Use Of Numerical Models Research Articles

Development of the Turbulent Diffusion Model of Fine Suspended Substances in the Lower Atmosphere Layer

A promising direction for solving the problem of air pollution by fine substances is the use of numerical modeling in the development of mathematical models of the transport of pollutants in the atmosphere. An urgent problem in applying mathematical models with numerical algorithms and software is constructing a qualitative model that would meet both the physical parameters and fulfill all the optimal conditions of numerical analysis. The main objective of this study was to develop an algorithm of a mathematical model based on the equation of distribution of impurities in a turbulent medium. That allows considering the simultaneous influence of wind speed, turbulence of atmospheric air, pollution parameters, direction, and wind force on the size of scattering zones. The unique feature of the study is the use of the coordinate splitting equation of impurities distribution in a turbulent environment with subsequent normalization and parameterization of conditions. Finding integrands functions in the calculation algorithm allows obtaining a stable computational algorithm of the proposed propagation model of fine suspended particles. The solution of the function implemented in the Mathcad Prime 7 software. Distributions of concentrations and their levels for various values of turbulence of atmospheric air and dangerous wind speed are received. The most significant number of fine particles is at a distance of up to 4 km from the emission source. Still, there is also the transfer of contaminants at more than 5 km (up to 57 % of the initial emission concentration). The model has convenient software and algorithmic software, the time of calculation of graphic visualizations up to 20 minutes on medium-power computers. The obtained mathematical model can use in systems of forecasting man-caused load on the environment for the prompt solution of environmental problems.

An ensemble of Antarctic deglacial simulations constrained by geological observations

The Antarctic ice sheet has the potential to make a significant contribution to future sea-level rise. Understanding this potential and making projections of future ice sheet mass change requires use of numerical models. Confidence in model projections can be improved by hindcasting: testing the model against past ice sheet changes. Robust deglacial model reconstructions are also used to correct satellite gravimetric measurements of current change for glacial isostatic adjustment processes. Here we present a new model ensemble of post-Last Glacial Maximum Antarctic deglaciation reconstructions. The ensemble is generated using the Parallel Ice Sheet Model (PISM) in which we vary a range of parameters including key glaciological controls, basal sediment strength, mantle viscosity, and climate forcing. We test the ensemble results against a database of geological constraints, and develop a new scoring scheme that allows us to determine metrics of model performance against past ice sheet grounding line extent, ice sheet thickness, and thinning rates, as well as present-day ice sheet configuration. We discuss the parameter combinations that lead to the highest-scoring simulations and we also compare our ensemble performance with existing published deglacial models, using the same scoring scheme. Exploring the characteristics of the highest-scoring ensemble members highlights some key features of deglacial behaviour including a relatively narrow range of past excess ice volumes at the LGM, Holocene retreat behind present-day grounding lines with commensurate volume minima, and readvance behaviours. The comparison also allows us to identify areas where more geological data would have high constraining power for ice sheet models.

Numerical Investigation of the Impact of Onshore Fish Farming on the Western Coast of Algeria

A methodology for aquaculture site selection is presented using a combined hydrodynamic/nutritional model to predict fish farm wastes and dispersion, using the indirect fish waste estimation method, and the numerical model MIKE 21. This method can be used as a basis for assessment of the environmental impact of fish farms. The models were applied for a virtual inland fish farm to harvest 450 tons of sea bass in the west coast of Algeria. The results show that the fish farm effluents quantities and dispersion depends on the production cycle and size, the hydrodynamic parameters, as well as the food quantity and composition. The suspended waste, nitrogen and phosphorus are respectively the main contributors to the fish farm pollution. The current speed varies from 0.005 to 0.045 m/s, while the nitrogen and phosphorus concentrations reached 2.1 mg/L, and 0.03 mg/L respectively. This study allows the Algerian authorities to decide upon delivering fish farming permissions in the studied area, by identifying the suitability of the area for aquaculture, and predicting potential fish farm pollution. The use of numerical models in aquaculture could help reducing installation, water treatment costs and the environmental impact of fish farms by contributing to the sustainability of the activity.

Applicable Investigation of SPH in Characterization of Fluid Flow in Uniform and Non-Uniform Periodic Porous Media

Today, the use of numerical modeling for characterizing properties of porous media and related concepts has been widely extended, especially in subsurface flow issues such as geological CO2 storage and petroleum recovery. Therefore, in this study, the fundamental problem of laminar fluid flow through uniform or non-uniform and periodic array of cylinders was functionally investigated using the smoothed particle hydrodynamics (SPH) method as a modern and applied method of modeling in order to develop the past studies and introduce a complementary numerical tool alongside laboratory methods. All modeling processes were performed in the form of dimensionless processes for generalization and applicability at different scales. The results were used to characterize properties of porous media and to investigate basic properties such as fluid velocity, permeability, streamlines, and hydraulic tortuosity. Accuracy of modeling was shown in comparison with the results obtained in the literature. In this study, the potential of the method has been investigated in order to show the ability in modeling characteristic laboratory experiments of porous media and the possibility of using it instead of them. For this purpose, three periodic models of uniform and randomly distributed non-uniform porous media with arrays of circular, square, and diamond-shaped cylinders in a porosity range of 30–95%, with different types of cylinder distribution at the pore scale, were investigated. New equations were proposed for permeability as a function of porosity. Moreover, the method of tortuosity calculation was investigated directly through the time history of properties in the SPH method, and shape factors were obtained for the studied porous media models. The results showed that the geometry of a square cylinder with distribution in a square grid led to a higher permeability than circular and diamond-shaped grids. In contrast, diamond-shaped geometry with distribution in a hexagonal grid led to higher permeability than the other two models. Furthermore, diamond-shaped geometry had higher tortuosity, and circular and square geometries had almost identical tortuosity. Increasing the size of the modeling domain and decreasing the size of cylinders (i.e., decreasing resolution) reduces effects of the shape and the geometry of cylinders and achieves the same results. Random and non-uniform distribution of cylinders within porous media reduces fluid velocity, permeability, tortuosity, and shape factor (p) compared to the uniform models.

Tolerance analysis by static analogy: numerical and experimental results

Industrial requirements to design high quality products in shorter and shorter times impose the use of numerical models to estimate the geometrical deviations of these products, which are assemblies, starting from the geometrical deviations of their components. Numerical models may support this estimation activity, thus reducing the time to market and the design costs. The free-body model is an interesting numerical method to translate the tolerance chain into a static problem solved by algebraic or graphical procedures by using the free-body diagrams of force analysis. This work presents a free-body model that is able to deal with dimensional and geometrical tolerances that involve translations of the features to which the tolerances are applied. Moreover, it validates the free-body model for tolerance analysis of rigid parts by defining and solving a case study through numerical and experimental activities. The present work uses a case study to demonstrate the effectiveness of the free-body model by underlining that the experimental results obtained are very close to those from the numerical model.

MRI-based numerical modeling of cardiac pulsed field ablation (PFA) with sub-microsecond pulses

Abstract Background The use of irreversible electroporation (IRE) for cardiac ablation in the management of cardiac arrhythmias, known as Pulsed Field Ablation (PFA), has gained the attention of many researchers, physicians and companies. Despite the demonstrated efficacy and safety profiles of the technique, there are still many open questions. One of them deals with the effective electric field thresholds necessary for cardiac tissue ablation. Contrary to radiofrequency (RF) ablation, where the thermotemporal thresholds for tissue damage are well established, the electric field thresholds for effective IRE are uncertain and depend on the tissue type and the waveform characteristics of the delivered electric field. Purpose The use of numerical models to understand the electric field distribution and the corresponding lesion for a specific electrode geometry are widely used in IRE for cancer treatment. Models can predict ablation volumes when the field thresholds are known or can be used to estimate the field thresholds when the lesion geometry is established post-treatment. The goal of the present study was to build a subject-specific realistic 3D numerical model to assess the ability of modeling to predict PFA lesions. Methods PFA experiments were performed in male mongrel dogs following a protocol approved by the Mayo Clinic Institutional Animal Care and Use Committee. Briefly, animals were sedated and intubated, and two non-irrigated deflectable catheters with an 8-mm tip were positioned on both sides of the interventricular septum under fluoroscopy guidance. Submicrosecond pulses were delivered in a bipolar fashion across both catheters. Sequences of pulses of 300 ns duration (or other durations in that range) were repetitively applied with voltage levels in the kV range. 30 days after the procedure, MRI with late gadolinium enhancement (LGE) were acquired to assess the presence of ablation lesions in the treated tissue. Ventricular areas were segmented from MRI images and 3D volumes were created. The generated 3D geometries were imported into software COMSOL Multiphysics. Realistic 3D geometries of the catheters were placed in the same positions than during the experiments, fluoroscopy videos recorded during the procedures were used as a guidance. The computed electric field intensity distributions were compared to the LGE areas to extract the range of electric field thresholds where the predicted lesion size was compatible with the real size of the LGE areas for each application site and pulsing protocol. Results and conclusions Our results show how the numerical model is able to reproduce the shape of the LGE fibrotic lesion areas observed 30 days after the procedure. Additionally, the model clearly confirms the dose-dependent lesion sizes observed experimentally. This study supports that numerical modeling is a valuable tool for understanding PFA treatments and that it could be used as patient-specific treatment planning tool. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie

Virtual pre-test analysis for optimization of multi-channel control strategies in direct field acoustic testing

Direct field acoustic excitation testing, or DFAX, is gaining the attention of the space industry as a reliable and flexible method to perform acoustic qualification tests of spacecrafts. The test aims at reproducing the sound conditions of the space launch using an array of high-powered loudspeakers placed around the test specimen. To achieve this end, advanced multi-input multi-output (MIMO) control strategies are employed to design the independent signals which drive the different speakers based on the responses acquired at the control locations over the test volume. Consequently, the performance and overall efficiency of the test campaign is then determined by a number of factors, among them stack configuration, test specimen orientation, number of speakers, control matrix and sensor location. To assist engineers in the design of such tests, this work proposes the use of numerical models to simulate the entire test set-up before the on-site campaign takes place. State-of-the-art vibro-acoustic solvers are employed to predict the pressure responses at all points in the test volume for various design choices, allowing test engineers to perform a virtual pre-test analysis based on numerical solutions to optimize their control strategy. The results included in this work illustrate the methodology followed to account for all the transfer functions of the electro-acoustic system as well as the validation of the levels of accuracy which can be achieved in a full-scale DFAX test via direct comparison with experimental measurements.

Scaling laws for unmitigated pile driving: Dependence of underwater noise on strike energy, pile diameter, ram weight, and water depth

Sound produced by marine pile driving activities poses a possible risk to marine life. The assessment and mitigation of this risk requires a prediction of the expected sound levels. While different analytical models have been presented to estimate the decay characteristics of pile driving noise, the estimation of the source level still requires the use of numerical modelling in most cases. The paper at hand discusses the possibilities and limits of estimating approximate source or any other levels by scaling laws, using measurement data from previous projects. The identified main influencing factors include strike energy of the hammer, pile diameter, ram weight, and water depth. The scaling laws are derived from theoretical considerations verified against results of a state-of-the-art finite element model for pile driving noise radiation. The found dependencies are then validated against a set of offshore measurement results. It is shown that the obtained scaling laws provide an option to approximately estimate the sound exposure levels of pile driving activities from one site to the other, within practical ranges of accuracy.

Simulation of diffuse source polluted water environment based on MIKE21: A case study of the urban section of the Bai river

Abstract Affected by urban construction and industrial discharge, the diffuse source pollution of river water environment in urban sections is becoming more and more serious. The use of numerical models can accurately and efficiently simulate the process of diffuse source pollution and analyze its evolution. Based on MIKE21, the urban river water environment model of the Bai river is constructed. After parameter calibration, it is proved that the model has high accuracy. Based on the discharge of this river section in 2018, the river diffuse source pollution is simulated under three hydrological conditions, and the BP neural network is used to simulate the river diffuse source pollution. Network assessment of water quality in dry years. The results showed that the four water quality indicators showed the spatial distribution characteristics of upstream>urban section>downstream, and the river water quality in the year showed the temporal distribution characteristics of flood season better than a non-flood season. The mean value of the coefficient of certainty R2 reaches 0.94 when comparing the simulated and measured values, which indicates that the model has high applicability and satisfactory fit. If the water quality of the water year does not meet the standard, the diffuse source pollution discharge should be reduced from May to October. This study can provide reference and guidance for urban river diffuse source pollution control.

Improving Results of Existing Groundwater Numerical Models Using Machine Learning Techniques: A Review

This paper presents a review of papers specifically focused on the use of both numerical and machine learning methods for groundwater level modelling. In the reviewed papers, machine learning models (also called data-driven models) are used to improve the prediction or speed process of existing numerical modelling. When long runtimes inhibit the use of numerical models, machine learning models can be a valid alternative, capable of reducing the time for model development and calibration without sacrificing accuracy of detail in groundwater level forecasting. The results of this review highlight that machine learning models do not offer a complete representation of the physical system, such as flux estimates or total water balance and, thus, cannot be used to substitute numerical models in large study areas; however, they are affordable tools to improve predictions at specific observation wells. Numerical and machine learning models can be successfully used as complementary to each other as a powerful groundwater management tool. The machine learning techniques can be used to improve calibration of numerical models, whereas results of numerical models allow us to understand the physical system and select proper input variables for machine learning models. Machine learning models can be integrated in decision-making processes when rapid and effective solutions for groundwater management need to be considered. Finally, machine learning models are computationally efficient tools to correct head error prediction of numerical models.

Methodology to Investigate the Transformation Plasticity for Numerical Modelling of Hot Forging Processes

Hot forging is a complex process involving the mutual influence of numerous thermo-mechanical-metallurgical material phenomena. In particular, the strains of transformation-induced plasticity (TRIP) have a significant influence on the distortions and residual stresses of the components. The TRIP strains refer to the anisotropic strains depending on the orientation and significance of the stress conditions during cooling superimposed to the phase transformation. With the use of numerical models, the impact of this effect can be investigated in order to ensure the production of high quality components. However, an experimental determination of the characteristic values of TRIP is challenging, which is why only few corresponding data are available in the literature. Therefore, this paper presents an experimental and numerical methodology as well as the results of studies on the interaction between stresses and phase transformations in the materials AISI 4140 and AISI 52100. The investigations of the TRIP strains are carried out using hollow specimens, which are thermo-mechanically treated in the physical forming simulator Gleeble 3800-GTC. The specimens are austenitised, quenched to test temperature and held there while diffusion controlled phase transformation takes place. The extent of TRIP as a result of different superimposed tensile or compressive loads is determined by means of dilatometry. In addition, the extent of TRIP for diffusionless martensitic phase transformations was investigated by continuous cooling tests under tensile and compressive loads. It was found that the transformation plasticity varies depending on the material, the phase type, the temperature and the tensile or compressive stresses. Subsequently, simulations of the physical experiments using the FE software Simufact.Forming verified the determined phase specific values of TRIP.

Back-Calculation Method for Estimation of Geomechanical Parameters in Numerical Modeling Based on In-Situ Measurements and Statistical Methods

An important element of numerical modeling for specific mining issues is the selection of model parameters. The incorrect determination of geomechanical parameters can result in significant calculation errors carried throughout the entire problem. This paper presents a method for determining effective geomechanical parameters for technological and residual pillars through the use of numerical modeling, specifically, back-calculation. This is based on the results of numerical simulations, measurement data (e.g., excavation convergence measurements), and statistical methods (a non-linear regression model with “dummy” variables). The result is that appropriate parameters of pillars are set out iteratively so that the displacements of selected points in the numerical model correspond (with some approximation) to the results of mine measurements. The procedure of determining pillar parameters is presented using a case study of one mining field in an underground copper mine, where the deposit is mined using the room and pillar system. Numerical calculations were performed using a Phase2 v. 8.0 program (Rocscience, Toronto, Canada), while statistical calculations used a Statistica computer program. The results of excavation convergence measurements performed in the analyzed mine have been applied. This paper shows that for the presented method, the resulting matching of theoretical values of convergence determined numerically for specified pillar parameters to in-situ results of convergence measurements, is very good (R2 = 0.9896). This work exemplifies a set of the parameters of pillars for an elastic model of rock mass, but this method can also be applied to other models.

Modeling the impact of soil cohesiveness on embankment stability under rapid drawdown

For embankment slope stability, soil cohesivity is one of the most important shear strength parameters. The effect of cohesiveness on the slope stability of a homogeneous embankment dam under rapid drawdown loading conditions was examined in this study. With the use of numerical modeling in GeoStudio, different situations were explored based on cohesiveness (0 kN/m2, 5 kN/m2, 10 kN/m2, and 15 kN/m2) under a 1 m per day drawdown rate. The factor of safety value obtained from the long-term steady-state condition under 15 kN/m2 cohesion was equivalent to a 116.8% increase from the one obtained under 0 kN/m2 cohesion. The factor of safety values obtained after subjecting the embankment to different soil cohesion levels yielded a p-value of 1.91 x 10-41, according to the Analysis of Variance. The calculated p-value (alpha value) is less than 0.05, suggesting that the differences between the examined cohesiveness values based on the list of the factor of safety values are statistically significant. The findings derived in this study show that it is significant to capture the effect of material characteristics during the design phase of an embankment dam.

Pragmatic Validation of Numerical Models Used for the Assessment of Radioactive Waste Repositories: A Perspective

The safety case for a radioactive waste repository relies heavily on results obtained by numerical models that assess the long-term performance of the engineered and natural barrier systems. Given that important engineering and public policy decisions are based on these models, it is essential that we critically evaluate their abilities and limitations, and thus justify the level of confidence we have in the inferences drawn from the modeling. In this article, we discuss some of the issues surrounding the modeler’s attempts to test, corroborate, confirm, and verify numerical models—a process sometimes referred to as model validation. This wide-ranging topic is approached by first examining its deep roots in the philosophy of science and hypothesis testing. However, the application of these principles to radioactive waste isolation calls for a more pragmatic approach, which has the narrower goal of corroborating site-specific models and their usefulness for a specific purpose. We focus on the practical aspects of validating hydrogeological models that are used to understand the evolution of the repository system. We will make the case that the responsible use of numerical models requires a sufficient understanding of the quality and robustness of the simulation results, with direct implications for how these results need to be interpreted, and how they can (or cannot) be used in support of important policy decisions.

Comparison of Numerical Methods for Thermal Performance Evaluation of Circuit Protection Devices in EV Application

With the growing demand of electric vehicles, design of circuit protection devices is now an important consideration in automobile industry. Modern day circuit protection devices have been constantly undergoing miniaturization due to requirement of minimizing the foot print for use in electrical vehicles and aerospace applications. This size reduction makes thermal management one of the most important aspects of their design. Use of numerical model to predict heat transfer can significantly reduce the cost and time required in testing physical prototypes. In this paper, three different approaches for numerically predicting temperature rise of circuit breakers are discussed and compared from the point of view of accuracy and computational effort. The three methods are 1) Finite volume based analysis in which conjugate heat transfer inside and outside the breaker is modelled by solving Navier-Stokes equations 2) Finite element based heat conduction model in which convection is modelled as boundary condition instead of solving for fluid motion, and 3) Thermal network based model which uses electrical analogy of heat transfer to solve a thermal resistance network. In the first two iterative models mentioned above, heat generation from current-carrying parts is calculated by solving Maxwell’s equations of electromagnetics by Finite element method. Eddy current losses and temperature dependence of electrical conductivity is considered in the calculation of heat loss. In all three methods, electrical and thermal contact resistances are added at appropriate locations based on analytical calculations. All three methods have been validated with temperature rise test results. In this paper, the heat loss and temperature of a molded case circuit breaker have been predicted by all three methods discussed above. It is observed that the Finite volume-based method is the most accurate amongst the three methods. It can computationally predict air motion and air temperature at critical locations. However, this additional accuracy comes at the cost of added effort in terms of additional mesh count and computation. The Finite elementbased method gives good accuracy but does not predict air temperature. The analytical network-based model is less accurate compared to other methods and relies on product expertise and experience. Based on the study, the following recommendations are made:1) The finite element-based method is best suited to evaluate designs which do not alter flow pattern significantly 2) The finite volume method is recommended to evaluate effect of flow altering design changes 3) The network-based model is recommended for initial evaluation of correct cross sections of current carrying members.

State and development prospects of the hydrological monitoring system of the Arctic Ocean

The article briefly substantiates the need for regular monitoring of the state of the waters of the Russian Arctic Seas and the Arctic Basin of the Arctic Ocean. The goals and objectives of monitoring hydrological conditions are formulated. General ideas about the development and construction of a system for monitoring hydrological conditions in the Arctic are expressed, taking into account the use of modern instruments and methods of oceanographic observations. It is shown that the most promising is the use of autonomous measuring complexes in the monitoring system, including moorings and drifting profiler buoys. The special value of satellite oceanographic data is emphasized. No less important are coastal observations carried out over the network of Roshydromet stations, as well as at research centers united into the Arctic Space-Distributed Observatory. The inclusion into this Observatory of the ice self-propelled platform “North Pole”, which will replace the drifting stations, will allow not only observing and measuring the main characteristics of the water masses, but also conducting controlled field experiments that will provide a deeper understanding of different-scale physical processes occurring in the waters of the Arctic Ocean. An important element of the monitoring system is data assimilation based on the use of numerical models that allow for the effect of the ice cover in the atmosphere-sea ice-ocean interaction system.

Numerical Study of Rectangular Tank with Sloshing Fluid and Simulation of the Model Using a Machine Learning Method

This paper presents a fluid sloshing model using the artificial neural network method (ANN). Determining the fluid sloshing model in the tank is a challenging task due to its nonlinearity and complexity of behavior to its environmental and operational conditions. Due to the problems of laboratory modeling, the use of numerical modeling to analyze this phenomenon can be justified. In this paper, first, the fluid sloshing in the tank is simulated by the smooth particle hydrodynamics method (SPH). The input-output data for training the artificial neural network is based on the obtained results. Finally, the maximum force due to the fluid sloshing is obtained by changing different parameters.

A continuous dynamic constitutive model for normal- and high-strength structural steels

The use of numerical models in the advanced analysis and design of steel structures, particularly under extreme loading conditions, is becoming increasingly widespread. A crucial component of such models is an accurate description of the material response. A systematic study into the dynamic constitutive modelling of structural steels is presented herein. The key features of the dynamic stress–strain characteristics of structural steels at various strain rates, i.e., test methods, material strength, strain-rate effect index and strain-rate effect models, are examined and discussed. Supplementary SHPB tests on both normal- and high-strength structural steels (Q235, Q355, Q460, and S960) under a wide range of strain rates up to 5000 s−1, filling gaps in existing datasets, are then carried out. A database of dynamic test results, containing 453 stress–strain curves, is systematically established and analyzed. Finally, a continuous dynamic constitutive model, capturing the dependency of both yield strength and strain rate, is proposed to predict the dynamic stress–strain response for structural steels, from normal- to high-strength material (235–960 MPa), and from static to high strain rate loading conditions (up to 5000 s−1).

Analysis of processes in magnetorheological sealer considering for magnetic fluid deformation

The small size of the working gap in the sealer makes many physical measurements difficult or impossible. The main way to study the processes inside the device is to use analytical and numerical mathematical modeling. Most researchers apply finite-element calculation of magnetic field and analytically find the difference in pressure. Currently, there are few studies devoted to multiphysics numerical calculations of the processes in magnetorheological seal. The use of numerical models allows considering the dependence of rheological properties of magnetic fluid on hydrodynamic, temperature and magnetic fields, the real geometry of the working zone. Compared to the analytical models, a numerical one includes a smaller number of assumptions and allows visualizing various flow parameters, which are especially important for the analysis. The purpose of this study is to analyze the effect of the deformation of the magnetorheological plug in case of pressure difference held by the sealer. The study is based on the developed numerical model with the related calculation of magnetic and hydrodynamic fields. The study is carried out based on the theories of ferrohydrodynamics, hydrodynamics and electromagnetic field. Integrated finite-element modeling of the magnetic and hydrodynamic fields of the magnetorheological sealer in Comsol Мultiphysics has been used. A numerical model of the magnetorheological sealer characterized by automatic rearrangement of the boundaries of the liquid plug based on the balance of pressures inside the liquid has been developed. The distribution results of magnetic induction and pressure in the working gap of the sealer, considering changes in the boundaries of the magnetic fluid, has been obtained. Comparison of the results of the obtained retained pressure drop and the results of other models has been carried out. A numerical mathematical model that considers the deformation of the magnetorheological plug has been developed. The model makes it possible to estimate the influence of centrifugal forces of the rotating shaft on the retained pressure drop. The results can be used to create high-speed seal components. The difference of the value of analytical calculation does not exceed 5 %. The assumption about full filling of the working gap with magnetic fluid 2,5 times underestimates the retained pressure difference at high shaft rotation speeds.

Analysis of the mechanical expansion process of thin-walled tubes for air heat-exchanger production

Finned tube air heat-exchangers are built by joining the tubes to the fins by various techniques. A technique mostly used for large heat-exchangers consists of fitting the tubes into the holes of the fins by expanding the tubes using a mechanical process. The expansion is achieved by inserting an ogive of a larger diameter into the tube. The intimate contact of tubes and fins due to the press fitting ensures the proper thermal connection. This work tries to describe an experimental-numerical procedure useful to study and predict the mechanical process and the process parameters. The procedure, based on material properties obtained from tensile tests and the use of the inverse method to identify the material parameters, is based on bi-dimensional finite element (FE) models used to simulate the expansion process. The FE model is then used for process optimisation regarding such parameters as the ogive shape and ogive sizes, friction coefficient and speed of insertion of the ogive into the tube. Indeed, size and shape uncertainties strongly influence the process parameters and the process quality, as well as the heat-exchanger efficiency. The use of numerical models was proven highly effective in predicting and optimising the process by quickly analysing the influencing factors and optimising the production.