Calculation Error Research Articles

Productivity Prediction Model of Tight Oil Reservoir Based on Particle Swarm Optimization–Back Propagation Neural Network

Single-well productivity is a crucial metric for assessing the effectiveness of petroleum reservoir development. The accurate prediction of productivity is essential for achieving the efficient and economical development of oil–gas reservoirs. Traditional productivity prediction methods (empirical formulae and numerical simulation) are limited to specific reservoir types. There are few influencing factors, and a large number of ideal assumptions are made for the assumed conditions when predicting productivity. The application scenario is ideal. However, in tight oil reservoirs, numerous factors affect productivity, and their interactions exhibit significant complexity. Continuing to use traditional reservoir productivity prediction methods may result in significant calculation errors and lead to economic losses in oilfield development. To enhance the accuracy of tight reservoir productivity predictions and achieve economical and efficient development, this paper investigates the tight reservoir in the WZ block of the Beibuwan area, considering the impact of geological and engineering factors on productivity; the random forest tree and Spearman correlation coefficient are used to analyze the main influencing factors of productivity. The back propagation neural network optimized by particle swarm optimization was employed to develop a productivity prediction model (PSO-BP model) for offshore deep and ultra-deep tight reservoirs. The actual test well data of the oilfield are substituted into this model. The analysis results of the example application yielded an RMSE of 0.032, an MAE of 1.209, and an R2 value of 0.919. Compared with traditional productivity prediction methods, this study concludes that the model is both reasonable and practical. The calculation speed is faster and the calculation result is more accurate, which can greatly reduce productivity errors. The model constructed in this paper is well suited for predicting the productivity of tight reservoirs within the WZ block. It offers substantial guidance for predicting the productivity of similar reservoirs and supports the economical and efficient development of petroleum reservoirs.

Hybrid Visual Odometry Algorithm Using a Downward-Facing Monocular Camera

The increasing interest in developing robots capable of navigating autonomously has led to the necessity of developing robust methods that enable these robots to operate in challenging and dynamic environments. Visual odometry (VO) has emerged in this context as a key technique, offering the possibility of estimating the position of a robot using sequences of onboard cameras. In this paper, a VO algorithm is proposed that achieves sub-pixel precision by combining optical flow and direct methods. This approach uses only a downward-facing, monocular camera, eliminating the need for additional sensors. The experimental results demonstrate the robustness of the developed method across various surfaces, achieving minimal drift errors in calculation.

Research of the calculation formula for working clearance leakage flow of the hydrogen circulation pump

The hydrogen circulation pump (HCP), a device for recovering unconsumed hydrogen gas in fuel cell systems to improve efficiency, is an important equipment in fuel cell systems. Efficient calculation of the output flow rate of the HCP is crucial for accelerating the product development process, but there is a lack of an effective calculation formula for the working clearance leakage. In this paper, a series of HCP models with different working clearances are established and calculated using an overlapping grid simulation method, verifying that the traditional Roots blower leakage flow formula is feasible for HCP, although the maximum calculation error reaches 10.71%. Further study the pressure distribution law inside the HCP chamber, and revise the traditional calculation formula accordingly, so that the average calculation error of the series models is reduced from 5.75% to 3.82%, and the maximum error is also reduced to 7.73%. Compared with the prototype test data, though the flow values obtained from the two calculation formulas are slightly higher, the calculation error of the correction formula is relatively smaller. The research results indicate that the correction formula can more accurately predict the flow rate of HCP and has important application value.

Suspect screening-data independent analysis workflow for the identification of arsenolipids in marine standard reference materials.

There has been limited research into arsenolipid toxicological risks and health-related outcomes due to challenges with their separation, identification, and quantification within complex biological matrices (e.g., fish, seaweed). Analytical approaches for arsenolipid identification such as suspect screening have not been well documented and there are no certified standard reference materials, leading to issues with reproducibility and uncertainty regarding the accuracy of results. In this study, a detailed workflow for the identification of arsenolipids utilizing suspect screening coupled with data independent analysis is presented and applied to three commercially available standard reference materials (Hijiki seaweed, dogfish liver, and tuna). Hexane and dichloromethane/methanol extraction, followed by reversed-phase high-performance liquid chromatography-inductively coupled plasma mass spectrometry and liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry. Using the workflow developed, mass fragmentation matching, mass error calculations, and retention time matching were performed to identify suspect arsenolipids. Arseno-fatty acids (AsFAs), arsenohydrocarbons (AsHCs), and arsenosugar phospholipids (AsSugPLs) were identified with high confidence; AsHC332, AsHC360, and AsSugPL720 in seaweed, AsHC332 in tuna, and AsFA474 and AsFA502 in the dogfish liver. AsHC332, AsHC360, and AsFA502 were identified as promising candidates for further work on synthesis, quantification using MS/MS, and toxicity testing.

Intraocular Lens Power and Corneal Topographic Change After Pterygium Surgery

PurposeTo investigate the impact of pterygium excision on intraocular lens (IOL) power calculation and corneal astigmatism. DesignsProspective cohort study MethodsWe enrolled 30 eyes with primary pterygium that underwent pterygium excision with a conjunctival autograft. IOL power calculation and keratometry using the IOL Master 700, along with topographic parameters using the Pentacam Scheimpflug topography system, were performed preoperatively and at 1, 3, 6, and 12 months postoperatively. We analyzed correlations between pterygium length/area and IOL power, as well as corneal topographic changes. ResultsThe mean pterygium length was 2.08 ± 0.58 mm, and the mean area was 6.05 ± 2.41 mm2. One year after pterygium surgery, the calculated IOL power values using all formulas were lower than the preoperative values. Pterygia with a horizontal length of 1.73 mm and an area of 4.45 mm2, and those with a horizontal length of 2.25 mm and an area of 6.95 mm2 created 0.5 D and 1.0 D errors in calculated IOL power, respectively (p<0.001). The calculated IOL power values changed significantly from preoperative to six months postoperatively but did not change significantly from six to 12 months postoperatively. Pterygia with a horizontal length greater than 1.83 mm (p<0.001) and an area greater than 5.1 mm2 (p < 0.001) created a 2.0 D error in anterior corneal astigmatism. ConclusionsPterygium causes errors in IOL power calculation, with greater pterygium length/area exerting a larger effect. Cataract surgery with IOL implantation is recommended at least six months after pterygium surgery. In combined case, calculated IOL power should be decreased by 0.5-1.5 D based on the pterygium length/area.

Kinetic analysis and calculation correction methods for moisture evaporation rate in pine lignocellulosic biomass

This study investigates the kinetics of moisture evaporation in pine wood during the drying stage, focusing on analyzing thermogravimetric (TG) curves. The research is based on the kinetic rate model and TG curves obtained at various heating rates, specifically 5, 10, 15, and 20 K/min for the heat release rate, within a temperature range from room temperature to 473 K. Utilizing thermogravimetric experiments and the kinetic rate model, the apparent activation energy and pre-exponential factor are calculated. Further refinement of these calculations is achieved using the Nelder-Mead algorithm. The results show good agreement between the average values of the apparent activation energy (37.88 kJ/mol) and pre-exponential factor (4458.20 s−1) and experimental measurements in the initial and later drying stages, with discrepancies noted in the middle stage. Establishing a relationship between the correction coefficients of these parameters and the heating rate leads to a reduction in calculation errors. Notably, the pre-exponential factor is found to be influenced by heating rates, while the apparent activation energy remains relatively stable. Moreover, the errors are significantly reduced after correction, and the error curve of 10 K/min is the most significant. Overall, the proposed correction method holds promise for accurately calculating moisture evaporation rates in lignocellulosic biomass, offering valuable insights for biomass drying applications.

Incidence and type of voluntary reported perianesthetic medication errors in community veterinary clinics in Calgary, Canada.

To collect medication error (ME) data during the perianesthetic period from small animal clinics. 6 small animal general practice veterinary clinics. Small animal general practice veterinary clinics were recruited in this prospective observational study, with staff given a presentation on medical errors and instructed on how to submit medication error reports to an online reporting system. Errors were classified according to type and timing. A total of 2,728 general anesthesia or sedation procedures were performed, with 49 ME reports submitted. One duplicated report of the same error was excluded, resulting in a ME rate of 1.8%. Most reports (69% [33/48]) were near misses. The remaining 31% were MEs that reached the patient but did not cause harm. Wrong dose errors were the most common type (63% [30/48]), of which 80% (24/30) were calculation errors. Premedication/sedation and maintenance were the most reported stages, at 47% (20/43) and 23% (10/43), respectively. None of the MEs reported resulted in an adverse event, with an approximately 2:1 ratio of near-miss to no-harm MEs. The observed patterns of MEs reported, including type and timing, represent a target for further education. These results quantify the ME rate in general practice veterinary clinics, providing an initial benchmark for MEs during the perianesthetic period.

Memristive Crossbar Array-Based Probabilistic Graph Modeling.

Modern graph datasets with structural complexity and uncertainties due to incomplete information or data variability require advanced modeling techniques beyond conventional graph models. This study introduces a memristive crossbar array (CBA)-based probabilistic graph model (C-PGM) utilizing Cu0.3Te0.7/HfO2/Pt memristors, which exhibit probabilistic switching, self-rectifying, and memory characteristics. C-PGM addresses the complexities and uncertainties inherent in structural graph data across various domains, leveraging the probabilistic nature of memristors. C-PGM relies on the device-to-device variation across multiple memristive CBAs, overcoming the limitations of previous approaches that rely on sequential operations, which are slower and have a reliability concern due to repeated switching. This new approach enables the fast processing and massive implementation of probabilistic units at the expense of chip area. In this study, the hardware-based C-PGM feasibly expresses small-scale probabilistic graphs and shows minimal error in aggregate probability calculations. The probability calculation capabilities of C-PGM are applied to steady-state estimation and the PageRank algorithm, which is implemented on a simulated large-scale C-PGM. The C-PGM-based steady-state estimation and PageRank algorithm demonstrate comparable accuracy to conventional methods while significantly reducing computational costs.

A novel method for measuring electrolytic conductivity with a polarization impedance control function

The article presents an idealized model of the differential method utilized in conductometry to measure electrolytic conductivity (EC). It identifies the main drawback of the widely used differential method: the inability to control the influence of polarization impedance on EC measurement results. A criterion for the absence of error caused by polarization effects is proposed, involving equality between the ratios of resistance differences and cell constant differences. A novel method for EC measurement, termed the double differential method, is introduced. This method relies on repeated differential impedance measurements and incorporates an additional third impedance measurement of a virtual liquid column. The new approach enables the identification of polarization impedance influence on EC measurements and the calculation of measurement errors for correction. A 3 times lower type A measurement uncertainty value can be achieved by averaging the corrected results.

Analisis penerapan akuntansi Pajak Penghasilan Pasal 21 pada karyawan PT. Manado Post

Manado Post is a Media Company under the Jawa Post Group. Manado Post has a large number of employees with the specifications of Permanent Employees and Non-Permanent Employees, so it has great potential in paying taxes, especially Article 21 Income Tax. In addition, there is the potential for errors in both calculating and recording Income Tax. This also affects accounting records, because errors in calculations will cause errors in accounting records. In addition, Manado Post on irregularities in both calculation and reporting of Income Tax caused by differences in views on the Income Tax Law. This also affects accounting records. Based on the reference background of this study, the subject matter can be formulated which will then be the object of discussion in this study. This study used qualitative descriptive method. A total of 55 employees were involved in the study, and of these, 15 employees were the subjects of the study. The qualitative research intended here is to illustrate how the accounting treatment of Article 21 Income Tax applied in Manado Post. The results showed that Manado Post did not fully follow the applicable Tax Law in calculating article 21 income tax on its employees. This causes an overpayment of Article 21 income tax by the company. In this case, Manado Post needs to improve understanding and compliance with applicable tax rules to avoid errors in tax calculations.

ВПЛИВ ПУЛЬСАЦІЙ ІМПУЛЬСНОГО ПЕРЕТВОРЮВАЧА НА ПОХИБКУ СЛІДКУВАННЯ ЗА ШВИДКІСТЮ БОРТОВОГО ЕЛЕКТРОПРИВОДА

An analysis of the tracking error was performed without taking into account the pulsations of the electric motor supply voltage and taking into account the pulsations of the electric motor supply voltage. The results of the calculation of the constant tracking error are presented, taking into account the influence of pulsations, which is a consequence of the pulse width modulation (PWM) process. Ref. 7, fig. 2.

An improved method for evaluating fracture density using pulsed neutron capture logging

Fracture density is a critical fracture evaluation parameter for the optimization and production prediction of hydraulic fracturing models. Nonradioactive tracer (NRT) techniques have successfully used a quantitative fracture density method based on neutron-induced gamma rays from formation elements. Furthermore, fracture density can be calculated using the formation capture cross section before and after hydraulic fracturing based on pulsed neutron capture logging. However, the response sensitivity of the macroscopic scattering cross section to the fractures decreases when the fracture density is high due to the neutron self-shielding phenomenon. Therefore, an improved fracture density evaluation method is applied, which combines the macroscopic capture cross section and the neutron self-shielding correction factor. In the new method, the peak area of titanium from the captured gamma spectrum is used to obtain a neutron self-shielding correction factor to improve the sensitivity of fracture density determination. Furthermore, the response of capture cross-section variation to fracture density at various tagged proppant concentrations and formation backgrounds is investigated. The findings indicate that the tagged proppant concentration influences the detection limit of fracture density and the sensitivity of fracture density identification. The accurate calculation range of fracture density using the new method has been extended from 5% to 10% under the condition that the tagged proppant concentration is 0.2%. Meanwhile, whereas water salinity significantly impacts capture cross-section variation, the effects of porosity, lithology, and fluid type on capture cross-section variation are negligible. A simulated fracturing example demonstrates the method’s applicability in various measurement environments. The results show that fracture density and height are consistent with the model settings after correcting for water salinity, and the fracture density calculation error is less than 3%. Therefore, our evaluation method for fracture density corrected for the neutron self-shielding effect improves response sensitivity and fracture density calculation accuracy.

Anti-tropical cyclone load reduction control of wind turbines based on deep neural network yaw algorithm

Rapid changes in the wind field of tropical cyclones can cause excessive loads and threaten the safety of offshore wind turbines. This paper designs a wind turbine yaw optimization strategy based on the deep neural network to reduce the structural loads of wind turbines caused by tropical cyclones. Firstly, the high-precision tropical cyclone data is used to analyze the characteristics of the wind field. Then, a pseudo-Monte Carlo experiment is designed to compensate for the incompleteness of the observed data. Furthermore, a robust nonlinear coupling model between the wind characteristics and the loads of the wind turbine is constructed by a deep neural network, and the optimal yaw angle is searched in real time based on this model. The simulation results show that the proposed deep neural network model based on pseudo-Monte Carlo scenario generation can robustly calculate the structural loads of wind turbines with a calculation error of less than 8 %. After applying this model to the real-time optimization control loop, the corresponding optimized yaw angle can be obtained according to the operating data of the wind turbine under tropical cyclone conditions so that the structural loads of the wind turbine are reduced. Compared with the no-yaw and traditional yaw strategies, the load suppression effect is 1 %–9 % under different working conditions. The proposed data-driven structural load model and load suppression algorithm will effectively improve the operating safety of wind turbines under tropical cyclone conditions.

Experimental and Numerical Simulation Research on Different Shapes of Flame-Stabilizing Baffles in the Furnace

The use of fully premixed combustion in small gas boilers can improve denitrification efficiency. On the basis of fully premixed combustion, adding flame stabilizers inside the boiler can further reduce production of oxides of nitrogen. Four types of flame-stabilizing baffles were added at a certain position inside the furnace after the fully premixed burner. Experiments were conducted separately on the Noporous baffle, and numerical calculations were performed for 36 operating conditions of the four baffles. The experimental results and numerical calculations indicate that under experimental conditions, NOx emissions were all below 40 mg/m3, and the net heat efficiency of the boiler was above 80%. Under a maximum firing rate, CO emissions are below 20 ppm, and the minimum error between the calculated and experimental values is 2.2%. The calculation error of CO emissions under various working conditions does not exceed 6.8%, indicating that the impact of different-shaped baffles on CO emissions is relatively small. When installing a Nonporous baffle, the error between the experimental and calculated exhaust temperature values under minimum firing rates is 6.6%, the error between the calculated and measured values under middle firing conditions is 2.9%, and the error between the calculated and measured values under maximum firing rate conditions is 3.0%. Among the four different partition conditions, the exhaust temperature of the Nonporous baffle is the lowest. Under the same excess air coefficient, the pressure in the furnace for the middle and maximum firing rate is higher than that of the minimum firing rate, and the experimental values are in good agreement with the calculated values. When installing the Strip baffle, the calculated CO2 emission is the lowest. The experimental results show that the NOx in the flue gas inside the furnace is mainly NO, and the NO content exceeds 75%, reaching a maximum of 85%. The experimental results show that the minimum NOx emission value is 26.9 mg/m3. The error between the measured and calculated NOx values when installing a Nonporous baffle is 20.4%. All of the above indicate that installing a flame-stabilizing baffle at an appropriate position in the furnace can further reduce NOx emissions, and the optimization amplitude is related to the shape of the baffle.

Lateral kinematic properties of offshore pipe piles embedded in saturated soil considering soil plug effect

AbstractThis study establishes a theoretical framework for analyzing the lateral oscillation of marine pipe piles. The additional mass model is introduced herein to consider the inertial fluctuation effect of the soil plug. Analytical mathematical methods are used to determine the complex impedance variation of the pile over a range of frequency effects. An investigation is performed to determine how the presence of soil plugs changes the lateral complex stiffness and natural frequency of pipe piles. Additionally, comparisons of the applicability of the plane strain model and continuous medium model have been conducted to enable the easy use of the theoretical model. The main conclusions can be drawn as (1) if the fluctuation inertia effect of the soil plug is not taken into consideration, the dynamic active length and the dynamic stiffness of the pipe pile will be underestimated; (2) for the soft soil, the plane strain model may give rise to substantial calculation errors attributed to them regardless of the vertical continuity of the soil, nevertheless, the calculation error decreases rapidly with the increase of soil shear modulus and vibration frequency.

Calculation of Porosity and CO2 Content in CO2-Bearing Gas Formations Based on Density and Neutron Logging Forward and Inverse Methods.

When the gas reservoir contains CO2, the logging response tends to be complex. When calculating porosity with neutron and density curves, the accuracy of porosity calculation is reduced due to the uncertainty of fluid parameters, which in turn affects the evaluation of CO2 content. It increases the uncertainty of reserve evaluation. In this paper, a forward modeling model of density logging is established based on the equivalent volume model, and the method of neutron logging is formed by putting forward the nonlinear formula of the reciprocal of the comprehensive deceleration length. The key parameters and their variation rules of neutron logging and density logging forward modeling under different temperature and pressure conditions are obtained by experimental means and Monte Carlo method, respectively. The variation law of the influence of different CO2 content on neutron logging and density logging curves is simulated. The research shows that with the increase of CO2 content, the neutron logging value of gas reservoir decreases, while the density logging value increases, and the greater the porosity of gas reservoir, the more obvious this change trend is. Compared with CH4, CO2 has a more significant impact on the excavation effect of neutron logging. On this basis, combined with the conductivity model of the study area, the porosity and CO2 content of CO2 bearing gas reservoir are solved by the least-square method. The practice shows that the relative error of porosity calculation is within ±4% and the error of CO2 content calculation is within ±10%, which proves the reliability of this method.

Coarse mesh finite difference acceleration of the random ray method

This paper presents the development and evaluation of the Coarse Mesh Finite Difference (CMFD) acceleration method to The Random Ray Method (TRRM). We demonstrate its effectiveness in accelerating the convergence of the fission sources and reducing the real statistical error in neutron transport calculations. TRRM treats the angular variable of the neutron flux stochastically and performs batch sampling of characteristic rays to transform the Method of Characteristics (MOC) into a stochastic process, that is capable of making significant strides in memory efficiency and computational performance for some problems. Despite its advantages, TRRM exhibits a potential challenge with a large number of inactive cycles and inherent inter-cycle correlation much like the Monte Carlo method. To address this, the CMFD acceleration method is explored and demonstrated to dramatically reduce the number of required inactive cycles and diminish inter-cycle correlation. Results from the numerical analysis of a 2D C5G7 core problem indicate that the application of CMFD leads to enhanced convergence, with the integration of a CMFD acceleration step every cycle offering the most substantial reduction in statistical noise and error. The study reveals that applying CMFD with every cycle effectively resolves the issue of needing inactive cycles and significantly lowers the inter-cycle correlation, thereby providing a more accurate estimation of standard deviation for pin power distributions. We conclude that using CMFD not only minimizes the number of inactive cycles of TRRM – much like normal Monte Carlo transport – but also lowers real statistical error effectively. For a targeted maximum standard deviation of 0.1% in the pin power, the addition of CMFD can decrease the number of necessary active cycles by 41% compared to standard TRRM, as demonstrated by the 2D C5G7 benchmark analysis.

Continuous optimization method of micro geometry for unparallel beveloid gears

To enhance the bearing capacity and minimize the loaded transmission error for unparallel beveloid gears, a continuous optimization method of micro geometry is proposed. Considering that the conjugate characteristic of tooth surfaces is destroyed by misalignments and modification, an unload contact analysis model is first developed. This includes a contact tooth sequence determination model and an unloaded transmission error calculation model for multi-tooth contact. To determine contact due to deformation, a potential contact point matching model of non-contact tooth surfaces is introduced. Further, a numerical loaded contact analysis model based on the influence coefficient method for unparallel beveloid gear is developed. For multi-tooth contact of modified tooth surfaces, the transmission error compatibility condition is introduced. Based on the loaded contact model, a continuous optimization model for the comprehensive performance of contact pressures and loaded transmission error within a meshing cycle is established. To improve optimization efficiency, a calculation strategy for continuous optimization is developed. The feasibility of the proposed method is validated using a numerical example.

Investigation on saturated vapor and two-phase refrigerant injection in the rotary compressor for the extreme hot and cold conditions

Vapor injection has been widely applied in the rotary compressor to improve the heating capacity and reduce the discharge temperature in the cold condition. However, under the evaporation temperature below −20 °C or the condensation temperature above 60 °C, the discharge temperature is still relatively high, which limits compressor performance and its continuous operation time. To keep the optimal performance and further reduce discharge temperature, this paper focuses on the two-phase refrigerant injection and proposes a mathematical method to investigate the effect of injection vapor quality on the compressor performance. Based on the proposed method, some performance parameters including cooling capacity, heating capacity, EER(COP), power, discharge mass flow rate and discharge temperature have been calculated and an experiment is conducted to test these performance parameters. The calculation errors between calculated and tested results are within 4% and it indicates that the proposed method is accurate to investigate saturated vapor and two-phase refrigerant injection characteristics. The simulated results show that the use of two-phase refrigerant injection results in the trade of a slight drop in cooling capacity, heating capacity and EER(COP) for a large drop in discharge temperature, which is valuable and meaningful for engineering application under the extreme hot and cold conditions.

Local heat transfer measurements of the fin on the blade crown by infrared thermography

Current research on heat transfer of the labyrinth surface mainly focuses on the whole structure made of the same material, but the heat conduction from the tip to the root will affect the measurement of the heat transfer coefficient. To minimize the influence of heat conduction, copper strips are embedded on the surface of the fin made of bakelite. The inverse heat transfer problem is solved using the temperatures collected by an infrared thermal imager to determine the local convective heat transfer coefficient. The error of the lumped parameter method is smaller compared to the differential solution. Constant heat flux experiments are used to validate the experimental results, and numerical analysis is performed to analyze the heat transfer mechanism. The flow field, the Nu number distribution, and fitting correlations of the fins are obtained. By comparing and analyzing the heat transfer coefficients obtained by the three methods, it is found that the lumped parameter method can eliminate the influence of heat conduction on the surface. Taking the lumped parameter method as a reference, the errors of stable heat flow and numerical calculation were 21 % and 4.7 %, respectively. Due to the influence of the vortex direction, the Nu number distribution along the height of the windward surface of the second fin is different from the others. The Nu number distribution along the x-direction on the top surface of the fin is similar to the tip of the windward surface. Along the flow direction, the average Nu number on the top surface of the first fin is 1.2 times that of the second one.