Simulation Of Transport Research Articles

Analysis of logistics measures of CEP service providers for the last-mile delivery in small- and medium-sized cities: A case study for the Aachen city region

The e-commerce sector’s rapid expansion has led to an increase in delivery activities both within and across cities, fuelling the growth of the courier, express, and parcel (CEP) services. CEP service providers are crucial for the distribution of goods across all types of cities, especially for last-mile delivery. However, CEP service providers need innovative approaches for their last-mile distribution in small- and medium-sized cities to reduce transport costs and negative environmental impacts. For this reason, this paper analyses the quantitative impacts of logistics measures of CEP service providers for last-mile delivery in small- and medium-sized cities, especially the resulting transport costs and environmental impacts, in the framework of a case study for the investigation area of the Aachen city region. A simulation-based analysis was conducted using the agent-based transport simulation MATSim and the linked route optimisation Jsprit. The results revealed that electric trucks are not cost-effective as a stand-alone logistics measure for last-mile delivery in small- and medium-sized cities. However, combining electric trucks with other sustainable logistics measures, such as parcel shops and parcel lockers, results in a viable logistics measure for last-mile delivery. It is possible to reduce total transport costs by at least 5.4% and CO2 emissions by at least 61.1%. Hence, CEP service providers should replace diesel trucks with a mix of sustainable logistics measures for last-mile delivery in small- and medium-sized cities to achieve better operational efficiency and lesser environmental impacts.

Floquet topological phase transitions in 2D Su-Schrieffer-Heeger model: Interplay between time reversal symmetry breaking and dimerization

Abstract In this paper, we present a theoretical analysis of 2D Su-Schrieffer-Heeger (SSH) model within the context
of Floquet topological insulators (FTIs). Generally speaking, FTIs are endowed with time reversal symmetry
(TRS) and its breaking by means of a time periodical process triggers a topological phase transition governed by
a Chern number. In our proposed model, the condition of TRS breaking is achieved by circularly polarized light
irradiation. The 2D SSH system represents actually a square lattice, where the first order neighbors hopping is
realized only on horizontal and vertical directions. One of the most important findings of our work is that the
TRS breaking is forbidden in the absence of diagonal hopping (between second order neighbors) and we give
a pure analytical proof. On the other hand, due to Peierls transition (PT) (dimerization), the 2D SSH model
undergoes a specific topological transition governed by a Zak phase. Going further, we pursue the interplay
between the TRS breaking and PT. We find thus an interesting topological frustration which is lifted upon PT.
The results are supported both analytically and numerically in terms of Chern numbers, spectral properties,
chiral edge states localization and Hall transport simulations. Our model is suitable not only for condensed
matter (materials), but also for cold gasses trapped in optical lattices or electric circuits.

Validation of three-dimensional simulation of beam transport using linear accelerator based on measured phase-space distributions

Validation of three-dimensional simulation of beam transport using linear accelerator based on measured phase-space distributions

Mapping neutron biological effectiveness for DNA damage induction as a function of incident energy and depth in a human sized phantom

We present new developments for an ab-initio model of the neutron relative biological effectiveness (RBE) in inducing specific classes of DNA damage. RBE is evaluated as a function of the incident neutron energy and of the depth inside a human-sized reference spherical phantom. The adopted mechanistic approach traces neutron RBE back to its origin, i.e. neutron physical interactions with biological tissues. To this aim, we combined the simulation of radiation transport through biological matter, performed with the Monte Carlo code PHITS, and the prediction of DNA damage using analytical formulas, which ground on a large database of biophysical radiation track structure simulations performed with the code PARTRAC. In particular, two classes of DNA damage were considered: sites and clusters of double-strand breaks (DSBs), which are known to be correlated with cell fate following radiation exposure. Within a coherent modelling framework, this approach tackles the variation of neutron RBE in a wide energy range, from thermal neutrons to neutrons of hundreds of GeV, and reproduces effects related to depth in the human-sized receptor, as well as to the receptor size itself. Besides providing a better mechanistic understanding of neutron biological effectiveness, the new model can support better-informed decisions for radiation protection: indeed, current neutron weighting (ICRP)/quality (U.S. NRC) factors might be insufficient for use in some radiation protection applications, because they do not account for depth. RBE predictions obtained with the reported model were successfully compared to the currently adopted radiation protection standards when the depth information is not relevant (at the shallowest depth in the phantom or for very high energy neutrons). However, our results demonstrate that great care is needed when applying weighting factors as a function of incident neutron energy only, not explicitly considering RBE variation in the target. Finally, to facilitate the use of our results, we propose look-up RBE tables, explicitly considering the depth variable, and an analytical representation of the maximal RBE vs. neutron energy.

Precursor sticking coefficient determination from indented deposits fabricated by electron beam induced deposition.

A fast simulation approach for focused electron beam induced deposition (FEBID) numerically solves the diffusion-reaction equation (continuum model) of the precursor surface on the growing nanostructure in conjunction with a Monte Carlo simulation for electron transport in the growing deposit. An important requirement in this regard is to have access to a methodology that can be used to systematically determine the values for the set of precursor parameters needed for this model. In this work we introduce such a method to derive the precursor sticking coefficient as one member of the precursor parameter set. The method is based on the analysis of the different growth regimes in FEBID, in particular the diffusion-enhanced growth regime in the center region of an intentionally defocused electron beam. We employ the method to determine the precursor sticking coefficient for bis(benzene)chromium, Cr(C6H6)2, and trimethyl(methylcyclopentadienyl)platinum(IV), Me3CpPtMe, and find a value of about 10-2 for both precursors, which is substantially smaller than the sticking coefficients previously assumed for Me3CpPtMe (1.0). Furthermore, depositions performed at different substrate temperatures indicate a temperature dependence of the sticking coefficient.

A study on the effects of dispersion coefficient on groundwater pollutant transport simulation.

A comprehensive scientific analysis of temporal and spatial fluctuations of pollutants during the migration of groundwater is essential for precisely predicting their dispersion patterns and promoting rational regional development planning. In this research paper, a field radial dispersion test was conducted in decentralized drinking water sources downstream of the Fu Tuan River basin in Rizhao City, Shandong Province, China (FRSC). Chloride ion (Cl-) solution was utilized as a tracer for the experiment. The longitudinal dispersion coefficient ( ) was determined by standard curve matching and using straight-line graphical methods. Additionally, the impact of on pollutant transport was investigated by creating the MT3DMS solute transport model with the help of GMS 10.4 software. The results indicate that the of the submerged aquifer varies depending on the distance from the source well in the main runoff direction. At distances of 10 and 15m, the values of were observed to be 0.56m and 0.88m, respectively. Moreover, when these observed values of are used as simulation parameters in solute transport modeling on the same space-time scale, the hydrodynamic dispersion effect exhibited by the well is found to be weaker than the actual hydrodynamic dispersion effect.

Predicting Transient Anomalous Transport in Two‐Dimensional Discrete Fracture Networks With Dead‐End Fractures

AbstractPollutant transport in discrete fracture networks (DFNs) exhibits complex dynamics that challenge reliable model predictions, even with detailed fracture data. To address this issue, this study derives an upscaled integral‐differential equation to predict transient anomalous diffusion in two‐dimensional (2D) DFNs. The model includes both transmissive and dead‐end fractures (DEFs), where stagnant water zones in DEFs cause non‐uniform flow and transient sub‐diffusive transport, as shown by both literature and DFN flow and transport simulations using COMSOL. The upscaled model's main parameters are quantitatively linked to fracture properties, especially the probability density function of DEF lengths. Numerical experiments show the model's accuracy in predicting the full‐term evolution of conservative tracers in 2D DFNs with power‐law distributed fracture lengths and two orientation sets. Field applications indicate that while model parameters for transient sub‐diffusion can be predicted from observed DFN distributions, predicting parameters controlling solute displacement in transmissive fractures requires additional field work, such as tracer tests. Parameter sensitivity analysis further correlates late‐time solute transport dynamics with fracture properties, such as fracture density and average length. Potential extensions of the upscaled model are also discussed. This study, therefore, proves that transient anomalous transport in 2D DFNs with DEFs can be at least partially predicted, offering an initial step toward improving model predictions for pollutant transport in real‐world fractured aquifer systems.

Mathematical modeling and numerical simulations of convective heat transport in a stagnant flow of water‐based copper, aluminum oxide and MWCNTs nanofluid upon a stretching spinning disk

AbstractThis study investigates the flow and heat transfer (HT) characteristics of a ternary hybrid nanofluid (THNF) composed of Cu, Al2O3, and multi‐walled carbon nanotubes (MWCNTs) over a rotating stretching disk under the influence of a magnetic field. As a result, THNFs hold promise for diverse applications, including HT enhancement, thermal management in electronics, lubrication, and biomedical uses. Thus, this study develops and simulates a mathematical analysis to investigate the flow of a ternary hybrid power‐law nanofluid over a rotatory stretching disk. The impact of the magnetic field and convective boundary conditions is also considered. The leading equations, including the energy, conservation of mass, and momentum, are altered into nonlinear ODEs and are numerically tackled using MAPLE 2022 to investigate the impression of relevant parameters upon dimensionless velocity, the concentration of nanoparticles, temperature, skin friction, mass, and HT rates. Furthermore, a trend is observed where the nondimensional tangential and radial velocities and the surface temperature decrease as the fluid transitions from pseudoplastic to dilatant behavior. This study confirms that THNFs outperform single and binary nanofluids (NFs) in HT, with key quantitative outcomes like the Nusselt number showing an increase of up to 15%. This enhanced performance stems from the synergistic effects of combining Cu, Al2O3, and MWCNT nanoparticles in the fluid. The Nusselt number is enhanced by 10%–15% when using THNFs compared to mono and hybrid NFs, and skin friction is reduced by 8%–12% under a moderate magnetic field.

Fluorescence molecular imaging-guided photodynamic therapy for early breast cancer in the prone position: feasibility evaluation with Monte Carlo simulations.

The successful diagnosis and treatment of early-stage breast cancer enhances the quality of life of patients. As a promising alternative to recently developed magnetic resonance imaging-guided radiotherapy, we proposed fluorescence molecular imaging-guided photodynamic therapy (FMI-guided PDT), which requires no expensive equipment. In the FMI simulations, ICG-C11 which has emission peaks at near-infrared wavelengths was used as the FMI agent. In the PDT simulation, Upconversion nanoparticles-Quantum dots-Rose bengal (UCQR) which was a PDT agent with upconversion capabilities was used. The feasibility of breast cancer diagnosis and treatment using our proposed method is evaluated through Monte Carlo simulations of exact light transport through a realistic breast model in the prone position. Monte Carlo modeling in voxelized media was performed. Fluorescence propagation from the tumor and the amount of singlet oxygen produced within the tumor were estimated from the calculated fluence. Next, the effects of tumor diameter and depth from the skin surface on the simulation results were evaluated. The simulation results showed successful detection of tumors with diameters of 5-9 mm in the 15-25 mm depth region, where tumors are commonly found. Furthermore, simulations have estimated that those tumors can be completely treated by PDT with less than ten light irradiations. This study suggests that fluorescent molecular imaging-guided photodynamic therapy may be a potential treatment for early-stage breast cancer. Our method would be more suitable than the conventional method for young women who are at higher risk of radiation exposure effects.

Water transport mechanisms during pressure-driven transport through polyamide nanogaps.

Molecular-scale simulations of pressure-driven transport through polyamide nanogaps (5-100 Å) were performed to investigate fundamental transport mechanisms. Results show that transport in nanogaps 10 Å is always subdiffusive, but superdiffusive transport was observed in nanogaps 20 Å. Near typical operating pressures for applications ( = 100 atm), only the 100 Å nanogap exhibited superdiffusive behavior. Since openings in common membrane materials are typically <20 Å, results indicate that subdiffusive to diffusive transport dominates for typical applications, such as reverse osmosis.

Global Hybrid Simulation of Dayside Magnetopause Energy Transport Under Purely Southward Interplanetary Magnetic Field

AbstractIn this paper, dayside magnetopause energy transport (energy transport across the separatrix surface to the magnetopause boundary layer and energy transport inside the magnetopause boundary layer) and its dependence on the magnetopause dynamic evolution under purely southward interplanetary magnetic field (IMF) conditions are studied via a 3‐D global hybrid simulation. By investigating the energy transport across the separatrix surface, current layer surface, and magnetopause surface, we find that the energy transport from the magnetosheath to the magnetopause boundary layer is mainly in the form of electromagnetic energy, while the energy transport directly across the magnetopause surface to the magnetosphere is mainly in the form of plasma energy. The energy transport across the magnetopause surface exhibits temporal variability, driven by the dynamic evolution of reconnection and flux rope. During the development of multiple X‐lines reconnection and flux rope, a substantial portion of solar wind energy does not directly penetrate the dayside magnetopause to the magnetosphere. Instead, it is transported with the reconnection outflow and flux rope from low latitude to high latitude, and with the drifting flow from the subsolar region to the tail magnetopause within the magnetopause current layer. These results significantly improve our understanding of solar wind‐magnetosphere coupling at the dayside magnetopause.

Investigation of cyclic water infiltration and dry-out in coated spruce using finite-element simulations

Accurate prediction of moisture distributions in wood is among the most critical challenges in timber engineering. Achieving this requires a well-coordinated comparison of experimental methods and simulation tools. While significant progress has been made in developing simulation tools in recent years, a lack of experience with and trust in these tools continues to hinder broader implementation, especially when it comes to free water and its absorption. Investigations and model advancements have allowed for the simulation of increasingly complex cases, including one-dimensional moisture transport above the fiber saturation point (FSP) in coated boards and below FSP in coated glued laminated timber (GLT). However, free water flow in coated GLT beams has not yet been addressed, which can become problematic in case of extreme scenarios, such as water infiltration. In this study, we demonstrate that the multi-Fickian free water transport model developed by some of the authors can successfully simulate three-dimensional coated cases. Uncoated and coated boards and GLT members were subjected to cyclic wetting and drying, both experimentally and numerically. To simplify the calibration process of the mass transfer coefficient of free water—identified as the most significant parameter for the simulation of free water transport—experiments previously conducted by some of the authors were simulated. Based on the simulation results, approaches for an initial estimation of the mass transfer coefficient were developed. If the water uptake of coated specimens is measured three days after continuous soaking in water and the result exceeds a specific limit, the coefficient can be sufficiently predicted. The simulation and experimental results show a good agreement.

Controllable spin rectification behavior of vertical and lateral VSe2/WSe2 heterojunction Schottky diodes.

Heterojunctions (HJs) based on two-dimensional (2D) transition metal dichalcogenides are considered promising candidates for next-generation electronic and optoelectronic devices. Here, vertical (V-type) and lateral (L-type) HJ diodes based on metallic 1T-VSe2 and semiconducting 2H-WSe2 with out-of-plane and in-plane contacts are designed. First-principles quantum transport simulations reveal that both V- and L-type VSe2/WSe2 HJ diodes form p-type Schottky contacts. Under zero gate voltage, V-type VSe2/WSe2 HJ Schottky diodes exhibit superior spin rectification behavior compared to L-type, with rectification ratios approaching 109 and 106, respectively. At 300 K, the ideality factor of the V-type diode is lower than that of the L-type and reaches the ideal state at 478 and 510 K, respectively. Notably, positive gate voltage can reverse the rectification direction in both diodes and weaken the rectifying effect in V-type devices. Conversely, negative gate voltage significantly increases the current in both diodes and enhances the rectification ratio of the L-type device to 109. These findings provide insights into the spin-dependent rectification behavior of V- and L-type VSe2/WSe2 HJs in Schottky diodes, offering theoretical guidance for exploring magnetic nanoscale devices based on 2D materials.

Optimizing Two-Echelon Logistics Network for Urban Logistics by LRP Heuristics with integrated Microscopic Transport Simulation

Optimizing Two-Echelon Logistics Network for Urban Logistics by LRP Heuristics with integrated Microscopic Transport Simulation

Computational Fluid Dynamics Simulation and Analysis of Non-Newtonian Drilling Fluid Flow and Cuttings Transport in an Eccentric Annulus

This study examines the flow behavior as well as the cuttings transport of non-Newtonian drilling fluid in the geometry of an eccentric annulus, accounting for what impacts drill pipe rotation might have on fluid velocity, as well as annular eccentricity on axial and tangential distributions of velocity. A two-phase Eulerian–Eulerian model was developed by using computational fluid dynamics to simulate drilling fluid flow and cuttings transport. The kinetic theory of granular flow was used to study the dynamics and interactions of cuttings transport. Non-Newtonian fluid properties were modeled using power law and Bingham plastic formulations. The simulation results demonstrated a marked improvement in efficiency, as much as 45%, in transport by increasing the fluid inlet velocity from 0.54 m/s to 2.76 m/s, reducing the amount of particle accumulation and changing axial and tangential velocity profiles dramatically, particularly at narrow annular gaps. At a 300 rpm rotation, the drill pipe brought on a spiral flow pattern, which penetrated tangential velocities in the narrow gap that had increased transport efficiency to almost 30% more. Shear-thinning behavior characterizes fluid of which the viscosity, at nearly 50% that of the central core low-shear regions, was closer to the wall high-shear regions. Fluid velocity and drill pipe rotation play a crucial role in optimizing cuttings transport. Higher fluid velocities with controlled drill pipe rotation enhance cuttings removal and prevent particle build-up, thereby giving very useful guidance on how to clean the wellbore efficiently in drilling operations.

Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels.

Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5-10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure-function correlations in these membrane pores.

EMC3-EIRENE simulations of edge plasma and impurity transport by toroidally localized argon seeding on CFETR X-divertor

Abstract Three-dimensional (3D) Edge Monte Carlo transport code EMC3-EIRENE has been employed to study edge plasma and impurity transport with toroidally localized argon seeding on Chinese fusion engineering testing reactor (CFETR) X-divertor configuration. The argon impurity seeded at different poloidal locations has been investigated to evaluate the varied profile of the main plasma in the scrape-off layer (SOL) and on the divertor targets, which shows a strong dependence on the poloidal position of argon gas puffing. The argon impurity seeded at the upstream SOL regions can result in a toroidally asymmetric distribution of electron density and temperature, while a toroidally symmetric distribution is obtained for argon seeded at the strike point regions. The deposition pattern of electron density and temperature shows the several lobe-like and island-like structures on the 3D divertor targets of CFETR with upstream argon injections, whereas the perturbed profile is achieved for argon seeding at the strike point regions. In order to verify the toroidal asymmetry of heat loads distribution, the argon impurity seeded at different poloidal locations has been investigated to estimate its influence on toroidal heat loads on divertor plates. The argon injected at the strike point regions gives rise to a toroidal asymmetry of heat loads distribution on divertor targets, while a toroidal symmetry of heat loads distribution is gained for argon injected at the upstream SOL locations.

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

Simple Energy Model for Hydrogen Fuel Cell Vehicles: Model Development and Testing

Hydrogen fuel cell vehicles (HFCVs) are a promising technology for reducing vehicle emissions and improving energy efficiency. Due to the ongoing evolution of this technology, there is limited comprehensive research and documentation regarding the energy modeling of HFCVs. To address this gap, the paper develops a simple HFCV energy consumption model using new fuel cell efficiency estimation methods. Our HFCV energy model leverages real-time vehicle speed, acceleration, and roadway grade data to determine instantaneous power exertion for the computation of hydrogen fuel consumption, battery energy usage, and overall energy consumption. The results suggest that the model’s forecasts align well with real-world data, demonstrating average error rates of 0.0% and −0.1% for fuel cell energy and total energy consumption across all four cycles. However, it is observed that the error rate for the UDDS drive cycle can be as high as 13.1%. Moreover, the study confirms the reliability of the proposed model through validation with independent data. The findings indicate that the model precisely predicts energy consumption, with an error rate of 6.7% for fuel cell estimation and 0.2% for total energy estimation compared to empirical data. Furthermore, the model is compared to FASTSim, which was developed by the National Renewable Energy Laboratory (NREL), and the difference between the two models is found to be around 2.5%. Additionally, instantaneous battery state of charge (SOC) predictions from the model closely match observed instantaneous SOC measurements, highlighting the model’s effectiveness in estimating real-time changes in the battery SOC. The study investigates the energy impact of various intersection controls to assess the applicability of the proposed energy model. The proposed HFCV energy model offers a practical, versatile alternative, leveraging simplicity without compromising accuracy. Its simplified structure reduces computational requirements, making it ideal for real-time applications, smartphone apps, in-vehicle systems, and transportation simulation tools, while maintaining accuracy and addressing limitations of more complex models.

Mobile Observation Field Experiment of Atmospheric Vertical Structure and Its Application in Precipitation Forecasts Over the Tibetan Plateau

AbstractWe carried out the first Mobile Field Observation Campaign of Atmospheric Profiles (MFOCAP) in the southeast Tibet and the Three‐River Source Region (TRSR) of the Tibetan Plateau (TP) by adopting two vehicle‐mounted integrated mobile observations (MO) system from July 18 to 30, 2021. Reliable MO data sets of air temperature (Ta), water vapor density (WVD) and relative humidity (RH) with high spatio‐temporal resolution over the TP were obtained and assimilated to improve precipitation forecast using the four‐dimensional variational (4DVAR) data assimilation (DA) method. The results show that Ta, WVD and RH profile data retrieved with the mobile microwave radiometer (MR) are credible over the TP. The atmospheric vertical structure measured by the mobile MR can reproduce the spatio‐temporal evolution characteristics of water vapor transport, temperature stratification and cloud structure. The distribution pattern of 24‐hr accumulated rainfall prediction with Ta profile DA was closer to measurements, and 6–12 hr forecasts for low to moderate rainfall in the central and western regions of Qinghai province were improved significantly. Data assimilation with air temperature retrievals from mobile MR observations were found beneficial for accurate simulation of water vapor transport, convergence and divergence of wind field, and upward motion associated with precipitation events. The finding of this study highlights the value of MR remote sensing observations in improving the rainfall monitoring and forecasts over the TP and downstream regions.