Simulation Of Transport Research Articles

Co-designing transport models as a heuristic planning tool

Recently the transportation sector has witnessed several new technologically driven disruptions that have amplified the complexity of city planning and policymaking. Traditional well-established processes of decision-making in urban planning and transportation are proving insufficient to deal with this degree of complexity and uncertainty. This paper proposes an alternative approach, combining qualitative and normative urban design, with quantitative and predictive transport modelling. This requires urban designers and transport modellers to co-create goal-driven and agile transport models that act as a heuristic tool to guide planning decisions in early design stages. Heuristic modelling is informed by design optioning and vice versa in an iterative loop. A case study is presented to demonstrate how this approach is operationalized to study the impacts of automated vehicles on urban planning. Design workshops are used as a method to elicit responses from stakeholders, which are used to co-create the simulation models. This collaborative process grounds the research in real-world practice and enhances the communication of design proposals and research findings across disciplines. By integrating design thinking methods with agent-based transport simulations, this approach provides a better understanding of emergent effects in complex urban systems and improves stakeholder engagement in the planning process. This article is part of the theme issue ‘Co-creating the future: participatory cities and digital governance’.

DecTree: a physics-based geochemical surrogate for surface complexation of uranium on clay

Abstract. Geochemistry is usually the computational bottleneck in coupled reactive transport simulations, which hampers the complexity of the systems and of the processes they can investigate. In recent years, promising speedups have been obtained by substituting the numerical solution of geochemical models with approximated surrogates borrowed from artificial intelligence and machine learning (AI/ML). In the framework of the DONUT/EURAD project a set of benchmarks were defined to assess the performance and the accuracy of different surrogate approaches in settings relevant to the safety assessment of nuclear waste repositories, such as the surface complexation and exchange of U(VI) on clay. In this context, this work introduces am original surrogate modelling approach based on recursive partitioning of parameter space, which exploits prior domain knowledge for the training. The surrogate, which can be represented as a decision tree, hence the DecTree name, performs dimensionality reduction by identifying functional relationships between outputs and input variables using a straightforward non-monotonic extension of the Spearman's rank correlation coefficient. New predictions are then interpolated from the partitioned training data. Applied to a low-dimensional geochemical model, DecTree shows virtually no training time and excellent accuracy, ensuring a throughput of around 500 000 predictions per second on a single CPU core.

Assessment of validity of local neoclassical transport theory for studies of electric-field root-transitions in the W7-X stellarator

Abstract The neoclassical ambipolarity condition governing the radial electric field in stellarators can have several solutions, and sudden transitions (in radius) between these can then take place. The radial position and structure of such a transition cannot be determined from local transport theory, and instead a non-rigorous model based on a diffusion equation for the electric field is usually employed for this purpose [1]. We compare global (full plasma volume) drift-kinetic simulations of neoclassical transport in the Wendelstein 7-X stellarator with this model and find significant discrepancies. The position r0 of the transition is not predicted correctly by the diffusion model, but the radial structure of the transition layer is in reasonable agreement if the diffusion coefficient is chosen appropriately. In particular, it should depend on the plasma temperature in the same way as the plateau-regime coefficient of neoclassical transport theory or the gyro-Bohm diffusion coefficient. In the small-gyroradius limit, the prediction of r0 by the diffusion model simplifies to the so-called Maxwell construction [2, 3]. However, this property also emerges from a wide range of other mathematical models in the appropriate limit. The basic assumption underlying these models is that the diffusion, or generalisations thereof, is independent of the radial electric field, which is however unlikely to be the case in practice. Presumably this fact explains the discrepancy between the diffusion model and the drift-kinetic simulations. Finally, it is found that global simulations replicate the phenomenon of spontaneous root transitions driven by variations in the electron-to-ion temperature ratio, as predicted by local theory in the small-gyroradius limit.

The influence of daily imaging and target margin reduction on secondary cancer risk in image-guided and adaptive proton therapy

Objective. Image-guided and adaptive proton therapy rely on daily CBCT or CT imaging, which increases radiation dose and radiation-induced cancer risk. Online adaptation however also reduces setup uncertainty, and the additional risk might be compensated by reducing the setup robustness margin. This work developed a framework to investigate how much this robustness margin should be reduced to offset the secondary cancer risk from additional imaging dose and applied it to proton therapy for head-and-neck cancer.Approach. For five patients with head-and-neck cancer, voxel-wise CT and CBCT imaging doses were estimated with Monte Carlo radiation transport simulations, calibrated with air and PMMA phantom measurements. The total dose of several image-guided and adaptive treatments protocols was calculated by summing the planning CT dose, daily and weekly CBCT or CT dose, and therapy dose, robustly optimized with setup margins between 0 and 4 mm. These were compared to a reference protocol with 4 mm setup margin without daily imaging. All plans further used 3% range robustness. Organ-wise excess absolute risk (EAR) of cancer was calculated with three models to determine at which setup margin the total EAR of image-guided and adaptive treatment protocols was equal to the total EAR of the reference.Results. The difference between the simulated and measured CT and CBCT doses was within 10%. Using the Monte Carlo models, we found that a 1 mm setup margin reduction was sufficient for most patients, treatment protocols, and cancer risk models to compensate the additional risk imposed by daily and weekly imaging. For some protocols, even a smaller reduction sufficed, depending on the imaging frequency and type. The risk reduction by reducing the margin was mainly due to reducing the risk for carcinomas in the brain and, for some patients, the oral cavity.Significance. Our framework allows to compare an increased imaging dose with the reduced treatment dose from margin reductions in terms of radiation-induced cancer risk. It is extendable to different treatment sites, modalities, and imaging protocols, in clinic-specific or even patient-specific assessments.

Evaluating the Usability of a Remote Ischemic Conditioning Device for Pre-Hospital Stroke Management: Insights from Paramedic Simulations

Background/Objectives: In acute stroke, often-prolonged hospital transport times present an opportunity for early interventions to salvage brain tissue. Remote ischemic conditioning (RIC), where brief cycles of ischemia–reperfusion in a limb are induced to protect the brain, is a promising treatment for this setting. We assessed the usability of a novel RIC system in a simulated emergency response scenario. Methods: Paramedics were asked to use the RIC device in an emergency stroke care and ambulance transport simulation, overseen by a confederate. Feedback on device use was collected through questionnaires, including the System Usability Scale (SUS) and the NASA Task Load Index (NASA-TLX), and a semi-structured interview. Questionnaire responses were summarized using descriptive statistics; interview transcripts were analyzed thematically. Results: Nine paramedics (including the confederate) participated, with a mean of 10.0 ± 10.3 years of professional experience. Questionnaire responses indicated high device usability (mean SUS score: 85.3 ± 12.9 out of 100) and low task-related demands, effort, and frustration (mean NASA-TLX domain scores: ≤3.9 out of 20). Seven paramedics stated they would use the device in daily practice. They expressed concerns related to display screen clarity, interference with standard procedures, cable management, device fragility, and patient discomfort. Suggested improvements included adding indicators of device performance and refining the cuff design. Conclusions: While the device was considered easy to use, paramedics also identified important areas of improvement. With a small, localized study sample, our findings are primarily applicable to the refinement of the RICovery system for use in future clinical trials in the same healthcare setting. However, feedback on the importance of mitigating potential interference of newly introduced procedures with those already established, robustness of equipment, and effective paramedic–patient communication may also help inform the design of other pre-hospital interventions.

Numerical Simulations Using iRIC Nays2DH for Sediment Transport Behaviors in Dam Breach Tests

After the breach of a landslide dam, the sediment in the breach opening will be carried downstream by the breach flood. The river channel will also be eroded by the flood, resulting in bed load transport. Three large-scale dam breach tests were conducted to investigate the sediment transport behavior after a dam breach. The topography data of the creek channel were measured before and after the dam breach tests to understand the sediment transport behavior. The sediment transport simulations of the dam breach tests were conducted using the iRIC Nays2DH software. The simulations focused on three types of test setups: the single dam, single dam with a spur dike, and double dam models. The terrain (DEM) for the numerical model input was designated based on the LiDAR results, and a flow hydrograph during the dam breach tests was applied. The accuracy of the simulations was assessed using the “coverage index” and “mean absolute percentage error”. A numerical parametrical study was performed to find the major parameters that influenced the simulations. The results showed that the dynamic behavior of water flow and sediment during the dam breach processes were effectively captured by the iRIC Nays2DH simulation, but with limitations. The average flow velocity of the flood in the single dam case was the fastest among the three types of dam breaches. Due to the contraction of the creek channel caused by the spur dike, severe erosion occurred locally, and the flow rate increased in the narrowed section. Water impoundment between the two dams after the first dam breach and the consequent breach of the second dam were also well-simulated for the double dam breach. The findings and simulations in this study help explain dam breaches better and can guide researchers working on sediment transport during dam-breach floods.

Grain Shape Dependent Thermal Conductivity of Polycrystalline Nanostructure

ABSTRACT We employed phonon transport simulations to provide insights into the relation between the grain shape of polycrystalline nanostructures and their thermal conductivity. Two types of polycrystalline nanostructures were modeled by using space-filling structures: one comprised of only a single grain shape (body-centered cubic, face-centered cubic, and simple cubic), and the other featuring two grains of differing sizes constructed by truncating vertices of cubes and filling the resulting volume. For the latter structures, various polycrystalline structures were created by tuning the truncation volume. Our phonon transport simulations in polycrystalline structures consisting of only single shape grains revealed that the boundary-scattering phonon mean free path, which determines the thermal conductivity of nanostructured materials, can vary by up to 10% depending on the grain shape. In addition, the mean free path increases with greater disparities in grain size in the polycrystalline nanostructures, with variations reaching up to about 10%. Furthermore, we found that the mean free path derived from phonon transport simulations is quantitatively consistent with the grain volume-to-surface area ratio in modeled polycrystalline nanostructures. This consistency indicates that the mean free path in polycrystalline nanostructures can be predicted using descriptors based on their fundamental structural features, without the need for numerical simulations.

Ensemble Monte Carlo transport studies of zinc-blende cuprous halides

We present a comprehensive theoretical analysis of intrinsic high-field transport in cuprous halides: CuCl, CuBr, and CuI. Ensemble Monte Carlo transport simulations were performed based on analytical approximations of the multi-valley and three-band electronic structure model. The deformation potentials, extracted from carrier–phonon interaction matrix elements calculated via the Wannier function approach, were employed to determine scattering rates. Our detailed analysis uncovers intriguing transport characteristics based on the complex valence band structures, resulting from spin–orbit coupling and band inversion. Remarkably, the hole mobility in CuI was exceptionally high, reaching up to 193 cm2/V s, while CuCl exhibited unusual temperature dependencies in hole transport. Additionally, the electron mobility in CuI was found to be 254 cm2/V s, indicating a minimal disparity between carrier mobilities, which is advantageous for optoelectronic applications.

Photodetector Based on Elemental Ferroelectric Black Phosphorus-like Bismuth.

Two-dimensional ferroelectric materials have emerged as a promising candidate for the development of next-generation photodetectors owing to their inherent photogalvanic effect (PGE) and strong light-matter interactions. Recently, the first-ever elemental-based ferroelectric material, black-phosphorus-like Bi (BP-Bi), has been successfully synthesized. In this work, we investigate the PGE of the monolayer (ML) BP-Bi by using ab initio quantum transport simulation. We find that the photocurrent of the ML BP-Bi in the ferroelectric direction (armchair) is significantly larger than that in the vertical ferroelectric direction [zigzag (ZZ)]. For example, despite the comparable optical absorption rates of BP-Bi in the armchair (ARM) and ZZ directions, the maximum photocurrent (133 mA/W) in the ARM direction is 2 orders of magnitude greater than that (4.70 mA/W) in the ZZ direction. The asymmetry is attributed to the breaking and existence of the mirror inversion symmetries along the ARM and ZZ directions, respectively. Our work paves the way for the research of the low-dimensional ferroelectric photodetector.

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Abstract Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and Fusion Pilot Plant (FPP) may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system (PCS) in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator (COTSIM) illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

A simulation framework for preclinical proton irradiation workflow

Objective.The integration of proton beamlines with x-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments. This work presents a simulation framework useful for optimizing beamlines, imaging protocols, and design of animal experiments. The usage of the framework is demonstrated, mainly focusing on the imaging part.Approach.The fastCAT toolkit was modified with Monte Carlo (MC)-calculated primary and scatter data of a small animal imager for the simulation of micro-CT scans. The simulated CT of a mini-calibration phantom from fastCAT was validated against a full MC TOPAS CT simulation. A realistic beam model of a preclinical proton facility was obtained from beam transport simulations to create irradiation plans in matRad. Simulated CT images of a digital mouse phantom were generated using single-energy CT (SECT) and dual-energy CT (DECT) protocols and their accuracy in proton stopping power ratio (SPR) estimation and their impact on calculated proton dose distributions in a mouse were evaluated.Main results.The CT numbers from fastCAT agree within 11 HU with TOPAS except for materials at the centre of the phantom. Discrepancies for central inserts are caused by beam hardening issues. The root mean square deviation in the SPR for the best SECT (90 kV/Cu) and DECT (50 kV/Al-90 kV/Al) protocols are 3.7% and 1.0%, respectively. Dose distributions calculated for SECT and DECT datasets revealed range shifts <0.1 mm, gamma pass rates (3%/0.1 mm) greater than 99%, and no substantial dosimetric differences for all structures. The outcomes suggest that SECT is sufficient for proton treatment planning in animals.Significance.The framework is a useful tool for the development of an optimized experimental configuration without using animals and beam time.

Effects of fluid properties on coarse particles transport in vertical pipe

The mineral resources in deep-seabed are attracting extensive attention. A numerical simulation of particle transport in a vertical pipe for a deep-sea mining system is conducted using the CFD-DEM method. The effects of fluid density, fluid viscosity and rheological parameters of non-Newtonian fluids on the liquid-solid flow behavior in a vertical pipe are investigated. For Newtonian fluids, increasing the density or viscosity enhances the particles' performance in following the fluid and reduces the slip velocity, but also increases the pressure drop. The efficient lifting of particles can be facilitated by adjusting fluid density and viscosity, while considering factors such as energy consumption. For non-Newtonian fluids, an increase in either the flow behavior index n or the consistency coefficient k results in an increase in the fluid's apparent viscosity. This leads to an increase in the particle suspension capacity and local particle velocity, along with a decrease in local particle concentration.

Simulation of heat generation and transport of GaN HEMT based on electron-phonon coupling

Simulation of heat generation and transport of GaN HEMT based on electron-phonon coupling

Numerical simulation and experimental study of microplastic transport under open channel shear flow: Roles of particle physical properties and flow velocities

Microplastic (MP) transport patterns under open channel shear flow remain unclear. This study investigates the transport laws of MPs at various flow velocities, MP densities, sizes and concentrations in the U-shaped experimental flume and the numerical flume based on Lattice Boltzmann Method (LBM). The results indicate that the average horizontal particle velocity and the transport distances of Polyvinyl chloride (PVC) and Polystyrene (PS) particles increase with the average cross-sectional flow velocity, while the average vertical particle velocity decreases with it. The total average particle velocity closely matches the average vertical particle velocity, regardless of the variation in MP size, density and concentration. Formula-based analysis reveals that the acceleration of spherical MP transport mainly depends on the particle size and its consequent relative drag force term (RDFT) under the conditions with a single type of MP particles, but on the particle density and its consequent RDFT and relative gravity term (RGT) in the case concerning different types of MP particles with identical particle sizes. The average horizontal particle velocity maximum of PVC and PS are both strongly correlated with the average flow velocity maximum in the cross-section. This correlation lowers with the MP particle size and concentration, and is independent of MP density. Our findings can provide reference for the prevention and control of MP pollution in rivers.

Diversified characteristics of the dissipative heat on the radiative micropolar hybrid nanofluid over a wedged surface: Gauss-Lobatto IIIA numerical approach

The present examination focuses on the Falkner-Skan flow of micropolar hybridized nanofluid via a wedge surface. The proposed study examines thermal radiative fluxing and heat dissipation in hybridized nanoparticle aqueous solutions. Simulations of uni-directional radiative transport in optically dense fluids use Rosseland's diffusion model. This study created a Cu-TiO2/water hybrid nanofluid by mixing Cu and TiO2 nanomolecules with H2O. Partial differential equations from Naiver-Stokes theory are used to generate the regulating flow phenomena, then convert them into ordinary differentiation equations using an appropriate similarity approach. Additionally, the three-stage Lobatto IIIA method is used to compute the formulae. Calculations are done using MATLAB's built-in bvp5c function. We found that increasing material characteristics slows fluid flow because micropolar nanofluids minimize drag. These alterations alter fluid flow and boost temperature. However, boosting thermal radiation and Eckert number slows heat movement but improves temperature profiles. Much prior research ignored thermal radiative fluxing and heat dissipation in the aqueous solution of hybrid nanomolecules (Cu and TiO2) in Falkner-Skan micropolar flow via a wedge surface. Tables show wall frictional factor and Nusselt quantity results. Micropolar fluid characteristic decreases velocity but increases micro-rotational velocity. Power-law parameters, volume fractions, radiation, heat source, and Eckert amount affect thermal contours.

Surface Flux Transport Modeling Using Physics-informed Neural Networks

Studying the magnetic field properties on the solar surface is crucial for understanding the solar and heliospheric activities, which in turn shape space weather in the solar system. Surface flux transport (SFT) modeling helps us to simulate and analyze the transport and evolution of magnetic flux on the solar surface, providing valuable insights into the mechanisms responsible for solar activity. In this work, we demonstrate the use of machine learning techniques in solving magnetic flux transport, making it accurate. We have developed a novel physics-informed neural network (PINN)-based model to study the evolution of bipolar magnetic regions using SFT in one-dimensional azimuthally averaged and also in two dimensions. We demonstrate the efficiency and computational feasibility of our PINN-based model by comparing its performance and accuracy with that of a numerical model implemented using the Runge–Kutta implicit–explicit scheme. The mesh-independent PINN method can be used to reproduce the observed polar magnetic field with better flux conservation. This advancement is important for accurately reproducing observed polar magnetic fields, thereby providing insights into the strength of future solar cycles. This work paves the way for more efficient and accurate simulations of solar magnetic flux transport and showcases the applicability of PINNs in solving advection–diffusion equations with a particular focus on heliophysics.

Ensemble Kalman Filter Data Assimilation into the Surface Flux Transport Model to Infer Surface Flows: An Observing System Simulation Experiment

Knowledge of the global magnetic field distribution and its evolution on the Sun’s surface is crucial for modeling the coronal magnetic field, understanding the solar wind dynamics, computing the heliospheric open flux distribution, and predicting the solar cycle strength. As the far side of the Sun cannot be observed directly and high-latitude observations always suffer from projection effects, we often rely on surface flux transport (SFT) simulations to model the long-term global magnetic field distribution. Meridional circulation, the large-scale north–south component of the surface flow profile, is one of the key components of the SFT simulation that requires further constraints near high latitudes. Prediction of the photospheric magnetic field distribution requires knowledge of the flow profile in the future, which demands reconstruction of that same flow at the current time so that it can be estimated at a later time. By performing Observing System Simulation Experiments, we demonstrate how the ensemble Kalman filter technique, when used with an SFT model, can be utilized to make “posterior” estimates of flow profiles into the future that can be used to drive the model forward to forecast the photospheric magnetic field distribution.

Bedform development in confined and unconfined settings of the Carchuna Canyon (Alboran Sea, western Mediterranean Sea): An example of cyclic steps in shelf-incised canyons

Newly acquired high-resolution multibeam bathymetry in combination with sub-bottom acoustic profiles, surficial sediment samples, and three-dimensional flow simulations made possible the characterization of bedforms along the axial channel and depositional lobe of the shelf-incised Carchuna Canyon (Alboran Sea, western Mediterranean Sea). This study aims to describe the erosional and depositional bedforms in confined and unconfined settings of the Carchuna Canyon in order to determine the genetic constraints on sedimentary processes leading to bedform development along the canyon in recent times.The straight Carchuna Canyon, deeply incised in the shelf up to 200 m off the coastline, hosts: (1) crescentic-shaped bedforms (CSBs) that exhibit distinctive crest concavities, asymmetries, and lengths along the axial channel; (2) continuous lateral levees and; (3) a channel bend with three depressed stretches of the levee crest that are less than 20 m high. A set of concentric sediment waves and two scour trails were identified proximal to the channel bend on the open slope east of the Carchuna Canyon. Two distinct acoustic groups consisting of four acoustic units with distinct acoustic patterns were defined along the sediment wave field. The sediment transport simulation shows the highest flow velocities along the Carchuna Canyon thalweg, while along the overbank deposition the highest velocity values occur along the top of the bedform crests, with the higher Froude values being found over the bedform lee sides.The occurrence of CSBs along the canyon axial channel suggests the imprint of confined sediment-laden gravity flows descending from the canyon head and exhibiting a flow variability along the canyon induced by local variations of slope gradient and/or sediment concentration. A spatial relationship is identified between the development of sediment waves over the overbank deposit and lowered levee crest heights at the channel bend. In contrast, more energetic downstream turbiditic flows exceed the levee crest at the channel bend, focusing the overflow and promoting erosion of the overbank deposit, thereby generating the scour trains. Based on the recent history of overbank deposition, two alternating scenarios of flow behavior can be interpreted. In a high-density turbidity current setting, erosion would prevail along the axial channel. Widespread spillover flows of coarse-grained sediments would occur in both levees, forming heterogeneous sedimentary patterns that change downslope within the depositional lobe due to lesser turbulence of spillover turbidity currents and gentler slope gradients. In contrast, in a low-density turbidity current setting, turbidity currents flowing along the Carchuna Canyon would form depositional bedforms in the axial channel, while spillover processes would be localized at the channel bend, forming either depositional or erosional bedforms over the depositional lobe according to the frequency, magnitude and focusing of turbiditic flows.

Studies on the [formula omitted] meson production in nuclear matter and the [formula omitted] correlation function

We first review results of transport simulations of 12 GeV pA reactions to study the ϕ meson in nuclear matter, especially focusing on the production mechanism of the ϕ meson in such reactions and on the generated dilepton spectrum. Next, we discuss a recent study calculating the ϕN correlation function, making use of a hadronic effective Lagrangian approach with coupled channels and comparing the result with the recent measurement of the same quantity by the ALICE collaboration.

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.