure durations are not applicable to deep-water explosions. The research findings and analytical methods presented in this paper can serve as crucial references for further studies on the characteristics of shock wave loads in deep-water explosions.

Assessment of postural sway with accelerometers: A comparison with force plate measures

Introduction &amp; Purpose Postural control is essential for maintaining balance during static and dynamic tasks. It is typically measured by centre of pressure (CoP) deviations using a ground reaction force plate (FP). Alternatively, more affordable and accessible accelerometer-based measures have been proposed. However, no consensus on the best protocol exists (Pinho et al., 2019). This study investigates the feasibility of assessing postural sway using linear acceleration data, considering sensor placement, task difficulty and analysed parameters. Methods The University of Vienna Ethics Committee approved this study (Ref. Nr. 01108). Ten healthy adults (6 M/4 F; 37.9 ± 14.8 years; BMI = 23.3 ± 2.3) performed eleven balance tasks, seven easy tasks from the Berg Balance Scale and four harder tasks with eyes closed, each lasting 20 seconds. Postural sway was assessed using a FP and five inertial measurement units (IMUs) attached to the upper spine (C7), lower spine (L1), sacrum and both thighs. Data were synchronously collected at 1500 Hz, zeroed, band pass filtered (3rd order Butterworth, 0.3-10 Hz; Martinez-Mendez et al., 2012), and cropped to 19 s. Outcomes included CoP path length, root mean square of sway amplitude in the anteroposterior (AP) and mediolateral (ML) directions for the FP, and RMS of the linear acceleration in AP and ML directions, along with their sum, for the ACC. Combinations of the two AP, two ML and two overall parameters were analysed by winsorised Pearson correlations and Bland Altman limits of agreement of z-scores for each task and for each sensor site. Fisher's Z-transformed correlation coefficients and limits of agreement were compared across task difficulty, parameter combinations, and sensor placement sites using a 3-way ANOVA. Results Pearson coefficients correlating the ACC parameters with the FP parameters averaged 0.60 (95% CI [0.54, 0.66]) for the easy tasks and 0.78 (95% CI [0.726, 0.84]) for the hard tasks, with no significant differences between sensor sites. A significant interaction (p &lt; 0.001) was found between task difficulty and parameter combination. Simple main effect analysis showed no difference between correlations of AP, ML and overall parameters for hard tasks but for easy tasks, where overall parameters showed the highest correlation, followed by ML and then AP parameters, all differing significantly from each other. The Bland Altman mean difference of z-scores between FP and ACC parameters was on average -0.002 (95% CI [-0.027, 0.024]). The lower and upper limits of agreement were on average -0.72 (95% CI [-0.84, -0.62]) and 0.73 (95% CI [0.62, 0.83]) respectively. Discussion The correlations between FP and ACC were higher during more challenging tasks, while the limits of agreement were broader and less precise in these tasks (data not shown). No optimal sensor placement site was identified as correlation and agreement between the two methods did not differ significantly between sites. The broad limits of agreement suggest relatively low precision of ACC measures compared to FP. Overall parameters often outperformed ML and AP parameters in terms of correlation and precision. Conclusion Accelerometer-based measures of postural sway showed high correlations with force plate measures but low precision when tasks where difficult enough to challenge participants’ balance. Sensor placement site did not influence correlation and precision. References Pinho, A. S., Salazar, A. P., Hennig, E. M., Spessato, B. C., Domingo, A., &amp; Pagnussat, A. S. (2019). Can we rely on mobile devices and other gadgets to assess the postural balance of healthy individuals? A systematic review. Sensors, 19(13), Article 13. https://doi.org/10.3390/s19132972 Martinez-Mendez, R., Sekine, M., &amp; Tamura, T. (2012). Postural sway parameters using a triaxial accelerometer: Comparing elderly and young healthy adults. Computer Methods in Biomechanics and Biomedical Engineering, 15(9), 899–910. https://doi.org/10.1080/10255842.2011.565753

A prospective birth cohort study on the association between gestational blood pressure and neurodevelopment in 2-year-old children

Objective: To investigate the association between gestational blood pressure and neurodevelopment in 2-year-old children. Methods: Based on the"Wuhan Healthy Baby Birth Cohort", 3 754 mother-infant pairs were enrolled in this study. Based on multiple blood pressure measurements during pregnancy, the mean, cumulative, and variability of blood pressure throughout the entire pregnancy and each trimester were calculated. Blood pressure variability was evaluated using standard deviation (SD), coefficient of variability (CV), and variability independent of mean (VIM). Follow-up testing of neurodevelopment in infants and young children at the age of two was conducted to obtain the Mental Development Index (MDI) and the Psychomotor Development Index (PDI). The multivariate linear regression and generalized estimation equation were used to analyze the association between gestational blood pressure data and neurodevelopmental index. Results: The age of 3 754 pregnant women was (29.1±3.6) years, with a pre-pregnancy BMI of (20.9±2.7) kg/m² and a gestational age of (39.3±1.2) weeks. The birth weight of 3 754 children was (3 330.9±397.7) grams, and the birth length was (50.3±1.6) centimeters. The results of the multivariate linear regression analysis showed that after adjusting for relevant confounding factors, the mean blood pressure, cumulative blood pressure, standard deviation of blood pressure, coefficient of variation of blood pressure, independent blood pressure variability of systolic blood pressure, diastolic blood pressure, and pulse pressure throughout pregnancy were negatively associated with the MDI and PDI scores of 2-year-old children. The analysis results of the generalized estimation equation showed that after adjusting for relevant confounding factors, the average systolic blood pressure in the first, second, and third trimesters was negatively associated with MDI/PDI. The negative association between cumulative blood pressure and MDI/PDI was only found in the first trimester. The negative association between blood pressure variation during pregnancy and MDI/PDI was mainly concentrated in the second and third trimesters. Conclusion: There is a negative association between gestational blood pressure and the neurodevelopmental index of 2-year-old children.

Temperature Compensation Method for Piezoresistive Pressure Sensors Based on Gated Recurrent Unit.

Piezoresistive pressure sensors have broad applications but often face accuracy challenges due to temperature-induced drift. Traditional compensation methods based on discrete data, such as polynomial interpolation, support vector machine (SVM), and artificial neural network (ANN), overlook the thermal hysteresis, resulting in lower accuracy. Considering the sequence-dependent nature of temperature drift, we propose the RF-IWOA-GRU temperature compensation model. Random forest (RF) is used to interpolate missing values in continuous data. A combination of gated recurrent unit (GRU) networks and an improved whale optimization algorithm (IWOA) is employed for temperature compensation. This model leverages the memory capability of GRU and the optimization efficiency of the IWOA to enhance the accuracy and stability of the pressure sensors. To validate the compensation method, experiments were designed under continuous variations in temperature and actual pressure. The experimental results show that the compensation capability of the proposed RF-IWOA-GRU model significantly outperforms that of traditional methods. After compensation, the standard deviation of pressure decreased from 10.18 kPa to 1.14 kPa, and the mean absolute error and root mean squared error were reduced by 75.10% and 76.15%, respectively.

Temperature and pressure jump coefficients at a liquid–vapor interface

The temperature and pressure jump coefficients at a liquid–vapor interface are calculated from the solution of the Shakhov kinetic model for the linearized Boltzmann equation. Complete and partial evaporation/condensation at the vapor–liquid interface are assumed as the boundary condition. The discrete velocity method is used to solve the problem numerically. The jump coefficients are tabulated as functions of the evaporation/condensation coefficient. The profiles of the vapor temperature and pressure deviations from that values at the interface corresponding to the liquid temperature and saturation pressure are plotted, and the solutions obtained from kinetic theory and continuum approach are shown to underline the effect of the jumps at the interface. The obtained results have been compared to those given by other authors, who applied the linearized Boltzmann equation as well as the model proposed by Bhatnagar, Gross, and Krook to it, and it was found that the pressure and temperature jump coefficients are relatively insensitive to the collision laws.

Hydraulic characteristics of a large rotation-angle baffle-drop shaft through synergetic discharge from dry and wet sides

To enhance the operational capacity and space utilization of baffle-drop shafts, this study improved the traditional baffle-drop shaft by expanding the wet-side space, incorporating large rotation-angle baffles, and installing overflow holes in the dividing wall. A three-dimensional turbulent model was developed using ANSYS Fluent to simulate the hydraulic characteristics of both traditional and new baffle-drop shafts across various flow rates. The simulation results demonstrated that the new shaft design allowed for discharge from both the wet and dry sides, significantly improving operational capacity, with the dry side capable of handling 40% of the inlet flow. Compared to the traditional shaft, the new design reduced shaft wall pressures and decreased the mean and standard deviation of pressure on typical baffles by 21% and 63%, respectively, therefore enhancing structural safety. Additionally, the new shaft achieved a 2%–12% higher energy dissipation rate than the traditional shaft across different flow rates. This study offers valuable insights for the design and optimization of drop shafts in deep tunnel drainage systems.

Distributed new energy access grid load voltage deviation adaptive compensation method

Abstract Due to the sensitivity changes of compensation penalty parameters, there is a significant deviation in the load voltage of the distributed new energy access grid. Therefore, it is necessary to consider distributed energy access and design a new adaptive compensation method for grid load voltage deviation. Considering the integration of distributed new energy, an adaptive compensation model for grid load voltage deviation was constructed, and an adaptive compensation inverter for grid load pressure deviation was designed to adaptively compensate for grid load voltage deviation. The experimental results show that after adaptive compensation, the voltage deviation value is lower, which has a good compensation effect, reliability, and certain application values, reducing the operational risk of distributed new energy grids.