ABSTRACT
Although great progress has been made in the synthesis of hierarchically structured zeolites (HSZs), the optimal design of HSZs is still very challenging due to the lack of mathematical ...models. This work proposes a multiscale model that is able to describe mass transfer and reaction at crystal, pellet, and reactor levels, by directly coupling model equations at two neighboring levels. Two types of HSZ particles are considered, and n‐hexane isomerization catalyzed by Pt/ZSM‐5 is taken as a model reaction system. The results show that the diffusion limitations in both micropores and macro‐/meso‐pores can significantly reduce the conversion at reactor level. The trade‐off between diffusion limitations and quantity of catalytic materials determines the optimal structure of HSZ particles. The optimized HSZ particles can be 52.9–1021.4% larger in conversion than their conventional counterparts. This work provides a powerful model and some useful guidance for the design of industrial zeolite catalysts.
Summary
A multi‐scale model is often constructed using different finite elements and consists of a global scale model for the structural system and a few local scale models for critical structural ...components so that the multi‐scale simulation can concurrently exhibit both global performance and local behavior of the structure. To ensure the multi‐scale model can best represent the real structure, multi‐scale model updating technique shall be developed accordingly. This paper thus presents a multi‐scale model updating method for a transmission tower structure using the Kriging meta‐model that actually is a surrogate for the multi‐scale model. Firstly, the multi‐scale model of a transmission tower is established by using beam elements to simulate global structure and solid elements to simulate local joints with bolt connections. Secondly, the multi‐objective optimization problem that involves multiple objective functions is established to update key parameters of the multi‐scale model so that the errors between the measured and predicted structural dynamic characteristics and multi‐scale responses can be minimized. To improve the computational efficiency and accuracy of optimization, the Kriging meta‐method is used to find the updated key parameters of the tower after a comparison with other meta‐methods is made. Finally, the proposed method is applied to a physical transmission tower model, which has been tested in a laboratory, to demonstrate the feasibility and accuracy of the proposed model‐updating method. The updated results show that the proposed updating method can improve the accuracy of the multi‐scale model of the tower in both global and local structural responses.
•The relaxation of the boundary conditions between layers improves the reproduction of the micromechanical behaviour.•The proof of concept results show good capabilities in the reduction of the RAM ...memory usages.•The future implementation of this methodology can boost the calculation of non-linearities in metamaterials.
ABSTRACT
There is accumulating evidence that, from bacteria to mammalian cells, messenger RNAs (mRNAs) are produced in intermittent bursts – a much ‘noisier’ process than traditionally thought. Based ...on quantitative measurements at individual promoters, diverse phenomenological models have been proposed for transcriptional bursting. Nevertheless, the underlying molecular mechanisms and significance for cellular signalling remain elusive. Here, we review recent progress, address the above issues and illuminate our viewpoints with simulation results. Despite being widely used in modelling and in interpreting experimental data, the traditional two‐state model is far from adequate to describe or infer the molecular basis and stochastic principles of transcription. In bacteria, DNA supercoiling contributes to the bursting of those genes that express at high levels and are topologically constrained in short loops; moreover, low‐affinity cis‐regulatory elements and unstable protein complexes can play a key role in transcriptional regulation. Integrating data on the architecture, kinetics, and transcriptional input–output function is a promising approach to uncovering the underlying dynamic mechanism. For eukaryotes, distinct bursting features described by the multi‐scale and continuum models coincide with those predicted by four theoretically derived principles that govern how the transcription apparatus operates dynamically. This consistency suggests a unified framework for comprehending bursting dynamics at the level of the structural and kinetic basis of transcription. Moreover, the existing models can be unified by a generic model. Remarkably, transcriptional bursting enables regulatory information to be transmitted in a digital manner, with the burst frequency representing the strength of regulatory signals. Such a mode guarantees high fidelity for precise transcriptional regulation and also provides sufficient randomness for realizing cellular heterogeneity.
•The efficiency factor that considers the catalyst layer structure was obtained.•A multi-scale and multi-objective model was proposed for catalytic distillation.•The parameters of column, and the ...structure of catalyst layer were optimized.
This work aims to establishing a multi-scale and multi-objective optimization strategy for the catalytic distillation process. Firstly, the catalyst layer efficiency factor correlation that embraces the influence of the catalyst layer structure was obtained and then coupled with the process simulation to establish a multi-scale model for the catalytic distillation process. On this basis, genetic algorithm was employed to realize the multi-objective optimization. The hydrolysis process of methyl acetate in the reactive dividing wall column was investigated. The equipment parameters and operational conditions of the catalytic distillation column, and the structure parameters of the catalyst layer are optimized simultaneously. The results indicated that the minima of the total annual cost, the gas emission cost and the exergy loss decrease by 19.26%, 23.11% and 67.27%, respectively, by comparing with the counterparts obtained from the single-factor sensitivity analysis. Furthermore, the catalyst cost decreases by 30.88% per year.
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•Underlying physics of fuel droplet heating and evaporation process was unfolded.•Macro, meso and micro/nano fluid elements of fuel droplet were accessed.•Lifetime of fuel droplet ...under engine conditions was quantified.•A vital step towards multi-scale modelling of fuel droplet was built.
Fuel consumption and energy efficiency are still of great interest in combustion engineering and science. This state-of-the-art review revisits the fuel droplet heating and evaporation in combustion engines by accessing the nano/microscopic, mesoscopic and macroscopic fluid elements. Both fluid flow and heat transfer have been intensively recovered when a fuel droplet (dodecane) is heating and evaporated into a background gas (nitrogen) crossing the liquid–vapour interface, kinetic region and the bulk regions of liquid and gas in terms of molecular dynamics simulations, kinetic theory modelling and conventional hydrodynamic approach at each scale. Moreover, the introduction of inelastic collisions between fuel molecules helps fully unfold the underlying physics of droplet heating and evaporation and resolve the ignition delay and combustion phasing in engines. The proposed multi-scale modelling of fuel droplet heating and evaporation will make significant input into a cleaner engine targeting the low-carbon emissions and enhance the energy efficiency towards net zero.
•A hierarchical multi-scale approach is presented that bridging nano to micro scale to study the elastic and fracture parameters of nanofibrous network with random and aligned distribution of ...nanofibers.•At the atomistic scale, molecular dynamics simulations on freestanding pristine and silver-doped polylactic acid nanofibers are used to determine the energy release rate, elastic modulus, and Poisson's ratio which serve to inform PD at microscale.•At the microscale, peridynamics is used to assess crack propagation and fracture toughness for Mode I and Mode II in both aligned and randomly oriented fibrous networks.•The framework allows the investigation of the effects of fibre orientation and surface treatment on the elastic and fracture properties of the nanofibrous network.•A good agreement with the available experimental data confirms the applicability of the proposed method.
Polylactic acid (PLA) nanofibrous networks have gained substantial interest across various engineering and scientific disciplines, such as tissue engineering, drug delivery, and filtration, due to their unique and multifunctional attributes, including biodegradability, tuneable mechanical properties, and surface functionality. However, predicting their mechanical behaviour remains challenging due to their structural complexity, multiscale features, and variability in material properties.
This study presents a hierarchical approach to investigate the fracture phenomena in both aligned and randomly oriented nanofibrous networks by integrating atomistic modelling and non-local continuum mechanics, peridynamics. At the nanoscale, all-atom molecular dynamics simulations are employed to apply tensile loads to freestanding pristine and silver-doped PLA nanofibres, where key mechanical properties such as Young's modulus, Poisson's ratio, and critical energy release rate are determined using innovative approaches. A new method is introduced to seamlessly transfer data from molecular dynamics to peridynamics by ensuring the convergence of the tensile response of a single fiber in both frameworks. This nano to micro coupling technique is then utilised to examine the Young's modulus, fracture toughness of mode I and II, and crack propagation in PLA nanofibrous networks. The proposed framework can also incorporate the effects of surface coating and fiber arrangements on the measured properties. The current research paves the way for the development of stronger and more durable eco-friendly nanofibrous networks with optimised performance.
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Aim
Bats are important components of mammalian biodiversity and strong bioindicators, but their fine‐scale distributions often remain less known than other taxa (e.g., plants, birds). Yet as highly ...mobile species with multiple needs in the landscape, bats impose serious modelling challenges, such as advanced use of neighbourhood analyses. The aims of this study were to test the use of a designed sampling of bats for biodiversity and conservation assessments, and to find appropriate modelling solutions for providing nature practitioners with reliable potential bat distribution maps in a mountain area of high conservation interest.
Location
The western Swiss Alps of Vaud.
Methods
We conducted a one‐year field survey combining passive acoustic recordings supplemented by mist net catching to collect data on bats. These data were then used to create univariate models with focal land use/cover variables using different focal window sizes to detect the optimal species‐specific scale of influence for each variable. The large number of selected variables was then used to create ensembles of small models at a 100 m × 100 m resolution, and the resulting habitat suitability maps were transformed into species distribution maps for practitioners.
Results
We were able to collect data to model 14 different bat species representing 66% of the Swiss bat diversity, including four red list species. In general, the most important variables were Euclidean distance to road or water, temperature and slope, but there was large variation among species both for the variable importance and for the optimal focal window size.
Main conclusion
Our study greatly increased the knowledge of bats in this region and showed that many of the red list species are nowadays disappearing from the intensively used lowland plains and restricted to the remaining forests along the slopes. Additionally, we highlighted the importance of selecting the variable scale on a species‐specific basis accounting for their mobility and range sizes.
Salinity gradient energy (SGE) capture by reverse electrodialysis (RED) is an emerging technology to advance the phaseout of conventional water-intensive energy sources in desalination industry. This ...paper assesses SGE recovery potential of an up-scaled RED system in seawater reverse osmosis (SWRO) desalination plants. Using a detailed RED system's model (i) we conducted a parametric evaluation of feed's concentration, feed's flow rate, and temperature to identify the optimal working conditions of an industrial-scale RED unit; (ii) we estimated SGE recovery of a RED plant in SWRO plants distributed worldwide, adopting a single-stage arrangement of the RED units; (iii) finally, to enhance energy yield, we examined different RED plant's layouts in a specific SWRO plant. The results underline the merits of this modelling tool to assist SGE-RED implementation in the utmost scenarios. Regarding RED plant's layout, findings reveal that the series-parallel arrangement of the RED units improves the power output and energy yield of the system but requires more RED units. Hence, a systematic evaluation through optimization of the hybrid process's configuration both at plant's scale and at RED unit's scale is needed to properly determine RED's SGE recovery potential from waste streams in SWRO plants.
•Upscaled RED unit performance assessment over wide-ranging operating conditions.•Appraisal of RED plant's SGE recovery in reverse osmosis plants spread worldwide.•Performance evaluation of single- and multi-stage RED plant's layouts.•The series-parallel RED plant's layout balances out power and energy yield.•The series-parallel layout triples power and energy yield but enlarges plant's size.
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