Traditional Simulation Methods Research Articles

CFD simulation of the pump trip runaway transient process of a pumped-storage power plant with head 700 m

Simulating transient processes of pumped-storage power plants is essential for the design and optimization of pump-turbine and water conveyance system. Because pressure pulsations and runner forces cannot be obtained from the traditional 1D transient simulation methods, 3D CFD simulations are necessary. In this study, the fast runaway transient process, occurring after the pump trip of a pumped-storage plant with a head of 700m, was simulated by using the CFD method that couples the 1D water conveyance system and 3D turbine. The phenomena, composed of water hammer fluctuations, pressure pulsation transitions, and flow pattern evolutions, were described and analyzed. We found that the flow patterns and pressure pulsations change violently as the working point goes through different regions. Especially, the pressure pulsations and unbalanced radial runner forces are the most severe in the S-shaped characteristic region. The strong impact on blades, large scale recirculating vortices in blade passages, obvious rotating stalls in vane and blade regions, transitional backflows at runner inlet and outlet, and strong circumferential velocity in vaneless space are the main sources. The dynamic working trajectory does not follow the measured static characteristic curve and demonstrates an undamped loop in the S-shaped region. This paper provides some evidence on the relations between flow structure and pressure pulsation features, although the mechanism of dynamic characteristics needs further investigations.

Совершенствование швартовных испытаний главного двигателя, работающего на винт фиксированного шага

The most important stage in vessel’s construction is acceptance tests. By testing the main power plant of the vessel the design solutions adopted to ensure stable operation of the main engine and the propeller are checked. Such a check of the main engine according to design characteristics at the quay wall can significantly reduce sea trials cost. In practice, the peculiarities of the propeller operation at zero free-flow velocity at the quay wall limit the operating modes of the main power plant and the possibilities of mooring tests. There are considered the traditional and innovative simulation methods and tools used in mooring tests. The methods allow unloading the engine in terms of torque bringing its operation mode closer to the design parameters. An urgent scientific and technical problem has been solved to reduce the mechanical stress of the main engine, which operates according to the mooring characteristic on a fixed pitch propeller. The factors influencing the value of the resistance moment of the propeller at a zero vector of the incident flow are determined. Possible directions for improving the acceptance tests of the main power plant by supplying an additional environment, i.e. air to the suction surface of the propeller blade, are substantiated. In the complex of computational fluid dynamics, a computational model of a fixed pitch propeller has been created. The amount of air required to change the propeller operating mode has been estimated. Resistance moment of the propeller for various methods of air supply to the propeller has been analyzed. Additional means of controlling the main engine operating mode at the stages of the ship's life cycle are proposed.

Identifying and mitigating systematic biases in fish habitat simulation modeling: Implications for estimating minimum instream flows

AbstractHabitat simulation approaches (e.g., PHABSIM) have been used to model instream flows in thousands of streams and rivers and remain the most widely implemented detailed instream flow methodology. However, recent studies suggest that conventional habitat simulation models incorporate assumptions that may systematically underestimate instream flow needs, particularly for drift‐feeding fish. These include: (i) systematic biases in velocity habitat suitability curves (HSCs) caused by territoriality where dominant individuals displace subordinate fish to lower velocity micro‐habitats at high densities, thereby inflating the fitness value of low velocities; (ii) habitat simulation models do not account for flow effects on prey flux to drift‐feeding fishes, which may decrease more rapidly with reduced flow than does available habitat; (iii) use of focal velocities to construct traditional HSCs, which systematically underestimates velocity preference within the broader foraging arena of a drift‐feeding fish, and (iv) inadvertent use of low‐velocity HSCs associated with daytime refuging behavior from predators that may underestimate the higher velocities necessary for crepuscular foraging. Collectively, these factors suggest that current and historic flow prescriptions using traditional habitat simulation methods may underestimate optimal rearing flows for salmonids and other drift‐feeding species by anywhere from 10 to 50%. This implies that traditional instream flow management may be failing to provide the intended level of protection for drift‐feeding fishes in multiple streams at landscape scales. We provide guidelines for identifying contexts where model predictions are likely to be biased and approaches for correcting them.

Prediction of coalbed methane production based on deep learning

Coalbed methane (CBM) is a clean energy source. The prediction of CBM production is a critical step during CBM exploitation and utilization, especially for geological well selection, engineering decision making, and production management. In past attempts, CBM production prediction methods have been limited to numerical simulation and shallow neural network. Compared with numerical simulation and shallow neural network methods, deep learning has a significant advantage in its ability to process big data with multiple sources and heterogeneity. Therefore, we developed a new method of CBM production prediction based on deep learning theory. The main novelties of this method are as follows. (1) A new feature extraction method for multiscale data sources is proposed by combining convolutional autoencoder and spatial pyramid pooling. (2) The CBM production prediction model based on deep learning is established by combining the affinity propagation (AP) algorithm and the long short-term memory (LSTM) network. Application and verification show that the accuracy of our new method is higher than that of the traditional numerical simulation and shallow neural network methods.

A novel incremental simulation of facial changes following orthognathic surgery using FEM with realistic lip sliding effect.

Accurate prediction of facial soft-tissue changes following orthognathic surgery is crucial for surgical outcome improvement. We developed a novel incremental simulation approach using finite element method (FEM) with a realistic lip sliding effect to improve the prediction accuracy in the lip region. First, a lip-detailed mesh is generated based on accurately digitized lip surface points. Second, an improved facial soft-tissue change simulation method is developed by applying a lip sliding effect along with the mucosa sliding effect. Finally, the orthognathic surgery initiated soft-tissue change is simulated incrementally to facilitate a natural transition of the facial change and improve the effectiveness of the sliding effects. Our method was quantitatively validated using 35 retrospective clinical data sets by comparing it to the traditional FEM simulation method and the FEM simulation method with mucosa sliding effect only. The surface deviation error of our method showed significant improvement in the upper and lower lips over the other two prior methods. In addition, the evaluation results using our lip-shape analysis, which reflects clinician's qualitative evaluation, also proved significant improvement of the lip prediction accuracy of our method for the lower lip and both upper and lower lips as a whole compared to the other two methods. In conclusion, the prediction accuracy in the clinically critical region, i.e., the lips, significantly improved after applying incremental simulation with realistic lip sliding effect compared with the FEM simulation methods without the lip sliding effect.

Design of an algorithm for an adaptive Value at Risk measurement through the implementation of robust methods in relation to asset cross-correlation

This study proposes an algorithmic approach for selecting among different Value at Risk (VaR) estimation methods. The proposed metaheuristic, denominated as “Commitment Machine” (CM), has a strong focus on assets cross-correlation and allows to measure adaptively the VaR, dynamically evaluating which is the most performing method through the minimization of a loss function. The CM algorithm compares five different VaR estimation techniques: the traditional historical simulation method, the filtered historical simulation (FHS) method, the Monte Carlo method with correlated assets, the Monte Carlo method with correlated assets which uses a GARCH model to simulate asset volatility and a Bayesian Vector autoregressive model. The heterogeneity of the compared methodologies and the proposed dynamic selection criteria allow us to be confident in the goodness of the estimated risk measure. The CM approach is able to consider the correlations between portfolio assets and the non-stationarity of the analysed time-series in the different models. The paper describes the techniques adopted by the CM, the logic behind model selection and it provides a market application case of the proposed metaheuristic, by simulating an equally weighted multi-asset portfolio.

Numerical modeling and experimental cross-validation of a solar thermal collector through an innovative hybrid CFD model

Heat pipe evacuated tube solar collectors are widely used in solar water heating systems. Due to the complex heat transfer processes taking place in the collector, performing direct numerical simulations will be computationally intensive. Hence, this study presents a novel hybrid computational method in order to simulate the collectors’ thermal behaviour during day/night time operation. This method is comprised of a previously developed resistance network based proper orthogonal decomposition method for simulation during operation hours where solar irradiation values are greater than zero. Afterwards, when irradiance is zero a Lattice Boltzmann method has been utilized for simulation. The novelties of this proposed method include reducing simulation time, accounting for the ambient working conditions of the collector and therefore, providing an accurate assessment of the temperature distribution inside the collector during the entirety of its operation in a full working cycle. Furthermore, the results obtained for full cycle operation have been compared to existing experimental data and it was found that the results were in good agreement, with an average error of 5.16%. Also it has been shown that the hybrid model is several orders of magnitude faster than traditional direct numerical simulation methods.

Numerical simulation of the drag and heat-transfer characteristics around and through a porous particle based on the lattice Boltzmann method

Porous particle flow is universal in nature and industry. However, in previous numerical simulations, porous particles have usually been assumed to be solid. It is necessary to study the flow and heat-transfer characteristics around porous particles because they are greatly different from those of impermeable particles. In this study, two-dimensional steady flow and heat transfer around and through a porous particle with a constant temperature placed in a cold fluid were numerically investigated. The effects of the Reynolds number (Re) and Darcy number (Da) on the flow and heat-transfer characteristics were investigated in detail. The investigated ranges of the parameters were 10≤Re≤40 and 10−6≤Da≤10−2. It is sophisticated to simulate porous particles with traditional simulation methods because of their complicated structure. Therefore, the lattice Boltzmann method was used to solve the generalized macroscopic governing equations because of its simplicity. The drag coefficient decreased with increasing Re or Da, but the decrease was not prominent in the range 10−6≤Da≤10−4. The heat-transfer efficiency of the front surface was much stronger than that of the rear surface. The heat-transfer efficiency between the particle and the fluid increased with increasing Re or Da. However, for 10−6≤Da≤10−4, the increase was not prominent and the heat-transfer enhancement ratio was slightly larger than one. Furthermore, the effect of Da became more prominent at larger Re. In addition, new correlations for the drag coefficient and surface-averaged Nusselt number were obtained based on the simulated results.

Multivariate geostatistical simulation with PPMT: an application for uncertainty measurement

ABSTRACT Grade models built by traditional estimation or simulation methods often fail to reproduce the complex relationships between the variables. This work investigates the use of the multivariate transformation called Projection Pursuit Multivariate Transform (PPMT), which fully decorrelates the multiple variables of interest, allowing the independent conditional simulation of each variable in the transformed space. Finally, the simulated variables are back-transformed, reproducing the initial correlations of the data. The PPMT workflow was applied to a nickel laterite deposit considering five variables: nickel, iron, silica, magnesium, and calcium grades. Conditional simulations of each variable were run and validated. The back-transformed realisations reproduced the multivariate relationships of the data. To calculate the uncertainties, mining panels equivalent to two and four weeks of production were generated using the k-means clustering technique. Uncertainties were summarised by the coefficient of variation (CV) and the results were used to define classes of mineral resources.

Simulation of a Mobile IoT System Using the DEVS Formalism

This paper proposes two novel methods to model and simulate a mobile Internet of Things (IoT) system using the discrete event system specification (DEVS) formalism. In traditional simulation methods, it is advantageous to partition the simulation area hierarchically to reduce simulation time; however, in this case, the structure of the model may change as the IoT nodes to be modeled move. The proposed methods reduce the simulation time while maintaining the model structure, even when the IoT nodes move. To evaluate the performance of the proposed methods, a prototype mobile IoT system was modeled and simulated. The simulation results show that the proposed methods achieve good performance, even if the number of IoT nodes or the movement of IoT nodes increases.

Application and Benchmarking of a Novel Coupled Methodology for Simulating the Thermomechanical Evolution of Sodium-cooled Fast Reactors Fuel Subassemblies

We employ a novel methodology to simulate the irradiation of Sodium cooled Fast Reactors (SFR) subassemblies. The proposed approach allows considering the coupling between key thermal–hydraulic and thermomechanical phenomena, which is usually neglected in traditional simulation methods. Comparisons between results obtained from coupled and uncoupled methodologies show that the latter can significantly over predict the stresses and the strains of highly irradiated fuel bundles. Additionally, we explore different options for the pin mechanical modeling. In particular, we show that a relatively simple beam-based finite element model for the fuel pins can be used to efficiently compute swelling and irradiation creep strains averaged over the cross section of the fuel claddings. However, if a prediction of the cladding swelling gradients is needed, the beam model must be replaced by a more computationally expensive 3D fuel pin model. An efficient method to estimate the fuel cladding temperature evolution based on a limited number of Computational Fluid Dynamics (CFD) simulations is also presented in this work, and its performance is evaluated. Finally, a numerical benchmark against the state-of-the-art coupled code system for the simulation of SFR subassemblies is presented. This benchmark shows that the proposed coupled methodology allows obtaining results that are in good agreement with the reference methodology. However, two clear advantages of the proposed methodology were identified. Firstly, the use of detailed CFD simulations in our methodology, compared to the lower resolution thermal-hydraulic model employed in the state-of-the-art approach. Secondly, considering the reduction of the coolant mass flow rate caused by the fuel bundle deformation, neglected in the pre-existing approach, which is shown in this work to have a potentially large impact on the coolant temperature distribution.

Simulation with Fuzzy Durations

Traditional stochastic discrete event simulation method requires the users to fit the task duration data with an empirical probability function or a theoretical probability density function. This has limited the application of discrete event simulation techniques from research stage to construction practice due to the tedious data fitting tasks required for the construction operation planners lacking of statistical background. On the other hand, usually the activity duration estimated by practitioners contains some kind of vagueness caused by estimator's subjective judgment. This type of vagueness may be more appropriate to be modeled by fuzzy numbers that can be assessed without data fitting. This paper proposes a new mechanism where fuzzy duration modeled by fuzzy numbers can be used in discrete event simulation. Consequently, the tedious data fitting tasks are eliminated but the uncertainty of task duration is still taken into account.

A Direct Bounded Control Method for Transient Stability Assessment

Abstract The paper proposes a direct method for transient stability assessment, which is more efficient than traditional time-domain simulation methods. To achieve this objective, a new bounded control law for the model of a power system is designed. This yields superior closed-loop transient performances when compared to those achievable with traditional automatic voltage regulators and power system stabilizers. The designed control law allows defining an energy-based Lyapunov function which is instrumental in assessing transient stability properties of the post-fault system. A case study on a single machine infinite bus power system model is presented to illustrate the merits of the proposed method.

A Wave Digital Newton-Raphson Method for Virtual Analog Modeling of Audio Circuits with Multiple One-Port Nonlinearities

The digital implementation of a nonlinear audio circuit often employs the Newton-Raphson (NR) method for solving the corresponding system of implicit ordinary differential equations in the discrete-time domain. Although its quadratic convergence speed makes NR attractive for real-time audio applications, quadratic convergence is not always guaranteed, since it depends on initial conditions, and also divergence might occur. For this reason, especially in the context of Virtual Analog modeling, techniques for increasing the robustness of NR are in order. Among the various approaches, the Wave Digital (WD) formalism recently showed potential to rethink traditional circuit simulation methods. In this manuscript, we discuss an original formulation of the NR method in the WD domain for the solution of audio circuits with multiple one-port nonlinearities. We provide an in-depth theoretical analysis of the proposed iterative method and we show how its quadratic convergence strongly depends on the free parameters (called port resistances) introduced when modeling the reference circuit in the WD domain. In particular, we demonstrate that the size of the basin where the WD NR solver can be initialized to converge on a solution with quadratic speed is a function of the free parameters. We also show that by setting each port resistance value as close as possible to the derivative w.r.t. current of the nonlinear element v-i characteristic we keep the basin size large. We finally implement an audio ring modulator circuit with four diodes in order to test the proposed iterative method.

A new bivariate Archimedean copula with application to the evaluation of VaR

Abstract In this paper, a new generator function is proposed and based on this function a new Archimedean copula is introduced. The new Archimedean copula along with three representatives of Archimedean copula family which are Clayton, Gumbel and Frank copulas are considered as models for the dependence structure between the returns of two stocks. These copula models are used to simulate daily log-returns based on Monte Carlo (MC) method for calculating value at risk (VaR) of the financial portfolio which consists of two market indices, Ford and General Motor Company. The results are compared with the traditional MC simulation method with the bivariate normal assumption as a model of the returns. Based on the backtesting results, describing the dependence structure between the returns by the proposed Archimedean copula provides more reliable results over the considered models in calculating VaR of the studied portfolio.

Influence of turbulence integral length scale on aerostatic coefficients of bridge sections

This study investigates the influence of turbulence on the aerostatic coefficients of typical bridges by obtaining force measurements via the simulation of turbulence in wind tunnels. The traditional simulation method for turbulence based on spires and grilles cannot be employed for the accurate simulation of the large integral scale of turbulence in an actual wind field. Thus, in this study, the turbulence integral length scale was effectively increased using an active control grid. The wind fields of different turbulence integral scales were generated by controlling the vibration frequency of the active control grid. The aerostatic coefficients of five typical bridge sections (single-box girder, twin-box girder, truss girder, edge girder, and edge-box girder) were measured under turbulent and uniform flow. The test results were compared and analyzed, which revealed that the drag coefficients increased in accordance with a decrease in the reduced turbulence integral length scale, and they were lower under turbulent flow than under uniform flow.

Prediction Method of Three‐Dimensional Crack Propagation Path Based on Deep Learning Application

In engineering, most structural components suffer from local damage in service or fabrication. Under different loading conditions, such local damage will further expand to large cracks and structural collapse. For ensuring longevity and reliability, the study of brittle crack growth is important. In structural damage prediction, various methodologies are commonly used and have demonstrated success in the past. Most traditional simulation methods, however, have the problems of large calculation quantities and long calculation times. At the same time, the mutual influence of crack opening stress and crack image on crack widening is rarely considered in existing works based on the deep learning framework. Herein, a deep learning model is developed to predict the spread of fracture of brittle materials under stress to improve the aforementioned problems. By developing a nonlinear relationship between crack stress and damage effects, this approach predicts crack growth, thus avoiding the loss of required information on crack growth behavior. The model emphasizes repeatability and extensibility, which is verified using extended finite element method (XFEM) Abaqus software through multiple sets of material crack data generated. This model's potential applications are material design and evaluation of residual life.

Simulation of a Synchronous Planar Magnetically Levitated Motion System Based on a Real-Time Analytical Force Model

The existing simulation method for the control of linear or planar magnetically levitated actuators always ignores the characteristics of the real physical object, which deteriorates the accuracy of the simulation. In this work, the proposed emulator for the magnetically levitated actuator is developed to consider both the force characteristics and the control algorithm. To model the real controlled object, the mathematical model for 1D (one-dimensional) and 2D (two-dimensional) magnetic arrays is derived where the yaw angle is taken into consideration using the coordinate transformation. The solution of the mathematical model is compared with the commercial BEM (boundary element method) software and the measurements from a force and torque testing setup to highlight the accuracy of the proposed mathematical model. Compared with the traditional simulation method of the motion control systems founded on the simplified system transfer function, the proposed simulation method has higher consistency and is closer to reality. The accuracy and efficiency of the proposed magnetic force model are further verified by the emulator based on the numerical force model and the testing data of the real setup.

An accelerated conservative sharp-interface method for multiphase flows simulations

In this paper, we develop an accelerated conservative sharp-interface method for multiphase flows simulations. Traditional multiphase simulation methods use the minimum time step of all fluids obtained according to the CFL conditions to evolve the fluid states, which limits the computational efficiency, as the sound speed of one fluid may be much larger than of others. To address this issue, based on the original conservative sharp-interface methods, the present method is proposed by solving the governing equations of each individual fluid with the corresponding time step. Without violating the numerical stability requirement, the states of one fluid containing larger time-scale features will be evolved with a larger time step. The interaction step between two fluids is solved for synchronization, which is handled by interpolating the intermediate states of the fluid with larger time steps. In addition, an interfacial flux correction is applied to maintain the conservative property. The present algorithm has be coupled with a wavelet-based adaptive multi-resolution (MR) algorithm to achieve additional computational efficiency. A number of numerical tests indicate that the accuracy of the results obtained by the present method is comparable to of the original costly method, with a significant speedup. The speedup increases with the dimensions and resolution, which indicates its applications in 3D high resolution simulations of multiphase flows.

An improved method for analyzing shear-lag in thin-walled girders with rectangular ribs

Because the traditional bar simulation method (BSM) cannot directly analyze the shear lag effect of thin-walled steel box girders with rectangular ribs on their top and bottom plates, this paper presents a new method to derive equivalent bar areas and governing differential equations to assess the shear lag effect. On the basis of this, an improved bar simulation method (I-BSM) is proposed for shear lag analysis. In addition, the paper analyzes the influence on the shear lag effect of the thickness of the top and bottom plates, the thickness of the rectangular ribs, and the height of the girder's cross-section. The results show that an increase in the thickness of the top and bottom plates will increase the shear lag effect of the top plate, but decrease the shear lag effect of the bottom plate. The thickness of the rectangular ribs, however, has little effect on the shear lag effect. An increase in the height of the cross-section will reduce the shear lag effect of the top plate and increase the shear lag effect of the bottom plate. In future, it is recommended to change the height of the cross-section and thickness of the top or bottom plate to adjust the shear lag effect while designing structures. The study also demonstrates the strong applicability of I-BSM as an effective approach to analyzing the shear lag effect of thin-walled steel box girders with rectangular ribs.