Numerical Analysis Research Articles

Assessment of a Full-Electric Floating Liquefied Natural Gas Concept for Harsh Sea State Conditions at Remote Ultra-Deepwater Locations

_ This work describes an offshore gas monetization solution for harsh environmental conditions at ultra-deepwater and remote locations, as an alternative to conventional onshore plants associated with long subsea pipelines for Greenfield projects. Although gas-to-liquids and marine compressed natural gas are initially evaluated, associated gas is supposed to be exported from deepwater floating production storage and offloading units to a central floating liquefied natural gas (FLNG) facility for additional treatment, fractionation, and liquefaction, producing liquefied natural gas (LNG) and liquefied petroleum gas (LPG) for further tandem offloading. To demonstrate the technical feasibility of the proposed FLNG, its key technologies are reviewed, including liquefaction process selection, cargo containment system, station-keeping, offloading, and power generation. A full-electric FLNG is proposed, replacing conventional feed gas power generation systems with inner hull nuclear power modules, envisaging neutral CO2 emissions and earlier first LNG drop milestone achievement. The FLNG general arrangement is developed, along with its internal cargo tanks layout, for preliminary LNG and LPG production rundown and feed gas throughput. Numerical analyses are carried out to show that static and dynamic tilt criteria can be met, even for harsh sea states. Gas import riser configurations for the challenging ultra-deepwater location are outlined, after appropriate FLNG station-keeping analyses, in addition to a feasibility assessment of seawater intake risers, aiming for an overall gas plant efficiency increase. Keywords FLNG; FPSO; LNG/LPG; associated gas; design (general)

Numerical and Thermodynamic Analysis of the Effect of Operating Temperature in Methane-Fueled SOFC

This study examines the thermodynamic and numerical analyses of a methane-fed solid oxide fuel cell (SOFC) over a temperature range varying between 873 K and 1273 K. These analyses were conducted to investigate and compare the performance of the SOFC under various operating conditions in detail. As part of the thermodynamic analysis, important parameters such as cell voltage, power density, exergy destruction, entropy generation, thermal efficiency, and exergy efficiency were calculated. These calculations were used to conduct energy and exergy analyses of the cell. According to the findings, an increase in operating temperature led to a significant improvement in performance. At the initial conditions where the SOFC operated at a temperature of 1073 K and a current density of 9000 A/m2, it was observed that when the temperature increased by 200 K while keeping the current density constant, the power density increased by a factor of 1.90 compared to the initial state, and the thermal efficiency increased by a factor of 1.45. Under a constant current density, the voltage and power density values were 1.0081 V, 1.0543 V, 2337.13 W/m2, and 2554.72 W/m2 at operating temperatures of 1073 K and 1273 K, respectively. Under a current density of 4500 A/m2, the entropy generation in the cell was determined to be 29.48 kW/K at 973 K and 23.68 kW/K at 1173 K operating temperatures. The maximum exergy efficiency of the SOFC was calculated to be 41.67% at a working temperature of 1273 K and a current density of 1500 A/m2. This study is anticipated to be highly significant, as it examines the impact of temperature variation on exergy analysis in SOFC, validating both numerical and theoretical results, thus providing a crucial roadmap for determining optimized operating conditions.

A Low-Rank Matrix Approach to Compute Polynomial Approximations of Smooth Two-Dimensional Functions

Polynomial approximation of smooth functions is becoming increasingly important in fields like numerical analysis and scientific computing. These approximations are vital in models that rely on spectral methods. To reduce the memory costs for large dimensional problems, various methods to provide data-sparse representations have been proposed, including methods based on singular value decomposition, adaptive cross approximation, and matrices with hierarchical low-rank structures, to mention a few. This work presents implementation details on the polynomial approximation of univariate smooth functions through the Polynomial1 class, and of bivariate smooth functions by low-rank matrix representation via the Polynomial2 class. These approaches are explained within Tau Toolbox, a mathematical software library for solving integro-differential problems by the spectral Tau method.

Research on seismic performance of prefabricated composite shear wall with end steel plate connection

Chinese construction industry is gradually transforming to industrialization, which promotes the development of prefabricated buildings. As an efficient lateral force resisting system, prefabricated steel-plate concrete composite shear wall structure has become a research hotspot in the field of architecture at home and abroad. Based on the mechanical characteristics of the shear wall, this paper proposes a end steel plate connection prefabricated composite shear wall structure. Through numerical simulation and analysis of the prefabricated composite shear wall with different connection areas and the cast-in-place composite shear wall, which verified the feasibility and reliability of end steel plate connection. Based on the above verification, the influence of different parameters on the seismic performance of the prefabricated composite shear wall with end steel plate connection has been further studied, and the theoretical calculation of bearing capacity is carried out. The results show that the length of the connector should be controlled within a reasonable range. The tie bars in the node connection area can improve the strength and ductility of the prefabricated composite shear wall. The aspect ratio and axial pressure ratio have obvious influence on the seismic performance of the wall, which should be reasonably selected in design.

Improving the accuracy of predictions in multivariate time series using dynamic vine copulas

In this work, we deal with non-stationary multivariate time series, proposing a method which uses copulas to produce more accurate forecasting. The idea is to apply a copula-based approach to identify change points and then split the time series into consecutive segments based on these change points. In each segment, we define the best-fitting copula family and forecast values of the time series of each segment using the corresponding fitting copula. We apply our model to a financial data set to test the predictive power of our approach. A simulation study is also presented for a detailed illustration and assessment of our proposed methodology. Based on the results of numerical analysis, we observed that our proposed approach will help us to improve the accuracy of forecasting in comparison with other existing methods such as traditional time series forecasting as well as neural network forecasting.

Standalone gradient measurement of matrix norm for programmable unitary converters

Programmable unitary converters are powerful tools for realizing unitary transformations, advancing the fields of computing and communication. The accuracy of these unitary transformations is crucial for maintaining high fidelity in such applications. However, various physical artifacts can impair the accuracy of the synthesized transformations. A commonly employed approach uses the system’s gradient to restore accuracy. Matrix norm is used to define error between matrices, and minimization of this norm using the gradient restores the accuracy. Although this gradient can indeed be physically measured using external equipment, it leads to a rather complex optical system. In this study, we propose a standalone method for measuring matrix norm gradients, where “standalone” means that no additional optical equipment is needed. This method is based on the mathematical fact that the central difference, which is generally used for the approximation of differentiation, can yield exact differentiation for any unitary converters. Furthermore, we introduce a new matrix distance that is suitable for optimizing unitary converters that use intensity detectors at the output. This distance also yields the exact differentiation with the central difference. Numerical analysis demonstrates that our method exhibits orders of magnitude higher tolerance to measurement noise than prior similar approaches.

Numerical Analysis of Blast Behavior for Non-ideal Explosive ANFO in Shock-Tube Test

In an explosion test using a shock tube, the behavior of pressure waves can be reproduced with high reliability. However, the explosion in a shock tube occurs in a confined space. It is difficult to predict the behavior of pressure waves and its effect on various concrete specimens by using the research findings related to free-field explosions. Moreover, few studies have focused on explosive-driven shock tubes. In this study, the behavior of pressure waves in a shock tube was numerically analyzed using a finite-element analysis program. The explosive used to generate the pressure waves was an ammonium nitrate fuel oil (ANFO), which exhibits non-ideal explosion characteristics. The Jones–Wilkins–Lee (JWL) and ignition-and-growth (I&G) equations of state were used for blast-pressure calculation. The analysis results were affected by factors such as the release rate of explosive energy and the development of the pressure waves in the confined explosion. The blast behaviors, such as the low release rate of explosive energy and the resulting increase in the impulse, were analyzed using the ignition-and-growth equation. The impulse produced during the development of waves reflected by the block installed at the tube inlet exceeded that produced by the tube wall. Such behaviors that occurred at the beginning of a blast affected the process of wave propagation along the shock tube and the wave reflection due to the test specimen at the outlet of the shock tube. In this study, the blast behavior in the shock tube, which could be referenced for the analysis of blast overpressure and its effect on concrete specimens, was numerically analyzed. Further research on the structural behaviors of concrete specimens due to blast overpressure is needed.

Robust damping improvement against the vortex-induced vibration in flexible bridges using multiple tuned mass damper inerters

The tuned mass damper inerter (TMDI) is considered as one of countermeasures to mitigate the very-low-frequency vertical bending vortex-induced vibration (VIV) in flexible bridges. However, the control robustness of the TMDI against the system uncertainty is a serious concern due to the limited inerter span capacity. In this paper, the multiple tuned mass damper inerter (MTMDI) is used instead of identical TMDIs to provide a robust equivalent damping ratio against the uncertain VIV within the entire lock-in wind speed range. A design framework of the MTMDI considering the inerter span length is proposed based on a universal VIV model suitable for the fully closed, centrally slotted, and semi-closed box decks. In the framework, the fluctuation of VIV characteristics with the wind speed, the probability of occurrence of the VIV, and the uncertainties in VIV characteristics and deck dynamics are considered, simultaneously. Two objection functions are defined to focus on the maximizing the equivalent damper ratio and reducing the VIV mitigation failure, respectively. Finally, numerical analysis of a flexible bridge-MTMDI system subjected to the VIV is performed. The results show that the wind speed probability distribution plays a role of weighting coefficient in the MTMDI optimization. The choice of the objective function depends on the mass ratio of the MTMDI and the level of the system uncertainty. The well-optimized MTMDI achieved a more robust control result than the TMDI within the entire lock-in wind speed range.

Discrete element model for effective electrical conductivity of spark plasma sintered porous materials

AbstractThis paper aims to analyse electrical conduction in partially sintered porous materials using an original resistor network model within discrete element framework. The model is based on sintering geometry, where two particles are connected via neck. Particle-to-particle conductance depends on neck size in sintered materials. Therefore, accurate evaluation of neck size is essential to determine conductance. The neck size was determined using volume preservation criterion. Additionally, grain boundary correction factor was introduced to compensate for any non-physical overlaps between particles, particularly at higher densification. Furthermore, grain boundary resistance was added to account for the porosity within necks. For numerical analysis, the DEM sample was generated using real particle size distribution, ensuring a heterogeneous and realistic microstructure characterized by a maximum-to-minimum particle diameter ratio of 15. The DEM sample was subjected to hot press simulation to obtain geometries with different porosity levels. These representative geometries were used to simulate current flow and determine effective electrical conductivity as a function of porosity. The discrete element model (DEM) was validated using experimentally measured electrical conductivities of porous NiAl samples manufactured using spark plasma sintering (SPS). The numerical results were in close agreement with the experimental results, hence proving the accuracy of the model. The model can be used for microscopic analysis and can also be coupled with sintering models to evaluate effective properties during the sintering process.

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem.

Julia is a general purpose programming language that was designed for simplifying and accelerating numerical analysis and computational science. In particular the Scientific Machine Learning (SciML) ecosystem of Julia packages includes frameworks for high-performance symbolic-numeric computations. It allows users to automatically enhance high-level descriptions of their models with symbolic preprocessing and automatic sparsification and parallelization of computations. This enables performant solution of differential equations, efficient parameter estimation and methodologies for automated model discovery with neural differential equations and sparse identification of nonlinear dynamics. To give the systems biology community easy access to SciML, we developed SBMLToolkit.jl. SBMLToolkit.jl imports dynamic SBML models into the SciML ecosystem to accelerate model simulation and fitting of kinetic parameters. By providing computational systems biologists with easy access to the open-source Julia ecosystevnm, we hope to catalyze the development of further Julia tools in this domain and the growth of the Julia bioscience community. SBMLToolkit.jl is freely available under the MIT license. The source code is available at https://github.com/SciML/SBMLToolkit.jl.

Recent Patents for Machine Vision Inspection in the Machine Tool Sector

Abstract:: In the current modern manufacturing industry, the demand for product quality control is increasing, as is the need for automation. However, the manual inspection may need to be noticed or undetectable in the complex production process. To solve this phenomenon, machine vision-based inspection of machine tools and their product features has become one of the key technologies in intelligent manufacturing. The basic principle of machine tool machine vision inspection is to transmit the object to be inspected to the computer through efficient image acquisition. Then, image processing or deep learning algorithms classify, locate, segment, and process the features of the thing. Finally, the computer makes the judgment of whether it is qualified. According to recent numerical analysis data, compared with traditional methods, machine tool machine vision inspection can improve the inspection efficiency by 30%, and the accuracy has reached 98%, much higher than manual inspection accuracy. This study provides an in-depth review of representative patents and machine tool vision inspectionpatents , and it comprehensively summarizes the research results from various dimensions in recent year. In the past five years, the average annual growth rate of machine tool vision inspection technology has reached 15%, showing the rapid development momentum of this field. The research content mainly focuses on designing vision detection structures, algorithm optimization designs, and personalized solutions for object differences.

Optical evaluation of internal damage to human hair based on second near-infrared window polarization microscopy.

Hair beauty treatments glorify human life. As a side effect, there is a risk of deteriorating the health of the hair. Optically polarized microscopy has been used for many decades to evaluate hair conditions owing to its ease of use and low operating costs. However, the low biopermeability of light hinders the observation of detailed structures inside hair. The aim of this study is to establish an evaluation technique of internal damages in a hair by utilizing a near-infrared (NIR) light with a wavelength of 1000-1600 nm, called "second NIR window". We built a laser scanning transmission microscope system with an indium gallium arsenide detector, a 1064 nm laser source, and optical circular polarization to visualize the anisotropy characterization of keratin fibres in hair. Samples of Asian black hair before and after bleaching, after permanent-waving, after lithium bromide (LiBr) treatment, and after heating was observed. Some parameters reflecting intra-hair damage were quantitatively compared with the parameters in digitally recorded images with analytical developments. The light transmittance of black hair was dramatically improved by utilizing the second NIR window. Numerical analysis of circular polarization in hair quantified the internal damage in chemically or thermally treated hair and found two different types of damage. The present method enabled quantitative evaluation of the condition changes in the cortex; for example, a decrease in circular polarizability by LiBr treatment and restoration by replacing the LiBr solution with water. In addition, black speckles were observed after the heat treatment. Longer heating and wetting times increased the appearance probability and size of the speckles. According to quantitative analyses, the emergence of black spots was independent of polarizability changes, indicating that they were not pores. Circular polarization microscopy based on near-infrared optics in the second NIR window provides an effective evaluation method for quantifying intra-hair damage caused by cosmetic treatments. The present method provides noninvasive, easy, and inexpensive hair evaluation and has potential as a gold standard in hair care research/medical fields.

Exploring nonlinearity in quarter car models with an experimental approach to formulating fractional order form and its dynamic analysis.

This study explores the inherent nonlinearity of quarter car models by employing an experimental and numerical approach. The dynamics of vehicular suspension systems are pivotal for ensuring passenger comfort, vehicle stability, and overall ride quality. In this paper we assessed the impact of various parameters and components on suspension performance, enabled the optimization of ride comfort, stability, and handling characteristics. Firstly, experimental analysis allowed for the investigation of factors that are challenging to model theoretically, such as stiffness nonlinearity and damping characteristics, which may vary under different operating conditions. Time domain and frequency response diagram of the model has been obtained. Secondly, a quarter-car with single degree-of-freedom presented and investigated in fractional order form. Fractional order dynamics emphasize nonlinearities in quarter car models, capturing real-world dynamics effectively. The proposed fractional-order nonlinear quarter car model employed Caputo derivative. For numerical analysis of fractional order system, the Adam-Bashforth-Moulton method is used and the disturbance of road assumed to be stochastic. Results show that the dynamic response of the vehicle can be chaotic. Influence of road roughness amplitude and frequency on vehicle vibration is investigated.

Numerical and artificial neural network analysis of tunnel liner design parameters – a comparative study

ABSTRACT This paper proposes the development of an analytical-based Artificial Neural Network (ANN) model for predicting the concrete segmental lining parameters and comparing it with the finite element method, Rocscience tool. To achieve this aim, the dataset was prepared for twelve different loading conditions using the analytical equations by Muir Wood and Curtis. Using this dataset, an ANN model was developed for predicting the segmental lining parameters, viz. displacement, bending moment, axial and shear force. Furthermore, the Rocscience tool was used to analyse the aforementioned design parameters, and the results of these two methods were compared and summarised. It is found that the developed ANN model shows reasonable results of liner design parameters with the Rocscience program. The efficiency of both techniques was evaluated using the statistical measures viz. Mean Absolute Error, Root Mean Square Error, and Coefficient of Efficiency. It is observed that the ANN model is best fitted for the prediction of liner shear and axial force, while it could not find the optimised solution for liner displacement and bending moment. The finding of this study showed that the developed ANN model can be applied to predict the tunnel liner design parameters instead of the alternative complicated and time-consuming techniques.

Heavy rainfall event in Nova Friburgo (Brazil): numerical sensitivity analysis using different parameterization combinations in the WRF model

Heavy rainfall event in Nova Friburgo (Brazil): numerical sensitivity analysis using different parameterization combinations in the WRF model

Numerical Analysis of Time-Dependent Strength and Stiffness in Palm Oil Fuel Ash-Stabilized Soil: Early and Long-Term Effects

Over the years, investigating the behavior of soft soil, stabilized using different techniques, has been recognized as a critical priority for geotechnical engineers. Numerous soil constitutive models have been utilized to simulate stabilized soil behavior, improve strength and ductility, and analyze load-deformation responses. However, further investigation is required to study stabilized soil's time-dependent strength and stiffness, especially at an early curing age. Early strength and stiffness development is crucial in engineering construction for improving building quality and efficiency and minimizing crack risk. Furthermore, estimating UCS from an early age aid in safety evaluation and ground-improvement analysis. Researchers are increasingly recognizing palm oil fuel ash (POFA) as an eco-friendly alternative to traditional soil stabilizers due to its abundant availability. This study proposes an advanced concrete constitutive model to simulate the time-dependent strength and stiffness of POFA-stabilized and cement-stabilized soil due to pozzolanic interactions. The model accurately measures strength and stiffness improvement from an early curing age to 28 days using finite element analysis (FEA) before then comparing the experimental results. Based on the experimental results, the UCS values of palm oil fuel ash-stabilized soil grew to 3.18 MPa and 3.89 MPa after seven and 28 days with an optimum content of 30% (POFA): 10% Magnesium Oxide (MgO). It exhibited a significant increase in early strength with 64.02% compared with cement-stabilized soil. For stiffness results, a slight increment of 9.26% was observed. Employing FEM, the sensitivity of the parameters to stress-strain behavior was investigated. Finally, the validity of the concrete constitutive model to predict the time-dependent strength and stiffness of stabilized soil was proved. Doi: 10.28991/CEJ-SP2024-010-05 Full Text: PDF

Fluid Structure Interaction Analyses of Elevated Storage Tank under Seismic Load

Elevated storage tanks are used to store fresh and waste water, cereal, oil and petrochemical materials. Therefore they serve in a wide area of utilization in this day and age. Analysis of a half full with water elevated storage tank is performed in the scope of this study. The structure is composed of a steel circular storage tank and frame typed steel stager. The structure is under the effect of earthquake loads as well as operational ones. Numerical model is generated by Finite Elements Analysis (FEA) software including fluid and structure parts. The interaction of the parts is provided by Coupled Eulerian Lagrangian (CEL) technique. While the structure constitutes the Lagrangian part, the fluid constitutes the Eulerian part. Interaction of Eulerian and Lagrangian parts are provided by general contact algorithms. Free surface movement of the water, maximum displacements and natural frequency values with related mode shapes of the structure are obtained after numerical analysis. Numerical results are verified by semi-analytical model, where the structure is modelled as single degree of freedom system. The accordance between results is numerically and visually obtained. The turbulent movement of water under the influence of an earthquake is modelled by utilizing the CEL technique. So, the effect of the dynamic pressure induced by the turbulence on the tank and the structural system has been taken into consideration.

Target temperature-based simulation method for predicting performance and designing aircraft thermal anti-icing systems

The prevention of ice build-up on aircraft surfaces is crucial for safe operations. Thermal ice protection systems, particularly electro-thermal systems, are commonly employed to mitigate ice formation. However, the weight of electric batteries used in these systems significantly impacts aircraft performance, necessitating the minimization of power load during design. Despite this requirement, effective anti-icing operation mandates a sufficient heat flux to maintain surface temperature above the freezing point and evaporate any runback water film. Previous research has utilized numerical simulation analysis to predict the performance of electro-thermal anti-icing systems. The conjugate heat transfer method has been commonly employed to predict temperature distribution on the protected surface. However, non-isothermal surfaces exhibit distinct local convective heat transfer coefficients that influence local thermal balance, unlike isothermal surfaces that adopt the loosely-coupled method for computational efficiency. In this study, we present a novel target temperature-based anti-icing simulation method that predicts the required heat flux for thermal ice protection systems without employing the conjugate heat transfer method. Our objective was to calculate the necessary heat flux to achieve the desired non-isothermal surface temperature for effective anti-icing. By eliminating the excessive iteration process associated with the coupling method for conjugate heat transfer, we have streamlined the simulation procedure. Through validation, target temperature-based anti-icing simulation method, when compared to the tight coupling method, demonstrated the ability to predict the same surface water flow rates while reducing computation time by up to 90 %. Furthermore, when applied to design problems, our method achieved approximately a 10 % reduction in the required heat capacity for anti-icing compared to experimental values. As a result, target temperature-based anti-icing simulation method offers a more efficient alternative to traditional conjugate heat transfer methods, providing valuable insights for both predicting anti-icing system performance and optimizing aircraft design.

Effect of temperature on the uniaxial tensile properties of wood plastic composites: Experimental investigation and numerical analysis

Seven groups of uniaxial tensile experiments on wood plastic composites with a High Density Polyethylene (HDPE) matrix at different temperatures were completed in this paper. The test temperatures ranged from -60 °C to 60 °C, with a temperature difference of 20 °C for each group. All samples exhibited tensile brittle fracture. The test results showed that the tensile strength of the specimens decreased continuously with increasing temperature. Taking 0 °C as the reference temperature, the ultimate strength of the sample at -60 °C was 1.63 times that at 0 °C. When the temperature was 60 °C, this value was 0.41. Then, it can be calculated that the ratio of the strength of the sample at -60 °C to that at 60 °C was approximately 3.93, and the corresponding ratio of the elastic modulus was approximately 4.52. This shows that the mechanical properties of WPC are sensitive to changes in temperature. The variation coefficient of the average strength and elastic modulus of WPC for different specimens at different temperatures was less than 0.17, showing good stability due to the small dispersion of mechanical properties among different samples at any specific temperature.

An Optical Detection Model for Stratospheric Airships

This study proposes a numerical model to simulate the thermal characteristics of stratospheric airships (SA). This model introduces a simple yet accurate method for the selection of the optical bands for target detection based on multispectral features. The key to this model is the selection of the spectral bands in which a significant radiation difference exists between the target and its surrounding background. Using the signal-to-noise ratio (SNR), detection probability, and false alarm rate as model evaluation metrics, and based on the analysis of the radiation differences between the target and atmospheric background, it is found that there are two narrow bands possible for SA detection: one with a central wavelength of 8.83 µm and a bandwidth of 0.35 µm and the other with a central wavelength of 11.51 µm and a bandwidth of 0.34 µm. Further numerical simulations and theoretical analyses under varying space environments demonstrate that considerable detection potential can be achieved; thus, the presented optical detection model is useful for the night detection of SA targets.