Computer Simulation Research Articles

Integration of acoustic micromixing with cyclic olefin copolymer microfluidics for enhanced lab-on-a-chip applications in nanoscale liposome synthesis.

The integration of acoustic wave micromixing with microfluidic systems holds great potential for applications in biomedicine and lab-on-a-chip technologies. Polymers such as cyclic olefin copolymer (COC) are increasingly utilized in microfluidic applications due to its unique properties, low cost, and versatile fabrication methods, and incorporating them into acoustofluidics significantly expands their potential applications. In this work, for the first time, we demonstrated the integration of polymer microfluidics with acoustic micromixing utilizing oscillating sharp edge structures to homogenize flowing fluids. The sharp edge mixing platform was entirely composed of COC fabricated in a COC-hydrocarbon solvent swelling based microfabrication process. As an electrical signal is applied to a piezoelectric transducer bonded to the micromixer, the sharp edges start to oscillate generating vortices at its tip, mixing the fluids. A 2D numerical model was implemented to determine the optimum microchannel dimensions for experimental mixing assessment. The system was shown to successfully mix fluids at flow rates up to 150µl h-1and has a modest effect even at the highest tested flow rate of 600µl h-1. The utility of the fabricated sharp edge micromixer was demonstrated by the synthesis of nanoscale liposomes.

Element-wise parallel deep learning for structural distributed damage diagnosis by leveraging physical properties of long-gauge static strain transmissibility under moving loads

The Transmissibility Function (TF) has gained considerable interest in structural damage detection because of its relatively high sensitivity to damage and robustness to excitation. This study proposed a distributed damage diagnosis method for beam-like structures based on a long-gauge static strain TF defined as the ratio of the Fourier transform of static strain response under moving loads from a target long-gauge sensor to that from the reference sensor. It has been discovered that each long-gauge static strain TF is independent of moving loads, making it an ideal damage indicator. It exhibits direct proportionality to the ratio of bending stiffness between the two measured zones covered by the target and reference long-gauge strain sensors while being unaffected by the stiffness of any other zones not covered by these two sensors. Moreover, the TF at zero frequency was proved to be equivalent to the ratio of static strain time history areas, relying solely on the stiffness of the covered zones. Leveraged by the physical properties of long-gauge static strain TF, an element-wise parallel deep neural network architecture was developed to decompose damage diagnosis into independent sub-tasks on the element level, utilizing a variational autoencoder (VAE) in the Bayesian inference framework for extracting features from the long-gauge strain TF and a regressor for mapping the features to elemental stiffness reduction. The divide-and-conquer strategy and element-wise parallel learning architecture allow for a significant reduction in the number of labeled training samples generated based on the updated numerical baseline model as it only requires simulated scenarios involving a single damage element. The efficiency and robustness of the proposed method were demonstrated through a numerical simply supported beam and a laboratory experiment on a two-span bridge.

Development of performance analysis model with numerical and dynamic energy modeling for an integrated PVT-HP system

This study delivers a comprehensive numerical analysis of an integrated photovoltaic/thermal-heat pump (PVT-HP) system, underscored by an innovative three-dimensional thermal energy storage (TES) model. Addressing the limitations of conventional one-dimensional TES models, which struggled with accurately simulating horizontal flows and the fluid state at various facility inlets, this research marks a significant advancement. Our development of a 3D TES model optimizes finite elements to reduce computation time and enhance accuracy, vital for precise energy analysis in buildings and air conditioning systems. The integration of this model with a network model allows for detailed analysis of flow rate changes and their impacts on heat transfer, crucial for the integrated PVT-HP system. Key findings include a 30 % increase in the temperature difference between the top and bottom layers of the TES when the flow rate is reduced from 50 LPM to 20 LPM, and a 1 % decrease in the heat pump's coefficient of performance (COP) with a 10 LPM reduction in flow rate. The study emphasizes that managing the flow rate is key to optimizing temperature gradients and system efficiency. Strategic adjustments in flow rate significantly affect thermal storage and transfer capabilities, proving essential in system performance. This research offers vital insights into optimizing PVT-HP systems, focusing on the importance of flow rate control in improving temperature management and overall system performance.

Effect of dispersive electrode position (anterior vs. posterior) in epicardial radiofrequency ablation of ventricular wall: A computer simulation study.

An epicardial approach is often used in radiofrequency (RF) catheter ablation to ablate ventricular tachycardia when an endocardial approach fails. Our objective was to analyze the effect of the position of the dispersive patch (DP) on lesion size using computer modeling during epicardial approach. We compared the posterior position (patient's back), commonly used in clinical practice, to the anterior position (patient's chest). The model considered ventricular wall thicknesses between 4 and 8 mm, and electrode insertion depths between .3 and .7 mm. RF pulses were simulated with 20 W of power for 30 s duration. Statistically significant differences (P < .001) were found between both DP positions in terms of baseline impedance, RF current (at 15 s) and thermal lesion size. The anterior position involved lower impedance (130.8 ± 4.7 vs. 146.2 ± 4.9 Ω) and a higher current (401.5 ± 5.6 vs. 377.5 ± 5.1 mA). The anterior position created lesion sizes larger than the posterior position: 8.9 ± 0.4 vs. 8.4 ± 0.4 mm in maximum width, 8.6 ± 0.4 vs. 8.1 ± 0.4 mm in surface width, and 4.5 ± 0.4 vs. 4.3 ± 0.4 mm in depth. Our results suggest that: (1) the redirection of the RF currents due to repositioning the PD has little impact on lesion size and only affects baseline impedance, and (2) the differences in lesion size are only 0.5 mm wider and 0.2 mm deeper for the anterior position, which does not seem to have a clinical impact in the context of VT ablation.

Three-dimensional simulation of granular flow using a mesh-free numerical model

Three-dimensional simulation of granular flow using a mesh-free numerical model

Harnessing solar power: Innovations in nanofluid-cooled segmented thermoelectric generators for exergy, economic, environmental, and thermo-mechanical excellence

Addressing the imperative need for advancements in thermoelectric generation, this study pioneers an analysis of nanofluid-cooled solar segmented thermoelectric generators with non-uniform cross-sections. Insights into thermal management, structural integrity, and economic efficiency in thermoelectric systems are provided, employing a numerical model that accurately represents thermoelectric effects by accounting for temperature dependencies of semiconductor materials. Through research, exploration of diverse coolant strategies, including TiO2, Fe3O4, Al2O3, and graphene, offers key insights into their impact on cooling dynamics. Findings demonstrate that graphene nanofluid, operating at a flow velocity of 2 m/s, outperforms others, achieving optimal power generation of 221.77 mW and an exergy efficiency of 8.99 %. Additionally, at a concentrated irradiance of 595 kWm−2, graphene leads in environmental benefits, with the highest CO2 savings of 0.38 kgyr−1, and demonstrates economic advantages with a cost-effective dollar per mW value of 3.79×10−6 $mW−1. Furthermore, the study verifies the structural integrity of these systems, with graphene achieving an optimal von Mises stress of 1.35 GPa at a semiconductor height of 0.2 mm. These advancements contribute to environmentally friendly and high-performance generators for sustainable energy solutions, paving the way for future innovations in thermoelectric technology.

A NUMERICAL MODEL FOR ANALYZING CROSS LAMINATED TIMBER UNDER OUT OF PLANE LOADING

This paper targets the validity of a novel numerical model for analyzing CLT under out of plane loading. This numerical model was initially developed for determining the shear lag effect that appears in laminated thin walled composite beams. A parametric study was conducted in order to determine the influence of orientation of layers in CLT panels on bending strength and deflection. For confirming the accuracy of the proposed model, the results from the numerical model are compared with the external results of the computer software Ansys. The differences in bending stress vary from 0.27% to 1.69% depending on the orientation of layers and for deflection the differences are ranged from 2.25% to 7.42%. A numerical study was conducted and obtained data corresponds to results obtained from experimental study. It was concluded that the proposed numerical method can enough precisely predict the behavior of CLT under out of plane loading.

Exploring the Esterase Catalytic Activity of Minimalist Heptapeptide Amyloid Fibers.

This paper investigates the esterase activity of minimalist amyloid fibers composed of short seven-residue peptides, IHIHIHI (IH7) and IHIHIQI (IH7Q), with a particular focus on the role of the sixth residue position within the peptide sequence. Through computational simulations and analyses, we explore the molecular mechanisms underlying catalysis in these amyloid-based enzymes. Contrary to initial hypotheses, our study reveals that the twist angle of the fiber, and thus the catalytic site's environment, is not notably affected by the sixth residue. Instead, the sixth residue interacts with the p-nitrophenylacetate (pNPA) substrate, particularly through its -NO2 group, potentially enhancing catalysis. Quantum mechanics/molecular mechanics (QM/MM) simulations of the reaction mechanism suggest that the polarizing effect of glutamine enhances catalytic activity by forming a stabilizing network of hydrogen bonds with pNPA, leading to lower energy barriers and a more exergonic reaction. Our findings provide valuable insights into the intricate interplay between peptide sequence, structural arrangement, and catalytic function in amyloid-based enzymes, offering potentially valuable information for the design and optimization of biomimetic catalysts.

A simple approach to produce hydrophobic biobased coatings using methylcellulose and organosolv lignin.

Substituting plastics with circular and sustainable alternatives has increasingly become a priority. Protective coatings, crucial components in numerous industries, are now in demand for biodegradable options to replace their plastic-based counterparts. Being one of nature's most abundant components, lignin remains underutilized, and this study focuses on investigating its potential for the production of biobased coatings. The method used here involved formulating coating suspensions by mixing methylcellulose and organosolv lignin powders and adding water to the mixture. Glass wafers were coated with the formulated suspensions using spin-coating. The morphology of the coated surfaces was assessed using optical and scanning electron microscopy. In addition, the wettability of the surfaces was examined through water contact angle experiments, and a numerical model was introduced to predict the water contact angle evolution over time. The results revealed that the sample coated with a 2.5 wt% lignin suspension exhibited the highest initial contact angle (114°), with a decreasing trend as the lignin fraction increases. Moreover, coatings with 3.5 wt% lignin and above exhibited lower surface coverage due to lignin particle aggregation and surface defects. By approximating the water droplet on the surface as a spherical cap, the introduced numerical model successfully predicted the time-dependent evolution of the water contact angle by showing strong alignment with experimental results. Taken altogether, we have showcased here a method for modifying coating properties-in a practical sense from water-absorbent to splash-proof-using readily available forest-based materials. This advancement is paving the way for sustainable protective packaging, aiming to replace styrofoam in the electronics and food industries.

Ocean iron cycle feedbacks decouple atmospheric CO2 from meridional overturning circulation changes.

The ocean's Meridional Overturning Circulation (MOC) brings carbon- and nutrient-rich deep waters to the surface around Antarctica. Limited by light and dissolved iron, photosynthetic microbes incompletely consume these nutrients, the extent of which governs the escape of inorganic carbon into the atmosphere. Changes in MOC upwelling may have regulated Southern Ocean outgassing, resulting in glacial-interglacial atmospheric CO2 oscillations. However, numerical models that explore this positive relationship do not typically include a feedback between biological activity and abundance of organic chelating ligands that control dissolved iron availability. Here, I show that incorporating a dynamic ligand parameterization inverts the modelled MOC-atmospheric CO2 relationship: reduced MOC nutrient upwelling decreases biological activity, resulting in scant ligand production, enhanced iron limitation, incomplete nutrient usage, and ocean carbon outgassing, and vice versa. This first-order response suggests iron cycle feedbacks may be a critical driver of the ocean's response to climate changes, independent of external iron supply.

Investigating the synergistic performance of masonry buildings with steel slabs in structural Design: A case of historical Mahmut Nedim Kurkcuoglu mansion in Turkey

The main aim of this study is to explore the collaborative performance of masonry structures incorporating steel slabs in their structural design. The focal point of the investigation is the historically significant Mahmut Nedim Kurkcuoglu Mansion located in Urfa, Turkey, renowned for its cultural heritage. The research methodology encompasses a comprehensive analysis of the mansion’s structural design, utilizing both numerical modeling and experimental testing. The findings of the study reveal that integrating steel beams into slabs within the structural design of masonry buildings can exert a significant influence on overall structural performance. This integration contributes to the heightened safety and durability of the structure. The results underscore the importance of accounting for the historical and cultural value of heritage buildings when implementing structural modifications. In terms of methodology, the research adds value to the field of structural engineering by offering insights into the incorporation of steel beams in the design of masonry structures. Moreover, it emphasizes the significance of preserving cultural heritage sites through sustainable and innovative engineering solutions. The study not only enriches the understanding of structural engineering but also holds practical implications for professionals such as architects, engineers, and preservationists engaged in the design and maintenance of heritage buildings. In conclusion, this research significantly contributes to the realms of both structural engineering and heritage preservation. Its implications extend to practical applications and can serve as a foundational platform for further exploration and investigation in this interdisciplinary domain.

Structural response of half-scale pumice concrete masonry building: shake table/ambient vibration tests and FE analysis

AbstractSeismic performance evaluation of masonry structures is of paramount importance for ensuring the safety and resilience of buildings in earthquake-prone regions. There are limited number of studies on pumice elements in the literature. In addition, there are almost no studies investigating the earthquake behavior of pumice masonry building as a whole structure. In this context, a comprehensive understanding of their seismic response and dynamic characteristics has been lacking. To address this knowledge gap, a shake-table experimental campaign was undertaken, wherein half-scale pumice masonry building was exposed to simulated seismic forces. To enhance the experimental findings, numerical simulations were performed to confirm and expand our comprehension of how the pumice masonry structure responds to dynamic forces. Integrating both experimental and numerical outcomes provides a holistic understanding of how pumice masonry buildings behave during seismic events. At the end of the experimental study, the frequency values of the pumice model were observed to decrease up to 23.5% in the modes compared to the undamaged state. In the numerical model, this value decreases up to 19.85%. For the undamaged and damaged model, the first three experimental mode shapes were similar to the numerical mode shapes. Both experimental and numerical results show that the expected damages occur in the same regions. These results show that nonlinear FE models can be helpful in determining potential damage model locations. The findings have implications for the seismic design and retrofitting of similar traditional masonry buildings, facilitating the development of resilient and sustainable engineering solutions in seismic-prone regions.

Comparison of simulation tools for optimizing borehole heat exchanger field operation

Model predictive control (MPC) is a promising approach for optimizing the performance of borehole heat exchangers (BHEs) in ground-source heat pump systems. The central element of MPC is the forward model that predicts the thermal dynamics in the ground. In this work, we validate the prediction accuracy of four BHE modeling approaches against real-world measurement data across various operational events and timescales. We simulate the fluid temperature leaving a BHE using a fully discretized 3-D numerical model, a resistance–capacitance model, a g-function model, and a hybrid model. The simulated temperatures are compared to measured temperatures using three validation metrics that quantify temperature offset, noise, and accuracy. The main reason for a mismatch between measured and modeled temperatures is a temperature offset of the simulated temperature. To remove this effect, the models were calibrated for their most sensitive parameter, the ground temperature, and their prediction accuracy over 4 years was evaluated. Thereby, model calibration seems to be a viable solution to account for an unknown load history. The results show that the resistance–capacitance model provides decent predictions in the short term and the g-function model in the long term. However, both models are strongly dependent on accurate calibration. The hybrid model provides the most accurate short and long-term predictions and is less dependent on calibration. Still, its integration into optimization syntax poses challenges compared to the other models. Although not yet applied in model predictive control, the hybrid model stands out as a promising choice for optimizing BHE field operations across various timescales.

A 2D numerical model for simulating landslide dam failure and induced morphological changes considering multi-layer and non-uniform sediments

ABSTRACT Landslide dams are formed by the blockage of rivers with landslides, or any debris flows. Such dams are prone to failure and therefore, simulation of their failure and induced morphological changes is of great importance for hazard mitigation. Multi-layer and non-uniform sediments are usually observed in landslide dam materials, but these are rarely considered in simulations. In this paper, a two-dimensional numerical model considering multi-layered and non-uniform sediments is proposed. The model solves the shallow water equations, the Exner equation considering the different size fractions and Hirano's active layer equation based on a finite volume scheme in a weakly coupled approach. Two experimental tests are used to assess the applicability and accuracy of the model. The results show that it can well simulate the flow and morphological changes, as well as the surface coarsening and fining phenomena related to multi-layer and non-uniform sediments. The numerical results of dam failure process and morphological changes are in overall good agreement with the experiments, but the peak discharge and bed elevation tend to be underestimated when finer material is considered. Finally, the influence of sediments fractions and active layer depth on numerical results, as well as the limitations of the model are discussed.

Antimalarial Delivery with a Ferritin-Based Protein Cage: A Step toward Developing Smart Therapeutics against Malaria.

Over the past two decades, the utilization of protein cages has witnessed exponential growth driven by their extensive applications in biotechnology and therapeutics. In the context of the recent Covid-19 pandemic, protein-cage-based scaffolds played a pivotal role in vaccine development. Beyond vaccines, these protein cages have proven valuable in diverse drug delivery applications thanks to their distinctive architecture and structural stability. Among the various types of protein cages, ferritin-based cages have taken the lead in drug delivery applications. This is primarily attributed to their ease of production, exceptional thermal stability, and nontoxic nature. While ferritin-based cages are commonly employed in anticancer drug delivery and contrast agent delivery, their efficacy in malarial drug delivery had not been explored until this study. In this investigation, several antimalarial drugs were encapsulated within horse spleen ferritin, and the binding and loading processes were validated through both experimental and computational techniques. The data unequivocally demonstrate the facile incorporation of antimalarial drugs into ferritin without disrupting its three-dimensional structure. Computational docking and molecular dynamics simulations were employed to pinpoint the precise location of the drug binding site within ferritin. Subsequent efficacy testing on Plasmodium revealed that the developed nanoconjugate, comprising the drug-ferritin conjugate, exhibited significant effectiveness in eradicating the parasite. In conclusion, the findings strongly indicate that ferritin-based carrier systems hold tremendous promise for the future of antimalarial drug delivery, offering high selectivity and limited side effects.

Research on Water Flooding Front Based on Dynamic and Static Data Inversion—A case study

To clarify the movement of water flooding front in fluvial reservoirs, this research takes BZ oilfield as an example. By comprehensively considering the [w1] equivalent flowing resistance theory of oil-water two phases, the horizontal micro-element equivalent method, and the strong heterogeneity of fluvial facies reservoir, the calculation model of non-piston water flooding front in horizontal well pattern is established. Firstly, five horizontal injection-production well groups in BZ oilfield are taken as examples to calculate the water breakthrough time of oil wells respectively. The calculation results are in good agreement with the actual production performance. In detail, the front advancing speed of the high permeability strip is 0.8 ∼ 1.6m/d, and the speed in low permeability strip is 0.12 ∼ 0.35m/d. When the oil well sees water, the advance speed of the low permeability strip becomes slower, resulting in uneven displacement and easily forming non-dominant potential areas. Moreover, the water flooding front advancing distance is simulated to be 300 ∼ 450m by establishing the reservoir numerical simulation model, which is close to the result of the proposed model, indicating that the calculation method is reliable. The research is of great significance for predicting the water breakthrough time of horizontal production wells, judging the weak affected area on the mainstream line, and timely optimizing water injection and tapping reservoir potential.

Generative design framework for RC deep beams using topology optimization and generative tie method: Experimental and numerical investigation

This research paper proposes a generative design framework that combines topology optimization and the Generative Tie Method (GTM). The study explores the design and performance evaluation of structural concrete deep beams using this framework. A comprehensive investigation involving computational simulations and rigorous large-scale experimental testing provides insights into the optimization strategies of structural concrete deep beams. Specimens designed in accordance with the proposed framework, with an allowable value of compressive strength reduction in concrete (ηadm) set to 0.7, exhibited lower ductility ratios compared to specimens designed with ηadm equal to 0.5. Ductility ratio losses varied significantly, ranging from 28.2 % to 66.2 % among specimens subject to the same optimization level. The topology optimization process significantly influenced stress distribution, cracking behavior, and overall ductility. The Global Warming Potential factor is employed to assess the environmental impact of the optimized structural members. Comparative analyses between the proposed design methodology and a traditional method demonstrate several advantages, including greater material efficiency, higher ductility, and reduced environmental impact. However, the framework demands advanced tools, expertise, and additional training for practical application.

Research regarding the influence of size on the compressive strength of spontaneous combustion coal gangue concrete utilizing the diffusion model

This passage employs the U2-Net model to segment images of spontaneous combustion gangue coarse aggregate (SCGCA) concrete cross-section and randomly placed aggregate library. These methods are used to construct the dataset and subsequently establish and train the diffusion model. Based on this model, a two-dimensional micro-mechanical model of SCGCA concrete was constructed, accurately reproducing the distribution, grading, and shape of the aggregate in the concrete. The size effect of SCGCA concrete is analyzed through experimentation and numerical simulation of two-dimensional micro-models. The findings of the study reveal that the dimension conversion factors for the 100 mm and 200 mm cubic specimens are 0.92 and 1.12 respectively, which demonstrates the evident size effect of SCGCA concrete. The remarkable coherence between the empirical results and the computational simulation results serves as a powerful validation of the durability and efficacy of the model delineated in this paper. In accordance with the theory of Bažant's size effect, this paper elucidates the size effect law of uniaxial compressive strength in SCGCA concrete models ignited spontaneously at different dimensions.

Clustered protocadherin cis-interactions are required for combinatorial cell–cell recognition underlying neuronal self-avoidance

In the developing human brain, only 53 stochastically expressed clustered protocadherin (cPcdh) isoforms enable neurites from individual neurons to recognize and self-avoid while simultaneously maintaining contact with neurites from other neurons. Cell assays have demonstrated that self-recognition occurs only when all cPcdh isoforms perfectly match across the cell boundary, with a single mismatch in the cPcdh expression profile interfering with recognition. It remains unclear, however, how a single mismatched isoform between neighboring cells is sufficient to block erroneous recognitions. Using systematic cell aggregation experiments, we show that abolishing cPcdh interactions on the same membrane (cis) results in a complete loss of specific combinatorial binding between cells (trans). Our computer simulations demonstrate that the organization of cPcdh in linear array oligomers, composed of cis and trans interactions, enhances self-recognition by increasing the concentration and stability of cPcdh trans complexes between the homotypic membranes. Importantly, we show that the presence of mismatched isoforms between cells drastically diminishes the concentration and stability of the trans complexes. Overall, we provide an explanation for the role of the cPcdh assembly arrangements in neuronal self/non-self-discrimination underlying neuronal self-avoidance.

Various lithospheric deformation patterns derived from rheological contrasts between continental terranes: insights from 2-D numerical simulations

Abstract. Continents are formed by the amalgamation of numerous micro-terranes and island arcs, so they have spatially varying lithosphere strengths. The crème brûlée (CB) model and the jelly sandwich (JS) model have been commonly used to describe continental lithosphere strength–depth variations. Depending on the strength of the continental lower crust, the CB and JS models can be further subdivided into two subclasses in which the I subclass (CB-I and JS-I) and II subclass (CB-II and JS-II), respectively, have a strong or weak lower crust. During the continental collision, lithosphere deformation is the byproduct of the comprehensive interaction of multiple terranes. Here we used 2-D thermomechanical numerical models that contain three continental terranes to systematically explore the effects of terranes with various strengths on continental deformation and studied the effects of different rheological assumptions on terrane deformation. We found four types of lithosphere deformation patterns: collision, subduction, thickening and delamination, and replacement. These simulation patterns are seen in observed deformation patterns and structures in East Asia, suggesting they are likely to be naturally occurring modes of intracontinental orogenesis.