Numerical Design Of Experiments Research Articles

Analyzing Homogeneity of Highly Viscous Polymer Suspensions in Change Can Mixers.

The mixing of highly viscous non-Newtonian suspensions is a critical process in various industrial applications. This computational fluid dynamics (CFD) study presents an in-depth analysis of non-isothermal mixing performance in change can mixers. The aim of the study was to identify parameters that significantly influence both distributive and dispersive mixing in these mixers, which are essential for optimizing industrial mixing processes. The study employed a numerical design of experiments (DOE) approach to identify the parameters that most significantly influence both distributive and dispersive mixing, as measured by the Kramer mixing index (MKramer) and the Ica Manas-Zloczower mixing index λMZ¯. The investigated parameters included mixing time, number of arms, arm size ratio, revolutions per minute (RPM), z-axis rotation, z-axis movement, and initial and mixing temperatures. The methodology involved employing the bootstrap forest algorithm for predicting the mixing indices, achieving an R2 of 0.949 for MKramer and an R2 of 0.836 for λMZ¯. The results indicate that the z-axis rotation has the greatest impact on both distributive and dispersive mixing. An increased number of arms negatively impacted λMZ, but had a small positive effect on MKramer. Surprisingly, in this study, neither the initial temperature of the material nor the mixing temperature significantly impacted the mixing performance. These findings highlight the relative importance of operational parameters over traditional temperature factors and provide a new perspective on mixing science.

A numerical investigation of energy dissipation mechanism of visco-hyperelastic bimaterials subjected to low-velocity impact

Impact protection equipment typically relies on the material failure mechanism and is frequently discarded after the impact. A promising alternative emerges utilizing a foam-infilled lattice bimaterial with shape recovery trait and customizable impact protection capability. This study employs a numerical approach to elucidate the energy dissipation mechanism exhibited by the bimaterial under low-velocity impact condition. The experiment-based inverse method is used to characterize visco-hyperelastic models for two base materials. The investigation reveals that the interaction between the two base materials significantly amplifies the foam’s energy dissipation capability, resulting in an overall higher energy dissipation for the bimaterial. Besides, the study establishes a close correlation between the bimaterial’s effective viscoelastic properties and the enhancement in energy dissipation. Furthermore, the numerical design of experiments (DOE) analysis of base material properties indicates that there is an optimal region for selecting the critical foam material constants for a significant improvement of bimaterial energy dissipation. The results reveal that the combination effect of material interaction and material viscoelastic properties constitutes the fundamental elements of bimaterial energy dissipation mechanism. The insight derived from this study can inform the future design and material selection of a more complicated bimaterial across a wide range of impact protection applications.

Helical airfoil corrugated tubes: A numerical comparison with common corrugated profiles and geometrical optimization by multi-objective algorithm

In this study, helical airfoil corrugated tube (HACT) has suggested to improve the heat transfer capabilities of the tube heat exchanger. Firstly, thermal-hydraulic performance of HACT is numerically compared with common helical corrugated tube (HCTs) such as helical semi-ellipse corrugated tube (HSECT), helical semi-circle corrugated tube (HSCCT) and smooth tube based on thermal performance parameters: Nusselt number (Nu), friction factor (f) and performance evaluation criteria (PEC). Helium under high Reynolds number (Re) is the working fluid of this study. By analyzing the numerical outcomes, it is found that HACT has the heat transfer coefficient roughly 4 % higher than that of HSECT, around 5 % higher than that of HSCCT and more than 60 % higher than that of smooth tube. Then, a multi-objective optimization (MOO) is carried out to optimize the geometrical configuration of HACT. Initially, a numerical experimental design is constructed using the Box-Behnken method within the response surface methodology (RSM), focusing on two objectives and three factors. Subsequently, significant regression models (SRM) are derived via analysis of variance (ANNOVA). Then, leveraging these significant regression models of Nu and PEC, the geometric optimization of HACT is executed using Non-dominated Sorting Genetic Algorithm (NSGA-II), ultimately leading to the attainment of the Pareto front. Finally, based on Pareto optimal set, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied for decision-making involving multiple objectives.

Coupled thermo-hydro-mechanical modeling on geothermal doublet subject to seasonal exploitation and storage

Combining the conventional high-temperature aquifer thermal energy storage system with the common geothermal reservoir development system is a potential alternative to increase energy access, but effects of natural parameters like fracture aperture and reservoir permeability and development parameters like flow rate and injection temperature on the efficiency of energy exploitation and storage have seldomly been investigated. In this study, three assessment parameters and three evaluation criteria were defined to evaluate the sustainability and efficiency of deep geothermal reservoirs with seasonal energy exploitation and storage, and a robust approach of optimizing the development parameters was proposed by combining numerical reservoir model, experimental design and surrogate model, and multiple response optimization method. Based on a case study of the geothermal doublet in Tsinghua University, China, the robustness and reasonability of the developed optimization method were demonstrated. The results show that the optimal development parameters can not only maximize the total recoverable energy and effective recovery efficiency, but also satisfy the requirements of sustainably developing deep geothermal reservoirs. The recoverable heat energy can increase about 20% by adding artificial thermal storage into geothermal reservoir development. Therefore, it is strongly recommended to add energy storage into the future geothermal reservoir development system.

Uncertainties of band sound levels when estimated from monochromatic outdoor sound propagation calculations

Octave band and third octave bands sound levels are widely used in environmental acoustics, and most numerical models for outdoor sound propagation estimate them through the combination of several monochromatic calculations. As some of these models can be very time consuming when long range distance calculations are needed, the number of monochromatic calculations performed for each band is often necessarily very limited. That induces uncertainties on the estimate of the noise level of the band that can be large when the spectrum amplitude varies widely inside a band. This is the case for example when interferences due to ground effects occur. The paper presents estimates of these uncertainties depending on frequency band and on source-receiver locations. The uncertainties are evaluated thanks to a quasi Monte-Carlo technique from many calculations using a Rudnick propagation model and a Latin Hypercube Sampling numerical experimental design for input parameters (source-receiver locations). The results provide practical indications on the minimum number of monochromatic calculations to do per band, in order not to exceed a given uncertainty level.

Research on In-Plane Deformation Performance of Rotating Honeycomb Structures.

Most natural materials have rotational and hierarchical properties, so they can show excellent mechanical properties such as shear resistance and impact resistance. In order to further improve the energy absorption characteristics of vibration absorbing structures, a new type of honeycomb structure with integral rotation and group rotation is designed and characterized. The effects of the geometrical parameters of rotation Angle on the impact deformation mode, stress response curve and energy absorption characteristics of the honeycomb structure are studied through numerical simulation and experimental design. The results show that the overall honeycomb performance of 15° is better than that of 0°, the specific energy absorption is the results show that the overall honeycomb performance of 15° is better than that of 0°, the specific energy absorption is increased by 6%, the bearing capacity is increased by 320 N, and the crushing force efficiency is increased by 2%. Compared with the whole cell and the group cell, the specific absorption energy increased by 35%, 73% and 71%. The results of this paper provide a new insight into the impact performance of monolithic and grouped rotating honeycomb structures, which is helpful for the results of this paper provide a new insight into the impact performance of monolithic and grouped rotating honeycomb structures, which is helpful for the optimization of crashworthiness structural design.

Analytical solutions for maximum fresh groundwater extraction in stratified coastal aquifers

Existing analytical solutions for defining maximum freshwater extraction in coastal aquifers mostly presume a homogeneous aquifer. In this study, analytical solutions for the pumping-induced interface toe position and the maximum pumping rate of a single well in stratified coastal aquifers are developed, based on the potential theory and the analytical solution proposed by Rathore et al. (2020), where aquifer stratification is concisely characterized by the total transmissivity and the transmissivity centroid elevation (hereafter “TCE”). Three typical aquifer domain scenarios are examined, including semi-infinite, infinite-strip, and rectangular coastal aquifers. The sensitivity analysis based on the proposed analytical solutions demonstrates that in all aquifer domain scenarios, a lower TCE leads to a more seaward interface toe and a larger maximum pumping rate, while the impact of total transmissivity is complicated, depending on the type of the inland boundary condition. The effect of inland and lateral boundary conditions on the maximum pumping rate is enhanced in the stratified aquifers of lower total transmissivity and TCE. Importantly, the boundary effects can be eliminated by properly defining the size of the stratified aquifer domain, providing valuable guidance for the design of numerical models and laboratory experiments that are often of finite sizes. Our analytical solutions can serve as a simple tool for the first-order assessment of allowable freshwater extraction in stratified coastal aquifers.

Prediction of thermo-mechanical performance for effusion cooling by machine learning method

Fast and accurate evaluation of performance of cooling structures is very critical to the design of hot-section components in gas turbines. In the present study, machine learning method was developed to predict thermo-mechanical performance for effusion cooling on flat plate. The geometric and thermodynamic parameters including blowing ratio, density ratio, hole inclination angle, hole pitch and spacing were studied. Latin hypercube sampling was used for the design of numerical experiments, and the data sets for training model were generated by computational fluid dynamics (CFD) solutions. A kind of deep neural networks (DNNs) was used to predict the distributions of solid temperature and stress. Based on the outputs of neural network, the effects of the geometric and thermodynamic parameters on thermo-mechanical performance were investigated in detail. The results show that thermal stress decreases with the increases of density ratio and blowing ratio, while the increases of hole spacing and pitch cause the increase of thermal stress. Compared with the CFD results, the proposed DNN method has mean absolute percent error of 0.5% and 0.08% and root mean square error of 6.95 K and 5.1 MPa as applying for predicting solid temperature and stress. On the whole, machine learning is a promising method for modelling effusion cooling with high accuracy.

Transfer learning-based crashworthiness prediction for the composite structure of a subway vehicle

Due to the lack of load/displacement sensors in a complex and uncertain crash test/accident of rail vehicles (e.g., vehicle-to-vehicle or train-to-train collision), only structural deformation images can be obtained while the crashworthiness indicators (e.g., force, displacement, energy absorption) cannot be measured directly. This paper aims to propose a transfer learning-based inverse method for extracting the structural parameters and crashworthiness characteristics by the deformed pictures of energy-absorbing structures. A finite element model of an energy-absorbing structure was firstly established and calibrated by experiments. Then, a number of deformation images were captured from the numerical design of experiment (DOE) through coding languages, which were saved as TFRecord format to reduce the computational time during the training of transfer learning models (i.e., VGG16, LetNet, AlexNet and ResNet50). The result showed that the transfer learning model, ResNet50, exhibited the best performance with R2 of 0.736 and 0.981, respectively, for predicting the structural parameters and crashworthiness characteristics. In addition, the number of full connection layers should be reasonably selected on the premise of maintaining accuracy and efficiency. A group of deformation pictures were randomly used as samples to validate the prediction of structural parameters and crashworthiness through the trained transfer learning model, where good consistence was observed. The proposed method is expected to bring the image recognition and big data prediction into the design and test of composite energy-absorbing structures, thus, auxiliary improve the crashworthiness of rail vehicles.

Application and assessment of divide-and-conquer-based heuristic algorithms for some integer optimization problems

In this paper three heuristic algorithms using the Divide-and-Conquer paradigm are developed and assessed for three integer optimizations problems: Multidimensional Knapsack Problem (d-KP), Bin Packing Problem (BPP) and Travelling Salesman Problem (TSP). For each case, the algorithm is introduced, together with the design of numerical experiments, in order to empirically establish its performance from both points of view: its computational time and its numerical accuracy.

A modeling framework to understand historical and projected ocean climate change in large coupled ensembles

Abstract. The ocean responds to climate change through modifications of heat, freshwater and momentum fluxes at its boundaries. Disentangling the specific role of each of these contributors in shaping the changes of the thermohaline structure of the ocean is central for our process understanding of climate change and requires the design of specific numerical experiments. While it has been partly addressed by modeling studies using idealized CO2 forcings, the time evolution of these individual contributions during historical and projected climate change is however lacking. Here, we propose a novel modeling framework to isolate these contributions in coupled climate models for which large ensembles of historical and scenario simulations are available. The first step consists in reproducing a coupled pre-industrial control simulation with an ocean-only configuration, forced by prescribed fluxes at its interface, diagnosed from the coupled model. In a second step, we extract the external forcing perturbations from the historical+scenario ensemble of coupled simulations, and we add them to the prescribed fluxes of the ocean-only configuration. We then successfully replicate the ocean's response to historical and projected climate change in the coupled model during 1850–2100. In a third step, this full response is decomposed in sensitivity experiments in which the forcing perturbations are applied individually to the heat, freshwater and momentum fluxes. Passive tracers of temperature and salinity are implemented to discriminate the addition of heat and freshwater flux anomalies from the redistribution of pre-industrial heat and salt content in response to ocean circulation changes. Here, we first present this general framework and then apply it to the IPSL-CM6A-LR model and its ocean component NEMO3.6. This framework brings new opportunities to precisely explore the mechanisms driving historical and projected ocean changes within single climate models.

Benchmark solutions for stochastic dynamic responses of rectangular Mindlin plates

There exist some researches on the benchmark responses of moderately thick plates based on Mindlin theory under static loads. In practice, rectangular Mindlin plates are often subjected to various random excitations. However, the benchmark solutions of analytically stochastic dynamic responses for rectangular Mindlin plates under random excitations were not investigated. In this paper, analytical power spectral density functions and root mean squares for stationary and nonstationary stochastic responses of rectangular Mindlin plates are derived, which provide benchmark solutions for other numerical methods and experimental design. Firstly, based on the closed-form free vibration analyses of rectangular Mindlin plates with two opposite simply supported edges, exact natural frequencies and modal shapes are obtained. Then, the pseudo excitation method is introduced into the decoupled differential equations of motion. By combining the exact solutions of free vibration, the analytical method for random vibration analysis of elastic Mindlin plate is proposed, and the analytical stochastic responses are derived. Due to the low efficiency of the AM based on symbolic operation, the efficient discrete analytical method, which can ensure that the results are exact in the spatial domain, is further developed. Finally, the performance of the proposed approaches is verified by comparing with the commercial software, Monte Carlo simulation, and literature. The remarkable effects of spatial distributions of excitations on the stochastic responses of Mindlin plates are illustrated. The important influences of parameters including relative thickness, elastic modulus, and boundary constraint degree on responses are revealed.

Thermo‐solutal Marangoni convective assisting/resisting flow of a nanofluid with radiative heat flux: A model with heat transfer optimization

AbstractThe mixed Marangoni assisting/resisting flow of a nanofluid with thermal radiative heat flux is analyzed when thermal and solutal buoyant forces are significant. The heat and mass transfer rates are simultaneously optimized by utilizing the Response Surface Methodology (RSM). The face‐centered Central Composite Design (fc‐CCD) is used for the numerical experimental design involved in RSM. The sensitivities of the heat and mass transfer rates are evaluated to compare the impact of the thermal and solutal buoyant forces. Appropriate scaling and similarity transformations are utilized to simplify the problem and then numerical solutions are obtained. The nanoliquid flow, temperature, and concentration profiles are plotted for the buoyancy assisting and opposing Marangoni cases. The Marangoni flow with opposite buoyancy is found to have a greater magnitude of velocity while the flows assisted by the buoyancy have a greater magnitude of temperature and concentration profiles. Thermal buoyancy force has a predominant (0.6%) impact on both heat and mass transfer rates compared to solutal buoyancy force. Buoyancy forces are positively sensitive to heat and mass transfer rates. The thermal radiation aspect augments the temperature profile throughout the domain. The optimized mass and heat transfer rates ( and ) is achieved at the highest level of the buoyancy forces and ratio of Marangoni numbers.

Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading

A multilevel performance-based design (PBD) framework is developed for panels of Protective structures subjected to air blast. These provisions improve the existing design approach of blast resistance structures for ultimate limit state. Present study develops probabilistic deflection-based capacity and demand models for three performance levels associated with four damage states occurring during an air blast. The chosen protective structures for current study are reinforced Normal Strength Concrete (NRC) and reinforced Ultra-High Strength Concrete (UHSC) panels. The probabilistic models are developed using Bayesian inference (Posterior Statistics). The database is generated through numerical experimental design using finite element (FE) based software, LS-DYNA. The influence of air blast on panel is validated on a panel and obtained results shows the trustworthiness of numerical model. Grounded on these models the fragility estimation is carried out and attained plots demonstrates the consistency. Using a reliability based approach, the Load and Resistance Factors for Design (LRFD) are developed associated with the proposed three performance levels. Hazard curves and total probability are estimated using established dataset from literature available. The estimated LRFD factors can be used for the design of NRC & UHSC panel of slab/walls of protective structure subjected to air blast.

Numerical and Experimental Investigations of Humeral Greater Tuberosity Fractures with Plate Fixation under Different Shoulder Rehabilitation Activities

The incidence of humerus greater tuberosity (GT) fractures is about 20% in patients with proximal humerus fractures. This study aimed to investigate the biomechanical performances of the humerus GT fracture stabilized by a locking plate with rotator cuff function for shoulder rehabilitation activities. A three-dimensional finite element model of the GT-fracture-treated humerus with a single traction force condition was analyzed for abduction, flexion, and horizontal flexion activities and validated by the biomechanical tests. The results showed that the stiffness calculated by the numerical models was closely related to that obtained by the mechanical tests with a correlation coefficient of 0.88. Under realistic rotator cuff muscle loading, the shoulder joint had a larger displacement at the fracture site (1.163 mm), as well as higher bone stress (60.6 MPa), higher plate stress (29.1 MPa), and higher mean screw stress (37.3 MPa) in horizontal flexion rehabilitation activity when compared to that abduction and flexion activities. The horizontal flexion may not be suggested in the early stage of shoulder joint rehabilitation activities. Numerical simulation techniques and experimental designs mimicked clinical treatment plans. These methodologies could be used to evaluate new implant designs and fixation strategies for the shoulder joint.

Study of the effect of mechanical uncertainties parameters on performance of PEMFC by coupling a 3D numerical multiphysics model and design of experiment

As the PEMFC is a complex multi-physics device whose reliability and durability depend on the thermal-mechanical-electrical and chemical parameters. In this paper, theoretical and numerical studies is proposed to optimize the fuel cell performance using multiphysics model and design of experiments. 3D finite element analysis including a fully coupling of thermal-electrical-mechanical model is proposed to predict the electrical resistance of fuel cell. As the mechanical parameters (bending radius of the bipolar plate, thickness of the GDL and clamping pressure) remain uncertain, the design of experiments procedure is used to optimize the fuel cell behavior under several conditions.

Experimental study of damage to ultra-high performance concrete slabs subjected to partially embedded cylindrical explosive charges

In this study, long and thin cylindrical charges were partially embedded in ultra-high-performance concrete (UHPC) and normal-strength concrete (NSC) slabs to investigate the damage characteristics of UHPC slabs subjected to explosions by conventional weaponry. The sizes of ejection and spalling craters were recorded after the experiment to compare the obtained data with the concrete slab damage characteristics predicted by current damage forecasting methods. The current damage forecasting methods were found to be unsuitable for the conditions considered in this study as they do not account for the effects of the explosive shape and depth of embedment (DOE) simultaneously. The results of the experiment using partially embedded charges indicated that the damage on the sides of the slabs decreased with decreasing slab thickness; the use of UHPC without fiber reinforcement instead of using NSC significantly increased the compressive strength but decreased the ability of the concrete structure to resist spalling damage; furthermore, a suggested estimation of the cone slope angle is 60° for theoretical analyses and the design of numerical simulation or field experiments.

Analysis of factors influencing on performance of solid tires: Combined approach of Design of Experiments and thermo-mechanical numerical simulation

Excessive loading conditions and internal heat build-up are the major causes of failures in solid resilient tires. Both operational and design related factors can affect tire performance including internal stress generation and heat build-up. In spite of their limitations, experimental techniques are still the most common method of identifying the factors that affect tire performance. This study explores a combined approach of numerical modelling and Design of Experiments (DoE) to identify the impact of several key design and operational factors on the performance of solid tires under different temperature levels. First, 3D Finite Element (FE) static and thermal models of the solid resilient tires are developed by incorporating suitable temperature dependent hyperelastic material models and relaxation properties. The temperature-dependent mechanical behaviours of rubber material are obtained by using Dynamic Mechanical Analyzer (DMA) and the William Landel Ferry (WLF) parameters. The developed FE thermal model is used to predict the tire performance, including the tire blasting region, which is then validated with experimental data. Secondly, a two-level fractional factorial DoE analysis is developed using response readings of maximum stresses, deformations and contact pressure obtained from the validated FE thermal model. The factors used in the DoE include the number of rubber layers, applied load, rolling speed, ramp angle and aperture level. The results provide optimal operational and design parameters of the solid resilient tire at different environmental temperatures and show the potential for considerable stress reduction with minimal changes to tire deformation and contact area. These results highlight the capability of the combined FEM and statistical design approach to drastically reduce the number of physical experiments required for obtaining optimal tire performance thus saving significant time and cost.

Numerical experimental design application in consequence analysis of ammonia leakage

Ammonia is a colorless gas, corrosive, and highly toxic. This compound can cause irreversible consequences for humans and the environment depending on the concentration. Currently, accidents involving ammonia leakage in industrial facilities are recurring. Thus, outlining contingency and mitigation strategies is crucial for the industry. In this work, we performed several simulations of ammonia leakage scenarios using the ALOHA® 5.4.7 software. Moreover, we propose a well-validated model with significant parameters to estimate the gas cloud volume for a range of environmental and leak conditions. The simplicity of this model facilitates its utilization and may enrich risk analysis and help in proposing adequate safety measures for specific atmospheric and leakage conditions.

Probabilistic demand models and performance-based fragility estimates for concrete protective structures subjected to missile impact

The manifold missile attacks upon structures and deficiency of codal provisions motivated the current study to develop probabilistic demand models for protective structures subjected to hard missile impact. These energy-based models are estimated using a defined performance-based design framework (PBD) with three performance levels associated with four damage states, i.e. from minor damage to total collapse. The evaluation of unknown model parameters is constructed using the Bayesian approach. The current and upcoming range of structural variables is chosen for numerical experimental design. LS-DYNA, a finite element (FE) numerical method, is used to generate necessary probabilistic data of Reinforced Concrete (RC) & Prestressed Concrete (PC) panels subject to a hard missile. Novel formulations for local damages of a target, such as perforation limit of RC panel & Ballistic limit of the missile for RC & PC panels, are estimated. The developed demand models are used to assess the fragility estimation of either panel under chosen performance levels for a containment structure located in Tarapur, Palghar, India. An accurate fragility plot and comparative study shows the consistency of probabilistic models with test results. These models consider aleatory and epistemic uncertainties in modeling, material & geometrical properties, strain rate & inertia effect, and complex interaction involved in an impact scenario.