Algorithm For Numerical Simulation Research Articles

Coil optimization of ultra-deep azimuthal electromagnetic resistivity logging while drilling tool based on numerical simulation

This paper presents a coil optimization method of the ultra-deep azimuthal electromagnetic (EM) resistivity Logging While Drilling (LWD) to obtain the best parameters of the tool for formation boundary detection by theory. First, a rapid numerical simulation algorithm, i.e. the Fast Hankel Transform (FHT) method, is developed to simulate the logging responses of the layered formation. A system of double inclined coils is selected based on the response characteristics and the depth of detection (DOD) from four common coils. Simulation results demonstrated that the optimal coils are perfectly suitable for anisotropic formation. Then, the crucial parameters of the frequency and spacing of the selected coils with a DOD of 30 m are determined using the Picasso diagram. In addition, the influences of the electrical parameter of the drilling collar and resistivity anisotropy of the formation on the response are investigated. The results show that the conductivity of the drilling collar, the thickness and the resistivity anisotropy of the formation all affect the DOD. Finally, formation models with different layers are created to verify the performance and signal intensity. The results demonstrate that the optimized coils not only have a large DOD but also possess a high signal intensity, further confirming the advantages of the preferred coils. Compared with the conventional physical experiment tests, the method of coil optimization proposed in this paper is more economical and efficient. The findings of this study can help better understand the detection characteristics of the different coils, which can provide theoretical support for designing and developing a tool with the best boundary capability.

Optimization investigation on the distribution of both inlets and outlets for the shell of a novel separated structure steam generator

The distribution of both inlets (downcomers for the steam generator) and outlets (risers for the steam generator) for the shell has an important influence on the overall thermal hydraulic performance of a novel separated structure steam generator (SS-SG). Nevertheless, there is no basis for reference in the design process so far. In this article the effect of both the inlets and outlets distribution on the vapor-liquid two-phase flow and heat transfer characteristics was studied and optimized with the help of experiment, numerical simulation and machine learning algorithm. The surrogate model was constructed by the backpropagation neural network based on the genetic algorithm (GA-BPNN). The average boiling heat transfer coefficient (HTC) was selected as the objective function to characterize the rationality of the flow field in the shell. To get the optimal distribution, the global optimization was performed by the genetic algorithm (GA). For the optimal structure obtained, the longitudinal flow was enhanced greatly compared to the original structure. This is beneficial to avoid the local flow stagnation and eliminate the enrichment of ion concentration for long-term operation. Meanwhile, the vapor accumulation at the top of the shell near the front tube-sheet has also been alleviated to some extent. It is beneficial to alleviate the thermal damage of the high heat flux due to heat transfer deterioration. Besides, the average pressure drop was only increased by 0.96%. The results of this investigation are of significance as a reference in the actual design of the novel SS-SG.

Optimization design and drag reduction characteristics of bionic borehole heat exchanger

As a renewable energy source, geothermal energy has drawn attention because it is clean, low-carbon, resource-rich, stable, and sustainable supply. In the mining and operation of a geothermal energy system, there is a certain amount of fluid resistance in the borehole heat exchanger where the fluid flows. As the resistance in the conventional borehole heat exchanger (CBHE) accumulates with the length increase, the pumping power increases, resulting in energy loss and affecting the operation of the entire geothermal system. A bionic borehole heat exchanger (BBHE) is designed using a circular groove as a bionic unit based on the bionic non-smooth surface hypothesis. Its structural characteristics are the circular groove’s depth, width, and slot pitch. Where the fluid faces the least resistance, minimization of the pressure drop was the optimization goal. Based on the outcomes of a CFD numerical simulation and genetic algorithm optimization study. These are the BBHE’s ideal structural parameters: diameter is 60 mm, 66 mm for the groove width, 418 mm for the slot pitch, and 80 mm for the groove depth. Compared to the CBHE, under identical numerical simulation settings, the fluid resistance reduction rate of BBHE can reach 13%. Increasing fluid velocity in the BBHE can increase the temperature transmission rate. The study’s findings can serve as a reliable source of scientific information for the use and management of geothermal energy.

ColESo: Collection of exact solutions for verification of numerical algorithms for simulation of compressible flows

ColESo is a set of subroutines that evaluate particular solutions of the Euler equations, the Navier – Stokes equations, and their linearized versions. These solutions were used by the author for the verification of high-order methods for the compressible flow simulation. It is convenient to use an exact solution when it is available for each point of the computational domain, accurate enough, and quick to evaluate. A solution given by a composition of elementary functions is usually a good choice, but the set of such solutions is too limited. ColESo adds to this set several solutions in integral form and provides their quick calculation with a good accuracy. Program summaryProgram Title: ColESoCPC Library link to program files:https://doi.org/10.17632/z7mypchgfz.1Developer's repository link:https://github.com/bahvalo/ColESoCode Ocean capsule:https://codeocean.com/capsule/0365245Licensing provisions: GPLv2.1Programming language: C++ (C++03 standard)Nature of problem: Verification of high-order methods for the simulation of compressible gas dynamics on curvilinear or unstructured grids.Solution method: Change of variables, Fourier transformation, Gauss–Legendre and Gauss–Jacobi quadrature rules.Additional comments including restrictions and unusual features: ColESo uses several special functions provided by Cephes Math Library and GNU LibQuadMath (for the quadruple precision). To define the Gauss – Jacobi quadrature rules, ColESo uses a code written by S. Elhay, J. Kautsky, J. Burkadrt. These libraries are open-access and distributable with compatible licenses.

Numerical Study of the Ejection Cooling Mechanism of Ventilation for a Marine Gas Turbine Enclosure

Abstract A marine gas turbine enclosure must be designed to prevent overheating of the electrical and engine control components as well as diluting potential fuel leaks. In order to achieve an optimal enclosure design, a numerical study of the ventilation-ejection cooling mechanism of a gas turbine enclosure is carried out in this paper. The evaluation index of the ejection cooling performance is first proposed and the algorithm of numerical simulation is verified. On this basis, orthogonal combinations of structural parameters are carried out for the expansion angle α of the lobed nozzle and the spacing S between the outlet plane of the lobed nozzle and the inlet plane of the mixing tube. The flow and the temperature distribution inside the enclosure are analysed under different operating conditions. The results show that the influence of the lobed nozzle expansion angle α and the spacing S on the performance is not a single-valued function but the two influencing factors are mutually constrained and influenced by each other. For any spacing, the combined coefficient is optimal for the expansion angle α = 30°. When the expansion angle α = 45° and the spacing S = 100 mm, the combined coefficient and the temperature distribution inside the enclosure are optimal at the same time.

A precise internal-stress calculation algorithm for the evolution of cracking risk of the steam-curing box girder

• The refined numerical model considers the temporal-spatial evolutionary difference. • The algorithm is established to reveal the thermal behavior of box girder. • The thermal stress evolution processes are monitored by the field test. • The results of numerical simulation and field tests are compared. • Parametric analysis is performed to investigate the influence of key factors. Thermal cracking caused by the combination of heat liberation and thermal boundaries becomes a more and more serious problem during the entire steam-curing process. To understand the rules of cracking risk and find the key factors determining the distribution of thermal stress, the numerical simulation algorithm is established and the verification field tests are deployed. Firstly, based on the equivalent maturity concept, a refined mathematic model of the thermo–mechanical coupling field is established, which fully considers the temporal-spatial evolutionary difference of material properties and hydration heat release. Secondly, the numerical algorithm is further set up for the evolution law of the thermal stress and cracking risk based on the finite element method. Thirdly, triaxial temperature strains of key points are monitored using Fiber Bragg Grating (FBG) sensors in the field. Effectiveness and accuracy of the model are verified by the agreement between numerical simulation and experimental results. Finally, based on the verified numerical model, parametric analysis is performed to investigate the influence of various key factors affecting the distribution law of the thermal stress field and the evolution law of the cracking risk. The results show that the curing temperature ( T h ) and parameters of the hydration exothermic model ( θ u and m ) are crucial to influencing the thermal behavior of the steam-curing box girder. The research provides a refined numerical algorithm of the thermo-mechanical coupling field and contributes to the high quality of huge box-girder during the entire steam-curing process.

Well control optimization in waterflooding using genetic algorithm coupled with Artificial Neural Networks

Optimum well controls to maximize net present value (NPV) in a waterflooding operation are often obtained from an iterative process of employing numerical reservoir simulation and optimization algorithms. It is often challenging to implement gradient-based optimization algorithms because of the large number of variables and the complexities to embed the optimization algorithm in the simulator solving workflow. Approaches based on repeated model evaluation are easier to implement but are often time-consuming and computationally expensive.

Forecast of convective events via hybrid model: WRF and machine learning algorithms

This presents a novel hybrid 24-h forecasting model of convective weather events based on numerical simulation and machine learning algorithms. To characterize the convective events, 13-year from 2008 up to 2020 of precipitation data from the main airport stations in Rio de Janeiro, Brazil, and atmospheric discharges from the surrounding area of around 150 km are investigated. The Weather Research and Forecasting (WRF) model was used to numerically simulate atmospheric conditions for every day in February, as it is the month with the greatest daily rate of atmospheric discharge for the data period. The p-value hypothesis test (with α=0.05) was applied to each grid point of the numerically predicted variables (defined as an independent attribute) to find those most associated with convective events using the output of the 3-D WRF grid. This one identified 36 attributes (or predictors) that were used as input in the machine learning algorithms' training-test process in this study. Several cross-validation training and testing experiments were carried out using the nine-selected categorical machine learning algorithms and the 36 defined predictors. After applying the boosting technique to the nine previously trained-tested algorithms, the results of the 24-h predictions of convective occurrences were deemed satisfactory. The RandomForest method produced the best results, with statistics values close to perfection, such as POD = 1.00, FAR = 0.02, and CSI = 0.98. The 24-h hindcast utilizing the nine algorithms for the 28 days of February 2019 was very encouraging because it was able to almost recreate the maturation phase of events and their eventual failures were noted during the formation and dissipation phases. The best and worst 24-h hindcast had POD = 0.97 and 0.88, FAR = 0.02 and 0.12, and CSI = 0.94 and 0.78, respectively.

Analysis of International Trade Competitiveness of Small Commodities Based on Numerical Simulation Algorithm

In order to improve the analysis effect of the international trade competitiveness of small commodities, this study combines the digital simulation algorithm to analyze the competitiveness of international trade of small commodities and builds a competitiveness analysis model. Furthermore, this study summarizes several main factors that affect energy resolution, presents methods to provide energy resolution, and discusses methods for reducing noise from both analog and digital perspectives. In addition, this study gives the design principle and implementation method of the FIR digital filter, which provides theoretical support for digital signal processing design. Through the data analysis, it can be seen that the analysis model of the international trade competitiveness of small commodities based on the numerical simulation algorithm proposed in this study has a good performance in the analysis of the competitiveness of international trade of small commodities.

Dynamic Stability and Responses of Beams on Elastic Foundations Under a Parametric Load

This paper is concerned with numerical simulation of both dynamic stability and responses of beams on elastic foundations under a pulsating axial parametric load in a single matrix method. First, the equation of motion of a beam on an elastic foundation with damping is derived and decoupled into a Mathieu–Hill equation. Three different elastic foundations are considered and compared: Winkler, Pasternak, and Hetenyi models. Then a novel numerical simulation algorithm is proposed to investigate both the dynamic stability and the responses of the beam simultaneously. Accurate instability diagrams are obtained by the numerical simulation and are substantiated by vibration response curves obtained from the same method. These numerically accurate diagrams are used to calibrate the approximate instability boundaries of various orders of Hill infinite determinants from the classical Bolotin method for the first time. A detailed discussion is presented on effects of various aspects including elastic foundation models, damping, and static and dynamic loads. The results provide insights into the efficient and safe application of beams on elastic foundations in engineering. The proposed numerical method can be extended to analyze dynamic stability and vibrations of systems under arbitrary parametric excitations where Mathieu–Hill equations are involved.

Ventilated cavity flows behind a backward facing step with a combination computational fluid dynamics and Error Back Propagation algorithm

Ventilated cavity flow is of a great practical interest for the features that may reduce the drag around the area near the cavity. The present paper demonstrates the prediction of ventilated cavity flows on the backward facing step, which establishes the prediction model of drag reduction by the numerical simulation and artificial intelligence algorithm. The results of the computational fluid dynamics are compared with available experimental data to validate the precision, which shows good agreement. This paper numerically analyzes the influence of the number, location and part ventilation volume of injectors on the drag reduction of ventilated cavity flows. With the same air-entrant coefficient, the number and location of injectors both have a significant impact on drag reduction performance. And the part ventilation volume of the injectors may also have a limited impact. Accordingly, the prediction model of drag reduction is established by the Error Back Propagation algorithm (BP algorithm) that has accurate algorithms and fast calculation to save time and computing resources. Meanwhile, the results indicate that BP algorithm can reasonably predict the performance of ventilated cavity flows, which means the model can optimize the drag reduction on ventilated cavity flows and it can be useful in engineering.

Sporadic micro-meteoroid source radiant distribution inferred from the Arecibo 430 MHz radar observations

ABSTRACT This work presents the result of sporadic meteor radiant density distribution using the Arecibo 430 MHz incoherent scatter radar (ISR) located in Puerto Rico for the first time. Although numerous meteor studies have been carried out using the Arecibo ISR, meteoroid radiant density distribution has remained a mystery as the Arecibo radar cannot measure vector velocity. A numerical orbital simulation algorithm using dynamic programming and stochastic gradient descent is designed to solve the sporadic meteoroid radiant density and the corresponding speed distributions of the meteors observed at Arecibo. The data set for the algorithm comprises over 250 000 meteors from Arecibo observations between 2009 and 2017. Five of the six recognized sporadic meteor sources can be identified from our result. There is no clearly identifiable South Apex source. Instead, there is a broad distribution between +/−30° ecliptic latitude, with the peak density located in the North Apex direction. Our results also indicate that the Arecibo radar is not sensitive to meteors travelling straight into or perpendicular to the antenna beam but is most sensitive to meteors with an arrival angle between 30° and 60°. Our analysis indicates that about 75 per cent of meteoroids observed by the Arecibo radar travel in prograde orbits when the impact probability is considered. Most of the retrograde meteoroids travel in inclined low-eccentricity orbits.

Determination of Landslide Displacement Warning Thresholds by Applying DBA-LSTM and Numerical Simulation Algorithms

Numerical simulation has emerged as a powerful technique for landslide failure mechanism analysis and accurate stability assessment. However, due to the bias of simplified numerical models and the uncertainty of geomechanical parameters, simulation results often differ greatly from the actual situation. Therefore, in order to ensure the accuracy and rationality of numerical simulation results, and to improve landslide hazard warning capability, techniques and methods such as displacement back-analysis, machine learning, and numerical simulation are combined to create a novel landslide warning method based on DBA-LSTM (displacement back-analysis based on long short-term memory networks), and a numerical simulation algorithm is proposed, i.e., the DBA-LSTM algorithm is used to invert the equivalent physical and mechanical parameters of the numerical model, and the modified numerical model is used for stability analysis and failure simulation. Taking the Shangtan landslide as an example, the deformation mechanism of the landslide was analyzed based on the field monitoring data, and subsequently, the superiority of the DBA-LSTM algorithm was verified by comparing it with DBA-BPNN (displacement back-analysis based on back-propagation neural network); finally, the stability of the landslide was analyzed and evaluated a posteriori using the warning threshold calculated by the proposed method. The analytical results show that the displacement back-analysis based on the machine learning (DBA-ML) algorithm can achieve more than 95% accuracy, and the deep learning algorithm exemplified by LSTM had higher accuracy compared to the classical BPNN algorithm, meaning that it can be used to further improve the existing intelligent inversion theory and method. The proposed method calculates the landslide’s factor of safety (FOS) before the accelerated deformation to be 1.38 and predicts that the landslide is in a metastable state after accelerated deformation rather than in failure. Compared to traditional empirical warning models, our method can avoid false warnings and can provide a new reference for research on landslide hazard warnings.

Matérn process-based simulation of wind speed time series

This work proposes a practical methodological framework for simulating long-term discrete wind speed time series, for applications to renewable energy systems. The framework is based on the Matérn stochastic process, that is used to identify and extract the short and long-term periodic components present in the mean and variance of a wind speed time series, and to characterize the residual random component. The procedure of construction of synthetic wind speed time series is developed, rooted in a fast numerical simulation algorithm for the Matérn process. We empirically validate the usefulness of the proposed framework by numerical experiments based on three real historical wind speed datasets. The results show consistent statistical similarities between the historical and simulated wind speed time series of data.

Optimization of Numerical Simulation Algorithm for Spontaneous Combustion in Goaf via a Compression Storage and Solution Method of Coefficient Matrix

In coal mine engineering, numerical software is used to analyze the behavior of coal rock damage and fluid migration. The order of the coefficient matrix used in numerical calculations is increasing, and this increases the computation steps in obtaining the coefficient matrix solution. The storage and solution of the coefficient matrix are key factors influencing the efficiency of the numerical software. Therefore, to save storage space and reduce the computation steps, the coefficient matrix must be effectively compressed and stored. In this work, the structural characteristics of different coefficient matrices are analyzed in detail, and we find that for different computational regions, as long as the nodes are numbered according to certain rules, the corresponding coefficient matrices will have similar structural characteristics. The nonzero elements are symmetrically distributed in the diagonal band, and all the elements on both sides outside the band are zero. Based on this, the coefficient matrix is compressed by a pivoting scheme, and the compressed matrix is directly eliminated by dislocation Gaussian elimination. Thus, a compressed storage method that integrates the compression and solution of the coefficient matrix is established. The compressed storage and calculation module is incorporated into our self-developed simulation software COMBUSS-3D to simulate the evolution of the temperature field in the goaf of Luling Coal Mine. Compared with the conventional method, the compressed storage module can significantly improve the computing rate of the simulation, by approximately 80%.

Two-dimensional numerical simulation of spontaneous potential logging data with account to clay content of a reservoir by finite element method

Spontaneous polarization potential (SP) logging remains one of the most widely used geophysical methods of borehole investigation. However, for a long time its interpretation was based on empirical dependences and analytical solutions in simplified formulations. At present the development of the method is associated with the development of new approaches to numerical modeling and quantitative interpretation of SP logging data. Application of numerical algorithms makes it possible to considerably increase information content and resolution of SP method. Nevertheless, most of the currently proposed approaches rely on a simplified description of SP signal formation, which may lead to errors in data interpretation for complex reservoir intervals. In this work, we propose an algorithm for numerical simulation of SP logging data as applied to the study of clayed fluid-saturated reservoirs. The physical and mathematical model of SP signal formation in terms of coupled fluxes for the case of electrochemical SP source is considered. The software realization of the algorithm includes a two-dimensional numerical simulation of SP signals based on the application of the finite element method in the axially symmetric model of the geological medium. The character of SP signals for reservoirs of different thickness at four values of the reservoir water saturation coefficient is studied, as well as the dependence of the shape and amplitude of the SP anomaly in a water- and oil-saturated clayed reservoir on the content and type of clay mineral. The obtained results, aimed at the development of the SP method, improve the quality of SP diagrams interpretation for the study of clayed reservoirs.

Numerical study of the porosity-permeability evolution due to chmically-active fluid injection

The paper presents a numerical algorithm for simulation of the reactive transport at the pore scale. The algorithm allows simulating pore space evolution, porosity, absolute permeability, and form factor changes due to core matrix dissolution or precipitation. We also, introduce the topological measure; the persistence diagrams of independent cycles in pore space to classify different dissolution scenarios. Using derived classification, we constructed the statistically reliable porosity-permeability relations for different dissolution scenarios.

Film thickness dependency and refractive index sensing capabilities of lossy mode resonances in metallic indium-rich ITO thin films

Film thickness plays a crucial role in determining the position and depth of lossy mode resonance (LMR). Herein, we explore the overall film thickness dependency of LMR properties of pulsed-laser-deposited metallic indium-rich indium tin oxide (ITO) thin films by employing a simple Kretschmann–Raether geometry. It is observed that the depth of LMR is increased monotonically with increasing film thickness. Extremely high attenuation values of − 20 d B for transverse electric and − 10 d B for transverse magnetic polarizations are achieved for the film with the greatest film thickness. Also, the LMR positions are considerably redshifted with increasing thickness. A numerical simulation algorithm based on the modified transfer matrix method, where surface roughness is taken into account with the application of anisotropic Bruggemann effective medium approximation, is used to simulate the experimental LMR spectra for all vacuum-deposited ITO thin films effectively. As an application of this study, refractive index (RI) sensing is demonstrated in the RI range of 1.3325–1.4459, and highest sensitivity values of 3840 nm/RIU and 2542 nm/RIU are accomplished for transverse electric and transverse magnetic polarizations, respectively. This study will help in attaining a deep level of understanding of the film thickness effect on thin film based LMR and elevate metallic indium-rich ITO as an excellent material template for LMR studies.

The design of an open-source carbonate reservoir model

This work presents a new open-source carbonate reservoir case study, the COSTA model, that uniquely considers significant uncertainties inherent to carbonate reservoirs, providing a far more challenging and realistic benchmarking test for a range of geo-energy applications. The COSTA field is large, with many wells and large associated volumes. The dataset embeds many interacting geological and petrophysical uncertainties in an ensemble of model concepts with realistic geological and model complexity levels and varying production profiles. The resulting number of different models and long run times creates a more demanding computational challenge than current benchmarking models. The COSTA model takes inspiration from the shelf-to-basin geological setting of the Upper Kharaib Member (Early Cretaceous), one of the most prolific aggradational parasequence carbonate formations sets in the world. The dataset is based on 43 wells and the corresponding fully anonymised data from the northeastern part of the Rub Al Khali basin, a sub-basin of the wider Arabian Basin. Our model encapsulates the large-scale geological setting and reservoir heterogeneities found across the shelf-to-basin profile, into one single model, for geological modelling and reservoir simulation studies. The result of this research is a semi-synthetic but geologically realistic suite of carbonate reservoir models that capture a wide range of geological, petrophysical, and geomodelling uncertainties and that can be history-matched against an undisclosed, synthetic ‘truth case’. The models and dataset are made available as open-source to analyse several issues related to testing new numerical algorithms for geological modelling, uncertainty quantification, reservoir simulation, history matching, optimization and machine learning. Supplementary material: supplementary data associated with this article can be found in the data repository for the COSTA model available at https://doi.org/10.17861/6e36e28d-50d9-4e31-9790-18db4bce6e5d and supplementary material is available at https://doi.org/10.6084/m9.figshare.c.5823571

Multiscale analysis of tunnel surrounding rock disturbance: A PFC3D-FLAC3D coupling algorithm with the overlapping domain method

Under the condition of high in-situ stress, the instantaneous excavation disturbs surrounding rocks, which shows different internal mechanisms on the different scales. At present, there still lacks numerical simulation algorithms for multiscale analysis in this field. A PFC3D-FLAC3D coupling algorithm with the overlapping domain method (ODM) was proposed. ODM can optimize the problem of energy reflection between different coupling domains and improve the accuracy of calculation. ODM was verified to a certain extent, including the velocity transmission and the mechanical deformation of models. In addition, the coupling algorithm with ODM was applied to the tunnel excavation under the assumption of the Kastner formula and the Songhua–Changchun diversion tunnel in China. In the tunnel excavation simulation, the simulation results showed that the coupling algorithm can characterize the stress distribution of surrounding rocks on the macro-scale, and reveal the phenomena of crack initiation propagation and large deformation on the micro-scale. By comparing with the empirical formula and the engineering data, it can be found that the coupling algorithm accurately and effectively realized the multiscale simulation of rocks disturbance. This research have some reference value for the multiscale investigation, which is the disturbance of surrounding rock caused by tunnelling.