Computer Simulation Research Articles

The influence of glycine on β-lactoglobulin amyloid fibril formation – computer simulation study

Abstract Amyloids are protein aggregates involved in various protein condensation diseases. Our study aims to investigate the influence of glycine on the fibrillization mechanism of β-lactoglobulin (BLG), a model protein known to form amyloid fibrils from hydrolysed peptides in low pH aqueous solutions. We conducted atomistic molecular dynamics simulations of aqueous solutions of native and unfolded BLG in glycine buffer at pH 2.0. During the simulations we put our focus on analysing protein-protein/buffer interactions, structural electrostatic potential mapping, and the residence times of glycine and glycinium near specific amino acid residues. Glycinium cations were found to preferentially interact with specific protein residues potentially masking the outer disulfide bonds, affecting thiol deprotonation and influencing disulfide scrambling equilibrium. These interactions can potentially hinder hydrolysis and change the fibrillization pathway. Further investigations, such as constant pH MD simulations, simulations on disulfide bounded oligomers are warranted to validate these findings and deepen our understanding of protein aggregation mechanisms.

Mathematical model of velocity and distribution law in gas lift reverse circulation well washing flow field for drilling shaft sinking

To reveal the velocity distribution law of a gas lift reverse circulation well washing flow field in drilling shaft sinking, a velocity mathematical model of well washing flow field is established. The theoretical analytical solutions and velocity distribution laws in the drill pipe and bottom hole were provided and validated through numerical simulations and similar model tests. Furthermore, this study explores the impacts of mud circulation, wind pressure, rock debris, and mud properties on the flow field distribution, presenting the sensitivity order of the factors. This study indicated the following findings. (1) The velocity theoretical model of well washing flow field was validated through numerical simulation and similar model tests, and the relative error ranged from 4.2 to 18.5%, demonstrating the high consistency. (2) The rock debris and mud experienced slight and consistent deceleration within the drill pipe. Upon reaching the gas input end, the axial upward return of the multiphase flow resulted in a “jumping” sharp increase. (3) The mud circulation, wind pressure, and void fraction positively correlated with the multiphase fluid velocity in the drill pipe, but negatively correlated with the mud density and slag content. The axial upward velocity of the rock debris decreased with increasing particle size and density. (4) The sensitivity of each factor to the discharge speed of rock debris was summarized as follows: air content > mud circulation > wind pressure > mud density > rock debris density > rock debris particle size > slag content. These findings could offer a theoretical basis for selecting well washing parameters and enhancing drilling and washing efficiency.

Numerical investigation of soil arching and integral abutment bridge in a pile-supported railway embankment

ABSTRACT Rail transport plays a crucial role in promoting sustainable mobility and tackling environmental challenges. However, the construction of a railway track on soft soil poses significant challenges due to the inherent instability and potential for excessive settlement. To address these issues, this study numerically assessed a pile-supported embankment and an integral abutment bridge. Two different numerical models are simulated in two-dimensional (2D) plane strain conditions. Findings from numerical analyses of the pile-supported embankment revealed that soil arching is significantly influenced by embankment height and pile spacing. The maximum settlement of the embankment decreases with an increase in embankment modulus and friction angle. Furthermore, a correlation among soil arching indicators was established. Conversely, the analysis of integral abutment railway bridges (IARBs) indicates that the performance of the transition zone is significantly influenced by factors such as approach slab geometry and multiple axle passages.

Automatic construction of Petri net models for computational simulations of molecular interaction network

Petri nets are commonly applied in modeling biological systems. However, construction of a Petri net model for complex biological systems is often time consuming, and requires expertise in the research area, limiting their application. To address this challenge, we developed GINtoSPN, an R package that automates the conversion of multi-omics molecular interaction network extracted from the Global Integrative Network (GIN) into Petri nets in GraphML format. These GraphML files can be directly used for Signaling Petri Net (SPN) simulation. To demonstrate the utility of this tool, we built a Petri net model for neurofibromatosis type I. Simulation of NF1 gene knockout, compared to normal skin fibroblast cells, revealed persistent accumulation of Ras-GTPs as expected. Additionally, we identified several other genes substantially affected by the loss of NF1’s function, exhibiting individual-specific variability. These results highlight the effectiveness of GINtoSPN in streamlining the modeling and simulation of complex biological systems.

Greening of India and revival of the South Asian summer monsoon in a warmer world

While it is accepted that the tropical hydrological cycle has intensified during past interglacial periods due to changes in insolation, greenhouse gases and ice volume, their respective influences are uncertain. Here we present a pollen record from Bengal Bay to reconstruct vegetation changes in India’s core monsoon zone during two warm periods, the current and last interglacial, comparing the data with numerical model simulations to assess the influence of different forcing mechanisms. Results show tropical forest expansion between 11.7-5 ka and 127-120 ka, defining two Indian humid periods, with the last interglacial showing the strongest monsoon activity, consistent with salinity reconstructions. Model-data comparison highlights boreal summer insolation as the primary driver of vegetation dynamics and monsoon intensity during interglacial periods, with CO2 and ice-sheets having a limited effect. Vegetation remains unaffected by pre-industrial CO2 variations above 250 ppmv, a threshold value that characterizes most interglacials of the last million years.

Analytical Model for Contaminant Transport in the CGCW and Aquifer Dual-Domain System Considering GMB Holes

Composite geomembrane cut-off walls (CGCW) have been widely used for the remediation of polluted sites, especially where the environmental conditions are complex. Accurate predictions of the GMB hole leakage and CGCW performance are essential for engineering design and cost control. This paper establishes empirical equations to predict the leakages through the CGCWs based on the numerical models. Additionally, an analytical solution for contaminant migration through the CGCW is proposed considering the effects of GMB holes. The accuracy of the established equations and analytical solution is verified by the numerical models. The key effects of the GMB thickness (TG), head loss (HG), cut-off wall hydraulic conductivity (kG), hole radius (rG) and shape on the leakage and CGCW performance are investigated. The results show that compared with other hole shapes, the leakage through the circular hole is lowest. This is mainly because the shape factor for the circular hole is 1.15–1.3 times lower than that for other shapes of holes with the same area. Additionally, the effects of the hole geometric properties and head loss on the CGCW performance can be more significant when the cut-off wall hydraulic coefficient is small. For example, the breakthrough time differences between the cases with rG = 0.005 m and 0.05 m are 0.8 and 5.0 years when kG = 10−10 and 10−9 m/s, respectively. This is because the impermeability of the CGCW is good when kG is small. This will weaken the impacts of the hole geometric properties on the leakage. The proposed empirical equations and analytical solution can provide effective suggestions for the design of the CGCW in different GMB hole cases.

Mathematical Modeling and Simulation of 1,3‐Propanediol Production by Klebsiella pneumoniae BLh‐1 in a Batch Bioreactor Using Bayesian Statistics

ABSTRACTMathematical modeling and computer simulation are fundamental for optimizing biotechnological processes, enabling cost reduction and scalability, thereby driving advancements in the bioindustry. In this work, mathematical modeling and estimation of fermentative kinetic parameters were carried out to produce 1,3‐propanediol (1,3‐PDO) from residual glycerol and Klebsiella pneumoniae BLh‐1. The Markov chain Monte Carlo method, using the Metropolis‐Hastings algorithm, was applied to experimental data from a batch bioreactor under aerobic and anaerobic conditions. Sensitivity analysis and parameter evolution studies were conducted. The root‐mean‐square error (rRMSE) was chosen as the validation and calibration metric for the developed mathematical model. The results indicated that the average tolerance of glycerol was 174.68 and 44.85 g L−1, the inhibitory products was 150.95 g L−1 for ethanol and 35.56 g L−1 for 1,3‐PDO, and the maximum specific rate of cell growth was 0.189 and 0.275 h−1, for aerobic and anaerobic cultures, respectively. The model presented excellent fits in both crops, with rRMSE values between 0.09 − 33.74% and 3.58 − 31.82%, for the aerobic and anaerobic environment, respectively. With this, it was possible to evaluate and extract relevant information for a better understanding and control of the bioprocess.

Ruta graveolens Plant Extract as a Green Corrosion Inhibitor for 304 SS in 1 M HCl: Experimental and Theoretical Studies

This study evaluated the corrosion inhibitory effects of Ruta graveolens leaf extract for 304 stainless steel in 1 M HCl. The analysis of the leaf extract using HPLC indicated that the primary compounds present in the leaf extract were rutin, caffeic acid, p-coumaric acid, and apigenin. The inhibition efficiency (IE%) of the extract was studied using weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and computational simulation (density functional theory, DFT). The effects of the inhibitor concentration and solution temperature were investigated. The results indicated that the IE% increased for increasing concentrations of the extract, while the reverse was true with increasing temperatures. At 25 °C and a 600 ppm extract concentration, the results indicated a maximum inhibition efficiency of 95%, 98%, and 96% by weight loss, potentiodynamic polarization, and EIS techniques, respectively. SEM observations showed a significant change in the surface morphology of the 304 SS with and without the addition of the inhibitor compound. At all temperatures, the adsorption of the inhibitor components onto the 304 SS surface was found to follow the Langmuir isotherm model, and the inhibition process was governed by physical adsorption. Furthermore, chemical interactions between the inhibitor and the 304 SS steel surface were elucidated via density functional theory (DFT) calculations.

Statistical mechanics of crystal nuclei of hard spheres

In the study of crystal nucleation via computer simulations, hard spheres are arguably the most extensively explored model system. Nonetheless, even in this simple model system, the complex thermodynamics of crystal nuclei can sometimes give rise to counterintuitive results, such as the recent observation that the pressure inside a critical nucleus is lower than that of the surrounding fluid, seemingly clashing with the strictly positive Young–Laplace pressure we would expect in liquid droplets. Here, we re-derive many of the founding equations associated with crystal nucleation and use the hard-sphere model to demonstrate how they give rise to this negative pressure difference. We exploit the fact that, in the canonical ensemble, a nucleus can be in a (meta)stable equilibrium with the fluid and measure the surface stress for both flat and curved interfaces. Additionally, we explain the effect of defects on the chemical potential inside the crystal nucleus. Finally, we present a simple, fitted thermodynamic model to capture the properties of the nucleus, including the work required to form critical nuclei.

Learning glass transition temperatures via dimensionality reduction with data from computer simulations: Polymers as the pilot case

Machine learning methods provide an advanced means for understanding inherent patterns within large and complex datasets. Here, we employ the principal component analysis (PCA) and the diffusion map (DM) techniques to evaluate the glass transition temperature (Tg) from low-dimensional representations of all-atom molecular dynamic simulations of polylactide (PLA) and poly(3-hydroxybutyrate) (PHB). Four molecular descriptors were considered: radial distribution functions (RDFs), mean square displacements (MSDs), relative square displacements (RSDs), and dihedral angles (DAs). By applying Gaussian Mixture Models (GMMs) to analyze the PCA and DM projections and by quantifying their log-likelihoods as a density-based metric, a distinct separation into two populations corresponding to melt and glass states was revealed. This separation enabled the Tg evaluation from a cooling-induced sharp increase in the overlap between log-likelihood distributions at different temperatures. Tg values derived from the RDF and MSD descriptors using DM closely matched the standard computer simulation-based dilatometric and dynamic Tg values for both PLA and PHB models. This was not the case for PCA. The DM-transformed DA and RSD data resulted in Tg values in agreement with experimental ones. Overall, the fusion of atomistic simulations and DMs complemented with the GMMs presents a promising framework for computing Tg and studying the glass transition in a unified way across various molecular descriptors for glass-forming materials.

A computer simulation study of a chiral active ring polymer

We investigate a ring polymer under the influence of chiral active Brownian forces in two dimensions using coarse-grained computer simulations. We observe a non-monotonic behavior of the radius of gyration of an active Brownian ring as a function of active force. However, the shrinkage of the ring in the intermediate strength of active forces becomes more pronounced in the presence of chiral active forces, and the shrinkage is monotonic at a given activity level as a function of the angular frequency controlling the direction of the active force. The distribution of radius of gyration, inter-monomer distance, and radial distribution suggest that the monomers come close to each other, eventually leading to the shrinkage of the ring. Moreover, the bond-correlation suggests that the chirality introduces a local folding of the monomers. Furthermore, using the diameter correlation function, we show that the ring performs tank-treading motion with a frequency following power-law relation with active force with exponent 3/2. The mean squared displacement of the monomers further assists the tank-treading dynamics by exhibiting oscillatory behavior.

Investigation of bubble interaction in a temporal and spatial heat flux partitioning model for subcooled flow boiling

CFD methodology for subcooled flow boiling is significantly affected by the heat flux partitioning model, which plays a crucial role in predicting the mass source term generated by wall boiling of the liquid phase. Although numerous models have been proposed, most research efforts have focused on the spatial dimensions of boiling heat transfer mechanisms, neglecting the temporal aspect. This study presents a heat flux partitioning model for subcooled flow boiling that considers both temporal and spatial dimensions. The model accounts for the contribution of heat flux from the superheated liquid layer during the bubble growth stage, liquid convection during the bubble wait stage within the bubble influence area in the temporal dimension, and heat flux from the overlapping area of bubble influence in the spatial dimension. An approach was developed to determine the bubble influence area by considering the bubble interaction based on the stochastic nature of nucleation sites on the heated wall, verified by the Monte Carlo method. The bubble dynamics parameters were experimentally derived to reduce the uncertainty associated with the boiling sub-models on the calculation. A comparative analysis of boiling curves and wall heat flux partitioning was conducted between the present model and the RPI model under various flow conditions. The results indicate that both models could reasonably predict the boiling curve. However, the RPI model tends to over-predict the proportion of evaporative heat flux, which is considered a weakness. Based on physical principles, the present model accurately captures the fundamental trend of wall heat flux partitioning. This research enhances the understanding of subcooled flow boiling and increases confidence in multiphase CFD methodology predictions.

Numerical modeling and experimental validation of low velocity impact of woven GFRP/CFRP composites

Low-velocity impact of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) composite laminates was studied experimentally and numerically. Hybrid laminates containing blocked layers of GFRP/CFRP/GFRP with all plies oriented at 0° were investigated. Relatively high impact energies were used to obtain full perforation of the laminate in a low-velocity impact setup. Numerical simulations were carried out using the in-house transient dynamics finite element code, Sierra/SM, developed at Sandia National Laboratories. A three-dimensional continuum damage model was used to describe the response of a woven composite ply. Two methods for handling delamination were considered and compared: (1) cohesive zone modeling and (2) continuum damage mechanics. The reduced model size achieved by omission of the cohesive zone elements produced acceptable results at reduced computational cost. The comparison between different modeling techniques can be used to inform modeling decisions relevant to low velocity impact scenarios. The modeling was validated by comparing with the experimental results and showed good agreement in terms of predicted damage mechanisms and impactor velocity and force histories.

Noise‐robust structural response estimation method using short‐time Fourier transform and long short‐term memory

AbstractStructural response estimation based on deep learning can suffer from reduced estimation performance owing to discrepancies between the training and test data as the noise level in the test data increases. This study proposes a short‐time Fourier transform‐based long short‐term memory (STFT‐LSTM) model to improve estimation performance in the presence of noise and ensure estimation robustness. This model enables robust estimations in the presence of noise by positioning an STFT layer before feeding the data into the LSTM layer. The output transformed into the time‐frequency domain by the STFT layer is learned by the LSTM model. The robustness of the proposed model was validated using a numerical model with three degrees of freedom at various signal‐to‐noise ratio levels, and its robustness against impulse and periodic noise was verified. Experimental validation assessed the estimation robustness under impact load and verified the robustness against environmental noise in the acquired acceleration response.

Supercritical CO2-driven intersections of multi-well fracturing fracture network and induced microseismic events in naturally fractured reservoir

PurposeSupercritical CO2 (SC–CO2) fracturing is a potential technology that creates a complex fracturing fracture network to improve reservoir permeability. SC–CO2-driven intersections of the fracturing fracture network are influenced by some key factors, including the disturbances generated form natural fractures, adjacent multi-wells and adjacent fractures, which increase the challenges in evaluation, control and optimization of the SC–CO2 fracturing fracture networks. If the evaluation of the fracture network is not accurate and effective, the risk of oil and gas development will increase due to the microseismicity induced by multi-well SC–CO2 fracturing, which makes it challenging to control the on-site engineering practices.Design/methodology/approachThe numerical models considering the thermal-hydro-mechanical coupling effect in multi-well SC–CO2 fracturing were established, and the typical cases considering naturally fracture and multi-wells were proposed to investigate the intersections and connections of fracturing fracture network, shear stress shadows and induced microseismic events. The quantitative results from the typical cases, such as fracture length, volume, fluid rate, pore pressure and the maximum and accumulated magnitudes of induced microseismic events, were derived.FindingsIn naturally fractured reservoirs, SC–CO2 fracturing fractures will deflect and propagate along the natural fractures, eventually intersect and connect with fractures from other wells. The quantitative results indicate that SC–CO2 fracturing in naturally fractured reservoirs produces larger fractures than the slick water as fracturing fluid, due to the ability of SC–CO2 to connect macroscopic and microscopic fractures. Compared with slick water fracturing, SC–CO2 fracturing can increase the length of fractures, but it will not increase microseismic events; therefore, SC–CO2 fracturing can improve fracturing efficiency and increase productivity, but it may not simultaneously lead to additional microseismic events.Originality/valueThe results of this study on the multi-well SC–CO2 fracturing may provide references for the fracturing design of deep oil and gas resource extraction, and provide some beneficial supports for the induced microseismic event disasters, promoting the next step of engineering application of multi-well SC–CO2 fracturing.

Noise generation and contribution of a single-gap bridge expansion joint: An experimental and numerical study

Noise generated from bridge expansion joints during vehicle passing has caused localized environmental problems around the world. The purpose of this paper is to investigate the vibration and noise radiation from the single-gap expansion joint induced by passing vehicles. First, a vibration and noise field test was performed for single-gap expansion joints in the highway ramps. Based on the tested results, two numerical models, involving a 3D tire-bridge expansion joint hybrid finite element model for the vibration analysis, as well as an acoustic boundary element model for the prediction of the noise radiation, were established and validated. The results of the numerical simulations and the field tests are well matched, which offers opportunities to predict the vibration and noise induced by vehicles passing through using the proposed methodology. Finally, the acoustic contribution and sound pressure distribution of different sound sources were discussed. The research showed that, for the single-gap expansion joint, the contribution of tire noise to the total noise level is dominant, and the contribution of structure-borne noise of the expansion joint and girder to the total noise level is insignificant. The findings emphasize the importance of tire noise and provide new ideas for noise control of single-gap expansion joints.

Subductability of continental lithosphere

Multiple lines of evidence from geological and geophysical observations indicate the deep subduction of continental lithosphere; however, the potential and driving forces of (self-sustained) continental subduction remain unclear. Here, systematic thermal-petrological models were conducted to quantitatively evaluate the subductability of continental lithosphere by analyzing its density structure and slab-pull evolution during subduction. The results indicate that the metamorphic densification of deeply subducted continental lithosphere (upper, middle, lower crust and lithospheric mantle) could provide considerable driving force for continental deep subduction. The numerical models further indicate that, if a Phanerozoic or Proterozoic continental lithosphere is dragged to a large depth of >300 km, then the continental slab pull overcomes the overall resistance force. Consequently, the continental subduction occurs self-consistently without any drag from the preceding oceanic slab. For Archean continental lithosphere, it is more difficult for self-sustained subduction to occur, due to the highly depleted mantle composition. In addition, we also systematically quantified the effects of multiple factors, including the scraping of continental crust, subduction velocity, subduction angle, and variable bulk-rock compositions of continental crust. Finally, a representative case study of the Himalayan orogen revealed that the slab pull of presently subducting Indian continental lithosphere ranges from 13 TN/m to 29 TN/m, providing a major contribution for the ongoing India-Asia collision.

Numerical model of a top-blown rotary converter preheating and charge heating with an oxy-fuel burner

Background The present work is conducted in the framework of the SisAl Pilot EU project, which aims to optimize silicon production in Europe by recycling materials and using carbon-emission-friendly technology. Silicon production experiments were conducted on laboratory and pilot scales in different types of furnaces, including top-blown rotary converters (TBRC) used as chemical reactors for molten slag-metal mixtures. In addition to experimental work, process optimization also relies on numerical modelling. Methods In this study, COMSOL Multiphysics® was used for the numerical testing of a new thermal design of TBRC by simulating its preheating and charge heating owing to an external heat source provided by an oxy-fuel burner. Results and conclusions The risk of slag solidification in TBRC during the aluminothermic reduction of silica was assessed. The model predicts that, with a useful burner power of 600 kW, the empty TBRC can be preheated to 1650°C in less than 30 min. Based on this model, the optimum burner power for maintaining the TBRC charge in a liquid state was determined. The influence of the TBRC inclination angle and its rotation frequency was studied numerically.

Unraveling the Geodynamic Evolution of the Pre– and Early–Andean Margin: Insights From Numerical Modeling

Unraveling the Geodynamic Evolution of the Pre– and Early–Andean Margin: Insights From Numerical Modeling

Model analysis and experiment study for effects of thermal viscous and fluid flow on ventilated acoustic metamaterials labyrinth

In many noise scenarios, ventilation is necessary. The practical realization of noise attenuation under the premise of ensuring ventilation is an urgent problem to be solved. In this paper, a ventilated acoustic metamaterial labyrinth (VAML) is proposed, and the corresponding analytical and numerical computational models are developed considering the thermal viscous effect (TVE). The loss in sound transmission of the VAML is quantitatively obtained and experimentally verified. The theoretical results are compared with the experimental results with an error of 0.6%. By comparing the transmission coefficient and the impedance at the entrance of the side branches, the mechanism of the TVE on the performance of VAML is analyzed, and it is clarified that the TVE is responsible for the sound absorption coefficient. The effects of structure parameters on the transmission coefficient of the VAML are analyzed individually. The results show that the resonant frequency of the system decreases as the length of channel 1 l1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_1$$\\end{document}, the length of channel 2 l2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_2$$\\end{document}, and the width of channel d increase. By adjusting the magnitude of these three parameters, the control of the resonant frequency can be realized. Meanwhile, as l1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_1$$\\end{document}, l2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_2$$\\end{document} and ventilation radius R decrease the valley of transmission coefficient decreases which means better noise reduction. Finally, the effect of flow velocity on the transmission coefficient is analyzed, revealing the mechanism of fluid action on macroscopic acoustic properties.