Numerical study of Richtmyer-Meshkov instability in finite thickness fluid layers with reshock.

The evolution of a shock-induced fluid layer is numerically investigated in order to reveal the underlying mechanism of the Richtmyer-Meshkov instability under the effect of a reshock wave. Six different types of fluid layer are initially set up to study the effect of amplitude perturbation, fluid-layer thickness, and phase position on the reshocked fluid-layer evolution. Interface morphology results show that the interface-coupling effect gets strengthened when the fluid-layer thickness is small, which means the development of spikes and bubbles is inhibited to some extent compared to the case with large initial fluid-layer thickness. Two jets emerge on interface II_{1} under out-of-phase conditions, while bubbles are generated on interface II_{1} when the initial phase position is in-phase. The mixing width of the fluid layer experiences an early linear growth stage and a late nonlinear stage, between which the growth of the mixing width is considerably inhibited by the passage of the first and the second reshock and mildly weakened during phase reversion. The amplitude growth of interfaces agrees well with the theoretical model prediction, including both the linear and nonlinear stages. In the very late stage, the amplitude perturbation growth tends to differ from the theoretical prediction due to the squeezing effect and stretching effect.

Coupling at the molecular scale between the graphene nanosheet and water and its effect on the thermal conductivity of the nanofluid.

Graphene nanofluid is a promising way to improve heat transfer in many situations. As a two-dimensional material, graphene's anisotropic thermal conductivity influences the heat transfer of nanofluids. In the present study, a nonequilibrium molecular dynamics (MD) simulation is adopted to study the interaction between graphene nanosheets (GNSs) and liquid water in water-based graphene nanofluids. Consequently, the coupling interaction between the orientation and length of GNSs and the thermal conductivity of nanofluids is then investigated. We discover that the molecular thermal coupling between GNSs and water can effectively influence the orientation angle of the GNSs. A preferential orientation angle of the GNSs inside the nanofluid is then observed during heat transfer. The preferential orientation angle decreases with the GNS length and has no apparent relation with the size of heat flux in this study. The overall thermal conductivity of the nanofluid decreases as the orientation angle of the GNS rises. Increasing the GNS length not only reduces the preferential orientation angle but also improves the thermal conductivity along the graphene length direction. The thermal conductivity of the nanofluid along the graphene length direction increases from 0.414 to 4.085 W m K-1 as the length increases from 103 to 3274 A. Our results provide the fundamental knowledge of the heat transfer performance of graphene nanofluids.

An integrated economic, energy, and environmental analysis to optimize evaluation of carbon reduction strategies at the regional level: A case study in Zhejiang, China.

China plays a crucial role in responding to global climate change. Provinces are the main sources of energy consumption and greenhouse gas emissions in China's economic and social development. However, it is still unclear how to achieve dual-carbon goals by formulating and implementing local policies to adapt to climate change. In this study, we take Zhejiang Province in China as the research object, based on the LEAP (Low Emissions Analysis Platform) model to construct four social scenarios under different policies, comprehensively considering regional economic characteristics, population, and energy consumption patterns. The results show that to achieve Zhejiang Province's goal of carbon peaking by 2030 while maintaining steady economic growth, additional measures are required to reduce energy consumption intensity or improve the power generation structure. Otherwise, energy demand will increase to 228.06 million tonnes of coal equivalent and carbon emissions will be 487.76 million tonnes in 2050. Moreover, developing clean energy and promoting CCUS technology can continuously reduce carbon emissions to 293.59 and 210.76 million tonnes respectively. The economic viability of CCUS power generation is contingent upon the development of carbon taxes in the future. Once the growth rate reaches 7.2%, power cost will be 167.77 billion RMB and CCUS will become economically advantageous in 2050.

The role of aorta distal to stent in the occurrence of distal stent graft-induced new entry tear: A computational fluid dynamics and morphological study.

Distal stent graft-induced new entry tear (dSINE) is an important complication of thoracic endovascular aortic repair (TEVAR) for the treatment of type B aortic dissection (TBAD). This study aims to explore whether the aorta distal to the stent plays an important role in the occurrence of dSINE. Sixty-nine patient-specific geometrical models of twenty-three enrolled patients were reconstructed from preoperative, postoperative, and predSINE computed tomography scans. Computational fluid dynamics (CFD) simulations were performed to calculate the von Mises stress in the CFD group. Meanwhile, morphological measurements were performed in all patients, including measurements of the inverted pyramid index at different follow-up time points and the postoperative true lumen volume change rate. In the CFD study, the time-averaged von Mises stress of the true lumen distal to the stent in dSINE patients was significantly higher than that in the CFD controls (20.42 kPa vs. 15.47 kPa). In the morphological study, a special aortic plane (plane A) with an extremely small area distal to the stent was observed in dSINE patients, which resulted in an inverted pyramid structure in the true lumen distal to the stent. This structure in dSINE patients became increasingly obvious during the follow-up period and finally reached the maximum value before dSINE occurred (mean, 3.91 vs. 1.23). At the same time, enlargement of the true lumen distal to the stent occurs before dSINE, manifesting as a continuous increase in the true lumen volume (mean, 0.70 vs. 013). A new theory of what causes dSINE to occur has been proposed: the inverted pyramid structure of the true lumen distal to the stent caused an increase in the von Mises stress in this region and aortic enlargement, which ultimately led to the occurrence of dSINE.

Entropy: An Inspiring Tool for Characterizing Turbulence-Combustion Interaction in Swirling Flames via Direct Numerical Simulations of Non-Premixed and Premixed Flames.

This article focuses on entropy generation in the combustion field, which serves as a useful indicator to quantify the interaction between turbulence and combustion. The study is performed on the direct numerical simulations (DNS) of high pressure non-premixed and premixed swirling flames. By analyzing the entropy generation in thermal transport, mass transport, and chemical reactions, it is found that the thermal transport, driven by the temperature gradient, plays a dominant role. The enstrophy transport analysis reveals that the responses of individual terms to combustion can be measured by the entropy: the vortex stretching and the dissipation terms increase monotonically with the increasing entropy. In high entropy regions, the turbulence behaves as the "cigar shaped" state in the non-premixed flame, while as the axisymmetric state in the premixed flame. A substantial increase in the normal Reynolds stress with the entropy is observed. This is due to the competition between two terms promoted by the entropy, i.e., the velocity-pressure gradient correlation term and the shear production term. As a result, the velocity-pressure gradient correlation tends to isotropize turbulence by transferring energy increasingly from the largest streamwise component to the other smaller normal components of Reynolds stress and is dominated by the fluctuating pressure gradient that increases along the entropy. The shear production term increases with the entropy due to the upgrading alignment of the eigenvectors of strain rate and Reynolds stress tensors.

Heat transfer mechanism in idealized healthy and diseased aortas using fluid-structure interaction method.

The heat transfer mechanism inside the human aorta may be related to the physiological function and lesion formation of the aortic wall. The objective of this study was to acquire the temperature distribution in the three-dimensional idealized aorta. An idealized healthy aortic geometry and three representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection were constructed. Advanced fluid-structure interaction (FSI) computational framework was applied to predict the aortic temperature distribution. The movement of the aortic root due to the heartbeat was also considered. The displacement distribution of the aortic vessel wall was consistent with clinical observation. The lesser curvature of the aortic arch, aneurysm body, coarctation region, and false lumen were all exposed to relatively high temperatures (over 310.006 K). We found that the rigid wall assumption slightly underestimated the magnitude of the whole aortic wall-averaged temperature while the changing trend and local temperature were like the results of the FSI method. Besides, the wall-averaged temperature would increase and the temperature inflection point would advance when the aortic vessel wall was loaded with a high heat flux. This pilot study revealed the aortic heat transfer mechanism and temperature distribution, and the findings may help to understand the physiological characteristics of the aortic vessel wall.

The atom sampling method for mesoscale molecular dynamics and its application to graphene assemblies.

Several coarse-grained (CG) molecular dynamics models have been developed to predict the mechanical behaviors of mesoscale graphene structures because of the enormous promise of graphene in various carbon-based nanostructures and the spatiotemporal limitations of experimental testing and atomistic modeling. Although the CG models reduced the number of degrees of freedom and speeded up simulations, the increased mass of the beads caused a significant mismatch in the system's total kinetic and potential energy. In this paper, we propose an atom sampling method for mesoscale molecular dynamics simulations, which could effectively mitigate the consequences arising from the increased mass of the beads in the CG models while still maintaining the computational efficiency of CG models. Then, the Tersoff sampling model of graphene using the atom sampling method is developed to coarsen graphene in planar directions. The mechanical responses of monolayer graphene and multilayer graphene (MLG) assemblies are simulated by the Tersoff sampling model, and simulation results obtained with the all-atom (AA) Tersoff model and CG models are compared. The results show that the Tersoff sampling model can reduce the misfit of kinetic and potential energy due to the fact that temperature changes more accurately reproduce the mechanical behaviors of graphene in the elastic and fracture zones compared to the CG models. At the same time, it further validates the atom sampling method for mesoscale simulations. The atom sampling method can also be easily applied to isotropic fluids and ordered crystal structures (including established coarse-grained models of these substances).

Toba-CPD: An Extended Chemical Percolation Devolatilization Model for Tobacco Pyrolysis.

Tobacco features chemical compositions different from that of raw lignocellulosic biomass. Currently, the performance of network models, like Bio-Chemical Percolation Devolatilization (Bio-CPD), on tobacco pyrolysis is unclear, and only global kinetics have been proposed for tobacco devolatilization, which does not have the versatility for a wide range of heating conditions and tobacco types. To address this issue, the present work first assessed the performance of the Bio-CPD model on tobacco pyrolysis through an a priori study, which showed large deviations. Afterward, an extended Chemical Percolation Devolatilization model for tobacco pyrolysis (Toba-CPD) was developed by modifying the kinetic parameters using a grid-search optimization strategy. The process of grid-search optimization strategy is based on the kinetic parameters of the Bio-CPD model and modified with experimental results of 11 tobacco types under a wide range of heating rates. Finally, the performance of Toba-CPD was measured with experimental results which were not used during parameters optimization. Results demonstrated that the Toba-CPD models could well reproduce the pyrolysis of various tobacco types under a wide range of heating rates (R 2 > 0.957).

Computational Screening of Metal-Organic Frameworks for Ammonia Capture from H2/N2/NH3 Mixtures.

The separation of ammonia from H2/N2/NH3 mixtures is an important step in ammonia decomposition for hydrogen production and ammonia synthesis from H2 and N2 based nonaqueous technologies. Metal-organic frameworks (MOFs) are considered as potential materials for capturing ammonia. In the present work, high-throughput screening of 2932 Computation-Ready Experimental MOFs (CoRE MOFs) was carried out for ammonia capture from H2/N2/NH3 mixtures by Grand Canonical Monte Carlo (GCMC) simulations. It was found that the high-performing MOFs are characterized by tube-like channels, moderate LCD (largest cavity diameter) (4-7.5 Å), and high Q st 0(NH3) (the isosteric heat of NH3 adsorption) (>45 kJ/mol). MOFs with high NH3 adsorption capacity often feature moderate surface area, while the surface area of MOFs with high NH3 selectivity is relatively lower, which limits the NH3 adsorption capacity. Q st 0 and the Henry's constant (K H ) are two energy descriptors describing the interactions between adsorbents and adsorbates. The former has a stronger correlation with the adsorption selectivity, while the latter has a stronger correlation with the adsorption capacity. By analyzing the molecular density distribution of adsorbates in high-performing MOFs, it was found that unsaturated coordinated metal sites provide the main functional binding sites for NH3. Most MOFs with high NH3 selectivity have multiple different metal nodes or other atoms except C, O, and H, such as N and P. Multiple metal nodes and nonmetallic atoms provide more functional binding sites. Finally, the adsorption behavior with various concentrations of gas mixtures was examined to verify the universality of the screening calculations, and the effect of framework flexibility on adsorption performance was explored.

Model reduction of coagulation cascade based on genetic algorithm.

Fibrin is an important product of the coagulation cascade, and plays an eminent role in platelet stabilization. Since coagulation cascade models typically involve the reaction kinetics of dozens of proteins, which will incur burdensome computational costs when coupled to blood flow in complex geometries, researchers often ignore this process when constructing thrombosis models. However, previous studies have shown that fundamental aspects of coagulation can be reproduced with simpler models, which motivated us to obtain a reduced-order model of fibrin generation through a systematic approach. Therefore, we introduced a semi-automatic framework to perform model-reduction of cascade reactions in this study, which consisted of two processes. Specifically, the retained protein species and cascade reactions were determined based on published studies and simulation results from the full cascade model, while the optimal reaction rates for the new cascade network were determined using a genetic algorithm. The framework has been applied to a 19-species coagulation model that triggers fibrin generation in internal fields via reactive boundaries, and a 10-species reduced-order model was obtained to reproduce the kinetics of fibrinogenesis in the full cascade model at different boundary tissue factor concentrations. This reduced-order model of fibrinogenesis would be valuable for thrombosis modeling that considers both the coagulation cascade and platelet activity. Furthermore, the framework proposed herein can also be applied to the reductions of other cascade reaction models.

Computational Prediction of Thrombosis in Food and Drug Administration's Benchmark Nozzle.

Thrombosis seriously threatens human cardiovascular health and the safe operation of medical devices. The Food and Drug Administration's (FDA) benchmark nozzle model was designed to include the typical structure of medical devices. However, the thrombosis in the FDA nozzle has yet not been investigated. The objective of this study is to predict the thrombus formation process in the idealized medical device by coupling computational fluid dynamics and a macroscopic hemodynamic-based thrombus model. We developed the hemodynamic-based thrombus model by considering the effect of platelet consumption. The thrombus model was quantitatively validated by referring to the latest thrombosis experiment, which was performed in a backward-facing step with human blood flow. The same setup was applied in the FDA nozzle to simulate the thrombus formation process. The thrombus shaped like a ring was firstly observed in the FDA benchmark nozzle. Subsequently, the accuracy of the shear-stress transport turbulence model was confirmed in different turbulent flow conditions. Five scenarios with different Reynolds numbers were carried out. We found that turbulence could change the shape of centrosymmetric thrombus to axisymmetric and high Reynolds number blood flow would delay or even prevent thrombosis. Overall, the present study reports the thrombosis process in the FDA benchmark nozzle using the numerical simulation method, and the primary findings may shed light on the effect of turbulence on thrombosis.

Chemistry-Informed Neural Networks modelling of lignocellulosic biomass pyrolysis.

Biomass pyrolysis is a complicated reaction process that involves complex components and reaction pathways. Due to measurement limitations, the intermediate components are difficult to be detected, therefore their detailed kinetics are still not well established. To address this issue, novel Chemistry-Informed Neural Networks (CINNs) were developed to derive the lignocellulosic biomass pyrolysis kinetics from the thermogravimetric analysis (TGA) measurements in published literature. The derived pyrolysis kinetics, involving eight species and eleven reactions, could accurately reproduce the pyrolysis process for both the seen and unseen samples with R2>0.95. The comparisons with the CRECK multi-step and Bio-CPD models also demonstrated the advantages of the derived kinetics in predicting both the final volatiles yield and the pyrolysis process for various biomass types. This study explored a new tool for establishing solid fuel conversion kinetics from TGA measurements using chemistry-informed machine learning approaches.

Component quantification of aortic blood flow energy loss using computational fluid-structure interaction hemodynamics.

BACKGROUND AND OBJECTIVES: The aorta serves as the main tube of the human blood circulation system. Energy loss (EL) occurs when blood flows through the aorta and there may be a potential correlation between EL and aortic diseases. However, the components of blood flow EL are still not fully understood. This study aims to quantitatively reveal the EL components in healthy and diseased aortas. METHODS: We construct an idealized healthy aorta and three idealized representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational hemodynamic studies are carried out by using the fluid-structure interaction simulation framework. RESULTS: Four kinds of EL components: viscous friction, turbulence dissipation, wall deformation, and local lesion are firstly acquired in healthy and diseased aortas based on the high-resolution blood flow information. Viscous friction contributes most to the EL (45.69%-57.22%). EL caused by the deformation of the aortic wall ranks second (15.18%-33.12%). The proportions of turbulence dissipation and local lesion depend on individual geometric characteristics. Besides, the buffering efficiency of the healthy and diseased aorta is about 80%. CONCLUSIONS: This study quantitatively reports the components of blood flow EL in healthy and diseased aortas, the finding may provide novel insights into the pathogenesis of aortic diseases.

Hemodynamic effects of stent-graft introducer sheath during thoracic endovascular aortic repair.

Thoracic endovascular aortic repair (TEVAR) has become the standard treatment of a variety of aortic pathologies. The objective of this study is to evaluate the hemodynamic effects of stent-graft introducer sheath during TEVAR. Three idealized representative diseased aortas were designed: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational fluid dynamics studies were performed in the above idealized aortic geometries. An introducer sheath routinely used in the clinic was virtually placed into diseased aortas. Comparative analysis was carried out to evaluate the hemodynamic effects of the introducer sheath. Results show that the blood flow to the supra-aortic branches would increase above 9% due to the obstruction of the introducer sheath. The region exposed to high endothelial cell activation potential (ECAP) expands in the scenarios of coarctation of the aorta and aortic dissection, which indicates that the probability of thrombus formation may increase during TEVAR. The pressure magnitude in peak systole shows an obvious rise, and a similar phenomenon is not observed in early diastole. The blood viscosity in the aortic arch and descending aorta is remarkably altered by the introducer sheath. The uneven viscosity distribution confirms the necessity of using non-Newtonian models, and high-viscosity region with high ECAP further promotes thrombosis. Our results highlight the hemodynamic effects of stent-graft introducer sheath during TEVAR, which may associate with perioperative complications.

Experimental and Kinetic Studies on Tobacco Pyrolysis under a Wide Range of Heating Rates.

In the present work, experimental and kinetic studies are conducted to explore and model tobacco pyrolysis characteristics under a wide range of heating conditions. First, thermal decomposition processes of a tobacco sample were investigated using thermogravimetric analysis/difference thermogravimetry (TGA/DTG) experiments under a wide range of heating rates (10-500 K/min), and the TGA/DTG profiles were compared to highlight the effect of heating rate on the pyrolysis characteristics. The results showed that the tobacco sample was sufficiently devolatilized at 1173.15 K (900 °C) and the final volatiles yields were not sensitive to the heating rate. Moreover, it was illustrated that the DTG curve presents a polymerization trend with the increase in heating rate. Then, kinetic parameters, including total component mass fraction, preexponential factor, and activation energy, were derived by deconvolution from TG/DTG profiles for each component with a one-step kinetic framework, and the correlations between kinetic parameters and heating rates were further explored and modeled. The results illustrated that four subpeaks can be found in the deconvolution, indicating the four components (volatile components, hemicellulose, cellulose, and lignin). In addition, the activation energy of each component was found to be insensitive with heating rate (with standard deviation less than 20%). Therefore, an average activation energy was used for each component to avoid the compensation effect and a power correlation between the heating rate and the preexponential factor could be found. A posteriori analysis also confirmed the validity of this correlation.

Mathematical modeling of shear-activated targeted nanoparticle drug delivery for the treatment of aortic diseases.

The human aorta is a high-risk area for vascular diseases, which are commonly restored by thoracic endovascular aortic repair. In this paper, we report a promising shear-activated targeted nanoparticle drug delivery strategy to assist in the treatment of coarctation of the aorta and aortic aneurysm. Idealized three-dimensional geometric models of coarctation of the aorta and aortic aneurysm are designed, respectively. The unique hemodynamic environment of the diseased aorta is used to improve nanoparticle drug delivery. Micro-carriers with nanoparticle drugs would be targeting activated to release nanoparticle drugs by local abnormal shear stress rate (SSR). Coarctation of the aorta provides a high SSR hemodynamic environment, while the aortic aneurysm is exposed to low SSR. We propose a method to calculate the SSR thresholds for the diseased aorta. Results show that the upstream near-wall area of the diseased location is an ideal injection location for the micro-carriers, which could be activated by the abnormal SSR. Released nanoparticle drugs would be successfully targeted delivered to the aortic diseased wall. Besides, the high diffusivity of the micro-carriers and nanoparticle drugs has a significant impact on the surface drug concentrations of the diseased aortic walls, especially for aortic aneurysms. This study preliminary demonstrates the feasibility of shear-activated targeted nanoparticle drug delivery in the treatment of aortic diseases and provides a theoretical basis for developing the drug delivery system and novel therapy.

Fluid-structure interaction: Insights into biomechanical implications of endograft after thoracic endovascular aortic repair.

Thoracic endovascular aortic repair (TEVAR) has developed to be the most effective treatment for aortic diseases. This study aims to evaluate the biomechanical implications of the implanted endograft after TEVAR. We present a novel image-based, patient-specific, fluid-structure computational framework. The geometries of blood, endograft, and aortic wall were reconstructed based on clinical images. Patient-specific measurement data was collected to determine the parameters of the three-element Windkessel. We designed three postoperative scenarios with rigid wall assumption, blood-wall interaction, blood-endograft-wall interplay, respectively, where a two-way fluid-structure interaction (FSI) method was applied to predict the deformation of the composite stent-wall. Computational results were validated with Doppler ultrasound data. Results show that the rigid wall assumption fails to predict the waveforms of blood outflow and energy loss (EL). The complete storage and release process of blood flow energy, which consists of four phases is captured by the FSI method. The endograft implantation would weaken the buffer function of the aorta and reduce mean EL by 19.1%. The closed curve area of wall pressure and aortic volume could indicate the EL caused by the interaction between blood flow and wall deformation, which accounts for 68.8% of the total EL. Both the FSI and endograft have a slight effect on wall shear stress-related-indices. The deformability of the composite stent-wall region is remarkably limited by the endograft. Our results highlight the importance of considering the interaction between blood flow, the implanted endograft, and the aortic wall to acquire physiologically accurate hemodynamics in post-TEVAR computational studies and the deformation of the aortic wall is responsible for the major EL of the blood flow.

An integrated fluid-chemical model toward modeling the thrombus formation in an idealized model of aortic dissection.

Type B aortic dissection is a major aortic catastrophe that can be acutely complicated by rapid expansion, rupture, and malperfusion syndromes. The separation of the intima from aortic walls will form a second blood-filled lumen defined as "false lumen (FL)", where the thrombus is more likely to form due to the local stasis hemodynamic conditions. Complete thrombosis of FL is associated with a beneficial outcome while patency and partial thrombosis will lead to later complications. However, the thrombosis mechanism is still unclear and little is known about the impact of chemical species transported by blood flow on this process. The proteins involved in the coagulation cascade (CC) may play an important role in the process of thrombosis, especially in the activation and stabilization of platelets. Based on this hypothesis, a reduced-order fluid-chemical model was established to simulate CC in an aortic dissection phantom with two tears. A high level of fibrin is continuously observed at the top of the FL and some time-varying areas between two tears, indicating a high likelihood of thrombus formation there. This finding is consistent with the clinical observation. The time evolution of coagulation factors is greatly affected by local hemodynamics, especially in the high disturbance zone where the evolution has characteristics of periodic changes consistent with the flow field. The ability of the proposed model to reproduce the CC response provides a potential application to integrate with a model that can simulate platelet activities, forming a biochemical-based model which would help unveil the mechanisms of thrombosis in FL and the clinical decision of appropriate treatment.

Hemodynamic consequences of TEVAR with in situ double fenestrations of left carotid artery and left subclavian artery.

The aortic major branches after thoracic endovascular aortic repair (TEVAR) could be preserved by in situ fenestration (ISF). This study aims to explore the hemodynamic consequences of ISF-TEVAR with double fenestrations. Two patients with aortic dissection and aneurysm, respectively, were treated by ISF-TEVAR and both the left carotid artery (LCA) and left subclavian artery (LSA) were reconstructed by fenestration technique. The blood was considered a non-Newtonian fluid and the Windkessel model was adopted at the aortic outlets. Simulations were performed in two postoperative models to analyze the effects of the double fenestration stents on the hemodynamics. The postoperative wall pressure of the LCA and LSA is relatively low and the pressure difference between the inner and outer walls of the protruding segment of the LSA stent is found. Acceleration occurs when blood flows around the fenestration stents and the shear-thinning rheological behavior is observed at the aortic arch. Moreover, regions susceptible to thrombosis are identified and the surface exposed to high relative residence time is located at the aortic arch after the LSA stent. The presence of the double fenestration stents has a profound impact on the postoperative hemodynamics, and the aortic arch and rebuilt branches should be closely watched during follow-up.