Numerical Computer Model Research Articles

Comparative Analysis of Machine Learning Techniques for Identifying Multiple Force Systems from Accelerometer Measurements.

The knowledge of the forces acting on a structure enables, among many other factors, assessments of whether the component's useful life is compromised by the current machine condition. In many cases, a direct measurement of those forces becomes unfeasible, and an inverse problem must be solved. Among the solutions developed, machine learning techniques have stood out as powerful predictive tools increasingly applied to engineering problem-solving. This study evaluates the ability of different machine learning models to identify parameters of multi-force systems from accelerometer measurements. The models were assessed according to their prediction potential based on correlation coefficient (R2), mean relative error (MRE), and processing time. A computational numerical model using the finite element method was generated and validated by vibration measurements performed using accelerometers in the laboratory. A robust database created by the response surface methodology in conjunction with Design of Experiment (DOE) was used for the evaluation of the ability of machine learning models to predict the position, frequency, magnitude, and number of forces acting on a structure. Among the six machine learning models evaluated, k-NN was able to predict with a 0.013% error, and Random Forests showed a maximum error of 0.2%. The innovation of this study lies in the application of the proposed method for identifying parameters of multi-force systems.

Effect of Sewage Sludge Addition on the Co-Combustion Characteristics of Municipal Solid Waste Incineration

This study employs a numerical computation model based on a municipal solid waste (MSW) incinerator in Nanning to investigate the impact of different sewage sludge (SS) co-combustion ratios and MSW incinerator temperatures on combustion efficiency. Using the FLUENT simulation method, this study systematically analyzes the distribution characteristics of the temperature field, velocity field, and pollutant concentration field within the furnace under various SS mixing ratios (5%, 7%, 10%, and 15%) and MSW incinerator temperatures (800 K, 1000 K, and 1200 K). The simulation results indicate that the combustion efficiency was optimal at an MSW incinerator temperature of 800 K, where the co-combustion of SS with MSW mixed effectively, leading to a stable and efficient combustion process. Furthermore, an SS co-combustion ratio of 7% was identified as the most effective in maintaining high combustion efficiency. These findings contribute to the optimization of co-combustion strategies for MSW and SS, enhancing both operational efficiency and environmental compliance.

Investigation of Aerodynamic Performance of Multi-element Airfoil in Free Surface Effect

Abstract This study examines the aerodynamic performance of the 30P30N multi-element airfoil flying on a free surface, a numerical computational model is established, the governing equations are addressed through the application of the finite volume method, while the volume of fluid method is utilized for the simulation of two-phase flow. Different mesh strategies and turbulence models are compared, with the numerical methods validated against experimental data. The aerodynamic properties of the 30P30N multi-element airfoil on the free surface at different wavelengths and wave heights are given by numerical computations, which show that the ground effect of the 30P30N multi-element airfoil differ from those on a clean airfoil, the aerodynamic coefficients of the 30P30N multi-element airfoil decrease as flight altitude lowers, with the pitching and drag moment of the slat is opposite to that of the main airfoil and the flap. Additionally, when the 30P30N multi-element airfoil flies over a regular wave surface, the aerodynamic coefficients of each component exhibit periodic behavior.

БАГАТОШАРОВІ ІНДУКТОРИ ДЛЯ УСТАНОВКИ ІНДУКЦІЙНОЇ ТЕРМООБРОБКИ АЛЮМІНІЄВИХ ЗЛИВКІВ ПРИ ПРЕСУВАННІ КАТАНКИ ДЛЯ СИЛОВИХ КАБЕЛІВ

On the basis of the developed mathematical model, computer (numerical) modeling of electrothermal processes in a multi-layer inductor installation, which is used for heating cylindrical aluminum ingots (blanks) before pressing the wire rod, as a basis for obtaining current-conducting cores of power cables from it, was carried out. Single-phase and three-phase multilayer inductors of the galette type were studied, as a result of which it was shown that the maximum value of the electrical efficiency of such an installation for both inductors is provided by their three-layer winding with a water-cooled copper tube of rectangular section. For both inductors, distributions along the radius and length of the aluminum blanks of the volumetric specific power and the specific linear power of heat release from the eddy currents induced in the blanks were obtained. For a three-phase inductor, such distributions were obtained when feeding it with voltages with phase shift angles of 120 and 60 degrees. The losses in the turns of the inductors and their distribution along the length and layers of both inductors were also studied. Ref. 8, fig. 7, tables 2.

Calculation of 3D Shape of a Hyperelastic Body for Nonlinear Elasticity Models Using the Newton Method

This article discusses methods for calculating the deformations of objects with hyperelastic materials within the framework of the nonlinear elasticity theory. This topic is relevant due to the use of new technological materials in industry, and as a result, the emerging task of preliminary numerical calculations for operational reliability, research and modeling of deformation behavior. The first part provides a brief overview of the main provisions and formulas of the nonlinear elasticity theory. Then the spatial discretization of 3-dimensional objects and the calculation of the deformation gradient using the finite element method are considered. The article provides an algorithm for solving this problem, such as minimizing the functional of stored energy, and also considers the class of permissible deformations. Afterwards, a detailed description is given, along with pseudocode, of the method of implementing and calculating the minimization by Newton’s method. The last part demonstrates an example of the calculations performed, based on the developed software that allows for numerical experiments and computer modeling of deformations of hyperelastic bodies, and one of the capabilities of which is to perform these calculations using Newton’s method.

Functionally graded fibre concrete constitutive model considering fibre spacing effects and interfacial interactions

The purpose of this paper is to establish a new constitutive model for functionally graded concrete (FGC) with high fiber content, considering randomly distributed cylindrical fibers and spherical, ellipsoidal, and cubic aggregates. Considering the fiber spacing coefficient and adjusting for the reinforcing effect of the fibers, the new correction factors include the fiber orientation coefficient, the fiber inclination impact coefficient, and the fiber spacing coefficient. Moreover, the interaction between the upper and lower interfaces of the FGC and the interaction between the fibers and the matrix are also considered. The interface adopts a cohesive bond-slip model to define interface plastic damage. The interaction between the fibers and the matrix is based on the rigid body-spring concept, where the matrix block is first discretized into rigid body-spring elements, which then interact with the fibers to produce bond-slip forces. During model validation, the proposed constitutive model was introduced into Abaqus using Python code. Finite element models for FGC, including the conventional uniaxial tensile model, dog-bone model, and four-point bending model, were established. The results indicate that for the FGC numerical computation model, the critical fiber volume fraction ρs ranges between 6 % and 7 %. However, the exact value should be determined based on specific practical conditions. When ρs is within the range of 0 %–6 %, the mechanical properties of FGC, such as peak stress, tensile strength, and toughness, increase with the increase in ρs. However, when ρs exceeds 6 %–7 %, the growth trend begins to slow down. In some cases, peak stress and tensile strength may decrease with an increase in ρs. At this point, the influence of the fiber spacing coefficient must be considered. Finally, by comparing with the experimental results, it is proved that the proposed constitutive model is feasible for studying the mechanical properties of FGC.

Characterization and optimization of continuous ohmic thermal sterilization based on the development of a predictive computational toolbox

Continuous thermal processing (CTP) is a common method for sterilizing food. However, it can result in an uneven temperature distribution, which can lead to a varying degree of processing intensity. Ohmic heating (OH) can be advantageous in this regard, as it enables volumetric heating for more homogenous treatments. However, evaluating the processing intensity distribution inside the equipment for OH is challenging due to the complex interaction between electrical, mechanical and thermal phenomena. Furthermore, the comparison of OH and conventional heating treatments often lack a profound basis of comparable treatment intensity considerations. To gain a deeper mechanistic understanding of the technology, a numerical computational fluid dynamics model for the OH sterilization of a clear carrot juice from the heating region to the cooling process was developed. The model was validated with thermal and electrical measurements and showed an error rate below 2.5% in its prediction capacities. Moreover, the model was implanted for the validation of the products sterilization and compared to a conventional validation approach, reviling a 33.3% underestimation of the thermal load by conventional manners, which can lead to faulty sterilization of the food product. Additionally, the model was expanded to also be able to predict the microbial inactivation ratio of the system with an average error of 1.10±0.74%. In addition, results indicate that the numerical calculation of the F0 values and their validation with the microbial inactivation ratio have a notable potential for localization and evaluation of hotspots in OH simulations. Therefore, it can be seen as a promising step for establishing a foundation for computer-assisted optimization of CTP and targeted processing.

Weld-joint design to optimize groove weld depth and mechanical properties for welding of nozzle onto pressure vessel

Full and partial set-in weld-joints connect the nozzle to pressure vessels to prevent lamellar tearing. This investigation aims to compare full and partial set-in weld-joints through computer simulations, numerical modelling, welding experiments, nondestructive examination and destructive testing. The nozzle-to-shell opening connection’s weld-joint design model is DN20, with a 50 mm shell wall thickness. The optimal groove weld depth, at a safety factor of 3.5, ranges from 20 to 50 mm. We investigated weld-joint design variations using design-of-experiment, which included actual welding and mechanical testing. The inter-run temperature and its interaction with the heat input were found to be statistically significant. The mechanical properties of welded joint are better than those of the specified material, A516 Grade 70, which include an average impact toughness of 89.5 J at -50 °C, a microhardness of 195 Hv10, an ultimate tensile strength of 533 MPa, a yield strength of 391.5 MPa and an elongation of 56.5%. The coefficients of determination of impact toughness and microhardness, which have R2 values of 88.73% and 76.65%, respectively, conclude a successful welding experiment. The design and mechanical testing results conclude the reliability of the weld-joints.

Ammonia as a hydrogen carrier: Simulation study of the ammonia cracker on thermo-fluid stability and key factors for scale-up

A typical technical problem in a hydrogen society is the difficulty in securing the economic efficiency of hydrogen storage and long-distance transportation. Hydrogen carriers that can convert hydrogen into other compounds are required to overcome this issue. Ammonia has many practical advantages as a hydrogen carrier and is drawing attention as a suitable substance. Therefore, a cracking technology that converts ammonia into high-purity hydrogen is necessary. In this study, a numerical computational fluid dynamics model of an ammonia cracker was developed. The flow and heat transfer characteristics were analyzed using a numerical model. The results showed that a nonuniform temperature distribution caused local cracking of ammonia and adversely affected the hydrogen production process. This results of this study can be used to help design large-scale ammonia crackers and efficient hydrogen production processes and contribute to building infrastructure for hydrogen storage/transport/utilization systems.

Dynamic Failure Characteristics of Sandstone Containing Different Angles of Pre-Existing Crack Defects

Fracture within the rock is one of the main factors leading to rock destabilization and has a significant effect on the stability of the project. In this study, sandstone is used as a research target, specimens with crack inclination angles of 0°, 30°, 45°, 60°, and 90° are prefabricated, and the split Hopkinson pressure bar (SHPB) impact test of sandstone with cracks is carried out based on digital image recognition technology to explore the dynamic damage characteristics of the specimens with five angles. The basic mechanical parameters of sandstone are tested to determine the RHT model intrinsic parameters, and the numerical computational RHT model of sandstone containing crack defects is established, which is verified in comparison with the test to analyze the validity of the model. Finally, the failure characteristics of the numerical model under initial stress were carried out. The study shows the following: with the increase in the fracture angle, the dynamic compressive strength and deformation modulus are distributed in a slanting V-shape, and the inclination angle of 45° is the smallest. The strain rate and energy dissipation rate are distributed in a slanting N-shape, and the inclination angle of 45° is the largest. The transmittance shows a decreasing trend, which is the opposite of the reflectivity pattern. The crack angle determines the location and direction of the initial crack, which affects the failure mode. In addition, the parameters of the RHT constitutive model suitable for sandstone are obtained, and the damage and strength patterns of the established RHT model are highly consistent with the laboratory test results. The damage range of numerical models for crack defects with different inclination angles is negatively correlated with confining pressure values and positively correlated with axial pressure values. The damage zones are symmetrically distributed approximately perpendicular to the direction of cracks, and the confining pressure has a contributing role in the peak of the element stresses; however, the axial compression has no contribution in the peak of the element stresses.

Simulation of thermal field in mass concrete with cooling pipes based on the isogeometric analysis method

As the water pipe cooling system is widely applied to controlling temperature in mass concrete structures, the precise simulation of the temperature field in mass concrete with cooling pipes embedded is meaningful. This paper presents an isogeometric analysis (IGA) with NURBS for heat transfer in mass concrete with consideration of the cooling pipe. The proposed method not only achieves the same level of accuracy with fewer nodes but also eliminates the time-consuming process of mesh in the traditional FEM. The coarsest parameter space which depicts small pipe and large concrete precisely is constructed to create an efficient model for numerical computation. In addition, the unique k-refinement in IGA is supposed to be the most appropriate encryption mechanism, and the knot insertion vector for effective refinement is calculated by considering the characteristics of temperature gradient distribution around the cooling pipes. In addition, a different calculation parameter has been discussed to show the stability and flexibility of the IGA. The obtained numerical results demonstrate the accuracy and efficiency of the proposed scheme in the simulation of transient temperature fields in concrete structures with cooling systems.

Predicting weld pool metrics in laser welding of aluminum alloys using data-driven surrogate modeling: A FEA-DoE-GPRN hybrid approach

Multi-physics computational models based on finite element analysis, offer detailed insights into the dynamics and metrics in the weld pool formed by laser welding. Conversely, data-driven surrogate models provide a cost-effective means to predict desired responses. These models establish statistical or mathematical correlations with input–output data, eliminating the need for additional simulations during design optimization. This study proposes a data-driven surrogate model, employing the Gaussian process regression network (GPRN), to predict weld pool metrics, such as weld width and depth of penetration in laser welding of aluminum alloy. A 3D computational fluid dynamics-based numerical model is initially constructed and experimentally validated to predict weld pool metrics. Subsequent experimental runs, guided by the design of experiments, include various configurations of process parameter settings. The developed numerical model computes weld pool metrics for each experimental run, forming a dataset for training and testing the GPRN model. The GPRN model is evaluated against simulated data, showing adequacy with a mean square error of 1.7 µm and mean absolute percentage error of 10−7, with experimental validation further confirming its accuracy, revealing a minimum error of 1.7%, a maximum error of 8%, and an average error of 3%. The key contribution and novelty of this study lie in the development of the hybrid data-driven model, which accurately predicts weld pool metrics while minimizing experimental and computational efforts.

Study of thermal properties and stresses in a 1.05 MW molten salt furnace for recovering and storing blast furnace gas waste heat

Utilizing a molten salt furnace to recover waste heat from blast furnace gas and storing it in high-temperature molten salt represents an innovative solution for steel waste heat recovery systems. In this study, a 1.05 MW spiral coil vertical molten salt furnace thermal energy storage system was constructed. During the thermal storage experiment under a 75 % heating load, the system achieved a heating efficiency of 74.57 % and a molten salt temperature of 560.3 °C. To analyze the thermal performance and thermal stress of the molten salt furnace, a three-dimensional transient numerical computational model using ANSYS Fluent and Matlab software was developed. A two-dimensional thermoelastic model was employed to assess the thermal stress of the spiral coil. The deviations between the experiment and simulation for the molten salt outlet and coil temperature were 1.40 % and 1.66 %, respectively. Furthermore, the three-dimensional temperature and thermal stress distributions under the benchmark case were simulated, finding that the maximum coil temperature reached 574.20 °C, while the maximum coil stress was 446.30 MPa. Increasing the heating load, molten salt inlet temperature, and time all lead to increased equivalent thermal stress. However, the location of the coil radius at 16 mm showed a minor sensitivity to heat flow density. Additionally, increasing the molten salt inlet mass flow rate by 0.1 kg/s resulted in a 2.99 MPa reduction in equivalent thermal stress. This paper provided valuable insights into the thermal properties and evolution of thermal stresses during the heating process in molten salt furnaces, offering a promising approach for recycling blast furnace gas in steel plants.

Investigation and perspectives of using Graph Neural Networks to model complex systems: the simulation of the helium II bayonet heat exchanger in the LHC

Large cryogenic systems, like those installed at CERN, are complex systems relying on many diverse physical processes and phenomena that are difficult to simulate and monitor in detail. With only a limited number of properties measured and made available for monitoring and control purposes, several processes contributing to the dynamics of the systems are ignored. This lack of information can reduce the accuracy and the capability of a model to track, predict, and anticipate the behavior of the system. Accurate analytical or numerical computer modeling can be developed to simulate the non-linear dynamics of the processes but they are complex, computationally intensive, and cumbersome to test, validate, and implement with different configurations and limited measurements of the hidden properties. In this work, we present our investigation of using Graph Neural Networks (GNN) to build a model of the helium II bayonet heat exchanger operating in the LHC at CERN. We are proposing to use a hybrid machine learning approach, where the parameters of the GNN model are estimated by a combination of supervised learning algorithms trained on experimental data and bounding physics equations and parameters. The GNN model was initially trained on data from the experiments performed on the LHC prototype magnet strings and validated on data extracted during the operation of the LHC machine. We demonstrate the model’s accuracy, repeatability, and robustness in various configurations. The model is also well inspectable and explainable, providing the time evolution of all variables. We report on the results and expected applications, which include predictive control, diagnostic, and operator training.

A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography

Objective. Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising. Approach. In this work, we propose a novel approach to rapid and non-invasive skin cancer diagnosis that leverages the technologies of difference-based electrical impedance tomography (EIT) and graphene electronic tattoos (GETs). Main results. We demonstrate the feasibility of this first-of-its-kind system using both computational numerical and experimental skin phantom models. We considered variations in skin cancer lesion impedance, size, shape, and position relative to the electrodes and evaluated the impact of using individual and multi-electrode GET (mGET) arrays. The results demonstrate that this approach has the potential to differentiate based on lesion impedance, size, and position, but additional techniques are needed to determine shape. Significance. In this way, the system proposed in this work, which combines both EIT and GET technology, exhibits potential as an entirely non-invasive and rapid approach to skin cancer diagnosis.

End-over-end (EoE) rotation of toroidal cans: An experimentally validated mathematical modelling study

Toroidal cans have been presented recently to improve the canning process efficiency, and previous studies focused on static and axial rotational processes. End-over-End (EoE) rotation is a significant agitation approach to increase the temperature uniformity of liquid canned products, and it would be important to observe the effect of this process combined with the toroidal cans. Therefore, in this study, this combined effect was considered to improve the process in the view of temperature uniformity. For this purpose, a computational numerical model was developed using - Star CCM+, and this model was validated with experimental data. Then, the rotational rate and headspace amount effects in a toroidal can geometry, including a liquid, were determined using this validated model. The numerical results indicated that these parameters influenced the heat transfer process with a resulting uniform temperature distribution through the EoE processing.

YTCommentQA: Video Question Answerability in Instructional Videos

Instructional videos provide detailed how-to guides for various tasks, with viewers often posing questions regarding the content. Addressing these questions is vital for comprehending the content, yet receiving immediate answers is difficult. While numerous computational models have been developed for Video Question Answering (Video QA) tasks, they are primarily trained on questions generated based on video content, aiming to produce answers from within the content. However, in real-world situations, users may pose questions that go beyond the video's informational boundaries, highlighting the necessity to determine if a video can provide the answer. Discerning whether a question can be answered by video content is challenging due to the multi-modal nature of videos, where visual and verbal information are intertwined. To bridge this gap, we present the YTCommentQA dataset, which contains naturally-generated questions from YouTube, categorized by their answerability and required modality to answer -- visual, script, or both. Experiments with answerability classification tasks demonstrate the complexity of YTCommentQA and emphasize the need to comprehend the combined role of visual and script information in video reasoning. The dataset is available at https://github.com/lgresearch/YTCommentQA.

A new experimental and numerical simulation method for measuring ash slag fluidity using VOF based on OpenFOAM

A numerical computational model of heated ash flow is proposed using the Volume of Fluid (VOF) method based on OpenFOAM. Established numerical model can accurately calculate the critical flow temperature (Tc) and critical flow velocity (Vc) of ash slag with the error of 1.5 % and 19 % from the experiment, respectively. Forty-five types of ash slag with widely varied properties in China were calculated based on the established model. Results show that high levels (>30 wt%) of Fe2O3 and CaO improve the flowability of the ash slag, and low levels of Al2O3 (10 wt%) also contribute to the flowability of the ash slag. Tc and Vc of the ash were distributed in the range of 1150 ∼ 1400 °C and 0.1 ∼ 1.0 mm/min, respectively. Tc and Vc change in opposite trends with the component content increases, indicating that a higher Tc corresponds to a lower Vc and fluidity reduction. Mathematical models for calculating the Tc and Vc of ash were obtained based on non-linear multiple regression and correlation coefficient, and prediction accuracy was within 10 % and 30 % for Tc and Vc, respectively. The proposed numerical simulation method and prediction model can provide an accurate reference for a wide range of ash fluidity. Also, it was demonstrated that elemental Na has a positive effect on ash flowability based on the model, which is important for measuring slag flowability in slag-tap furnaces.

Advancements in Iso-Diameter seeded growth of CdZnTe crystals: A numerical modeling approach and applications in liquid phase Epitaxy

CdZnTe (CZT) is the preferred material for HgCdTe (MCT) infrared detectors and room temperature nuclear-radiation detector applications. However, their widespread application is hindered by the low yield, attributed to intrinsic thermophysical properties like extremely low thermal conductivity and stacking fault energy, complicating the growth of large-volume crystals. Based on steady-state computer numerical modeling simulation, this paper examines the impact of seed size variations (from 15 mm to 90 mm) in the crystal growth process on the initial growth surface morphology, simulations indicate that larger seed crystals are predisposed to developing more convex interfaces, which are conducive to enhanced crystal growth. An optimized Vertical Gradient Freeze (VGF) method employing iso-diameter seed (having the same diameter as the grown crystals) of approximately 90 mm has been developed to grow single crystals with reduced defect density in a VGF furnace, and the applications in liquid phase epitaxy (LPE) are also discussed.

Non-Linear Behavior of Double-Layered Grids

Abstract This study presents a numerical approach to an analysis of the mechanical behavior of double-layered tensegrity grids. We present a comparative study on the behavior of tensegrity grids through geometric nonlinear analysis (GNA) and combined nonlinear analysis (CNLA) (geometric and material), considering the possible effect of evolution in the elasto-plastic domain of the cable elements. The effect of the relaxation of cable on the amplification of the displacement of these grids was taken into account. The updated Lagrangian formulation, which modifies the Newton-Raphson iterative scheme with incremental loading, was adopted. We have developed a numerical computational model specific to tensegrity structures that simulates the geometric and material nonlinear behavior. The reliability of the calculation tool developed has been validated. Additionally, the results of the application of the numerical model on a grid, which was generated based on demi-cuboctahedral tensegrity cells, are presented.